design and development of a rendering system for vehicle riding 1 design and development of a rendering system for vehicle riding n. sreeram charan1,*, k. maheshwar reddy1, e. rakesh reddy1, and n. malarvizhi2 1ug student, department of computer science and engineering, school of computing, vel tech rangarajan dr. sagunthala r&d institute of science and technology, avadi, chennai-600062, tamilnadu, india 2professor, department of computer science and engineering, school of computing, vel tech rangarajan dr. sagunthala r&d institute of science and technology, avadi, chennai-600062, tamilnadu, india abstract this paper propounds the design and development of a web-based system for a car rental company. it enables admin to rent a car that can be used by a customer on a payment basis. the car information can be added to the system or existing car information can be edited or deleted too by the administrator. the gsm/gps based content alert for car rental system making the car available for every common man with a minimum cost and effective use of time, therefore, this application helps the customers to be comfortable and to have the privacy ride as traveling became the part of life. this system makes processing tasks easier and eliminates the traditional record-keeping process. hence this system enhances the car and customer management and provides customer satisfaction thereby maintaining customer retention. keywords: gsm/gps module, customer relationship management, tracking, software as a service. received on 29 june 2020, accepted on 30 january 2021, published on 29 march 2022 copyright © 2022 n. sreeram charan et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i17.161 1. introduction recently, online car rental system facilitates the business owners in handling the business situations smoothly with the development of various built-in models added to the existing car system in addition to their component details, vehicle check-in and check-out details, vehicle history details, expiration details, insurance registration details, and the vehicle availability timings with the date. generally, the user should create a profile when they are ready to take a car by paying the rent and the system will provide with the necessary payment mode. once the registration process had been completed, the user will have a unique id along with their login password provided from the admin side. customers have their rights to pick the car of their own choice specified with the brand names. customers, while selecting a particular type of car could be able to receive the entire details of the vehicle including mileage details (km/hr), rent of the particular car type, cost of the car etc. users should *corresponding author. email: vtu9891@veltechuniv.edu.in offer the system with sufficient information such as the name, address, location of travel, total members accompanying the car, total number of service days etc. the authentic person could be able to receive significant information whenever necessary. customers should provide the system with significant details regarding their particular travel location every time so that the admin could track their cars very easily. they could also cancel their booking status anytime and also select the car types based on the particular members they take on-board. they also have the total authority of changing their travel places. admin system is enabled with the automatic reminder feature through which the customers license, insurance, service and replaced components details could be received based on the particular vehicle. 2. literature survey eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e4 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ mailto:vtu9891@veltechuniv.edu.in n. sreeram charan et al. 2 in today's market, rental options for cars are flooded for the customers to choose the best based on their preferences. customers are provided with plenty of choices in making their own innovative services and products based on the rental opinion [1]. online car rental system serves the best in serving several families and working professionals to get to a place. over the past few years, many shoppers gained advantage from the car rental system in india. this rental business had made an emerging opportunity for the novice customers as previously the locations were limited only to certain physical distances [2]. though the remote locations have not been exterminated; the nature of achieving all these possible function is due to the power of internet. at the present situation, users can register their car online by paying the required rent and once the registered customers reach their car at their doorstep they are free to go anywhere. this serves as a major advantage for both the car rental company as well as the customers in managing their business efficiently. the web-based car rental management information system [3] helps in improving the efficiency of rental history data transmission. comparing to the other manual systems, this system promotes shorter time delivery. data stored in the cloud environment will simplify the process of obtaining data and generating reports. the rental vehicle's web system [4] is a system created using javascript. this application promotes the complete functionality of call center for the web-based car rental broker companies. this process will simplify the problems faced by the travel agencies and the tourists in making reservations online, making payment and comparing the price of the vehicles through which they travel. the administrator could also manage the data in a very short duration. as the system keeps records of the customers, an administrator can manage the customers easily. in this twenty-first-century user-friendly web-based vehicle rental system is popular in tourism[5]. the web-based system uses server components of distributed applications with http protocol for exchanging data between servers and clients. the administrator can easily manage a secure webbased system. the several features of this system are: customers can enter their details, customers can do vehicle booking with date and time, customers can view all types of vehicles and customers can view the total amount to pay. both the car rental company and the customer get a huge benefit with the online rental system that also helps in managing the system effectively by promoting a complete satisfaction to the customers' requirements. this also offers huge advantage to the company owners, business organization sand the customers in getting excellent services. the authors in [7] proposed an anonymous car rental protocol based on nfc technology. all the personal data regarding the users will be send to the trusted third party (ttp). through this system, the car hire providers will not receive any information regarding the users (anonymity) and the rental companies will not assume any link among the users' identity and rental records with the rental history (unlinkability). also if there are consumer disputes or accidents, the rental company can request that ttp reveal users' identity (traceability) and provides users free choice of their preferred vehicle (flexibility). 3. proposed system 3.1 modules description the three important modules are: 1. registered user 2. guest user 3. administrator authorized users are said to be the one who had registered their personal details in the registration page of the system. after the successful registration, user can login to their account with the valid email id and the password. if the user forgot their registered email id and password then with the help of their personal information they could be able to get access to their account. following things could be done by the user after the successful login: • car booking • know details of car booking • upload their own profile information • update password • post testimonial • view testimonial • log out guest users can see the website and check out the information about rental cars. guest users can enquire about the system through contact us page. the administrator is the superuser of a system that can manage everything on the system. the several features are: • create vehicle brands • post vehicle • manage vehicle brands( edit, delete) • control vdehicle booking • upload testimonials • query to contact the service • manage customers • admin dashboard(admin can view the count of registration users, total booking, total customers, total queries, etc) • logout 3.2 proposed system architecture the web-based car rental system interfaced with the sms technique serves as a very user-friendly purpose. customers can be able to make their payments, bookings, sms and provide their vehicle issues to the employees, which they monitor through the specified system. administrators can add the new data or edit or delete the existing data. thus, there will be no delay in the availability of any information. for security enhancement, the customers are asked to create their eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e4 design and development of a rendering system for vehicle riding 3 own user account prior to their booking. the notifications will be sent to the customers regarding their car reservation through sms thereby making the customers, administrator and employees effort easier. the architecture of the proposed system is given in figure 1. figure 1. system architecture 3.3 uml diagrams figure 2. use case diagram figure 3. customer details figure 4. vehicle details 4. system testing system testing cannot be carried out as a monolithic unit; rather the testing procedure is carried out at several stages with the implementation. any sort of errors determined in the program components will be identified during the testing procedure. the information from the later process will be fed back to the earlier stages and therefore holds to be repetitive. the level in which testing process is carried out involves a unit with the smallest testable part of the software. it consists of one output with single or many inputs. white box system testing strategy is mainly carried out that involves with the developers considering the internal system mechanism, component or application to check the expected working of source code. this testing strategy involves with the written codes, statements, internal code logic, paths branches etc. on the other hand, black box testing strategy involves by testing the software functionality without any internal design reference, algorithm, or program code. the main focus of this testing strategy is to obtain an output for the given input and execution conditions ignoring all the system mechanism and the internal components. to develop our system we have used the xampp server, php as front end, html css and javascript for user interface design and mysql for database design. eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e4 this is the title 4 4.1 screenshots figure 5. home page figure 6. customer registration figure 7. admin login figure 8. admin homepage figure 9. login page eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e4 design and development of a rendering system for vehicle riding 5 figure 10. my bookings 5. conclusion in this paper, we have presented an online rental system which is beneficial to both the customers and the rental company to manage the business efficiently and effectively and satisfy the needs of the customers at the click of a button. using this system saves time for the customer and sorts out the billing problem also. this system is more convenient than bearing the cost of owning and maintaining the vehicle. references [1] swati y. dhengre, snehlata r. golam, asmita b. lokhande, devyani n. kandalkar, “cloud computing customer relationship management for online rental system”, international research journal of engineering and technology" e-issn: 2395 -0056 volume: 04 issue: 02,2017. [2] mohd nizam osman, nurzaid md. zain, zulfikri paidi, khairul anwar sedek, mohamad najmuddinyusoff, “online car rental system using web-based and sms technology”, crinn, vol 2, isbn: 978-1-387-00704-2 277,2017. [3] gaurav patel, amol koli, rakesh kadam, rahul bhat, prachi kshirsagar, “on hire: car rental system”, international journal of engineering research in computer science and engineering, vol 5, issue 3, 2018. [4] bayu waspodo, qurrotul aini and syamsuri nur,” development of car rental management information system”, international conference on information systems for business competitiveness, 2011. [5] sasikala and deepti, “real-time services for cloud computing enabled vehicle networks,” journal of real-time services for cloud computing enabled vehicle networks, volume 11, issue 1, 2013. [6] sari, “building application system car rental reservation and payment online web-based. [7] chennupati yogender sai, d.saravanan, yanamadala varun tej, tubati hari vineesha, "smart renting of vehicles using iot" international journal of innovative technology and exploring engineering, issn: 2278-3075, volume-8 issue-6, 2019. eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e4 security surveillance and home automation system using iot 1 security surveillance and home automation system using iot a. sanjay1, meenu vijarania2,* and vivek jaglan3 1student, amity university haryana, manesar, india 2assistant professor, amity university haryana, manesar, india 3professor, graphic era hill university, dehradun, india abstract internet of things provides connectivity and user interoperability among different systems, devices, networks and services in particular control systems. iot can be envisioned as a network of connected devices which are capable of providing intelligent services. this paper presents a security surveillance system in buildings based on iot using raspberry pi. it can be used at industries, homes and office etc, where the camera records the movement of objects and using iot devices and the data is stored on to the server. the idea is to lock the door even from outside the house and it can be opened using the android phone itself. if some intruder tries to break or to get in anonymously, the system will detect the person and photo will be clicked by the security camera and send the message along with photo on to the owner’s mail, thus creating the evidence for our safety. some additional features for automation like rain sensing windows using rain sensor and servo motor and automatic light on/off for saving electricity and reduce human effort with ir senor and a simple led have also been implemented in this paper. hardware implementation has been done for the proposed model and it will be applicable for monitoring home, industry, office etc. in the absence of user. keywords: iot, sensors, home automation, security, android, surveillance, raspberry pi handling editor: akshat agrawal (amity university gurgaon, india) received on 06 july 2020, accepted on 25 july 2020, published on 06 august 2020 copyright © 2020 meenu vijarania et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.21-7-2020.165963 *corresponding author. email: meenuhans.83@gmail.com 1. introduction now a days, digital technologies have been revolutionized where different things and people are interconnected in order to send/receive the information. it intends to benefit the people with the help of internet services. in iot, various things like sensors and other devices are connected through internet to exchange and collect the information with each other. it enables various devices to collaborate, interact, and, learn from each other’s experiences just like humans do. using iot billions of objects are intelligently connected in variety of applications. iot is broadly deployed in variety of domains namely: agriculture, healthcare, smart cities. smart buildings and smart security are becoming a reality with the combination of underlying communication and monitoring infrastructure that comprises of smart devices such as actuators, cameras, sensors, meters and rfids. now days, societies have high demand for security and surveillance as there is rapid developments of embedded system and security awareness. much research is still going on to improve the design of intelligent surveillance and security system to enhance monitoring capabilities and security of remote places. the main focus of this paper is to implement the functionality of wireless home automation features and home security. the model of the currently built system sends the alert message to the owner using iot if some intruder tries to break or to get into the home anonymously. the system will detect the person and photo will be clicked by the security camera and sends the message along with photo on to the owner’s mail. whereas, the person entering in the house is identified as guest, then the owner can open the door using his mobile phone instead of triggering security alarms. the owner can do various activities like switching on various appliances inside the house, which are eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e1 http://creativecommons.org/licenses/by/3.0/ 2 also connected and controlled by the micro-controller in the system to welcome his guest. these are main key features and the main objectives of the paper : 1. this project has been included with a face detection module with the help of raspberry pi. 2. open cv with the cascades for the face which is combined with a camera. it can a detect a face of the person standing for a long time in front of the house. 3. for automation it a preprogrammed process in which it does take input from the sensors and take the action as per the command give for the action for example when a sensor gives a output through gpio 4. pins (general purpose input/output). 5. for android door lock i have used a socket connection for the raspberry pi to communicate with a android device which sends command for the raspberry pi to lock or unlock the door. 6. using sensors like (rain sensor, ir sensor) for rain sensing windows and to automatic switch on and off the light when there are needed. 2. related work various models for building surveillance have been proposed earlier. these models optimized the surveillance system by using ultrasonic sensors [2], photovoltaic array [3], wireless sensor networks [4]. by introducing tel monitoring, intelligent fish eye camera techniques surveillance system was improved. though, these techniques were not able to control the surveillance operation sitting at remote place whenever the event occurred. in [5] author suggested a intelligent and automatic system for smart home using sensor networks. the author used zigbee and ieee 802.15.4 to develop energy efficient smart home system and it collect the data using passive infrared (pir) sensor, occupancy sensor and photo sensor. in [6] author proposed a smart home automation scheme using iot and raspberry pi. home appliances are connected and monitored using internet. surveillance and sensing operation is conceded by raspberry pi. motion sensor and camera were used for detecting motion and intruder at the door. 3. proposed work in home security there are two modules: • smart security camera • android door lock. in this project face detection module has been implemented with the help of raspberry pi and open cv with the cascades for the face which is combined with a camera, it can a detect a face of a person standing for a long time in front of the house. then it takes a photo of the persons face and email it to the owner’s mail id through smtp protocol (simple mail transfer protocol). the architectural diagram is shown in the figure 1. for android door a socket connection is created for the raspberry pi to communicate with a android device which sends command for the raspberry pi to lock or unlock the door. a socket provides end to end connectivity between two programs running on the network. every socket has a associated port number so that the transport layer can recognize the application for which the data is destined. the endpoint address is combination of port number and ip address. a. sanjay, meenu vijarania and vivek jaglan eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e1 3 figure 1. architecture of security surveillance and home automation system figure 2. block diagram of smart security camera and android door lock security surveillance and home automation system using iot eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e1 4 2.1. home automation features for home automation there are two modules: i) rain sensing windows ii) automatic light on and off. for rain sensing windows a rain sensor is used to check the rain and then when the value of the sensor become 0 (which means it is raining .) then the windows of the house automatic closes and when the value becomes 1 again(which means the rain has stopped.) the windows will automatically open itself. the rain sensor is shown in figure 3. for automatic lights off/on a led and a ir sensor has been used, it is simple a but a useful feature that saves electricity. the value of the ir is 1 then led will glow and if the value is zero then the led will not glow. in simple words if there is any person enters the room the light will switch on and it will automatically switch off when the person leaves the room. figure 3. rain sensor figure 4. block diagram of rain sensing windows table 1. development environment hardware configuration software requirement raspberry pi 3b model 64gb memory card micro servo 9g(2) ir sensor pi camera led with resistor breadboard rain sensor android studio vnc viewer python 3.7.9 rasbian os (jessie) core java xml for desgin opencv 3.1.1 3. experimental setup the basic hardware setup of the proposed system is shown in figure 4. it consists of a raspberry pi, relay, motor, pir sensor. the raspberry pi communicates with all the other devices attached to it. the pir sensor detects when an intruder enters in the range of it and sends that information to the raspberry pi. after that, the raspberry pi sends a signal to the web camera to take a photo. the photo taken by the web camera is temporarily stored in the local storage of the raspberry pi, then raspberry pi sends a mail to the corresponding mail id with an attachment of the image taken. 1. all the connections are connected to raspberry pi through jumper wires male and female respectively. 2. all the sensors are connected to separate gpio pin and ground connection. 3. and the camera is connected to specific connector provided with the raspberry pi. figure 5. connections of the sensors a. sanjay, meenu vijarania and vivek jaglan eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e1 security surveillance and home automation system using iot 5 3.1 pi camera raspberry pi supports a light weight and portable pi camera module. using the serial interface protocol mipi camera communicate with pi. it is normally used in image processing, machine learning or in surveillance projects. it has a fixed focus lens. the advantage of miniature size camera is that it can be installed in a small space. the most important benefit of this camera over a usb webcam is that it is able to make use of the graphics processing capability of the broadcom cpu. figure 6. smart camera and door lock figure 7. mail received from pi eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e1 6 4. conclusion & future scope the proposed method provides a low power and low cost solution for monitoring the human presence and controlling the device from anywhere in the world. this is useful for monitoring home, industry or office etc, in the absence of the user. this can be easily controlled from anywhere by knowing the ip address of the network connected to the raspberry pi, so that door will be locked when intruder is inside the room. acknowledgements. dr. meenu vijarania is currently working in amity university haryana. she has done b.tech, mtech and ph.d in computer science. she has published various papers in international journals and conferences. her area of interest are wireless networks, internet of things, genetic algorithm. dr. vivek jaglan is currently working as professor , graphic era hill university, dehradun. he has completed his b.tech,m.tech in computer science. he has published various papers in reputed international journals and conferences. his area of interest are soft computing, machine learning. references [1] k.s. pachpor, c.n.deshmukh, home automation and surveillance: a review, international journal of science and engineering applications, 8(4):111-114. [2] bai, y.-w., xie, z.-l., li, z.-h., 2011. design and implementa-tion of an embedded home surveillance system with zero alertpower using a photovoltaic array. in: 2011 ieee 15th interna-tional symposium on consumer electronics (isce), 14—17 june,pp. 373-378. [3] sulc, v., 2011. home automation with iqrf wireless communicationplatform: a case study, no. c., pp. 212— 217. [4] wibowo, s.b., putra, g.d., hantono, b.s., 2014. development ofembedded gateway for wireless sensor network and internetprotocol interoperability. in: 2014 6th international conferenceon information technology and electrical engineering (icitee),7—8 october, pp. 1—4. [5] dae-man han and jae-hyun lim, “smart home energy management system using ieee 802.15.4 and zigbee, ieee transactions on consumer electronics, vol. 56, no. 3, pp. 1403-1410, august 2010 [6] v.patchava, h. b. kandala, and p. r. babu’“a smart home automationtechnique with raspberry pi using iot”, international conferenceon smart sensors and systems (ic-sss), pages 1–4, dec 2015. [7] n. oza, n. gohil, "implementation of cloud based live streaming for surveillance", proc. int. conf. commun. signal process. (iccsp), pp. 0996-0998, apr. 2016. [8] r. rameshwar, a. solanki, a. nayyar, b. mahapatra, green building management and smart automation, india: igi,2020, 7, green and smart buildings: a key to sustainable global solutions, 146-163. [9] setiya purbaya , dodi wisaksono sudiharto ,catur wirawan wijiutomo, “design and implementation of surveillance embedded ip camera with improved image quality using gamma correction for surveillance camera”, 3rd international conference on science and technology computer (icst), 2017. [10] a. ahuja, integration of nature and technology for smart cities, 3rd ed.; springer international publishing:basel, switzerland, 2016; p. 390. [11] p. rajiv, r. raj, m. chandra, email based remote access and surveillance system for smart home infrastructure, perspectives in science, 2016, 8, 459—461. [12] gayathri, p. , krishna paramathma, m., paramathma, m.k., 2014.design and implementation of embedded home surveillance sys-tem by using mms modem. in: electronics and communicationsystems (icecs), 13—14 february, pp. 1—5. [13] nguyen, d.v., le, h.t., pham, a.t., thang, t.c., lee, j.y., kugjin, y. ,2013. adaptive home surveillance system using http streaming.in: 2013 international joint conference on awareness scienceand technology and ubi-media computing (icast-umedia), 2— 4november, pp. 579—584. [14] pawlak, a., horoba, k., jezewski, j., wrobel, j., matonia, a., 2015.telemonitoring of pregnant women at home — biosignals acqui-sition and measurement. in: 2015 22nd international conferenceon mixed design of integrated circuits & systems (mixdes),25—27 june, pp. 83—87. a. sanjay, meenu vijarania and vivek jaglan eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e1 iot enabled weedicide control using image processing at agriculture field the aim of this project is to automate plant monitoring and smart gardening using iot in the arduino mega platform. identifying diseases in plants leave is a challenging task for farmers and also for researchers. the key highlight of the project is able to detect the type of disease by use of image processing. image processing steps are pre-processing, spot segmentation and features extraction, and classification. the extracted features are optimized by genetic algorithm and classified by knn classifier. we proposed a methodology that is tested for four types of apple plant disease including healthy leaves, black rot, rust, and scab. when the disease is identified we provided a pesticide solution displayed in the lcd display and the same is sent to the farmer mobile with the help of gsm. all the stages are monitored in an iot webpage. iot enabled weedicide control using image processing at agriculture field g.manjula1, p.visu2, s.chakaravarthi3 1p.g student, department cse, velammal engineering college, chennai, india, gmmanju17@gmail.com. 2professor, department cse, velammal engineering college, chennai, india, pandu.visu@gmail.com 3professor & head, department of cse, velammal engineering college, surapet, chennai, chakra2603@gmail.com abstract keywords: iot, image processing, arduino mega platform, gsm, smart farming. received on 22 april 2020, accepted on 30 january 2021, published on 30 june 2021 copyright © 2021 g.manjula et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.30-6-2021.170252 resources for agriculture will be lower in the upcoming 1. introduction internet of things (iot) is the trending technology for smart farming to gain efficiency, productivity and resolve various issues present in the agriculture field. internet of things (iot) network consists of various sensors that are used to monitor the soil acidity level, temperature, humidity and other variables. we used arduino platform that is easy-to use hardware and software. internet of things (iot) gives a new look in the domain of smart farming and agriculture area. farming and agriculture is the backbone of human life which gives food, grains, and other raw materials. technology holds a huge role in increasing production and decreasing manpower [1]. iot aims to combine the physical world with the virtual world with the help of internet as the medium to communicate and exchange information [7]. internet of things (iot) interconnects with sensors, actuators, and heterogeneous computing devices within the existing internet infrastructure and the development environments [5]. in agriculture for irrigation we are using huge consumption of fresh water nearly 90% in the developed countries. the increased demand for water and the arising climate changes are anticipating that the water decades [2]. the current challenges in agriculture field are pesticide management, crop monitoring and automated harvesting .supplying the optimal treatments according to the orchard characteristics provides an efficient management of the crop or farms.[6] .the manual inspection of fruit diseases is a difficult process which can be minimized by using automated methods for detection of plant diseases at the earlier stage[8]..in the traditional farming that requires huge man power and there is no level of usage of fertilizer whereas in the automated farming it is more convenient than traditional farming. 2. proposed methodology the fig 1 shows the block diagram of the overall proposed work. in our project the main motive is automatic plant monitoring and identifying the plant disease and provide pesticide solution and all the stages of plant monitoring is updated in the iot module. for every plantation the major eai endorsed transactions on smart cities research article 1 eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e5 mailto:college,%20chennai,%20india,%20gmmanju17@gmail.com. mailto:pandu.visu@gmail.com mailto:chakra2603@gmail.com mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ factor is soil ph level and climatic conditions. here we monitoring about apple plantation, like other plants we started from the seeding. in traditional method either we collect seeds from the stores or extract the seeds from an apple fruit. later on germinating the seeds by irrigation i.e. imbibitions followed by respiration, effect of light on seed germination, mobilization and development of the embryo. after that plant is transplanted to larger area to grow before that some essential measures should be taken such as sunlight, soil, space. the best ph level for apple tree is 5.0 7.0.after the tree sheds with green leaves the major problem arises is apple disease. disease identification and providing solution to it is a challenging task. figure 1. block diagram of overall proposed work we proposed a methodology for automatic plant monitoring and disease identification and pesticide solution for apple plant disease. we have taken three types of apple plant disease black rot, apple scab, apple rust .like every plantation we started from seeding the land using servo motor .the figure 2 is the servo motor. the servo motor is a small device with an output shaft and the shaft can be positioned to specific angle with a help of coded signal by the servo. the servo motor can rotate approximately 180 degrees i.e. 90 degree in each direction. figure 2. servo motor after the servo motor does the seeding then pump motor start the work for irrigation mostly apple plant grow in hill areas so initial stage only requires more water than the upcoming stages .the figure 3 is the pump motor. the pump required huge power so we used relay for the power supply. a pump motor is a direct current motor device that moves fluids. it works under the principal of motoring action. figure 3. pump motor the figure 3 is the ph sensor. the best ph range for apple plant is 5.0-7.0 is acidic in nature if it is 7.0 < then the soil is alkaline. if the soil is alkaline the micro servo motor starts for fertilizer. the micro servo motor performs the same operation as servo motor. figure 4. ph sensor the ph level now is checked after the fertilizer and if it is acidic then the step is the image processing for disease identification .we have taken three apple leaf disease black rot, apple scab, apple rust compared with an healthy leaf. we used machine learning algorithm .the figure 5 shows the snapshots of leaf disease from initial original leaf is the input followed by four steps preprocessing, segmentation, feature extraction, classification. preprocessing: preprocessing is the basic level of abstractions that eliminates the unwanted distortions or enhances some image features for future processing. mostly the preprocessing are similar such as the neighboring pixels of the one object in the original image or the brightness value may be similar so distorted pixel as stored as a mean value of neighboring pixel. for preprocessing technique the original input image is resized and converted into gray scale image using the filters. after that we used 3d box filtering, de-correlation, 3d-gaussian filter, and 3d-median filter for the better vision of the disease spots in the input image. segmentation: image segmentation is a common technique used in digital image processing and analysis to divide an image into multiple parts of regions based on the characteristics of the pixels in the image.. feature extraction: the feature extraction starts from an initial data set and get extracted and refrained to non redundant data. the resultant set of data is the feature vector. some of the feature extractions are shape features, color features, geometrical features, texture features. shape features are called as visual feature ex: shape of the image 2 g.manjula, p.visu, s.chakaravarthi eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e5 such as triangular, circular or some other shapes. color features are local feature of the image such as color, texture, segmented regions geometrical features are geometric features like points, curves, lines corner and edge features. we used three feature extraction methods such as glcm (grey level co-occurrence matrix), lbp (local binary pattern), region segmentation and genetic algorithm. glcm gives the texture features of the test image like contrast, correlation, energy and etc. then the lbp gives the various different shape features of the input image. after that we used genetic algorithm for best feature selection in order to classify the different leaf diseases. classification: for classification we used knn (k-nearest neighbour) algorithm. for every leaf disease the affected spot will be different .we used a data set for different leaf images and the spots are valued .euclidean distance is used for distance metric. 9. black and white image 10.small object removed image apple rust 1. input image 2.resized image 3.3d-box filtered image 4.decorrelated image 5.3d-gaussian filtered image 6.3d-median filtered image 7. hsi colour space 8.s-channel image final output image: apple scab 1 .input image 2.resized image 3.3d-boxfiltered image 4.decorrelated image 3 iot enabled weedicide control using image processing at agriculture field eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e5 5. 3d-gaussian filtered image 6. 3d-median filtered image 7. hsi -colour space 8.s-channel image 9. black and white image 10. small objects removed image final output image: black rot: 1. input image 2. resized image 3. 3d-box filtered image 4.decorrelated image 5. 3d-gaussian filtered image 6.3d-median filtered image 4 g.manjula, p.visu, s.chakaravarthi eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e5 7. hsi-colour space 8.selected s-channel 9. black and white image 10.small object removed image final output image: healthy 1. input image 2.resized image 3.3d-box filtered image 4.decorrelated image 5. 3d-gaussian filtered image 6. 3d-median filtered image 7. hsi colour space 8.s-channel image 5 iot enabled weedicide control using image processing at agriculture field eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e5 9. black and white image 10.small objects remove image final output image: figure 5. snapshots of leaf disease identification from input image to final output image the figure 5 shows the overall process of all leaf disease identification from input image to final outputs are elaborated in the snapshots. after the disease identification, now the disease is displayed in the lcd display with pesticide solution and the same message is sent to the farmer mobile with the help of gsm. now the farmer loads the pesticide solution and then the micro servo starts to spray the solution. the overall processes from seeding to pesticide stage are enrolled in the iot module. the figure 6 shows the webpage that stores the overall stages. figure 6. snapshots of iot webpage 3. conclusion iot is an emerging technology and we proposed a methodology for smart farming with the use iot components. the world population increases day by day so apart from traditional farming methods here we proposed automated farming techniques in apple plantation and the major problem arises in every plantation is disease identification .we have taken three major apple plant disease and provided solution for it. smart communication between the farmer and the field by gsm and the iot webpage are also achieved. references [1] nurzaman ahmed, debashis de, senior member, ieee, and md. iftekhar hussain, member, ieee “internet of things (iot) for smart precision agriculture and farming in rural areas.”ieee internet of things journal, vol. 5, no. 6, december 2018. [2] f. viani, member, ieee, m. bertolli, m. salucci, member, ieee, and a. polo student member, ieee “ low-cost wireless 6 g.manjula, p.visu, s.chakaravarthi eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e5 monitoring and decision support for water saving in agriculture” ieee sensors journal, vol. 0, 2017. [3] georgios m. milis, student member, ieee, christos g. panayiotou, senior member, ieee, and marios m. polycarpou, fellow, ieee“semantically enhanced online configuration of feedback control schemes.” ieee transactions on cybernetics 2017. [4] yun-wei lin, yi-bing lin, fellow, ieee, ming-ta yang, and jun-han lin “ardutalk: an arduino network application development platform based on iottalk.”ieee systems journal 2017. [5] sukhvir kaur1, shreelekha pandey1, shivani goel2,”semi automatic leaf disease detection and classification system for soybean culture”iet image processing 2018, vol. 12 iss. 6, pp. 1038-1048. [6] francisco yandun*, giulio reina, miguel torres-torriti, george kantor, and fernando auat cheein “a survey of ranging and imaging techniques for precision agriculture phenotyping.”ieee/asme transactions on mechatronics 2017. [7] olakunle elijah , student member, ieee, tharek abdul rahman, member, ieee, igbafe orikumhi, member, ieee, chee yen leow , member, ieee, and mhd nour hindia, member, ieee “an overview of internet of things (iot) and data analytics in agriculture: benefits and challenges.” ieee internet of things journal, vol. 5, no. 5, october 2018. [8] muhammad attique khan, m ikramullah lali, muhammad sharif, kashif javed, khursheed aurangzeb, syed irtaza haider, abdulaziz saud altamrah, and talha akram. “an optimized method for segmentation and classification of apple diseases based on strong correlation and genetic algorithm based feature selection.” ieee access 2019, vol 1. [9] ms. kiran r. gavhale, prof.ujwalla gawande,mr.kamal o.hajari. “unhealthy region of citrus leaf detection using image processing techniques.” international conference for convergence of technology – 2014 9781-4799-37592/14/$31.00©2014 ieee [10] omer mohamed elhassan ahmed, abdalla a. osman, sally dafaalla awadalkarim. “a design of an automated fertigation system using iot.” 2018 international conference on computer, control, electrical, and electronics engineering (iccceee). 9781-5386-4123-1/18/$31.00 ©2018 ieee. 7 iot enabled weedicide control using image processing at agriculture field eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e5 apple rust final output image: final output image: final output image: final output image: towards an iot-based system for monitoring of pipeline leakage in clean water distribution networks 1 towards an iot-based system for monitoring of pipeline leakage in clean water distribution networks tuyen phong truong1, giang thanh nguyen1 and luong thanh vo1 1can tho university, can tho city, vietnam abstract climate change-causing drought is wreaking havoc in the mekong delta, but water usage and management are still inefficient, resulting in a loss rate of more than 20%. this research is being carried out to contribute to lowering the rate of water loss and improving the management of the clean water supply. this suggested system makes use of wireless sensor networks, the internet of things, and cloud database storage technologies. the readings collected by the flow and water pressure sensors at the sensor nodes installed along the plumbing system will be relayed to the gateway through the lora wireless communication network. the gateway will aggregate the collected data, upload it to a cloud database, and then analyze it to detect and give an appropriate alert for water leaks if any occur. an application for the android smartphone assists in visually monitoring recorded data. the research results have been evaluated in operation, with initial results fulfilling the key requirements. keywords: internet of things, leaking pipe, lora technology, smart cities, water distribution systems. received on 10 december 2021, accepted on 31 march 2022, published on 31 march 2022 copyright © 2022 tuyen phong truong et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i17.230 1. introduction currently, the covid-19 pandemic has threatened cities and communities, endangering not only public health but also the economy and social fabric, directly affecting community health and quality of life, particularly the lack of clean water for daily life and production [1]. according to a 2015 global report, one in every ten people (roughly 2.1 billion people worldwide) lacks access to safe drinking water. according to interreg central europe [2-3], we lose 25–50% of clean water every day, causing many people to live in water scarcity. the shortage of clean water in daily life and production in vietnam, like in other affluent countries, is becoming increasingly significant. the average rate of revenue loss and loss of clean water in 2015 for the whole country was 30%, equivalent to about 5.5 billion vnd per day [4]. saigon water supply corporation (sawaco) has also created an online water supply management system with network management, incident management, and real-time updates. however, the system is still underutilized and the cost is still prohibitively high. even though it has been in use since may 2019, the drainage rate in the first nine months of 2020 at thu duc water supply joint stock company, where the system was installed, is still 12.85 percent [5]. a wide number of research studies regarding water leakage in water distribution networks have been carried out. some of them have been focused on developing algorithms for detecting and estimating leakage models and integrating them into a water distribution network hydraulic model. consequently, a lot of cad software has been proposed to detect the location and compute the leakage quantities of water for solving the network leakage flows [6–10]. on the other hand, there are some others focused on pipeline leak detection technology based on optical fiber sensing technology and a proposed algorithm for pipeline leakage detection [11]. the technique may use the frequency domain to discover leak spots by obtaining time-domain signal characteristics of pipeline leakage. there were also some research projects on building a leak detector for clean water supply pipes using the negative correlation method, which is based on the detection and measurement of the time deviation of the sound emitted from the leak point when handling the audio signal recorded at the two ends of the pipeline segment. however, because they are only zoning the problem area, they cannot pinpoint the precise location of the leak. in addition, the device has been unable to survey a long pipeline because the sensor is insensitive due to eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e5 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ t. p. truong, g. t. nguyen and l. t. vo 2 environmental noise, and it cannot be connected to multiple sensors at the same time [12–13]. as a result, there are still some concerns that need to be addressed in current research, such as high cost due to having to spend money to deliver messages if using a mobile network, and centralized processing on a circuit board. these restrictions have implications in terms of geographical location, such as the inability to set up the system over a vast area and the difficulty of expanding it. therefore, the goal is to deploy the system over a large area using a wireless sensor network. because the measurement system is simple to set up and inexpensive, wireless sensor nodes are used to easily expand the system. the organization of this article is presented as follows. section 1 provides an overview of the current situation, causes, and solutions for water leaks in clean water supply systems. section 2 discusses the design and implementation of the proposed pipeline leakage monitoring system, which includes the hardware architecture and embedded software. section 3 presents experiments to evaluate the operation of the water leak monitoring system on the main pipeline before section 4 concludes the article by presenting a summary of the results and the research plans. 2. system design 2.1. system overview figure 1. the overview of the pipeline leakage monitoring system a lora wireless sensor network, depicted in figure 1, consists of one gateway and three sensor nodes that exchange data using long-distance, ultra-low power lora technology. the gateway, which acts as a link between the lora network and the internet, is in charge of data aggregation and real-time data updates to the firebase cloud. an android smartphone application allows for easy visual monitoring of recorded values obtained from sensors for detecting water pipeline leaks. in figure 2, the stm32 blue pill [14], which equips an stm32f103c8t6, an arm 32-bit cortex m3 architecture with high-performance and almost all the standard peripheral interfaces for reading sensor values, is used for control circuitry at the sensor node. the sensor node is designed to receive data from sensors using common peripheral communication standards such as uart, i2c, spi, and so on, and then transmit data to the gateway using lora wireless transmission, specifically the lora ra-02 module. the lora ra 02 module is a small lora transceiver that uses a semtech sx1278 chip and operates at 430–435 mhz. it has low energy consumption and a transmission range of around 15 kilometers [15–17]. the gateway used here is a raspberry pi 4, compact and highperforming [18]. the gateway in this case is a raspberry pi 4, which is small but powerful in performance. this is an embedded computer with an ethernet connector and wi-fi for internet connectivity that runs the operating system on a memory card for easy control programming. in addition, as can be seen in figure 2, the raspberry pi 4 also supports a standard spi interface connected to the ra-02 module to facilitate data transmission between the lora wireless sensor network and data upload to the cloud database. figure 2. system block diagram and communication between the gateway and a sensor node 2.2. hardware design to extend the lifetime of the proposed system the sensor node powered by a battery will be buried deep alongside the clean water supply pipeline system in the actual application conditions, so the power supply for the sensor node to operate is a concern. the investigation of energy-saving modes to determine the best method for assisting the sensor node in consuming less energy. the sensor node's hardware has two designs for this purpose: stop mode (the microcontroller power-down mode) and power off (see figure 3). the sensor node reduces power consumption while in use with energy-saving modes. as a result, a device capable of waking the microcontroller from sleep mode is required. the rtc ds3231 module, with two built-in alarms, a 32 khz temperature-compensated crystal oscillator, and a backup battery to maintain accurate timekeeping when the device's power source is disconnected, is one of the suitable choices [19]. the power-off method is an effective solution to save maximum energy for the sensor node. for this reason, lp5907, texas instruments' linear voltage regulator with low noise, output current up to 250 ma, high resistance to power fluctuations [20], is used to manage the power supply for the microcontroller and lora module. eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e5 towards an iot-based system for monitoring of pipeline leakage in clean water distribution networks 3 figure 3. block diagram of two power-saving modes for sensor node under normal conditions, the data from 10 sensor readings will be stored at the sensor node before being sent to the gateway to save energy. unless a leak is detected, the data will be sent immediately. as a result, eeprom was used to ensure that the data stored at the sensor node is not lost when the power is turned off. cat24c128 is a 128kb serial eeprom that is internally organized into 16384 words and is divided into 256 pages with 64 bytes each for the write buffer, as well as write protection and error correction code [21]. figure 4. the electronic circuit board of the sensor node was inside a protective plastic box to avoid damage flow and pressure sensors are integral parts of the system to monitor parameters that aid in leak detection of water supply lines (see figure 4). the hall yf-05 dn20 measures water flow rates from 1 to 30 l/min. in the presence of flowing water, it generates square pulses that create a magnetic field to activate the hall sensor [22]. a pressure sensor (sku237545) generates an output signal when the applied force with 12-bit resolution, a pressure range of 0–200 psi, an accuracy of 1.5%, and a response time of fewer than 2 milliseconds [23]. a gps (global positioning system) module is installed to locate the location of the system's sensor nodes. because the sensor nodes are fixed, the board is designed with an extra slot for connecting the gps, allowing the gps module to be reused for multiple sensor nodes. the venus638flpx-l gps module operates in tracking mode by default, automatically responding to data at a frequency of 1 hz with a compact design and high accuracy [24]. figure 5. the electronic circuit board of the gateway 2.3. embedded software development in this system, a lora gateway (see figure 5) is often deployed at a high position, and it can thus establish direct communication with all sensor nodes. the gateway of the lora network is set up to operate in two phases. phase 1 performs the construction of the routing table and establishes the sensor network by sending a broadcast message and waiting to receive a response message, which is the identifier, from the sensor nodes operating in the coverage area. phase 2 is the process of collecting data from sensor nodes, processing data, uploading data to the cloud, and warning when there is a pipeline leak. the program on the gateway needs to perform phase 1 periodically to update the active sensor nodes after executing phase 2 n times. most of the time, the sensor network will collect data to satisfy the requirements of monitoring and warning, but still, ensure optimal connections in the network to help the system operate stably and long-term. figure 6. flow chart of process on the sensor node eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e5 t. p. truong, g. t. nguyen and l. t. vo 4 because the sensor node is permanently installed, the packet is divided into two types: a coordinate packet that contains the longitude and latitude of the sensor node's installation position, and a data packet that contains the sensor node's data. only when the gateway requests it is this packet sent. the data packet contains flow, pressure, date, and time values, as well as time synchronization between the gateway and the sensor node, which aids in the detection of water pipe leaks. during the system's operation, this packet is always sent to the gateway. to save energy, the sensor node only works for a set amount of time and then goes into the power-saving mode for the remainder of the time. the flow chart in figure 6 explains this in detail. 2.4. android app development an application for android smartphones has been developed to allow users to easily access and visually observe the system installation location, flow, and pressure parameters at each node, which are displayed on the map. when a leak in the pipeline is detected, users are notified. the graphs are plotted separately for each flow or pressure parameter per node and are automatically refreshed based on a real-time updated firebase database. details can be seen in figure 7. figure 7. measurement data is uploaded to a cloud database and updated to the application on an android smartphone in real-time 3. experiment 3.1. compare power saving modes according to the experimental results, the power consumption in run mode is 0.1476 wh. stop mode consumes 0.0145 wh, which is 10 times less than run mode, and power off consumes 0.0126 wh, which is 11 times less. in stop mode, the system consumes 0.0145 wh, which is 10 times less than in run mode, and its power off mode consumes 0.0126 wh, which is 11 times less. a 3.7v-2200 mah li-ion battery is used to power the sensor node, which reads data from sensors every 2 minutes. the data is aggregated and sent to the gateway after every 255 reads. as a result, the system's operating time is approximately 7.5 days. table 1 summarizes the power consumption of the stm32f103c8t6 in experimental measurements. table 1. power consumption of microcontroller working stages working time (t) electricity consumption stop mode power off reading sensor 30 s 0.0041 wh 0.0041 wh saving energy 530 s 0.0020 wh 0.0001 wh sending data 40 s 0.0084 wh 0.0084 wh 3.2. experiment to detect water leakage figure 8. a basic experimental study on leakage for the water supply pipe in figure 8, the water supply pipe system in the experiment consisted of two branches, which were fitted with two sensor nodes each at the two ends of the pipeline, about 5 meters apart. branch three was not fitted with sensor nodes and was fitted with a drain valve at the end of each branch. when there is a water leak in the pipeline at branch 1, the water flow at node 1 is greater than the flow at node 2. the pressure deviation at node 1 does not change much depending on the water supply flow into the pipeline, and the pressure at node 2 decreases (see cases 1 and 3 in table2). if the water valve at the end of branch 1 is opened, the pressure at node 2 will decrease due to dynamic pressure, and the flow at node 2 will be less than at node 1 (see cases 1, 2, and 4 in table2). when the water valve at branch 3 is opened, the pressure in node 1 and node 2 decreases together, but the flow does not change. eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e5 towards an iot-based system for monitoring of pipeline leakage in clean water distribution networks 5 after completing pipe installation and supplying water to the pipes (assuming they are not leaking), calculate the "leak threshold" value using sensor references and consider the difference in received values at the beginning and end of each pipe. the gateway will issue an alert when the next data collection shows the calculated value exceeding the threshold. from case 1, the first collected values are viewed when the system is installed and the leakage threshold is determined as follows: pthreshold = 1.02989, fthreshold = 0. suppose the pipeline is leaking in case 3, p = 1.063736 > pthreshold and f = 33 > fthreshold, combine the two conditions on the gateway that raises the alarm. table 2. experimental measurements case studies node 1 node 2 flow (ml/min) pressure (bar) flow (ml/min) pressure (bar) 1. not leak and not open valve 0 1.181209 0 0.151319 0 1.147363 0 0.148901 0 1.142527 0 0.146484 2. not leak and open valve 100 1.533901 100 0.158571 100 1.526923 100 0.158571 133 1.188462 133 0.134396 3. leaking and not open valve 33 1.198132 0 0.134396 33 1.181209 0 0.129560 50 1.173956 0 0.127143 4. leaking and open valve 133 1.181209 116 0.134396 90 1.176374 73 0.137650 83 1.546264 66 0.156154 4. conclusion this paper presents the design and implementation of a leak detection system for clean water supply pipelines. the system established a lora wireless sensor network that allows the detection and warning when there is a leak in the water supply pipeline over a large area. an application on smartphones helps users to visually observe the flow rate and pressure parameters based on applying a real-time database service. in the experimental measurement, a lora network consisting of 4 sensor nodes and 1 gateway was deployed that collects and uploads data to the cloud in realtime through an internet connection. for electrical energy saving, power supply control circuitry and embedded programs were developed. experimental results show that the proposed hardware and software design help enhance system performance. for future work, we plan to improve the quality of the sensors used for more accurate and reliable measurements, continue to improve the hardware and software, and conduct more experiments and calibrations on the actual water supply pipeline system. references [1] kenth hvid nielse. using smart water in cities. new straits timers. october 22 2020. https://www.nst.com.my/opinion/columnists/2020/10/6345 04/using-smart-water-cities (accessed on 9 december 2021). [2] lam hong. warning about the risk of water shortage. nhan dan (people) newspaper. september 27 2019. https://nhandan.com.vn/tin-tuc-the-gioi/bao-dong-nguy-cothieu-nuoc-sinh-hoat-369008/ (accessed on 9 december 2021). [3] anh vu. thirst threatens the world. ministry of natural resources and environment (vietnam). june 21 2019. http://dwrm.gov.vn/index.php?language=vi&nv=news&op =nhin-ra-the-gioi/con-khat-de-doa-toan-cau-8216 (accessed on 9 december 2021). [4] decision no. 2147/qd-ttg of the prime minister (vietnam). national program to combat loss of revenue and clean water by 2025. https://vanban.chinhphu.vn/default.aspx?pageid=27160&d ocid=97899 (accessed on 30 march 2022). [5] quang dinh. water supply with smart technology in the industry 4.0 era. september 20 2020. tuoi tre news. https://tuoitre.vn/cap-nuoc-bang-cong-nghe-thong-minhthoi-40-20200926104940329.htm (accessed on 9 december 2021). [6] m. tesfaye, s. narain, h. k. muye. modeling of water distribution system for reducing of leakage. journal of civil & environmental engineering.2020; vol. 10: 6. [7] j. almandoz, e. cabrera, f. arregui, e. cabrera, r. cobacho. leakage assessment through water distribution network simulation. j. water resour. plan. manag. 2005; vol. 131:6. [8] m. maskit and a. ostfeld. multi-objective operationleakage optimization and calibration of water distribution systems. water (switzerland). 2021; vol. 13:14. [9] k. b. adedeji, y. hamam, b. t. abe, a. m. abu-mahfouz. leakage detection and estimation algorithm for loss reduction in water piping networks. water (switzerland). 2017; vol. 9:21. [10] a. adamuscin, j. golej, m. panik. the challenge for the development of smart city concept in bratislava based on examples of smart cities of vienna and amsterdam. eai endorsed transactions on smart cities. 2016; volume 1, issue 1. [11] kazeem b. adedeji, yskandar hamam, bolanle t. abe, adnan m. abu-mahfouz. pipeline leak detection technology based on distributed optical fiber acoustic sensing system. ieee access. 2020; vol. 8:21. [12] pengxiang technology. acoustic emission monitoring of pipeline leakage. february 03 2014. https://www.ndttech.net/en/solutions/acoustic_emission_t esting/299.html (accessed on 9 december 2021). [13] tran viet chau. research and manufacture leak detector on clean water supply pipeline using negative correlation method on pc platform. project report at can tho university, vietnam. 2017. [14] stmicroelectronics. stm32f103x8-medium-density performance line arm-based 32-bit mcu. eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e5 t. p. truong, g. t. nguyen and l. t. vo 6 https://www.st.com/resource/en/datasheet/stm32f103c8.pdf (accessed on 9 december 2021). [15] lora alliance. lora and lorawan: a technical overview.https://loradevelopers.semtech.com/uploads/documents/files/lora_an d_lorawan-a_tech_overview-downloadable.pdf (accessed on 30 march 2022). [16] semtech corporation. sx1276/77/78/79 137 mhz to 1020 mhz low power long range transceiver rev. 7, 2020. [17] h. mroue, g. andrieux, e. m. cruz, g. rouyer. evaluation of lpwan technology for smart city. eai endorsed transactions on smart cities. 2017; volume 2, issue 6. [18] raspberry pi trading ltd. bcm2711 arm peripherals. https://datasheets.raspberrypi.com/bcm2711/bcm2711peripherals.pdf (accessed on 30 march 2022). [19] maxim integrated. extremely accurate i2c-integrated rtc/tcxo/crystal, rev 10. https://datasheets.maximintegrated.com/en/ds/ds3231.pdf (accessed on 30 march 2022). [20] texas instruments. lp590 250-ma, ultra-low-noise, low-iq ldo, snvs798o –april 2012–revised june 2020. [21] on semiconductor, eeprom serial 128-kb i2c cat24c128 rev. 17 https://www.onsemi.com/pdf/datasheet/cat24c128-d.pdf (accessed on 30 march 2022). [22] seeed technology co. ltd. water flow sensor. https://wiki.seeedstudio.com/water-flow-sensor/ (accessed on 30 march 2022). [23] rev robotics, “analog pressure sensor data sheet”, rev.11,2015, https://www.revrobotics.com/content/docs/rev-11-1107ds.pdf (accessed on 9 december 2021). [24] skytraq technology, inc. venus838flpx 50hz -165dbm low-power gps module. https://www.skytraq.com.tw/homesite/venus838flpx_pb _v1.pdf (accessed on 9 december 2021). eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e5 does collective consciousness compromise during epidemics and pandemics? 1 does collective consciousness compromise during epidemics and pandemics? anoushka khanna1,2, namita i1, rina chakrabarti2, prem kumar indraganti1,* 1drug repurposing and translational research lab, institute of nuclear medicine and allied sciences, defence research and development organization, brig sk majumdar road, timarpur, delhi-110054, india 2aqua research lab, department of zoology, university of delhi, delhi-110007, india abstract the ongoing pandemic, covid-19, has received unprecedented global attention. though a pathogen is essentially the causative agent, the dynamics of the cause-effect in major events like the ongoing covid-19 pandemic is not well understood. it is not even clear if the focused attention of the normal population impacts the safety and health of the exposed victims and in what way the different groups interact with each other, is also a big question. the idea of panpsychism and hierarchical consciousness suggests that consciousness functions beyond an individual and works at distinct levels such as family, community, state, territories, nations, and world. in this perspective, keeping in mind, the idea of hierarchical consciousness, the impact of higher consciousness in major events like the covid-19 pandemic, on the well-being and fate of the exposed population along with the probable role of quantum entanglement, has been discussed. keywords: covid-19, sars-cov-2, consciousness, collective consciousness, hierarchical consciousness, epidemics, pandemics, mass casualty, global consciousness project, quantum entanglement, reality. handling editor: sweta saraff, amity university kolkata, india received on 07 june 2020, accepted on 07 september 2020, published on 22 september 2020 copyright © 2020 anoushka khanna et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.18-8-2020.166358 why is there a need to understand collective consciousness? collective consciousness is a compound word. collective means a group or aggregate of individuals or things; taken as a whole; combined together and consciousness refers to the state of being aware; internal knowledge; of being able to subjectively experience something. in combination, it can be surmised that collective consciousness is a set of ideas, thoughts, proclivity shared by all, operating as a unifying force within the community [1],[2]. the term was 1st described by a french sociologist, emile durkheim in 1893 and according to him, it is the collective conscience of the people that allows the maintenance of social order. it is merely the collective perception of people in the society that becomes a driving force in any given situation [3]. epidemics and pandemics involve the exposure of masses, which often result in devastating effects on a substantial number of people at the same time. during such mass exposure scenarios, the virulence of the pathogen is considered accountable for the rising number of infections and mortality worldwide along with other aggravating factors like stress and fear which can disturb the overall well-being of the people living in the affected regions. however, a better understanding of all the contributing factors resulting in mortality or other outcomes is necessary to facilitate improved management of the contagion [4]. the ongoing pandemic, covid-19 has attracted worldwide attention, creating immense psychosocial disturbances. the disease is new with its cause and emergence still being a big question mark with no in-hand treatment and vaccine, has created a lot of anxiety and fear of the unknown, amongst the human population [5]. here, in this article, how the focused thoughts of the unaffected population might impact the eai endorsed transactions on smart cities research article *corresponding author: 91-9958456999 (mobile), prem@inmas.drdo.in, prem_indra@yahoo.co.in eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e5 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ mailto:prem_indra@yahoo.co.in anoushka khanna et al. safety and health of the infected people and overall mortality along with the possible role of global consciousness in driving the spread of the pandemic, has been discussed. before analysing the role of collective consciousness and focused thoughts on the overall well being of the society in mass exposure scenarios, it is important to understand the very basics of consciousness and how it connects a group. the impact of collective consciousness on day to day life and the thought process during the face of the pandemic-covid-19 according to the psychiatrist roger walsh, “the state of the world reflects our state of mind” i.e. the condition prevailing in the world is the reflection of our collective consciousness (focused attention). the operation of collective thoughts can be seen all around us in everyday life which is necessary for the proper functioning of the society and can be recognised in community, organisations, nation, human population as a whole, and so on [6]. according to the sociology professor, mary kelsey at the university of california, instead of existing as individuals, we tend to survive in groups and communities, following the rules of the society. this behaviour is not just restricted to humans but many species around the globe tend to thrive together to optimize their survival. a glimpse of collective consciousness can be easily seen in classroom settings or group activities (sports, adventurous or risky activities) where the motivation of the teammates and the enthusiasm of people around them can bring positivity and lead to better understanding (collective efforts of a teacher and motivated students) and results, brought about by collective effort. only hard work alone at the individual level cannot bear fruits until it is combined with the positive energy and the source of it can be from the team members, family, community, or entire nation. for instance, when we come across some tragedies occurring in other people’s life or the world, we can feel and connect with their pain and sorrows even without coming in contact with them [7]. this means that we all share a common belief and have an inner knowing which exists at a certain frequency, accessible to all. amidst the on-going covid-19 pandemic and lockdowns imposed in many countries of the world, it has resulted in psychological distress, and signs of irritability, depression, anxiety, low mood, insomnia, fear, emotional exhaustion. these were also evident in those who were quarantined either within their homes or other facilities. this sense of detachment from the society is being experienced by a majority of the human population collectively, world-over leading to negative thoughts, fear of infection, stigmatization (health workers, doctors, essential servicemen) [8],[9]. nevertheless, these have become the contributing factors in aggravating stress and negatively impacting the immune system and thus increasing the chances of infection and affecting the mortality rate. in testing times like this, the collective strength and unity of thoughts were observed twice in india; firstly, when prime minister, mr. narendra modi urged the citizens of the country to clap hands, ring bells, or bang plates on march, 22nd and secondly, lighting of lamps on the night of 5th april to express gratitude towards the corona warriors. this gesture of collectivity became an example for many countries as it marked the awakening of the feeling of togetherness (collective consciousness, focused attention), motivating the health workers and realising that the entire country can unite as one in the battle against covid-19. this was nothing but an experience of shared consciousness that connected everyone and will probably give them the strength to not only fight the disease but also the mental distress that arose from isolation. then again, how this collective consciousness connects the group and synchronise them as a unit, is still needed to be deciphered. how are people connected to each other? we humans along with other animal species display social behaviour and tend to survive in groups to optimise the overall survival. one of the possible theories of this behaviour is the emergence phenomenon that occurs when simple entities interact to form a complex entity having new properties, entirely different from its parts i.e. ‘complexity arising from simplicity’[10],[11]. it basically implies that many things interact with each under a certain set of rules, creating something above and beyond themselves. for instance, an individual ant is not smart and productive (simple) in itself, it cannot work as a colony of ants can. a group of ants can distribute their jobs (gatherers, workers, soldier, caretakers) by secreting certain chemicals and work in unison to build complex structures, waging war with other colonies thereby producing order out of chaos. so, what a colony (overall system) can carry out, a single ant (a simple component of the complex system) does not have that capability. in simple words when a bunch of small things can do some big things, that phenomenon is called emergence [12]. millions of molecules (not alive) interact to form robust structures like proteins, organelles subsequently giving rise to the smallest unit of life: a cell which further cooperate to form a complex organism with remarkable capacities. consciousness is also regarded as an emergent property and combining consciousness of a group of people give rise to collective consciousness of the society, nation, world and so on [2]. therefore, the emerging global consciousness has capacities that are superior and beyond its individual components [13]. according to emile durkheim, the division of labour in the society i.e. appointing specified tasks to certain people, is necessary for proper functioning and order in 2 eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e5 does collective consciousness compromise during epidemics and pandemics? 3 the society and inculcates the feeling of solidarity among individuals [3]. this can only take place if the society is organised and follow certain set of rules, share common beliefs and this connection between the individuals and society is nothing but collective consciousness. for instance, anything committed outside the order of the society, on which we collectively don’t agree upon is termed as a crime and is wrong in everyone’s eye. although a group or family of individuals (higher level of consciousness, focused attention) which functions efficiently as a unit, is not a physically connected arrangement but still somehow, they manage to communicate and thrive as a group by sharing a collective viewpoint. it may be due to non-physical factors, one of them being collective consciousness that contributes to the eloquent functioning of a group and maintain order in the society. on the other hand, a question may arise that how consciousness, that is the state of being able to subjectively experience something, can interact with anything beyond an individual’s body. many instances from the past, somehow portray strong connection within the groups, leading them to follow each other’s footsteps. the dancing plague is one such phenomenon that emerged around the 13th century in europe, in which people would just gather and engage themselves in a dancing frenzy that would go on till the point of exhaustion which sometimes resulted in death. a single episode could afflict as many as 1100 people at the same time and the cause of this still remains elusive. it did not require any physical contact with the affected person and even the sight and sound were considered sufficient to contract it and start sporadically or even take form of an epidemic [14],[15]. furthermore, in 1841, charles mackay explained about the madness of crowds and their psychology, highlighting many incidents from the past where humans displayed the potential of collective delusion. one of the most dramatic and popular episodes of such behaviour is evident from the witch hunts that began in the 1400s in europe. it was an epidemic of terror that resulted in the torture and execution of a large number of people accused of witchcraft and were considered to be the cause of all the calamities that took place. it was probably the collective mindset of people that made them believe this delusion which turned into witch-mania and subsequently cultural madness. it was like a chain reaction triggered by one accusation that finally became a widespread hysteria (witch craze) [16],[17]. there are many such examples in human history that give us an idea that we have a potential to become insane together, influence one another so profoundly (connection between individuals) and how collective consciousness can compromise and give birth to negative results (collective madness) which can give rise to a delusional new reality. based on the above discussion and many such incidents from history and our daily experiences, it is evident that a strong unseen connection does exist and several theories have been proposed till date to explain it. the theory of panpsychism which states that everything has a mind or in other words, every entity possesses some consciousness, seems to have a potential [18]. additionally, it has already been proposed that an individual is made up of different conscious layers like atoms, molecules, cells, tissue, organs, systems, organism and the conscious level increases hierarchically giving rise to individual consciousness (the top most level). more importantly, human consciousness is just the result or the sum of all the conscious layers in the body that makes it unique and higher above all. according to this theory of hierarchical consciousness, a certain level of consciousness imparts control over its immediate lower level like within an individual, atoms are directly under the control of molecules [2],[4]. since, the human consciousness has resulted from progressively increasing consciousness (hierarchical consciousness), it has been predicted that a group of individuals i.e. a family will form a higher level of conscious layer and similarly a community will be above it. so, based on these assumptions, it has been previously proposed that consciousness although a nonphysical entity, can be extended beyond an individual to higher levels like family, state, nation, world, and even beyond it (entire cosmos), thus connecting everyone and everything. thus, the consciousness of a nation i.e. the focused thoughts of people living in it will certainly be higher than an individual and can impart control over its lower levels (family, individuals). however, its relevance is still qualitative in nature but its existence cannot be denied. furthermore, this concept of collective consciousness and its capacity to extend beyond an individual, group, or nation can be applied to situations of pandemic (covid19) and mass exposures, to explain the impact of higher order of consciousness (collective thinking) on the exposed population and the overall well-being of everyone in the face of pandemic. collective consciousness and the spread of a pandemic. covid-19 has received unprecedented attention and has become a cause of global concern. this outbreak which originated in wuhan, china has severely affected 217 nations with over 5 million confirmed cases of infection, costing the lives of more than 3 lakh people worldwide and still counting [19]. it has brought a sudden break in the daily life, adversely impacting the economy and overall mental health. although, the underlying cause of the disease is sars-cov-2 but other non-physical factors are also contributory. moreover, the problem does not reside in covid-19 alone, rather it is in fear of contracting the virus, panic, temporary unemployment, distance from the family (social isolation) and terror, caused by the spread of this pandemic. epistemology (a branch of philosophy) that is concerned with knowledge, states that all knowledge that we possess may not always arise out of our own experience [20]. it dictates the development and application of some cognitive processes eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e5 anoushka khanna et al. at the expense of others. thus, even without experiencing the disease, the knowledge of fear (experienced by others) that is somehow communicated through the collective consciousness, creates disturbances and changes our thoughts. this pandemic is a situation where massive number of people all over the world have concentrated their attention on just one thing i.e. covid-19. additionally, with lockdowns implemented worldwide and increasing mental stress, collective consciousness has somehow compromised which may worsen the situation. as dr. hagelin once said “our minds profoundly mirror the hierarchical structure of nature”. so, based on the idea of hierarchical consciousness if the superior layer like family community, nation is severely compromised, it would adversely affect the lower layers. here, higher level of consciousness being massive human population having a negative viewpoint (collective focused thought of unaffected population) about covid-19 which may impact the outcome of infected population. this can be best explained by the global consciousness project that began in the 90s to study the presence and activity of global consciousness in the world and its interaction with physical systems. random number generators were used, that produced completely random sequences of zeroes and ones which deviated from this unpredictable pattern during group settings i.e. when human consciousness became coherent [21]. at various events, it was evident that the network of rngs became slightly structured whenever feelings of large number of people synchronized. this project, originally started at the princeton university, has become the scientific basis for the existence of global consciousness and connection between humans. they could also conclude that under certain circumstances, human consciousness (collective), also affected the outcome of the events [22]. several empirical studies involving global events have been carried out. during terrorist bombing in iraq, the bomb explosion was like a stimulus that evoked emotional reactions among people all around the world which synchronised their response (global consciousness) as recorded by rng [23]. 9/11 terrorist attack was one of the major events that attracted global attention and according to roger nelson, the data collected from the rng started changing (synchronising) even before the attack and displayed departures from random expectation after it (due to coherent emotional response) [22],[24],[25]. it would not be wrong to say that global consciousness impinges on the physical reality additionally, pleasant occasions like new year’s eve or when group mediation event take place, a spike/a pattern is observed in the data [25]. the deviation from the randomness was also observed on march 22, when the indians clapped as that event was responsible for synchronising the feelings of millions of people and when human consciousness becomes coherent, the network of rngs became slightly structured [26]. there are various such incidents that are recorded and analysed under the ongoing gcp which supports the impact of collective consciousness [27]. thus, it can be comprehended that praying (focused attention) together during crises like this on-going pandemic, is more than just positive thinking and may have verifiable benefits [21]. on the contrary, when everyone in today’s world has an easy access to internet, social media and 24hour news, with the media presenting the pandemic as if it were the end of the world, it is difficult to hold a positive view. so, the spread of negative, fake and exaggerated information increases the chances of global consciousness to hold negative thoughts [6]. most of the people are under the impression that there is no escape from covid-19, as cases continue to rise and no treatment as such, without considering the fact that if our immune system is strong enough, it can fight the disease and save our lives. this thought process of the masses can severely affect the infected population and may play a role in increasing the mortality rate. since, the immune system is the key in combating the covid-19, it is all the way more necessary to maintain positive thoughts collectively as the persistence of negativity in the collective consciousness can cause stress amongst the population which in turn can compromise the immune system and make the individual more susceptible to the virus. henceforth, it can be implied that mortality due to covid-19 does not depend solely upon the virulence of sar-cov-2 but also on the collective viewpoint of the population. apart from this, the imposed lockdowns have created mental stress and collective stress is also known to compromise the global consciousness. some of the experiments involving a large group of people practicing transcendental meditation at a synchronised time have shown to display reduced violence, crimes and other social ills. thus, it was proposed that criminal behaviour and other problems does not simply arise within an individual but it is a result of strain in the collective consciousness of the society or a community. the scientific evidence can be gained from several studies where rng was used to collect data during group meditation practices, where transcendental meditation and yogic flying technique (by great yogi maharishi) was performed and the data showed deviation from randomness to a more structured one (maharishi effect) [28],[29],[30]. therefore, it can be suggested that such practices could be performed during these stressful times to ameliorate situations that affect collective consciousness in order to divert the face of the pandemic. nevertheless, there is a need to understand the scientific basis of how mass consciousness can influence the outcome in any given situation. does collective consciousness impact the outcome? einstein talked about how we are all linked and how change in one thing in this universe affects others too. he explained entanglement in his epr paper published in 1935 and called it as “spooky action at distance”. in simple words, quantum entanglement means that all the energy or entities are intertwined and locked together eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e5 does collective consciousness compromise during epidemics and pandemics? 5 even if they are spatially separated and individuality of each entity is surpassed [31]. according to david bohm the entire universe is whole, undivided and continuously flowing. since the entire cosmos has originated from a single entity, it has been previously proposed that the entire universe may be connected in some way linking everything, irrespective of the spatial separation [32],[33]. thus, it can be suggested that quantum entanglement might be behind the collective thoughts of the people that has the capacity to influence each other and the events that take place [34]. this might also invoke some questions in the mind of the readers whether free will exists or not and is reality, a mere illusion? carl jung once said that schizophrenia is a condition where “the dream becomes the reality”[6]. it can also be argued that there is no such thing as objective reality. richard feynman’s double slit experiment is a suitable example to explain the subjective nature of reality [22]. so, keeping in mind the concept of collective consciousness and quantum entanglement, it can be apprehended that reality is subject to change based on our collective thinking and we are capable of affecting each other and the final outcome especially during pandemics like covid-19 which involves worldwide focused attention. collective consciousness: a possible step in combating pandemic in smart cities. we are all familiar with the old saying that strength lies in unity. whether it is struggle for independence or fight for equal rights, there are great examples in our history, illustrating the united strength of people in achieving the unachievable. thus, the concept of collective consciousness has been into play for a very long time but its potential and role has not been fully realised yet. it would not be incorrect to say, together we can move mountains! keeping in mind, the power of collective thoughts, it can be put into action in the current scenario (ongoing pandemic). it is important to remember that 100 years back, when science and technology was not as advanced like the present day, humans were successful in defeating the pandemic, we surely are better equipped to combat it now. moreover, many life-threatening diseases/ disorders exist but we don’t stress about them in a similar way. media plays a crucial role in moulding thoughts and changing a viewpoint. as it is said, with great power comes great responsibility, amidst the ongoing pandemic, the media should make use of their power and try to focus on the positive news like the increase in the recovery rate since the outbreak, the improving health care facilities, the journey of those who have successfully defeated the disease and also showcase that with proper precautions and safety measures, it is possible to protect oneself from covid-19. if the number of increasing infections, is a reality and the public should be aware of it, then the rise in the recovery rate is also the truth and it should be portrayed with the same enthusiasm or even more, like the spread of the pandemic (negative view) is displayed. now a days when covid-19 has become the talk of the town and it is all that everyone thinks about, promoting news like “covid-19 may never go away”, only aggravates the negative thought amongst the population, leaving them in despair or without having something better to look forward to[35]. fear and undesirable thoughts can create disturbances in the consciousness at an individual level and in case of a pandemic, a massive number of people experience such disturbances collectively. the concept of hierarchical consciousness, where each entity is governed by the consciousness of its superior entity, can be utilised as an additional strategy to combat the pandemic to some extent. organising thoughts and inculcating positive attitude at an individual level can bring about changes in the viewpoint of the masses. some studies have reported the potential role of collective consciousness in the healing of culture, society, nation, etc. repairing thoughts (through meditation, motivation) and promoting positive thinking can cause healing [36]. moreover, it has already been tested that collective consciousness strengthens when a group of people focus on a common event or thought, creating coherence amongst group which is probably evident through group meditation events displaying ordered data on rng whereas low-coherence events showing random data [37]. restoring optimistic thinking amongst people (repairing the collective consciousness) and motivating them might prove to be an important measure in this ongoing pandemic. conclusion through this article, it can be put forward that collective consciousness is at play in every aspect of life. we have yet to realise its full potential in changing the outcome. in case of pandemics, like covid-19 or any other event involving masses (terrorist attacks, sports, nuclear accidents), the impact may be governed by hierarchical consciousness. the viewpoint of higher consciousness (communities, cities, states, nation, entire world) may directly influence the infected/ exposed population (lower conscious level) which in turn is dependent upon prior knowledge (internet, media) and severely affect the mortality rate. therefore, in tough times like these, along with following the safety measures, the world should unite in their thoughts and focus their views towards positivity in order to get a favourable outcome that can help us to fight this pandemic. acknowledgements. authors gratefully acknowledge the support from defence research and development organization (drdo), delhi, india and department of science and technology (dst). eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e5 anoushka khanna et al. references [1]. piepmeyer a. collective consciousness. https://csmt.uchicago.edu/glossary2004/collectiveconsc iousness.htm. [2] indraganti pk, indracanti n, khanna a.(2019) consciousness: a possible gateway for protection against radiation induced damage. austin biochem.;4(1). [3] simpson, george in durkheim e. the division of labour in society. new york: the free press [4] indraganti p., namita i, khanna a.( 2020) does collective consciousness has a role in radiation mass exposures and epidemics ? front drug, chem clin res;3:1-4. doi:10.15761/fdccr.1000139 [5] ravi philip rajkumar.( 2020) covid-19 and mental health: a review of the existing literature. asian j psychiatr.;52. [6] elgin d.( 1997) collective consciousness and cultural healing. (gouge d, ed.). calfornia: alonzo environmental printing. [7] connecting to the collective consciousness. https://www.elephantjournal.com/2015/11/connectingto-the-collective-consciousness/. [8] minding our minds during the covid-19. https://www.mohfw.gov.in/pdf/mindingourmindsdurin gcoronaeditedat.pdf. [9] brooks sk, webster rk, smith le, et al.(2020) the psychological impact of quarantine and how to reduce it: rapid review of the evidence. lancet;395:912-920. [10] emergent properties (stanford encyclopedia of philosophy). https://plato.stanford.edu/entries/propertiesemergent/#bib. [11] bar-yam y.( 2018) emergence of simplicity and complexity*. [12] identifying emergent behaviors of complex systems — in nature and computers – the new stack. https://thenewstack.io/identifying-emergent-behaviorscomplex-systems-nature-computers/. [13] feinberg te, mallatt j. (2018) phenomenal consciousness and emergence: eliminating the explanatory gap. front psychol;11:12. [14] donaldson lj, cavanagh j, rankin j. (1997) the dancing plague: a public health conundrum. public health;111(4):201-204. [15] davidson a. (1867) choreomania: a historical sketch, with some account of an epidemic observed in madagascar.. [16] mackay c. (1852) memoirs of extraordinary popular delusions. vol 1. 2nd ed. london. [17] karabacak e.( 2018) the european witch-craze. [18] chalmers dj. (2013)panpsychism and panprotopsychism. amherst lect phil;8:19-47. [19] coronavirus disease 2019. https://www.who.int/emergencies/diseases/novelcoronavirus-2019. [20] moser pk. (2015) epistemology. encylopedia libr inf sci.. [21] the global consciousness project. http://noosphere.princeton.edu/. [22] nelson rd, radin d, shoup r, bancel p. (2002) correlation of continuous random data with major world events. found phys lett;15:537-550. [23] nelson rd. (2020) evoked potentials and gcp event data. j sci explor;34(2):246-267. [24] nelson rd. connected: the emergence of global consciousness, by roger d. nelson | spr.ac.uk. https://www.spr.ac.uk/book-review/connectedemergence-global-consciousness-roger-d-nelson. [25] nelson r. (2006) the global consciousness project. explor j sci heal.;2(4):342-351. [26] m r. princeton university research shows collective action works the hindu businessline. https://www.thehindubusinessline.com/news/princetonuniversity-research-shows-collective-actionworks/article31264154.ece#. [27] formal results: testing the gcp hypothesis. http://noosphere.princeton.edu/results.html. eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e5 does collective consciousness compromise during epidemics and pandemics? 7 [28] evidence of the collective consciousness & the maharishi effect. https://subtle.energy/evidence-of-thecollective-consciousness/. [29] collective consciousness and meditation: are we all interconnected by an underlying field? https://www.huffpost.com/entry/collectiveconsciousness-meditation_b_822288. [30] mason li, patterson rp, radin di. (2007) exploratory study: the random number generator and group meditation. j sci explor.;21(2):295-317. [31] di biase f.( 2019) quantum entanglement of consciousness and space-time a unified field of consciousness. neuroquantology.;17(3):80-85. [32] weber r. (1989) reflections on david bohm’s holomovement. (valle r.s. ver, ed.). boston, ma: springer us;. [33] bohm d. (1980) david bohm wholeness and implicate order. great britain: routledge and kegan paul;. [34] maldonado ce.( 2018) quantum physics and consciousness: a (strong) defense of panpsychism. trans/form/acao.;41(spe):101-118. [35] coronavirus | world health organisation says the virus may never go away the hindu. https://www.thehindu.com/news/international/coronavir us-may-never-go-away-warnswho/article31578415.ece. [36] sethi y. healing through collective consciousness at jungian society. https://familyconstellations.com.au/healing-throughcollective-consciousness/. [37] ivtzan i. meditation on consciousness. j sci explor. 2008;22(2):147-159. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1 .1.686.5218&rep=rep1&type=pdf. eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e5 acknowledgements. r. m. kamal, n. a. elsayed and n. g. gado 1 smart cities: sustainable and safety roads study model r. m. kamal1,*, n. a. elsayed2 and n. g. gado3 1 lecturer–department of housing & architecture, national housing and building research centre hbrc, giza, egypt 2 lecturer of architecture and planning, modern academy for engineering and technology, giza, egypt 3 lecturer of architecture, modern academy for engineering and technology, cairo, egypt abstract sustainable satisfaction in smart cities has been discussed extensively within the academic context, however; it is argued the fast-urban development and technology, strong trend towards facilitating of urban communities through achieving user’s satisfaction. consequently, urban planners have had to work hard to raise awareness and increase the quality of life among with future development, global goals, which are easily adopted in new cities which includes tools and mechanisms to achieve such goals . this research aims to respond to the hypothesis by answering the following question: what are the sustainability road elements would that enable achieving a good quality of life and user’s satisfaction in smart new cities??? hence, the challenges of implementing a maximum level of satisfaction to improve smart new cities’ performance to meet resident expectation and keep it ahead. this paper pinpoints through applying various methods, concepts and practices. using mixed methods offers a sharper insight into the research question and problems than a single methodology approach, theoretical studies includes articles that address relevant subjects. moreover, by analyse and compare the performance of the chosen international european smart city case studies in terms of pros and cons methods and efficiency. the researchers plan to apply their research techniques, by suggesting a check list to reach a comparative analysis for improving the current situation, raise life standards in a sustainable manner, which may help the new egyptian cities those based on the principle of artificial intelligence (ai) to face any challenges and improve their opportunities, through a comprehensive and effective management system. keywords: smart cities new cities sustainability development goals quality of life user’s satisfaction received on 10 december 2019, accepted on 19 may 2020, published on 21 may 2020 copyright © 2020 r. m. kamal et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.164662 *corresponding author. email: rhmokamal@yahoo.com 1. introduction the main idea of the smart city can be back traced to the early 1970s, since the community analysis bureau started using computer technology for collecting databases, cluster analysis and infrared aerial photography, collect data, issuing reports and direct resources to the field that most important for fighting off potential devastations and reducing poverty.[1] a smart city's success depends on its capability to have a strong relationship between the government (bureaucracy and regulations) and private sector. it is necessary cause most of the work done; is to create and maintain a digital, data-driven environment occurs outside of the government. surveillance devices include sensors, cameras and server for high traffic streets could be supplied from different vendors. as the high population density within cities continues are keeping grow, the necessaries for these urban areas to accommodate such increases are getting more essential by making and help infrastructure to become more efficient. smart city applications can enable these improvements, advance operations and improve the quality of life for residents. smart city applications empower urban cities to discover and make new value from their current infrastructure. the enhancements made to encourage new eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e2 2 income streams and operational efficiencies, helping governments and residents save money. however, several major characteristics are used to indicate city's smartness. these important characteristics include:  infrastructure technology.  environmental activities.  high functioning public transportation framework.  confident sense of urban arranging and planning.  utilize human resources (hr) to live and work inside the city. however, the primary goal of this smart city is to build an urban environment that yields a high quality of life, performance for to its residents while also generating overall economic growth. as a result, smart cities major advantage is considered as their ability to facilitate and increased delivery of infrastructure services to its residents with less cost. the research aims to highlight the comparative analytical approach reviewing some european and local experiences in order to monitor the pros and cons of each of them. in achieving the objective of the study, the remainder of this paper is organized as following, figure1, which explains the methodology and sequence of search steps. this framework will guideline planning and urban development processes in new smart cities in egypt towards sustainability, achieving the principles of quality of life and the user’s satisfaction. figure 1. research methodology 2. theoretical study 2.1. smart cities concept several approaches in defining smart city are considered. in general, 'smart cities are cities that use information and communication technologies to increase operational adequacy, share information with the public and upgrade the quality of government services and resident’s welfare. [2] a smart city is an urban area that uses different types of electronic internet of sensors to collect information and then reuse analysis and prudence data gained from it to manage assets, resources and services effectively.[3] a smart city is a nomination given to a city that combine information and communication technologies (itc) to promote the quality and performance of urban services alike energy, transportation and utilities in order to reduce resource consumption, waste and overall expenses. the general aim of smart city is to improve / enhance the city quality of living for its citizens through smart technology. [4] while the exact definition varies, they all agreed in the goal of achieving sustainability in urban communities, in addition to the overarching mission of smart city to improve the quality of life for residents by using data analysis and smart technology. 2.2. smart city component there are various elements that describe the city to be considered as smart. such cities are supported by different types of technologies, includes:  information / communications technology (ict)  connected internet of things (iot) network by using the physical devices.  geographical information systems (gis) smart cities utilize their web of connected iot devices and other technologies to achieve their goals of improving the quality of life and achieving economic growth. successful smart cities follow four steps:  collection: gathering data in real time throughout smart sensors  analysis: information collected by the smart sensors is determined in order to draw significative insights.  communication: the analysis results phase is studied with decision makers through strong communication networks.  action: cities use the insights drawn from the data to find solutions, optimize operations and guideline management to improve the quality of life for its residents. r. m. kamal, n. a. elsayed and n. g. gado eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e2 3 these technologies may vary; however, all works together to collect and contextualize huge amounts of information that can be used to improve the components and systems running within a smart city. 2.3. the importance of smart cities/smart roads: urbanization is predicted to increase even more in the near coming years. the united nations reports that about 55% of the total populace right now resides in an urban area or city; this is set to rise 68% by the coming decades. the smart technology will assist growth for city’s sustainability and improve efficiency for residence welfare and government efficiency in urban areas in the coming years. particularly population increases show that almost all future population growth will occur in urban regions.[5] with the increases of population in egypt, 104 million, according to the latest analysis conducted in 2017. in conjunction with the increase in life requirements and needs, the new urban communities authority has launched the fourth generation of new cities, which are planned based on artificial intelligence (ai). the number of 4 cities have been launched as a first stage for now, while 20 other smart new cities are being adopted to be included in the coming plans of the authority.[6] this paper focuses on the element of smart roads as one of the most important components of smart cities in supporting management, control, organization and connecting parts of the city as having the capability to define crises and disasters. [7] as well as energy saving, security and convenience for users. [8] this importance is also due to the problems faced by most egyptian cities as traffic jams on all levels of road networks, especially at peak times. the figure shows the possibility of using smart networks in ways to remedy and solve the expected problems before they occur, figure 2. figure 2. smart city management and control through smart road network 2.4. fostering sustainability with smart cities sustainability is another major facet of smart cities, which its achievement based on four rules includes environmental, urban, economic, social and administrative sustainability. while cities already present environmental advantages, the availability of smart road networks, including technology-based tools and devices, will help in sustaining cities. one of the most there most important methods to be described smart are:  energy saving elements: where the operation of smart traffic systems that include follow-up traffic to work traffic signals in accordance with traffic congestion, in order to provide immediate traffic information to road users such as traffic sites or traffic accidents in addition to displaying messages and instructions, important traffic safety tips to increase traffic management efficiency, figure 3. in support of environmental and economic sustainability, the sensitive led technology is used to provide energy consumption as needed, and even to support some methods with solar cells that produce energy and thus reduce carbon emissions. as well as environmental monitoring devices and climate sensors as shown in figure 4 as one of the smart columns’ models used, including smart monitoring devices connected to the main network on the road for collecting and analyse data. figure 3. example of how to display road guidance to increase traffic management efficiency. figure 4. examples of smart columns used by smart methods. smart cities: sustainable and safety roads study model eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e2 4  surveillance devices: through surveillance cameras, sensors where follow-up and reporting traffic system failures also coordinating with maintenance department for further repairs, when needed. the traffic electronic panel’s operation as well as the programming of traffic signals within the central signal control system, as well as following up on advertising campaigns, support the (gis) to serve all organizations, departments and authorities. moreover, control of the main gates, entrances and collection of fees as shown in figure 5. it also monitors traffic violations on smart roads, and police can then use the surveillance cameras installed in cases of crimes. figure 5. elements of monitoring and control through the main entrances by smart methods 2.5 relation of smart ways with improving quality of life: beginning in the mid-20th century, scientists realized that the quality of life is not only material wealth, but many other factors also to be considered as: health, education, freedom, and luxury. as the term quality of life interest began to understand and interpret the relationship between the population and the built environment surrounding them, then, it evolved in the nineties through some large research center to study the quality of life of individuals in cities and develop the theoretical approach to quality of life and methodologies used to measure and evaluate. un, habitat then issued the city prosperity index where the quality of life was considered from the basic dimensions for measuring urban prosperity.[9] whereas the road network is one of the components of the constructed environment that the population deals with, and most importantly because of direct friction and daily use. the more technology and smart applications the system involves, the higher the user satisfaction is. 3. international examples of smart cities while numerous urban cities over the world have begun implementing smart technologies, still a few stand outs as the uttermost ahead being developed. about of the new smart city projects is concentrated in the middle east and china. reykjavik and toronto were listed beside tokyo and singapore as some of the world's smartest cities. in 2018 regularly, thought about the best quality level of the gold standard of smart urban cities, dubai, united arab emirates, smart city technology is used for traffic routing, parking, infrastructure framework and transportation. the city likewise uses tele-medicine and smart medicinal healthcare, just as smart buildings, smart utilities, smart education and smart travel industry. 3.1 the united arab emirates, dubai city experience dubai was chosen as a model for the experience based on being an arab country similar in general circumstances with egypt as well as being a smart and sophisticated city throughout the middle east. intelligent traffic solutions (its) [10] preparing and design, electronic traffic systems using smart traffic systems, that can achieve safe, effective and smooth transport within specific schedules and budgets. preparing studies and design smart traffic system, which includes suggested studying traffic systems for proposed sites, designing traffic systems’ communication networks and e-linking, supervising implementation of the traffic works, in addition to the implantation of toll collection system. operating the smart traffic systems, which include observing the traffic movement in the emirate of dubai through activating surveillance cameras and sensors, effective operation of the traffic signals lights that aligns with roads, congestion levels, following-up and reporting traffic system dysfunctions and failures’, to coordinate with the maintenance department to repair damages caused, operating electronic traffic display panels and programming of traffic signals within the centralized signals control system. following-up, advertising and induction campaigns which presents all about intelligent traffic systems and raise awareness among citizens about these systems. developing, designing and sustaining (gis) to serve all roads and transport authority’s (rta) affiliates, agencies and departments. also, design, integrated, centralized geographic database to be implemented and managed, in addition to coordination with all other concerned departments, government agencies and other stakeholders to gather geographical data and process it, in order to be stored in central databases as pre-approved standards. r. m. kamal, n. a. elsayed and n. g. gado eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e2 smart cities: sustainable and safety roads study model 5 receiving all traffic information and data relating to the movement and set up traffic databases. assessing and evaluating systems that will be purchased by the traffic department and setting necessary standards to be met in the software and hardware related to (gis) and in line with the latest international standards. meeting the needs of concerned departments for pre-packaged software and in-house developed applications to provide accurate information that through which geographic data can be updated, propose and implement training programs about (gis) 's services and software. establish standard specifications for the (as built drawings) and other data, in addition to help the departments in setting terms of the projects in the parts related to traffic data and geographical and maps sections. coordinating with the authority's information technology department of the rta and followingup requirements of the e-government in areas relating to (gis) and the development of information security, as well as information distribution policies. projects: linking light signals with traffic control center using 3g technology,2015. the project includes interfacing all optical traffic signals in the emirate (408 intersections) with the traffic control center via 3g technology. the venture is part of the government of dubai initiative to transform dubai into a smart city. it includes replacing the cables/ wire line used to connect light signals to the traffic control center in dubai with a wireless network, just as associating detached signals with the center utilizing 3g technology.[11] the new framework has high convenience & efficiency and is effectively maintained. it wipes out the lag in the timing of light signals and is viewed as a cost-efficient compared to the past situation, which required an escalated cable infrastructure, phone lines to run the service close by each traffic light signal. led power saving technology in streetlights, 2014. [12] the project is crystalised in the use of led light technology in streetlights, aiming the aim of rta to achieving and generate power saving of approximately 380,368 kwh/year, and thereby reduce carbon dioxide (co2) emissions by 163.6 tons/year. as part of the authority’s (rta’s) initiatives towards saving power consumption and lift the profile of the emirate in driving the green economy and support practical sustainable improvements of projects and the business sector. the work is ready for action in supplanting the lights of the current traffic signals progressively by led lights empowering the saving of about 1 million kwh per year and decreasing co2 emissions by 430 tons/year while following the full accomplishment of the project. with more than 20% of the project works under phase i have been finished and the whole project is set for full fulfilment by 2018. it is noteworthy that, the rta rolled out 32 power-saving initiatives in 2014, including 8 action in corroboration of the green economy as part of its commitment to upholding government efforts. smart parking inspection application,2019 [13] the new application allows parking inspectors in the emirate to rapidly distinguish vehicles in breaking of the law governing the use of public car parks in the emirate of dubai. the advantages of the new application contribute in raising the efficiency of open public parking inspectors in the emirate of dubai, in addition, raising the productivity of work filed. the new smart parking inspection application has a gathering of smart & technical features characterized by several smart technical specifications, including information storage of vehicles in committed of the law regulating public parking. alerting observer to take suitable action in respect of violating vehicles. it insight fully positions, vehicles incompliant with the rules and increasing the quality of images taken of such infringing vehicles, which would reflect positively in, turn on the speed of reacting to complaints and marking them off in a timely closure. adoption of water flow technology to remove ground marks and dyes spilled on the streets, 2015 [14] the project revolves around the launch of a modern technology take off the recent water jet blasters using cutting-edge technology in removing markings and paints spilled on the streets. this system is the most developed in its field regarding of speed and performance, just as being environmentally friendly. the authority is the region's in the van in using the water jet flow technology to remove markings and paints spilled on the streets. this ground breaking technology was previously limited use in removing rubber deposits materials left from aircraft tires due to friction with runways; especially after the successful experimental use of this new technology its first trial in 2010. removing of road markings and spilled paint through water jet blasting technology and the re-sucking of used water is environment-friendly and does not inflict any harm to the public health compared to the old traditional method of singing the sand flow mechanism. furthermore, the new technology is inexpensive, speedy and free from passive impacts on the flow of traffic as it does not demand traffic transformation. this technology is also described by high speed equalling 10 times the speed of the traditional sample and it is notable that rta is providing to utilize this service to contractors and another entity upon request at competitive prices. eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e2 r. m. kamal, n. a. elsayed and n. g. gado 6 completion of 65% of intelligent traffic systems expansion project roads and transport authority (rta) announced that the completion rate of the intelligent traffic systems expansion project had reached 65%. on completion as this project will broaden the scope of intelligent traffic systems in support of making dubai the smartest city in the world. [15] the project will expand the coverage of dubai’s roads by intelligent traffic systems from the present 11% to 60%, cut the time of detecting accidents and congestion build-up on roads, hence ensuring a quick response. the authority had started the installation of new dynamic messaging signs (dms) on main roads to relay instant traffic information about road condition to motorists. the project entails the construction of 112 dynamic messaging signs fitted with the latest technologies at selected locations on dubai’s road network as well as around mega-event spots, such as expo 2020”, figure 6. figure 6. intelligent traffic systems expansion project these signs will provide immediate traffic information about road users such as congestions, accidents, instructions and tips related to traffic safety. for enhancing the efficiency of traffic management, there is two types of signs depending on road classification, number of lanes and traffic volumes. the first type of signals is those installed on roadsides, while the second are large signs that cover entire road lanes. rta has completed the installation 18 panels and work is underway to complete the rest panels according to the project schedule. 3.2 case hamburg city in germany projects: hamburg, germany to test first smart road in europe hamburg, germany has been chosen as the first location in europe for testing of smart roads to begin. the hamburg port authority and cisco built the section of road to make the first smart road a reality. the roadway took four months to work close to hamburg’s docks and the road lanes, three streets and the kattwykbrucke connecting bridge. may 2015, the road has been opened and its trimmed with cameras and sensors mounted to light posts along the road. the four segments that make the road smart enclose smart lighting, smart traffic, smart environment, and smart sensors. the smart lighting has heat sensors and only turns on when a person walks or rides by on a bike. as the pedestrians pass by the lights, they turn off behind them to save power. the smart environment is a series of environmental sensors that transmit data via wifi to let monitors keep an eye on the environment near the port. smart traffic features use management features to improve and optimize traffic flow. if there is a hold up on the road, it is recorded, and information is shared with authorities immediately. the cameras in the system don’t record faces or vehicle registration information, that data is blocked on the video recorded. the bridge area is a vertical lift bridge to allow ships to pass and is 290 meters long. the bridge lifts about once every two hours and takes 20 minutes to go through its complete cycle. the smart sensors help the bridge to operate smoothly and prevent any shipping delays to the port. the smart road will be tested until april 2016 to gather data to determine the impact it has on traffic and efficiency. [16] cisco and hamburg city are well on way to building first-ever smart road about a year ago, cisco and the hamburg port authority (hpa) had got together to build the world’s first ever smart road. the new method called smart road project, would be used to monitor and manage city roads. the smart road ‘proof of concept’ objective to enhance resource management, traffic overflow, infrastructure condition and environmental management, utilize an internet of everything (ioe) concept with accurate information and data analysis. prudence gained out of this would enable cisco, hpa and ecosystem companies to decide on a broader improvement of such solutions in the port of hamburg. today, this initiative was updated with fresh information on exactly how the streets around hamburg’s port would be transformed. traffic management assists the port road administrator with monitoring road traffic. occurrences are identified automatically, and the port road chief officer is notified to coordinate with different authorities. structural sensors give accurate data on the state of dynamic infrastructures as an example, the kattwyk lifting bridge, empower the technical maintenance eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e2 7 department to precisely and predictably the upkeep plan and repairs. environmental sensor transfer data that are utilized to improve investigation of the environmental situation in the port territory. smart lighting upgrades safety for people on foot and cyclists in the port and spares at the same time. all sensors and systems involved in this experiment are associated with an exceptionally secure network infrastructure. data is processed by examination programming, and findings are made available via a centralized, incorporated dashboard. cisco likewise sets up a complete security structure for the entire establishment that gives visibility into safety and security and empowers the port administration to act continuously. the smart road is a consequence of the memorandum of understanding (mou) marked between the city of hamburg and cisco in april 2014. accomplices in the smart port ecosystem are philips (intelligent lighting), agt international (analytics software), t-systems (deutsche telekom’s it benefits, services and consulting division), world sensing (observing and sensors) and kiwi (video investigation and anonymization). “with smart road, hpa is piloting an integrated concept of the internet of everything for the first time, with various relevant use cases for the port and the city, running on a real infrastructure”. “smart road is a key step in making the vision of the internet of everything a reality”. [17] 3.3 comparative assessment model for the international smart cities case studies through the previous theoretical study and analysis of (dubai city and hamburg city), a number of elements have to be taken into account in future plans that will provide intelligent/ smart road networks that support and positively affect any new smart and sustainable city as follows, table 1: table 1. comparative assessment model for the international examples of the smart cities smart road support elements sub-elements dubai city hamburg city energy saving elements (preserving the environment) 1 led ● ● 2 solar cells system 3 increasing the efficiency of the road infrastructure ● ● 4 climate sensations ● smart road support elements sub-elements dubai city hamburg city security supports 5 surveillance cameras ● ● 6 smart dashboards (roads, traffic safety, visibility, etc.) ● 7 emergency services ● ● 8 central signal control ● ● 9 central control of main gates and entrances ● 10 central control of toll stations 11 security control (crimes ...) ● 12 road flow and re-pull technology ● 13 monitoring traffic violations ● 14 gis-gps ● luxury support elements 15 road commercials screens ● 16 sound system 17 weather information (temperature humidity ...) intelligent applications 18 parking lots and alternatives ● 19 gps ● ● 20 use of vehicles electronic traffic boards ● 4. the egyptian smart cities case study as for egypt, we find that it has recently taken its first steps towards intelligence in many different fields in parallel with global trends. perhaps our concern is to discuss main roads, projects, developments as the suez road, as well as planning and design for the new smart and sustainable fourth generation cities, that will be fulfilled in the coming covenant. mostakbal smart city, considered as one of the demonstrated models, located in east cairo, the capital, on the cairo-ismailia desert road, which is considered as the connecting link between (the new administrative capital, new cairo, madinaty and shorouk), figure 7. [18] smart cities: sustainable and safety roads study model eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e2 8 figure 7. the mostakbal city location 4.1 the mostakbal city experience the new mostakbal city of is one of the sustainable ecofriendly cities, as it depends on solar lighting, spacious green spaces and good natural lighting and ventilation. its road network is also designed to support artificial intelligence, increasing the chances of raising the quality of life for users. the mostakbal city phases are divided into five phases, the first one is the best area to attract the population, while the second phase, extends on an area of 1715 acres, contains a lot of services and facilities such as health, administrative, commercial, and entertainment services. as for the third, fourth and fifth stage is residential compounds, figure 8. [19] figure 8. the mostakbal city phases a package of smart systems has been identified for the city's implementation, such as:  use smart systems to control the road lighting network.  installation of internal surveillance cameras throughout the city.  use of control systems for the entry of individuals and cars to the city.  use control systems to manage parking lots.  use its smart traffic light control systems.  use internal radio broadcast control systems to make advertisements/ calls/ announcements throughout the city, or to play music in public places and park area. from the above, the elements that were extracted from the aforementioned experiments and from the theoretical study can be applied to the egyptian experience represented in the mostakbal smart city and extent its achievements to various divisions through the following check list, table 2: table 2. mostakbal city assessment model check list smart road support elements sub-elements mostakbal city energy saving elements (preserving the environment) 1 led  2 solar cells system  3 increasing the efficiency of the road infrastructure  4 climate sensations security supports 5 surveillance cameras  6 smart dashboards (roads, traffic safety, visibility, etc.) 7 emergency services  8 central signal control  9 central control of main gates and entrances  10 central control of toll stations 11 security control (crimes ...)  12 road flow and re-pull technology 13 monitoring traffic violations  14 gis-gps  luxury support elements 15 road commercials screens  16 sound system  17 weather information (temperature humidity ...)  intelligent applications 18 parking lots and alternatives  19 gps  20 use of vehicles electronic traffic boards r. m. kamal, n. a. elsayed and n. g. gado eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e2 9 5. conclusion smart city mainly depends on modern technology and how it can be applied at all levels of the city, especially the roads and traffic through: (i) preparing & implementing intelligent traffic studies and designs concerning intelligent traffic system, which comprise studying suggested traffic systems’ sites, designing traffic systems’ communication networks and e-linking, overseeing implementation of the traffic works, in addition to the implantation of toll collection system. (ii) the design smart applications, technology appropriate to the size and density of the city, which contributes to reduce the traffic congestion daily rates such as the application of new by parking lots. (iii) connecting light signal networks to a wireless system based on 3g technology to follow up its work, to avoid breakdowns. (iv) applying gis system on all geographical databases for roads with a maximum use for traffic, as if to know the congestion rates, as in google maps app. (v) the primary goal of a smart city is to preserve the environment keep it sustainable for future generations references [1] [online]https://internetofthingsagenda.techtarget.com/defin ition/smart-city. [accessed 20 november 2019] [2] conference: bin al habib m., bin hamed a. activating e-tourism within the plan of transformation to smart cities. smart cities under current changes (reality and prospects);29-30 march; berlin, germany. democratic arabic center for strategic, political & economic studies; 2019.p10-26. [3] wikipedia [online]https://ar.wikipedia.org. [accessed 20 november 2018] [4] conference: nezha a., mohamed a. definition of the smart city, intelligent transportation, and morocco experience: sale city model. smart cities under current changes (reality and prospects);29-30 march; berlin, germany. democratic arabic center for strategic, political & economic studies; 2019.p309-321. [5] journal article: sharifi a., yamagata y. resilient urban planning: major principles and criteria. energy procedia. 2014 jan 1;61(supplement c):1491-5. [6] gouda r., sustainable urban model for developing new cities in egypt, phd thesis, faculty of engineering, cairo university, 2019. [not published] [7] journal article: myeong, s., jung, y. and lee, e. a study on determinant factors in smart city development: an analytic hierarchy process analysis. sustainability,2018; 10(8): p.2606. [8] rta [online] https://www.rta.ae/wps/portal/rta/ae/home [accessed 20 november 2019] [9] rta [online] https://www.rta.ae/wps/portal/rta/ae/home [accessed 20 november 2019] [10] rta [online] https://www.rta.ae/wps/portal/rta/ae/home [accessed 20 november 2019] [11] rta [online] https://www.rta.ae/wps/portal/rta/ae/home [accessed 20 november 2019] [12] rta [online] https://www.rta.ae/wps/portal/rta/ae/home [accessed 20 november 2019] [13] rta [online] https://www.rta.ae/wps/portal/rta/ae/home [14] [online] https://www.rta.ae/wps/portal/rta/ae/home [accessed 20 november 2019] [15] albayan [online]https://www.albayan.ae/across-theuae/news-and-reports/2019-08-25-1.3633432 [accessed 20 november 2018] [16] slashgear [online]https://www.slashgear.com/hamburggermany-to-test-first-smart-road-in-europe-11396318/ [accessed 20 november 2019] [17] the internet of all things [online]https://www.theinternetofallthings.com/cisco-andhamburg-city-are-well-on-way-to-building-first-eversmart-road-20150604/ [accessed 20 november 2019] [18] mostakbal city [online]https://www.dimensions-eg.com [accessed 12 march 2020] [19] mostakbal city [online] http://wikimapia.org/17504880/mostakbal-city [accessed 12 march 2020] smart cities: sustainable and safety roads study model eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e2 application of sentiment analysis in understanding human emotions and behavior 1 application of sentiment analysis in understanding human emotions and behaviour sweta saraff1,*, roman taraban2, rishipal3, ramakrishna biswal4, shweta kedas5 and shakuntala gupta4 1amity institute of psychology and allied sciences, amity university, kolkata, india. ssaraff306@gmail.com 2department of psychological sciences, texas tech university, usa. roman.taraban@ttu.edu 3humanities & applied sciences, s, haryana, india. rishipal_anand@rediffmail.com 4department of humanities and social sciences, national institute of technology, rourkela, india. rkbpsych@gmail.com, shakuntala.naik@gmail.com 5department of computer science, national institute of technology, rourkela, india. shweta.kedas@gmail.com abstract introduction: presently, naturalistic observation is considered as critical in understanding, and predicting the complexities of feelings and sentiments. emerging trends of social media has completely revolutionized the process of communication. social media, microblogging, and other means of e-communication can be used for extracting the content to decode the quality, valence, and effectiveness of communication. objectives: in this paper, we represent the explanatory urge of mental health assessment during a pandemic situation, especially in a smart city scenario. methods: we reviewed the role of sentimental analysis, as an emerging application tool for emotional and behavioural analysis for the population affected by a pandemic. this paper examines the prospect of analysing the sentiments through machine learning tools to understand, describe, and predict human behavior. conclusion: further analysis of this psychological e-content can be used to understand and predict the patterns of human sentiments. keywords: sentiment analysis, human behavior, emotions, natural language processing received on 24 june 2020, accepted on 21 september 2020, published on 06 october 2020 copyright © 2020 saraff, s. et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.6-10-2020.166547 *corresponding author. sweta saraff, ssaraff306@gmail.com 1. introduction the covid-19 pandemic has caused an immediate, focused demand for technological assistance in all the mediums of human communication. in a smart city, we consider most of the citizens are netizens, and institutions have a soft, virtual connection with society. today everyone is using more of text messages, than calling or interacting personally. face to face interaction has reduced and youth tend to express their emotions and moods through social media, which may be text, emoticons, punctuations, etc. recently sentiment analysis has been considered as a powerful tool to support psychological evaluations and predict mental health conditions. the multifaceted nature of the expression of valence especially with relation to emotion thought, affect, choice, and decisiveness, has intrigued scientists, philosophers, psychologists, and recently data analysts. with social media surging as the primary mode of communication, both computer scientists and data crunchers have taken a keen interest in both subjective and objective eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e4 mailto:ssaraff306@gmail.com mailto:rishipal_anand@rediffmail.com mailto:rkbpsych@gmail.com http://creativecommons.org/licenses/by/3.0/ 2 analysis of the information being shared in the form of written material over social platforms like facebook, twitter, blogs, etc. this information has the potential to make deep inroads into the minds of the users through text analysis using both supervised and unsupervised machine learning. since a simple text can provide multiple details about the person, it is always pragmatic to have the objective clear from the beginning. a psychologist will look for different constructs and their variances than a business analyst from the same information. the mental health professional would look into the pattern of thought, mood and affect, identify personality type, etc. whereas a business analyst would pay more attention to their shopping pattern, holidays, or payment style. both are looking into patterns and sentiment towards their area of interest. quite often it is difficult for a client to express their innermost thoughts and feelings in the first few meetings with the practitioner, many times the therapist fails to elicit adequate responses leading to an incomplete or incorrect diagnosis. any unattended mental illness has irreparable consequences that may be harmful to self, family, peers, or maybe society in general. it is difficult for youth to manage their stress and anxiety in tough times. the need for psychological services in stress management and optimal wellbeing is growing fast. risk assessment of self-harm, suicide, and violence is difficult to accurately ascertain through self-rated questionnaires and unstructured tests like rorschach inkblot test, thematic apperception test or, draw a person. queries may be biased towards expected responses and cultural differences. artificial intelligence (ai) based algorithms have the potential to support therapists in understanding valence, attitude, and decision making capacities of an individual. this paper attempts to study application of sentiment analysis in psychological assessments through machine based analytical tools. 2. language and emotions human language is a tool to express emotions apart from gestures, postures, and facial expressions. it transmits information in the forms of words, symbolic or acoustic representation of semantically relevant and syntactically organized in a phrase or sentence. though language and emotions are two parallel systems, coexisting and have a relationship in which one system affects the performance of the other. both perform the function of communication between people (bamberg, m. 1997). the relay of emotions in a language is culture-specific. the eastern part of the population relies heavily on the use of emotionally rich words in comparison to the people residing in the west. emotions are both verbally and nonverbally expressed, and it is easier to comprehend the verbal messages than the non-verbal mode of communication. language enriches human thought and accelerates the process of problem-solving and decision making. sometimes words such as joy, surprise, anger, agony, fear, disgust, etc. seem to convey the target message more than facial expressions, which are more culture-specific. fridlund (1997) suggests that the universal facial expressions postulated by paul ekman do not provide a comprehensive account for cultural differences or deviations in different social contexts. paul ekman is known for his pioneering work in the study of emotions and their relation with facial expressions. he has a keen eye in detecting lies and had developed an atlas of emotions. he has conducted crucial research on the universality of expression of basic emotions in humans. (ekman p. 1992). paul ekman (1992) describes emotions as “emotions are viewed as having evolved through adaptive value in dealing with fundamental lifetasks. each emotion has unique features: signal, physiology, and antecedent events. each emotion also has characteristics in common with other emotions: rapid onset, short duration, unbidden occurrence, automatic appraisal, and coherence among responses. these shared and unique characteristics are the product of our evolution and distinguish emotions from other affective phenomena.” 2.1. emotional disorders mental health professionals have always attempted to understand and control deviant and undesirable behavior, which is harmful to self or others and contrary to cultural beliefs and ethos. an observation is made and recorded for any unusual patterns of behavior that also include discrepancies in thinking and emotional disturbances. most of the time, clients present with two kinds of emotional responses in a clinical setting, either they are disruptive, nonadjusting, or low activity, succumbing to stress (table 1). each individual has a specific coping mechanism in response to internal and external stressors. lack of family support, peer pressure, the pressure created by self or organizations, the need for overachievement, perfectionism, controlling attitude, and lack of self-regulations create imbalance or disharmony in life. these lead to emotional imbalance, and sometimes it is difficult to note them accurately and on time. timing is crucial for a successful prognosis in any ailment, whether it is mental or physical. table 1. mental and behavioural disorders with some of their characteristic features based on dsm v (american psychological association, 2013) mental and behavioural disorders some characteristic features schizophrenia spectrum and other psychotic disorders delusions, hallucinations, disorganized behaviour, low selfcare, diminished emotional expressions, etc. bipolar and related disorders elevated mood, flight of thought, inflated self-esteem, uncontrollable excitement, over activity, incomprehensible speech, etc. depressive disorders depressed mood, loss of concentration, irritability, sweta saraff et al. eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e4 application of sentiment analysis in understanding human emotions and behavior 3 sleeplessness, loss of pleasure, loss of appetite, suicidal ideation, etc. anxiety disorders apprehension about possible misfortune, headache, trembling, nervousness, sweating, palpitations, epigastric discomfort, excessive vigilance, etc. obsessive compulsive disorders recurrent thoughts in the form of image, idea or impulse, extremely distressing, lack of self-control, high level of anxiety, restlessness, suicidal thoughts and depressed mood, etc. traumaand stressor-related disorders presence of stressor, low coping mechanism, lack of social support, emotional detachment, fearful dreams, loss of appetite, considerable weight loss/gain dissociative disorders loss of integration between past and present, lack of awareness of self and control over bodily movements, attention seeking behaviour, somatic symptom and related disorders depression, anxiety related to continuously changing physical symptoms, unexplainable body pain, loss of interest in daily activities, sexual and menstrual complaints. 2.2. assessment of emotions, thought and behaviour psychiatric interviews are both structured and unstructured depending upon the referral settings, goals, and context of the interview. the interviewer tries to establish rapport and orients the interview in such a way as to find out the cause for change in behavior. its goal is to collect evidence and organize them efficiently to reach a conclusion based on the multiaxial system of the diagnostic and statistical manual of mental disorders (dsm-5). this interview is directional and considers both inclusion and exclusion criteria. often a semi-structured and open-ended question is asked like the history of present illness, course, precipitating and predisposing factors, family background, personal history related to childhood and adolescence, any history of substance abuse, sexual history, etc. a mental status examination aids the case history and is incremental to psychiatric case workup. it includes observation of the interviewer on general appearance and behavior, mood & affects, perception, thinking, speech & language, attention, concentration & memory, insight, and judgment (grothmarnat, 2009). behavioural assessment includes neuropsychological assessment, selfreported and standardized inventories and projective or unstructured assessment. the primary goal of undertaking these assessments is to find out the reasons behind the shift from usual behavior and come to an appropriate diagnosis for the well-being of the client. a pandemic accompanies real-life tragedy, mental and emotional health challenges, and psychological vulnerabilities are visible in all age groups. the mental health fall-out management needs a systematic approach to provide an urgent, timely support system (meyer et al. 2014). thus, sentiment analysis is useful during the development of a social support network system to handle pandemic situations. sentimental analysis can emerge as an integral part of epidemiological surveillance development and implementation of a system. the result of this hybrid analysis aims to promote community spirit and participation desired in a pandemic situation. the systematic approach in data mining incorporated with sentimental analysis is already in use of inter-institutional coordination during a pandemic threat. sentimental analysis can emerge as an integral part of epidemiological surveillance development and implementation of a system. the result of this hybrid analysis aims to promote community spirit and participation desired in a pandemic situation. the systematic approach in data mining incorporated with sentimental analysis is already in use of inter-institutional coordination during a pandemic threat. 2.3. application of sentiment analysis in psychological assessment most of the available information about the client is dependent on a family member or friend. in some cases, the information is accessed directly from the client. the chances of biases are high. sometimes gender, culture, age, and economic status also interfere with the correct diagnosis (farbstein et al., 2010). in modern times, with the advancement of technology, we must work towards developing a strong, and empirically evidenced measures to rule out the problems inherent in the present system. opinion mining or sentiment analysis is an opportunity in the hands of clinicians to identify new variables from both subjective and objective information provided by the clients. it adds a new dimension to the assessment that is relevant in the present situation. with social media emerging as a new platform for general discourse, ignoring or avoiding such a critical source of information that may add new elements in diagnosis, is unacceptable and renders the earlier conventional mode of diagnosis as incomplete. 3. sentiment analysis average per day human-computer interaction (hci) time is more than human to human interaction. the prevalence of whatsapp chat, facebook messages, or tweets as means of expression provides real-time and quality data that can help in analysing through natural language processing (nlp). technological advancement has broadened the application of sentiment analysis in various fields like political debates, business reviews, medical fields, etc. sentiment analysis uses a computer-based algorithm to analyse perspectives, valence, and subjectivity of social media communication. sentiment analysis (sa), also known as opinion mining (om) study the opinion, attitude, eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e4 4 or emotion towards an entity that may be an individual, event, or a thing. medhat et al. (2014) posit that though both terms sentiment analysis and opinion mining are interchangeable, the main task of sa is to identify the sentiment in a specific opinion and then categorize the inherent valence in terms of its polarity. there are three levels of taxonomies in sa: document-level, sentence-level, and aspect-level or entity-level. the document-level sa endeavours to categorize a document based on the positive, neutral, or negative emotions associated with it. the whole document is assumed to be directed towards a particular topic. similarly, the sentence-level sa tries to identify whether the given sentence is subjective or objective. next, it analyses the sentence to determine the polarity of the valence. medhat et al. (2014) in their survey also discuss the opportunities text mining or sa has provided in related fields. emotion detection (ed) helps in identifying emotions at both the conscious and subconscious levels. both the implicit and explicit meanings in the text or document are extracted. transfer learning aims to evaluate data from one source and use it in another destination. building resources supports the development of a lexiconbased dictionary or corpora in which sentiments are organized based on their polarity. 3.1. opinion mining cambria et al. (2017) discuss sentiment analysis mainly as a positive or negative opinion. an opinion includes sentiment (positive or negative), evaluation of the situation, person or anything related to the subject, estimation, and attitude formation toward the target of the opinion. the opinion is further categorized, based on abstraction, into a single or an array of opinions. bing liu (2017) gives a comprehensive idea about different components of the opinion in quadruple, o = “g,s,h,t” “where g is the sentiment target, s is the sentiment of the opinion about the target g, h is the opinion holder, and t is the time when an opinion is posted.” each component is important, and if any part is missing, we will miss the critical information in ascertaining the weight to the particular opinion. sentiments in a sentence determine the polarity of the valence (emotion) in the text associated with the target of the opinion, and in case of, multiple targets, a specific sentiment is listed for a particular target. words such as amazing, awesome, appalling express emotions that aid in the development of algorithms to extract sentiments as well as opinion targets. (liu, 2017; hu and liu, 2004; qiu et al., 2011; zhuang et al., 2006). b. liu (2017) – “an emotion is a quintuple: (e, a, m, f, t)” where e is the target entity, a is the target aspect of e that is responsible for the emotion, m is the emotion type or a pair representing an emotion type and an intensity level, f is the feeler of the emotion, and t is the time when the emotion is expressed. an excerpt from a young mother shared on facebook “motherhood is the greatest thing and the hardest thing. i am not a supermom… i just do the best i can… i am still struggling… because i love u both. i am a mother first… blessed to have that role in life. the world can like me, hate me, fall apart around me…. at least i have both of u around me …i’m happy. discovering strengths, i did not know i had and dealing with fears which i did not know existed. in a lot of ways, both of u come into my life to teach me. life is tough….but trust me will find me by your side…in every thick & thin. i am your strength and not your weakness… i am proud of u both…hope i make you proud too.” here the entities are the two children towards whom the emotions are targeted. the feeler of the emotion is ‘i” or the mother and the difficulties faced in dealing with motherhood are the target aspect related to both children. the use of superlatives and strong words like hate, the greatest, and the hardest convey the intense emotion of the author. emotions such as hope and happiness are related to children, and despair & tiredness are related to self. psychologists such as plutchik, r., & kellerman, h. (eds.). (2013) have classified discrete emotions based on their intensities. this collection of high as well as low intensity emotion-laden words uses language as a vehicle to communicate emotion coherently. non-verbal patterns of communication such as gesture, posture, and facial expressions are more culture-specific than language. mostly they convey more information than words. moreover, a language depends on a fixed set of syntactic rules and semantics, written into phrases or sentences. the use of quality in a language requires a basic level of expertise for ease of access to mental lexicon, which is vulnerable to decay over time. 3.2. approaches towards implementing sentiment analysis (sa) there are multiple approaches to implement sentiment analysis, the most popular being: • rule based systems there are a set of predefined rules which are used to determine the sentiment portrayed by a given text. • machine learning based systems these are mostly classifiers that use existing data to train a model using various machine learning algorithms. this is used to classify text into having binary sentiments (positive, negative) or multiple classes. example for multi-class sentiment analysis include rating the product on a scale of 1 to 5. • a hybrid application of both rule based and machine learning systems. rule-based systems: to be able to perform meaningful analysis, the text must be pre-processed uniformly. there are a lot of aspects in a text that is intuitive to humans but not to machines. for example, all punctuations are removed along with ‘meaningless’ words such as conjunctions, prepositions, articles, etc. these are generally known as sweta saraff et al. eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e4 5 ‘stop words’ and do not really contribute to the context or meaning behind the text, hence can be omitted. the remaining words are converted to lowercase, after which we use a collection of predefined words commonly referred to as a ‘bag of words’ that have a ‘sentiment value’ associated with it. we can match these words in our text with its corresponding sentiment value. the cumulative sum of the sentiment value of all the words would tell us whether the text has an overall positive or negative sentiment. figure 1. plutchik’s wheel of emotions (borth, d., ji, r., chen, t., breuel, t., & chang, s.-f. (2013) figure 2. the techniques of sentiment classification (medhat et al, 2014) application of sentiment analysis in understanding human emotions and behavior eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e4 sweta saraff et al. 6 figure 3. the steps and components of a machine learning classifier by moujahid, a. (2016). this system will have a low accuracy as it doesn’t take into account the fact that words may have different meanings when combined. for example, ‘happy’ would have a positive sentiment value, and if the phrase ‘not happy’ appears in the text somewhere, it would still signify positivity, which is incorrect. we could include rules to account for such cases i.e. negate the value of a word when it is preceded by ‘not’. however, it will still not account for commonly used idioms or phrases, and a lot of complex rules will be needed to attain even a satisfactory accuracy level. machine learning-based systems: sentiment analysis is a classic application of nlp (natural language processing) and machine learning algorithms. it can be considered a classification problem where we input the given text into a classifier model, and it returns the category the text belongs to. 3.3. text data representation for machine learning models the text data must be converted into a numerical representation, to train a classifier with a machine learning algorithm, called word or text embedding. word embedding is a natural language processing technique that maps text data to vectors of fixed dimensional size. bag-of-words model, n-grams model, tf-idf model, word2vec are few language models that are used for the process of feature extraction from the text. stop words, in natural language processing refers to those words which are too frequent to be informative. examples of stop words are articles, pronouns, and prepositions. in english, the semantics of a few words are similar, and distinguishing those using representative models will increase overfitting. for example, "likes", "liked", "likely" have the same semantic and word stem. the words are normalized to overcome this problem. stemming is one such normalization method used in natural processing language. the most simple, effective, and commonly used ways to represent text for machine learning is the bag-of-words representation. the bag-of-words model uses the frequency of each word in the text, disregarding the grammar and word order, as a feature to train the classifier. the computation of the bag-of-words model requires three steps: tokenization, vocabulary building, and encoding. tokenization is the process of splitting a given text data into smaller units called tokens. vocabulary is built, by using all the words present in the document and numbered. for the encoding process, the frequency of each word in the vocabulary of each document is noted. the main drawback of the bag-of-words representation is that it discards the word order. there may be cases where two different sentences with unlike meanings, have the same bag-of-words representations. for example, consider the sentences: “it's bad, not good at all” and “it's good, not bad at all”. both the above sentences have the same bag-of-words representation, even though the meanings are different. therefore, for capturing context when using a bag-of-words representation, counts of pairs or triplets of tokens that appear next to each other are considered. pairs of tokens are known as bi-grams, triplets of tokens are known as tri-grams, and sequences of tokens are known as n-grams. term frequency-inverse document frequency (tf-idf) is a method used in information retrieval and text mining. this method gives weights to words to evaluate the importance of the words. naive-bayes multinomial naïve-bayes is used for the task sentiment analysis. to determine the probabilities of a given text belonging to various classes, by using the joint probabilities of classes and text. eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e4 7 the bayes theorem is written as: p(a/b) = p(b/a) *p(a) / p(b) where p(a/b) represents the probability of event a given that b has occurred. hence, for our purpose, ‘a/b’ would be the event that the text belongs to category ‘a’ given that ‘b’ set of words occur in the text. for this approach to work well, we need a vast collection of words, sentences, and phrases in our training data. this is because if the sample text contains a unique combination of words that is not present in the training data, its probability will be zero. logistic regression this is a common method used to approximate a certain value on the y-axis given a set of features on the x-axis. here y is the independent variable would be the required category that the text belongs to, and x is the dependent variable would be the set of features extracted from the text. we then plot the training data set as points on a graph. now, various methods with varying accuracies are used to approximate the closest category that the given text can belong to. support vector machines similar to regression, svms are a non-probabilistic linear model that plot training data points on a multidimensional space. it is designed in a way that there are separate regions formed for each category. for example, we can have two features x and y, and two categories positive and negative. we can plot the points in a two-dimensional space with x and y as axes and tag each data point represented by an (x, y) coordinate as positive or negative. we then draw a plane best separating the positive and negative data points. now, we extract the features from the given text and plot it accordingly. whichever side of the separating plane this point lies on, is the category it belongs to. deep learning approach recurrent neural network (rnn) is a deep learning technique that is used for sequential data such as text, speech, stock prices, etc. rnn is the most powerful of all kinds of neural networks because of its internal memory. another method includes the implementation of bidirectional rnn. in rnns, the information cycles through a loop, and the output layer can get information from past states only. in the case of bidirectional rnns, the output layer can get information from past and future states simultaneously. the deep learning techniques try to simulate the behavior of a human brain using artificial neural networks to process the data. one advantage is that deep learning returns better results as the number of data increases and is more accurate than other algorithms for larger data sets. 4. challenges faced multiple challenges arise when trying to derive the sentiment behind words through the use of logic and algorithms because text and speech are essentially subjective at their core. language is highly intuitive, and the human brain can interpret it clearly after years of conditioning. hence it would be unfair to expect the same level of accuracy from a machine. subjectivity and context play a major part in understanding text. if the sample text is complex and has a specific context associated with it, sentiment analysis methods may not yield correct results, since they only take into consideration the logical implications of words and phrases. there are ways to incorporate the context into the algorithm, and sometimes the machine may be able to interpret the context from the text itself. irony and sarcasm are possibly the biggest roadblocks for sentiment analysis because there is absolutely no way for a machine to understand that a sentence means the complete opposite of what it says. even though we can include sarcastic sentences in the training data, the machine will not be able to distinguish the original sentence from its sarcastic version as both of them have the same collection of words. for example, ‘how was your experience using our product?’ ‘too good to be true.’ this response may either be sincere or sarcastic which can only be understood if the tone or context of the sentence is known. the words ‘good’ and ‘true’ will still be registered as positive in most of the algorithms, and hence the result might be incorrect. comparisons or similes may also create challenges if not properly accounted for in the algorithm used. this is because the subject of the sentence has to be identified. for example the sentence, ‘phone a is better than phone b’ is positive for company a while being negative for company b at the same time. hence, the mere presence of the positive word ‘better’ should not determine the sentiment behind the sentence as a whole. similarly, there are a lot of nuances that are starting to appear in the text in modern times. this can be observed more when the text is from social media posts etc. there are a lot of words and phrases social media users come up with regularly which may not have any meaning when read without context. emojis made out of special characters also appear very frequently after sentences and may prove to be essential to their sentiment, sometimes even more than words. most of the machine learning tools are designed to analyse english texts only. there is a need for the development of corpora based on multiple languages for its ubiquitous use in mining psychological data. hence, taking into consideration all the contemporary nuances making their way into the text, along with the innate subjectivity of language, we must be wary of the accuracy of sentiment analysis methods. however, it is still extremely useful for multiple use cases. text mining or sa is qualitative and provides a promising tool in the hands of the physician to explore different avenues in a natural setting which is otherwise application of sentiment analysis in understanding human emotions and behavior eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e4 8 implausible. consent of the client before extracting information from social media is crucial. we must also be sceptical at the same time as not to compromise on matters of confidentiality, and all the ethical guidelines must be followed. references [1] american psychiatric association. (2013). diagnostic and statistical manual of mental disorders (5th ed.). arlington, va: author. [2] bamberg, m. (1997). language, concepts and emotions: the role of language in the construction of emotions. language sciences, 19(4), 309-340. [3] borth, d., ji, r., chen, t., breuel, t., & chang, s.-f. (2013). large-scale visual sentiment ontology and detectors using adjective noun pairs. 223–232. https://doi.org/10.1145/2502081.2502282 [4] cambria, e., das, d., bandyopadhyay, s., & feraco, a. (2017). guide to sentiment analysis. https://doi.org/10.1007/978-3-319-55394-8 is [5] ekman, p. (1992). an argument for basic emotions. cognition & emotion, 6(3-4), 169-200. [6] farbstein, i., mansbach‐kleinfeld, i., levinson, d., goodman, r., levav, i., vograft, i. ... & apter, a. (2010). prevalence and correlates of mental disorders in israeli adolescents: results from a national mental health survey. journal of child psychology and psychiatry, 51(5), 630639. [7] fridlund, a. j. (1997). the new ethology of human facial expressions. the psychology of facial expression, 103. [8] groth-marnat, g. (2009). handbook of psychological assessment. john wiley & sons. [9] hu, minqing and bing liu. 2004. mining and summarizing customer reviews. in proceedings of acm sigkdd international conference on knowledge discovery and data mining (kdd-2004). [10] liu, b. (2017). many facets of sentiment analysis. in a practical guide to sentiment analysis (pp. 11-39). springer, cham. [11] medhat, w., hassan, a., & korashy, h. (2014). sentiment analysis algorithms and applications: a survey. ain shams engineering journal, 5(4), 1093-1113. [12] meyer, o. l., castro-schilo, l., & aguilar-gaxiola, s. (2014). determinants of mental health and self-rated health: a model of socioeconomic status, neighborhood safety, and physical activity. american journal of public health, 104(9), 1734-1741. [13] moujahid, a. (2016). a practical introduction to deep learning with caffe and python. retrieved [14] february, 19, 2018. [15] plutchik, r., & kellerman, h. (eds.). (2013). theories of emotion (vol. 1). academic press. [16] qiu, g., liu, b., bu, j., & chen, c. (2011). opinion word expansion and target extraction through double propagation. computational linguistics, 37(1), 9-27. [17] zhuang, l., jing, f., & zhu, x. y. (2006, november). movie review mining and summarization. in proceedings of the 15th acm international conference on information and knowledge management (pp. 43-50). acm. sweta saraff et al. eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e4 an analysis of trends, developments and transparent issues in the making of indian smart cities 1 an analysis of trends, developments and transparent issues in the making of indian smart cities aatif jamshed1,* 1abes engineering college, ghaziabad, uttar pradesh, india abstract during the past few years, interest has grown in the creation and application of methods, structures for smart city evaluation. this reflects the increasing awareness of the value of systems for better planning and architecture of efficient and stable communities. a city is a vast and permanent human community that offers many resources and opportunities for its people. the rapid urbanization and growth have put a lot of pressure on local services and service delivery. the research discusses many potential resources that can make a city smart across growing city dimensions and also discusses the initiatives of the indian government towards a smart city. this paper is a survey of a variety of papers, covering the actual case study from a more comprehensive framework, such as e-mobility, which covers the smart city subject from. keywords: smart city, iot, ecosystem model, capability layers handling editor: akshat agrawal (amity university gurgaon, india) received on 07 august 2020, accepted on 24 august 2020, published on 31 august 2020 copyright © 2020 aatif jamshed et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.18-8-2020.166042 *corresponding author. email: aatif.jamshed@abes.ac.in 1. introduction what a smart city is all about. the response is that the idea of an intelligent city is not generally accepted. various people say different things. the conceptualization of smart city therefore depends on how much development, readiness to change and changes, the resources and expectations of people differ from town to city and city to country. defining a smart city [1]: a smart-city has developed infrastructure to capture, process, and analyse real-time data in order to better the lives of its citizens. the study indicates that every smart city initiative needs strong guidelines on new technologies and data, a functioning administrative structure, and some form of community engagement. brooks rainwater, co-author, and founder of nlc city solutions and research centre [4] said, technological innovation is closely related to urban growth. although "trends in intelligent city development" shows no one-size-fits approach to the implementation of intelligent city systems, it makes three recommendations which must form the core of each plan: the most successful smart or intelligent city initiatives are those with clear goals that solve public issues that are unique to every city. cities will turn at collaborations with colleges, non-profit groups, and the business sector [4]. figure 1. smart city vision eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e4 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ mailto:aatif.jamshed@abes.ac.in aatif jamshed 2 figure 1 reveals the smart city vision. smart-city is an integrated system of intelligent treatment, smart technology, smart environment, smart workplace and smart citizens of course [3]. partnerships provide cities with many advantages, including access to finance and external expertise. cities will strive to follow best practices and smart city growth systems. city officials will take into account and develop technical principles and structures for smart-city growth [7]. within a smart city the main network components would include: • suitable water supply, health and education • providing guaranteed power and sanitation and the disposal of solid waste, • efficient public transport and urban mobility; • low-cost housing, particularly for the elderly, • robust it and digitalization integration, 1.1. govt. initiatives an scm underlined in figure 2 below has been initiated by the govt.of india through the mohua-ministry of housing and urban affairs. the scm of the government of india supports cities that provide the citizens with a healthy and secure environment for their core amenities and good quality of life, and the introduction of smart' technology. these smart policies cover e-governance ict programs, online government facilities, and relatively reduced prices to improve key service efficiency [11]. the aim of the smart cities project is to encourage communities with modern services and inhabitants with a better standard of life, a healthy and prosperous climate, and the implementation of smart technologies. the purpose and target is to look at limited areas, construct a model that can be used as a lighthouse in other developing cities [12], and to develop a replicable model of sustainable development. the smart city program of the state is a bold, innovative initiative. it is intended to build templates that can be replicated in and out of smart city, catalyzing the creation of parallel smart cities across the world's various cities and regions. source: india.gov.in figure 2. smart cities mission the goal of the smart cities mission [10] is, therefore, to accelerate economic growth and enhance people's quality of life by promoting urban development and technology creation, in particular technology that contributes to smart outcomes. area-based planning would turn existing areas including slums, into betterdeveloped neighbourhoods, although enhancing the profitability of the city as a whole [14]. modern areas beyond cities will be built to meet the increasing development of metropolitan areas. in order to improve technology and facilities, the smart technologies architecture will enable cities to leverage software, knowledge and data. this will improve the quality of life, generate employment and develop prosperity for everyone, particularly the poor, and vulnerable, contributing to sustainable cities [8]. 1.2. case study analysis bhubaneswar e-mobility plan: bhubaneswar, by major public transit network investments and last mile connectivity modes, the goal is to trigger a 20% change to public transport by 2021. according to the bus modernisation programme, 38.7kmspriority transit corridors would need 148 new electric passenger buses to carry 192,000 passengers daily. first-last-mile within its abd connectivity, the city proposes the deployment of 500 e-rickshaws, the associated infrastructure and charging stations from 2021.ventures will serve as a catalyst to help bhubaneswar achieve its target goal of 30% of vehicles powered by electric vehicles in town by 2030 [9]. via participatory policy-making, good governance, and free access to it, bhubaneswar is a: • city based on public transportation that facilitates involved, integrated, and affordable mobility choices eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e4 an analysis of trends, developments and transparent issues in the making of indian smart cities 3 • vivid community with numerous housing, educational and leisure facilities while improving its history, culture and cultural cultures • children's friendly town with open, secure, inclusive and vibrant public areas • eco-city that resides in harmony with nature to sustain a stable, clean, green and balanced climate • the regional economic centre, through the presence and empowerment of their governments, local businesses and informal workers, is attracting knowledge-based businesses and sustainable tourism development. the e-vehicle policy [13] outlines key measures through governments of states / cities as follows: • determination of the correct area / routes for electrical rickshaw service within the city • define the regulatory requirements for electric rickshaws in odisha to ensure maximum coverage • finalization of draft electric rickshaws legislation • determination of electric vehicle tariff to be paid • odisha electricity regulatory commission approval of tariff • to identify sustainable operating models for infrastructure charging • define the requisite amendments to the building laws • establishment of an air ambient fund structure • describing auto-rickshaw buyback system structure 2. role of iot in connected cities the internet of things (iot) supports cities connecting disparate public services, infrastructure and networks. such intelligent cities produce quantitative data in real time to more efficiently monitor initiatives and resources and to assess their effects instantly [13]. platooning trucks transport freight easily from port to destination. smart distribution systems warn operators as freight is transferred between locations. when the time comes to retain or replace public transport and community service cars connect with their home entity. self-driving vehicles carry users to and from the area, offer transport and delivery to others. apps work with intelligent parking meters to warn drivers about the availability of parking. the sensors measurement the volume of waste in public receptacles so that sanitation workers can optimize productivity on their way. solar panels will be tracked to see how much electricity they produce and if maintenance is required. led lamps are sensitive to the environment and periodically notify the public works department when the bulbs need to be adjusted. sensors track fireprone situations in urban parks and forested areas. sensors are now able to identify flames in buildings and trigger an alarm call to the fire service. power plants can be tracked in order to track health and local police can be aware of the pollution rates. cities depend on and promote ecommerce to be competitive in the economy of 21st century [16]. drones can be used for law enforcement and firefighting as remote outposts for maintenance inspections and for environmental protection. areas not open to public access cannot be monitored to keep illegal workers out. commercial applications include precision production, aerial imaging and parcel distribution in the near-coming future. cities should create smartphones and wearable devices and allow residents an integral member of the internet network that interacts with the community [17]. table 1 says what internet stuff means for towns? table 1. iot-internet of things mean for cities. transport utilities services smart logistics waste mgmt. fire detection vehicle fleet solar panels radiation levels self-driving cars lighting e-commerce parking water and wastewater surveillance cameras/drones the latest trend is to smart cities. citizens around the world are working to make communities more prepared with electricity, security, education and transportation technologies. cities are creative centres, social beehives, hotbeds of invention and perhaps the most interesting cities to explore in the country. cities are growing; the united nations predicts that by 2035[17], [18], 67 percent of world's people will live in the urban regions, according to national geographic. smart cities utilize ict to be smarter and more effective in resource use, resulting in expense and electricity reductions, increased infrastructure efficiency and quality of life, and decreased environmental impact – both promoting creativity and the low-carbon economy. table 2 lists some of the world's inventive stakeholders [15]. table 2. global smart cities and their inventions name of city equipped technology vienna smart energy vision toronto low-carbon economy solutions new york optimize business process solutions london congestion tax tokyo smart grid barcelona low-carbon solutions. table 3. smart cities in india and their latest inventions eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e4 aatif jamshed 4 name of city equipped technology indore kahn riverfront development surat smart city centre visakhapatnam all abilities children park coimbatore smart street bench delhi ndmc open space development bhubaneswar e-mobility plan for reader's convenience knowing, this article included many acronyms. table 4 shows all the acronyms included [14]. table 4. list of acronyms abbreviation description scm smart cities mission iot internet of things sca smart city agent cap consistency availability partition resist scc smart city challenge 3. background study h kumar et.al [1] propose a multi-dimensional hierarchy of services and critical infrastructural growth. furthermore, it will enable politicians, local planners, government officials and infrastructure providers to identify and gain more insight from potential creative solutions for sustainable community development in the smart city transition process. in the concrete framework to describe urban development, five main fields (planning and public design, ict services and smart solutions) are discussed. the current sctf is supported by research and experience in many intelligent cities around the world to highlight its usefulness. furthermore, an elegant and systemic simulation for the city transformation process demonstrates the interrelationship between the ideas collected. j laufs et.al [2] have assembled a list of security initiatives for intelligent communities and have recommended different improvements to the strategic status quo on the ground. finally, we suggest three specific groups to categorize security measures in smart cities: those initiatives utilizing modern sensors with existing actuators, those trying to turn old devices smart, and those implementing completely different features. those topics are then addressed in depth and the significance for the general field of public protection and governance of a set of initiatives is assessed. a sharifi et.al [3] discussed general knowledge on aspects such as geographic scope, research size, demographic target and production process. this also describes structure, thematic focus zones, and repeated indicators in systems, and includes detailed detail on the various techniques and methods used to assess city smartness. results show that different approaches were taken, but some commonalities also exist. index is the system-wide model of the most common themes: environment, people, politics, climate, accessibility, living, and records. this typology research can be used for many purposes; it can act as a reference frame for those who use appropriate schemes to analyse the efficiency of smart cities, can be used as a framework for more strategic review of evaluation schemes, and can also direct the development of better educated schemes. pa johnson et.al [4] conceptualized how the modern smart city incorporates people not only as a community, but as a series of micro-transactions integrated in the city's real-time climate. a smart city system monitors this transactional resident and translates it across other networks into intelligent community decision-making. we have developed four different interaction modes to address this shift from traditional methods of communicating with people and the metropolitan environment to micro-transactions: sort (intentional contribution), tweet (intermediate third parties), tap (interaction accepted or requested) and switch (ambient motion driven transaction). such four approaches are used to address core concerns on how the citizens in the emerging era of the smart cities interact with the government and how these interactions form people's political relationships and build different power outlets in the private sector. m lom et.al [5] created a new concept, smart city agent. the sca is the main building block for smart city modelling. however, this paper's approach emphasizes the interconnection of various systems within a town. its strength is better data exchange and heterogeneous agents. this knowledge management strategy is the missing link in the increasing demand for partial smart city technologies, allowing applications to be replicated in dynamic environments like a city. the appropriateness of the value of the proposed alternative as seen on an electric car charging usage case. results show the approach to dynamic behaviour modelling. s edge et.al [6] aimed throughout the face of spatial and social change, brought out common viewpoints and insights throughout downtown kitchener, ontario, canada, an intensely clever city on the development track. they adopt an innovative analytic procedure (cap) method and offer a collection of complex vignettes focusing on the experiences of these stakeholder groups centred on data collected from a neighbourhood dialogue involving representatives of city government, technology and start-up sectors, community service organizations and public leaders. the vignettes highlight various assumptions about the role of technology in enhancing quality of life and demonstrate incapacity to turn shared and equal goals into practice on the ground. we contend that cap is an important tool for addressing and eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e4 an analysis of trends, developments and transparent issues in the making of indian smart cities 5 enhancing the inclusiveness and openness of conversations and debates in smart cities. 4. impact on real state new house-building figures are main economic indicators. which means they'll give you heads-up on the housing market 's prospects. the figure 3 below shows the number of new private-owned housing units launched in 2009-2020[15]. figure 3. new privately owned housing units impacts predicted are: • improved data collection of data should allow stakeholders to better understand a property or location, its environment and inhabitants. • in the coming years, stronger demand is expected for smart buildings [16], which use digital processes to manage a range of operations such as monitoring and controlling resources, climate, protection and other main features. • advances in technology are disrupting the conventional structures of businesses choosing where to conduct business; purchasing or leasing an office; building it to their specifications; and designing equipment for their employees to perform their work. • in smart cities, data centres are required to play a leading position as the hubs for massive data acquisition, storage, retrieval and archiving. there are following categories of property types [20]: • residential land covers new and resale properties. the most popular is single-family housing. • features shopping centres and strip malls, hospital and residential facilities, hotels and offices. • commercial real estate covers factories and land and warehouses. • land includes vacant land, farmland and ranches. 5. challenges for smart city solutions recognizing that cities are the drivers of development and attracting a million people per minute from rural areas, the government launched the scc-smart city challenge [17], handing over targeted urbanization to the states. the aim of the scm-smart cities mission strategy is to encourage communities that have key services and have people with quality of life, a safe and healthy climate, and 'smart' solutions. key challenges and their description is enlisted in table 5 [15]. table 5. key challenges of smart cities challenge description infrastructure utilization of sensor technology security and hackers cyber-terror threats privacy concerns invasion of privacy educating community awareness in citizens being socially inclusive smart transit programs smart cities are utilizing sensor networks to obtain and analyse knowledge to increase the quality of life for people. sensors gather data from rush-hour statistics to crime rates and air quality in general. installing and operating these devices calls for complex and costly systems. how are they going to get that power? does hard-wearing, solar or battery operation require this? and, for power loss, maybe a combination of all three? large urban areas are now threatened by upgrading decades-old networks such as electric wires, steam pipes, and rail tubes, as well as high-speed broadband. broadband wireless coverage is growing, but connectivity is limited in major cities. recent debate about cyber-terror risks to fragile, aging power grids has a little more anxiety and cynicism about technology and defence. smart cities spend more time and money in infrastructure, while technology firms build apps with creative built-in systems to defend against ransomware and cybercrime. with block-chain being the focus of the computing industry, many developers are finding ways to integrate these cryptographic technologies into current security-enhancing applications. any big city wants a compromise between quality of life and privacy breach. while everybody has to achieve a more comfortable, happier and safe atmosphere, nobody likes to know like any family member is actively watching them [18]. cameras mounted on any street corner can help to discourage violence, but they may also generate distrust and fear among law-abiding people. another important factor is the sum of data collected daily by all occupants with smart sensors. eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e4 aatif jamshed 6 to effectively maintain and grow an informed society, it takes intellectual persons who are interested in the usage of new technology to utilizing them actively. for a current city-wide technological program, the development phase must include informing residents in the public regarding its advantages [19]. real-time updates are an innovative concept for a busy society with smart transportation services providing riders. so what if one half of the city 's populace does not afford mass transport or uber? what about the elderly residents, without having mobile devices or apps? this is crucial because smart city development needs empathy for all groups of society, not just the wealthy and technically developed ones. innovation should often contribute for getting communities together instead of dividing them on the basis of income or jobs. 6. nation-building initiatives in india the nation-building initiative aimed at turning india into a regional centre for design and manufacture. following are the list of some initiatives shown in figure 4: • make in india • india.gov.in national portal of india • incredible india • smart net (urbanization solution) figure 4. list of nation building inititives 6.1. project’s schemes by govt. government has initiated various beneficiary programs shown in figure 5 for the benefit of people and, of course, country under the umbrella of national initiatives. figure 5. list of beneficiary programs/schemes on behalf of west bengal housing and construction infrastructure corporation ltd (wbhidco ltd), bengal urban new town's city development plan (cdp), designed and submitted by infrastructure development limited (buidl) –kolkata, to be listed under the satellite town planning scheme for urban infrastructure about seven mega towns. new town, part of the rajarhatgopalpur area, is a rapidly developing satellite town in metropolitan kolkata place (kma), which has the capacity for construction of infrastructure. therefore, the town is expected to be able to absorb additional population growth and help lighten burden on city of kolkata [21]. 7. ecosystem framework – a model a smart city is a city with six characteristics, based on the "simple" blend of self-decisive, autonomous and informed people [20]. figure two demonstrates our smart city architecture structure. an environment composed of individuals, organisations, enterprises, regulations, laws and processes interconnected to achieve the desired effects in figure one is a lively and prosperous community. this community is flexible, sensitive and still important for everyone living, working and visiting the area. an intelligent city incorporates technologies to speed up, activate and turn this ecosystem [21]. in the intelligent city environment there are four types of value producers. we create and absorb value for one of the results mentioned in figure7 project’s schemes nerudp amrut jnnurm satellite towns urban transport lumpsum provision hriday nulm swachh bharat mission eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e4 an analysis of trends, developments and transparent issues in the making of indian smart cities 7 figure 6. the smart city ecosystem framework. if you think of a wise city, you immediately think of civic and quasi-governmental infrastructure such as smart car parking, smart water supply, intelligent lighting etc. in reality, three others – corporations and associations, neighbourhoods and people – co-exist in the intelligent community. figure 7. the smart city ecosystem framework. businesses and organisations should create programs that leverage knowledge to produce outcomes for their stakeholders. some examples of "smart" companies include uber and lyft for personal mobility and nextdoor for knowledge sharing [22]. communities are wise, albeit rather clustered cities. many examples include schools, office parks, terminals, freight facilities, multinational units (mdus) or residential projects, housing developments / districts, commercial districts, and even individual "smart" houses, which may be smart neighbourhoods. we need intelligent resources that can be precisely customized to their stakeholders. intelligent infrastructure suppliers in smart cities are either tenants or regular individuals. a citizen living near a dangerous crossroads can point a camera to the intersection and broadcast information to traffic planners and the police live. to order to track ozone and pollen rates at certain times of year, homeowners put air quality monitoring sensors on their property and provide this information to certain community members. residents can opt to temporarily or permanently render such intelligent services free of charge or dependent on fees. a smart city is an ecosystem consisting of several capability layers listed in table 6. whilst technology is an important facilitator, it is just one of the fundamental technologies that any intelligent community requires. no one is more important than the other. in the clever city, every skill plays a different role. these capabilities must be integrated and coordinated to fulfil their mission. table 6. list of capability layers name of layer description value layer visible layer for city residents & others innovation layer. variety of innovation programs governance & operations layer upgrade their existing infrastructure policy & financing layer partners are required to build, operate information and data layer open data initiatives security layer. seamless layer of trusted connections. infrastructure layer. support a new class of value creators the following steps are important: understand the architecture and adapt it to the sense of a special field of the smart city ecosystem. include this idea in the development and execution of the intelligent urban visions, policies and strategies. defining current capabilities and vulnerabilities on many dimensions in the sense of intelligent municipalities. understand what the four ways of sense consumers require. evaluate smart city projects and strategies on existing and evolving environments. this approach helps to decide what the projects need and what is required to complete the projects. prioritize and develop expertise at different habitat levels. a smart city needs new talents and knowledge. improvements in capabilities by strategic partnerships and agreements with service suppliers, where possible. eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e4 8 8. conclusion technology has made many potential lifestyles dreams a reality the smart city is just one of the technological solutions. the concept of smart cities is extended in other parts of the world including the u.s., mexico, finland, south korea, sweden, and others. such cities should make a quality of life leap. smart cities are designed to fit the contemporary city's needs and potential. the "smart" city, intelligent world, knowledge community, smart communication, and wireless media are among the nomenclatures used. although the real estate sector is making significant strides in smart buildings' growth and innovation, it is important that they obtain a comprehensive understanding of how these innovations match and integrate with the wider smart city environment. in particular, stakeholders in the real estate sector will need to consider new data sources and how to build on them to support land asset creation, construction, and management. 9. future work smart city projects are projected to expand in the future, revolutionizing areas such as health care, healthcare, and policing, while also promoting the encrypting development [24] and progress of engaged people who will adopt and use technological technologies and services like smart people. future study can have utilized different deep learning frameworks for progressive databases [25]. this study will continue using factors such as: power efficiency, service quality, data transmission speed, range, sensor size, data storage, data transmission reliability, delivery cost, network type and processor to review these published papers on sensor and routing protocols. references [1] journal article: kumar, h., singh, m. k., gupta, m. p., & madaan, j. (2020). moving towards smart cities: solutions that lead to the smart city transformation framework. technological forecasting and social change, 153, 119281. [2] journal article: laufs, j., borrion, h., & bradford, b. (2020). security and the smart city: a systematic review. sustainable cities and society, 55, 102023. [3] journal article: sharifi, a. (2020). a typology of smart city assessment tools and indicator sets. sustainable cities and society, 53, 101936. [4] journal article: johnson, p. a., robinson, p. j., & philpot, s. (2020). type, tweet, tap, and pass: how smart city technology is creating a transactional citizen. government information quarterly, 37(1), 101414. [5] journal article: lom, m., & pribyl, o. (2020). smart city model based on systems theory. international journal of information management, 102092. [6] journal article: edge, s., boluk, k., groulx, m., & quick, m. (2020). exploring diverse lived experiences in the smart city through creative analytic practice. cities, 96, 102478. [7] journal article: yigitcanlar, t. (2015). smart cities: an effective urban development and management model? australian planner, 52(1), 27-34. [8] journal article: anttiroiko, a. v., valkama, p., & bailey, s. j. (2014). smart cities in the new service economy: building platforms for smart services. ai & society, 29(3), 323-334. [9] conference: castro, m., jara, a. j., & skarmeta, a. f. (2013, march). smart lighting solutions for smart cities. in 2013 27th international conference on advanced information networking and applications workshops (pp. 1374-1379). ieee. [10] journal article: m. vanis and k. urbaniec, “employing bayesian networks and conditional probability functions for determining dependences in road traffic accidents data,” 2017 smart city symposium prague (scsp), may 2017. [11] journal article: pagani, f. bruschi, and v. rana, “knowledge discovery from car sharing data for traffic flows estimation,” 2017 smart city symposium prague (scsp), may 2017. [12] journal article: p. pecherkova and i. nagy, “analysis of discrete data from traffic accidents,” 2017 smart city symposium prague (scsp), may 2017. [13] journal article: anandakumar, h a, & umamaheswari, k. a (2017). supervised machine learning techniques in cognitive radio networks during cooperative spectrum handovers. cluster computing, 20(2), 1505–1515. doi:10.1007/s10586-017-0798-3 [14] conference: v. kostakos, t. ojala, and t. juntunen, “traffic in the smart city: exploring city-wide sensing for traffic control center augmentation,” ieee internet computing, vol. 17, no. 6, pp. 22–29, nov. 2013. [15] conference: u. nakarmi and m. rahnamay naeini, “towards integrated infrastructures for smart city services: a story of traffic and energy aware pricing policy for charging infrastructures,” proceedings of the 6th international conference on smart cities and green ict systems, 2017. [16] conference: wenzhao liao and zhiren fu, “a cloud platform for flow-based analysis of large-scale network traffic,” iet international conference on smart and sustainable city 2013 (icssc 2013), 2013. [17] journal article: anandakumar, h. b, & umamaheswari, k. b (2017). an efficient optimized handover in cognitive radio networks using cooperative spectrum [18] sensing. intelligent automation & soft computing, 1–8. doi:10.1080/10798587.2017.1364931 [19] journal article: k. b. malagund, s. n. mahalank, and r. m. banakar, “app controlled: cloud service oriented smart city traffic management,” 2016 symposium on colossal data analysis and networking (cdan), mar. 2016. [20] conference: m. r. alifi and s. h. supangkat, “information extraction for traffic congestion in social network: case study: bekasi city,” 2016 international conference on ict for smart society (iciss), jul. 2016. [21] conference: y. tian and l. pan, “predicting short-term traffic flow by long short-term memory recurrent neural network,” 2015 ieee international conference on smart city/socialcom/sustaincom (smartcity), dec. 2015. [22] journal article: arulmurugan, r., sabarmathi, k. r., & anandakumar, h. (2017). classification of sentence level sentiment analysis using cloud machine learning techniques. cluster computing. doi:10.1007/s10586-0171200-1 aatif jamshed eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e4 an analysis of trends, developments and transparent issues in the making of indian smart cities 9 [23] conference: imawan, f. putri, and j. kwon, “tiq: a timeline query processing system over road traffic data,” 2015 ieee international conference on smart city/socialcom/sustaincom (smartcity), dec. 2015. [24] journal article: kumar, a., mehra, p. s., gupta, g., & jamshed, a. (2012). modified block playfair cipher using random shift key generation for smart. international journal of computer applications, 58(5). [25] journal article: jamshed, a., mallick, b. & kumar, p. deep learning-based sequential pattern mining for progressive database mainly for bins. soft comput (2020). https://doi.org/10.1007/s00500-020-05015-2 eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e4 prognostic modelling for smart cities using smart agents and iot: a proposed solution for sustainable development 1 prognostic modelling for smart cities using smart agents and iot: a proposed solution for sustainable development shafqat ul ahsaan1, ashish kumar mourya2,* 1department of computer science and engineering, jamia hamdard, delhi-110062 2department of computer science and engineering, gautam buddha university, india abstract currently, scientists are working on smart cities for providing artificial intelligence based smart facilities and services that can tackle different problems raised by rapid urbanization and boom in population growth. the internet of things is also being used with other smart technologies to provide better solutions to the environment. it is also known as a network of networks. mobile agent technology has also gained more attention. we are using it with different internet-based services. in this research, we have proposed two models with a sustainable approach. our first model focused on monitoring air quality which consisted of several sensors, arduino uno board, and raspberry pi 3. the second model explores the potential of the mobile agent technique to lever the internet of things in the modernization and personalized services for smart cities. keywords: smart city, internet of things (iot), software agent, mobile agent, artificial intelligence (ai), digital initiative, arduino uno board, raspberry pi 3 received on 21 february 2021, accepted on 13 may 2021, published on 13 may 2021 copyright © 2021 shafqat ul ahsaan et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-5-2021.169916 1. introduction the idea of the high-tech smart city is moderately new, and it will soon take over to knowledge city, digitalized city, and feasible city. although, it has been used regularly exclusively after 2012, although the conversation about its architecture and thought in recent years. there is a lack of unanimity about it. smart city term has covered the different sub-themes such as smart urbanization, smart financial system, sustainability, and smart environment, high-tech technology, energy conservation, smart mobility, smart medicare, and so on [1]. with the advancement on the internet of things devices and their application, mobile spectrum, broadband communication, next-generation, cloud-based technology, etc.; informatization has a propensity of higher smarter phase. recently some corporate houses issued the concept of “smart globe". smart globe believes that sensing devices are embedded in public places like public transport station, bridges, subways, roads, buildings, rainwater harvesting systems, dams, mercantile equipment, and healthcare devices, and then physical facilities can be professed, so digital technology extends into the physical world, creating an "internet of things". moreover, the internet of things may relate to networking to numeral the social community and physical system [2]. the human being, the machine, electronic devices can be managed in the incorporated system through networking and cloud computing, so the human's invention and life can be managed more accurately and energetically to get smarter, hoist resource usage and productivity, and improve the association between human and environment. the smart (high-tech) city also relies on the iots, sensing devices, and cloud computing to provide an extensive network of linked electronic devices. smart sensing devices and large-scale data analytics to enable the move from the internet of things to real-time control. smart devices-based machinery has revolutionized the digital era and became an important field of life particularly eai endorsed transactions on smart cities research article *corresponding author. email: ashishkumarmourya@gmail.com eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e3 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ shafqat ul ahsaan, ashish kumar mourya 2 in the context of sustainability. internet of things (iot) is a collection of objects that are connected in such a way that they form a network. these networks of objects can communicate with each other utilizing the internet, mobile phones, sensors that have been implanted at specific areas, radio frequency identification (rfid), general phone radio service (gprs), and computers [1-2]. these objects communicate with the help of unique addresses that allow them to be verified and addressed over the network. the objects in the network are assigned with a specific task and send reports to the users [3]. internet of things technology is applying in smart cities as a key component. for instance (see figure 1), to offer user-friendly services, the data capture by digital home appliances including refrigerators, washing machines are share and use in a smart home environment [2]. figure 1. iot application domain smart devices-based machinery has revolutionized the digital era and became an important field of life particularly in the context of sustainability. internet of things (iot) is a collection of objects that relate to each other in such a way that they form a network. these networks of objects can communicate with each other by means of internet, mobile phones, sensors that have implanted at specific areas, radio frequency identification (rfid), general phone radio service (gprs) and computers [1-2]. the advancement in technology with the passage of time has changed the overall scenario. these objects communicate with the help of unique addresses that allow them to be verified and addressed over the network. the objects in the network are assigned with a specific task and send reports to the users [3]. mobile agents (software agent technology) have some advantages that have boosted the internet of things technology. the key role of mobile agents is to minimize networking capacity, encapsulate protocols to resolve network latency. they can perform autonomous tasks during accumulation, which would otherwise require large configuration. however, the drawback of this technology is the use of unique technology and host environment is expected by many agent systems that make it difficult to use them and entail that especial skills are required in the formation of agents. mobile agents are executable (runtime) entities which can switch from one host to another along with the software applications’ internal state. this means that an executing agent on the current system will interrupt its execution and continue with another system. a special case of moving code integrating remote evaluation with internal state preservation is mobile agents [4, 5]. 2. challenges and need for iot in smart city as smart city concepts continue flourishing tirelessly, their challenges need to be considered from beginning for population growth, economic development, and social progress to follow the same path. every smart city scheme includes high-tech lighting, imaginative transport systems, and high-tech utility metering for electricity and water. all these emerging technologies and integrations fully depend on sensor-centred data gathering and analysis. while the various benefits of smart city initiatives remain, due to specific city requirements and different interpretations of implementation principles, several difficulties when it comes to deployment. some important challenges that need to be tackled when we talked about the smart city concept are listed below: • high-speed internet connectivity • low-cost iot devices • data security • governance • gps enabled transport services • interoperability implementation of sensing devices in smart cities like iot is an extraordinarily complex practice. it needs a lot of strategies and sometimes a large number of investments. this is because the internet of things system consists of many diverse components. implementation of each of the iot components bears different challenges along with it, so we must be careful during applying these smart city management policies. therefore, the implementation of iot in the smart city is one of the biggest challenges because it needs time and huge money. that is why policymakers across the world are trying to make the atmosphere more users friendly to develop and working on the cheapest devices. this manuscript has worked on the following objectives: i. the proposed study provides a solution for smart city development with sustainable approaches. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e3 prognostic modelling for smart cities using smart agents and iot: a proposed solution for sustainable development 3 ii. what are the main challenges and hurdles in between the development of smart cities? iii. the proposed study also compared different studies that have been carried out so far. iv. the proposed study also built two models for smart cities. v. analysis of state of the art about smart city technology 3. comparative study of different models for smart city in literature, there are more than enough definitions for smart cities, but the universal definition has not been framed yet. it looks that digital and smart city both the terms are frequently used in educational research to delineate the "intelligence" of a city. the outline regarding the term; how a city is said to be smart is covered in different research publications. what are the characteristics of a smart city? there are almost all researchers from every field who mainly focus on sustainable development of cities with elevated reliance on a permanent progressive route map for the development of cities. a setup to consider the model of smart cities is built on eight significant features: people and communities, leadership and organization, advanced machinery, policy context, control, economy, infrastructure, and natural surroundings [1]. these factors act as the foundation of a consolidative framework that puts forward the guidelines and outline to neighbouring governments for envisaging smart city projects. the model and connection of the smart city with the digital city is based on the core content of implementation procedures, the tackle to buildability, and the impact of its progress. the smart city fundament is the primary step to set up the smart city skeleton and structural design on the whole; its progressive configuration and the area wise precision of tracing the properties as a foundation of the development of smart city planning united with the entire amenities and organization allied to the smart city agenda [2]. in [3], the authors’ put forward an approach that can be used for the computation of smart city indices. although, they choose heterogeneous indicators, include a vast amount of information. the paper is concerned with the calculation of allocated weights and the approach used here is based on fuzzy logic for the considered indicators. the authors'[4] presented the paper with a new concept of the u-eco-city into a check and concentrate on whether the u-eco-city is an astounding smart and sustainable city that represents an ultimate 21st-century city model or just a branding deception. eco-city proposal is the striving step of the 21st century. eco-cities are considered as zero-carbon, carbonneutral, low-carbon, ubiquitous-eco, and sustainable, highlight their position as per sustainability. this study focuses on ubiquitous-eco-city (u-eco-city). here in [5], the authors' discussed in detail the favourable circumstances using ict and considered it as a promising technology to lessen the use of energy in our cities. the authors' developed an analytical model in which the study of ict opportunities is pooled with a typology of domestic functions, i.e. all the daily activities that require energy. the energy that is required for domestic functions is evaluated with the help of a consumption-based point of view. this paper [6] proposes a theoretical agenda to study and examine two principal cases from the us and asia. the main objective of this paper is to focus on the progress in building an efficient smart city by amalgamating a variety of practical viewpoints with contemplation of smart city characteristics. here a model is developed to carry out case studies probing how smart cities were being put into practice in san francisco and seoul metropolitan city. the study's experimental outcome implies that efficient, sustainable smart cities appear under methods that are influential in which communal and economic sectors are brought together to coordinate their activities and resources on an open advanced policy. in [7], the authors' have developed a conceptual model that makes it simple to interpret how neighbouring administrations build up demand-side guidelines tools that inspire the growth and dispersal of sustainable-driven transformations that boost limited fiscal growth. the authors in [8] give a broad understanding of the idea of a smart city while elaborating the categorization of relevant application domains, like buildings, living, government, natural assets and liveliness, transportation and mobility, economy, and people. it also investigated the dispersal of smart proposals employing an experimental study meant for exploring the percentage of province enclosed by a city's paramount performance to the full potential domains of smart projects and accepting the function that various demographic, geographical, trade and industry and municipal variables may be affecting the arrangement move to build a smarter city. in this study, results disclose that the advancement patterns of a smart city are extremely dependent on its confined circumstances. in [9], current studied opus and currently programs for the sustainability and the conditions suitable for living in cities and monitored indicators that are required for effective monitoring. in this study, the development through indices was proposed through principal component analysis, and the real time data is used as an alternative of historical data as the essential information that one may build a set of indicators to elucidate the proposal. this article [10] summarizes and gives a detailed introduction regarding eco-town based urban-development implantation in the city north-western europe. the authors' emphasized the development of ecotowns and the rules and regulations, processes, and models with the help of which the eco-towns were started. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e3 shafqat ul ahsaan, ashish kumar mourya 4 in [11], the main focus is to find the role of innovative, intelligent urban machinery and tools in the developmental progress of smart cities. the authors put forward a comprehensive review regarding the applications of the smart city framework while coming across the emerging practices of ubiquitous eco-cities. this paper [12] highlights the differences in public transport among the two famous cities of the united kingdom like newcastle and southern brazil city florianopolis. the study made a comparison of models, measures for the progressive growth of florianopolis as a sustainability model in south america. hence, a detailed investigation of changes, models that were built and the similarities and differences have been verified to discover the behaviours that direct social and political process in the field of urban sustainability. this paper gives a proportional depiction of social and financially viable indicators like the gross domestic product (gdp) per capita, price increases, employment, as well as the historical population evolution of the two cities. within [13], the authors' performed a relative case-study of three asian cities like penghu in taiwan, seoul in south korea, and tianjin in china and revealed the special effects of multiple nationwide methods to eco-city progress. in their study, they have compared the asian cities with two european cities, freiburg (germany) and samso (denmark). the investigation makes out four transforming antecedents of the growth of an eco-city in asia, which are (1) the presence of a dedicated local public authority, (2) deployment of a countrywide approach and policy, (3) a combination of national potential, and (4) commerce activity the continuous engagement of local citizens. in [14], '16' sets of city measurement framework (8 smart-city and 8 municipal sustainability evaluation models) composed of '958' indicators in total by separating the indicators into three groups and 12 divisions. the paper put forward a comparison of modern technologies and smartness that must be implemented to make a city smart to urban sustainability frameworks. a common motive of smart cities is to improve sustainability with help of technologies. in this [15] paper, an indicator agenda for the estimation of low carbon city (lcc) was known from the viewpoint of energy pattern, societal and livelihood, economic, inner-city mobility, solid waste, carbon and environment, and water. a complete assessment scheme was engaged for lcc ranking utilizing the entropy weighting factor method. the standard standards for lcc documentation were also known. the model was practiced in 10 international cities to grade them according to their low-carbon levels. a comparative study was done at multiple points of trade and industry, societal, and green development improved the entire study. the outcome proved that stockholm, vancouver, and sydney position at the top level than the standard value, signifying these cities gained a grade value far above the ground in the emission of low-carbon growth. 4. iot based model for monitoring air quality the basic outline of the first model is drafted in figure 2. it is composed of several sensors, an arduino uno board, and raspberry pi 3. raspberry pi 3 is a convenient and alarming single board computer (sbc) that includes an arm processor and works on linux operating system. it is an adaptable system-on-chip (soc) panel that can be used for multiple purposes. in raspberry pi 3, bcm2837 chip is used which is based on 64-bit arm v7 quad-core processor and runs across operating systems like windows 10, ubuntu mate, and raspbian. the bcm2837 chip operates at a clock rate of 1.2 ghz and is employed using 1 gb of ram and 40 unmitigated gpio pins [16,17]. it provides internet access through bcm43143 wi-fi module. raspberry pi is the core component of the architecture that controls the system. the sensors are being installed at multiple locations within the vicinity for detecting the concentration of multiple gases like carbon dioxide, oxygen, nitrogen dioxide, ozone gas, etc. these gas sensors are linked to an arduino uno board which is connected to raspberry pi 3 via universal serial bus (usb) cable. the data captured by the detector/sensors is directly fed to raspberry pi 3 in communication with the arduino uno board to the cloud. the mq9, mq7, mq8, mg811, and mq135 gas sensors are analog sensors that measure the gas concentration in the region where they are being installed [18]. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e3 prognostic modelling for smart cities using smart agents and iot: a proposed solution for sustainable development 5 figure 2. air quality monitoring system 4.1 arduino uno board arduino uno is an inexpensive microcontroller chipboard based on atmega-32p that can be configured simply with raspberry pi and provides a very efficient analog to digital conversion (adc). arduino uno board has the feature like a usb interface, 14 digital i/0, 6 analog inputs primarily for reading analog sensors but can also be used as gpio pins, which allow interfacing with various other boards [19]. each of the digital pins is capable to perform input or output operations, using functions like pin mode to digital read and digital write. arduino uno microcontroller board can be programmed using a simple integrated development environment using c or c++. raspberry pi 3, model is enabled with wi-fi having double the performance power as compared to its existing generations. the proposed architecture makes use of lightweight message queuing telemetry transport (mqtt) protocol. the mqtt protocol smoothens the way of communication among sensors and clients. the data captured by the sensors are sent to the cloud through the internet and is accessible to clients. the data is visualized over the console by making use of device id [20]. 4.2 raspberry pi 3 raspberry pi 3 is a convenient and single board computer (sbc) that includes an arm processor and works on linux operating system. it is an adaptable system-on-chip (soc), multifunctioning board. in raspberry pi 3, bcm2837 chip is used which is based on 64-bit arm v7 quad-core processor and operates on software systems like windows 10, ubuntu mate, and raspbian. the chip operates at a clock rate of 1.2 ghz and is employed with 1 gb of ram and 40 unmitigated gpio pins. it provides internet access utilizing the bcm43143 wi-fi unit [18]. it is fixed with 4 usb ports,3.5 mm audio jack, 1 full high-definition multimedia interface (hdmi) port, 1 ethernet port, the display interface, and compound video camera interface. it provides a micro sd slot which allows the users to store software like operating systems and some necessary drivers. raspberry pi 3 has a permanent esp8266 wi-fi module that is appropriate for connecting wi-fi to the model through the uart serial connection. it is loaded with some exciting features like 802.11b/g/n protocol, wi-fi direct, and a consolidated tcp/ip protocol stack [19,20]. 4.3 sensing unit the sensing unit contains an adequate number of gas sensors implanted at different locations. there are different types of gas detecting sensors such as mq7, mq8, mq9, mg811, and mq135. these sensors are extremely sensitive to carbon dioxide, ozone, nitrogen dioxide, etc. mq135 is widely used for the finding of alcohol, co2, nh3, and smoke with the minimal response time. 4.4 software architecture it mainly consists of node-red and integrated development environment. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e3 6 node-red is a convenient, open-source, flow-based development tool for visual programming developed by ibm. it is widely used for iot based applications. it is a commonly used tool that allows iot developers to merge apis, hardware devices, and online services with ease. node-red is loaded with inbuilt libraries consisting of thousands of nodes and flows that permit the user to hook up all types of services and devices. a simple click mechanism is offered by the node-red to set up the flows by iot developers to a lightweight execution environment [21]. 4.4.1 integrated development environment arduino based programs can be compiled in any software processing language that is provided with a compiler for the translation of programming code into the machine understanding form. integrated development environment (ide) can run on any hardware or software platform forms the foundation for arduino [20]. it proves to be extremely influential for the people who are professionals in the field of project development, programmers, and researchers to build up different kinds of arduino based projects by making use of multiple types of sensors. arduino ide is software for which the source code is freely available, licensed to permit modifications and redistribution of its source code, created from the incorporated development environment for data manipulation [21]. as we know that ide is platform-independent, hence it can be executed on linux and windows-based operating systems. ide has some attractive features like a toolbar for common functions, a massage area, and a text console. the programming languages supported by arduino ide are c, c++ which can be used to write programs within ide. 5. proposed smart city architecture with iot by using mobile agent the second model that we have introduced based on mobile agent technology for enabling interoperability and world-wide intellect with intelligent stuff in the web of things as shown in figure 3, with assorted small, batteryoperated devices that consumes very less power where the systems spread across different systems that relate to each other from end-to-end and obligations. we consider the necessities to permit mobility operators in the iot against various contexts: the intelligent stuff, the mobility agent, and the arrangement. smart objects like iot devices are loaded with digital elements, such as detectors, transducers, and actuators in each place of the smart city. all of this electronic machinery should be identifiable and accessed as resources of the digital stuff. these actuators in the vicinity where they are installed route the captured information makes them capable to comprehend their circumstances and to enhance the way of decision making on the fly and hence promote better and intelligent decisions. smart stuff in the internet of things backing multiple interface models, like centralized communication, publish and subscribe messaging, eventdriven communication, and simulcast messages. digitalized stuff can participate in every condition and various networking techniques such as intranet work and internet-based communications across a disparate set of devices connected. smart peripherals in iot need to carry a lot of distributed training models: macro programming languages, code relocation, task offloading, cyber foraging, and virtual machines. shared resources digital objects keep their support and potential, which comprise captured and refined data, object's competence, and besides host-based resource agents. these sources can be utilized in cooperation with additional stuff and operators in their procedures. the mobile agents preserve their status, uncovered using smart objects. as the condition of the task is loosely coupled into a hardware piece of equipment, the status of the task is cacheable, and agents offer durability in connection with failures". the resource segment that is implanted in the vicinity states where the agent drifts across the system with the meticulous relocation guidelines given in the metadata section. we can make use of any relocation policy, for example, 1) the agent calls on every object scheduled in the neighboring source section only one time 2) the agent believes the neighboring source segment as a loop flowing among the devices, 3) the agent communicates with every object simultaneously 4) the neighboring source segment registers gateways or proxies, which allocates the agent to many distant smart objects. the relocation strategy can also be measured as a system resource. on every occasion the neighboring source part is mentioned, the smart objects depend on the information framework, like the network configuration warehouse for relocation directions. this mobile agent relocation process needs, at the lowest, that the agent is replicated in the host-based equipment and launch to the updated host, where the status is first reorganized by performing the compute-intensive task. then the host enrolls the agent into the system server or directory catalyst. at this point, the improved agent status is open to the elements of the system and further objects gain the right to use the updated status in the host that is not existing before. following the registration, an acceptance is sent to the earliest, which permits the host to delete the agent against its memory and set the previously used resources free. shafqat ul ahsaan, ashish kumar mourya eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e3 prognostic modelling for smart cities using smart agents and iot: a proposed solution for sustainable development 7 figure 3. mobile agents based proposed model with iot 6. conclusion smart city projects have been proven their importance for a high-tech living society. iot devices with a high-speed internet connection have been used in a smart city. in this work, we proposed two architectures one of them uses mobile agent-based technology to configure the internet of things in a smart city. the mobile agent technology is executed on a platform that is wholly distributed and fault-tolerant to make the whole concept stronger. the characteristics of decentralization and load distribution among different kinds of multi-source devices could interact with each other on a peer-to-peer system to provide the services to clients. these functionalities may include day-to-day tasks as controlling electronic appliances remotely and cleverly or navigating around a remote location. the proposed architectures also include execution of services using speech commands and speech to text prompts. our proposed architectures also find few major applications in a smart high-tech city situation where unknown people such as guests may use services without taking help from others. the proposed models may show to be scalable &robust and can accommodate to a big city. references [1] conference: bolívar, m. p. r. (2016, june). mapping dimensions of governance in smart cities: practitioners versus prior research. in proceedings of the 17th international digital government research conference on digital government research (pp. 312324). [2] journal: bunce, s. (2016). pursuing urban commons: politics and alliances in community land trust activism in east london. antipode, 48(1), 134-150. [3] journal: castelnovo, w., misuraca, g., &savoldelli, a. (2016). smart cities governance: the need for a holistic approach to assessing urban participatory policymaking. social science computer review, 34(6), 724-739. [4] conference: cocchia, a. (2014). smart and digital city: a systematic literature review. in smart city (pp. 13-43). springer, cham. [5] conference: marsh, j., molinari, f., & rizzo, f. (2016). human smart cities: a new vision for redesigning urban community and citizen’s life. in knowledge, information and creativity support systems: recent trends, advances and solutions (pp. 269-278). springer, cham. [6] journal: ismagilova e, hughes l, rana np, dwivedi yk. “security, privacy and risks within smart cities: literature review and development of a smart city eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e3 8 interaction framework” [published online ahead of print, 2020 jul 21]. inf syst front. 2020;1-22. doi:10.1007/s10796-020-10044-1 [7] journal: md. humayun kabir, an overview of the internet of things (iot) and iot security, research gate, june 2020. [8] conference: liesbet van zoonen, privacy concerns in smart cities, government information quarterly 33 (2016) 472–480 [9] journal: ali m a abuagoub,“iot security evolution: challenges and countermeasures review”, international journal of communication networks and information security (ijcnis) vol. 11, no. 3, december 2019 [10] journal: aditya tiwary, manish mahato, abhitesh chidar, mayank kumar chandrol, mayank shrivastava, mohit tripath, “internet of things (iot): research, architectures and applications”, international journal on future revolution in computer science & communication engineering, issn: 2454-4248 volume: 4 issue: 3 [11] conference: se-ra oh, young-gab kim, security requirements analysis for the iot, (2017) [12] book chapter: butt, talal &afzaal, muhammad, “security and privacy in smart cities: issues and current solutions”, (2019), 10.1007/978-3-03001659-3_37. [13] conference: is farahat, as tolba, mohamed elhoseny, waleed eladrosy, security in smart cities: models, applications, and challenges, springer (2019), pages 117-142 [14] conference: fadi al -turjman, hadizahmatkesh, ramiz shehroze; “an overview of security and privacy in smart cities' iot communications”,first published: 08 july 2019 [15] journal: barun, benjamin c. m. fung, farkhund iqbal, babar shah, “security and privacy challenges in smart citie” sustainable cities and society 39 (2018): 499-507. [16] website: “internet of things”. url: www.wikipedia.com. date of access:20/10/2020 [17] conference: kumar, s. and jasuja, a., 2017, may. air quality monitoring system based on iot using raspberry pi. in 2017 international conference on computing, communication and automation (iccca) (pp. 1341-1346). ieee. [18] conference: kiruthika, r. and umamakeswari, a., 2017, august. low-cost pollution control and air quality monitoring system using raspberry pi for internet of things. in 2017 international conference on energy, communication, data analytics and soft computing (icecds) (pp. 2319-2326). ieee. [19] journal: maksimović, m., vujović, v., davidović, n., milošević, v. and perišić, b., 2014. raspberry pi as internet of things hardware: performances and constraints. design issues, 3(8). [20] journal: vujović, v. and maksimović, m., 2015. raspberry pi as a sensor web node for home automation. computers & electrical engineering, 44, pp.153-171 [21] conference: nayyar, a. and puri, v., 2016, march. a review of arduino board's, lilypad's & arduino shields. in 2016 3rd international conference on computing for sustainable global development (indiacom) (pp. 1485-1492). ieee shafqat ul ahsaan, ashish kumar mourya eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e3 http://www.wikipedia.com/ transfer learning-based method for automated e-waste recycling in smart cities 1 transfer learning-based method for automated e-waste recycling in smart cities nermeen abou baker1,*, paul szabo-müller1 and uwe handmann1 1ruhr west university of applied sciences, lützowstr. 5, 46236 bottrop, germany abstract introduction: sorting a huge stream of waste accurately within a short period can be done with the support of digitalization, particularly artificial intelligence, instead of traditional methods. the overlap of artificial intelligence and circular economy can flourish many services in the environmental technology domain, in particular smart e-waste recycling, resulting in enabling circular smart cities. objectives: we analyse the growing need for automated e-waste recycling as an essential requirement to cope with the fast-growing e-waste stream and we shed the light on the impact of artificial intelligence in supporting the recycling process through smart classification of devices, where the smartphone is our case study. methods: our study applies transfer learning as a special technique of artificial intelligence by fine-tuning the output layers of alexnet as a pre-trained model and perform the implementation on a small-size dataset that contains 12 classes from 6 smartphone brands. results: we evaluate the performance of our model by tuning the learning rate, choosing the best optimizer, and augmenting the original dataset to avoid overfitting. we found that the optimizer of stochastic gradient descent with momentum and 3 𝑒𝑒−4 as a learning rate brings almost 98% model accuracy with generalization. conclusion: our study supports automated e-waste recycling in decreasing the error-rate of e-waste sorting and investigates the advantages of applying transfer learning as the best scenario to overcome the rising challenges. keywords: artificial intelligence, transfer learning, circular economy, automated e-waste recycling, smart cities. received on 19 march 2021, accepted on 12 april 2021, published on 16 april 2021 copyright © 2021 nermeen abou baker et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.16-4-2021.169337 1. introduction the enormous use of digitalization has a profound impact on every domain. many concerns are raised with the growth of urbanization, like pollution, traffic congestion, rising welfare costs, and last but not least growing waste streams. the concept of circular economy (ce) was primarily aimed to enhance the recovery of end-of-life of products lifecycle by optimal recycling them, reusing them as raw materials, reducing the need to extract new resources, and closing the product loop. smart cities have been suggested as a solution to tackle the aforementioned problems, driven by digitalization, and to promote a sustainable environment *corresponding author. email: nermeen.baker@hs-ruhrwest.de through ce. in line with this, we discuss the role of digitalization, particularly artificial intelligence (ai), in the environmental technology domain and investigate how automated electrical and electronic waste (or the so-called ewaste) recycling can support shifting towards a sustainable environment, thus achieving ce goals. to achieve them efficiently, the classification of waste can maximize the performance of the whole process. waste classification is a significant step for efficiently sorting and separating into different models and types. therefore, the need for smart sorting is growing to support smart recycling. the remainder of the paper is divided into the following sections: section 1 introduces our research motivation, the importance of automated e-waste recycling driven by digitalization, and to achieve sustainable smart cities. section eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e1 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ mailto:nermeen.baker@hs-ruhrwest.de nermeen abou baker et al. 2 2 reviews related work in automated waste classification. section 3 discusses the background on convolutional neural network (cnn) architecture. section 4 presents our method. section 5 is devoted to results and discussion and finally concludes our work. 1.1. research motivation in this article, we focus on adopting ai as a key technology for enabling automated e-waste recycling. one of the model services provided by the smart cities’ concepts is digitalization, and due to the fact of the proliferation of digitalization, we considered e-waste as a model example. ai can be involved in many areas in the e-waste management system like collection, classification, sorting, etc. the motivation behind this study is gaining benefits of more proper e-waste recycling by automation, tackling the growing rate of e-waste in smart cities, and highlighting the advances of ai for this purpose. ai and ce can fuel the initiatives on smart cities to offer sustainable opportunities. as per [1], the biggest motivations for ce are technology development, new socio-economic opportunities, awareness, and change of consumer mentalities to adopt more sustainable products. on the contrary, some constraints face this movement, like poor legislation, lack of data collection standard process, and poor public participation. these obstacles inhibit smart cities from moving towards ce as well. our argumentation is to emphasize the importance of ai to encourage the automated recycling of e-waste in the smart cities’ context by investigating the following aspects: • the need to reduce human intervention by adopting automation and reducing the need for labor. • gain the benefits from applying ai techniques, particularly transfer learning, like using a small-size dataset rather than creating a big dataset, which is one of the painful tasks when designing a neural network (nn), decreasing the burden of long computational time, getting a high accuracy in sorting compared to the human-based process. overall, our method supports reducing the error rate of e-waste sorting, and it is easier than building the nn from scratch. to illustrate how we prove our investigation, we introduce the flow of the proposed method by insisting on the need for automated e-waste recycling and the impact of digitalization, transfer learning particularly on this process, to achieve circular smart cities as shown in figure 1. figure 1. the flow of using transfer learning for automated e-waste recycling in smart cities 1.2. the need for automated e-waste recycling in the take-make-dispose paradigm or the so-called linear economy, the generation of waste has dramatically increased in the last few decades. to overcome this problem, ce has been mainly proposed to confirm the social and environmental aspects of sustainability. due to the great adoption of digitalization globally, e-waste is the fastest growing waste stream. this problem is one of the biggest challenges in reducing pollution, preserving valuable materials, and alleviating the toxicity and contamination of entering the eco-system. the organization for economic cooperation and development defined e-waste as “any appliance using electric power that is obsolete or has reached its end-of-life” [2]. the growing concern about informal e-waste recycling is alarming, especially on the improper way of processing in their final fate, like burning or melting them in acid baths and recovering only a few portions of valuable materials. general e-waste contains 60 different elements, like copper, aluminium, gold, platinum, and other metals represent 60% in e-waste, but 2.7% like cadmium, mercury, chromium are hazardous, and they will have poisonous and negative consequences on human health and the environment if they are not treated properly [3]. moreover, when these recyclable elements are not recovered, new raw materials have to be extracted, and it will end in a lack of resources and higher energy consumption. as per [3], many rare earth elements (rees) are in e-waste, like 30% for silver in switches, 12% for gold in integrated circuits, 30% for copper in cables and 19% for cobalt in rechargeable batteries, and 79% for indium in liquid-crystal display (lcds), compared to mine global production. the previous figures aligned with growing sales of electronic devices and short lifespans, emphasize the initiatives to find a smart solution and adapting ce strategies like recycling e-waste. many directives tried to create legislations to process ewaste management; for example, the eu’s waste electrical eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e1 transfer learning-based method for automated e-waste recycling in smart cities 3 and electronic equipment (weee) stipulated the design of electronic devices should respect the eco-design, is easy to dismantle and recovered, and the producers are entitled to the take-back programs. whereas in the us, the american ewaste recycling systems divided e-waste into ten categories based on the toxic substances, complexity, and profit from recycling [3]. the benefits of automated e-waste recycling, including a reduction in cost collection and complexity of e-waste processing, importing of raw materials, carbon dioxide (co2) emission, and negative impacts on environment and labour health, besides boosting continuity of resources are the reasons behind choosing the need for automation of recycling to enable ce [4]. 1.3. influence of digitalization on automated e-waste recycling digitalization, including the internet of things (iot), big data, and ai, has a major influence on many sectors and can also be applied within the waste management system, resulting in improving the recycling process in two folds: for producers by enabling them to use recyclable materials and better purchasing and sorting decisions, as well as for recyclers for better waste sourcing options [5]. consequently, these digital technologies act as catalysts to ce, but how can ai, in particular, mimic humans to create intelligent machines to solve such intricate problems? ai plays a vital role in enhancing existing recycling infrastructure, including improving data collection and data mining processes to obtain a higher quality level than the typical analysing approaches besides automated sorting (where our study focus) leads to higher accuracy and better waste segregation quality. e-waste collection can also be improved by advances of ai, particularly in optimizing the ewaste collection routes to maximize the mass and the number of collected waste, besides navigation and tracking capabilities, especially the e-waste by storing, processing, analysing, and optimizing the necessary information, which ultimately will increase the whole waste management efficiency [6]. the next step is sorting e-waste, which is a prerequisite for high-rate recycling. the partnership between ai and robotics is gradually being adopted by many waste management applications, like analysing the streams of images and predicting the patterns to support the sorting process, and extending the lifespan of electronics through predictive maintenance [7]. 1.4. circular smart cities we presented the term of circular smart cities in previous work [8], where the smart city paradigm could be linked to ce driven by the support of ai. the ce principles aligned with ai are expected to support the circular cities concept, and smart cities are consequently benefitting from implementing these developments [8]. creating sustainable and eco-friendly cities with the help of digital technologies to provide smarter, liveable, and durable services is proposed under the label smart city. the authors of [9], defined six characteristics of smart cities, which are: smart governance, smart mobility, smart living, smart people, smart economy, and smart environment. our argumentation incorporates the last two components by increasing sustainable chances when adopting contemporary technologies. on the other hand, the smart city concept may encounter some obstacles about the security and privacy issues, which drives much research to work on like, recognizing people’ faces [10, 11] to access restricted areas [8–10], improving traffic flows by partly autonomous drones and vehicles [12] [13], traffic management and smart tracking, assistance systems [14, 15], predictive maintenance [16, 17], and last but not least, smart waste management [18]. the switch to digitalization can broadly improve the whole process of the waste management system by including digital identity tags for the waste container (iot), digital order processing (ecommerce), digital payments, digital communication with customers (chatbots), and storing and connecting with governmental databases (cloud services), which leads to better insights of waste patters (ai). ai plays a fundamental role in supporting complicated services in many domains in the smart cities’ context, due to the rising focus on digitalization-oriented technologies. the authors of [19] pointed out that new business models could be implemented by coherently applying ai as a successful potential for smart cities. this technology is essential due to the massive datasets gathered by sensors since this data needs to feed the decision support applications that leverage ai [20]. while the huge amount of data is created by different means in smart cities context, it needs to be turned into insights. ai is the key solution to play this role, in a various range of applications like healthcare, education, security, transportation, and the environment. ai has proved its ability to intelligently process large amounts of collected data created by sensors and produce significant information from it, based on recognizing patterns and features [21]. cnn is the basic building block of ai, and it has a special feature of self-programming with minimum human intervention, which gives ai to primarily act as a unique factor to enable circular smart cities. further details about cnn architecture will be presented in section 3. 2. related work automated recycling becomes an indispensable process due to the huge amount of the produced waste and its increasing detrimental effects on the environment and human health. it provides many advantages also to the economy. one of the general classification models was introduced based on shapes, and dimensionality matching has been applied by [22]. it calculates the similarities and concurrencies of several shapes and uses the result to recognize the object. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e1 nermeen abou baker et al. 4 another classification method based on the reflectance properties of surfaces has been proposed by [23]. this method suggests an algorithm for estimation that learns correlations between surface reflectance and data enumerated from an observed image. a study conducted by [24], who used the bayesian framework with the help of the augmented latent dirichlet allocation (alda) model to classify images based on their materialistic properties like glass, metal, fabric, etc. this classifier reaches 44.6% accuracy by processing the surface of each image. also, the waste domain classification using ai has been conducted in previous research. using ai can be a very productive way to automate this process based on the collected images. a study by [25] used sensors in collaboration with machine learning algorithms to automatically sort waste based on textures and colours. [26] used cnn to identify waste in images. the study presented a smartphone application to enable the user to report a pile of waste and identify its location, with an accuracy rate of 87%. 3. background on cnn architecture ai is a type of machine learning that allows the machine to develop using pattern recognition. there are three categories of learning: supervised, unsupervised, and reinforcement learning [27]. our approach uses supervised learning to implement the classification using cnn, which is a nn that consists of layers as building blocks and uses the convolution operation in at least one of the layers, where the number of layers represents the depth of the network. if the number is large, the network will be called a deep neural network with many hidden layers. it can learn features directly from image data. cnn is used to train a dataset divided into a training set, which is a set of images that corresponds to predefined classes (or labels), and a validation set to estimate the performance of the model. cnn uses the training set as labelled inputoutput pairs and performs training based on learning given examples, then it predicts the appropriate output for a given input. in order to obtain a good prediction performance, the training methods need to optimize the weights of each neuron-connection and to calculate the results to become as close as the expected class. most of cnn contains the convolution, pooling, fully connected, and softmax layers as building blocks, and they are defined as follows: • cnn: the advantage of the convolutional layer, especially in classification, is that the kernel acts as a filter, sweeps the image in all directions, and catches the features by making the process shift-invariant. these filters are applied to each image to activate unique features (like edges, blobs, colours, brightness, etc.), then the output of each layer is used as an input to the consequent layer. • pooling layer: it is added usually between the consecutive convolutional layers. it simplifies the output by reducing the size of the matrices and gives a general look to the image, so the resulting matrix is smaller than the image matrix, but it contains the most prominent features. usually, maximum or average functions are used for pooling in popular cnn architectures [28]. • fully connected (fc) layer: it is the last layer in cnn, which is used to flatten the 2d spatial features into a 1d vector and perform the learning. • softmax layer calculates the probability for each label in the dataset as an output of the model. 4. method to put the previous concepts, namely ai, ce, and circular smart cities together in practice, we used the following technical aspects. deep learning usually requires being trained on a huge amount of data on neural networks. to design a cnn from scratch, the network architecture should be well-designed, including the number of layers, the number and specification of filters, besides tuning the training parameters like learning rate, optimizers, and activation functions. next, this network should be trained for a relatively long time on a huge dataset. a promising alternative to designing from scratch is using the transfer learning technique [29]. transfer learning uses previously learned knowledge from a source task and transfers them to the target task. it is a special ai technique that helps a system adapt to new circumstances that allow processing data, extracting features, and making predictions. pre-trained models are rich with feature representations because they were trained on a large number of images. our study uses transfer learning by freezing the transferred parameters from a pre-trained model, particularly alexnet that was introduced by [30], which classifies one million high-resolution images (imagenet) into one thousand labels. it is a deep convolutional neural network that consists of 650,000 neurons, 60 million parameters, and 630 million connections. its architecture consists of eight layers, including five convolutional layers, and three fully connected layers, besides three pooling operations, as shown in figure 3 for the original model. in standard alexnet architecture, the first two convolutional layers are followed by an overlapping max-pooling layer, the other three convolutional layers are connected directly, and the final convolutional layer is followed by a max-pooling layer. alexnet has been used extensively in the research due to its simple, and not-so-deep architecture. one of the main characteristics of alexnet is using rectified linear unit (relu) activation function that leads to faster training than other activation functions like sigmoid or tanh. it is an effective activation function that maps the negative values with zeros and maintains positive values. another advantage of using alexnet that it has a dropout layer. cnn has a huge number of parameters that can cause overfitting, which can be prevented by regulating the network to memorize them too much. practically, it can be implemented by randomly stopping the neuron’s contribution eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e1 transfer learning-based method for automated e-waste recycling in smart cities 5 in forward or backward propagation, leading to dropping the units with their connection during training [31]. for implementation, we created the dataset manually from the internet. it contains 650 rgb images. the computing environment was matlab r2020b with a deep learning toolbox was used for implementation installed on a laptop used windows 10 (64 bits) equipped with i5 processor, and requires matlab parallel computing toolbox with cuda (which is a parallel computing platform and programming model developed by nvidia for general computing on a graphics processing unit (gpu)) of asus nvidia geforce rtx 2070s 8gb for the acceleration of training process. the dataset consists of 12 smartphone models, a relatively small dataset, from 6 brands, namely acer, htc, huawei, apple, lg, and samsung. since most of the frontside of smartphones look similar recently, we collected images that focus on the backside where unique features like the logo, camera lenses are distinguished. the dataset is split into 80% for the training set and 20% for the validation set. figure 2 shows an example of a subset of the dataset. figure 2. example of a subset of the dataset we started by loading alexnet, replacing the last three layers to classify 12 labels, then training the network on our smartphone dataset, finally assessing the network on the validation set, and checking the performance. regarding the training options, we set the mini-batch size to 64, which represents the number of the subsets of the training set that are processed on gpu simultaneously. after the whole batch is sent to the network and the error of the batch is propagated backward into the weights, every weight in the network is being updated. higher values of batch-size lead to better convergence and higher accuracy. however, it is limited to the available memory of the gpu [25] full pass of training process over the entire training set uses mini-batches called one epoch. to control the early stop, we set the max epochs as 30, and the training set was shuffled before each epoch. in the beginning, the network was initialized with frozen pre-trained weights for all layers except the last three layers, as described in previous work [8]. the learnable weights of alexnet are frozen in the fully connected layer. to perform the fine-tuning, replacing this layer with a new fully connected layer has an output value equal to the number of classes in the new task. the details of the proposed implementation are presented in figure 3. 5. results and discussion after setting the layers configuration and the training options, the model is ready for prediction. evaluating the performance of the network is a challenging task and depends on the computational complexity. we performed three different experiments to choose the best parameters for our model with a baseline of data augmentation, optimizers, and learning rate. 5.1. baseline: data augmentation data augmentation is creating alternative copies of the original dataset by adding more images effortlessly, and it is mainly used to alleviate small-size datasets and overfitting problems. a significant factor that should be evaluated is a generalization. if there is a large distance between the training and validation accuracy, practically happens when the model is very complex for the available amount of the training set, and the model is not able to generalize, or the so-called overfitting. the following operations were applied to perform data augmentation, random x reflection, random y reflection, random x translation, random y translation, random x scale, random y scale, random x shear, random y shear, where the scale range is [0.9 1.1] and the translation and shear range is [-50 50] pixel. an example of our dataset augmentation can be seen in figure 4. as a result, each image is multiplied by 9 to get 5850 images in the dataset, including the original unchanged set. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e1 nermeen abou baker et al. 6 figure 3. the implementation diagram of the original alexnet architecture and the fine-tuned model 5.2. baseline: optimizers choosing the right optimizer can help to reach the global minima, reduce the loss function, and set up the correct parameters. the loss function is one of the most important metrics for testing the network performance, which represents the difference between the predicted output and the target class. to minimize the loss function, the gradient descent updates the weights and biases of the network by taking small steps at each iteration of the opposite direction of the gradient. to set the training options, we tested three popular optimizers. gradient descent considers the whole data at one time that leads to redundant and inefficient computation, but stochastic gradient descent (sgd) computes random selection or small subset instead. however, sgd may oscillate along the path of steepest descent towards the optimum, where the surface curves have more steeply on the dimension. the momentum alternatively helps to accelerate sgd towards the local minima and reduce oscillations. sgd with momentum, or sgdm, uses a single learning rate for all parameters, whereas rmsprop (which is a gradient-based optimization technique used in training neural networks) tries to improve the network performance by adapting learning rates by parameter to optimize the loss function [32]. in comparison, the adaptive learning rate optimization algorithm (adam) computes individual adaptive learning rates and momentum to converge faster. it uses an estimation of the first and second moments of the gradient to adapt the learning rate for each weight [33]. we performed seven learning trials and table 1 shows the accuracy range of each method. table 1. the accuracy mean and standard deviation of each method. implementations 3e-4 accuracy sgdm 98.3505 ± 2.0155 adam rmsprop 95.2577 ± 3.0427 93.1959 ± 3.8635 from the table, it is clearly noted that sgdm provides better performance compared to adam and rmsprop. this result also supports the study presented in [34], who conducted empirical research and stated that, although adam proves that it converges faster than other optimizers, it does not converge to the optimum solution and generalize well in classification as sgdm does. figure 4. example of used data augmentation eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e1 transfer learning-based method for automated e-waste recycling in smart cities 7 5.3. baseline: learning rate learning rate controls the speed of training, for a smaller learning rate the model could have higher accuracy, but it takes a longer time to train. one of the biggest challenges of gradient descent is choosing a proper learning rate. too small learning rates may dwindle around the minimum and get slow convergence and too large learning may cause unstable training process. transfer learning mostly uses a smaller learning rate since the learned weights have already significant optimization. performance comparison based on a variety of learning rates has also been conducted to choose the best option for the proposed model. figure 5 visualizes a box chart that represents the distribution of accuracies. the median accuracies per each box are drawn in the middle of the box, and the upper and lower quartiles are shown at the top and the bottom edges of the box, respectively. the whisker endpoints illustrate the lowest and highest accuracy. we tried to guess the learning rate by reducing the learning rate when the loss oscillates widely and keeps getting worse, whereas when the loss is slowly and consistently falling we increased the learning rate. figure 5. box chart of accuracy scores for different learning rates using sgdm optimizer from the box chart, it is clearly illustrated that the learning rate that corresponds to 3 𝑒𝑒−4 provides better performance compared to other learning rates. as shown in figure 6, a combination of setting the proposed data augmentation and sgdm optimizer with 3 𝑒𝑒−4 learning rate has the best model generalization performance and reaches almost 98% accuracy. figure 6. accuracy and loss function performance of our model 6. conclusion in a nutshell, our method underlines the important role of ai in shifting towards automated e-waste classification, hence supporting circular smart cities. by the example of aienhanced automatic smartphone classification, we showed that e-waste management could be significantly enhanced by using digital technologies that speed up the process. the suggested method supports two important decision factors in implementation, by reducing the error rate of e-waste sorting and it is easier to use transfer learning than building the nn from scratch. we tested the performance by the tuning learning rate and optimizer, besides performing data augmentation to avoid the overfitting and small-size dataset problems. however, our approach should not only be used as an endof-pipe technology, which may result, for example, in socalled rebound-effects. hence, it cannot replace the transition to a more sustainable economy and society, which requires dedicated efforts in the respective fields of action, such as new business models or user preferences. nevertheless, our approach and automated e-waste management, in general, could alleviate contemporary e-waste problems quickly and diminish cost effectively, which builds a basis for a more sustainable world in the future. automated e-waste classification is not the end of the story. therefore, we try to develop a (semi) automated e-waste management system in our circular digital economy lab (cdel) in order to get the full benefits from ce and digitalization, where we integrate our model with other systems such as robotics, iot, and data mining. acknowledgements this work has been funded by the ministry of economy, innovation, digitization, and energy of the state of north rhinewestphalia within the project prosperkolleg. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e1 nermeen abou baker et al. 8 references [1] b. esmaeilian, b. wang, k. lewis, f. duarte, c. ratti, and s. behdad, “the future of waste management in smart and sustainable cities: a review and concept paper,” waste management (new york, n.y.), vol. 81, pp. 177–195, 2018, doi: 10.1016/j.wasman.2018.09.047. 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[online]. available: http://arxiv.org/pdf/ 1705.08292v2 eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e1 predicting diabetes disease for healthy smart cities predicting diabetes disease for healthy smart cities hugo peixoto∗, vasco ramos, carolina marques and josé machado algoritmi center, university of minho, campus gualtar, braga 4710, portugal abstract introduction: diabetes is a chronic condition that affects a large portion of the population and is the leading cause of numerous health problems. its automatic detection could improve the communities’ overall well-being. objectives: the primary goal was to introduce advancements to the subject of healthy smart cities by studying an approach for predicting the occurrence of diabetes in the pima female adult population using data mining. methods: this study uses crisp-dm to analyze the results of six different models acquired from three different iterations of the same dataset. discussion: this study found that the most promising model is k-nn, which obtained results of almost 92% of f1 score with the third data preparation strategy. conclusion: acceptable results were achieved with the k-nn model and the third data preparation strategy, but more research into improving the data preparation processes and their influence on the outputs of each model is needed. received on 15 march 2022; accepted on 21 april 2022; published on 22 april 2022 keywords: data mining, diabetes, crisp-dm, classification, ml models, smart cities, smart health copyright © 2022 hugo peixoto et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eetsc.v6i18.589 1. introduction smart cities are designed with the goal of enhancing and providing a good quality of life for its residents by expanding urban infrastructure, encouraging innovation, and improving the healthcare system available to them, all while adhering to the values of equality, efficiency, and foresight [1, 2]. smart health is a prominent area of the smart city concept. with the covid-19 pandemics, the research and application of ehealth related topics have only increased in our society. a recent indepth report on smart cities published by deloitte [3], unveiled that key applications of smart health in smart cities vary from simplified processes for diagnosing diseases to streamlining their treatment, not to mention supporting well-being through early intervention and prevention using digital technologies. one of the key examples of this argument is a diabetes prevention program developed by the new york state department ∗corresponding author. tel: +351 253 604 430 ; fax: +351 253 604 471 ; email: hpeixoto@di.uminho.pt of health1, which allows participants to use virtual monitoring and interact with life coaches and other participants. as a result, it is evident that illness prevention and early and automatic detection, particularly of chronic diseases, is a critical application of academic research in smart cities with a massive impact on people’s lives. in this context, this paper is the evolution of a previously published work, in [4], to deepen the study previously conducted and explore improvement opportunities identified in that work. as such, building on what was already achieved, the main goal is to diversify the application of data mining techniques previously applied to identify the occurrence of diabetes illness on patients using a dataset from the pima female adult population, taking into consideration several factors. this article is divided into five sections in terms of content. the second section, background and related work, follows the introduction with a brief summary 1https://www.health.ny.gov/health_care/medicaid/redesign/ ndpp/index.htm 1 eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e1 https://creativecommons.org/licenses/by/4.0/ mailto:<hpeixoto@di.uminho.pt> https://www.health.ny.gov/health_care/medicaid/redesign/ndpp/index.htm https://www.health.ny.gov/health_care/medicaid/redesign/ndpp/index.htm hugo peixoto et al. of what is smart health and its role in the smart city concept, followed by an explanation on diabetic illness, and, lastly, earlier research and related work on the issue at hand. the third part, methodology, discusses the crisp-dm procedures in use, which include business and data comprehension, data preparation, modeling, and assessment. the analysis and discussion of both the attained outcomes and the underlying work that was necessary to reach those results are presented in section four. finally, the last part discusses the conclusions as well as future work and improvements on the current work. 2. background and related work 2.1. smart cities and smart health smart cities are a collection of technology techniques and mechanisms woven together by digital systems capable of collecting and analyzing massive amounts of data generated by a variety of sources, including low-cost sensors, mobile devices, and networks. all of this information is gathered and evaluated in order to develop intelligent and automated mechanisms that improve the overall quality of life for residents [5]. as such, the endeavor to transform current cities into smart ones can and will undoubtedly impact and disrupt different sectors, such as urban mobility, transportation, resources (water, power and heating energy, etc) and waste management, environment, politics and governance, economy and, of course, health and healthcare [6, 7]. smart health, as its parent concept, can also be seen as a complexion of different concepts, such as mobile health and electronic health. these concepts include every system and application that focuses on improving and streamlining the complexity of clinical processes, and illness treatment. the area more specific to smart health is the preparation and analysis of all the generated health data and use that data to extract relevant knowledge that is crucial to develop intelligent and, most importantly, automated processes such as early illness diagnosis and identification. this last effort of being able to achieve early, intelligent and automated illness diagnosis is being undertaken by a multitude of different research teams, on different illnesses, by the usage of machine learning and data mining techniques [8, 9]. 2.2. diabetes diabetes is a chronic disease that occurs when the pancreas fails to generate enough insulin2 or when the body’s own insulin is used ineffectively. uncontrolled 2insulin is a hormone that helps to keep blood sugar levels in check. diabetes leads to hyperglycemia, or high blood sugar, which over time causes catastrophic damage to many body systems, including neurons and blood vessels. it can cause problems in many areas of the body and increase the risk of early death in any form. kidney failure, amputation of a limb, vision loss, and nerve damage are all possible outcomes. adults with diabetes have a two to threefold increased risk of heart attacks and strokes. furthermore, untreated diabetes during pregnancy raises the risk of fetal mortality and other complications. finally, early detection is possible with relatively simple blood tests. this disease affects approximately 422 million people worldwide, the majority of whom live in lowand middle-income countries, and causes 1.6 million deaths each year. both the number of cases and the prevalence of diabetes have risen dramatically in recent decades [10]. 2.3. related work the practice of detecting patterns in data is known as data mining. in order to yield a benefit, the patterns detected must be relevant. useful patterns allow us to make nontrivial predictions on new data [11, 12]. in the health industry, content and structure began to change at a rapid pace as a result of computerized technology. the health services that are provided must be quick, accurate, and qualified, as well as satisfy the requirements. to attain these objectives, healthcare professionals must have the most up-todate and correct information, which they must employ as a meaningful aspect in their decision-making processes [13]. data mining, which allows for the extraction of relevant and valuable knowledge from vast amounts of data, provides for effective use of healthcare data. data mining is utilized in healthcare to assist doctors detect and forecast various ailments [14–16]. furthermore, the use of data-mining techniques aids in the creation of a streamlined pipeline that includes all relevant phases of this type of work (data analysis, preparation, model development and application, results evaluation, and deployment) and simplifies the review, improvement, and comparison process [17, 18]. in [19], the study suggested to identify and categorize the existence of diabetes illnesses by using data mining approaches. there were 520 instances in the dataset, each with 17 characteristics. the dataset was used to test seven different classification algorithms, including bayes network, nave bayes, j48, random tree, random forest, k-nn, and svm. according to the obtained results, k-nn had the maximum accuracy of 98.07%, making it the best approach for identifying and classifying diabetic illnesses on the examined 2 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e1 predicting diabetes disease for healthy smart cities dataset. this work also discussed methods to clean and supplement data, both in terms of amount and quality. for predicting type 2 diabetes mellitus (t2dm), the study in [20] developed a hybrid prediction model consisting of two separate algorithms: the modified kmeans algorithm and the logistic regression algorithm, both of which were based on data mining techniques. the key issues that needed to be addressed were improving the prediction model’s accuracy and making the model adaptable to other datasets. previous research have produced models based on the same assumption as the one used in this work, therefore the purpose was to compare the results of this study to those of the other studies. the dataset utilized in this investigation was the same as that used in the previous one (the pima indians diabetes dataset). when the acquired findings were compared to the results of the previously stated research, it was discovered that the model had a 3.04% greater prediction accuracy (approximately 94%) than the ones used for comparison. furthermore, the model guaranteed that the dataset is of appropriate quality. as a result, the model has been demonstrated to be beneficial in the actual management of diabetic health. 3. methodology the data used in this work was originally provided by the national institute of diabetes and digestive and kidney diseases, and has the purpose of diagnostically predict whether or not a patient has diabetes, based on some diagnostic measurements and medical indicators. the dataset is available at kaggle3. in respect to data mining, this project will use the cross industry standard process for data mining (crisp-dm) methodology, which is a six-phase hierarchical and iterative process model that accurately covers the data science life cycle. business understanding, data understanding, data preparation, modeling, evaluation, and deployment are the six phases [21, 22]. this methodology was chosen because of its numerous benefits, including standardization of applied processes, which makes the entire approach easily replicable, clear evaluation metrics and methods, a clear structure of what to study and analyze, which increases the chances of success, and finally, the ability to apply data mining models in real-world scenarios [23]. 3.1. business understanding the purpose of this study, as stated earlier, is to diagnostically predict whether or not a patient has diabetes, considering characteristics such as insulin 3https://www.kaggle.com/uciml/pima-indians-diabetes-database level, plasma glucose concentration, blood pressure, skin thickness, among others. it is also relevant to point out that this study is focused on a very specific population: all patients are females, at least 21 years old, of pima indian heritage. 3.2. data understanding as previously indicated, the dataset used in this study contains data on pima indian women aged 21 and above. it has 768 instances, each with eight characteristics and one extra column containing the respective class. • pregnancies: number of times pregnant; • glucose: plasma glucose concentration a 2 hours in an oral glucose tolerance test; • blood pressure: diastolic blood pressure (mm/hg); • skin thickness: triceps skin fold thickness (mm); • insulin: 2-hour serum insulin (mu u/ml); • bmi: body mass index (weight_in_kg/(height_in_m)2); • dpf: diabetes pedigree function; • age: age (in years); • outcome: class variable that specifies if tested positive for diabetes (0 or 1): 0 if yes, 1 if no. to better understand each attribute, it was created the table 1. it displays the amount of missing values, as well as the lowest and maximum values, and the average and standard deviation for each property. the class variable outcome has two possible values: yes or no. figure 1 depicts the data distribution for the outcome class, which contains 268 occurrences of yes (34.9%) and 500 instances of no (65.1%), indicating that almost 35% of the patients tested positive for diabetes while the other cases did not. figure 1 clearly illustrates that the distribution of cases throughout the class outcome is skewed, with a large majority of the occurrences classed as no. the ml models will have poor prediction accuracy if the data is uneven or biased, particularly for the minority class. furthermore, a feature analysis was also conducted in order to understand which features have the greatest and least weight in determining whether or not the individual has diabetes, through a correlation matrix between the different attributes. figure 2 presents the obtained correlation matrix. as it can be seen, the least relevant features are insulin and skin thickness, as they present very low 3 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e1 https://www.kaggle.com/uciml/pima-indians-diabetes-database hugo peixoto et al. table 1. attribute description attribute missing values min max avg std. dev. pregnancies 0 0 17 3.9 3.4 glucose 5 0 199 121 32.0 blood pressure 35 0 122 69.1 19.4 skin thickness 227 0 99 20.5 16.0 insulin 374 0 846 79.8 115.2 bmi 11 0 67.1 32.0 7.9 dpf 0 0.1 3.4 0.5 0.3 age 0 21 81 33.2 11.8 figure 1. distribution of outcome (class) correlation values for the outcome class compared to the other attributes and, in absolute values, almost null since their correlation factors are below 0.1 (0.066 and 0.09, respectively). on the other hand, it is possible to perceive that bmi and glucose are the two most important features for predicting the outcome class, with glucose being the most relevant since its correlation factor is the highest (0.48) and with a significant lead over bmi (0.31). 3.3. data preparation first strategy. in order to have a starting point with few modifications to understand the potential of the dataset in a nearly unmodified state, while also serving as a basis for comparing the results of subsequent strategies and corresponding improvements to the results, the first strategy of data preparation was defined as a twostep process. figure 2. correlation matrix first, the mapping of all missing values, which were described as zeros, to nan values so that the models would not fail because of non expected data. second, normalizing the data to values between 0 and 1. other than that, no further transformation operations were performed, nor were any originally available attributes removed. second strategy. since the first strategy was simply to establish a baseline of comparison and evaluation, the second data preparation strategy involved adding further transformations to the dataset to improve its potential for success once it is used to train the ml models. thus, the previous steps of mapping the missing values and normalizing the data were retained and supplemented with the removal of all instances with missing values and the removal of identified outliers once the normalization process was complete. it was also taken into account the skewness of the dataset, which was addressed by applying replication techniques to the existing data to increase the number of instances associated with the presence of diabetes and to balance the proportion of positive and negative instances for the diabetes test. finally, the last step was to shuffle the obtained dataset to introduce randomization in the process. third strategy. since the second strategy was more focused on achieving high prediction results, the obtained dataset was not truly representative of the problem and therefore not reliable. thus, it was decided to develop a third data preparation strategy more focused on producing a credible and representative dataset, taking into account the possible degradation of the results. 4 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e1 predicting diabetes disease for healthy smart cities the second strategy took the approach of removing all instances with missing values, alternatively this strategy took the approach of removing only the attribute with the most missing values. in the dataset, there were two main attributes with missing values: insulin with 374 instances (49% of all instances) and skin thickness with 227 instances (29% of all instances). these were also the attributes identified as the least relevant features for predicting the occurrence of diabetes, which reinforced the option of removing at least one of them. removing both columns would significantly reduce the number of attributes (there would be only six) and the dataset itself, resulting in a poorer and more error-prone dataset. therefore, in order to compromise and maintain the maximum number of instances while discarding much of the missing values, it was decided to remove only one of these two attributes: insulin, which, as mentioned earlier, had the highest percentage of missing values and lowest correlation factor. from this point on, the same steps as in the second strategy were followed, i.e., normalization, identification and removal of outliers, oversampling to correct the data imbalance, and data shuffling. finally, it should be noted that in both the second and third strategies, the final dataset comprised about 1250 instances, with a similar distribution of the outcome class (the obtained datasets are balanced). 3.4. modeling in this phase, the goal was to find and select the best machine learning models, keeping in mind that this is a classification problem. as a result, considering [24], six different machine learning techniques were selected: logistic regression (lr), naive bayes (nb), support vector machine (svm), random forest (rf), gradient boosted trees (gbt), and k-nn, with k = 10. in addition to the models to be used, the technique for training and evaluating each of the selected ml models was also selected. to begin, the dataset was divided into two subsets: 70% of the dataset was used to train the machine learning model, while the remaining 30% was used to test the model. the cross-validation technique was used to train the machine learning model with 50 folds. then, the model was evaluated with the testing dataset, yielding the evaluation metrics. after several tests, the number of folds for cross-validation was determined by choosing the value that provided the best overall results while meeting the requirement of not promoting overfitting or under-fitting phenomena. the implementation of the stated strategy, on rapidminer, is shown in figure 3. figure 3 shows the implementation of the specified strategy, on rapidminer. figure 3. base modeling approach 3.5. evaluation being the problem at hand a classification one, it was decided not to use accuracy alone as the performance measure, since this would be misleading. instead, the combination of accuracy, precision, recall, and f1 score was used to compare the models [25]. to clarify these concepts: • accuracy the ratio of correctly predicted examples to the total examples. • precision the ratio of correctly classified positive examples to all examples classified as positive. • recall actual positive rate of all positive examples, i.e. the proportion of correctly classified examples. • f1 score weighted average of precision and recall. these concepts have mathematical representations, as follows: • p recision = t p t p+fp • recall = t p t p+fn • f1score = 2 ∗ recall∗p recision recall+p recision in addition, the results presented below were calculated as the average of three different executions for each ml model. first strategy. the evaluation process began with the dataset that resulted from the first data preparation strategy. the table 2 summarizes the achieved results for each machine learning model. as it is possible to perceive the dataset in its almost natural state does not produce good results, since every model fell short of reaching the minimum level of 75% in every metric, for the exception of the k-nn model that was able to achieve approximately 75% of accuracy and precision. furthermore, all models achieved virtually the same results, proving that in most cases the quality of the dataset impacts directly the results, despite the selected model and that a poor dataset, both in quality and size, can undermine 5 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e1 hugo peixoto et al. table 2. testing results (first strategy) ml model accuracy (%) precision (%) recall (%) f1 score (%) lr 72.10 74.02 69.35 71.61 nb 73.75 71.88 71.38 71.63 rf 73.58 71.07 69.34 70.17 svm 71.89 73.05 69.38 70.18 gbt 69.21 70.55 66.63 68.53 k-nn 75.33 75.15 73.83 74.48 the entire data-mining process, meaning the data preparation phase is one of extremely importance to the whole process. second strategy. the next step was to train and test the models with the dataset that resulted from the second data preparation strategy. the table 3 shows an overview of the results of each model for that dataset. table 3. testing results (second strategy) ml model accuracy (%) precision (%) recall (%) f1 score (%) lr 77.98 79.11 75.49 77.26 nb 77.31 77.85 78.57 78.21 rf 93.72 94.14 93.32 93.72 svm 94.59 98.00 91.97 94.89 gbt 96.45 96.47 96.88 96.67 k-nn 98.06 97.26 98.01 97.71 the first thing clearly noticeable in the results presented in the table 3 is the big improvement of the results when compared to the results obtained with the first dataset, specially since the applied models are the same. with this strategy it was also possible to understand what models were more appropriate to the problem at hand, given some of them performed better than the other, which hadn’t happening in the previous case. as it can be seen in table 3, both the logistic regression and naive bayes models were the ones that originated poorest results in every metric of evaluation, which is a clear indication that these models are not the most suitable to the prediction and classification at hand. the remaining four models: rf, svm, gbt and knn produced far better results, being the k-nn model the one with highest overall performance with an f1 score of almost 98%. third strategy. finally, the models were trained and tested with the dataset from the third data preparation strategy, given that the latter describes the problem more accurately. the table 4 summarizes the obtained results for each model. table 4. testing results (third strategy) ml model accuracy (%) precision (%) recall (%) f1 score (%) lr 76.55 75.48 75.97 75.73 nb 73.46 73.23 73.61 73.42 rf 85.83 86.79 87.68 87.23 svm 73.77 97.91 75.40 85.20 gbt 87.39 88.14 87.99 88.06 k-nn 91.14 92.02 91.36 91.69 as was the case with the second dataset, these are also much better results than those obtained with the dataset from the first data preparation strategy, despite being considerably worse than the results from the second strategy. these two observations are not without reason and were quite predictable. since the second and third strategies built on the data preparation executed on the first strategy and added more transformations to further improve the quality of the data it is understandable the results from these two resulting datasets are better than the results from the dataset from the first strategy. on the other hand, the second data preparation strategy had its core focus on improving as much as possible the dataset to achieve high evaluation results, whereas the third strategy tried to create a compromise between a dataset that would produce good results but that would also faithfully represent the problem and context in question, something the second dataset fails considerably. analyzing the table 4, it can be seen that the overall performance of the lr, nb and svm was worst than the rf, gbt and k-nn models. similarly, the k-nn model showed itself as the most suitable for the problem at hand, with an accuracy of 91%, precision and recall of 91.4% and, more importantly, with a f1 score of 92%. 4. discussion this section will address and discuss the overall strategies applied during the execution of the present work and, also, the achieved results. the first thing worth pointing out is the dataset itself and the goal of this work, which is to contribute to smarter and efficient cities and societies with regard to its health by providing a proposal on a model to 6 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e1 predicting diabetes disease for healthy smart cities automatically identify the occurrence of diabetes in a person. the dataset used is very focused and particular to females from the pima population. however, the findings and advances presented in this paper can be extrapolated and replicated with other datasets that contain a broader diversity of population, reinforcing the relevance and applicability of what was developed in the course of this work. early on in the data analysis process, it became clear that the dataset was skewed, implying that there was a higher weight of instances on a class (in this case, the instances classified as no), jeopardizing the applicability of machine learning models, which would result in poorer predictive performance. the initial data preparation method did not address this issue on purpose to establish the earlier assumption that skewed data would result in worse models and that it was a problem that needed to be addressed. three datasets were produced with different data preparation strategies and core goals. the first strategy aimed to transform the original dataset as little as possible to create a baseline of results to compare with and to highlight the problems of the dataset and their effect on the results achieved by the machine learning models. the second strategy was created so that the best results could be obtained when different models were used, however it turned out to be unrepresentative of the situation since the data was multiplied several times to balance the dataset and provide the greatest possible performance. as a result, models that were theoretically good (with strong metrics in both training and testing, due to the dataset containing too many repeated examples) but had no real application in the situation were created. because it was deemed insufficient, while producing good results, a third strategy was devised with the goal of striking a balance between good outcomes and accurate portrayal of the problem. the models in this third strategy did not perform as well as those in the second strategy, but they were more suited to the problem, and, therefore, the third data preparation strategy it was chosen as the final approach. when modeling, six distinct models were used: lr, nb, rf, svm, gbt, and k-nn, with 70 percent of the dataset being used for training and the remaining 30 percent for testing. a cross-validation approach was employed to train the model, and then the model was tested. this technique ensures that procedures are consistent and coherent throughout various tests and executions, allowing for more confidence in the capacity to compare findings and recreate the specified circumstances in subsequent iterations. when evaluating the first strategy, it was noticeably that all models performed poorly no matter how good or sophisticated the model was, meaning the dataset was the problem and that it needed further improvement and transformation in order to achieve good results. in regard to the second strategy’s evaluation, it was evident that the overall performance metrics were acceptable when utilizing rf, svm, gbt, and k-nn, as they had an f1 score superior to 90%. lr and nb were not considered suitable given the achieved values were around 77%. since k-nn achieved f1 score values of around 98%, it was thought to be the best model for this particular strategy. in the final strategy, nb and lr presented the worst performance with 73% and 76% of f1 score, respectively, followed by the svm with an f1 score of roughly 85%. rf and gbt had similar results but gbt had an overall improvement, having an f1 score of 87% and 88%, respectively. with a f1 score of around 92%, the k-nn model proved itself as the most suitable to the given problem and dataset. finally, it is worth evaluating the whole research process through a swot analysis, i.e., the main strengths, weaknesses, opportunities and threats in this study. strengths. one of the major strengths of this work is the used methodology and approach that, as previously stated, provides consistency and coherence, meaning it is reliable and easy to replicate, as well as provides confidence in the achieved results. weaknesses. the dataset’s low representation of the global population and the ability to predict false positives can be seen as drawbacks to the effective evaluation of this work. opportunities. this study has the potential to solve a global problem by predicting the occurrence of diabetes disease in each and every individual, which, if detected early, could save many lives. although only the female pima population was used in this dataset, it can be scaled to other women around the world. with the increase of developments in this field, this study can contribute to healthy smarter cities. threats. the most serious threat discovered was the unbalanced and poorly-representative data. this can lead to difficulties in fully describing the problem in a more global approach. 5. conclusions and future work the goal of this research was to contribute to the scientific progress of smart cities, particularly smart health, by developing a model capable of predicting whether or not a person, specifically a pima indian woman, has diabetes. given the dataset, the k-nn model using the third strategy of data preparation produced satisfactory results while preserving an accurate depiction of the problem, with an overall 7 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e1 hugo peixoto et al. performance of 92% for accuracy, precision, recall, and f1 score. the dataset presented the most significant challenges in developing a successful model: it had many more non-diabetic cases than diabetes patients, as well as a substantial number of missing variables. furthermore, the results although based on a highly specific dataset are a substantial indicator of the reasonableness of a faster, smarter diabetes diagnostic with the help of data mining processes and techniques, which will positively contribute to earlier diagnosis, resulting in an improvement of the lives of the population affected by this disease. finally, the work more prone to future improvement is the research and experimentation of more complex and sophisticated oversampling techniques to produce synthetic data instead of replicating the existing data and the a thorough study on how the obtained knn model behaves with other datasets that represent the same problem, i.e., instead of focusing on a small group of people, diabetes occurrence is identified and classified across the entire population, or at least a more general population. acknowledgement. this work is funded by “fct—fundação para a ciência e tecnologia” within the r&d units project scope: uidb/00319/2020. the grant of vasco ramos is supported by the project “integrated and innovative solutions for the well-being of 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(2015) a review on evaluation metrics for data classification evaluations. international journal of data mining & knowledge management process 5(2): 01– 11. doi:10.5121/ijdkp.2015.5201. 9 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e1 https://doi.org/10.1109/ismsit50672.2020.9254720 https://doi.org/10.1016/j.imu.2017.12.006 https://inseaddataanalytics.github.io/inseadanalytics/crisp_dm.pdf https://inseaddataanalytics.github.io/inseadanalytics/crisp_dm.pdf https://doi.org/10.1016/j.procs.2021.01.199 https://doi.org/10.5121/ijdkp.2015.5201 1 introduction 2 background and related work 2.1 smart cities and smart health 2.2 diabetes 2.3 related work 3 methodology 3.1 business understanding 3.2 data understanding 3.3 data preparation first strategy second strategy third strategy 3.4 modeling 3.5 evaluation first strategy second strategy third strategy 4 discussion strengths weaknesses opportunities threats 5 conclusions and future work secured authentication systems for internet of things 1 secured authentication systems for internet of things gowtham m1,*, m. k. banga2 and mallanagouda patil2 1research scholar, department of computer science and engineering, nie institute of technology, mysuru & dayananda sagar university, bangalore, karnataka, india 2department of computer science and engineering, dayananda sagar university, bangalore, karnataka, india abstract introduction: in these days, an enormous extent of contraptions are interconnected with the remote advances which gave the principal light to the front line development of internet of things (iot). different quick contraptions and machines are by and by watched and controlled using iot conventions. the developments of iot are by and by spread to the entire sphere by which there is superb system in the devices related using iot. from the assessment reports of statista.com, the closeout of splendid home contraptions raised from 1.2 billion dollars to 4.4 billion dollars from year 2015 to year 2019 in the united states. as indicated by the report from economics times, there will connect with more than 2 billion units of esim based contraptions by year 2024. with the use of esim, the endorsers can use the progressed sim card for the astute contraptions and the organizations can be activated without need of the physical sim card. it is one of the progressing and confirmed employments of internet of things (iot). objectives: the presented research manuscript is presenting an outline of the present state of iot security. methods: past the standard applications, iot is under research for the earth watching and prior notification to the coordinating workplaces so the fitting moves can be made. as per the news report by grand view research inc., the overall iot marketplace size is shown to contact more than 5,000 million dollars by year 2025. the presented iot suggests the radio advancement standard with lpwan so the enormous consideration of sharp devices should be conceivable with more significant level of execution in the system. results: the key positive of the paper integrates the evaluation of internet of things with the assorted dimensions in addition to the cavernous analytics with the implementation aspects towards the security mechanism. the paper is having the focus and goals towards the association of security aware mechanism for the cumulative performance of iot based environment. conclusion: with the gigantic utilization of iot, there is have to incorporate the higher level of security and honesty for the protection mindful system condition. keywords: internet of things, iot, security mechanisms, secured iot environment received on 09 march 2020, accepted on 08 april 2020, published on 21 april 2020 copyright © 2020 gowtham m et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.163998 *corresponding author. email: gouthamgouda@gmail.com 1. introduction internet of things (iot) is an imaginative worldview moving toward the two businesses and people each day life [1]. it implies the organized interconnection of reliably dissents, which are furnished with inescapable learning. it not simply targets extending the ubiquity of the internet, yet also at driving towards an especially spread arrangement of contraptions talking with individuals similarly likewise with various devices. because of snappy advances in fundamental eai endorsed transactions on smart cities review article eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e3 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ mailto:%20gouthamgouda@gmail.com gowtham m, m. k. banga and mallanagouda patil 2 developments, iot is opening significant open entryways for innumerable novel applications that assurance to improve the idea of human's lives, empowering the exchanging of organizations. internet of things (iot) [2, 3] is the eventual fate of all the present-day gadgets around the world. giving them internet network makes iot the following outskirts of innovation [4, 5]. conceivable outcomes are boundless as the gadgets convey and connect with one another which make it considerably additionally fascinating for the worldwide markets [6]. for instance, rolls-royce declared that it would utilize the microsoft azure iot suite and furthermore the intelligence suite of cortana to monitor the fuel use, for execution examination, to streamline the fly courses and so forth which improves the aircraft effectiveness. the gadgets must speak with one another, information from these gadgets must be gathered by the servers, and the information is then dissected or given to the individuals [7, 8, 9]. fig. 1. smart city as classical scenario of iot the paper is having key focus on the security mechanisms with the cryptography based approaches in addition to the advanced security aware approaches for iot environment. the usage patterns and implementations with the blockchain in iot can elevate the performance and security [10, 11] of iot environment and it integrated in this work as the goal. 2. attack categorization according to iot architecture there exist different types of architectural models of iot, but predominantly the iot architecture is considered to have four layers, as shown in fig. 1. table 1 depicts a snippet of the different security issues at the different layers of iot system [12, 13]. table 1. security and layered aspects security concerns applicatio n & interface layer servic e suppo rt layer network layer device layer insecure web interface yes yes yes insufficie nt authentic ation/auth orization yes yes yes yes insecure network services yes yes lack of transport encryptio n yes yes privacy concerns yes yes yes insecure cloud interface yes insecure mobile interface yes yes yes insecure security configura tion yes yes yes insecure software/f irmware yes yes poor physical security yes yes 2.1. security threats at the sensing/perception layer to implement security features with iot it is recommended to embed security systems onto the device itself and hence the devices should have ability to accommodate and maintain authenticity. the devices must also have the ability to avoid any breach of access to preserve security of the stored data. iot security systems must ensure strict prevention of the unauthorized access while assuring flexible inter-operability amongst other devices in ad hoc network condition [13, 14]. 2.2. other threats and issues there can be a huge probability that the assailants may need specialized information and in this way decimate gadgets and since the fenced in areas for gadgets are not eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e3 secured authentication systems for internet of things 3 carefully designed they can be opened up effectively and their equipment can be gotten to by means of tests and stick headers [15, 16]. subsequently, to guarantee physical security, it is inescapable that the iot gadgets be made alter opposition making it hard to get the delicate data, for example, individual information, cryptographic keys or qualifications and so on. there have been accounted for certain situations when the iot gadgets were not possibly solid to shield their code and information from outside access which in the long run makes the assailant to clone whole gadget or control the product or information. maybe a couple of the models are the physical security assault when several brilliant traffic light gadgets were harmed by hoodlums who took the sim cards of gadgets [17, 18]. those sim cards were later used to make cell phone brings in south africa alongside a few vehicle crashes at the area and an extra cost to fix the whole framework. lately, numerous instances of cloning debit and credit card has come into light where absence of physical security came about into colossal money related misfortunes [19, 20, 21]. node capture: it has been recently referenced that in spite of the assaults on physical security, an assailant can extricate the data from the gadgets without pulverizing it [22]. sinkhole attack: such assaults are seen in the networks when sensors are left unattended for long lengths. during the sinkhole attack, the traded off hub removes the data from the entire closures by the nodes [23]. selective forwarding attack: in some cases the malicious nodes may pick information packets and drop them out, inevitably performing selective filtering for example sifting the specific packets while conveying the rest, independent of the way that dropped packets [24, 25] may convey some sensitive data. witch attack: the event of this sort of assault is basic if there should be an occurrence of disappointment of a genuine node and a pernicious node exploiting it, since the disappointment of authentic node occupies the accurate connection and enables it to make all its future communications [26, 27] with the malignant hub and hence prompting information misfortune. hello flood attacks: during such assaults a pernicious node starts a hello flood assault by sending hello message to all the neighbouring node and after that effects their accessibility. these attacks can cause non accessibility of assets to genuine clients by circulating countless gibberish solicitations to a specific help [27, 28]. security threats at the network and service support layers the service support layer spoke to in the figure 1 delineates the iot the executives framework and encourages on boarding gadgets and clients, applying strategies and leads and arranging computerization crosswise over gadgets. the most basic assignments performed at this layer are job based access control to deal with the character of client and gadget and the activities they are approved to perform. further so as to accomplish non-renouncement, it is of central criticalness to keep up a review trail of changes performed by every client and gadget so it is difficult to invalidate moves made in the framework [29]. this observing could be useful in recognizing the assaulted gadgets in the event of recognition of any anomalous conduct. a piece of the assaults at the network and service support layer has been given in the consequent area. man-in-the-middle (mitm) attack: man-in-themiddle assault is a case of the listening stealthily conceivable in the iot. as gadget confirmation includes trade of gadget personalities, data fraud is conceivable because of man-in-the-middle attack. replay attack: during the trading of character related data or different other credentials in iot this information can be parody, adjusted or replayed. replay assault is basically a type of dynamic man-in-the-middle attack. denial of service attack: as the iot gadgets in iot are resource compelled, they are powerless against asset use attack. attackers can send messages or demands [30] to a particular gadget to expend its resources. fig. 2. different layers of iot model table 2. possible attacks layers types of attacks perception layer jammers, replay attacks, sybil, selective forwarding, synchronization attack. passive interference, active jamming of temporarily disabling the device, replay attacks. network layer sinkhole, unfairness, false routing, hello and session flooding, eavesdropping, cloning, spoofing, impersonation, and network protocol attacks. eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e3 gowtham m, m. k. banga and mallanagouda patil 4 application layer injection, buffer overflows, unauthorized tag reading and modification. the current manuscript will study the current flow improvement of iot security inquire about and table 2 gives the possible attacks in the iot ecosystems. troubles in smearing security parts in iot and its ambush courses will in like manner be discussed. when contrasted with different overviews, this paper discoveries the flow iot verification security systems in the exploration. different segments of the displayed original copy are partitioned as pursues. segment ii examines the related work, segment iii issues recognized by review, segment iv suggestions for reinforcing the security instruments in iot and conclusion of the general research is displayed in segment v, and the references utilized in this paper are given toward the finish of the composition. 3. attack categorization according to iot architecture in this segment, we briefly deliberate the current access control, user access control, and intrusion detection and prevention schemes proposed in the literature for wsns. we at that point underline in detail on the client verification issue in wsns in light of the fact that it will be the principle dialog of this original copy. the taxonomy of security issues at different layers, table 1 it is noticed that user authentications, access control, user access control, and intrusion detection and prevention are the primary security issues in the iot ecosystem. shin et al. [31] focused on confirmed key understanding plan for secure communication among clients and iot gadgets, where a two-factor validation model was created. authors have tried; be that as it may, the key issues like stolen smart card or smart card loss attack (scla), offline password speculating as well as recovery utilizing brute force assault which are normal nowadays couldn't be tended to by authors and because of its higher computational and correspondence cost, the suggested approval plan may not relevant to run of the typical sensor nodes. wazidet al. [32] built up a secure user authenticated key management protocol for generic iot networks. the authors focused on planning another lightweight multifaceted remote client verification conspire for hierarchical iot network (hiotn), called the user authenticated key management protocol (uakmp). authors proposed to abuse client smart card, password, and individual biometrics to structure authentication model. certainly the utilization of different factors, for example, smart card, password, and personal biometrics makes generally speaking framework increasingly proficient or secure; be that as it may, a couple of key perspectives, for example, session data, building up a vigorous various parameter based confirmation couldn't be created which could make by and large framework computationally productive and pragmatic. what's more the utilization of non linear or bilinear (bidirectional) hashing method could have made framework progressively effective. j. srinivaset al. [33] the proposed plan underpins the adaptability and parts of a wsn without influencing the supportiveness of the enlistment or check arrangement of both the customer and sensor nodes and regular affirmation dismissing the upsides of the course of action, the proposed plan has a greater computational overhead than further lightweight validation plans. challaet al. [34] built up a secure signature-based authenticated key establishment scheme for future iot applications. authors focused basically on the security arrangement for cyber-physical frameworks, for example, smart grids and shrewd transportation, they built up a signature-based authentication and key agreement scheme essentially centers on signature-based authentication that can't be expressed as strong in current day hacking or breaking situation. moreover, the old style signature based approaches would have been expanded with certain increasingly successful lightweight cryptosystem. porambageet al. [35] created 2 group key establishment protocols for protected multicast communications among the resource compelled devices in iot however, group key establishment can accomplish better security arrangement for a predetermined number of nodes. anyway under practical iot applications with an enormous number of nodes and decentralized application condition, these methodologies appear to be limited. in any event, sharing of key data over the nodes may be ruptured accordingly causing unauthenticated information get to. this work, even couldn't address security during channel transmission. ninget al. [36] worked on an aggregated-proof based hierarchical authentication system for the internet of things. authors focused on a current u2iot design, to plan an aggregated-proof based hierarchical authentication scheme (apha) for the layered systems. solidly, 1) the aggregated-proofs are set up for various focuses to accomplish in reverse and forward unknown information transmission; 2) the coordinated way descriptors, homomorphism capacities, and chebyshev chaotic maps are together smeared for mutual verification; 3) not the same access authorities are dispersed to achieve hierarchical access control. could be effective for maintaining node anonymity; however is complicated. mick et al. [37] proposed laser: lightweight authentication and secured routing for ndn iot in smart towns. (observably, named information organizing (ndn) project deals highlights usable by iot applications) it very well may be additionally increased with upgraded ecc making it progressively appropriate. besides, the incorporation of various security components can be more successful than the old style laser. as in eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e3 secured authentication systems for internet of things 5 smart city there can be diverse application condition or end client equipment and subsequently utilizing various parameters is progressively compelling. it can be called as presenting all the more testing security approach can cause unapproved get to additional to confound and consequently progressively secure for real clients. he et al. [38] prescribed ecc based rfid authentication schemes for internet of things in healthcare environment with elliptic curve cryptography. further enhancement of ecc can be done. mohd.et al. [39] worked on a lightweight block ciphers for iot to augment energy optimization and survivability it requires significant optimization not only for computational cost but also as per environment. heung et al. [40] suggested a lightweight privacypreserving information aggregation system, called lightweight privacy-preserving data aggregation (ldpa), for fog computing-enhanced iot. the suggested lpda is portrayed by utilizing the homomorphism based encryption, chinese remainder theorem, and one-way hash chain techniques to not just total half and half iot devices' information into one, yet additionally early filter inserted false data at the network edge. it can be effective; however optimization in terms of better cryptosystem, multiple security constraints etc can’t be ignored. xuet al. [41] worked on network security condition awareness (nssa). be that as it may, it is constrained by its capacity to mine and assess security circumstance components from multi-source assorted system security data. to deal with this issue, this manuscript recommends an iot sort out security condition care model with a situation thinking system reliant on semantic transcendentalism and customer described standards. mysticism advancement can give a united and formal depiction to deal with the issue of semantic heterogeneity in the iot security space. in this manuscript, four key subzones are suggested to reflect an iot security situation: setting, assault, powerlessness, and system stream. this paper only focuses on semantic nature exploitation for security provision. it can’t be an ideal solution for major iot ecosystem purposes. diroet al. [42] prescribed utilizing lightweight cryptographic capacities, for example, elliptic curve cryptography to accomplish fog-to-things communication requires optimization to yield a better and robust solution. yuan et al. [43] suggested a dependable and lightweight reliance system for iot edge devices dependent on multi-source criticism data combination. to start with, due to the multi-source input system was utilized for worldwide trust estimation our trust computation component is progressively dependable against sassing assaults brought about by vindictive criticism suppliers. by then, lightweight trust evaluating framework was applied for joint efforts of iot edge gadgets, which is sensible for huge scale iot edge figuring since it energizes low-overhead trust preparing counts. simultaneously, a criticism data combination calculation dependent on target data entropy hypothesis was applied, whereby the trust components are weighted physically or emotionally feedback appliance can augment computational overhead and bandwidth exhaustion thus making it inappropriate for major mission critical communication over d2d ecosystem. zahra et al. [44] concentrated on beating the security disputes experienced during the information redistributing from fog client to fog node and applied shibboleth otherwise called security and cross area access control convention between fog client and fog node for improved and secure correspondence between the fog client and fog node use of multiple parameters can make solution more viable and trustworthy, especially when user (node) remains in uncertain use condition. diroet al. [45] recommended lightweight cryptographic functions, such as elliptic curve cryptography for iot augmentation of ecc can’t be ignored. and employing certain enhanced ecc with other security feature can make it a better solution, especially for iot. zhenget al. [46] explained the protection issues in clients' information sharing they use attribute-based encryption to empower information distribution. in like manner, they cleared the property planning limit and use the credit blossom channel to shroud all of the attributes in the passage control structure. in order to progress the adequacy of encryption, an on the web/disconnected encryption advancement was proposed in the encryption arrange. online-offline encryption approach during encryption could bring down energy consumption however the time delay for users often remains an open question. removal of attribute matching can make it computational better; however its robustness remains limited for a large scale real-time iot ecosystem. chen et al. [47] examined secure uplink transmission in a normal internet of things (iot) organization, where various sensors communicate with a controller through the help of a non-trusted hand-off. ding et al. [48] suggested a novel pairing-free data access control system based on cipher text-policy attribute-based encryption (cp-abe) with elliptic curve cryptography, abbreviated pf-cp-abe. optimization of ecc can be the scope; however inclusion of multiple parameters can make system more effective. elhosenyet al. [49] recommends a crossbreed security model for securing the diagnostic text data in medical images. the suggested model is created through coordinating either 2-d discrete wavelet change 1 level (2d-dwt-1l) or 2-d discrete wavelet change 2 level (2d-dwt-2l) strategy with a suggested crossbreed encryption scheme. the proposed hybrid encryption scheme is fabricated utilizing a mix of advanced encryption standard, and rivest, shamir, and adleman calculations. here, the focus is made on image data security. on the other hand efficacy of rsa often remains dependent on the bit size. ecc can be a better asynchronous cryptosystem solution. ruanet al. [50] conceptualized leakage resilient (lr) security system for password-based authenticated key exchange (pake) protocol. suggest the lr pake eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e3 gowtham m, m. k. banga and mallanagouda patil 6 convention by utilizing diffie-hellman key trade, lr storage (lrs) and lr invigorating of lrs properly and officially suggest security evidence in the standard system. ecc can be a better solution than the classical diffie hellman. its efficacy for a typical next generation iot system remains a suspicion. the security, privacy and safety risks related to iot that was worked in this study were ddos attacks made with iot devices, espionage and eavesdropping. another risk was that personal data can be stolen and used to harm the user in different ways, for example identity theft, hijack mail and social accounts, plan and commit burglary and blackmailing. the awareness of the risks related to iot devices correlates with how interested a person is of technology. the more interested a person is of technology, the better awareness the person have regarding the risks associated with iot devices. even though many people are aware of the risks related to iot devices, they do not protect neither their router nor their iot devices actively. this is because people don’t know how they can protect their router or devices. 4. problems identified considering the significance of a robust and efficient security model for the current iot ecosystems, though a number of efforts have been made; however realization of the major at hand systems under different attack conditions seems confined to alleviate adversaries. undeniably, majority of the existing systems are primarily focused on employing single cryptosystem approach to assist transmission security between communicating peer nodes; however in function varied attack events have proved limitations of these all classical cryptosystems. for example, most of the existing security algorithms are found vulnerable to the attacks caused due to: • smart card loss attack (scla) and several registered in users with the similar credentials attack. • offline password guessing and/or retrieval using brute force attack, • sensor node spoofing, • replay attack and forgery attack • privileged-insider and session-specific temporary information attacks. • user anonymity or non-linking is not addressed in practical iot specific security systems. • user impersonation attack or the session specific temporary information attack (sstia) and offline password guessing attack • gateway node bypassing and sensor-node key impersonation. furthermore, majority of the existing systems don’t reserve user’s and/or sensor’s anonymity, mutual authentication, secrecy of the secret nodes of the sensor node or gateway node and ignore intractability need of the network. inclusion of such robustness could strengthen iot communication system, especially sensor assisted m2m communication system to retain seamless communication. it can be considered as the prime driving force for the current research work and allied future proposition. in this research the emphasis is made on exploiting multi-level security provisioning to the wsn assisted m2m communication to serve secure communication across iot ecosystem. 5. recommendations i would recommend doing studies regarding how manufactures can design and create a safer device and maintain it safe for the users. for further studies, it would also be interesting to investigate how companies who sells iot devices store the data about their users – how well do they protect all the collected data? when looking at the current solution compared to the cia-triad, there is definitely benefits when using block chains in an iot network of this type. the experience and knowledge gained from researching and implementing this solution to create an understanding on how blockchain technology can support the communication and security in an internet of things network. leads us back to the starting problem statement: how do you maintain the information safety in an internet of things network based on block chains and user contribution? the block chain technology offers plenty of solutions to information security problems that can occur in iot networks, especially within the integrity of the information and the availability of the services since block chains is peer-to-peer. the biggest problem is within confidentiality where all the information on the block chain can be accessed by everyone which makes this not a suitable solution for a system were sensitive or classified information is stored, because even if we encrypt the information with a really secure encryption method the encryption could still be solved in theory. the existing schemes either require more communication and calculation costs for the resource constrained sensor nodes or they are vulnerable to several attacks such as malicious node deployment attack, sybil attack, node replication attack and wormhole attack. hence, designing of an efficient and more secure access control mechanism is an interesting research problem, which will be based on certificate based analytics. an important difference between current and future mobile architectures is, indeed the variety of devices for which security solutions must be found. current mobile phones are vulnerable to many attacks, e.g., malware, denial-of-service (dos), tracking and cryptographic attacks. future networks will include iot devices, which are even more attack-prone, and can be used as "tools" in cyber-attacks. the transition to5g networks is expected to not only combine, but to compound risks to all types’ of devices. for 30 years, 3rd and 4th generation mobile networks have allowed users to receive service anywhere, at any eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e3 secured authentication systems for internet of things 7 time. the dawning and visionary 5th generation mobile network(5g) aims to create a highly-decentralised architecture, including a massive internet of things and a non-federated core network, making telecommunication ubiquitous. the two of the most important cryptographic challenges for future mobile communications, unanswered by current 3g/4g solutions today are designing: • a versatile secure-channel establishment protocol in 5g networks; • secure and privacy-preserving protocols for resource-restricted iot devices. 6. conclusion in conclusion, as per the iot security engineering, security alleviation includes every one of the layers in the essential iot design, namely, perception, network, and application, regardless of the way that it is seen that by far furthermost of the present components are smeared to the network layer. it moreover can be assumed that a fitting iot hazard showing might be worthwhile in manipulating incredible iot security control. here this manuscript mainly concentrated on current disadvantages in access control mechanisms. the researchers and it companies can work on current authentication drawbacks so that the future iot environment can be secured with higher performance. acknowledgements. we are thankful to our organization and the research supervisors for their consistent assistance and guidance towards the research perspectives and the dimensions associated with the work inscribed. references [1] u. raza, p. kulkarni, m. sooriyabandara, “low power wide area networks: an overview”, ieee communications surveys & tutorials, vol. 19, issue 2, january 2017, pp. 855-873. 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[50] o. ruan, j. chen and m. zhang, "provably leakageresilient password-based authenticated key exchange in the standard model," in ieee access, vol. 5, pp. 2683226841, 2017. eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e3 critical success factors of green project management for sustainable housing 1 critical success factors of green project management for sustainable housing dina khater1,*, a. samer ezeldin2 and medhat elshazly3 1lecturer, arab academy for science and technology, faculty of engineering, architecture department, egypt 2american university in cairo, school of sciences engineering, department of construction engineering, professor and chair, egypt 3faculty of engineering, cairo university, architecture department, professor of architectural design and building technology, egypt abstract the growing demand for green construction, which is associated with increased perceptions of the risks associated with going green, highlights the need for a standard or benchmark that should be identified for project management practices to ensure successful sustainable urban development, assess its progress and report the results. the article argues that this would require a rephrasing of the project management processes as the execution of green building projects requires changes to the traditional project management aspects. therefore, the article will address the significant changes needed for project management practices that are appropriate to provide procedural parameters to a green building project. based on this perspective, the article explores the integration of concepts of sustainability into knowledge areas and processes of project management and how it can be used as a tool to sustainably implement the construction projects. the article results to reach the critical success factors of a work plan which is introduced as a guide model. the introduced guide model was validated to ensure the integration of sustainability into the management of sustainable development and fast track mega projects, called green project management (gpm) with egyptian sustainable development in the housing sector as the case study. keywords: green project management, sustainable, housing, critical success factors. received on 25 november 2019, accepted on 20 may 2020, published on 03 june 2020 copyright © 2020 dina khater et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.164857 1. introduction green buildings has been presented through design and construction activities in several egyptian research related to the field of building projects. nonetheless, green building in the egyptian building industry is still in the early stages of making a systematic change on the practical level. regulations and laws in egypt have not achieved a systemic structure or implementation mechanism to introduce an integrated green cycle in planning, design, pre-construction, *corresponding author. email: dinah.khater@gmail.com construction and post-construction to sustainably deliver construction projects. adopting this pattern and taking responsibility for the full change in the view of the authors would be successfully carried out by the project managers (pms), being the key people in all organizations who should assume the following role: "to deliver the temporary organization, the project, to a permanent organization, the globe". the perception of green buildings projects is based upon considering the project life cycle stages (plc) as an integrated process and an interconnected system from inception to operation and so project management processes eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 http://creativecommons.org/licenses/by/3.0/ mailto:dinah.khater@gmail.com dina khater, a. samer ezeldin and medhat elshazly 2 are assumed by the authors. however, for the housing projects that involve the end user (the owner or the tenant), the project management activities would be required to go further to ensure full integration of plc phases and to be green and so project management processes to ensure sustainability objectives achievement. this will be established through the introduction of the end user as one of the stakeholders [7]. the case gets more difficult in housing projects than other projects, as the owners of other projects (hotels, commercial, industrial … etc) are paid back the high initial cost they endured during the project initiation stage during the project operation stage. the contribution of green project management (gpm) in enhancing the performance of communities’ sustainable development process is revealed through the triple constraints pf project management (scope – cost – time) which will tend to keep constant with the same rigidity as the iron triangle and will align with sustainability triple bottom line (people – environment – profit) instead of contradicting them as it seems from an overall perspective, table 1 [13]. table 1. a comparison between sustainability and project management visions [13] sustainability vision project management vision long term + short term oriented short term oriented in the interest of this generation and future generations in the interest of sponsor / stakeholders life-cycle oriented deliverable/result oriented people, planet, profit scope, time, budget increasing complexity reduced complexity 2. project management aspects and sustainability fundamentals the sustainable housing projects criterions and the success models in project management in several researches highlight the lack of a structured project management framework that considers incorporating sustainability principles through plc stages. wu et al. (2010) emphasized that it is not sufficient to build a green building with new materials and technologies that are environmentally friendly. additionally, the previous literature about sustainability in the project management context has focused on the project content and outcome not the way of management. in fact, the importance of an integrated approach in the whole project lifecycle, from planning till operating is not only for sustainable projects but as well to manage this process. it is necessary to propose a management work plan through the life cycle stage of green building. the project management body of knowledge [9] describes project cycle as a series of sequential process groups with determined names that are related to one of the plc stages, i.e. inception, design and tendering stages or construction stage or construction and operation … etc. knowledge areas are performed through these process groups project management which has been mapped in pmbok matrix, table 2 [9]. the authors are looking to formulate the integration concept between project management processes and plc stages in accordance with the sustainability long-term vision which mandates introducing new knowledge areas and viewing the traditional ones differently. 2.1. project management processes the project management has five processes (initiation, planning, execution, controlling and closing). these five process groups perform many relationships such as: overlapping, end to start … etc [9]. the process groups are linked by their results or outcomes, the result or outcome of one can often become an input to another. among the central process groups, the links are iterated. for such, the planning process provides the project execution process with a documented project plan followed by documented progress updates throughout the project development. in addition, the project management process group are not discrete, they are overlapping activities that occur at varying levels of intensity throughout each phase of the project, figure. 1. the process group interactions can also perform cross phases such that closing one phase provides an input to initiating the next. for example, closing a design phase requires customer acceptance of the design document. simultaneously, the design document defines the product description for the implementation phase, figure. 2. the non-discrete character of process groups will be utilized by the authors in relation with sustainability vision for plc stages for the proposed management work plan. 2.2. project management knowledge areas in the project management body of knowledge (pmbok) [9] the process groups are the chronological phases that the project goes through in each of its stages, and the knowledge areas occur throughout any time during the process groups. the process groups are horizontal, and the knowledge areas are vertical, table 2 [9]. these knowledge areas are the core technical subject matter of the project management profession, and they bring the project to life. this article will introduce another concept which will have the project management processes goes chronologically in linear relationship with plc stages. a new version for mapping the project management process groups, project management knowledge areas and project life cycle stages will be illustrated from sustainability perspective by the researcher which contradicts with that one in pmbok. 2.3. project management success factors for sustainable housing for the sustainable housing various definitions exist; the european union (eu) defined sustainable social housing in eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 http://www.projectengineer.net/the-pmbok-process-groups/ http://www.projectengineer.net/project-management/ http://www.projectengineer.net/project-management/ critical success factors of green project management for sustainable housing 3 terms relative to: the quality of construction; social and economic factors with regard to affordability and psychological impacts; and eco-efficiency such as efficient use of renewable resources in the built environment [4]. the following figure. 3 proposes a sustainability framework to evaluate the performance of housing projects sector [10]. it shows a schematic framework for understanding and evaluating the key components of and strategies for achieving sustainable housing. examination of figure. 3 would reveal that the framework is made up of the four facets of sustainable development; namely, social; economic; cultural and environmentally sustainable housing policies and programs. additionally, it indicates that the development of sustainable housing policies and programs do not necessarily translates to suitable housing without the engagement of sound implementation strategies by housing developers and project managers. this underscores the vital role of robust management and managers capacity in the successful implementation of sustainable housing policies and programs. the plc management is sustainable when the entire break down of work activities are directed in such a way that enhances the reduction of the environmental impacts and preserves the sustainability parameters. while, project management best practices may be described as an optimized solution to perform the scope of work in order to achieve high performance [10], it can be argued that it is fundamental to provide a problem-free housing projects management process which permits the housing to become sustainable. the common variables which act as the success factors for traditional project management are scope of work and its understanding, communication management, client involvement, project team, decision making authority, realistic cost and time estimate, project control, problem solving abilities, risk management, adequate resources, performance monitoring …etc [2]. additionally, the main problems in traditional project management are basically with projects planning and implementation, cost and time overruns and quality non-achievement [3], while in gpm, sustainable project planning (spp), sustainability principles activation are introduced by the researcher to maintain sustainability practices continued through the plc stages and orchestrated comprehensively by an integrated planning process. 3. surveying the current status of egyptian housing projects in government sector a definition was derived for sustainable project management from combining the triple-p element of sustainability and the life cycle views [5], which was elaborated to: sustainability in projects and project management is the development, delivery and management of project organized change in policies, processes, resources, assets or organizations with consideration of the (six) principles of sustainability in the project, its result and its effect [1]. however, the alignment between sustainability and project management is still very rare [4] and the link to defining a sustainable process and methodology for project management is still absent [5]. hence, an integrated approach is vital in green building process which would require an effective role of project managers during the plc of green building. sustainable performance (sp) of a construction project during its life cycle (lc) is a main objective to achieve sustainable development (sd). the factors affecting sp of construction project can be examined in three main categories: economic sustainability factors (esf), social sustainability factors (ssf), and environmental sustainability factors (ensf). these factors are classified in relation to the plc stages; inception phase, design phase, construction phase and operation phase [1]. based on this line of reasoning, studies that promote the integration of the sustainability concept into project management were deployed [8,14]. the authors have elaborated these studies to address the sustainability dimensions through plc stages and relate them with the basic tools of project management which are project management processes and knowledge areas. the authors proposed a work plan that is designed to discuss factors of sustainability in project life cycle and sustainability in project management knowledge areas. the designed work plan was developed through a structured questionnaire to survey the current status of project management practices. the questionnaire aimed to accomplish the work plan development that maintains the linkage between the temporary character of project management and the long term of sustainability through (2) sections, table 3, 4, 5 and 6: section (1): factors affecting sp of construction projects throughout plc stages from project management perspective have been investigated on likert scale rating. the key variables were coded and clustered into three sets aligned with the sustainability triple bottom line and the basic project management process aspects [13,8]. section (2): check listing the level of application of project management practices in housing projects on a likert scale rating. the government recent national housing developments were surveyed in 4 different cities and for 4 different levels of income. the questionnaire was discussed in interviews, site visits and correspondences to monitor and report the current status of project management practices from sustainability perspective with a total of (115 engineers) working as design project managers, construction managers, construction supervision engineers, architects, owner representatives and pmo managers in addition to contractors in order to monitor and report the current status of project management practices from sustainability perspective. a total of (106 engineers) has responded to this questionnaire, table 7. additionally, in the operation stage a total of (168 end users) who have moved to live in their units and those who are waiting to move gave their responses through a questionnaire that was available on google documents, its link was announced on social media where end users were informed and easily responded. the results of the questionnaire revealed the gaps in the existing project management processes to perform sustainably. the authors then identified the places to intervene in the existing processes. therefore, the potentials eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 dina khater, a. samer ezeldin and medhat elshazly 4 of project management to ensure green housing projects delivery were concluded as will be illustrated hereafter. table 2. project management process group and knowledge area mapping [9] eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 5 figure 1. overlap of process groups in a phase [9] figure 2. interaction between phases [9] figure 3. sustainability of housing [6] critical success factors of green project management for sustainable housing eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 dina khater, a. samer ezeldin and medhat elshazly 6 table 3. questionnaire section (1), sustainability factors (economic factor “ef”, social factor “sf” and environmental factor “enf”) in project inception stage [developed by author] analysis on likert scale st ro ng ly d is ag re e d is ag re e n eu tra l ag re e st ro ng ly ag re e sustainability factor / project stage (inception stage) ef 1. was the capital budget defined to plan and control project total cost (life cycle cost analysis)? has it been extended to consider not only elementary cost but total cost for building-up, operating project over its life cycle? 9% 55.5% 35.5% 2. was the planned profit extended beyond focusing on stage or sectional profits and considered total profit from operating a construction project across its life cycle? 9% 64.50% 12% 11.50% 3% sf 3. was land selection for project site based on cropland and natural resources protection? 18.75% 81.25% 4. were negative impacts avoided from project development on any cultural and natural heritage? 18.75% 81.25% 5. was the project able to provide local employment? 100% 6. has the project improved local infrastructure capacity: drainage, sewage, power, roads … etc? 18.75% 37.50% 43.75% 7. were end users cultural aspects considered (cultural background, financial category and their identity? 18.75% 25% 25% 31.25% en f 8. were potential air pollution from the proposed project and its impact on local climate examined? 100% 9. was waste generation at both project construction and operation stages examined? 100% table 4. questionnaire section (1), sustainability factors (economic factor “ef”, social factor “sf” and environmental factor “enf”) in project design and construction stages [developed by author] analysis on likert scale st ro ng ly d is ag re e d is ag re e n eu tra l ag re e st ro ng ly ag re e sustainability factor / project stage (design stage) ef 1. was the total cost involved in plc, i.e. site formation, construction, operation, maintenance cost considered? 46.25% 11.25% 42.50% 2. were economic consideration given for durability and availability for material selection? 16.75% 34.75% 41% 7.50% 3. how far clustering and prototype have been followed? 33.50% 32% 33% 4. how much was the compliance with the site conditions considered (topography and site survey)? 18.50% 33% 48.50% 5. how do you evaluate the mistakes and discrepancies in delivered design documents? 15% 15% 70% sf 6. how do you evaluate the considerations in designing process for life safety and emergencies? 100% en f 7. is the designer knowledgeable of energy savings and environmental issues? 25% 16.50% 58.50% 8. was modular and standardized components to enhance build ability and to reduce waste generation utilized? 25% 16.50% 58.50% sustainability factor / project stage (construction stage) ef 1. how far do you agree that the following expenses / cost is planned and well managed? 1.a. materials cost (concrete, steel, timber, brick … etc)? 37.5% 62.50% 1.b. energy cost? 37.50% 62.50% 1.c. water resources cost? 37.50% 62.50% 1.d. equipment costs for using various equipment, tools? 37.50% 62.50% 2. how far do you agree that the following expenses / cost is planned and well managed? eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 7 analysis on likert scale st ro ng ly d is ag re e d is ag re e n eu tra l ag re e st ro ng ly ag re e 2.a. labor cost? 32.50% 67.50% 2.b. professional fees paid to various professionals? 31.25% 15% 53.75% 3. the afforded site security (various types of measures for protecting the site safety)? 37.50% 6.25% 56.25% sf 4. are there standardized measures during for on-site health, site hygiene, safety measures and insurance? 50% 43.75% 6.25% 5. is there a provision for public safety (warning boards and signal systems, safety measures)? 87.50% 6.25% 6.25% en f 6. is the application of renewable materials and materials reuse (rubble, earth, concrete, steel and timber) applied? 72.50% 24.50% 3.75% 7. are there a policy conditions / iso conditions applied to manage the following: 1.a. air emission and pollution? 100% 1.b. waste produced from project operation? 80% 20% 8. are consideration being given to the reduction of earthwork and excavation, formwork, reinforcement, concreting and waste treatment during structural operation? 20% 80% table 5. questionnaire section (1), sustainability factors (economic factor “ef”, social factor “sf” and environmental factor “enf”) in project operation stage [developed by author] analysis on likert scale sustainability factor / project stage (operation stage) validity evaluation n o d on 't kn o w ye s 1. were you informed about the units handing over date? 61.25% 13.75% 25% 2. were you periodically notified about any delay in work progress and modified delivery date? 61.25% 13.75% 25% 3. were you able to follow up on the work progress? 41% 12.50% 46% 4. did you notice a change in master planning, facades design, residential units plan design, the finishing model you chose? 31.25% 12.50% 56.25% satisfaction evaluation ve ry d is sa tis fie d d is sa tis fie d n eu tra l sa tis fie d ve ry sa tis fie d 5. how satisfied are you with the unit that was allocated to you by lottery system? 15% 13.75% 27.50% 25% 18.75% 6. how do rate the following (price / m2)? 12.50% 33.75% 5% 26.25% 22.50% 7. how do you rate (flat area) and (flat interior design)? 25% 25% 10% 30% 10% 8. how do you rate advantage of reserving at this sector? 16.25% 30% 10% 30% 13.75% table 6. questionnaire section (2), project management knowledge areas [developed by author] analysis on likert scale st ro ng ly d is ag re e d is ag re e n eu tra l ag re e st ro ng ly ag re e project budget 1. is the project budget according to contract? 63% 37% 2. how much is the total actual project budget, the expenses incurred, sum m2 of construction floor area, the rework costs? 75% 25% 3. do you think green buildings cost more than traditional buildings? 75% 25% 4. do you think these are of financial benefit for green buildings: 4.a. lower energy/water usage, less waste disposal 4.b. durability of building materials 100% critical success factors of green project management for sustainable housing eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 dina khater, a. samer ezeldin and medhat elshazly 8 analysis on likert scale st ro ng ly d is ag re e d is ag re e n eu tra l ag re e st ro ng ly ag re e contract conditions 5. are there any "green" requirements in the contract? 100% 6. are you satisfied with incentive/ penalty clauses in contract? 25% 75% project team characteristics 7. do you agree about the following: 7.a. importance of organizing team relationships in rfp? 100% 7.b. the contractual terms for project team members? 100% 7.c. the team member’s experience in similar facilities, green buildings, delivery systems adequate? 75% 25% 7.d. the team communication of this project? 25% 50% 25% design and construction process 8. how is the timing of communication within team members, is it satisfactory? 50% 25% 25% 9. do you agree about presence of a gb consultant? what do you think about his contractual position? 25% 75% 10. how is the design charettes and commitment level of team members? 25% 50% 25% analysis on likert scale ve ry u ns at is fa ct or y u ns at is fa ct or y n eu tra l sa tis fa ct or y ve ry sa tis fa ct or y project scheudle 11. how do you evaluate the variance between the planned project duration and the actual project duration? 50% 25% 25% 12. how far is the reflection of the speed of the following on project schedule: 12.a. construction (actual duration/floor area)? 25% 75% 12.b. material availability (time delay because of supplying materials)? 70% 15% 15% 12.c. equipment availability (time delay because of lack of equipment)? 70% 15% 15% 12.d. labor availability (time delay because of lack of labor)? 75% 25% project quality 13. how do you valuate the difference in level between quality expectation of owner and real project quality? 15% 10% 15% 60% 14. how do you evaluate the budget and time required to rework unsatisfied quality requirement works? 3.75% 30% 2.5% 63.75% design and construction integration 15. how are you satisfied with the consultants’ / contractors’ work integration? 10% 28.75% 37.50% 23.75% 16. how do you evaluate the involvement of a "green" consultant? 87.50% 6.25% 6.25% 17. how do you evaluate decision making process in this project? 10% 33.75% 17.50% 38.75% eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 9 table 7. interviewees in visited projects in different cities number of interviews /questionnaires responses sherouk city new cairo city 6th october new administrative capital (***) (*) (***) (**) (*) (***) (**) (****) (****) city authority engineer (owner representative) 1 1 1 1 1 1 1 5 5 architects 3 3 5 3 5 5 3 supervision consultant 2 2 3 2 owner's management consultant 1 city authority engineer (supervision) 1 1 1 1 contractor 1 3 1 2 4 1 2 4 3 technical office 1 1 1 1 1 1 1 1 1 contractor project management consultant 2 2 2 sub-contractor 2 2 2 city authority engineer (external works supervision) 1 1 1 contractor (external works) 1 1 1 end user 25 20 20 14 25 30 19 10 5 total % 23% 33% 27% 18% 3.1. concluding the current gaps the analysis of the received responses for the questionnaire resulted in supporting the authors hypothesis and revealed the gaps in the efficiency of the current projects performance to be sustainable due to the following analysis conclusions: (i) the fragmentation in the management of plc stages and the diversity of stakeholders causes implication in time, cost and risks evaluation as a consequence of conflicts in decision making. (ii) gpm processes should ensure the comprehensive planning for plc stages, while monitoring and controlling should overview the design, tender and construction stages. sustainability performance can be assessed through sustainable project planning (spp) which a new introduced project management knowledge area by the authors. (iii) the lack of the integration between plc stages supports the project management capacity to bridge this gap to have plc stages streamlined with defined sustainable targets. hence, stresses the importance of the chronological linear relationship between project management processes and plc stages. (iv) project managers should be responsible to plan for the mechanism for sp achievement, facilitate the collaboration among various professionals through plc stages and have them consistent and coordinated. 3.2. the places to intervene the sustainability criterions should be continuous through plc stages. this would be achieved by successful planning that adopts an integrated process between project management processes and plc stages, which is called sustainable project planning (spp). gpm framework is defined by the authors as the management process that maintains an integration concept based on a linear relationship between project management practices and sustainability criterions through plc stages. the establishment of this comprehensive perspective is assumed to deliver the projects sustainably as will be validated in the coming section. 4. validation of the proposed framework surveying the current status of project management practices has concluded the factors for managing the integration between sustainability triple bottom line and project management processes through project life cycle stages in findings record which were interpreted into the analysis of the gap between the current practices and the proposed framework. these factors will boost the correlation between project management processes and sustainability principles through project life cycle stages. the designed work plan which has been developed through the previous questionnaire, table 8 will be put into a guide model to represent the structured approach for this integrated process based on the concluded current gaps, table 9. for the validation of this guide model, it was evitable to conduct another questionnaire. the correlation between different variables was the basis of the construct, accordingly the mapping project management areas of knowledge to the project management processes through the project life cycle stages (plc) that will be performed. 4.1 the guide model the authors at this stage is looking to formulate the integration concept between project management processes and project critical success factors of green project management for sustainable housing eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 dina khater, a. samer ezeldin and medhat elshazly 10 management knowledge areas through the project life cycle, therefore the establishment of the comprehensive perspective to deliver the adequate sustainable performance. the following table 9 explains the proposed guide model illustrated through the adjusted mapping of the project management knowledge areas to the project life cycle stages (plc) and the project management processes in a linear integrated form (one comprehensive stage) not fragmented stages with isolated project management processes. the project stages (inception, design, tendering, construction and operation) are considered collectively as wbs (work breakdown structure) linked linearly with the project management basic processes in a chronological sequence. on the vertical line is the project management areas of management, they have been divided into groups then sub-groups and traced through the life cycle. this perspective is proposed to ensure the diligent delivery of green based construction projects. the performed mapping introduces (3) important goals that contradict with pmbok: (1) new alignment of project management processes and areas of management, (2) a guide model for green project management in housing projects and (3) defining green project management critical success factors. this necessitate the inevitability to validate this approach through conducting another questionnaire with the previous interviewees of the previous questionnaire. 4.2 matrix conformity the guide model matrix is introduced as an interpretation for the previously illustrated conclusions. the level of the conformity with the new defined mapping matrix which is between new project management knowledge areas through project life cycle and project management processes will define the place of the deficiency. the matrix details identify the green project management tasks through project life cycle stages towards green project management, table 9. 5. conclusions ensuring the streamline of sustainability vision in project management processes and practices through project life cycle stages can be achieved when maintaining the longterm vision which requires the project managers engagement to sustainability. this revert us back to the paper focal point which is to integrate the project management aspects and the sustainability principles introduced by researcher as integrity concept. 5.1 new alignment of pm processes and adjusted pm knowledge areas through plc stages (correlation coefficient method) to introduce the new shift needed to apply and integrate sustainability in project management, the correlation between project management processes and project management adjusted knowledge areas through plc stages. interviewee will rate the linear relationship between the stages of plc and pm processes with the new alignment of pm knowledge areas. in the statistics science, correlation coefficients are used to determine how strong a relationship is between two variables, its value varies from +1 (means strong relationship) to negative correlation at -1, with a neutral relation at zero (no relation). the ranges of respondents’ responses were used to determine the correlation matrix between gpm knowledge areas through project life cycle stages and project management processes. this has refined the proposed guide model and turn it from draft version to a final version that will be considered as the work plan. conclusions confirmed the agreement of the interviewees about the new alignment of pm processes and adjusted pm knowledge areas through plc stages. 5.2 the performance matrix of green project management the correlation coefficient values were defined for the relation between pm areas of knowledge through plc stages which were agreed to be positive among the interviewees of the validation questionnaire. this helped in building the correlation matrix (correlation statistic method performed by excel) and compare it with the proposed guiding model. in the same context, the need to identify the dominant factors and the less dominant factors in this matrix is the pillar for getting guiding model draft version into the final version, table 8 and table 9. the conformity with the performance matrix (guide model) reflects that the gpm practices is on the right track towards success. therefore, guide the way for enhancing the green project management performance. to reach this point, guiding model was discussed in the validation questionnaire and (3) questions was asked after the interviewee finalizes his review for the model about the following: 1. defining gpm success criteria, table 10. 2. identification of critical success factors for green project management, where gpm success is considered as the dependent factor and gpm knowledge areas are considered as the independent factors, table 11 3. ranking the critical factors influencing the success of gpm, table 12. 5.3 critical success factors for green project management (ranking method) the final goal will seek the critical success factors for managing sustainable performance in housing projects through a systematic series of questions introduced in the validation questionnaire. the methodology of this questionnaire is to rate the variance of knowledge areas eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 11 contribution to green project management success, which is obtained from the knowledge areas as components of the green project management. a crucial step to reach this was a question about green project management (gpm) success criteria, where respondents replied with their level of agreement by ticking on ten-point likert scale, 0 (not important) to 10 (very important) the area/areas of knowledge the respondent thinks they directly relate to the success of sustainable based project management, table 10. here, the most prominent knowledge areas were determined as variables determining the criterions of gpm success. the areas of knowledge which had below 5 grades were excluded (red highlighted). respondents are then requested to re-assess their replies through the next question about identifying the critical factors influencing the success of gpm where respondents replied with their level of agreement by ticking on ten-point likert scale, 0 (not important) to 10 (very important), for each of the proposed areas of knowledge according to the respondent believe about the success of sustainable based project management, table 11. the result of this question was then computed to reflect the scores each area of knowledge has achieved. the third question was about ranking the critical factors influencing the success of gpm in an ascending order starts from (1) to (9), where ranks equal to 5 grade and above were excluded, table 12. this indicator was emphasized by asking the respondents to assume the weight of each factor towards the success of gpm according to its importance as they rated it. the given weight was based on their experience and related to their vision for an ambitious plan. table 8. mapping green project management (gpm) areas of knowledge to project life cycle (plc) and project management (pm) processes [developed by author] project management areas of knowledge project life cycle stages / project management processes in iti at io n planning, execution and monitoring & controlling c lo si ng d es ig n te nd er c on st ru ct io n 1.sustainable project planning 1.1 plan development 1.2 plan evolution 1.3 assess & control 2. project integration management 3. contract management 4. scope management 5. green building check listing 6. communication management 7. constructability management 8. sustainability principles activation 8.1.1 time 8.1.2 cost 8.2.1 stakeholders 8.2.2 culture 8.3.1 external policy 8.3.2 internal procedures 9. product management 9.1 quality management 9.2 procurement management 10. risks management 10.1 design risks 10.2 construction risks 11.challenges management 11.1 impact management 11.2 solution innovation critical success factors of green project management for sustainable housing eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 12 table 9. a guide model (mapping green project management (gpm) areas of knowledge to project life cycle (plc) and project management (pm) processes [developed by author] project management areas of knowledge project life cycle stages / project management processes initiation planning, execution and monitoring & controlling closing design tender construction 1. sustainable project planning 1.1 plan development develop projects strategic objectives develop sustainability parameters 1.2 plan evolution developing project management plan develop the framework for integrating sustainability principles through project plan direct and manage project work communication of project management plan and sustainability assessment system report 1.3 assess & control develop sustainability assessment system evaluate and update project management plan evaluate the integration of sustainability goals project learned lessons 2. project integration management 2.1 planning develop project charter develop igbp-pdri model develop procurement method develop quality standard (qmif) identify project constraints 2.2 execution identify stakeholders’ interests develop stakeholders’ requirements maintain procurement method ensuring quality management integrated framework (qmif) 2.3 monitoring & control monitor and control project work perform integrated change control 3. contract management development of contractual relationship guidelines (crg) contract drafting issue green requests for dina khater, a. samer ezeldin and medhat elshazly eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 critical success factors of green project management for sustainable housing 13 project management areas of knowledge project life cycle stages / project management processes initiation planning, execution and monitoring & controlling closing design tender construction proposals contract management 4. scope management 4.1 planning collect stakeholders’ requirements define scope plan scope management 4.2 execution create overall wbs for project milestones create work breakdown for stage milestones 4.3 monitoring & control scope validation and control reporting changes 5. communication management plan communication management manage and control communications manage integrated change control 6. sustainability principles activation (economic principle) projects constants: 8.1.1 time initiating baseline time schedule planning integrated time schedule updating time schedule and include dated corrective actions 8.1.2 cost early stage design decisions identify target group capabilities develop project budget scale with respect to sustainability green building life-cycle analysis direct and manage life-cycle analysis recommendations projects variables (housing projects): determining housing affordability identify target group performing feasibility study direct and manage feasibility study recommendations implement sustainability assessment, evaluate and decide corrective actions 6. sustainability principles activation (social principle) projects constants: 8.2.1 stakeholders identify stakeholders plan project team management manage stakeholder engagement and develop project team control stakeholder’s engagement and project team management 8.2.2 culture identify target group eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 dina khater, a. samer ezeldin and medhat elshazly 14 project management areas of knowledge project life cycle stages / project management processes initiation planning, execution and monitoring & controlling closing design tender construction requirements identify sustainability decisions orientation sustain sustainability decisions orientation projects variables (housing projects): implement housing social criterions determining density and urban form determining dwelling size developing density and urban form developing dwelling size direct and manage sustainability decisions ensuring adaptability ensuring social acceptability implement sustainability assessment, evaluate and decide corrective actions 6. sustainability principles activation (environmental principle) projects constants: 8.3.1 external policy determining water conversation and energy efficiency methods determining construction materials determining construction methods 8.3.2 internal procedures identify sustainability decisions orientation develop internal procedures implementing process and procedures regulations sustain sustainability decisions orientation projects variables (housing projects): maintaining quality of life criterions developing housing indicators reflecting the acceptable quality of life maintaining humanization in design development direct and manage sustainability decisions implement sustainability assessment, evaluate and decide corrective actions 7. quality management plan quality management perform quality assurance control quality 8. procurement management plan procurement eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 critical success factors of green project management for sustainable housing 15 project management areas of knowledge project life cycle stages / project management processes initiation planning, execution and monitoring & controlling closing design tender construction management conduct procurements control procurements close procurements 9. risks management plan risk management plan preventive technique identify risks perform qualitative & quantitative risk analysis plan risk responses identify risks perform qualitative & quantitative risk analysis plan risk responses identify risks perform qualitative & quantitative risk analysis plan risk responses apply integrated remedial technique eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 16 table 10. gpm success criteria [developed by author] le ve l o f a gr ee m en t su st ai na bl e pr oj ec t pl an (s pp ) in te gr at io n m an ag em en t c on tra ct m an ag em en t sc op e m an ag em en t c om m un ic at io n m an ag em en t su st ai na bi lit y pr in ci pl es a ct iv at io n pr od uc t m an ag em en t r is k m an ag em en t 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 3 0 5 0 0 0 0 0 0 4 5 5 0 7 0 0 5 17 5 5 25 10 25 7 7 25 25 6 15 10 10 5 7 7 17 5 7 30 28 5 35 28 11 35 35 8 15 20 20 20 22 20 10 10 9 15 3 17 5 18 22 5 5 10 12 1 35 0 15 30 0 0 ten-point likert scale 0 (not important) to 10 (very important) table 11. identifying the critical factors influencing the success of gpm [developed by author] le ve l o f a gr ee m en t su st ai na bl e pr oj ec t pl an (s pp ) in te gr at io n m an ag em en t c on tra ct m an ag em en t sc op e m an ag em en t c om m un ic at io n m an ag em en t su st ai na bi lit y pr in ci pl es ac tiv at io n q ua lit y m an ag em en t pr oc ur em en t m an ag em en t r is k m an ag em en t 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 4 0 7 0 7 0 0 5 17 17 5 10 25 10 25 7 7 25 25 25 6 15 5 10 5 7 7 17 5 5 7 25 35 5 35 28 11 35 35 35 8 20 20 20 20 22 20 10 10 10 9 15 5 17 5 18 22 5 5 5 10 12 0 35 0 15 30 0 0 0 total scores 97 97 97 97 97 97 97 97 97 ten-point likert scale 0 (not important) to 10 (very important) table 12. ranking the critical factors influencing the success of gpm [developed by author] scores rank average rank weight factor sustainable project plan (spp) 60 3 3.5 0.23 integration management 55 5 6 0.04 contract management 60 3 3.5 0.20 scope management 55 5 6 0.04 communication management 65 1 1.5 0.21 sustainability principles activation 65 1 1.5 0.18 quality management 55 5 6 0.04 procurement management 35 9 9 0.03 risk management 50 8 8 0.03 dina khater, a. samer ezeldin and medhat elshazly eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 17 references [1] adnan, e., bernd k. and hadeel a., “factors affecting sustainable performance of construction projects during project life cycle phases”, international journal of sustainable construction engineering & technology, vol. 7, issue 1, pp. 50-68, 2016. [2] chawlaa, v.k., chandab a.k., angraa, s. and chawla, g.r., “the sustainable project management: a review and future possibilities”, journal of project management, vol. 3, issue 3, pp. 157-170, 2018. [3] dey, p.k., “benchmarking project management practices of caribbean organizations using analytic hierarchy process benchmarking”, an international journal, vol.9, no.3, pp. 326-356, 2002. [4] gareis, r., heumann, m. and martinuzzi, a., “relating sustainable development and project management”, irnopix, berlin, germany, 2010. [5] grevelman, l. and kluiwstra, m., “sustainability in project management, a case study on enexis”, united kingdom and the netherlands: university of greenwhich and saxion university of applied sciences, 2009. [6] ibem, e. and aduwo e., “a framework for understanding sustainable housing for policy development and practical actions”, architects colloquium, covenant university, nigeria, 2015. [7] khater, d., “a holistic framework for green project management to deliver sustainable housing”, journal of engineering and applied science, vol. 67, no. 3, jun. 2020. [8] mauro l. and marly m., “key factors of sustainability in project management context”, international journal of project management, vol. 35, issue 6, pp. 1084-1102, 2016. [9] project management institute, “a guide to the project management body of knowledge (pmbok guide)”, vol. 6, 2017. [10] ramabadron, r., dean, j.w. jr and evans, jr, “benchmarking and project management: a review and organizational model”, benchmarking for quality management of technology, vol. 4, pp. 47-58, 1997. [11] report of european housing ministry held in czech republic, prague, vrom, “the 2005 sustainable refurbishment of high-rise residential buildings and of surrounding areas in europe”, 2005. [12] silvius, a.j.g., brink, j. van den and köhler, a., “views on sustainable project management”, ipma scientific research paper series. helsinki, finland, 2009. [13] silvius, g., schipper, r., planko, j., brink, j. van den and köhler, a., “sustainability in project management”, gower publishing limited, farnham, england, 2012. [14] sudha r. and timea k., “sustainability in project management”, umea university, school of business and economics, msc strategic project management, european, 2017. critical success factors of green project management for sustainable housing eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e5 mobile health applications during epidemic management in india: a review eai endorsed transactions on smart cities review article 1 mobile health applications during epidemic management in india: a review rajgourab ghosh1,*, sanjeev kumar2 1amity institute of biotechnology, amity university, kolkata, india, rajgourav@hotmail.com 2all india institute of medical sciences, bhopal, india, docsanjiv@gmail.com abstract introduction: smart cities endeavour to provide a good quality of life to its inhabitants. the covid-19 pandemic necessitates redrawing the framework of epidemic management in india. information, communication & technology (ict) solutions such as mobile health (mhealth) can complement this. objectives: to review ict and mhealth used for epidemic management in smart cities of india. methods:a systematic review was conducted to identify the use of ict or mhealth applications for epidemic management in smart cities. a predefined search strategy and a predefined eligibility criterion to search for articles published in english on medline were used. results: our study showed ict and mhealth use has increased during the recent covid-19 pandemic in india and available solutions can be applied in smart city framework to improve epidemic management and achieve mhealth targets. conclusion: we conclude that there have been many advances in the provisions of ict and mhealth interventions in india in context to smart cities and scope for improvements abound. keywords: ict, mhealth, smart cities, epidemic, disease surveillance received on 14 september 2020, accepted on 15 september 2020, published on 05 october 2020 copyright © 2020 rajgourab ghosh and sanjeev kumar, licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.5-10-2020.166546 *corresponding author. email:rajgourav@hotmail.com 1. introduction smart cities are conceptualized around the ideas that they would provide a good quality of life to its inhabitants using principles of equity, efficiency, and foresight. several nations have developed policies to design smart cities. the smart cities are expected to have robust and flexible core infrastructure and incorporate technologies to this end. innovations in the data sciences and technology have become the guiding principle in improving human health with changing urban landscape (ramaswami et al, 2016). these innovations have often been termed as smart solutions which include smart mobile phones (smartphones), smart applications (apps) for these phones, etc. under the smart cities mission of the ministry of urban development, government of india (moud), new delhi municipal council (ndmc) has been selected as one of the first twenty cities (http://smartcity.ndmc.gov.in/). many municipal services can now be availed simply through tapping on an app e.g. ndmc311 app or calling a number. also dedicated websites are used to provide doorstep delivery of public services by the new delhi government (https://ar.delhigovt.nic.in/content/doorstep-deliverypublic-services) or provision of cash for elderly or immobile patients through india post. (www.indiapost.gov.in) are a part of smart city project. similar smart solutions include continuous and remote monitoring of the health status of the elderly (majumder et al., 2017). smart solutions in healthcare can save both lives and money. the use of such smart health solutions would further transform a usual city into a smart city and eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e1 mailto:rajgourav@hotmail.com mailto:docsanjiv@gmail.com http://creativecommons.org/licenses/by/3.0/ rajgourab ghosh and sanjeev kumar 2 add to the mission of 'universal healthcare'. this becomes more evident and a necessity in the ongoing pandemic of covid-19. as a part of providing good quality of life, smart cities are expected to be resilient to epidemics. the public health care system of india has been strewn with inadequacies in funding, infrastructure, and human resources. it has been reported that there are only 7 hospital beds on an average for every 10,000 of its population. health resources have remained favourable towards urban india with 65–70 % of infrastructure and human resources allocation though ~70 % of the population resides in rural areas (morris et al, 2016). in april 2020 there were nearly 1.9 million hospital beds, 95000 icu beds, and 48,000 ventilators in india (kapoor g. et al, 2020). decision making in public health requires timely input in form of data relating to public health problems, infrastructural deficiencies, lacunae in human resources in healthcare, and implementation gap of the interventions. by understanding the distribution and determinants of health-related events in specified populations scientifically, diseases, and other health problems can be controlled before taking their toll on human life and economy. monitoring and surveillance form the backbone of any well-performing public health system. in surveillance, health data is collected, collated, analyzed, and interpreted in an ongoing manner. it provides information for action. health surveillance includes detection of disease outbreaks, registration of cases, confirmation by standard methods, line-listing and reporting of these cases, data analysis and interpretation, epidemic preparedness, response, and control, followed by feedback. understanding of chain of infection helps in identifying the targets in the chain such as cases, source, reservoir, mode of transmission, susceptible host, portal, or entry or exit of the infectious agent. covid-19 pandemic necessitates redrawing the framework of epidemic management in india. surveillance and monitoring are some of the important processes in epidemic management. the government launched the integrated disease surveillance project (idsp) in late 2004 as the response mechanism to outbreaks and epidemics. but, the idsp's current model of surveillance is not equipped efficiently for populationlevel infectious disease surveillance. this gap has been especially pronounced during the ongoing covid-19 epidemic of india. while idsp is supposed to identify outbreak and epidemic based on surveillance data, it doesn't provide updates on the current status of the ongoing covid-19 pandemic in india. predictability for newer containment areas is missing on idsp or other portals such as the national centre for disease control (ncdc). the multiplicity of agencies involved in epidemic surveillance and the absence of timely information have undermined the risk communication available to citizens. there are examples of the use of crowd sourced data to provide dynamic and updated information on the covid-19 pandemic both at the global level and in india. websites such as www.worldometer.info and www.covid19india.org have been widely used both by health experts and citizens to keep themselves updated. it would be useful to know about smart health solutions for epidemic management in india. in the current article, we have tried to identify and evaluate mobile health applications used for epidemic management in india. 2. methodology 2.1. eligibility criteria we used the following criteria to include studies for our systematic review: 1. original studies using primary data published in english language reporting about health issues in smart cities of india 2. original studies using primary data published in english language reporting use of ict (especially mobile health or mhealth applications) by frontline health workers or other categories of health staff of india 3. original studies using primary data published in english language reporting methods of epidemic management in india 2.2. search strategy we used the following search expressions on pubmed on 23 june 2020 to identify eligible studies: 1. smart [ti] and city [ti] and india 2. (smart city) and ict 3. ((mobile [ti] and health [ti]) or mhealth [ti] or ict [ti] or (information [ti] and communication [ti] and technology [ti])) and india (epidemic [ti] or pandemic [ti] or outbreak [ti]) and (management [ti] or surveillance [ti] or reporting [ti] or investigation [ti]) and india). 2.3. selection of studies and data extraction both authors independently checked the articles obtained through the search process for eligibility. both the authors used a standard data extraction sheet to collect the required variables (epidemic management, mobile health or mhealth, smart city, etc). the results were screened and finally eligible original studies were included for the eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e1 mobile health applications during epidemic management in india: a review 3 identification of smart ict solutions for epidemic management used in india. 3. results two articles were obtained by using the expression “smart [ti] and city [ti] and india” for search. the number of studies obtained by using the other three search strategies was 25, 181, and 174 respectively. title and abstracts of these studies were scanned to screen for eligibility. by using these search criteria, we could not find any studies on the use of ict for epidemic management in india for smart cities. hence we proceeded to conduct a narrative review of selected studies from this pool. 4. discussion 4.1 disease surveillance and epidemic management system in india many of the public health level disease control programs target one or all stages of the chain of infection of a particular disease. the concept of quarantine also emanated from the surveillance of plague in 13th century europe. eradication of smallpox was possible through surveillance of cases and containment. this was aided by the vaccination of all susceptible in the containment zone. eradication of poliomyelitis was possible through surveillance of the acute flaccid paralysis (afp) cases and vaccination drives among under-five children in the country. (banerjee et al, 2000) one of the recent examples of successful containment of a potential national-level epidemic was the outbreak of nipah virus (niv) in kerala. timely identification of the outbreak followed by appropriate containment measures helped dissipate the risk of the outbreak becoming a state or national level epidemic. surveillance was one of the keys to this success through quick identification of the niv source in pteropus bats, contact tracing of diagnosed cases, and risk communication with the public. (sahay et al, 2020). similarly, during the 2003 pandemic of severe acute respiratory syndrome (sars), surveillance and containment measures helped in mitigating the risk of spread to other countries by using effective quarantine, mobility control, and contact tracing (tognotti e., 2013). this strategy of quarantine is currently the primary step in controlling the current pandemic scenario of covid-19. at the national level too, efforts to establish a proper surveillance system have been done time and again. the government of india initiated its efforts towards a robust national level disease surveillance mechanism through the launch of the idsp in 2004 to obtain timely data for action on diseases having potential for outbreak and epidemic. (sharma et al, 2010) this was preceded by the national surveillance program for communicable diseases (nspcd) started in 1997-98 by the national institute of communicable diseases (nicd) in 5 districts on a pilot basis. idsp website mentions that there is a central surveillance unit (csu) in delhi connected to state surveillance units (ssus) in all states and union territories which are further connected to district surveillance units (dsus) in all districts. a laboratorybased it enabled disease surveillance system exists for epidemic-prone diseases. idsp has a system of rapid response teams (rrts) which is activated on suspicion of a possible outbreak of a disease from the local population. but the idsp network seems to be inefficient for population-level communicable disease surveillance. data for the 'rapid response' is collected every week through reporting by health workers, clinicians, and laboratories. subsequently, the team visits the concerned area to establish the presence of the outbreak, its nature, and its extent. most of these tasks are done in offline mode. periodic innovations such as sms based disease surveillance system for real-time monitoring was tried in andhra pradesh, but not scaled at the national level. there are 675 dsus in the country currently. csu provides supervision and feedback to prus. (das et al., 2020) a media scanning and verification cell was established in 2008 at ncdc, new delhi to monitor health news emanating from mass media. this team has trained epidemiologists and public health consultants and monitors global and national media to provide ‘early warning’. there are partners such as the website www.healthmap.org started by a group of researchers from boston children hospital which aids the process. the media verification is conducted manually by the central team. the team at ncdc activates the respective district surveillance officer to verify any public health news arising from their area and reported in the media. the last report of such media alerts on the idsp website was available for 2016. idsp also has a system of obtaining disease alerts directly from citizens through its 24x7 toll-free number 1075. an attempt to integrate health information for action has been made through the launch of the integrated health information platform (ihip). under this, an idsp mobile app has been developed for use by health workers, clinicians, and laboratory staff to record idsp related data in selected districts of india. 4.2 development of technologies for ict and health monitoring in smart cities computing technologies have dramatically changed the face of healthcare. examples are the provision of telehealthcare services (mhealth), electronic health records (ehrs), and personal health records (phrs) which made an appearance in the early 1990s in the usa. ehr technologies are getting harmonized by the integration of health data with other domains such as socio-economic, environmental, and behavioural and such integration is eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e1 rajgourab ghosh and sanjeev kumar 4 working towards precision medicine. (evans ra, 2016) mobile diabetes remote monitoring and self-management has been one of the early application areas of mhealth (istepanian et al., 2016). india being a vast country has its own limitations in providing healthcare especially specialized ones to farflung areas as well as densely populated city spaces and this is where the role of mhealth can be extremely important. in the times of current epidemics and pandemics like hiv, sars, niv, covid-19, etc. it assumes greater use and applicability. the use and accessibility of broadband and mobile services are now a reality in india where most of the city dwellers have mobile phones and broadband connections. a simple app registered to a user and connected to city health services can be a game-changer in case of any health-related emergency. services such as simple text messages have been tried successfully to improve treatment adherence. (lemay et al, 2012, stenner et al, 2012). the ict and mhealth based approach to coordinate care systems (tamrat et al, 2012) remote monitoring (rm) of disease and surveillance (place et al, 2014) can be effectively used to highlight their uses in a smart city-based approach to mhealth. under the smart city project for improving health infrastructure new delhi municipal corporation (ndmc) as a pilot project has installed health atm’s in few places in new delhi. automated health screening with integrated devices with checkup option of over 40 health parameters is being made available to citizens. a walk-in to the health atm allows a patient to have quick preventive health checkup on prescription of doctors. the patient can also communicate with a doctor through a web camera provided in the health atm (http://smartcity.ndmc.gov.in/content/projects/projectdetails/health-atms). these improvements in health infrastructure are a boost for providing mhealth benefits especially during an epidemic when appointments with doctors are rare. the use of big data has also transformed disease surveillance in developed countries. analysis of google search behaviour through the inbuilt tool google trends (™) has shown that epidemics can be predicted earlier than traditional surveillance methods. this method has been shown to produce an early warning of seven days for the h1n1 epidemic in the usa. similar google trends (™) analysis has been shown to have a time-lag correlation with other outbreaks of ebola virus disease, zika, dengue fever, chikungunya as well as covid-19 in many countries. but these studies have been done after the outbreaks and epidemics were over. google trends (™) provides such analysis at the city level too. similar big data analysis has been tried using data from twitter (™) and youtube (™) too. smart city administrators can use this tool to see whether it can predict outbreaks and epidemics in real-time or help in identifying hot-spots during ongoing epidemics. 4.3 mhealth in india: policies and actions the number of mobile connections in india has grown to over 1.1 billion with around 56 % of the subscribers living in urban areas. the internet subscribers are pegged at 38.02 per 100 citizens among these, the wireless internet subscribers approximately comprise 98 % of all internet subscribers. nearly 500 million people owned a smartphone in 2018 (coai, 2019). these emerging changes require evaluation of their role in the health system strengthening. india also adopted the national digital communications policy (ndcp) in the year 2018. due to this policy, it is expected that the use of telemedicine would increase, more so during the ongoing covid-19 pandemic. ndcp aspires to promote ict towards the achievement of sustainable development goals (sdgs). (51st world telecom and information society day, wtisd, united nations). targets of mhealth may be achieved in developing countries (malvey et al, 2017). health systems have developed and incorporated the use of mobile devices in their healthcare providers in india (majumder et al, 2015). a national digital health blueprint (ndhb) has been developed by taking advantage of the national digital health eco‐system (ndhe) facilitated by the ministry of health and family welfare (mohfw). the overall vision of nhp (national health policy) 2017 is the guiding light for ndhb. a specialized national digital health mission (ndhm) will implement the ndhb in a time-bound manner using a written action plan. there is a layered framework in ndhb. it consists of a vision and a set of principles as the core of the framework. the core leads to layers having hardware and other infrastructure, software data hubs, structural building blocks, indicators of standards, and regulations. websites (eg. https://www.nhp.gov.in/) and mobile applications (e.g. myhealth) provide access and delivery of the services. there are integrated call-centres for real‐time monitoring. it has been envisaged that most of the services would be delivered using the 'mobile-first' principle. (ndhb, mohfw, india, 2020). this kind of policy based on the push towards digitalization of medical infrastructure using ict and mobile technology will greatly propel the momentum towards the integration of mhealth components into a smart city framework very conveniently and will be greatly helpful in managing diseases and epidemics. 4.4 epidemics management through mobile-based technologies epidemics of communicable diseases can reach a larger susceptible population in a shorter period of time due to higher proximity in residential areas, workspaces, public transport, market places, etc. at the time of an epidemic, eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e1 5 all resources are stretched beyond limits and it is prudent to focus resources according to the severity and incidences of the disease. it is also desirable to save time and prevent program errors to avoid inappropriate risk communication with people. epidemics are characterized by case definition i.e. suspected, probable, or confirmed. indicators such as cumulative incidence (cui), secondary attack rate, infection mortality rate, etc. are used to describe the disease frequency. cui is the proportion of new cases developing among the total susceptible population at the beginning of the outbreak or epidemic. high-risk areas may be shown in different parts of the city and evolving scenarios of high cui or decrease of it (chen q et al., 2016). space-time scan statistics (stss) has been used to capture disease-specific time and location distribution through both retrospective and prospective methods. the stss has special utility in identifying the clustering of cases during epidemics. the number of cases with its location shared can help in assessing the control and command center of smart cities to decide how many and what type of personnel need to be deployed to manage that particular incident in realtime with lesser chances or errors. there are software such as satscan to obtain such results. (kulldorff et al, 1996 and kulldorff et al, 2001). other methods such as indicator-based surveillance (ibs) and event-based surveillance (ebs) are used for early detection of outbreaks. (pavlin et al, 2003) public health officials would receive reports of previously defined diseases in the form of structured and validated reports from laboratories in the ibs method. information obtained from non-health sources such as mass media, society emanating and propagating rumours, news stories, social media posts, blog contents, messaging systems, and websites, etc constitutes ebs. (cdc bulletin, may 30, 2019) automated intelligence methods such as opensource intelligence (osint) are other modes of surveillance (griggs et al, 2013, asi et al. 2018). by using one or more of these methods of surveillance, health-related data can be shared on a common platform and communicated directly to the smart city suite of apps, where the respective agencies involved in healthcare can intervene and can provide immediate relief. mobile devices can be used both by health workers and community-dwellers in field conditions to obtain primary data from the affected areas within the smart city ict framework to help in coordinating the epidemic management efforts effectively. it is cheaper to use mobile health technologies in comparison to many other health system efforts. mobile phones can be quickly equipped with data collection platforms or apps to transmit the data of individuals of the locality within the city with tagged geo locations and help in mapping of the disease. while there are plenty of apps in the android play store (google inc., usa) and app store (apple inc., usa) free or paid, a large number of them are local / country-specific in nature while others are global. these rely on validated data obtained from govt approved data centers like hospital or municipal reports whereas a large number of apps take and consolidate data from unvalidated sources like crowd sourcing platforms, social media sites, and third-party data sources. common examples during the ongoing covid-19 pandemic are www.worldometer.info, www.covid19india.org, etc. specific keywords were used such as infection, infectious diseases, outbreak, epidemic, pandemic, surveillance, public health, bioterrorism, cbrne and reported 17 applications for surveillance of one disease, seven for many diseases, and two apps related to possible bioterrorism agents (mohanty et al, 2019). these apps consisted of tracking in real-time on an interactive map, daily alerts, reporting of diseases/ outbreaks by users, and options to monitor many diseases together. another modality of epidemic management recently being used is based on crowd mobility data. disease spread is often promoted by the movement of people. therefore, by developing spatial-transmission models of infectious diseases, the epidemic spread can both be monitored and predicted. data incompleteness or unavailability for countries like india is an issue for such endeavors. by using methods of network analysis, the dynamics of disease transmission in epidemics can be elucidated better (ali and keil, 2006, neiderud c-j, 2015). analysis of data about the movement of people can provide evidence on public response to interventions such as social distancing guidelines. (buckee et al, 2020). such mobility networks can help in the identification of containment zones rather than incomplete lockdowns in cities when accessed through ict. the 'national informatics centre', (nic) india has established connectivity through broadband at 378 data centers. these data captures can complement idsp’s systems. however, bureaucratic labyrinths and challenges in the operationalization of the call centers of idsp and edusat (education satellite) are obstacles in the dependability and consistency of such high-end technology. (das et al, 2020). further, these mobility datasets can be used to assess where people's movements are originating from a disease hotspot and this might pre-empt public health authorities on the emergence of new clusters. any city faces immense challenges in controlling the spread of dangerous epidemics depending on biomedical waste management, decontamination of ambulances every time by thorough cleaning or fumigation. terminal decontamination of patient care centers or hospitals used to treat patients is also an important part of epidemic management. a smart city system would also monitor the time table and status of the above decontamination procedures of various hospitals in real-time using ict to instill confidence in city dwellers for the treatment of diseases during epidemics. in any handheld mobile communication device, the use of web-browsers can be of importance if there are no apps developed yet for a particular issue. mobile health applications during epidemic management in india: a review eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e1 rajgourab ghosh and sanjeev kumar 6 4.5 covid-19 as a case study for epidemics monitoring using mhealth. the 'covid-19' pandemic is a life-changing ongoing event in which almost the whole of the global population came to a halt. more than nine million people became sick and more than 0.4 million died. the lockdown in many countries has led to harsh living conditions for others. the highly communicable and deadly nature of the disease without any cure has forced people to stay away from contact and to maintain extreme hygiene and follow social distancing measures. the use of ict during the 'covid19' epidemic has been unprecedented. researchers have reported the use of apps in this regard. in a study, the google (™) play and the apple (™) app stores were searched using the terms ‘covid-19’, ‘coronavirus’, ‘pandemic’, an ‘epidemic’, individually. the authors also ran a keyword search for covid-19-related apps using the phrase ‘covid-19 mobile apps in india’. the search was conducted in the first week of april 2020 and updated on may 3, 2020. out of the 346 app information, the authors reported that 27 apps (54%) provided information on preventive strategies not targeted to covid-19, 19 apps (32%) were related to movementmonitoring, eight apps (16%) had functionality for contact tracing, and identification of hotspots (bassi et al, 2020). the government of india launched "aarogya setu", an app available in 11 indian languages. this has especially been designed for covid-19 contact tracing, warning, and self-assessment (www.mohfw.nic.in) while it helps in self-assessment using a questionnaire it can be used for contact tracing in real-time. it helps in alerting the user against any unintended exposure or contact with any probably infected persons or their proximity to any containment area or zones within the city using a bluetooth (™) interface on their smartphones. since the adoption of guidelines on home quarantine of asymptomatic patients, this or similar app can incorporate user fed data about the daily status of symptoms, physical parameters like temperature, heart rates, and oxygen saturation levels to preempt smart health systems to identify the need for a hospital transfer. the use of the "mygov'' app (www.gov.nic.in) has been a source of health information to people about the disease. the "ayush sanjivani'' app (www.ayush.nic.in) launched by the indian government can help people on the selection and use of immunity boosting herbal/ ayurvedic concoctions. the need for volunteers during the epidemic becomes paramount due to immense pressure on the existing health services. another website www.covidwarriors.gov.in provides a platform for trained human resources in health and volunteers to get deployed at short notice. this kind of volunteer-based service can be amalgamated into the smart cities' smart app concept. some states like delhi have already launched a "delhi corona” app (www.delhi.gov.in) for providing the statespecific data such as bed availability in state-run hospitals based on real-time occupancy of coronavirus affected patients among other useful statistics and information. the use of health atms upgraded with testing facilities can also provide a big relief for citizens of a smart city when it is difficult to get doctor’s appointments during an epidemic. these facilities when added to the smart city ecosystem of apps or suite of apps concept can quickly help in assigning the patient to the nearest hospital which has beds available and prevents any inconvenience to patients or health workers to find hospitals and save critical time and prevent early deaths. the community health workers (chws) in india were conceived for 'task-shifting' from higher-level medical providers, such as doctors and nurses, to lay workers, especially in response to the burden of the hiv epidemic (who, 2006). india has trained chws like “accredited social health activists” (ashas) and anganwadi worker (awws) who often provide door to door services. most of the states had already trained these chws in the use of ict and provided them smartphones during previous program implementation such as rmnch+a. during the ongoing covid-19 epidemic, these health care workers (hcws) have helped in preliminary screening in the community and obtain realtime data on epidemic status. the village resource centers (vrc) of indian space research organization are examples of improving connectivity between tertiary care hospitals and primary health care centers. (http://eresource.org/content/files/remote_rural_populati on.htm). such connectivity can be used between different quarantine centers or primary health centers in a smart city framework. services like referral of patients to higher levels of care or providing information about available beds for hospitalization can be achieved faster. while any epidemic causes severe mental stress and individuals are directly or indirectly affected by the disease, the affected persons can contact various helplines or use their mobile phones to chat with the counselors of government or ngos using ict enabled technologies even while staying in their containment zones. a 24×7 toll-free mental health rehabilitation helpline 'kiran' (1800-500-0019) was recently launched on 7 sept 2020. the helpline, which was developed by the department of empowerment of persons with disabilities (depwd), aims to provide the first line of counselling in response to the increasing mental health issues among people due to the covid-19 pandemic. among the worst affected by the epidemic are the hcws dealing with this epidemic daily. health staff, especially in the government system, often suffers mental health issues. these have an increased likelihood of escalation during the current covid-19 pandemic. a dedicated helpline for all frontline personnel is helpful. helplines have been started on mental health both at the national level and by many state government and health-related associations. for example, there is karnataka state helpline 104, ima helpline 999116375, and 999116376, as well as one from nimhans helpline eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e1 7 (080-46110007). while telephone helpline exists, an ict using a mobile app providing direct av communication links connected to the vital parameters detecting anxiety of the hcws can be activated to bring the support system including psychiatrists, families, and friends together to support the hcws in times of stress. one of the biggest fallout of the covid-19 pandemic has been the difficulty of non-covid-19 patients to obtain healthcare. this brought focus on another important constituent of mhealth which is telemedicine and telehealth. there has been recent improvement in internet infrastructure in the form of improved speeds, larger storage capacity, harmonized data transmission formats, better encryption, and safety in password protection. data safety norms have improved since the passage of the health insurance portability and accountability act or hipaa of 1996, usa. health information is now more readily available in digitized form. telemedicine has been scaled up especially during the covid-19 pandemic (devin et al, 2020). the indian government also revised the telemedicine guidelines in march 2020 to motivate the healthcare providers to increase its use without fear of legal hassles. the indian government also launched the "e-sanjeevani opd” as an online opd service to this effect. several mobile apps by the private sector like practo (™), lybrate (™), docsapp (™), etc. are already functional or being launched to newer regions. a large number of private registered medical practitioners (rmp) can opt for the inbuilt app-based diagnosis tools using ict enabled visuals and discussions and safely provide relief to patients right from their home. the issue of protection of data available on these platforms is a constant concern. digital information security in healthcare act ('disha') was drafted by mohfw which is to be subsumed in the ‘data protection framework on digital information privacy, security & confidentiality’ act being drafted by the ministry of electronics and information technology (meity). in the meantime, mohfw has circulated telemedicine practice guidelines with relaxations during the covid-19 epidemic on 25th march 2020. recorded video tutorials and patient selfhelp guides can be transmitted via video-sharing platforms like youtube (™). in case of communication which requires feedback and monitoring by doctors, live demonstrations in telemedicine apps are required. recently another mobile app the "eblood services” mobile application by mohfw was launched. indian red cross society (ircs) has partnered in this effort. another major necessity of many people during any disaster especially like these epidemics is the access to monetary resources, especially for those in containment zones or not having transportation facilities to go to banks or atms. doorstep delivery of cash was started by indiapost payments bank, department of post, govt. of india (www.indiapost.gov.in) using aadhar based digital verification of the person by the visiting postoffice personnel using the mobile technology and access. similarly provision of essential commodities like food and medicines was also compromised during the lockdown. doorstep delivery of ration and medicine and many other services using ict and telecommunication services helped tide over these difficulties for city dwellers where lockdown was more stringently enforced. all the above problems being faced by the people staying in cities can be very easily sorted out by using icts along with access to mobile devices and the citizens of smart cities can use the full features of mhealth and successfully sustain the deadly epidemic. 5. conclusion the ongoing pandemic of covid-19 has tested the earlier framed national policies and recent developments in ict interventions in real-time. in this review, we conclude that there have been many advances in the provision of mhealth interventions at national and state levels. ict solutions such as ihip of idsp, "aarogya setu" app, "mygov'' app, "ayush sanjivani'' app, “esanjeevani opd” app, “eblood services" app, “delhi corona" app, etc have successfully launched for healthcare provisions. innovations like the health atms connected to doctors or hcws to help citizens are very useful towards the integration of mhealth in the smart cities framework especially during epidemics. though we couldn't identify any published ict intervention to manage epidemics in smart cities of india, we believe that the recent advances in mobile and ict related technologies introduced at national and state levels can be customized for this purpose too. the rapid advance and access of handheld or mobile devices to the citizens in cities in general and smart cities, in particular, should usher in a wave of ict and mobile telecommunication based medical interventions. the recent policy decisions by the government of india and the release of ndhb, 2020 has brought a much-needed boost in this direction. the principles of equity, efficiency, and foresight relevant in unleashing full features of mhealth for smart cities in india need to incorporate the opportunities presented by the amalgamation of icts into these policy changes. the implementation of timelines will benefit mhealth and its incorporation into smart city networks and disease management much more easily. the importance and seamless integration of citizens' health data with municipal, health, and other public services using the mhealth platform in a smart city framework during an epidemic cannot be more emphasized with the current changes for densely populated cities of india. acknowledgements the authors acknowledge their families and host institutions for providing them time and support to complete this manuscript. mobile health applications during epidemic management in india: a review eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e1 rajgourab ghosh and sanjeev kumar 8 references [1] ramaswami a, russell ag, culligan pj, sharma kr, kumar e. meta-principles for developing smart, sustainable, and healthy cities. science. 2016; 352(6288):940-943. doi:10.1126/science.aaf7160 [2] majumder s, aghayi e, noferesti m, et al. smart homes for elderly healthcare-recent advances and research challenges. sensors (basel). 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[36] mohfw, government of india https://www.mohfw.gov.in/pdf/hcwmentalhealthsupport guidancejuly20201.pdf mobile health applications during epidemic management in india: a review eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e1 http://www.who.int/hiv/toronto2006/takingstockttr.pdf towards strategies to capture and retain mobile ticketing customers 1 towards strategies to capture and retain mobile ticketing customers marta campos ferreira1,2,*, catarina ferreira1 and teresa galvão dias1,2 1faculty of engineering, university of porto, rua dr. roberto frias, 4200-465 porto, portugal 2inesc-tec, faculty of engineering, university of porto, rua dr. roberto frias, 4200-465 porto, portugal abstract introduction: when compared to traditional ticketing systems, mobile ticketing has several advantages, allowing ubiquitous and remote access to payments, avoiding queues and replacing notes and coins. it also allows service providers to reduce their costs and achieve operational and productivity gains. however, while some cities have implemented mobile ticketing solutions on their public transport network, the adoption of such services appears to have limited success. the causes that lead to such a low rate of use of the service are still unknown. objectives: this paper presents an in-depth study of the reasons that lead mobile ticketing customers to adopt or abandon this type of service and establishes a series of strategies to attract and retain customers. methods: it uses the city of porto, portugal, as an illustrative example, where a mobile ticketing solution, called anda, was launched. customer complaints related to 6 months of using anda were analysed and usability tests were carried out with real customers in the context of use. results: this analysis allowed to identify a series of factors that lead people to adopt or abandon this type of services. then, a series of strategies were defined and identified that allow to capture and retain mobile ticketing customers during the various stages of the mobile ticketing lifecycle: user onboarding, user engagement, user retention and user reinstall. for each of the stages of this life cycle, the main concerns to be considered were also listed, a series of tactics were defined to reverse the abandonment trend and a series of kpis were specified to measure the efficiency of the strategies. conclusion: this paper fills an important research gap in the literature, being very useful in shaping future strategies for successful mobile ticketing solutions. keywords: mobile ticketing, urban passenger transport, customer loyalty, customer churn. received on 31 march 2021, accepted on 08 april 2021, published on 09 april 2021 copyright © 2021 marta campos ferreira et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.9-4-2021.169182 1. introduction as the world becomes increasingly interconnected, the adoption of technology is one of the most influential factors in human progress. immediate access to the internet or possession of a smartphone is now taken for granted in many advanced economies. it permeates commerce, social interactions, politics, culture and everyday life [1]. in addition, while high-income economies continue to use more *corresponding author. email: mferreira@fe.up.pt internet and have more high-tech devices, in recent years, there has been a tendency for emerging countries to follow and copy these behaviors. these patterns are now global, regardless of how fast they grow in each type of economy. in 2018, more than 3.5 billion people, 47% of the world's population, were connected to the mobile internet [2]. internet access and innovative services facilitate access to modern public health services, free education services and financial services, including mobile payments. thus, the mobile phone has become a fundamental gateway to the digital economy. the general adoption of mobile devices to eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e5 http://creativecommons.org/licenses/by/3.0/ marta campos ferreira, catarina ferreira and teresa galvão dias 2 pay for goods and services is a widespread reality [3][4][5]. mobile payments are designed to provide users with a secure, convenient, consistent, efficient and reliable payment experience [6]. however, security and privacy issues, as well as the interaction and reliability of the service, can be some of the concerns that users share [7]. mobile payments can be applied to various sectors, such as public transport. there, mobile payment comprises prepaid options where mobile phones act as a wallet and ticketing itself where passengers buy and authenticate tickets on their mobile phones. the last resort is only possible due to a service based on emerging technology called mobile ticketing. as with mobile payment services, mobile ticketing is a process in which customers can order, pay, obtain and validate tickets only on mobile devices and without requiring a physical ticket. a mobile ticket contains a single ticket check, varying according to the technology used. while some mobile ticketing systems require validation via sms text [8], a qr or barcode [9], others require near field communication (nfc) [10]. mobile ticketing services solutions take advantage of wireless communication and thus aim to free customers from difficult purchasing decisions, allowing easier access to other services. the convenience of this technology makes it fully adequate to deal with the problems of urban congestion and stress in metropolitan areas. as public transport improves passenger mobility, by means that are safe and of high quality, it can be seen as the necessary solution for urban sustainability. however, the complexity of the transport networks and the lack of continuous options reduce the attractiveness of the sector. long waiting times in the queues to purchase and validate tickets make people abandon this solution and choose to use their own vehicle. mobile ticketing in the public transport sector can offer an innovative, ubiquitous and engaging service [11]. although some cities have implemented mobile ticketing solutions on their public transport network, the adoption of such services appears to have limited success [12]. the causes that lead to such a low rate of use of the service are unknown. however, researchers claim that churn factors are somehow related to the acquisition phase or the user experience [13]. others claim that usage rates are still low because mobile payments require customers to change their behavior to deeply entrenched payment habits [14]. in an attempt to understand the phenomenon, the authors [14] studied the failure of three cases of mobile payment in switzerland: the m-maestro project, the european initiative compliant with visa, and mobile payments by postfinance. postfinance initiative, for instance, failed to provide additional value to customers and local merchants. they faced significant difficulties in finding a workable balance between interoperability and the ease of use for customers, resulting in a clumsy solution that suited the physical environment and the behaviors associated with payments at local stores. at the end of the study, the authors acknowledge that more research is needed to formulate a more complete structure, based on the richest process data from the mobile payment diffusion trajectories. on the other hand, despite recognizing that, despite the growing number of mobile payment applications, very few solutions have been successful, [15] selected some of those few successful platforms to study the success factors. the authors conclude that the success of mobile payment platforms lies in the platform’s ability to balance the reach (number of participants) and the range (features and functionality) of the platform. in the city of porto, portugal, a mobile ticketing application, called anda was deployed in june 2018 [16]. an analysis of the level of use of the service allowed us to conclude that there are many customers who have never used the application, although they have downloaded it, and others who, despite having already used it, preferred to give up the application and continue to use the traditional ticketing system. this reality occurs with a series of similar mobile ticketing applications on the market and the literature fails in explaining this phenomenon. therefore, this paper aims to identify and analyze the customer adoption and churn factors of mobile ticketing services and to propose strategies for customer acquisition and retention. this work is based on an in-depth analysis of the case of porto, portugal. half a year of complaints and usage data for anda were analyzed. these are data on the interaction between users and customer support made by phone, email and social networks in addition to data on the history of using the app of those who complain. additionally, usability tests were carried out on the anda application, with real users in the context of use. thus, it is possible to establish the causal relationship between all the extracted data and then to identify the reasons for the adoption and the churn factors. based on this, the life cycle of a mobile ticket customer can be defined from customer onboarding to customer acquisition, customer retention and customer reengagement. for each of those stages, the critical success factors are identified and a set of useful strategies is set to attract and delight customers. in the next sections the paper methodology is described, followed by the results of the analysis of complaints and user validation data. the discussion of the results is presented together with a proposal of service improvement in each of its stages. the final section presents the conclusions. 2. methodology this paper aims to identify customer adoption and churn factors of mobile ticketing services and define customer capture and retention strategies. it uses the city of porto, portugal, as an illustrative example, and follows complementary methodological approaches such as the analysis of complaints and suggestions from customers and usability tests to the application of mobile payments. each of these approaches is detailed below, after a brief overview of public transport in the metropolitan area of porto eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e5 towards strategies to capture and retain mobile ticketing customers 3 2.1. public transport in the metropolitan area of porto this is the body text with no indent. this is the body text with no indent. this is the body text with no indent. metropolitan area of porto (amp) is composed of seventeen municipalities in an area of 2.040 km2 and has a population of about 1.7 million inhabitants. the public transport system consists of three subsystems: buses, light subways and suburban trains. the three are all integrated into a multimodal public transport ticketing system, called andante. this system was originally designed for the use of a smart card with contactless rfid technology. passengers can load the andante card with occasional trips or with a monthly pass, depending on the number of trips they intend to take during the month. it is an open system, in which the passenger must validate the card at the beginning of a trip and whenever he changes vehicles, touching the travel card in the ticket reader. amp is divided into 124 geographic travel zones and the journey fare depends on the number of zones crossed during a trip. the greater the number of zones travelled, the more expensive the ticket is. andante is also a time-based system because passengers can change their mode of transport as many times as they want during a certain period, but when the time is up, the ticket will no longer be useful. the complexity of the andante system makes it more difficult for passengers to become familiar with the location of zone boundaries and to understand how the crossing system works and what type of tickets they should buy for a given trip. it is in this context that the anda mobile application emerges, whose main purpose is to facilitate access to public transport services. anda is based on a check-in/be-out scheme, requiring an intentional user action when entering the vehicle (tapping the mobile phone on the ticket reader) and the alight station is automatically detected by the system, as well as intermediary stations along the trip. the mobile phone interact with ble beacons installed in metro and train stations and inside buses, through bluetooth connection, to locate the customer along the transport network [16]. the price to be paid by the customer is calculated through a fare optimization algorithm, which minimizes the cost for the passenger, freeing them from difficult purchasing decisions [17]. anda was launched in june 2018, having been widely publicized in the media and accompanied by a massive communication plan. the objective was not only to disseminate the new service, but also to explain how it works. it involved news in tv channels, newspapers and social networks, placing outdoors and stands at stations, decorate vehicles, distribute flyers and informational leaflets, and having promoters presenting the service and helping customers. 2.2. customer complaints and suggestions analysis in order to have a better understanding of how to capture and retain customers, it is crucial to first assess and then become fully informed about the behavior of current users. by identifying usage patterns, as well as their trend, it is easier to see the indicators of customers who are about to churn. customer feedback is a valuable tool to understand how the service has been communicated to current and potential users. complaints analysis allows to understand how users perceive the application and what are their expectations and needs about it. this makes it easier to recognize the vital areas for improving communication with the customer and, therefore, improving the service as well. since its complete implementation, customers using the anda application interact daily with the customer service, through several channels, such as telephone, e-mail, facebook, google play and physical stores. this interaction can serve several purposes, such as asking questions, reporting errors, or making suggestions for improvement [18]. the information from the various channels is collected on a single platform, to be further processed and analyzed. the object of this study is the complaints received by the intermodal transports of porto (tip) during 6 months of using anda from september 2019 to february 2020. the choice of this time interval is related to the fact that it is a normal period of use, only with regular updates of the application, but without major changes that would imply a greater influx of complaints. the analysis included three main aspects: complaints, complainants and the effects of complaints on the use of anda. firstly, the data on complaints includes the date on which the statements were made, the reasons for which they were made, the responsible carriers and the means of communication through which they were made. second, with regard to claimants, information is collected about their social profile whether they belong to a certain age group or benefit from help due to their social status and the type of ticket they use most. information was also collected on the distribution of claimants in the different months. finally, to assess the impact of complaints on usage, the application's validation history data is considered. to perform a descriptive analysis of the data gathered, ms excel and rapid miner software were used. 2.3. usability testing usability testing is a tool designed to determine the extent to which an interface facilitates a user's ability to complete routine tasks [19]. n this case, the main objective was to understand how intuitive the application is for new users who have never had contact with it and, at the same time, to identify problems in the daily interaction of regular users. the test results were expected to generate relevant and valuable suggestions to make the app clearer and accessible to everyone using public transport. it was also expected that the test would result in a list of usability problems that lead consumers to abandon this type of service. eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e5 marta campos ferreira, catarina ferreira and teresa galvão dias 4 the anda usability tests were carried out with eight participants (according to [20], between 5 and 8 users are sufficient to achieve meaningful results). of the chosen customers, four were regular users of anda for over a year and four were people who had never contacted the application. of the regular users, two people from the selected ones were users who presented complaints to the system during the period under analysis. the test administered to users was divided into three parts. the first part consisted of a pre-test questionnaire to characterize the participants. the objective was to collect demographic information and information on the level of experience with the andante and anda system. the second part consisted of asking users to perform 16 tasks in the application. they were asked to think and speak aloud while performing each task, in order to record their experience. during the execution of the task, the time they took to complete was measured. in the end, participants were asked to rate the task in terms of difficulty and usefulness on a scale of 1 to 4, where 1 is very easy and useless, and 4 very difficult and very useful. choosing a scale with an even number of options has to do with avoiding neutral responses. the third part consisted of a post-test interview with focused questions and open answers. the objective was to assess the general perception of users in relation to the application and its usability. questions were asked about the features they liked the most and the ones they liked the least. likewise, suggestions were made for improvements and strategies that would have an effect on the acquisition of new users. a question was also asked about the security of the app and whether they would suggest the app to someone who doesn't know it. as the purpose of the test was to assess problems that could arise during normal use of the application, the test was carried out in context. it was carried out with each participant individually. that is, only the user and the tester were presented so that there was no external influence on the participants' behavior. for each participant, a trip was made, whose initial and final stops were chosen by them. the means of transport used was also chosen by users. the tester was responsible for presenting the application to users, explaining the purpose of the test and how it would be performed, reading the tasks and questions on the test form, asking for permission to record audio and video, writing the responses and comments of the participants, timing the completion of each task and taking notes on the behavior observed throughout the test. in addition, in the final part of the test, the tester was responsible for interviewing each user in order to collect their opinion, highlights and insights about the application. 3. results this section presents the results of the analysis performed, with regard to the analysis of complaints and suggestions and to the usability tests. 3.1. customer complaints and suggestion analysis this section starts by presenting the data of the complaints, followed by the presentation of complainers’ characterization. finally, the conclusions resulting from the crossing of data from the history of usage of anda app and the complaints data are presented. the complaints during the period under review, the total number of complaints received by anda app is 1223. of these, only 68% (832 complaints) were submitted by different users, which means that 32% of users completed at least more than once. so far, most of these records (95.5%) are resolved and closed, but those that are still open require action by third parties for example, external technical teams. the problems that can arise in the use of anda are several and can be categorized by the reasons that caused them. the main reasons are related to the validation of the trip, login and registration in the app, the correct filling of the trips, the consultation of personal data, the associated tariff and the disregard of intermediate stops. fig. 1 shows the distribution of the main reasons for complaints. in addition, there are other reasons that can lead to a complaint beacons, payment methods, questions, enrollment, data changes, suggestions for improvement, inspection and account deletion but the total number of records for these reasons is not relevant to considered in this study. porto's intermodal transport consists of 19 public transport operators and anda can be used in all of them. in addition, it is important to mention that 76.3% of complaints are not related to the trip itself and to the operators, but to issues related to the application or billing. complaints to carriers are 23.7% of the total. anda's complaints can be submitted by the most diverse means of communication, but two of them stand out for their great use: the application's crash report (64%) and email (32.5%). among the rest are links (3%), the official facebook page (0.4%) and the google play store (0.2%). figure 1. distribution of complaints by reason eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e5 towards strategies to capture and retain mobile ticketing customers 5 the complainers the total number of anda users from september 2019 to february 2020 is 5759 and 14% of them are complainers of the service. usage data allows us to know that, on average, about 3,103 people use the app to travel on porto's transport services per month. likewise, it is known that about 203 complaints are filed per month. in fig.2. it appears that, over the period studied, the relationship between the number of users and the total number of complaints received remained practically constant. based on the validation data, it is known what types of tickets were purchased by the claimants. most people who complain purchase single tickets (69.9%), that is, for occasional trips. in addition, tip groups users by social profile according to their age group or social status. by analyzing these data, it can be seen that the majority of complainants belong to the “normal” social profile (49.1%) which means that they are adults who do not benefit from any type of discount. among the remaining profiles are people who have lower rates (social +) (44.9%), university students (3.6%), students under 18 (6.4%), and seniors over 65 (0.7%). the distribution of users by social profile also allows knowing that the users who most complain are the “normal” and “social +”. also, fig. 3 shows that in all groups, the number of complaints is higher than the number of complainers, which, once again, reaffirms that there are users complaining more than once. figure 2. number of complainer vs number of complaints, by social profile. the effects of the complaints finally, to understand the effect of complaints on the use of anda, it is necessary to cross the data of both – complaints and validations. by knowing the complainers, it is noticeable their influence on the use of the application. likewise, it is interesting to find out whether the use-complaint relationship is uni or bilateral. when categorizing by type of users, as seen in fig. 4a, it is possible to see that 78.7% of the complainers are people who use the app to make trips. however, 17.6% of app users complained without ever having used it 9.9% complained before using it and 7.7% complained without ever having used it. in addition, 3.7% of complainers submit their statement at the time of their first trip. to deepen this connection, it was also assessed the use of the app on trips after the last complaint. in fig. 4b it can be seen that the majority (79%) continued to use anda, but 21% did not do it again. 3.2. usability testing in carrying out the usability test, four people who use anda on their usual trips regular users and four people who had never been in contact with the app first-time users were selected. the choice of participants took into account some aspects that were relevant to be analyzed. demographically, people of both genders and all age groups were selected in order to get in what sense the existing problems can result from generational differences. participants with different degrees of knowledge of the intermodal andante system were also chosen. on the one hand, participants were selected who usually know and use this transport network and, on the other hand, participants who use public transport but with less regularity. all regular figure 1. number of users vs. number of complaints, per month a b figure 4. a. types of complainers; b. effect of the last complaint eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e5 marta campos ferreira, catarina ferreira and teresa galvão dias 6 users chosen are customers who have been using the app for at least a year. another aspect that was considered in the choice of the test participants concerns the complaints made to the application, during the period under analysis september 2019 to february 2020. from the regular users, some were chosen who presented complaints in that period and others who did not. the demographic information of the participants, as well as their level of knowledge of andante, and the complaints presented to anda are detailed in table 1 and table 2 respectively. table 1. test participants demographics . table 2. test participants knowledge of andante system first-time users regular users inexistent 0 0 little 1 0 reasonable 1 0 good 1 1 very good 1 3 through the performance of usability tests, the perception of a significant difference in the behaviour of regular users and first-time users was clear (see fig. 6 and fig. 7). while the experts are very comfortable navigating the app and accessing the various screens available, consumers who had never been in contact with anda felt6060 more lost and insecure during the test. behind this problem is the lack of guidance for users in the first interaction with the app. the need for a feature or screen that explains how to use the app makes the entire user experience based on a long and timeconsuming trial and error approach. the technical problems arising from the interaction with the app – be it the long activation time of payment methods, the inability to end the trip immediately, the difficulty in understanding whether the password has been changed, among other are concerns that must be addressed. the greater the number of usability problems that users encounter, the greater their dissatisfaction with the app will become and consequently, the greater the likelihood that they will churn the service. the fact that users feel that sending a crash report will not be effective is also a problem that must be avoided. complaints to the service aim to understand the problems that arise during the use of anda so that they can be resolved. when customers feel that their statements will not be analysed and that their opinion is not relevant to the service, they can abandon the app. finally, in addition to the problems already mentioned, users said that the lack of exposure to the app is the main cause of little use of anda. regular users have reported that they generally need to present and explain to others who travel with them that it is possible to travel on tip through a mobile ticket application. in this sense, they consider that the realization of advertising campaigns directed to different types of users students, families, the elderly, etc. it would be an asset. first-time users regular users complainers noncomplainers age f m f m f m 18-29 2 1 0 0 0 1 30-44 0 0 1 0 0 0 45-59 1 0 0 1 0 0 60 or + 0 0 0 0 1 0 figure 5. perceived difficulty of tasks performed figure 6. perceived usefulness of tasks performed eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e5 towards strategies to capture and retain mobile ticketing customers 7 4. discussion the analysis of the complaints and usability tests opens the ground for several reflections and sets the path for the future development of the mobile ticketing services. in this sense, customer adoption and churn factors regarding mobile ticketing services are identified, as well as customer capture and retention strategies. 4.1. customer adoption and churn factors the analysis of complaints and usability tests made it possible to identify the factors that lead public transport customers to use mobile ticketing applications and the reasons that motivate the churn, which are presented below. adoption factors accessibility of the mobile applications: not only being able to travel, but also paying for a trip using just a smartphone, is seen as a major trend in the future. users consider it an advantage not to need the smartcard to travel and, instead, to be able to buy the ticket, validate it and even present it for inspection on the mobile phone. flexibility of the mobile applications: the fact that these applications are compatible with different transport operators and make it possible to travel on different means of transport be it buses, subways, trains, among other just using the mobile phone is extremely useful. ubiquity of the service: not having to go to a store or vending machines to purchase tickets is one of the main benefits of using these apps. being able to avoid the queues to buy tickets is extremely convenient for users. sustainability of the service: the fact that these applications are environmentally friendly and, unlike traditional travel methods, do not require physical cards paper or plastic is also a reason why users choose these applications. churn factors bad first-time user experience: the first contact with the application is essential. if at first users feel that the service provided does not meet their expectations, they will stop using it. recurrence of usability and technical problems: there are problems with mobile apps. however, if these problems have become recurring and have not been resolved in a timely manner, this is a reason for users to stop using the application. lack of response to customer feedback: following the usability problems that may arise, if users submit complaints to the service and, therefore, do not obtain a favourable response or resolution, it is possible that they will stop using the application. depreciation of customer value: customers of mobile ticket applications like to feel that using these applications has some advantage over traditional methods. when mobile ticketing customers feel that the application does not benefit them from traditional ticket customers, the first ones will stop using it. negative influence of lost customers: customers may abandon the service for a variety of reasons. if the reasons for abandonment have to do with the bad user experience, these lost users can communicate a wrong image of the application to current and potential customers, causing them to abandon the service as well. the lack of advertising campaigns: the lack of knowledge about the existence of mobile ticketing applications is another problem that must be addressed. the discriminatory factor for people who use this type of app in public transport compared to the majority who use traditional tickets is worrying. social pressure can lead users to abandon the service. the lack of mass and targeted advertising campaigns is at the root of the lack of consumer awareness. 4.2. customer capture and retention strategy after studying the effect of comparing the results of the analysis of complaints and usability tests, as well as the main factors of adoption and abandonment of mobile ticketing applications, it is essential to define a strategy to capture, acquire and retain new clients. in this sense, four fundamental stages were identified in the process of using this type of applications: user onboarding, user engagement, user retention and user reinstall. for each stage of the life cycle, the main aspects to be considered are identified according to the results obtained and a series of tactics are established to increase the value of the service for customers. the different segments of users, as well as the appropriate channels to reach them, are also considered in the proposal presented. user onboarding the data referring to users who complain without having ever used the app are indicators that their first interactions with the service are not meeting their expectations. for technical or usability reasons, some users do not initially find the type of experience they were looking for and give up on the application before actually using it. to counter this trend, table 3 lists a number of tactics that can be put into practice. regardless of the user segment, the application should present a welcome message on first use, encourage users to sign up emphasizing the benefits of the eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e5 marta campos ferreira, catarina ferreira and teresa galvão dias 8 service and display a brief demonstration of the application and its main features. table 3. strategy to improve user onboarding for different types of user segments. user segment tactics channels installed but not registered • welcome users on the app and introduce the main features of the app. • encourage the register in the first 24 hours. • incentivize registration with rewards on the app (cashback, ticket discount). • in-app notifications • push notifications registered but not activated • welcome app users after the register. incentivize them to complete the payment information. • stimulate users to make their first travel using the app, with rewards (cashback, ticket discount). • in-app notifications • push notifications • sms • email • reminders registered and activated • encourage greater use of the app with rewards (cashback, ticket discount). • in-app notifications • push notifications • sms • email • reminders user engagement once familiar with the service, users need to be converted and start using it consistently and frequently. the data collected shows that 9.9% of the complainants are people who complained before traveling with the app. in addition, 3.7% are users who complained shortly after using the app for the first time. if these values are not taken into account and if these users are not motivated to give the service a new chance, it is very likely that they will churn it. at this stage of the cycle, the service should encourage the consumer to perform actions on the app be it filling out payment information or taking a trip stimulating the commitment already established. notifications with special offers are also useful to promote constant use and encourage repeated interactions for example, trips of the same type or with similar routes. table 4 shows the different strategies to be targeted at different users at the engagement stage. table 4. strategy to improve user engagement for different types of user segments. user segment tactics channels onboarded but non-converted • urge users to make their first travel using the app – push different use cases at different times. • create custom campaigns offering rewards for first users (cashback or travel discount). • in-app notifications • push notifications first-time converted • confirm completion of first travel. thank the choice of service, up to 5 min after it finishes. • encourage users to keep using the app. • push notifications • sms • email repeat converted • encourage continuous use through targeted personalized campaigns based on usage patterns. • promote different services with rewards (cashback or travel discount). • in-app notifications • push notifications • sms • email users not completing actions (abandonment) • notify users 1 hour and 24 hours after they abandon a task. • push notifications • sms • email • reminders no activity • remind users that have no activity in the app in the last 30 days. • push notifications • sms • email user retention mobile ticketing applications services tend to have difficulty retaining users. a consistent and constant customer base is the main basis for the sustainable growth of any service. at this stage, the data on the number of complaints and the number of claimants for each social profile are noteworthy. while in the "normal" profile the number of complaints per claimant is approximately 3/2, in the rest the values increase by approximately two times. this information can become relevant as users dissatisfied with the service tend not only to abandon it, but to negatively influence potential new users. the more complaints a person sends, the greater their dissatisfaction with the service and the greater the likelihood of canceling it. eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e5 towards strategies to capture and retain mobile ticketing customers 9 to optimize retention, users can be motivated to repeat the same interactions with the app in exchange for discounts on regular travel or reimbursement of the amount to be paid at the end of each month. careful and attentive analysis must be carried out to control the retention rates of current and potential users, as well as personalized promotional campaigns and reminder of available offers. table 5 shows some tactics to be implemented. table 5. strategy to improve user retention for different types of user segments. user segment tactics channels engaged but not loyal (hibernating) • communicate with the user and understand what’s their perception of the app. send messages to obtain an assessment of the service. • send customized campaigns with "we miss you” messages. • in-app notifications • push notifications • email engaged and loyal • ensure app rating and reviews. • reward loyalty with travel discounts or cashback. • in-app notifications • push notifications • email user reinstall the reasons for uninstalling a mobile application can be of the most varied types, from problems with interaction with the interface, inefficiency of features, low performance or disastrous user experience. at this stage, it is important to consider the data relating to the effect of the last complaint. in other words, 21% of claimants have stopped using anda since the last complaint. this aspect means that the reasons that motivated the complaint or the resolution obtained in the complaint became the reason for discontinuing the use of the app. thus, the likelihood of uninstalling the application increases the more time that has passed since the last time it was used. to recover inactive or discontinued customers, conducting an analysis of user behavior, as well as requesting feedback from former customers, can be useful to understand the points of friction between them and the application and possibly eliminate them. to recover lost users, targeted promotional offers can be put into action. table 6 presents some strategies to be used. 4. conclusion the success of mobile ticketing applications depends a lot on the service provider's ability to attract and retain customers. this article presents an in-depth study of the reasons that lead mobile ticketing customers to adopt or abandon this type of service and establishes a series of strategies to attract and retain customers. table 6. strategy to improve user reinstall for different types of user segments. user segment tactics channels converted but disengaged • run customized campaigns with the latest offers. • update users’ preferences. suggestion on discounts based on new preferred routes. • send reminding messages about the advantages of the service. • email churned • run personalized email survey seeking feedback to understand the reasons for app uninstall. • run “we miss you” or “check what your missing” campaigns, highlighting new promotions and cashback offers. • run “we’re just a click away” campaigns, following the suspension policy between 43rd to 50th days after uninstalling the app. • email re-acquired • run personalizes “welcome back” campaigns, highlighting new promotions and cashback offers. • in-app notifications • email this study uses the city of porto, portugal, as an illustrative example. in june 2018, a mobile ticketing application called anda was launched to the market. this application allows passengers to pay for the use of public transport in the metropolitan area of porto, without the need to know the fares in force or use physical cards. despite its ease of use, it appears that its use falls short of expectations, which is the case with many services of this kind around the world. eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e5 marta campos ferreira, catarina ferreira and teresa galvão dias 10 thus, customer complaints related to 6 months of using anda were analyzed and usability tests were carried out with real customers in the context of use. this analysis allowed to identify a series of factors that lead people to adopt this type of services such as the accessibility and flexibility of mobile applications and the ubiquity and sustainability of the service. on the other hand, factors that underlie customer churn were identified, such as having a bad first-time user experience, recurrence of usability and technical problems, lack of response to customer feedback, depreciation of customer value, negative influence the lost customers and lack of advertising campaigns. taking into account these factors, a series of strategies were defined and identified that allow to capture and retain mobile ticketing customers, during the various stages of the process of using mobile ticketing applications: user onboarding, user engagement, user retention and user reinstall. for each of the stages of this life cycle, the main concerns to be considered were also listed, a series of tactics were defined to reverse the abandonment trend and a series of kpis were specified to measure the efficiency of the strategies. from the point of view of future work, the methodology used and the results generated open the door to a series of other investigations. applying this method to mobile ticketing applications in other cities or deepening the applicability of the strategy of attracting and retaining customers in a real context makes it possible to carry out other scientific work relevant to the areas of design and service management. acknowledgements. the authors thank transportes intermodais do porto for providing the data necessary for this work. references [1] poushter, j.: smartphone ownership and internet usage continues to climb in emerging economies. pew res. cent. february, (2016). [2] gsma: the state of mobile internet connectivity 2020. gsma reports. (2020). [3] garrett, j.l., rodermund, r., anderson, n., berkowitz, s., robb, c. a: adoption of mobile payment technology by consumers. fam. consum. sci. res. j. 42, 358–368 (2014). https://doi.org/10.1111/fcsr.12069. [4] abrahão, r. de s., moriguchi, s.n., andrade, d.f.: intention of adoption of mobile payment: an analysis in the light of the unified theory of acceptance and use of technology (utaut). rai rev. adm. e inovação. (2016). https://doi.org/10.1016/j.rai.2016.06.003. [5] fontes, t., costa, v., ferreira, m.c., shengxiao, l., zhao, p., dias, t.g.: mobile payments adoption in public transport. transp. res. procedia. 24, 410–417 (2017). https://doi.org/10.1016/j.trpro.2017.05.093. 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[9] ferreira, m.c., fontes, t., costa, v., dias, t.g., borges, j.l., cunha, j.f. e: evaluation of an integrated mobile payment, route planner and social network solution for public transport. in: transportation research procedia. pp. 189–196 (2017). https://doi.org/10.1016/j.trpro.2017.05.107. [10] ferreira, m.c., cunha, j.f. e, josé, r., rodrigues, h., monteiro, m.p., ribeiro, c.: evaluation of an integrated mobile payment, ticketing and couponing solution based on nfc. (2014). https://doi.org/10.1007/978-3-319-05948-8_16. [11] ferreira, m.c., nóvoa, h., dias, t.g., cunha, j.f. e: a proposal for a public transport ticketing solution based on customers’ mobile devices. in: procedia social and behavioral sciences. pp. 232–241 (2014). [12] dahlberg, t., guo, j., ondrus, j.: a critical review of mobile payment research. electron. commer. res. appl. 14, 265–284 (2015). https://doi.org/10.1016/j.elerap.2015.07.006. [13] cheng, s.k.: exploring mobile ticketing in public transport an analysis of enablers for successful adoption in the netherlands expertise centre for e-ticketing in public transport. (2017). [14] ondrus, j., lyytinen, k., pigneur, y.: why mobile payments fail? towards a dynamic and multi-perspective explanation. proc. 42nd annu. hawaii int. conf. syst. sci. hicss. (2009). https://doi.org/10.1109/hicss.2009.510. [15] staykova, k.s., damsgaard, j.: adoption of mobile payment platforms: managing reach and range. j. theor. appl. electron. commer. res. 11, 65–84 (2016). https://doi.org/10.4067/s0718-18762016000300006. [16] ferreira, m.c., dias, t.g., falcão, j.: is bluetooth low energy feasible for mobile ticketing in urban passenger transport? transp. res. interdiscip. perspect. 5, 100120 (2020). https://doi.org/10.1016/j.trip.2020.100120. [17] ferreira, m.c., dias, t.g., cunha, j.f. e: codesign of a mobile ticketing service solution based on ble. j. traffic logist. eng. 7, 10–17 (2019). https://doi.org/10.18178/jtle.7.1.10-17. [18] duarte, s.-p., ferreira, m.c., sousa, j.p. de, sousa, j.f. de, galvão, t.: improving mobility services through customer participation. in: advances in mobility-as-a-service systems improving (2021). [19] dumas, j.s., redish, j.c.: a practical guide to usability testing. intellect books, exeter (1999). [20] dumas, j.s., fox, j.e.: usability testing: current practice and future directions. in: the human-computer interaction handbook (2007). eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e5 accessibility of the mobile applications: flexibility of the mobile applications: ubiquity of the service: sustainability of the service: bad first-time user experience: recurrence of usability and technical problems: lack of response to customer feedback: depreciation of customer value: negative influence of lost customers: the lack of advertising campaigns: effectiveness of lockdown and disaster preparedness in combating covid 19 pandemic in india 1 exploring the effectiveness of lockdown and disaster preparedness in combating covid 19 pandemic in india antarjeeta nayak1, soumya subhadarshini padhee2, aditya pinaki nayak3, ramakrishna biswal1,* 1department of humanities and social sciences, national institute of technology, rourkela, india 2nabard financial services ltd., bengaluru, india 3hcl technologies, sydney, australia abstract objectives: 'stay home, stay safe' is the till now available effective remedy for novel coronavirus. india is the first nation compared to other countries affected by covid-19 to enforce a 'nationwide lockdown' at the earliest. methods: google mobility data and disaster preparedness metrics were analysed to evaluate the effectiveness of lockdown as a social distancing intervention. results: results showed that in india, lockdown is a useful measure in flattening the epidemic curve. second, odisha's disaster preparedness is more efficient in containing and combating covid 19 pandemic. conclusion: further, a brief analysis of the travel histories showed that the period of coming in contact with the virus and being tested is quite long, thus increasing the chances of spreading the virus through contact with others. we suggest, instead of fourteen days of quarantine, thirty five to forty days of quarantine would be more effective in combating the spread. keywords: covid 19, disaster preparedness, lockdown, pandemic received on 29 june 2020, accepted on 26 september 2020, published on 05 october 2020 copyright © 2020 antarjeeta nayak et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.5-10-2020.166543 *corresponding author. email: rkbpsych@gmail.com 1. introduction towards the end of 2019, china has reported pneumonia of unknown cause, which was later termed as covid-19 caused by novel coronavirus (who, 2019). the symptoms of the disease vary from mild fever to severe respiratory illness leading to death in some cases. it was identified that the virus was spreading through cough, sneeze, and tiny droplets from the affected persons. within three months of the onset of the virus, it has spread worldwide, including india. based on the symptoms, having highly contagious, and in the absence of any vaccine, maintaining social distance is the only solution to restrict the rapid spread in an overpopulated country like india. as a result of which lockdown was imposed all over india. people in india were advised to stay put at their homes or wherever they are throughout the lockdown period. all inter and intrastate movements by any means were suspended instantly. apart from following the ideal procedure established by the government of india, different state disaster management department also adopted various other strategies to handle the outspread of covid-19 in their respective states. there is an eerie of silence across the globe with the lockdown. the fear of infection and the coronavirus itself is speeding fast, and faster than we ever imagined. many have already left us, and many are still struggling hard to be with us. with the insane escalation of the virus, we are shrouded in fear of our vulnerable existence. superpowers and technological advancements look helpless before the microscopic terrorist. significant interventions are undertaken to mitigate the epidemic and prevent the persistence of corona infection among the human population. with the vaccines undiscovered and the antibodies under experimentations, non-pharmaceutical intervention seems to be the best way to eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e2 http://creativecommons.org/licenses/by/3.0/ mailto:rkbpsych@gmail.com antarjeeta nayak et al. 2 cope with the pandemic. reducing social contacts through several social and physical distancing policies and public awareness actions can help break the coronavirus chain. stay home; stay safe is the remedy till now to stop the spread of the virus. earlier, words like social distancing, containment, and quarantine, which found their place in the dictionary's pages, are now the frontline weapons to fight the virus. the term 'quarantine' is derived from the italian 'quaranta,' which refers to the 40-day sequestration imposed on arriving merchant ships during plague outbreaks in the 14th century (sheddy, 2002). it ideally means to isolate oneself from the rest. the technique was used to reduce the history of contagious diseases from plague to severe acute respiratory syndrome (sars) to ebola during the early onset. however, the number of days for quarantine varies from pandemic to pandemic and population to population (barbisch, 2015). coronavirus being a novel virus, the symptoms and the duration was vaguely figured during the initial period. therefore, the measure of the effectiveness of lockdown has been a major look through. further, considering the frequency of the outspread, the preparedness of the disaster management wing of the different state government of india was also in the limelight. the availability of beds, oxygen cylinders, and other vital equipment, maintenance of travel history, prevention plans, number of tests, and involvement of local community leaders, daily media bulletin, and others were some of the measures followed by disaster management units to tackle covid-19 outspread. there is also strong evidence that proves the effectiveness of social distancing, as it contained the first wave of covid 19 outbreak in its birth centre, china, and proved to be effective in italy and spain too (kraemer et al., 2020; zhang et al., 2020 and chen et al., 2020). thus, social awareness and policy intervention's impact on the outbreak cannot be ignored. the pandemic and its after-effects are not limited to any single country or continent; iknstead, they become a severe threat to the whole world. responsiveness towards social mobility and awareness matters a lot. the application of social distancing interventions like school closure, work from home, increased case isolation, and community contact reduction is highly effective in flattening the epidemic curve and reducing the maximum daily case numbers and lengthening outbreak duration. these were also found to be effective even after ten weeks of delay from index case arrivals (milne and xie, 2020). thus, to evaluate the effectiveness of lockdown in india concerning the number of confirmed cases from 14th march to 26th april, we used the google mobility data (gmd) for every state in india. we adopted a quasi-experimental approach to measuring the impact of standard policies on people's staying at home and their mobility in public places. besides getting a brief idea about the effects of lockdown on social mobility, we have also tried to analyse how human behaviour affects social mobility and the spread of the pandemic. several countries and their county or states have adopted a number of complementary policies that may have some positive consequences. it is also crucial to determine which interventions have a significant impact on the war against corona. therefore, identifying effective policies could help the policymakers around the globe to respond efficiently to the outbreak. if compared to other countries affected by covid 19, india is the first country that earned applause from the united nation's organization (uno) for its fight against covid 19. un praised india's first 21-days nationwide lockdown as a "comprehensive and robust" response to the raging covid 19 pandemic. it is not that other countries did not adopt the lockdown dosage to fight against corona. but, india is the first nation to enforce a lockdown at the earliest compared to other nations. here, when we say 'at the earliest' or the 'first nation,' we mean the number of active cases and fatalities india had, compared to other nations, while declaring a lockdown, to stifle the spread of coronavirus. other than lockdown, india made its headway in prevention and containment, including strengthening surveillance, laboratory capacity, contact tracing and isolation, risk communications, and initiating emergency measures, which is the need of the hour. talking about india and its strategies to fight against corona, we are talking about 1.3 billion people and her 28 states and 8 union territories. under lockdown, india has adopted a "cluster containment strategy" to contain the disease within a defined geographic area through early detection of cases, thus, breaking the chain of transmission. most of the states of india have joined hands with the centre to fight against the virus aggressively. several indian states have proactively come up with innovative solutions to contain the deadly virus throughout the country. kerala is the first indian state to register covid 19 patients. it adopted extensive testing of symptomatic cases, followed by a detailed contact-tracing process and then publishing the route map of an infected person so that everyone with the potential to be infected could be put in self-isolation. to create awareness on covid 19 and to convert educational institutions into hospitals to offset for shortages, the government of kerala undertook an initiative called the corona safe network. there are two major components: the corona literacy mission and the corona care centre (ministry of health and family welfare, kerala, 2020). similarly, odisha, another indian state, is always counted among the poor and backward states. but, when it comes to containing and combating covid 19 pandemic, the state has drawn the attention of uno and the world health organization (who) for its disaster preparedness and receiving appreciation from the indian government too. proactive preparedness is odisha's hallmark, with it becoming the first indian state to impose full lockdown (before countrywide lockdown was imposed), and also the first to extend it until 30th april 2020. it was the first state to announce exclusive covid 19 hospitals and delivered them within a week in two districts, and now every district of odisha has at least one covid hospital. the state is further giving free medical treatment to all covid 19 patients. the state's containment program is rooted in the strategic use of information technology. leading the country, odisha devised an incentive program by offering inr 15,000 for all people returning from foreign and eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e2 effectiveness of lockdown and disaster preparedness in combating covid 19 pandemic in india 3 declared within 11 hours of their arrival on a government portal. with the help of this declaration portal, over 5,000 international returnees and about 35,000 domestic returnees from covid 19 affected states, registered, and were asked to observe home quarantine. the government of odisha has also taken care of its elderly citizens' economic conditions by securing an advance payment of social pension of four months to around 2.8 million beneficiaries (ministry of health and family welfare, odisha, 2020). life and livelihood both are important. odisha has set an example in this regard. the state has also proved itself in maintaining all the covid records, which can be referred for a vivid analysis anytime and making the fight against the deadly virus more robust and transparent. talking about bhilwara, a district in rajasthan, which was worst affected by the virus, adopted a complete lockdown backed by curfew, sealing the borders and undergoing the health screening of the entire population. these measures helped in controlling the spread of the virus throughout the state. among all the states of india, maharashtra tops the chart of covid19 positive cases. the state has come up with a cluster containment plan to deal with the contagion. it uses data analytics, drones, and traditional patrolling methods to survey crowded places and control the spread. thus, different states of india come up with several covid fighting strategies that need to be analysed to record the efficiency of the states and to adopt and replicate the same to increase the preparedness during the time of an outbreak. with this, we have undergone a state-wise analysis of the strategies undertaken in the fight against covid 19 in india. the state with strategic soundness, disaster preparedness, and efficient management of human resources, maintenance, and transmission of information to tackle the condition can set an example for others and help the country win the global fight against covid 19. all the disaster preparedness parameters undertaken by all the states of india are thus used in developing an index, which can be further used by any smart city, state, or nation to combat the pandemic or similar situations in the future. 2. data and method covid 19 as the infectious disease spread from one person to another through direct or indirect contact. in this context, contact tracing and mobility of the individuals play a significant role in fighting corona's spread. in a vast country like india, with a population of 1.3 billion, the response against corona depends a lot on tracing the mobility and the contact spread. therefore, to evaluate the effectiveness of the spread of covid-19, both qualitative and quantitative analyses have been incorporated. to understand the movement of people and their mobility behaviour in relation to various government regulations concerning different states of india from 14th march 2020 to 26th april 2020, a timeline study of google mobility data (gmd) was used. further, the disaster management strategies of different states have been populated from the respective state's disaster management website, social networking accounts, country's covid-19 information portal, etc. since the transmission of infection has an exponential trend, social contact tracing soon became a massive and practically impossible task within the time available for response. in the later period of the corona days, many countries came up with smartphone apps to track the suspected individuals and notify otherwise healthy ones to take precautions. india too has an indigenously developed app by the name aarogya setu app. the development of such apps was also critical as it involved a lot of personal user data. the intrusion level into private data, security, and many more aspects had to be considered to launch the app, which took time to be installed to trace the spread. moreover, the availability of the data from these apps is also an awkward reach. hence, google mobility data (gmd) is used in the current study. as google was already collecting similar data since long through the google map application, the users had elegance and trust, so we deployed the same mobility information in corona's fight. google mobility data is a part of google map users on various smartphone platforms. in the early days of corona, google started releasing global community-level data to help the researchers and government machinery use them in policy-making decisions. these community mobility reports are used in the study as a tool in combating covid 19. the reports, chart, movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential areas helped study various aspects of the spread of the virus. a simple time series analysis is performed to map the mobility data with the number of confirmed cases from 14th march to 26th april 2020 (6 weeks or 43 days) to measure the effectiveness of lockdown, which is the essential measure undertaken to reduce the mobility and spread of the virus. various states of india have adopted several strategies to combat the spread of the coronavirus. we need to understand how controlling the mobility of people, proactive planning to prevent a disaster from happening through the collection of travel and contact histories of individuals and human behaviour interact in spreading or controlling the virus. 3. result 3.1. lockdown in combating covid 19 with the execution of nationwide lockdown in india from 24th march 2020, a significant change was marked at the mobility trends. the analysis that follows discusses the effect of lockdown in containing the spread of covid 19 through gmd (see figure-1). eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e2 antarjeeta nayak et al. 4 figure 1. google mobility trends in india the x-axis represents dates, and the y-axis represents the percentage change in the mobility compared to the base rate of movement clustered at a specific region level. changes in residential mobility have a positive trend, while others have a negative direction as stay home stay safe is the only preventive measure available to fight against corona. the purpose of nationwide lockdown was to force all the citizens to remain at their respective homes, to break the chain of social contamination, avoiding social gatherings, and maintaining social distancing are the essential mechanisms of the process. as a result, maximum people stayed at home, showing a positive trend in residential mobility. workplace mobility, even though it is negative, but has not decreased by 100% as compared to residential mobility. some cyclic variation is observed in the workplace mobility, as the emergency workers, frontline fighters like the police force, doctors, paramedical staff, hospital workers, and other individuals engaged actively on the ground to fight with the pandemic and supposed to go to their respective workplaces. besides, some emergency production and manufacturing industries like medicines, ventilators, personal protective equipment (ppe), masks, sanitizers, and even movement of construction workers engaged in building emergency covid hospitals across the country made the trend for workplace mobility a cyclic one. other than these groups, some others provide emergency services like banking, internet, telecom, and entertainment sectors also contributed to the cyclic trend of workplace mobility. the black vertical line in figure-1 represented the date when the lockdown policy was announced. we can observe an instant spike in mobility just before the enactment of lockdown. this spike indicates that citizens responded to speculation of the nationwide lockdown before it was imposed and showed the citizens' fast reaction to the change. the day before the official declaration of nationwide lockdown by the government of india, india's prime minister had appealed for janata curfew as on 22nd march. as the number of positive cases and the number of deaths were increasing at an alarming rate worldwide, people of india speculated the lockdown to be followed in india with an immediate action that can last for an indefinite period. as such, with the declaration of a nationwide lockdown for 21 days from 24th march midnight, people started to collect all necessary items for the next 21 days. as such, we can see an instant spike in grocery, pharmacy, transit stations, and retails. people gathered at the stores collecting groceries, medicines, and other necessary items as they feared the essential things for a living would go out of stock due to nationwide lockdown. even though the items will be available, they won't get out of their places to fetch them. so, apprehending the uncertainties, people want to store essential items resulting in a higher mobility trend in grocery, pharmacy, and retail stores. but, immediately after the lockdown, there is a fall in mobility at these places as recorded by gmd. from the above observations, we can infer that the enforcement of nationwide lockdown had its effect on the social mobility of the population. moreover, the main focus of the country like india was to curtail the social gatherings and social contaminations to combat the pandemic. india is a highly populous country, and obeying social distancing without legal enforcement of nationwide lockdown would not have been possible. indeed, nationwide lockdown played a significant role in reducing the speed of the spread of the virus instead of the current phase of unlock-1.0 beginning 08th june 2020 (till the writing of this article), where we see a sharp rise in the covid 19 cases. in the later part of this paper, the effectiveness of lockdown in the fight against the deadly virus based on simple regression is discussed. next, we present a state-wise mobility status post lockdown. figure -2 and -3 represents the state-wise change in residential, retail, and recreation-related mobility due to nationwide lockdown. the x-axis in the figures represents the dates. the left of the y-axis represents the percentage change from baseline mobility. the right of the y-axis tracks the red line, indicating the date when lockdown began. however, there is some data unavailability for lakshadweep. from figure-2, we can observe a difference in residential mobility while comparing the states like manipur and mizoram with delhi, chandigarh, maharashtra, telangana, tamilnadu, gujarat, kerala, and karnataka. from among all the states, manipur showed a notable trend in residential mobility. the state adhered to lockdown in a significant way of staying at homes even earlier than the declaration of the nationwide lockdown. therefore, the number of reported cases of covid 19 is much lower in manipur compared to other states like delhi, chandigarh, maharashtra, gujarat, kerala, tamilnadu, telangana, and karnataka. these states showed a late response to lockdown by not staying at respective residents. there is a similar trend in recreation and retail mobility (figure-3) too. initially, there is a fall in retail and recreation mobility due to janata curfew. then we can see a spike that shows the mass moving to gather necessary items just before complete lockdown. this trend is almost similar to the countrywide retail and recreation mobility data. then, gradually with the enforcement of lockdown, there is a significant adherence to the policy. eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e2 5 figure 2. state-wise residential mobility trend in india figure 3. state-wise retail and recreation mobility trends in india since the level of adherence to lockdown policy is different in different regions of india, to measure the effectiveness of lockdown as a measure to combat covid 19, we checked for the correlation between the mobility and rate of growth in the number of covid cases. the reported positive covid cases were collected from the government website (https://www.covid19india.org/). next, we attempted to see whether people's movement and the rise in the new cases go together. as the states differ with the population density, rather than looking at the number of covid cases only, we need to normalize it to the population. hence, we used a fixed effect control for controlling the variation in the state data and have logged the people in that. it is also marked that there is a certain gestation period between the infection and the symptoms to appear. hence, if we want to look at the impact of mobility and growth of cases, we have to use the lagged data. one of the major issues faced during the analysis was the cyclic tendency of the mobility data, i.e., on some days, it increased; some other days, it decreased, as discussed earlier. so, if the proper lag duration was not chosen, we might have ended up in precisely opposite effects of mobility on the number of cases. hence, we experimented with the number of lag days during various regressions. we used regression with (log of a number of new cases +1) as the dependent variable and the percentage change in different types of mobility as the covariates. we chose the lag that represented the actual average of duration when the symptoms started appearing. moreover, depending on whether the length is also different for different countries since the lockdown policy was implemented nationwide, we assumed that the rate of transmission was mostly similar. we chose an average of 14-21 days as followed for the quarantine as well as to detect the symptoms of the cases. a positive magnitude represents a positive impact (see table-1). with an increase in 1% of mobility for retail and recreation, there is a 0.96% increase in the number of cases. the same happens with the rise in the movement for grocery & pharma, transitk & stations, i.e., a 1% increase in mobility increases the number of cases by 0.29% and 0.5%. the movement to parks shows an increase in mobility for parks. it reduces the number of cases, as the people were homebound, they visited the gardens in their apartments or the community making the impact skewed. however, it is weird if we look at the no lag regression (table-1). residential mobility has a positive effect (1.01). regression equation – where (i) we have explained why we have regressed lag6 and lag 0. (ii) we have taken log ( new cases + 1) as the dependent variable; in some states, the new cases were zero new cases some days, the distribution of new cases had long thin tails. that suggests staying at home also increases the number of cases. but how does this happen? this is where the lag comes in. the detection of transmission of the disease is not instantaneous. if we observe an increase in the number of cases, the transmission for the said case has occurred at least a few days earlier. to capture the impact of change in residential mobility, we need to lag the mobility data. the question comes then, what is the best lag period to test (2, 3, 5, 6, 8, 9,? ? how many days). unlike odisha, where the testing facility is much faster with the average period of detection being four days, the average day of screening in maharashtra is 13 days. as per the literature and indian council for medical research reports, the average detection period in india is six days. we also found that the date has a positive coefficient (3.37), which means cases increase by days, which is quite apparent. since the average national detection period is six days, we took the lag of six days to see what happens to the number of positive cases with the announcement of lockdown. by examining the values of table-2, we found a 1% increase in mobility for retail and recreation and parks increase the number of cases by 0.44% and 0.19%, respectively. in contrast, a 1% increase in mobility for grocery and pharmacy reduces the number of cases by 0.12%. such a result may be explained by increasing mobility to those places to avail the masks, sanitizers, and effectiveness of lockdown and disaster preparedness in combating covid 19 pandemic in india eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e2 https://www.covid19india.org/ antarjeeta nayak et al. 6 hand washes to prevent the infection. for this reason, the increase in mobility is reducing positive cases. an increase in movement to parks by 1% increases the number of cases by 0.19%, as visiting the parks increases the risk of social gatherings and transmission of the infection. mobility for transit and stations if increases by 1%, it is also expanding the number of cases by 0.56%, as this makes more and more people prone and vulnerable to the virus due to high social gathering and less social distancing. kan increase in mobility for workplaces by 1% increases the number of cases by 0.7%. the results found are also very significant. workplaces encourage a higher degree of social gathering and a higher risk of infection. in addition to this, the covid frontline workers are bound to go to their respective workplaces that increase the risk of disease, which is quite apparent. with this regard, we can justify 'work from home' as a better initiative of nationwide lockdown to combat covid 19. not only 'work from home,' but 'stay home, stay safe' is also an essential mechanism of lockdown. these mechanisms work significantly in combating covid 19, which is in our findings. one percent increase in residential mobility reduces the number of cases by 0.55%. during six lag (table-2), the impact on residential mobility is negative, and retail & recreation, parks, grocery and workplace, transit, and station like confirmed mobility is positive, which help us to defend the fact that lockdown is a move in a right direction to fight against the pandemic. since the covariates are significant in lag6 regression, we can interpret that the number of new cases is more than 0 (n case of retail and others), and we reject the null hypothesis. similarly, for residential mobility, the impact is significant and less than 0. table 1. regression with no lag estimate std. error t value pr(>|t|) significance (intercept) -6.224e+02 5.702e+0 1 -10.916 < 2e-16 *** date 3.374e-02 3.107e-03 10.861 < 2e-16 *** log population 5.290e-01 2.905e-02 18.208 < 2e-16 *** retail and recreation 9.660e-03 2.659e-03 3.633 0.000289 *** grocery and pharmacy 2.947e-03 1.833e-03 1.608 0.108090 * parks -7.117e-03 1.156e-03 -6.154 9.56e-10 *** transit stations 5.019e-03 2.103e-03 2.387 0.017100 * workplaces -1.247e-02 2.025e-03 -6.155 9.49e-10 *** residential 1.018e-02 4.243e-03 2.400 0.016500 * significance codes: ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 residual standard error: 0.9589 on 1574 degrees of freedom (1 observation deleted due to missing) multiple r-squared: 0.3562, adjusted r-squared: 0.3529, f-statistic: 108.9 on 8 and 1574 df, p-value: < 2.2e-16 table 2. regression with lag 6 estimate std. error t value pr(>|t|) significance (intercept) -6.191e+02 5.696e+01 -10.868 < 2e-16 *** date 3.357e-02 3.106e-03 10.805 < 2e-16 *** log population 5.060e-01 2.884e-02 17.544 < 2e-16 *** lag(retail and recreation) 4.450e-03 1.685e-03 2.640 0.008372 ** lag(grocery and pharmacy) -1.260e-02 1.861e-03 -6.769 1.82e-11 *** lag(parks) 1.907e-03 1.194e-03 1.597 0.110504 * lag(transit stations) 5.627e-03 2.173e-03 2.589 0.009704 ** lag(workplaces) 7.035e-03 2.082e-03 3.378 0.000747 *** lag(residential) -5.583e-03 4.254e-03 -1.313 0.189517 * significance codes: ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 residual standard error: 0.9806 on 1568 degrees of freedom (7 observations deleted due to missing) multiple r-squared: 0.3286, adjusted r-squared: 0.3251 f-statistic: 95.91 on 8 and 1568 df, p-value: < 2.2e-16 thus, with all the above mobility graphs and the mobility regression with the number of positive cases, it is proved that lockdown had a positive impact on combating the spread of the virus. our result is "lockdown helped counter the rate of spread." the drastic change in mobility was due to forced lockdown with the cooperation from the state administration. reduction in mobility is due to the same; offices are closed, people started working from home, and many more. it was enforced to reduce interaction among the population and reduce infectious contact. hence, we can easily establish causation validating our results. lockdown being a lawful action was seriously adhered to by maximum indians to control the spread of the pandemic. lockdown, along with several other measures like telecasting of several entertainment programs on the national entertainment channels, helped india observe a fruitful lockdown nationwide and ensure that people stayed in their respective homes. 3.2. disaster preparedness and corona fight world health organization declared corona a public health emergency of international concern on 30th january 2020, without any prescribed cure for the epidemic and preparedness as the only way to restrict covid 19. odisha is the first state of india to declare covid 19 a 'disaster' under the provisions of the disaster management act, 2005 on 13th march 2020, to empower public officials to combat the spread of covid 19 adequately. it becomes most important to measure the preparedness of several other states to fight the pandemic. to know the readiness to fight against corona, we have analysed all the preparedness parameters adopted by different states of india. each metric was allotted a weight (table-3) to develop an index to measure how preparedness for the pandemic can be useful in the fight and eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e2 7 control the spread of corona. further, the weights can help examine each state's relative standing in the battle against corona. the weights allotted have been validated with the expert consultations working in this field, the frontline line warriors and health workers, and researchers. table 3. parameter to measure the disaster preparedness preparedness parameters allotted weights testing datart pcr tests / rapid antibody tests 5 gender-wise covid cases 4 age-wise covid cases 4 district wise summary 4 number of general beds 7 number of icus 9 number of doctors deployed (3 shift) 10 number of nurses deployed (3 shift) 10 number of paramedics deployed (3 shift) 10 number of group d (3 shift) 10 number of new patients admitted in general beds (gender wise segregation) 5 suspected cases 5 gender-wise suspected cases 5 confirmed covid cases 3 gender-wise confirmed covid cases 3 gender-wise suspected cases in general beds 7 gender-wise confirmed covid cases in general beds 7 new patients admitted in icu beds 7 gender-wise number of new patients admitted in icu beds 7 number of recovered cases 2 number of deaths 2 daily record of number of n95 masks available 9 daily record of number of surgical masks available 9 daily record of number of ppe kit availability 9 daily record of amount of hand sterilizers available in all covid hospitals 9 daily record of availability of oxygen in all covid hospitals 9 daily record of number of ventilators available in all covid hospitals 9 number of medical ambulance available 9 case -wise travel history 8 daywise number of reported cases 3 every day press release on covid 19 from 19th march, by specially designated covid 19 spokesperson 1 information education and communication materials for covid 19 available in english and concerned state's language 1 disable friendly and bilingual (state language and english) 1 helpline numbers for covid19 1 updates in the social accounts 1 number of testing centers 1 government hospitals involved 1 mental well being and emotional support 6 quarantine facility 6 government helpline numbers (category wise) 6 with the allotted weights, we calculated the state-wise weighted preparedness (table-4) to see which state is more prepared in the fight against the pandemic. table 4. state-wise ranking of disaster preparedness for the pandemic rank state weights for disaster preparedness 1 odisha 225 2 bihar 90 3 maharashtra 75 4 uttarakhand 58 5 tamil nadu 53 6 madhya pradesh 49 7 west bengal 44 8 chhattisgarh 41 9 kerala 38 10 karnataka, puducherry 37 11 jharkhand 34 12 delhi, gujarat 33 13 rajasthan 30 14 andhra pradesh & chandigarh 29 15 meghalaya 26 16 punjab 25 17 jammu & kashmir & kladakh 19 18 haryana 18 19 goa 16 20 himachal pradesh 15 21 assam 14 22 telangana 10 23 arunachal pradesh 6 24 tripura 5 almost all out of 28 indian states and eight union territories have been ranked for their preparedness. some states and union territories like andaman & nicobar island, manipur, mizoram, and uttar pradesh counted the preparedness below five and are thus, not undertaken in the list of readiness for the pandemic. odisha occupied the first rank among all the states and is the first state to declare covid 19 a disaster; the government adopted all preparedness measures to face the hard times of covid 19 firmly. having faced super cyclone in 1999, odisha has managed many natural calamities in the past very effectively. though covid 19 situation demanded a different strategy than previous disasters, the experience of managing disasters helped the state maintain all records by adopting a transparent regulation of systems for which the state leads the preparedness for the covid 19 list. in the latter part of this paper, we have also analysed the travel histories of positive cases, one of the special measures undertaken by the state to combat the pandemic. other than this, states like bihar, maharashtra, uttarakhand are also well prepared. it is interesting to note that the states like bihar and odisha, always listed as underdeveloped and poor states of india, are on the top when it comes to the administration of the state during the time of the covid 19 crisis. indeed, these states know something better than other effectiveness of lockdown and disaster preparedness in combating covid 19 pandemic in india eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e2 antarjeeta nayak et al. 8 states regarding disaster management because of their repeated exposure to other natural calamities. there is a scope for these states to develop and lead the disaster preparedness guidelines for the entire country. learning the knowhow of disaster preparedness could be an asset for any progressive and forward-looking government. now, to equate the disaster preparedness of the states with the pandemic, we calculated the best fit exponential rate of growth of the number of new cases in every state (table-5). then we evaluated the correlation between the disaster preparedness and the number of covid cases. the correlation is low (0.21) and positive. this suggests that if the states are more prepared, the numbers of positive cases reported are also high, and this is obvious because there are more testing and early detection of the corona cases. table 5. states with the exponential rate of increase in number of covid cases & their weights for the preparedness state rate of exponential increase till 25th april weighted preparedness odisha 0.1269 225 andhra pradesh 0.1781 29 bihar 0.1175 90 chandigarh 0.0531 29 chhattisgarh 0.1015 41 delhi 0.1569 33 goa 0.0224 16 gujarat 0.1614 33 haryana 0.083 18 himachal pradesh 0.1005 15 jammu & kashmir 0.1416 19 karnataka 0.0998 37 kerala 0.07 38 ladakh 0.0163 19 madhya pradesh 0.1749 49 maharashtra 0.143 75 puducherry 0.0671 37 punjab 0.1272 25 rajasthan 0.1567 30 tamil nadu 0.1903 53 telangana 0.1372 10 uttarakhand 0.0935 58 west bengal 0.1511 44 assam 0.0494 14 jharkhand 0.1688 34 tripura 0.0306 5 meghalaya 0.1499 26 correlation (r) = 0.213008719 data source 2 – the rate of exponential increase is taken from https://api.covid19india.org/covid india org api website directly. we use historical data until 25th april and compute the exponential best fit line. the best fit line is calculated with the help of the least squared error technique. arunachal pradesh, even though it had six as the weighted preparedness value, but is not taken for further calculation due to the unavailability of data required for finding its correlation with covid 19. to further examine the effectiveness of the disaster preparedness index, we have undertaken three more indicators: 1) states having more than 7000 tests, 2) states having more than 15000 tests, and 3) states having more than 100 corona cases. the relation of the preparedness with these indicators was found to be negative [indicator-1= -0.03, indicator-2 -0.05, indicator-3 -0.04] (table-6). the results suggest that disaster preparedness (including testing and other measures) reduces covid cases. the states having more than 15000 tests seem to be highly prepared as the rate of growth of the number of cases is negatively correlated. if it is compared with the states having more than 7000 tests, the correlation is high, i.e., -0.054824653 > 0.035355195. table 6. measuring the effectiveness of disaster preparedness index states having more than 7000 tests rate of expone ntial increa se till 25th april weight ed prepare dness states having more than 15000 tests rate of expone ntial increa se till 25th april weight ed prepare dness states having more than 100 corona cases rate of expone ntial increa se till 25th april weight ed prepare dness odisha 0.1269 225 odisha 0.1269 225 odisha 0.1269 225 andhra pradesh 0.1781 29 andhra prades h 0.1781 29 andhra prades h 0.1781 29 bihar 0.1175 90 bihar 0.1175 90 bihar 0.1175 90 chhattisga rh 0.1015 41 delhi 0.1569 33 delhi 0.1569 33 delhi 0.1569 33 gujarat 0.1614 33 gujarat 0.1614 33 gujarat 0.1614 33 haryan a 0.083 18 haryan a 0.083 18 haryana 0.083 18 karnat aka 0.0998 37 jammu & kashmi r 0.1416 19 jammu & kashmir 0.1416 19 kerala 0.07 38 karnat aka 0.0998 37 karnataka 0.0998 37 madhy a prades h 0.1749 49 kerala 0.07 38 kerala 0.07 38 mahara shtra 0.143 75 madhy a prades h 0.1749 49 eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e2 9 madhya pradesh 0.1749 49 rajasth an 0.1567 30 mahara shtra 0.143 75 maharasht ra 0.143 75 tamil nadu 0.1903 53 punjab 0.1272 25 punjab 0.1272 25 telanga na 0.1372 10 rajasth an 0.1567 30 rajasthan 0.1567 30 tamil nadu 0.1903 53 tamil nadu 0.1903 53 telanga na 0.1372 10 telangana 0.1372 10 west bengal 0.1511 44 west bengal 0.1511 44 correlation= -0.035355195 correlation= -0.054824653 correlation= -0.049605683 hence, with the increase in the number of tests as a parameter of preparedness, the positive cases are reducing. increased testing prompts an early detection of the cases, thus reducing the contact cases and the spread of the virus. a similar result was also observed with the states having more than 100 confirmed corona cases. all these results show the efficiency of the disaster preparedness index in combating covid 19. further, this index can be replicated by any state, smart city, and nations to be prepared during the pandemic like covid 19 or other disasters. 3.3 travel and contact histories in combating covid 19: a case of odisha the travel and contact history of all covid positive cases maintained by the government of odisha proved highly effective in knowing several covid 19 dynamics. in the current study, 73 positive cases and their travel and contact history as of 20th april 2020 were analysed. initially, the travel history gives us an idea about the origin and causes of the spread of the virus in the state. out of 73 positive cases, 43 have a travel history, and 28 positive cases did not have any history of traveling but diagnosed positive through contact with other positive cases. there was neither any travel history nor any contact tracing for two cases. these two cases were suffering from cold, visited the hospitals, and were tested covid positive. analysing the 43 covid positive cases having a record of travel history, we can see 28 cases (65%) (see figure-4) are returnees from kolkata (table-7). next, seven positive cases (16%) related to people moving in and out of odisha state. third, five cases have a connection with the delhi nizamuddin markaz congregation (see table-7), who later became the source of the spread of the virus in their region. out of 2 from delhi, 1 had a connection to nizamuddin. so, out of 43 positive cases, a count of 6 (i.e., 14%) had links to nizamuddin congregation. if we focus on the histories of those 28 positive cases that did not have any travel history, we can still find the nature and source of infection. all the 28 persons are either a close relative or the neighbours, or somehow had in contact with the earlier positive cases (table-8). it is observed that case no-61 is regarded as the super spreader who infected seven other persons by contacting them. from table-8, we can see that out of 28 cases without travel history, 46.42% (n=13) got infected through close relatives, 21.42% (n=6) each got infected through close contact and neighbours, and finally, 10.71% (n=3) got infected through co-passengers. hence, people need to maintain safe physical and social distance from others even if they do not have any travel history. further, it was observed that in odisha, individuals in the age group of 31-40 years are the most affected by covid 19, followed by the 51-60 years of age group. a similar trend is observed throughout india, with 31-40 years of the age group being the most affected one. as between 31-40 years, it is the productive age, and they are also exposed to several works, places, and people, thereby becoming the most vulnerable group. the trend of positive cases at different ages in odisha and india is the same (figure-5). table 7. delhi nizamuddin markaz and the spread of covid 19 in odisha area to which the person from nizamuddin congregation belonged to count of nizamuddin traveler bhadrak 2 cuttack 1 puri 1 rourkela 1 total 5 table 8. contact tracing and spread of covid 19 in odisha case no. who tested covid positive nature of contact with other persons number of persons infected through contact (contact cases) 41 close contact 2 42 close contact 1 61 close relative 7 69 close contact 2 73 close relative 2 74 close relative 1 42 close relative 3 42 close contact 1 64 co-passenger 3 7,8,22,39 neighbours 5 101,102 neighbours 1 total 28 effectiveness of lockdown and disaster preparedness in combating covid 19 pandemic in india eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e2 antarjeeta nayak et al. 10 a gender-wise, corona positive cases in odisha state and india also shows the same trend, where the males are affected the most (india-66.8% & odisha-79.4%) as compared to the females (india-33.2% & odisha-20.5%). comparing the males of odisha and the nation as a whole, the males of odisha have a higher percentage of positive cases (india-66.8% < odisha-79.4%). however, the females of odisha have lower positive cases compared to the whole of india (odisha-20.5 % < india-33.2%) [figure-6]. figure 4. travel history contributing to covid 19 spread in odisha figure 5. age-wise distribution and covid 19 infections eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e2 11 figure 6. gender-wise distribution of covid 19 infections the first exposure or contact with the virus is crucial to understand the spread. as we do not know the source of infection every time, we are prone to this infection at every step outside the house and coming in contact with the carrier directly or indirectly. therefore, the time between the first exposure and the date of getting to know about it seems essential. the travel and contact histories of positive corona cases, as maintained by the government of odisha, indicates before getting tested for corona, an individual used to roam freely for more than 20 days, which may or can be the source of spread (table9). table-9. positive cases and time lag between first contact & confirmation of corona k table-10. tested samples and type of covid cases sample tested no. of cases asymptomatic 61 symptomatic 4 sample collected as a part of contact tracing 6 neither symptomatic nor asymptomatic/ contact cases 2 total confirmed cases 73 the history of the positive cases confirmed in odisha vividly shows a higher number of asymptomatic cases than symptomatic and other cases (table-10). the higher numbers of asymptomatic cases have a higher window of spreading the virus by contacting others. more frequent and random tests may hold the key to trace positive cases quickly. further, as the maximum days of being tested and finding to be covid positive is 36 days, the quarantine period may be increased to 40days for the suspected and contact cases (table9). meanwhile the govt. of odisha had increased the quarantine period from 14 days to 21+7 days (21 days at quarantine centres and seven days of home quarantine) (the indian express, 9th may 2020). but, keeping in view the rate of random tests done per day, it is advisable to increase the period up to 40 days. as the tests increase, the quarantine days may be reduced accordingly. further, home sample collection or sample collection at community centres where the physical distancing norms can be followed should be encouraged. 4. conclusion novel coronavirus (ncov-19 or covid 19) is a household name now. with no immediate preventive or curative in sight, precaution is our best bet. lockdown, shutdown, isolation, quarantine, and sanitization like behavioral interventions have proved their efficiency in the fight against the virus. we have analyzed the movement-related information of people, effectiveness of lockdown, disaster preparedness, and effectiveness of maintaining travel and contact histories in combating the no of corona positive cases time period (in days) between first contact and corona positive confirmation 1 1 day to 36 days 2 24 to 34 days 3 4 to 30 days 4 18 to 21 days 6 27 to 31 days 7 23 days 9 22 days effectiveness of lockdown and disaster preparedness in combating covid 19 pandemic in india eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e2 12 spread of infection. the quantitative analysis of the google mobility data proved lockdown as an efficient and effective way to combat the epidemic and containing the spread. the sharp rise in the number of cases after the relaxation of lockdown is proof of it. the rate of spread is much faster during the relaxation or unlock phase. staying prepared during disasters saves life and wealth. however, it has been assumed that there are negligible false-positive cases in the data reflected by the country's covid-19 information portal and google mobility data. odisha state in india has set an example in the entire country by adopting a proactive approach to tackle the situation. incidentally, it may be noted that the variation in the density of the population in a state, the nature of travel, and the frequency of individual interaction may differ from state to state even during lockdown. the mobility data assumes a uniform distribution of population and hence, infection. however, efforts can be made to improve the strategy to tackle the outspread of the virus. one of the strategies involved in this process is maintaining a record of the travel and contact histories that helped the government chalk out specific and measurable actions. the travel history of all covid 19 positive cases maintained by the government of odisha proved highly useful in knowing the origin and the causes of the spread of the virus in the state. a qualitative, as well as a quantitative analysis of the travel histories helped to gather in-depth knowledge about the origin, causes, and direction of the infection and several other aspects, which is very resourceful in assessing corona, the pandemic. the findings of the current study suggest that preventing an epidemic is possible with the adoption of the right strategies that are based on authentic information, documentation, and preparedness. policymakers must utilize the successful strategies adopted to manage the pandemic like situations in the future by documenting it systematically. the authentic data acquisition and data management seem very crucial in controlling infectious diseases in smart cities. acknowledgements we thank soumyakanta padhee (research scholar, university of wisconsin, madison, usa) for his help in the inferential statistical analyses used in this paper. references [1] chen, n., zhou, m., dong, x., qu, j., gong, f., han, y., ... & yu, t. (2020). epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in wuhan, china: a descriptive study. the lancet, 395(10223), 507-513. [2] kraemer, m. u., yang, c. h., gutierrez, b., wu, c. h., klein, b., pigott, d. m., ... & brownstein, j. s. (2020). the effect of human mobility and control measures on the covid-19 epidemic in china. science, 368(6490), 493497. [3] milne, g. j., & xie, s. (2020). the effectiveness of social distancing in mitigating covid-19 spread: a modelling analysis. medrxiv. [4] sehdev, p. s. (2002). the origin of quarantine. clinical infectious diseases: an official publication of the infectious diseases society of america, 35(9), 1071. [5] zhang, c., chen, c., shen, w., tang, f., lei, h., xie, y., ... & xu, y. (2020). impact of population movement on the spread of 2019-ncov in china. emerging microbes & infections, 9(1), 988-990. [6] department of health and family welfare, odisha. (https://health.odisha.gov.in/) [7] directorate of health services, govt. of kerala.(https://dhs.kerala.gov.in/) https://www.covid19india.org/ [8] is there a case for quarantine? perspectives from sars to ebola. available at: https://escholarship.org/uc/item/2hw70775 [9] the indian express. (2020). odisha government extends covid-19 quarantine to 28 days. retrieved from https://www.newindianexpress.com/states/odisha/2020/ma y/09/odisha-government-extends-covid-19-quarantine-to28-days-2141064.html [10] world health organization: rolling update on corona virus (covid-19) available at : https://www.who.int/emergencies/diseases/novelcoronavirus-2019/events-as-they-happen antarjeeta nayak et al. eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e2 https://health.odisha.gov.in/ https://dhs.kerala.gov.in/ https://escholarship.org/uc/item/2hw70775 https://www.newindianexpress.com/states/odisha/2020/may/09/odisha-government-extends-covid-19-quarantine-to-28-days-2141064.html https://www.newindianexpress.com/states/odisha/2020/may/09/odisha-government-extends-covid-19-quarantine-to-28-days-2141064.html https://www.newindianexpress.com/states/odisha/2020/may/09/odisha-government-extends-covid-19-quarantine-to-28-days-2141064.html medbot-medical diagnosis system using artificial intelligence 1 medbot-medical diagnosis system using artificial intelligence sanjay kumar m1,*, vishnu prasad reddy g1, sai ganesh k v1, and n. malarvizhi2 1 ug student, vel tech rangarajan dr. sagunthala r&d institute of science and technology, chennai 2 professor, vel tech rangarajan dr. sagunthala r&d institute of science and technology, chennai abstract introduction: one of the fastest developing technologies in the present world is the virtual assistants. these assistants could manage with the medical-related tasks and helps both the providers as well as the patients. through artificial intelligence, users can communicate through voice or text interface with the chatbot and also receive responses based on that. basically, a chatbot can converse with a real person. objectives: in this paper, a chatbot named medbot stands for medical diagnosis system using artificial intelligence mainly focusing of skin and eye related problems. methods: the medbot helps in connecting the available patients, make their appointments, helps in finding the specialized person and provide them access to get the accurate treatment. results: this medbot helps in providing healthcare support online for 24×7 and it also responds to common and precise questions. conclusion: it helps in generating the leads and forwarding them to the sales automatically. by querying the patients sequentially, it guides them with the problem they are facing with. keywords: learning, php, mysql, artificial intelligence. received on 30 june 2020, accepted on 30 january 2021, published on 20 july 2021 copyright © 2021 sanjay kumar m et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.20-7-2021.170554 1. introduction a malignant tumor quickly grows up and expands through typical brain regions. this is also called as brain cancer usually develops quickly, and sometimes invades stable brain regions or crowds. such tumors often drain a regular brain's blood supply. benign level brain tumors did not include tumor cells, and appear to develop gradually. malignant level brain tumors split into two types: one is primary, another one is metastatic. primary type brain tumors fire up within the skull. as tumor cells found anywhere in the body break apart and migrate into the brain, a metastatic tumor is created. metastatic level brain tumors are often malignant. mainly brain tumors are categorized according to the origin of the tumor, the amount of tissue affected, whether it is benign or malignant type, among other factors [1] [2] and now, the medical bot technology is gaining traction in health care, where it serves patients and providers helping to execute myriad tasks. through artificial intelligence, users can communicate through voice or text interface with the chatbot and also receive responses based on that. basically, a chatbot can converse with a real person. in this paper, a chatbot named medbot stands for medical diagnosis system using artificial intelligence mainly focusing of skin and eye related problems. the medbot helps in connecting the available patients, make their appointments, helps in finding the specialized person and provide them access to get the accurate treatment. clinicians can also use chatbots to retrieve quickly and easily information related to drug relations and side effects. these chatbots question patients and compare answers to cases with their medical database. for these reasons, the accessibility of chatbots in healthcare system is relevant and more accessible. we have developed our medbot using php and mysql with wamp server. one of the nice things about a chatbot is that it is so accessible that you can use it eai endorsed transactions on smart cities research article *corresponding author. email: msanjaykuma6@gmail.com eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e1 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ sanjay kumar m et al. 2 on your smartphone. chatbots also provide improved access to healthcare by delivering advice or counselling remotely at lower costs. this could ease the burden on medical professionals. the most commonly employed algorithm for medbot is the random forest; it is one of the important model of classification that is able to classify the image with high precision. random forest is a ensemble model that performs both classification and regression. so it is called as ensemble random forest (erf). in training, number of decision trees is used; in output class, individual trees produce the class output. combination of tree predictors is called as random forest. the basic principle of random forest is combining the week learners together to strong learner. 2. objectives the modern digital imaging systems helps in providing high-resolution images, which could be very useful in handling the clinical situations when compared to the conventional systems. sliding window strategy is utilized in computing the pitiful qualities. for any dismal qualities for the adjoining obstructs in the left picture, the square areas in the left picture are moved by one pixel in the flat heading [3]. for any two nearby squares in the left picture is same with the correct picture then the entire computation of condition (2) ought to be subtracted from the pitiful estimation of furthest left pixels and increase the value of the furthest right pixels to the past tragic esteem [4]. for this situation, the request of figuring dismal is changed. the tragic estimations of all aberrations for a square in the left picture are determined [5] [6]. 3. methods considering the difficulties of the previously existing technology, initial analysis is done after which the whole activity will be computerized. the medbot system had been proposed in this paper that focuses on the skin as well as the eye problems [7] [8]. the system proposed hereby could be accessed only by the user and the admin. these two entities need to login the application with the valuable credentials to get access with the android system as represented in figure 1. each tasks and module will be managed and accessed accurately once the admin makes a successful login. the tasks performed by the admin includes login, arrange questions and answers, view the users, update hospital details and also update available doctors’ details [9-13]. user needs to register to get credentials and after getting credentials they can view the webpage, view hospital details, view available doctors. figure 1. 3.1. modules and description the proposed system contains the following modules: • home page module • admin login module • user login module home page module home page module is the first page where admin and user interact with the chatbot. this module contains tags such as about us, contact us, admin login and user login. eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e1 medbot-medical diagnosis system using artificial intelligence 3 about us: about us explains and gives a clarity to the user about the chatbot and how does it is useful to solve their health issues. contact us: contact us consist of name, phone number, and email id of the administrators of the website. users can contact the administrators using these details. admin login: this is the login page for the admin to manage the chatbot. the operations of the admin are explained in admin login module. user login: this is the login page for the user to login to the chatbot and chat with the chatbot and solve their health issues. the detailed operations of user are explained in user login module. admin login module login: admin can login by using credentials. manage questions & answers: admin can arrange questions and answers. view users: admin can see the details of the user who has used the chatbot. manage hospital details: admin can add, update, and delete hospital details into the chatbot. manage doctor details: admin can add, update, and delete details of available doctor into the chatbot. user login module logins used by websites, computer applications, and mobile apps, are a security measure designed to prevent unauthorized access. registration: user needs to register to get credentials. login: user can login using credentials homepage: user can view the webpage hospital details: user can see the hospital details doctor details: user can view the available doctors. chat with bot: user can chat with both regarding the query and solve their health issues. 4. results in this paper, we have described a medbot system that was designed to support patients and health professionals exclusively for eye and skin problems. patient’s perceptions regarding enjoyment and attachment bond with the medbot are also found to be good. table 1 and 2 shows the sample eye diseases and skin diseases with symptoms and suggestions respectively. table 1. eye diseases with symptoms and suggestions table 2. skin diseases with symptoms and suggestions the hospital details and screenshots to solve various eye and skin problems is given in figures 2,3 and 4 by chatting with our medbot. eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e1 4 figure 2. hospital details in medbot figure 3. chatting with medbot sanjay kumar m et al. eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e1 medbot-medical diagnosis system using artificial intelligence 5 figure 4. chatting with medbot 5. conclusion precise brain tumor detection is a crucial consideration for physicians to handle. for diagnostic imaging, magnetic resonance imaging (mri) performs a significant function compared with other imaging methods. accurate brain tumor analysis from anmri image by doctor is dependent on his experience. for this reason, we propose a technique which diagnosis the brain tumor automatically in easy and effective manner. in this paper, we have described a medbot system that was designed to support patients and health professionals exclusively for eye and skin problems. patient’s perceptions regarding enjoyment and attachment bond with the medbot are also found to be good. in our future work, we will assess additional measures and possible outcomes through our medbot system. references [1] abbas saliimi lokman, jasni mohamad zain fakuli sistem komputer & kejuruteraan perisian,” designing a chatbot for diabetic patients”, acm transactions on management information systems (tmis), volume 4, issue 2, august 2015. [2] divya, indumathi, ishwarya, priyasankari, kalpana devi, “a self-diagnosis medical chatbot using artificial intelligence”, journal of web development and web designing, volume 3 issue 1, 2018. [3] udendhran r, a hybrid approach to enhance data security in cloud storage, icc '17 proceedings of the second international conference on internet of things and cloud computing at cambridge university, united kingdom — march 22 23, 2017, isbn: 978-1-45034774-7 doi>10.1145/3018 [4] pohle and k. d. toennies, “segmentation of medical images usingadaptive region growing,” proceeding spie— medical imaging, vol.4322, pp. 1337–1346, 2001. [5] t. y. law and p. a. heng, “automated extraction of bronchus from 3dct images of lung based on genetic algorithm and 3d region growing,”proceeding spie — medical imaging, vol. 3979, pp. 906–916, 2000. [6] w. m. wells iii, w. e. l. grimson, r. kikinis, and f. a. jolesz,“adaptive segmentation of mri data,” ieee transaction medicalimaging, vol. 15, no. 4, pp. 429–442, aug. 1996.. [7] al-badarneh et al., h.najadat. and i.jordan, ``a classifier to detect mri brain images’”, the acm international conference on advances in social networks analysis and minning, pp.784-787, 2013. [8] dagar, preety & jatain, aman & gaur, deepti. (2015). medical diagnosis system using fuzzy logic toolbox. 193197. 10.1109/ccaa.2015.7148370. [9] iantovics, laszlo barna. (2007). the cmds medical diagnosis system. proceedings 9th international symposium on symbolic and numeric algorithms for scientific computing, synasc 2007. 246-253. 10.1109/synasc.2007.40. [10] heba mohsen, abdel-badeehm.salem, “ classification using deep learning neural networks for brain tumors” elsevier, volume 3, issue 1, pp.68-71, (2018) [11] aliisin, cemdirekogulu, melikesah “ review of mribased brain tumor image segmentation using deep learning methods” elsevier, procedia computer science 102 317324 (2016) [12] mung chiang, fellow, ieee, and tao zhang, “fog and iot: an overview of research opportunities”, ieee internet of things journal, vol. 3, no. 6, december 2016. eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e1 figure 2. hospital details in medbot apps in time of pandemic: digital usage and gratifications in transition towards #smartcity 1 apps in time of pandemic: digital usage and gratifications in transition towards #smartcity surhita basu1,* and baby gharami2 1asst. professor, dept. of journalism & mass communication, women’s college, calcutta, baghbazar, kolkata, india, pin: 700003. 2pg scholar, dept. of journalism & mass communication, women’s college, calcutta, baghbazar, kolkata, india, pin: 700003. abstract introduction: the study explores how during covid-19 pandemic online apps helped people applying uses gratification paradigm to identify needs, usages and gratification of users. objectives: the paper investigates how covid-19 pandemic has affected the usage pattern of online apps? what is the gratification level of using online apps during covid-19 pandemic? how users perceive the use of online apps during covid-19 pandemic? methods: the study employs small scale snowball sampling survey across major cities of india addressing questions on comparative usage pattern of online apps before and during the pandemic, users’ gratification and users’ opinion of using online apps. results: usage of few apps like news, video, health increased during the pandemic with frequency and intensity of usage. users are concerned with misinformation spread through social media, demeaning family bonding due to high usage of apps, digital divide failing to provide enough job opportunities. conclusion: specific apps to deal with health emergencies should be developed along with mechanism against spread of misinformation and strategic attempts for digital inclusion. keywords: apps, social media, uses gratification, pandemic, india, post-humanism, smart city, risk society received on 26 june 2020, accepted on 04 december 2020, published on 19 january 2021 copyright © 2021 surhita basu et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.19-1-2021.168222 *corresponding author. email:surhita@gmail.com 1. introduction discussing ulrich beck’s thesis on global risk society, developed in the post-chernobyl era, d. s. l. jarvis [1] wrote, “risks are now incalculable and beyond the prospects for control, measurement, socialisation and compensation.…science now fails us, with conflicting reports, contradictory assessments and wide variance in risk calculations. faith in the risk technocrats evaporates, the hegemony of experts dissolves and risk assessment becomes no more than a political game than advances sectional interests.” the recent covid-19 global pandemic has similarly stripped off the embellished blanket of safety and security that the late modern society so laboriously has woven in the minds of people. capitalism with its nature of abundance and manufactured eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e5 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ mailto:surhita@gmail.com s. basu and b. gharami 2 stability maintains a hierarchy that ensures best benefits for the ones in the higher strata of structure. when situation such as a global pandemic hits hard challenging the core essence of capitalism, the stability is shaken down to mere irregular access of basic essentials – at times even not that. this triggers a demand for a new system of society, politics, culture and economics that would not fail humanity at times of such crisis. thus innovative solutions and creative outlooks for every aspect of life and living become that essential vaccine which safeguards the civilization in its struggle for survival. technology since long attempted to ease this struggle in various ways. the gradually increasing dependency of human on technology has pushed the society closer towards an era of post-humanism [2]. this fetched a densely mediated world where interaction and cohabitation with technology is of much higher frequency than with other human beings. however this change has not occurred just during the pandemic. there have been continuous attempts for gradual transformation towards a digital world over past few decades. the smart city mission of government of india [3] acknowledges “robut it connectivity and digitalization” with e-governance as core infrastructure elements of a smart city. further in 2016 india identified 20 cities for developing round one smart cities of india. india and the world at present are facing an unprecedented global crisis in this digital age. due to the covid-19 pandemic the gradual digitalization process witnessed a challenge for serving the suddenly increasing netizens in right way. india’s internet data consumption at the beginning of lockdown rose by 13% with 308 petabytes being consumed every day [4]. this high consumption of data clearly shows that citizens are accessing internet more than before as the crisis sets in. this triggers the question how people in this first large scale global pandemic of digital age are coping with the situation with the help of internet. are there innovative solutions that internet is providing for everyone in their fight for survival? for what purposes people are using internet? how online apps are helping them in such situation? how satisfied people are with the services of these apps? further there have been various concerns with the rising usage of online apps. such diverse recent concerns raise queries about quality and nature of experience of the users as well as their reaction to various issues related to the usage of online apps during the pandemic. the present study thus seizes the opportunity to investigate these questions. india, with second highest number of internet users in the world [5], with 40% internet penetration [6] till far and at the first phase of developing smart cities, becomes a valuable case study to explore how a developing nation with huge possibility of digitalization is coping up with this pandemic. 2. usage and gratification when bernard berelson investigated in 1945 ‘what “missing the newspaper” means’ during new york’s newspaper delivery strike [7], it was not only the beginning of a new era of theoretical and empirical exploration into the role and effect of mass media in society, but it was the beginning of a search into the interdependency and inter-relation between human and mediated manufacture. the proliferation of the uses gratification paradigm [8] enjoyed major contributions from lazarsfeld [9] , herzog [10] and wilbur schramm [11]. the core assumption of the paradigm is that media are used more in cases where the motives for using the media are met with greater satisfaction of the needs. as mcquail [12] has explained, “personal social circumstances and psychological dispositions together influence both general habits of media use and also beliefs and expectations about the benefits offered by media, which shape specific acts of media choice and consumptions followed by assessments of the value of the experience (with consequences for further media use) and possibility, application of benefits acquired in other areas of experience and social activity.” different social situations demand greater usage of media for satisfying various needs. usage of media can increase to ease social tensions, to attain information for social awareness, to replace real life opportunities, for social affirmation of specific values and to be updated to participate and be included in social interaction. the covid-19 pandemic has witnessed increased use of internet. this then triggers obvious questions behind the motives, uses and gratifications of using the medium. recent studies on uses gratifications have explored social networking sites [13], online games [14], mobile apps [15], virtual communities [16] and more. different researches have tried to capture the factors that lead the users to use social media and identified factors like social interaction, entertainment, escape, information, exposure, influence and inclusiveness to be important determinants [17]. gan et al [18] further classified the types of gratifications as cognitive, affective, social and tensionreleased. hsiao et al. [19] classified motivations as utilitarian, social and hedonic. there have also been studies on the usage of social media during pandemic [20] [21], particularly the h1n1 pandemic [22] of recent past. however not any past pandemic in recent times has been as severe as covid-19 pandemic and has not witnessed this scale of upsurge of use of internet globally. thus it provides an opportunity to investigate the impact of pandemic in the changing nature of usage and gratifications that internet users are drawing from the medium. further application of uses gratification concept in analysis of the rising apps and social media usage pattern has been scarcely used, particularly in the background of pandemic and health communication. in this context the present study stands distinct as it explores different usage of online apps and social media during the recent pandemic, particularly as an exploration of a theoretical extension. as the study focuses on the users’ behavioural pattern during the covid-19 pandemic eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e5 apps in time of pandemic: digital usage and gratifications in transition towards #smartcity 3 along with their preferences, opinions and gratifications of using the apps, it takes an in-depth look into the dynamism of uses gratification theory, into the changing usage patterns during the most recent pandemic and into the shifting relation between man and machine at the verge of post-humanist world. by investigating the motives behind the rising usage of internet, the study also attempts to comprehend the tendency of increasing usage of internet during the pandemic, establishing a relation between two. in the selection of its sample from a developing nation, india which is in process of transforming towards the first phase of smart cities, the study stands distinct offering a perspective from a multicultural, multi-lingual, multi-religious and dual economic nation. the study thus not only provides a theoretical deliberation, but also provides an understanding of people’s usage of digital technology for survival in difficult times, giving substantial evidences and references for developing smart cities. 3. method the present study thus explores the usages and gratifications of online apps including social media during the covid-19 pandemic of 2020. for this the study explores the following research questions. • rq1: how covid-19 pandemic has affected the usage pattern of online apps? • rq2: what is the gratification level of using online apps during covid-19 pandemic? • rq3: how users perceived the use of online apps during covid-19 pandemic? for rq1, to explore the impact of the pandemic on the behavioural pattern of using online apps, the research focused to compare the usage pattern before and during the pandemic based on accessing internet, frequency of using internet, intensity of using internet, activities in internet and preferences of apps usage. for rq2 the gratification level was measured through simple rating scale. for rq3 the respondents’ direction and degree of opinions were measured based on various statements related to using apps during covid-19 pandemic. for all these measurements, survey method [23] has been applied. considering all the respondents are users of online apps, the survey was conducted online. the online survey questionnaire consists of 25 questions excluding the demographical questions. the questions were developed to detect the users’ access pattern of internet, their frequency of accessing internet, their intensity of using internet, their activity patterns in internet, their choice of apps, the intensity of using the apps, the changes in using internet and apps before and during the pandemic, their satisfaction level of using the apps during the pandemic along with testing the direction and degree of opinion on nine different aspects of using online apps during pandemic. the questionnaire was developed keeping in mind the research questions. so a series of questions was asked to compare the usage pattern of online apps before and after pandemic to explore the first research question as how the pandemic has affected the usage pattern. also many questions were asked along with a rating question to understand the gratification level of online apps used during the pandemic, as the second research question demands. to address the third research question a series of questions were asked to understand the direction and degree of agreement with various statements that represent different perceptions towards usage of online apps during the pandemic. thus the survey instrument ensured face validity. also as the result showed, the survey instrument significantly illustrated predictive, concurrent and construct validity by offering results that affirmed with the published internet usage statistics, general predictions of apps usage and the theoretical explanation of usage gratification. for the survey the data was collected from different cities of india keeping in mind the urban centres, metropolitan areas and phase-one smart cities as urban penetration of internet is higher than the rural penetration in india [24]. the survey sample collected was mainly through purposive snowball sampling initiated from the established network of the researchers. the snowball sampling was initiated purposefully approaching at least one respondent from most of the proposed smart cities of india. the respondent was then requested to forward the online survey link further among other people they know residing in those areas and using internet. this has helped to approach many people across india who are now in a transition phase towards a more digital lifestyle and those who are already using internet heavily. thus the sampling technique ensured targeted useful responses to be included in the survey. as the purpose of the study was to detect the possible changes in the usage pattern of online apps due to covid-19 pandemic and to analyze the perceptions of the users on using online apps during pandemic, the study thus aimed for a small scale intensive investigation where the background of the respondents was analyzed to understand the responsive patterns. the survey was conducted during the months of may and june 2020 with the total sample size of 204. with a substantive requirement of 100 survey sample size for any statistically significant result [25] and considering the non-parametric nature of sample collection for rather detailed understanding of the survey responses rather than generalization, the sample collected sufficed the purpose. survey data was analyzed based on descriptive statistics and discussed in reference to uses gratification and other established theories. 4. result 4.1. demography eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e5 s. basu and b. gharami 4 for the small scale survey data collected was of 204 respondents. among this 82% of the respondents fall under the age group of 18 to 36 years, followed by 9% between 13 and 17 years and 5% between 37 and 45 years of age. so the respondents are mostly of young age group with only seven respondents being above the age of 46 years and one above 71 years. the behavioural aspects and opinions thus largely reflect that of the young internet users. considering 72% of internet users in india are from the age group of 16 to 39 years and 81% from the age group of 16 to 49 years [24], the emphasis on the young internet users for this study is thus justified. quite expectedly thus 58% of the respondents are students, while 31% are salaried and 11% are earning otherwise. 70% of the respondents have completed their postgraduate or graduate degrees in which 34% have completed the graduate degree. 20% of the respondents are yet to complete their graduate degree while 6% of the respondents hold degrees higher than masters’. 58% of the respondents are female while 42% are male. however in case of representation from economic classes, the respondents come from a wide range of sections without any particular bias to any specific category. thus 17% respondents are from category of monthly average family income of 20,001 to 30,000 indian rupees, followed by 16% respondents from the category of 10,001 to 20,000, 14% from 30,001 to 50,000, 13% from 1,000 to 10,000 and 12% each from 50,001 to 70,000 and from 90,001 to 1, 50,000. to summarize out of 199 respondents who responded to this question, 60% of the respondents have average monthly family income below 50,001 indian rupees and 38% of respondents have average monthly family income above 50,001. 32% of the respondents however have three family members, while 30% have four family members and 17% have five family members. thus it can be said 79% of the respondents have three to five family members. to establish a better perspective in this regard, the 2011’s census report of india considered rupees 816/capita/month to be the rural poverty line of india [26]. 3% of the respondents have also declared their average monthly family income to be less than 1,000 rupees. the responses came from 87 different cities from 20 states of india. 4.2. usage pattern access table 1. comparison of internet access devices: before and during the pandemic table 2. comparison of internet access points: before and during the pandemic in consideration of choice of device through which the respondents accessed internet, based on table 1 it can be seen that 97% of the total respondents who used mobile before the pandemic kept using it with a slight drop of 0.5%. however before the pandemic 44% of the total respondents used personal computers, which during the pandemic shot up to 46%. this change of percentage can be explained with the fall of usage of organizational computers from 15% to 5% and the fall of usage of computers at cyber cafes from 2% to 0%. in both the cases of pre-pandemic and during the pandemic, no one was there who was not using internet. this explains that out of 17% of the users who were earlier using internet at organizations or at cyber cafés, only 2% started to use internet at personal computer during the pandemic. however as no one was not accessing internet it explained that the respondents had more than one device to access internet and thus used internet during the pandemic either via their own mobiles or via their other device available at home. pandemic it seemed could not make anyone to lose their internet access. the users found a way to access internet even during the pandemic. similarly before the pandemic, as is evident from table 2, 89% of the respondents were using internet with their personal internet connection which witnessed a little drop of 3% during pandemic with 86% users accessing internet with their personal internet connection. this drop in usage of personal internet connection can be explained with 3% rise of home internet connection usage which rose from 38% usage pre-pandemic to 41% usage during the pandemic. there was also an expected considerable drop of percentage of using internet connections available at public places. this shows that during pandemic people are mode of access percentage of users before pandemic during pandemic mobile 97 97 personal computers 44 46 workplace computers 15 5 public computers 1.5 0 point of access percentage of users before pandemic during pandemic personal connection 89 86 home connection 38 41 workplace 15 3 public places 4 0.5 not accessing 0 0.5 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e5 apps in time of pandemic: digital usage and gratifications in transition towards #smartcity 5 going to use internet connections at home more than that of their personal mobile devices which are generally used more while travelling or outside home. wi-fi zones created in public places of various cities in such situation could not be useful. frequency and intensity internet usage has increased considerably during the pandemic. there have been reports stating that in the first few weeks of the lockdown in india, internet usage shot up by 13% [4]. figure 1. percentage of respondents using internet before pandemic based on frequency and intensity of access figure 2. percentage of respondents using internet during pandemic based on frequency and intensity of access in agreement to the same, the present study finds, as evident from figure 1 and figure 2, that while in the prepandemic time only 25% respondents were using internet almost all the time in a day, during the pandemic, the same shot up by 10 point to 35%. similarly before the pandemic only 16% respondents were using internet whole day while during the pandemic 28% respondents were using internet whole day. however earlier while 48% of the respondents were using internet daily for some time, it fell down to 31% during the pandemic. there is 5 point drop among the frequent users and 3% drop among the users who used internet rarely. so the frequent users and rare users of internet became more regular users during the pandemic. however there was none before or during the pandemic who was not using internet. there was still one case where the respondent reduced using internet during the pandemic than earlier in the sample collected. this shows that in cases where someone was using internet mainly for professional reasons, might choose not to use internet much during the pandemic. here the reason of using internet lesser than earlier is not the issue of access, as every respondent did have access to internet before and during the pandemic, the reason might be the personal choice exercised by the user. figure 3. percentage of respondents using online apps during pandemic based on frequency and intensity of usage further, in using different apps and social media, as it is found from figure 3 that 21% of the respondents are using apps for five to seven hours every day, while 17% respondents are using for 12 to 15 hours every day and again 17% of the respondents are using for two to four hours a day. 15% respondents are using apps for eight to 11 hours a day. 13% respondents interestingly have responded stating they use internet for whole day while 10% respondents use internet more than 16 hours a day. only 3% respondents use internet every day for an hour or two, while 1% use less than an hour and 2% does not use internet every day. this shows as the frequency of using internet increased during the pandemic, respondents were intensively using different apps and social media. following henry assael’s [27] classification of users of internet, only 7% of the respondents are not heavy users of internet. even raising the time determinant of heavy users of assael from 20 hours a week to 25 hours a week of internet usage, only 24% of the respondents would not qualify as heavy users of internet among the study respondents. thus the intensity of using internet for almost three fourth of the respondents qualify them as heavy users of the medium. this not only shows the increasing dependency of people on internet during pandemic, but also shows the spreading extensity of population using internet heavily. activity as the frequency and intensity of internet usage increased during the pandemic, the obvious question that is triggered is whether the online activity pattern has also changed during the pandemic. table 1 shows the finding of the question as what the respondents were spending so much of their time on in internet. eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e5 s. basu and b. gharami 6 table 3. comparison of internet activity pattern: before and during the pandemic type of activity on internet percentage of users before pandemic during pandemic communicate 72 70 study 67 70 video 64 68 music 62 62 news 57 63 professional 51 49 shopping 45 25 financial transaction 35 36 in comparison of activities done by the internet users before and during the pandemic, it is found as is evident from table 3 that there are slight drops in the percentage of users during the pandemic, who used internet prior to pandemic to communicate and for professional work. there is a serious drop of percentage of users during the pandemic who used internet prior to the pandemic for shopping purpose. as various professional and ecommerce activities were stalled due to lock-down, the drops in percentage of users of such activities could be explained. in the same time, there is considerable increase of percentage of users from before the pandemic to during the pandemic on online activities such as news consumption, studying and video watching along with a slight increase in financial transactions. these changes are evident in the data presented in table 3. as the lock-down and social distancing became norms during the pandemic, a large section of respondents who were students, had to shift their course-work activities online which is evident from the data. however rather than communicating with others, respondents were spending more time consuming news and videos. this offered an interesting finding that even though social distancing and lockdown have compelled people to stay in door, still rather than using internet to connect with each other more than before, the respondents had chosen to use internet more for news updates and for entertainment. thus the usage of internet has been not only to connect, but also for surveillance and entertainment – the classic functions of mass communication [12] as extended in this digital era. use of apps the present study attempts to explore particularly the usage of apps including social media before and during the pandemic. transferring service accesses to userfriendly applications has been a characteristic of smart cities. the present study explores different services and activities chosen to be done through online apps during the pandemic. table 4. comparison of apps usage pattern: before and during the pandemic type of apps percentage of users before pandemic during pandemic news 64 71 food delivery 52 25 cab booking 52 10 video 49 53 e-wallets 43 36 reading 40 47 photo 39 40 grocery shopping 32 28 health 0 31 there have been drastic changes in apps usages before and during the pandemic, as evident from table 4. the apps which witnessed huge fall in usage during pandemic and lockdown are food delivery apps, cab booking apps and online wallets. as lock-down, social distancing and contamination scare were prevailing the reason for the drop of usage of these apps can thus be explained easily. however interestingly online grocery shopping apps usage also declined which in the same logic could have risen as people were expected to prefer online mode of transactions for regular purchases. in such cases contamination fear and lack of availability of online groceries might be reasons for this decline of online grocery apps. the apps which witnessed sharp rise in usage are news apps, video apps, reading apps, photo apps and off course health apps. the choice of news and video apps agrees with the fact that more people were using internet for news and watching videos as seen earlier. however in addition to that more people have started to use reading apps and photo apps during the pandemic. this can be explained as that due to lock-down respondents found different ways to use their time resulting into sharp rise in reading activities and slight rise in using photo apps. what is most striking is the use of health apps which none was using before the pandemic, but 31% of respondents were using during the pandemic. it is interesting to note that in this digital age, social distancing, lock-down and pandemic would drive people to resort to health apps. this digital assistance is thus equipping people to navigate through difficult times such as this health emergency. respondents also chose apps that they were using the most before and during the pandemic. the top five apps before the pandemic were – (i) video watching apps with 19% user-respondents (ii) social networking apps with 17% user-respondents (iii) news apps with 12% user-respondents (iv) music apps with 11% user-respondents (v) shopping apps with 8% user-respondents eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e5 apps in time of pandemic: digital usage and gratifications in transition towards #smartcity 7 the top five apps used by the respondents during the pandemic were – (i) news apps with 25% user-respondents (ii) video watching apps with 24% user-respondents (iii) social networking apps with 11% user-respondents (iv) music apps with 8% user-respondents (v) reading apps with 6% user-respondents in both these cases there had been wide variety of usage. the range is more diverse during the pandemic rather than before the pandemic. before the pandemic, there were users who mostly used reading apps, learning apps, food delivery apps, cab booking apps, online wallets, photo apps etc. however during the pandemic, there were respondents who were using learning apps, online wallets, health apps, photo apps and many. the variety of apps usage increased during the pandemic than before showing increasing interest among the users in exploring new apps and using them to fulfil different purposes. 4.3. users’ experience usage of applications the respondents were asked to rank-order the purposes for using the applications during the pandemic. the first preference of the top ten purposes served by the applications is as follows. (i) entertainment (ii) news/information (iii) learning (iv) connecting with others (v) creative expression (vi) shopping (vii) financial transactions (viii) professional work (ix) health & fitness (x) social work the second preferences for the top ten purposes served by applications during the pandemic are as follows. (i) news/information (ii) entertainment and connecting with others (iii) connecting with others (iv) learning (v) professional work (vi) creative expression (vii) professional work (viii) health and fitness (ix) social work (x) shopping thus it is observed that most of the respondents found entertainment to be the most important purpose served by the online apps, followed by news and information. the top five important purposes thus served by the online apps are entertainment, news and information, learning, connecting with others and creative expressions. few believed professional work is also an important purpose for using the apps. however contrarily they claimed that the least important purposes served by these applications are social work and health and fitness, followed by shopping and financial transactions. thus it can be deducted that during the pandemic online applications are widely used to get information and news of the world; during the lockdown with spare times in hand, people used apps for entertainment purposes as well. however as social distancing became a norm these apps helped them to connect with others and keep on learning when outdoor activities were stalled. these apps helped the users to spend their time with creativity which in turn helped them to keep up their mental health as well. when lockdown and fear of contamination were prevailing these apps helped them to purchase their daily essentials. however apps were not much used for health and fitness purposes which can be an area of development for similar situations in future. there is very minor applicability of apps in social service during the pandemic, even shopping option was also limited to many. users’ gratification respondents’ satisfaction with online apps was very high as seen in the result. in a scale of 0 to 10 where 0 is the worst and 10 is the best experience of using apps during the pandemic, 82% of respondents rated 6 or above and 53% respondents rated 8 or above. only 6% respondents rated their experience 4 or below while 13% respondents rated at the mid-point of 5. the detail of the responses can be seen in table 3. table 5. users’ experience rating of online apps usage during pandemic where 10 is the best and 0 is the worst rating point percentage of users 10 20 9 14 8 19 7 19 6 10 5 13 4 5 3 1 2 0.5 1 0 0 0 in a separate question 49% of users responded that online apps during health emergencies such as covid-19 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e5 s. basu and b. gharami 8 pandemic are useful while 30% respondents believed it to be very useful. 20% respondents find it to be neither useful, nor useless. only 1% respondent found the apps not useful. definitely online apps have helped the respondents in different ways during the pandemic with high level of satisfaction. in a detail analysis between the types of apps used mostly during the pandemic and satisfaction level of using the apps, it is found that out of the 50 respondents who mostly used news apps during the pandemic, 15 found that very useful while 29 found that to be useful and none found it to be useless in any degree. similarly out of total 49 respondents who mostly used video watching apps 16 found it useful while 23 found it very useful as none found it useless at any degree. among the two respondents who marked usage of online apps during pandemic as useless and as very useless, one who was using video watching apps mostly marked it as useless and one who was using social media apps mostly marked it as very useless. 4.4. users’ opinion new users 59% of the respondents agreed with the opinion that during pandemic many people who were not using any online app earlier have started using these. 26% respondents strongly agreed with the statement while 11% neither agreed, nor disagreed. only 4% disagreed while none strongly disagreed. this shows that there is high possibility that not only the frequency and intensity of the usage of online applications have increased during the pandemic, but the number of new users have also increased. adding new users explains the increasing necessity of online apps during pandemic and increasing dependency of people on online apps to survive through the situations such as the pandemic. new usage 61% agreed with the opinion that many people have found new usage of online apps during the pandemic. 28% respondents strongly agreed with the statement while 11% neither agreed nor disagreed. only 1% respondent disagreed with the statement while none strongly disagreed. this shows the possibility that people have devoted their time in exploring online apps and the features of the existing apps. this exploration of online apps shows that people are not only interested in using apps but also looking for different support mechanism during the pandemic though these apps. for example, it is seen earlier that 31% of the respondents who were not using health apps have started using it during the pandemic. thus many people have found new usage of online apps during the pandemic making the citizens much more dependent on digital technology. necessity of apps 31% of the respondents agreed with the statement that without the online apps it was not possible to survive through the pandemic, while 26% respondents strongly agreed with the statement. 24% respondents neither agreed nor disagreed with the statement while 15% disagreed and 3% strongly disagreed. thus while 57% respondents agreed with the statement with varying degree, only 18% respondents disagreed with the statement in varying degree of the opinion. the dependency of users on online apps during the pandemic is obvious. as is seen earlier, for news or for entertainment or to connect with others, online apps have been a major support during the pandemic. these apps have made life much easier of the users. however in the same time it has to be kept in mind that there exists certain percentage of users who found online apps redundant and believed it to be possible to live through such emergency situation without such support. misinformation while 49% respondents agreed with the statement that social media have crated lots of misinformation among citizens during the pandemic, 18% strongly agreed with it. 27% of the respondents neither agreed nor disagreed with the statement, while 6% respondents disagreed. none of the respondents strongly disagreed with the statement. 67% of the respondents thus believed that though online apps were useful during pandemic but simultaneously it was responsible for creating lots of misconception and misunderstanding which are dangerous in times like health emergencies. in this context it has to be kept in mind that 71% of the respondents were using apps for news consumption during the pandemic. the primary purpose served by the apps was to receive news and information. in such situation when people are depended on apps for the news, it becomes a major concern if misinformation is spread through these apps. alienation as online apps have been used to to connect with others during the time of lockdown and social distancing, it simultaneously for many has created distancing within the family. 40% of the respondents agreed with the statement that online apps are responsible for generating alienation and social distancing within the family while 12% respondents have strongly agreed with the statement. 26% respondents neither agreed nor disagreed with the statement. however there are 19% respondents who disagreed with it while 1% strongly disagreed. thus while 52% believed online apps were responsible in creating distance among family members, 20% respondents did not think so. in a time of crisis, online apps are helping people to cope up with the situation; however simultaneously increasing usage of online apps is creating different set of problems. eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e5 apps in time of pandemic: digital usage and gratifications in transition towards #smartcity 9 employment economic slowdown due to pandemic has resulted into possibility of recession. this has hit hard many small businesses and enterprises. many people have lost their jobs and faced pay cuts. however as many services were available online, different apps offered the opportunity of earning for many. 27% of the respondents thus believed that online apps have provided job opportunities for many during the financial crisis due to pandemic while 10% of the respondents strongly agreed with the statement. interestingly 41% of the respondents neither agreed nor disagreed with it while 18% respondents disagreed and 3% respondents strongly disagreed. so only 37% respondents agreeing with the employability aspect, 21% disagreeing and 41% uncertain about it, it is to be noted that a nation like india with 40% internet penetration online apps might not largely be source of income for many; however simultaneously in time of crisis it has helped many people as well. surveillance there have been many instances prior to pandemic when surveillance through social media and various other apps has come under severe criticism. in the same time there have been instances where application of digital surveillance technology has helped in controlling spread of pandemic [28]. 44% respondents agreed with the statement that surveillance through online apps cannot be avoided during health emergencies and pandemics. 7% respondents strongly agreed with the statement while 8% respondents disagreed and 3% respondents strongly disagreed. 37% of the respondents neither agreed, nor disagreed. more than half of the respondents 51%, accepts the fact that surveillance through apps are necessary to cope up with pandemic. digressive non-productivity there is growing number of studies on the side-effects of using social media and online apps heavily [29]. one of the major concerns with the heavy users of social media and other online apps is the resultant lethargic condition which becomes a hindrance towards productivity. this also creates diversion from many serious issues and concerns. in the present study 29% respondents agreed with the statement that online apps are wasting time which could have been used in more productive manner during the pandemic. 14% of the respondents strongly agreed with the statement while 18% respondents disagreed and 1% only strongly disagreed. 38% of the respondents neither agreed, nor disagreed with the statement. this shows that there is a concern among the user-respondents who are mostly heavy users of internet during the pandemic that their productivity is stalled with heavy usage of online apps. awareness of sensible and smart usage of technology is also necessary with the advancement of technology. future of apps 54% of the respondents agreed with the statement that use of online apps was going to rise. 27% of the respondents strongly agreed with the statement while 17% neither agreed, nor disagreed and only 2% disagreed with none strongly disagreeing with the statement. a country like india which was gradually growing towards digitalization, covid-19 pandemic has worked as a big push towards it. as the business, lifestyle and social functions are going to change a lot after the pandemic it seems the respondents believed the digitalization of india, people’s usage of and dependence on online apps are going to rise faster and further. this has indeed hastened the process of creating smart cities in india. 5. discussion baran and davis [30] writes in explaining the uses gratification concept that “uses gratifications approach provides a framework for understanding when and how different media consumers become more or less active and what the consequences of that increased or decreased involvement might be.” there have already been statistics released by various organizations on the increased use of internet during the covid-19 pandemic. the questions that the present study attempts to answer are when and how internet users are becoming more or less active and what the impact is of this increased or decreased usage of internet and of particularly online apps. the study affirms with other reports that there has been increased use of internet during pandemic. as people are staying in-door during the lockdown period, tendencies were seen towards using the home internet connection more rather than personal connection. digitalization and developing smart cities include creating free wi-fi hubs in different public spots for easy access of internet. though the initiative should be applauded, yet it is important to note that during times like pandemic, many people are dependent on home internet connection and not the public ones. to bridge the digital divide, it is thus important to install free wi-fi zones in areas where there is lack of home internet service providers or less access to paid internet connectivity. thus it will help to inform and update the residents of that zone during pandemic or health emergencies. the frequency of accessing internet has also increased during the pandemic with more people using internet daily than before and for longer duration. this definitely calls for developing an infrastructure that can support sudden rise of traffic and data consumption which became difficult to handle at the beginning of the lock-down period in india. as stated earlier the present study attempts to explain the reason behind this rise of traffic and describe its nature. the main three activities that witnessed sharp rise during the pandemic are news and information consumption, watching videos and study related activities. as lock-down implemented few restrictions, so there were few expected declines like that eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e5 s. basu and b. gharami 10 of online shopping activities. the three major usage of internet and online apps during the pandemic are surveillance or information gathering about this sudden unexpected situation of pandemic and developing an understanding of the situation, entertainment as easing up social tensions that resulted due to health emergency as well as to pass the free times during the lock-down. also as many of the respondents were students, so a lot of learning activities shifted online also received a considerable share. one interesting addition to the list of apps has been health apps which witnessed a surge of users during the pandemic. this explains that internet users were not only using apps to get news and information about the pandemic, but they are also transferring the knowledge into action by downloading and using health apps either for maintaining their health and fitness or to purchase medical products and services, or simply to avail many added features that health apps started to provide during the pandemic. in any case it is evident that many people are trying to survive through the health emergency with the help of online apps. so investment in developing such apps for providing useful information and availing necessary services should be encouraged and initiated. the user-respondents as it is seen are very satisfied by using online apps during the pandemic. as the satisfaction levels are compared with the activities it is seen that these gratifications are generated with the quality and quantity of information and news received through online apps, the high level of entertainment offered by various apps and social media. pandemic also has worked as a big push by inspiring and compelling many to use online apps to satisfy various purposes. maintaining social distancing, fighting out the fear of contamination and keeping up mental health these news, entertainment, learning apps have helped the users in various ways. the dependency and utility of the apps were so high that most of the users accepted surveillance through online apps if that means more safety from the chances of contamination. however in the same time there have been serious concerns with misinformation spread via social media. in cases of health emergencies misinformation might cause lives of people, create a lot of misconception leading to malpractices. the high usage of social media and other online apps have also driven the users into a self-centred world alienated from other family members. much of the times the apps were used for entertainment purposes, that appeal to right brain mostly, leading to higher release of dopamine creating a hypnotic state for the users [31]. as krugman effect [32] studies established, this creates a hypnotic effect compelling the users to lose much of their productive time and human interactions. interactive media such as internet mostly demand active participation of the audience. uses gratification concept has proliferated from this active audience studies. however even in such cases the acknowledgement of the users that they are losing much of their productive time and family bonding due to internet and online apps, illustrates that features of posthuman era where less human interaction and more digital interaction controls the lives of people. though online apps have been very useful in the times of pandemic, yet it has to be kept in mind that over-dependency on digital technology might affect society in a negative way. there rises the necessity of digital detoxification to be promoted even in the times of pandemic. another important aspect of using online apps during pandemic is that it has created many job opportunities at the time of financial crisis resulted out of the health emergency. however in a country like india where internet penetration is only 40%, wherein the global inequality index ranks the country among the bottom 15 [33], the concern with digital divide should be high. india is still in transition towards digitalization, with first round of smart cities developing. investing on apps to fight health emergencies as such in future is essential, but not the only solution. covid-19 pandemic has created the big push where many laggards have transformed into adapters of the new technology, as with roger’s diffusion of innovation [34] concept can be explained. however still a large section of population does not have fast and uninterrupted internet connection. priority should be for digital inclusion along with developing more suitable health apps. also a mechanism for fighting misinformation should also be established. developing apps might not be only solution in such cases, society should be trained and awareness should be spread on sensible usage of apps. 6. conclusion the first research question (rq1) was, how covid-19 pandemic has affected the usage pattern of online apps. as is evident from the result and discussion the pandemic has increased the frequency and intensity of using internet. people have shifted from using public internet connections to home internet connections. there is higher amount of news and entertainment video consumption during the pandemic than before along with declining usages of shopping, food delivery, cab booking and financial transactions apps. many new users have been added during the pandemic as many new apps have been explored by the users. thus the main usages of online apps including social media during the pandemic as identified are surveillance or information accumulation, news and information processing for understanding the situation, entertainment and connecting with others. the second research question (rq2) was about the gratification level of using online apps during covid-19 pandemic. as seen in the result section, the gratification level of using online apps has been very high. many users believed it would have been difficult to cope up with the pandemic, lockdown and social distancing without online apps. thus it can be said that information seeking need, entertainment need, need for developing comprehensive understanding of the situation, need for social interaction were largely satisfied with the online apps during the pandemic. eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e5 apps in time of pandemic: digital usage and gratifications in transition towards #smartcity 11 the third research question (rq3) was how users perceived the use of online apps during covid-19 pandemic. in this explorative question it was found that though most of the users are satisfied using the online apps, but there is concern with misinformation spreading through social media apps. there is also a wide-spread acknowledgement of the fact that high usage of online apps has resulted into low level of interaction with family members. digital divide has also been a concern. in case of creating job opportunities in time of financial crisis these apps have not been very successful due to this digital divide. the users acknowledge that the future holds higher amount of digital penetration with more activities going online and more people resorting to online apps usage. the study thus in the stream of uses gratification theories explores the usage and gratifications from online apps, particularly during and as result of the pandemic. in its exploration the study has dependent on purposive snowball sampling which if adapted to a stratified random sampling procedure with larger sample size might produce result appropriate of generalization. however that would require much time and resource as a major project. the present study thus can be used as preliminary work for such large scale projects offering probable variables and insights to explore. further as the study is conducted online only, it does not include a particular section of the society which might not access internet or access very little. to understand and include the nature of internet usage of this section of society, only online survey might not be appropriate. the present study targets 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[34] e. m. rogers, diffusion of innovations, 3rd ed. new york : london: free press ; collier macmillan, 1983. eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e5 a methodical plan towards smart economy in new egyptian cities 1 a methodical plan towards smart economy in new egyptian cities abstract introduction: initial patterns of urbanization world demonstrate differing scenarios in different continents, requiring diverse methodologies, policies, and strategies. the information & communication technology (ict) leads to the development of the city management and smart economy which does not adhere to borders and nationalities. the egyptian economy passed through various stages of development in the last few years, the government policy has national egyptian initiatives towards the smart economy. objectives: stand on the structure of the smart economy to draw the path for egypt's local economy to evaluate the existing economic state and conclude to a guiding methodology towards the smart economy in new egyptian cities. methods: analytical approach to investigate "concepts, the smart economy as a pillar of smart city, urban entities, examples of smart economy projects around the world". cross-analysis between national governmental initiatives in egypt to support the smart economy and some development indicators in the new cities. results: the difference in the locations, inhabitants' nature of new cities, requires various and varied approaches to process towards the smart economy. conclusion: the research proposes an adaptation methodical plan for developing the smart economy concept in new egyptian cities, this plan depends on the constants, variables, policies on both national & local levels. keywords: smart cities – smart economy – egyptian governmental initiatives – new cities received on 05 december 2019, accepted on 14 may 2020, published on 21 may 2020 copyright © 2020 reham m. hafez, licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.164661 *corresponding author: reham_hafez@hotmail.com 1. introduction it is the time of a global urban transition; cities are reflected as the main forms of achievements in human civilization over the ancient and modern history, and the location of economic activities. at present, cities are the source of goods production and services for both internal and external consumption. cities embody a sense of innovation —all aided by the incessant technological progress that man develops every day. today’s city is a high-speed communication hub with a complicated system of information and communication technologies’ (icts) infrastructure [1]. cities become an engine of economic growth due to fast communication devices; laptops and mobile [2]. cities also act as ‘magnets of hub and ‘centre of wellbeing’ for a vast array of skilled and unskilled people who are looking for a better quality of life. cities can perform these miscellaneous functions as they proclaim to have better infrastructure and services (compared to their rural counterparts), which aid their economies and related creative and technology-driven production procedures. [3] reham m. hafez housing & building national research center (hbrc), egypt eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e1 http://creativecommons.org/licenses/by/3.0/ mailto:reham_hafez@hotmail.com reham m. hafez 2 the concept of the smart city is based on a municipality that uses information and communication technologies to improve the quality of government services, increase operational efficiency, and share information with the public. the uk department for business, innovation, and skills (bis) defines the term smart cities as: "a management process, in which increased citizen engagement, infrastructure, social capital, and digital technologies make cities more livable, resilient and rise its ability to face challenges" [4]. the british standards institute (bsi) defines the smart city as “the active integration of physical, digital and human systems in the built environment to realize the better future for its residents [5]. the smart economy is one of the main pillars of the smart city. 2. research methodology  the study depends on an analytical approach to investigate the concept & aspects of the smart economy focusing on its applied projects and urban utility.  related reviews of the literature of the smart economy (definition & structure) were collected. an inductive analysis approach of plans and projects was reported from the smart cities around the world in an attempt to draw the path in which how the city's economics can be transformed into smart.  cross-analysis between the egyptian national initiatives towards the smart economy and the local development in new cities to evaluate the current situation.  a methodical plan towards smart economy in new egyptian cities is suggested as a result of the evaluation of the current situation. 3. the smart economy 3.1 the smart economy concepts, definitions. the smart economy, in general, is the concept which concerns with the knowledge economy, where innovation and technologies are well-thought-out as the main sources of powerful force [6]. there are many approaches to illustrate the structure of the smart economy such as:  smart economy is a concept of how to realize the best for the existing and future generations at the same time, through policies that encourage innovation and creativity combined with scientific research, higher technology, and care for the environment. [7]  it is a multidimensional concept, described by three unified dimensions: economic, social and physical. economic: as there are innumerable opportunities and economic resources, allowing all groups in society to obtain a good income to achieve a good standard of living. [8] social: the smart economy provides the best health and education standards that enable an individual to build his capabilities intelligently and effectively physical: where the smart economy enables the individual to take advantage of his capabilities in achieving self and community development.  the smart economy uses networks to organize the innovation clusters and shared cooperation between enterprises, research centers, and the citizens to sustainable development. [9]  smart economy supports the enterprise through the expenditure of human resources (knowledge, skills, and creativeness), changing thoughts into valuable practices, products, and services [10] 3.2 the smart economy as the main pillar of smart city smart city system consists of six pillars: (i) smart people, (ii) smart city economy, (iii) smart mobility, (iv) smart environment, (v) smart living, and (vi) smart governance. each one of these pillars has its characteristics to contribute to the smart city system and closely interlinked with the others. the research illustrates it in the following table. [1] table 1. pillars of smart city system smart people smart economy smart mobility (1) people should be elearners. (2) open-minded (3) have a good healthy life. (4) work professionally. (5) have a high human development index (6) flexible, resilient to changes. (7) participate in public life. (1) understands its modern economy. (2) is driven by technology & innovation and supported by universities, (3) has enlightened entrepreneurial leadership. (4) economic opportunities for all people categories. (1) it focuses on people's mobility, to reduce the vehicle's movement. (2) supports & encourages walkability and cycling. (3) it has vibrant streets (at no additional cost). (4) good management of traffic congestion. eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e1 https://searchcio.techtarget.com/definition/ict-information-and-communications-technology-or-technologies https://searchcio.techtarget.com/definition/ict-information-and-communications-technology-or-technologies 3 (8) a smart city maintains a high graduate enrolment ratio and has people with a high level of qualifications and expertise. (9) its inhabitants aware of lifelong learning and use e-learning models. (5) uses local material, develop national production. (6) accepts globalization challenges. (7) promotes a sharing economy. (8) thinks locally, acts regionally, and competes globally. (5) sustainable transport system. (6) has balanced & innovative transportation options. (7) will has integrated mass rapid transit systems, such as metro rail, light metro, monorail, or ‘sky train’ for high-speed mobility. (8) high-speed mobility in density areas. smart environment smart living smart governance (1) protects and values the natural heritage, unique natural resources, biodiversity, and environment. (2) is attractive and has a strong sense of place that is rooted in its natural setting. (3) conserves the ecological system in the city region. (4) embraces and sustains biodiversity in the city region. (5) efficiently and effectively manages its natural resource base. (6) has recreational places for people of all ages. (1) respects the local history, culture facilities, and nature. (2) active downtown, 24 h and 7 days a week. (3) provides women, and children, senior citizens with safety, security and ideal place. (4) it improves the urban way of life. (5) uses natural and cultural assets to build a good quality of life. (6) deals and concerns with all small details of citizens. (7) has high-quality houses and open public spaces. (1) has practices of transparent decision (2) uses & operates through intelligent technologies and spatial data to make the decisions. (3) constantly innovates e-governance for the benefit of all its residents. (4) has the ability to deliver public services in an efficient and effective way. (5) has a participatory vision from the society in, planning, budgeting, implementation. (6) works in the aim of sustainable urban development strategy 3.3 the linkage between the smart city pillars. from these main pillars, we can summarize the main keywords for a smart city in the opposite fig. 1, we can determine what the smart city should offer to its citizens: an adaptable, accessible, reliable, scalable, and resilient way for living, such as: ■ good quality of life for its residents. ■sustainable economic growth with different job opportunities. ■ the easy life of access to social and community services. ■ create a sustainable environmental approach to development. ■ ensure efficient service and infrastructure such as water supply, public transportation, drainage, communication support, and other utilities; ■ resilient to climate change and environmental matters. ■ provide effective controlling and local governance tools ensuring impartial policies. so the smart economy is the main core of the smart city. it drivers the city initiatives, determining the degree of economic competitiveness through innovation, entrepreneurship, brands, productivity, labour market flexibility, as well as integration between the local and global markets. 3.4 urban basis entities & projects for the smart economy the urban society illustrates the structure of the smart economy as a developed urban area that creates a better quality of life through sustainable economic development, using human resources, social capital. many urban entities can support the smart economy; the research will list examples in this field in the following lines: 1.smart creative industry the smart creative industry reconnoitres smart solutions using intellectual technologies, to optimize the industrial operations towards an optimal value chain. it has: technologies and fig. 1. the linkage between the smart city pillars a methodical plan towards smart economy in new egyptian cities eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e1 http://www.businessdictionary.com/definition/developed.html http://www.businessdictionary.com/definition/urban.html http://www.businessdictionary.com/definition/quality-of-life.html http://www.businessdictionary.com/definition/economic-development.html http://www.businessdictionary.com/definition/human-capital.html http://www.businessdictionary.com/definition/social-capital.html reham m. hafez 4 communications support, access to international & national trade, market competition, internet services, and free flow of ideas. therefore, the smart city ideas are the capitalization of ideas and skills of city development. and it is built by governance in different degrees and also by different associations and technological interpretation. 2.clean and green industries green industries is an economic activity that aims to minimize its effect on our environment, so it ropes the green economy to decrease giving out to air, water, and soil from the industry. the green industries endorses the globular economy, resource efficiency and the conservation of natural resources. [11] 3.free trade zone – special economic zone ftzs are established to speed up development by creating a highly business environment and encourage foreign investment. the idea of a free trade zone is a custom of the hubs countries which invest their outstanding location to attract businesses through cost advantages and preferential treatment. they, thus, contribute to the change of the national economy as a whole. it moves on from being a labour-intensive economy to skills and technology-intensive one. 4.smart e-commerce and shopping electronic commerce is the transaction of goods or services over computer networks, mostly social media channels and the internet. e-commerce stages provide people with e-commerce software and services, through different technological devices such as funds transfer, digital marketing, mobile banking, mobile commerce, internet marketing, supply chain management, electronic data exchange, record management systems, and automated data collection systems. these services help to reduce the time of delivery after automatic payment is made, which ranges from a few hours to many working days. 5.smart real estate a smart real estate is a platform for managing the process of real estate trading and dealings with numerous solutions anywhere and anytime. the new platform allows complete operations of displaying and sale of real estate utilities using internet browsers and smart devices, so it's comprehensive numerical management of real estate dealing, excluding paper documents and decreasing brokerage procedures. 6.a smart work centre (swc) it is an office centre within the closeness sites of a residential community, which provides space to citizens in an individual or a group work setting, through the use of it technologies and multiple applications. the local community can get daily needs as child daycare, high-end catering services, financial services, supplemented by good access to highways and public transport. so the benefits of a smart work center are : (1)provide the citizens with a physical workspace close to their residence, resulting in minimize transportation demands and achieve good productivity. (2)support and help local citizens in the local community. (3) gathering employers can provide their workers with flexible working space options. 3.5 examples of different economic projects in smart cities around the world according to the previous urban basis entities, the research has collected examples of different economic projects that have been applied in smart cities around the world as illustrated in table 2. table 2. examples of different economic projects in smart cities around the world projects city (1) creating new technology jobs: smart london export programmer using citizen's initiatives. (2) create new district heating networks. (3) implementation of congestion charging, ‘oyster’: smart ticketing, announcement information of real-time travel for buses. (4) talk london: a collaborating website aims to comprise citizens in policy discussions, (5) london data store: gives citizens access to the city data from different public departments. (6) london boroughs: online services of saving money by moving to and joining with neighbouring on transporting them london eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e1 5 (1)city-zen: virtual power plant: storage and trade of surplus solar energy through home batteries (2) smart flow: optimize traffic through smart data and different applications, enhance parking efficiency, and promote eco-friendly. (3) smart energy playground for the whole family : reinventing the first gaming platform by transforming the generated energy into lights, (4) thousands of businesses, households, and job opportunities through (1) pick up garbage, along with solar panels powering bus stops (2) energy-efficient roofing insulation, automatically lowering light switches, smart meters, and ultra-low energy led lights. amsterdam (1) combined solar panels: tokyo’s corporate collaborations have generated homes with storage batteries, and energy-efficient applications connected to a smart grid. (2) control of over 100 train lines and transporting upwards of 14 billion passengers per year tokyo (1) the investment map: it’s a combined application that can be used by businessmen, developers, citizens, visitors can do real estate best practices through clever real estate market applications : enable the investors to access many investment project opportunities through their smart devices.  allows complete process of displaying and sale of real estate from start to finish using internet browsers and smart devices (android, ios). allows developers to propose their projects to concerned investors from all over the world.  the investment map project was implemented by google inc. performs dubai based on the previous section, the needed essential projects for the smart economy in cities distributed according to city –district – neighbourhood were concluded as shown in fig. 2. fig. 2. the needed essential projects for (city –district neighbourhood) 4. steps towards a smart economy in egyptian cities. 4.1 egypt sustainable development strategy egypt has economic growth, averaging 3%–5% from 2016 to 2019 [12]. egypt has adopted an neighbourhood district city a methodical plan towards smart economy in new egyptian cities eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e1 https://amsterdamsmartcity.com/projects/city-zen-virtual-power-plant https://amsterdamsmartcity.com/projects/city-zen-virtual-power-plant https://amsterdamsmartcity.com/international-projects/smart-flow https://amsterdamsmartcity.com/international-projects/smart-flow https://amsterdamsmartcity.com/international-projects/green-energy-playground-for-the-whole-family https://amsterdamsmartcity.com/international-projects/green-energy-playground-for-the-whole-family reham m. hafez 6 investment policy as the main key to economic growth. the investment policy depends on reducing obstacles to how international companies invest and run in egypt, which enhance employment opportunities and increase egypt's competitive power across the region. main challenges faced egypt throughout the past few years as follow: 1.the increase in population growth rate. egypt is one of the most overcrowded countries in africa and the middle east. the assessed population of 2019 is 100.39 million instead of 72.7 million in 2006. egypt takes the place of 14 ranks in the world. the population of the capital, cairo, around 10.902 million (estimations, 2019) [13]. the density of egypt as a whole is 84 people / square kilometers. cairo has a heavy density of 46,349 per kilometer square. overall, egypt ranks 126th in the world in terms of population density [14]. a majority of the population survives on the sides of the nile river, in an area of 40,000 square kilometers. cairo, alexandria, and giza are the three largest cities in the country. 2.lack of clear sustainable policy to allow utilizing human resources in a way that would contribute to human development. these vital problems were the incentive to do this research, where egypt needs to make changes to systems, infrastructure, and economic progress to achieve the benefits of the development. citizens need a decent quality of life; this includes main keywords sufficient freshwater; worldwide access to domestic energy, the ability to mobile efficiently from one point to another; a sense of safety and security. egypt economics had faced what may seem to be conflicting objectives. due to the instability of political conditions through the 30 years ago, so there’s a vital need to restore economic permanence to achieve better standards of living with more job opportunities, less poverty, well health and education systems. these are the main reasons why people ran to the streets in 2011. at the same time, there’s a long-standing need to reduce budget deficits, public obligation and inflation, and adequate foreign exchange funds. egypt launched in 2016 the country's sustainable development strategy for the next 15 years intending to raise gross domestic product (gdp) growth to 12 percent in 2030, up from the 4.2 percent attained last fiscal year, while reducing the budget deficit to 2.28 percent from 11.5 percent. the sustainable developing strategy incorporates economic, social, and environmental dimensions in addition to knowledge and innovations,". [15], in conjunction with that egypt’s ict 2030 strategy concentrates on the dimensions of sustainable development, with three pillars: the economic pillar: highpoints economic development, transparency and efficiency of governmental organizations, energy, and investment. there are pilot programs (business setup – boost a business –market accessskills development – support services – invest in egypt). the social pillar: highlights education and training, health, culture, and social justice. the environmental pillar: focuses on the environment and urban challenges. [16] 4.2 national egyptian initiatives towards the smart economy the government of egypt has launched the main programs to achieve the strategic targets through three main goals, namely; economic development, the competitiveness of markets and human capital. these programs seek to: 1. law 15 of the year 2004 information technology industry development agencyis considered the first step of the technological support of governmental entities. this low aims to floor the way for the transmission of the e-business services in egypt capitalizing on different decrees of the authority as activating the egyptian e-signature law and supporting an exportoriented it sector in egypt. 2. maximize the use of local energy sources – traditional or renewable – and the development of the productive capacity of the energy sector to be more effective in boosting the economy and adapt to the ever-growing changes in the field of energy. 3. promote human resources through two main axes; education and health, it also includes fair access to the basic health interventions for all citizens by up to 80 percent and ensuring 100 percent coverage of vaccinations nationwide. 4. seek to place 10 egyptian universities on the list of the top 500 universities in the world. 5. adopt a more effective administrative & transport system by increasing services provided by non-governmental organizations. 6. stipulates placing egypt among the top 40 countries in reducing waste in government spending, and to be among the top 20 least corrupt countries in the world. 7. include major reorganizations in the fields of itc industry and investment. 8. establishing some principles of smart cities & smart economics in developing new cities that are being planned, such as eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e1 http://worldpopulationreview.com/world-cities/cairo-population/ http://worldpopulationreview.com/world-cities/alexandria-population/ http://worldpopulationreview.com/cities/ 7 new administrative capital and new allaman. the research presents and evaluates in the following section table 3. various government initiatives and its effects for supporting the pillars of smart economy. table 3. national initiatives and its effect to support the smart economy government initiatives smart economy pillars in no va tio n su pp or te d by un iv er si tie s d iv er se ec on om ic op po rt un iti es . w or k lo ca lly b ut th in k gl ob al ly . m ak e st ra te gi c in ve st m en ts su pp or ts , an d pr om ot es sh ar in g ec on om y. t he h ig h fle xi bi lit y of th e la bo ur m ar ke t. w el co m es hu m an re so ur ce s su st ai na bl e na tu ra l re so ur ce encouraging investment in all fields establish a new administrative capital. development of the suez canal region as a logistics hub. restructure of governmental agencies. digital transformation and automation of government systems. issuing the law of the incentives of science, technology, and innovation, issued no. 23 of 2018 . establish a science valley, technology incubators, and technology companies. the exploitation of egypt's geographic location as a hub for aviation and transit tourism. adopt a program to enhance the competitiveness of the egyptian product in local and international markets. the trend to rely on the local product in the industry. the national project of gridconnected small scale solar systems. programs to support small and medium enterprises. establish technology universities. a methodical plan towards smart economy in new egyptian cities eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e1 reham m. hafez 8 transforming cultural institutions into centres for the development of creativity from the table we can conclude the following: (1) there are many government initiatives and attempts to go towards the ict system in egypt, which supports most pillars of the smart economy. (2) the government is focusing mainly on the policy of supporting domestic and foreign investment in economic development, which helps the exchange of expertise in various fields. (3) the linkage between the universities and the researches centres is missing especially on the local economy level. 4.3 new egyptian cities as a key for economic development egypt has 249 existing populated cities in 27 governorates and 42 new cities distributed in all governorates [17]. recently, most of the foreign & national investments are headed to the new cities in addition to its current economic base. the industry is considered one of the main economic bases of egyptian cities, in addition to services, and trade. the new cities have urban plans and specific infrastructure that can be developed and transformed into smart if they are compared with existing cities. numbers of different new egyptian cities in different regions were chosen, belonging to the urban and agricultural governorates to show some indicators about the economic base and the percentage of investments shown in table (4) as follow:  east cairo: el-shorouk el-obour –badr – new cairo.  west cairo: 6th of october sheikh zayed.  delta region: 10 ramadan new damietta.  alexandria region: borg el arab.  north upper egypt region: new fayoum.  south upper egypt region: new assiut. table 4. indicators about the economic base and the percentage of investments in some new cities in egypt city population area no of factories job opportuni ties investmen t (billion egp) actual (1000 person) target (1000 person) ( 1000 fadden ) working under constructio n 10 ramadan 850 2100 95 2997 1028 500000 29.2 new damietta 169 500 6.67 516 206 18696 7 6 october 1500 3000 171.4 1690 694 148000 35.8 zayed 350 675 10.386 5.3 new cairo 1000 2000 85.580 67 290 6000 32.6 el shrouq 340 500 16.110 7.3 badr 180 840 18.500 564 730 30000 9.6 obour 600 900 13.416 1283 754 111000 11.4 borg el arab 166 750 47.403 1299 840 11500 4.9 new fayoum 3500 140 12851 6 426 5000 1.1 new asuit 35 750 30.000 7 50 200 4.1 fadden = 4200 square meter source: the official website of the new urban communities authority, www.newcities.gov.eg [17] from the table we can conclude the following: 1. the new egyptian cities can be divided into 3 categories. first: cities have high numbers of investment and job opportunities (the strong economic base) such as 10 ramadan, 6 october, and new cairo, all of them are located in the greater cairo region. eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e1 9 second: cities have low numbers of investment and job opportunities such as new damietta, badr, obour, new borg el arab, new fayoum and new asuit. third: cities have no industrial economic base: such as zayed and el shrouq. 2. cities around the capital cairo attract the largest amount of investment. 3. cities in the upper egypt region have limited chances for attraction investments. 5. results  the new cities in egypt have attracted investments through the last 30 years, so they have created a lot of job opportunities through their industrial zones which are considered one of the key sectors that supports the economy and national production.  the egyptian government is moving towards the digital transformation with quick steps although the knowledge and technology sector is still nascent, it is supported by government initiatives at the national level.  there are no trails to settle the ideas of the smart economy at the local levels in new cities.  the difference in the locations, inhabitants' nature of new cities, requires various and varied approaches to process towards the smart economy. 6.recommendations each new egyptian city has a special nature in terms of location, population, and economic base. due to the nature of the smart economy which depends on the use of human capital-knowledge, skills, creativity, and natural resources, each city needs a special integrated plan which can take it towards the smart economy. that local communities in egypt need an intermediate link that can be identified as smart economy& technology companies. this new sector can be used to create economic bases for cities whose development has not specific economic bases such as the cities of zayed and el shorouk and demonstrates programs and projects of the smart economy that can be applied in the other cities according to their economic bases. setting an executive framework for applying smart economy programs & projects within new cities developing plans through the participation of individuals and the private sector. providing urban and technological entities to support the transition towards smart which integrates with the economic base of the city. the research proposes an adaptation methodical plan for developing the smart economy concept in new egyptian cities illustrated in the following fig. 3. a methodical plan towards smart economy in new egyptian cities eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e1 reham m. hafez 10 cities classification national variables international variables c on st an ts v ar ia bl es po lic y ict transaction local producing technology companies local smart economy plans smart economy local units with support from technology local universities n at io na l l ev el l oc al l ev el economic variables economic base demographic variables urban variables economic assets density location work power education skills economic power land uses the frame work understand the needs of the city the assessment assess the issue to be addressed the tools present the solution and support implementation of social fig. 3. proposed a methodical plan for developing the smart economy concept in new egyptian cities references [1] bharat dahiya, t.m.vinod kumar, (2017), smart economy in smart cities, international collaborative research, chapter 1, springer, research gate, january). [2] un-habitat, (2010), the state of asian cities, unhabitat, fukuoka [3] dahiya, b (2012) cities in asia, 2012: demographics, economics, poverty, environment and governance cities, vol. 29, supplement no. 2, pp. s44–s61 [4] bis (2013), smart cities background paper, london: department for business innovation and skills [5] bsi (2014), smart cities framework – guide to establishing strategies for [6] bakici, t, almirall, e and wareham, j (2013), a smart city initiative: the case of barcelona, journal of knowledge economy 4(2): 135–148. http://dx.doi.org/10.1007/s13132-0120084-9 [7] schaffers h, komninos n, pallot m, trousse b, nilsson m, and oliveira a (2011), smart cities and the future internet: towards cooperation frameworks [8]torres, l, pina, v, and royo, s (2005), e-government and the transformation of public administrations in eu countries: beyond npm or just a second wave of reforms? online information review, 29(5), pp. 531-553 http://dx.doi.org/10.1108/14684520510628918 [9] zygiaris, s (2013), smart city reference model: assisting planners to conceptualize the building of smart city innovation ecosystems, journal of the knowledge economy 4(2):217–231. http://dx.doi.org/10.1007/s13132-012-0089-4 [10] un-habitat,(2013), state of the world’s cities 2012/2013: prosperity of cities, routledge, new york, and unhabitat, nairobi [11] dahiya, b ,(2012), asian cities in the 21st century, east asia forum, available at http://www.eastasiaforum.org/2012/06/26/asian-cities-in-the21st-century/ (accessed 21 may 2015) [12]https://www.worldbank.org/en/country/egypt/overview. [13] central agency for public mobilization and statistics, publication [14] https://www.encyclopedia.com/places/africa/egyptian-politicalgeography/egypt eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e1 http://dx.doi.org/10.1007/s13132-012-0084-9 http://dx.doi.org/10.1007/s13132-012-0084-9 http://dx.doi.org/10.1108/14684520510628918 http://dx.doi.org/10.1007/s13132-012-0089-4 https://www.worldbank.org/en/country/egypt/overview a methodical plan towards smart economy in new egyptian cities 11 smart cities and communities, pas 181:2014 [15] policy review: national e-commerce strategy for egypt, (2017), united nation conference on trade and development, new york and geneva [16] the official website of the monastery of communication and information technology. http://www.mcit.gov.eg/ict_strategy [17] the official website of new urban communities authority, www.newcities.gov.eg , accessed oct 2019. eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e1 http://www.mcit.gov.eg/ict_strategy http://www.newcities.gov.eg/ http://www.newcities.gov.eg/ housing & building national research center (hbrc), egypt 3.1 the smart economy concepts, definitions. 3.2 the smart economy as the main pillar of smart city 3.3 the linkage between the smart city pillars. 3.4 urban basis entities & projects for the smart economy 3.5 examples of different economic projects in smart cities around the world 4.1 egypt sustainable development strategy egypt has economic growth, averaging 3%–5% from 2016 to 2019 [12]. egypt has adopted an investment policy as the main key to economic growth. the investment policy depends on reducing obstacles to how international companies invest and run in egypt, ... 4.2 national egyptian initiatives towards the smart economy 4.3 new egyptian cities as a key for economic development using the thinglink computer tool to create a meaningful environmental learning scenario 1 using the thinglink computer tool to create a meaningful environmental learning scenario j.a.f.a. batista1, m.m.p. souza1, t.d. barros1, nishu gupta2,* and m.j.c.s. reis3 1university of trás-os-montes e alto douro, vila real, portugal 2srm institute of science and technology, kattankulathur, chennai, india 3university of trás-os-montes e alto douro/ieeta, vila real, portugal abstract the primary objective of a smart city is to optimize city functions and promote economic growth, while also improving the quality of life for citizens by using smart technologies and data analysis. within this context, this article presents a learning scenario which is built with the “thinglink” computer tool. this learning scenario was applied in an educational context of teaching spanish as a foreign language. active methodologies have been used so that students, at their own pace, with the help of the teacher, could not just develop subject-specific skills, but also transversal skills, in a perspective of education for an informed citizenship, interventional and responsible. a significant global improvement of 14.39 % in students’ performance was verified, the number of grades below 50% was greater in the test applied before the completion of the learning activities, and the number of maximum grades was lower in the test applied before the completion of the learning activities. keywords: smart cities, smart environment, learning contexts, thinglink, computer tools, spanish as a foreign language. received on 18 january 2022, accepted on 17 february 2022, published on 21 february 2022 copyright © 2022 j.a.f.a. batista et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.21-2-2022.173457 *corresponding author. email: nishugupta@ieee.org 1. introduction it is well known that the ultimate goal of a smart city is to optimize city functions and promote economic growth, while also improving the quality of life for citizens by using smart technologies and data analysis [1–3]. emphasis should be placed on how the technology is used rather than on how much technology is available. additionally, the smartness of a city is measured through a set of characteristics, which includes environmental initiatives. on the other hand, environmental education should allow individuals to explore environmental issues, participate in problem solving, and take action to improve the environment. as a consequence of this education, people should develop a deeper understanding of environmental issues and have the skills to make informed and responsible decisions. in the current school, according to the humanist paradigm of post-modernity, the student, “digital native” [4], must be the dynamic agent in the teaching/learning process, being the builder of his/her own knowledge, by being involved in knowing how to do in action, learning to know, researching, doing, solving problems, exercising critical and creative thinking, living together, being, questioning, evolving, and being able to develop various skills. that is, it is up to the school to guide its action, meeting the four pillars of education defended by delors [5], namely: “learning to know”, “learning to do”, “learning to live together” and “learning to be”. at least in portugal, these assumptions are well expressed in opinion no. 4/2017 [6], of 30th may, of the portuguese national council of education: “the skills and knowledge considered fundamental for the 21st century in oecd member countries, according to the work ‘21st century skills and competences for new millennium learners in oecd countries’, are varied and include, among others, creativity/innovation, critical thinking, problem solving, decision making, communication, collaboration, literacy in the use and access to information, investigation and research, media literacy, eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e3 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ j.a.f.a. batista et al. 2 digital citizenship, information and communication technologies (ict) operations and concepts, flexibility and adaptability, initiative and self-orientation, productivity, and leadership and responsibility” (p. 10744). today, schools are facing several challenges. in fact, in two centuries, schools have changed little, despite the fact that students, society and the labour market have undergone changes, as it continues, in most cases, very much rooted to the industrial paradigm where the teacher, in the traditional classroom, tries to teach the same to all students, as if it were a “factory”, as they follow “the school day and week according to the logic of the assembly chain, passing from hand to hand of teaching until supposedly the finished product came out” [7, p. 73]. however, schools cannot continue to try to train 21st century students with teachers who use 19th century methodologies, much less be seen as “factories for reproducing social inequalities” [8, p. 6], but rather as “shipyards of humanity” (idem), since students have changed, as has society and the labor market, with only a few school institutions missing to monitor and correspond to these changes. this idea is corroborated by formosinho, machado and mesquita [9], who argue that, “in the 21st century, the portuguese educational system maintains the school format it inherited from the 19th century and it is difficult for it to disassociate from it at the level of school organization and the curriculum (...)” (p. 62). given the information and knowledge society and rapid technological advances, it is a conditio sine qua non that the teacher follows the change, investing in a new educational paradigm, based on humanist and constructivist theories, in which students, through active methodologies and resorting to the effective and contextualized integration of technologies, they are guided to autonomously and critically build their own knowledge, ceasing to be simply consumers of information, as was the case in the industrial age model. in this perspective, the teacher, as a critical and creative agent of change, must invest in training and professional development, given that the teaching profession is always in constant updating of knowledge and skills so that he/she can correspond to the various challenges of the 21st century school. in the pedagogical experience presented here, we chose to create a learning scenario, using the “thinglink” computer application, in which students are invited to perform seven challenges, using the learningapps, google forms, quizizz, kahoot!, canva and lino tools, with the aim of promoting awareness for the defense of the environment, broadening the lexicon on the subject of the environment, knowledge of the main natural disasters and the development of multi-literacy skills. it was developed aimed at the following objectives: to raise awareness of the protection and preservation of the environment; to promote values and attitudes within the scope of environmental education; to expand vocabulary related to the environmental theme; to know the main environmental problems; to know the main natural disasters; to understand an audiovisual message; to develop the ability to research, select and process information, written expression, autonomy, critical thinking, creativity, collaborative work and digital competence. according to the achieved results, we found that the use of technologies in the classroom can make a difference, contributing to learning to become more motivating and fruitful, increasing the level of motivation and interest in the foreign language (spanish), as well as to an improvement in educational success. the remaining of this paper is organized as follows. section 2 is dedicated to present the importance of the use of digital tools in the learning process. the “thinglink” as a teaching and learning tool is presented in section 3. section 4 is used to present the pedagogical experience and the results achieved. the paper concludes with the presentation of the main conclusions in section 5. 2. the importance of digital tools in learning in portugal, since the 80s of the 20th centuries, there have been several political intervention initiatives for digital training, both at the level of teachers and schools, in order to develop a school with digital resources and teachers trained for teaching, using ict. along this path, several initiatives stand out, such as the minerva project, nónio século xxi, ciência viva program, internet at schools program, european school net, seguranet, edutic, crie mission team, educational resources and technologies team (rte), the technological plan for education (pte) and, more recently, the action plan for the digital transition. these initiatives have been contributing to a growing appreciation of digital skills in the school context, to a digital equipping of schools and to raising teachers' awareness of the use of digital technologies in the classroom. despite all the efforts and investments mentioned above, it was found, with the pandemic resulting from covid19, that the use of digital platforms and tools reached a significant peak during distance learning. in this sense, the school, known as it used to be, had to adapt, forcibly, to new times. educational technologies have always been arousing great interest in terms of their potential for motivating, engaging students and improving learning. in this perspective, we intend to show the possibilities and positive contributions that digital tools make possible in the teaching/learning process, namely in terms of the assistance they can give to the strategies and methodologies used, in order to assess their relevance and impact. a great number of studies indicate that the use of technological tools, in an educational context, is an asset eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e3 using the thinglink computer tool to create a meaningful environmental learning scenario 3 for teachers and students who use them, in contrast to those who still resist them. freeman et al. [10] sate that “although theories of learning that emphasize the need for students to construct their own understanding have challenged the theoretical underpinnings of the traditional, instructor-focused, “teaching by telling” approach, to date there has been no quantitative analysis of how constructivist versus exposition-centred methods impact student performance (…)” (p. 1). according to freire [11], one should not be a naive appreciator of technology. although we, a priori, know that technology brings a huge potential of stimuli and challenges to the curiosity of children and adolescents, there is an imperative and vast path that must be taken to transform it into a tool for social inclusion, as also reflected in the portuguese decree-law no. 54/2018, of 6th july, and the development of citizenship in a wellstructured and defined political-pedagogical project. it is also worth highlighting some recent portuguese legislation on the importance of using technologies, in order to shorten distances in terms of learning, motivation and the acquisition of skills required of the 21st century student, namely: dispatch no. 6478/2017, of 26th july [12], on the profile of students leaving mandatory schooling (paseo), which contains skills required of students directly related to the importance of knowing how to use digital resources proficiently, in almost all domains. in this sense, digital resources have their space and role very well defined with regard to the aid tool for the construction of knowledge; decree-law no. 54/2018, of 6th july [13], referring to inclusive education, in which digital technological resources are presented as tools to shorten distances, facilitators and promoters of inclusion; decree-law no. 55/2018, of 6th july [14], on curricular autonomy and flexibility, which establishes the curriculum for basic and secondary education, the guiding principles for its conception, operation and assessment of learning, in order to ensure that all students acquire knowledge and develop skills and attitudes that contribute to achieving the competences provided for in paseo. in fact, the available digital technologies allow us to capture, store, organize, search, retrieve and transmit the relevant information with extreme efficiency. it should be noted that any place can contribute as an educational space, both for its characteristics of individual formation and a place of connection with the school world. kenski [15] advocates that ict provide a new type of interaction between the teacher and the students, enabling the creation of new ways of integrating the teacher with the school organization and with other teachers. the use of different tools thus becomes an ally of the teaching/learning process. as stated by giordan [16] we must take advantage of this opportunity to access different sources of information and knowledge brought by communication mediated by computer networks. the incorporation of ict in education has consequences, not only for teaching practice, but also for the learning processes. however, the simple incorporation or use of ict by itself does not necessarily generate processes of innovation and improvement in teaching and learning. in fact, there are certain specific uses of ict that seem to have the ability to trigger these processes. in the teaching/learning process, by using new technologies, the teacher, as a mediator or advisor, begins to consider the profile of the students, their prior knowledge, learning preferences, cognitive styles, contents and teaching/learning methods. the internet is not just a communication and information search tool, as it constitutes a space for learning and collaboration for the construction of knowledge. in this follow-up of ideas, and according to [17], technology applied to education can bring numerous advantages to the student, as long as it is well integrated and contextualized in the curriculum. for this to happen, the teacher has the important role of exploring the learning possibilities that digital tools bring to the student, using them in a collaborative and interactive way, and as tools in the construction of knowledge. basically, icts are characterized by a set of technological resources that, integrated with each other, make it possible to share, through multidimensional communication, all the knowledge produced. the incorporation of ict in schools, as long as the teacher has adequate training, can bring benefits to the student and should induce research and reflection on practice, as well as pedagogical innovation. in terms of the use of technologies in education, several authors point out that the integration of ict in teaching should be understood as a dynamic process and continuous reflection in which both technologies and pedagogical practices can be analysed and transformed, accordingly with the contexts and individuals involved [18]. in this assumption, digital tools can be used as important tools or technological resources that, integrated with each other, facilitate the teaching/learning process, arouse the interest of the student, enabling the contextualization of the topic dealt with, the manipulation of parameters and observation of the results, in addition to allowing interactivity and interdisciplinary. in summary, digital tools, by a short definition, are “any type of software or hardware that can be used for education” [19, 20]. moreover, authors in [21] state that sustainable development of technologies give life for idea of smart cities which consist of all the visions towards modern world. with regard to learning support platforms, these have proven to be an asset, as they facilitate the availability of resources in different formats, such as text, video, audio, links to websites, information for students, teacherstudent interaction through communication and research tools, tools to support collaborative learning, recording of activities carried out by students, learning paths that combine various digital tools created by teachers and/or students, among others. through the digital resources available on these platforms, the student finds him/herself in a central place in relation to learning, because he/she eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e3 j.a.f.a. batista et al. 4 decides when and where to access work, which resources to use and with whom he/she wants to work. these digital platforms, combined with the web of digital hyperlinks to a multitude of tools and technological resources, started to be used in a hybrid teaching regime, in support of nonface-to-face sessions, and also in support of the in-person regime, at all levels of teaching and subject areas. the “thinglink” computer tool is an excellent example of such platforms. concerning the portuguese case, the first steps towards the use of the computer and the internet as resources for teaching and learning were done in the late 90’s of the xx century. for example, in [22] and [23] the authors present their experience “in furthering the educative use of information technology and the internet in the primary schools of northeast portugal”. this was the first experience of its kind in portugal, involving 1,137 schools, more than 1,700 teachers, and roughly 13,000 students. they concluded that “the transfer of the training process from the university campus to the schools and communities themselves allowed for a very high degree of teacher participation” and that “the efforts to put theory into practice in the classrooms were rewarded by a quicker rate of acceptance of it in the classroom”. after these first steps much work is being done and experiments were conducted reaching from studies involving both students from the regular curriculum (“normal” students) [24] and students with disabilities [25]. researchers in [26] present the foundation of a framework for interactive adaptive learning systems that gives extensive attention at each stage of the design process to the end-user: learners. 3. thinglink as a teaching-learning tool to access the “thinglink” tool it is necessary to register or login with a google, microsoft, or social media account, such as facebook or twitter. this tool is available in an educational version for students and teachers, being only free in edu basic mode, as edu premium is paid. it is a tool with a very intuitive interface that allow us to assign labels (tags) of interactivity, in a 2d or 360º image, or even in a video, allowing the integration of other images and videos, titles, text, audio, quizzes, questionnaires and links to diversified content. the user can also choose the icon and its color, as well as the place where it will be placed, in the image or video selected as “background”. it is a tool with a lot of educational potential to address and consolidate varied themes and content, access content and activities anytime and anywhere (provided there is an internet connection), promote a more stimulating, active and interactive learning that “not only helps to focus students' attention but also helps them to learn” [27, p. 10]. it also allows an individual or group learning path, according to the pace of each student, and the development of various skills, which can be used in any subject or interdisciplinary project to create a learning scenario or a guided virtual visit, under a face-to-face, distance or hybrid learning. the sharing of the built product is done through a link, incorporation on websites, email or social networks. “thinglink” is available for ios and android, but it is also capable of producing content automatically available for web applications. 4. presentation of the pedagogical experience and the results obtained as stated in the introduction section, the learning scenario was created within the thematic unit on environment, in the spanish as a foreign language course, aimed at the following objectives: to raise awareness of the protection and preservation of the environment; to promote values and attitudes within the scope of environmental education; to expand vocabulary related to the environmental theme; to know the main environmental problems; to know the main natural disasters; to understand an audiovisual message; to develop the ability to research, select and process information, written expression, autonomy, critical thinking, creativity, collaborative work and digital competence. figure 1 shows a general overview of the learning scenario [28]. the target audience was 21 students, with an average age of 14 years old, from a 9th grade class at a secondary school in the district of vila real, portugal. these 21 students were all from the same class, and all the students of the class were included in this experience. in fact, we have access to only one 9th grade class, and because the number of students participating in this study is relatively small, we have conducted a case study. in the construction of the learning scenario, in addition to “thinglink”, the tools learningapps, google forms, quizizz, kahoot!, canva, lino and mentimeter were used, having chosen, as support, a 360º image of a representative landscape of the douro demarcated region. figure 1. general overview of the learning scenario. the learning scenario was created using a 360º photograph. eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e3 using the thinglink computer tool to create a meaningful environmental learning scenario 5 the students, the main actors in the entire teaching/learning process, were invited to embark on a stunning journey from the bank of the douro river to the top of the mountain, using their smartphones. along the way, they carried out, working in pairs, seven challenges, namely: • challenge 1 – audiovisual comprehension of the video “la hora del planeta 2021: pongamos a la tierra en el centro de todo” (earth hour 2021: let's put the earth at the center of everything) of the non-governmental organization world wildlife fund (wwf), through a questionnaire made on google forms; • challenge 2 – solving questions about environmental problems, with the learningapps application; • challenge 3 – association of the name of the natural disasters with the respective image, using the learningapps application; • challenge 4 – solving of a questionnaire, using google forms, to expand the lexicon on the theme of the environment; • challenge 5 – participation in the game created with the quizizz tool; • challenge 6 – participation in the game created with the kahoot! tool; • challenge 7 – research, selection and processing of information for the creation of a poster with the canva tool, containing examples of beneficial and harmful behaviors for the environment, and subsequent publication on the lino digital wall. a test was applied, before and after the conclusion of the seven challenges/learning activities, whose global results are shown in figures 2 and 3. according to these plots, we can see that there is a significant improvement in students’ performance, which goes from 66.71% to 81.1%, that is, there is an increase of 14.39%. figure 2. distribution of the total scores of the test applied before the learning activities. figure 3. distribution of the total scores of the test applied after the learning activities. regarding the lowest classification in the test applied before the learning activities, it is verified that it is 22% while in the test applied after the completion of the learning activities it is 49%. the number of grades below 50% in the test applied before the completion of the learning activities is six and, in the test, applied after the completion of the learning activities it is only one. as for the maximum grade (100%), in the test applied before the completion of the learning activities, only one student managed to obtain the maximum value, and in the test applied after the completion of the learning activities, there were five students. table 1 shows the performance of the class in each question of the tests, both before and after the completion of the seven learning challenges/activities. table 1. global results of the tests, both before and after the completion of the seven learning challenges/activities. question before after 1 4 out of 10 items with a correct response rate of less than 50% 2 out of 10 items with a correct response rate of less than 50% 2 16 correct answers 19 correct answers 3. a 61.9% 75.0% 3. b 76.2% 81.0% 3. c 90.5% 90.5% 3. d 90,5% 95.2% 3. e 61.9% 66.7% 3. f 57.1% 75.0% eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e3 j.a.f.a. batista et al. 6 4 18 correct answers 20 correct answers 5 15 correct answers 16 correct answers 6 12 correct answers 18 correct answers given the obtained results in each question of the tests (before and after the completion of the entire set of activities), we can conclude that there was a positive evolution in the students’ learning. at the end of the learning scenario, the students also filled out a self-assessment questionnaire, created in google forms, in which 57.1% of the students rated the importance of the topic and the content covered as “interesting”, and 42.9% rated it as “very interesting”. no student reported “not interesting” or “not at all interesting”. regarding the degree of satisfaction with the activities performed, 52.4% revealed being satisfied, and 47.6% very satisfied. nobody mentioned that they were little or not satisfied. concerning overall performance of students in carrying out the activities, it was considered good. as for the assessment of the level of performance in the competence areas of the portuguese “profile of students at compulsory schooling”, mobilized to meet the challenges, applying a five-level likert scale, it stands out level 4 in languages and texts, information and communication, critical and creative thinking, and interpersonal relationships. level 3 was assigned only in scientific and technological knowledge, which reinforces the idea that students, despite being born in a digital context, have a superficial knowledge of technologies, when used for learning and knowledge construction. level 4 is also highlighted in terms of motivation to carry out the challenges, participation, commitment and duration of the learning scenario. according to the opinion expressed by the students, interactive games made with kahoot! and quizizz, as well as the questionnaire done on google forms, were the most appreciated challenges. the construction of a digital poster with the canva tool was the one that aroused the least interest, since it implied more complex multi-literacy skills required of the 21st century citizen. in other words, these data support the thesis that it is urgent to teach students to make the most of digital applications, enabling them in the new digital literacies. also, according to the five-level likert scale, 19% of students globally attributed level 3 to the learning scenario, 57.1% to level 4 and 23.8% to level 5. finally, using the mentimeter tool, it was found that most students have the opinion that they performed the activities very easily, as can be seen in figure 4. as an example, we present some very positive testimonies from students about the pedagogical experience developed: “the kahoot! and quizizz tools helped in learning.” (a2); “the learning scenario was very creative and a good way to learn and learn more about the environment.” (a3); “the classes are being fun.” (a5); “i, in general, enjoyed all the challenges.” (a7); “i found the learning scenario very interesting and interactive.” (a8); “i liked the activity; it was productive and very interesting.” (a16); “i think that, with this activity, we learned a lot about the environment and natural disasters.” (a18); “i really liked it, because it’s a very important topic, which we can’t forget about.” (a19). figure 4. students' opinion on the developed activities (in spanish, the language used to develop the learning scenario). 5. conclusions improving the quality of life for citizens by using smart technologies and data analysis is the ultimate goal of a smart city. the smartness of a city is measured through a set of characteristics, which includes environmental initiatives. people’s education should develop a deeper understanding of environmental issues and have the skills to make informed and responsible decisions. currently, students live immersed in technologies, which are a natural part of their modus vivendi, of which the mobile phone stands out, as they live connected 24 hours a day and can no longer imagine their life without this equipment. in this sense, this mobile device, rather than continuing to be banned in many educational establishments, should be integrated into everyday classroom practices as a powerful tool for learning and building knowledge, whether in spanish as a foreign language classes or in classes from other subjects, in order to break with teaching that is still too “transmissive” and include emerging strategies, such as task-based learning, collaborative learning, game-based learning, and “gamification” of which the learning scenario presented here is an example. in fact, implementing the bring your own device (byod) concept, making the students’ mobile devices pedagogically profitable, is a way of giving them a more active role in the teaching/learning process and making them content producers. in view of the results obtained and the observations made, we believe that technologies, combined with pedagogy, eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e3 using the thinglink computer tool to create a meaningful environmental learning scenario 7 enhance more stimulating, enriching and lasting learning, thus contributing to increasing motivation for a foreign language, improving the quality of the learning experience and, concomitantly, the increase in educational success. as we have seen above, there was a significant improvement in students’ performance, which had grown from 66.71% to 81.1%, corresponding to an improvement of 14.39 %. we have also observed an improvement regarding the lowest classification achieved by the students, which was 22% in the test applied before the learning activities, and 49% in the test applied after the completion of the learning activities. the number of grades below 50% in the test applied before the completion of the learning activities was 6 and, in the test, applied after the completion of the learning activities was only 1. as for the maximum grade (100%), in the test applied before the completion of the learning activities, only 1 student managed to obtain the maximum value, and in the test applied after the completion of the learning activities, there were 5 students. it is therefore urgent to invest in the promotion of active learning activities in order not only to correspond to the challenges of the new educational paradigm, but also to the interests, expectations and needs of each and every student, in a school that it is intended to be inclusive, open to creativity, experimentation and innovation, a motor for the development of skills registered in the profile of students on leaving mandatory schooling and a lever for everyone’s success. references [1] zanella, a., bui, n., castellani, a., vangelista, l., zorzi, m. internet of things for smart cities. ieee internet of things. 2014; 1(1): 22–32. 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[8] azevedo, j. ciclo de seminários de aprofundamento em administração e organização escolar: sucesso escolar, indisciplina, motivação, direção de escolas e políticas educativas. porto: faculdade de educação e psicologia da universidade católica portuguesa. 2012; como se tece o (in)sucesso escolar: o papel crucial dos professores. pp.1– 12. https://repositorio.ucp.pt/handle/10400.14/22381, last accessed 2021/06/05 (in portuguese). [9] formosinho, j., machado, j., mesquita, e. formação, trabalho e aprendizagem – tradição e inovação nas práticas docentes. lisboa: edições sílabo. 2015. (in portuguese). [10] freeman, s., eddy, s. l., mcdonough, m., smith, m. k., okoroafor, n., jordt, h., wenderoth, m. p. active learning increases student performance in science, engineering, and mathematics. proceedings of the national academy of sciences of the united states of america, 111(23), 2014. 8410–8415. [11] freire, p. pedagogy of freedom. rowman & littlefield 2000. 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[17] chen, c., kang, j. m., sonnert, g., sadler, p. m. high school calculus and computer science course taking as predictors of success in introductory college computer science. acm transactions on computing education. 2021; 21(1). [18] calenda, m., iannotta, i. s., tammaro, r. evaluation rubric for digital competence assessment: an exploratory study. in: chova, lg and martinez, al and torres, ic. proceedings of the inted 2016: 10th international technology, education and development conference, 2016. 2469–2479. [19] mahiri, j. digital tools in urban schools: mediating a remix of learning. ann arbor: university of michigan press. 2011. [20] gottapu, s. k., kapileswar, n., santhi, p. v., chenchela, v. k. maximizing cognitive radio networks throughput using limited historical behavior of primary users. ieee access. 2018; 6, 12252-12259. [21] balog, m., iakovets, a., hrehova, s. road traffic rfid pedestrians detecting system for vehicles. eai endorsed transactions on smart cities. 2019; sc20(9): e2. [22] reis, m. j. c. s., santos, g. m. m. c., ferreira, p. j. s. g. promoting the educative use of the internet in the portuguese primary schools: a case study. aslib proceedings. 2008; 60(2), pp. 111-129. doi 10.1108/00012530810862455. [23] reis, m.; santos, g.; teixeira, c.; vieira, n.; carvalho, s. internet as a learning tool in the ‘trás-os-montes e alto douro’ region. proceedings of the international conference on ict’s in education, junta de extremadura, consejería de educación, ciencia y tecnología, sociedad de la información; november, 2002; badajoz, spain. pp. 1494-1498. eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e3 https://dre.pt/home/-/dre/107099845/details/maximized https://dre.pt/home/-/dre/107099845/details/maximized http://dx.doi.org/10.7213/rde.v4i10.6419 j.a.f.a. batista et al. 8 [24] santos, g. m. m. c., ramos, e. m. c. p. s. l., escola, j; reis, m. j. c. s. ict literacy and school performance. turkish online journal of educational technology. 2019; 18(2), pp. 19-39. [25] reis, m. g. a. d., peres, e., bessa, m., valente, a., morais, r., soares, s., baptista, j., aires, a. p., escola, j. j., bulas-cruz, j. a., reis, m. j. c. s. using information technology based exercises in primary mathematics teaching of children with cerebral palsy and mental retardation: a case study. turkish online journal of educational technology. 2010; 9(3), pp. 106-118. [26] battou, a., baz, o., mammass, d. an interactive adaptive learning system based on agile learner-centered design. eai endorsed transactions on smart cities. 2018; sc18(7): e5. [27] carvalho, a. a. a. aplicações para dispositivos móveis e estratégias inovadoras na educação. lisboa: me/ dge. https://erte.dge.mec.pt/sites/default/files/noticias/app_para _dispositivos_moveis.pdf, last accessed 2021/5/5 (in portuguese). [28] https://www.thinglink.com/video/1441894405970591745, last accessed 2022/02/10. eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e3 https://www.thinglink.com/video/1441894405970591745 energy efficient technique for cluster-head selection in iot network 1 energy efficient technique for cluster-head selection in iot network vishwas d b1,*, gowtham m1 and gururaj h l2 1assistant professor, department of computer science and engineering, nie institute of technology, mysuru, india 2associate professor, department of computer science and engineering, vidya vardhaka college of engineering, mysuru, india abstract introduction: wireless sensor systems (wsn) clusters specific transducers that give detecting services to internet of things (iot) devices with limited energy and capacity assets. clustering calculation assumes a significant job in control preservation for the energy compelled organizes. objectives: picking a cluster head can suitably adjust the load in the network in this way increasing strength utilization and improving lifetime. since substitution or energizing of batteries nodes is very difficult, control utilization becomes one of the critical plan issues in wsn. methods: the paper focus around an effective cluster head selection decision that rotates the cluster head position among the nodes with higher energy level when compared with other. the calculation thinks about beginning strength, unwanted energy and an ideal estimation of cluster heads to choose the following gathering of cluster sets out toward the system that suits for iot applications, for example, ecological examination, smart city communities. results: reproduction examination shows the better altered version algorithm to anything the leach. conclusion: v-leach clustering algorithm improves network lifetime, packet throughput and average residual energy compare to leach. keywords: wsn, iot, ch selection, lifetime, energy efficient, residual energy. received on 13 march 2020, accepted on 09 april 2020, published on 17 april 2020 copyright © 2020 vishwas d b et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.163992 1. introduction internet of things (iot) is an environment of interconnected devices and articles by means of the network empowering them to send and get information. it is an imperceptible yet smart place that detects, controls and can be modified [1], by utilizing installed innovation to speak with each other. the iot gives quick access to data identified with any device with high profitability and efficiency [4]. till date, around 5 billion savvy devices are now associated and by 2020 around 50 billion devices to be associated [1]. the quantity of individuals really imparting may surpass the quantity of devices /machines associated with them for all goals and purposes. this will produce immense traffic where people may turn into the minority of generators and beneficiaries of traffic [5]. this gives the explanation behind examining iot for different inquire about areas inferable from its difficulties and openings [4]. wsn goes about as a medium that supports the virtual advanced world to this present reality. small sensors or actuators associated with each other are liable for detecting and moving the qualities to the internet. wsn involves sensor head sent in a system field to screen different physical and ecological parameters. the directing way of information from the detecting node to the sink node or base station (bs) must to be structured in a energy effective way since energizing the sensor battery is for all intents and purposes incredible [2]. not quite the same as the spontaneous system, wsn implied for iot. application faces various difficulties as far as various sensor nodes, equipment, and method of correspondence, battery power and computational expense to give some examples. aside from detecting, the sensors utilized in the iot worldview are with extra functionalities and needs to confront new eai endorsed transactions on smart cities review article *corresponding author. email: vishwasdb91@gmail.com eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e2 vishwas d b, gowtham m and gururaj h l 2 difficulties as far as qos (quality of service), security and power the board [3]. a portion of these issues are tended to by embracing different mechanical changes in crude conventions what's more, plans utilized for wsn. qos requirements in iot based wsn faces huge difficulties like unexpected asset content, repetition in information, dynamic size of the system, less dependable medium, heterogeneous organize, and various bs or sink nodes. the key security issues in wsn incorporates information credibility and privacy, information uprightness and freshness in information [6]. decrease of intensity utilization has consistently been a core issue in planning wsns. ongoing research result has come up with various plans to decrease energy and broaden arrange life span for appropriate use of assets. steering calculation assumes a critical job all the while. clustering assembles a chain of importance of clusters or gatherings of detecting nodes that gathers furthermore, moves the information to its individual cluster head (ch). the ch then gatherings the information and sends the combined to sink node or base station (bs) which goes about as middleware between the end client and the system. among the clustering calculation, drain (low energy adaptive clustering hierarchy) is an old style convention that thinks about energy for various levelled steering of information. the system is gathered into groups, and the sensor node transmits its information to the relating ch [8]. the convention randomly chooses chs in a stochastic way for each round. the ch speaks with every node of the group called part nodes to gather the detected information. the ch allocates tdma (time division multiple access) calendars to its relating group part. the part node can transmit information during the dispensed availability [6]. the information is then checked for repetition and compacted previously speaking with the sink node the chs legally speak with bs in leach convention; consequently the power utilization in sending information from ch to bs will be more when contrasted with the correspondence between the chs. therefore, the chs will reduce its energy inside a brief timeframe. multi-bounce correspondence, on the other hand, can be useful to overcome this issue, yet still not compelling in instances of little organizes. choosing a ch is a complex work as different variables have to be considered for determination of best node in the group [9]. the components incorporate the separation between nodes, slow energy, portability and throughput of every node. filter calculation improves the lifetime of the system in correlation with direct or multi-bounce transmission yet at the same time has numerous disorders. the appointment of group heads is finished randomly which doesn't promise legitimate appropriation and ideal arrangement. the nodes with lesser energy have equivalent need as that of those with a higher energy level to be chosen as ch. thus, when a node of low leftover energy gets chosen to fill in as ch, it ceases to exist rapidly bringing about shorter system range [12]. here we plans to choose the ch thinking about significant parameters like the underlying energy, remaining energy of the particular node and the ideal number of chs in the arrange. the adjustment is done in the old style leach calculation. with the consummation of each round, the lingering energy of the non-ch nodes are checked, and the one with the higher energy level in distinction with others has a higher likelihood for ch determination for the current round. this would avert the system to cease to exist too soon along these lines improving the organize lifetime. 2. related work one of the significant issues of iot is to deal with an enormous number of sensors that will be conveyed, as far as the expense of adjusting and upkeep [12]. further replacing sensor batteries which are now situated in the system field can be a monotonous activity [14]. for example, in the event that a sensor is to be sent on a specific creature.it requires the battery of the sensor to outlast the creature which is unmistakably more reasonable. this prompts another significant test which is control the executives. solid start to finish information transmission with legitimate clog control and low parcel misfortune proportion are a portion of the other significant worries in wsn [15]. the essential objective of any sensor system is to course the information collected by sensors and forward it towards the bs. the least complex technique to convey information is immediate transmission where the nodes need to guide its information to the base station or sink node. be that as it may, if the separation among sink and system is enormous, the node will cease to exist rapidly because of pointless energy utilization [14]. grouping calculation diminishes the undesirable control utilization in conveying information to bs by gathering the system into clusters. each cluster is doled out a ch that sends information to bs. a significant stage in the grouping calculation is the ch election race process that should ensure uniform energy dissemination among the sensor nodes [15]. drain convention has seriously been adjusted by specialists to improve the system execution. specialized analysts are contributing overwhelmingly in improving existing calculations for better execution of the iot framework [16]. an energy effective trust inference strategy was examined in [17] for wsn-based iot systems. the plan uses chance methodology investigation to diminish organize overhead by determining an ideal number of proposals. the energy mindful plan keeps up sufficient security and furthermore decreases the inertness of the arrange. a time sensitive ch determination is proposed in [18] called tbleach that sets well-disseminated clusters and upgrades the lifetime by 20 to 30%. the separation among nodes and bs are considered for limit based ch determination in [15] that improves lifetime by 10%. the in et al. in [14] have adjusted the likelihood for the determination of ch dependent on the remaining energy of every node. the system lifetime upgrades by 40eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e2 energy efficient technique for cluster-head selection in iot network 3 half. another ch determination strategy for collection of information is talked about in [19] that disposes of excess and upgrades the organize lifetime. the edge worth is changed by considering a hotness factor that characterizes the overall hotness of a specific sensor node to that of the system. ch is chosen utilizing molecule swarm advancement (pso) in [19]. the criteria for choice have a target work in terms of node degree, intragroup separation, lingering energy, also, various ideal chs. the model performs better in terms of different system measurements in contrast with different steering conventions. pso-echs is talked about in [20], where pso based ch determination is made utilizing parameters like node to node separation, separation to bs and leftover energy. another enhancement method called grouped gary wolf search improvement is utilized in [20] for security. ch determination to improve the system lifetime. an improvement of leach was proposed in [19] where remaining energy assumes a significant job in ch election decision. a straightforward multi-jump way to deal with leach was likewise considered, and it is discovered that the two conventions perform superior to leach by broadening lifetime after a specific timeframe. a no probabilistic multi-criteria based ch determination was displayed in [19] where the system is isolated into independent zones. the ch or zone head is chosen utilizing the anp (analytical system process) choice device. a lot of parameters have been gathered from where the best parameters have been chosen for cluster head determination. the iot, being a universal system, associates shrewd devices and items to the cloud. wsn gives a stage to the gathering and correspondence of information to screen and control the physical world for the advancement of the general public [20]. imparting remote advances depletes more power when contrasted with the devices intended to get inactive. the rising number of savvy devices interfacing with the network has made energy protection a surplus parameter in iot planning. creating energy proficient procedures for arrangement of sensor systems have consistently been a testing task for analysts. at the point when fused with iot, power turns into an increasingly critical issue attributable to the quantity of devices being associated in huge scale. to keep up iot guidelines, specialists have focused on device energy monitoring strategies, for example, grouping where the decision of ch ought to be done reasonably. different strategies for proficient ch choice was examined from the above mentioned writing that upgrades the system execution. be that as it may, significant parameters like leftover energy, beginning energy and an ideal number of clusters in the system, have not been considered as far as we could possibly know for change in the limit an incentive for ch choice. 3. system model the quick increment in public thickness in urban zones requires current frameworks with reasonable administrations to meet the prerequisites of the city occupants. subsequently most recent advances in correspondence innovations, for example, iot has been in request to give a structure to the improvement of savvy urban areas [16]. this segment displays an ecological observing situation that utilizations wsn as a vital piece of iot. the nodes are gathered in four distinct rooms to shape clusters as appeared in fig.1. may there be eight sensor nodes in each room where as it were one node can turn into the ch (stamped red) for every moment of time. the sink node gathers information from the chs of each room what's more, sends the melded data to the end client. for the framework model, some sensible suppositions have been embraced as pursues: fig. 1. condition checking utilizing iot. • nodes are static and homogeneous with starting energy 0.5j also, are appropriated in rooms to screen factors, for example, stickiness, temperature, sound, and glow. • nodes are taken arbitrarily and transmit its information intermittently. • each room has a ch that speaks with the bs either in the single bounce or multi-jump correspondence. • bs/sink is fixed and introduced in the system. • the bs gets the information from each ch and spread it to the cloud. nature observing applications [17] requires the legitimate steering of information with the goal that the system energy can be utilized viably. in the event that a node with lesser remaining energy is chosen as ch in one of the room, it will prompt the finish of transmission of information from that room. accordingly, the end client won't get total data for observing of natural conditions. the correspondence model utilized in [28] appeared in fig. 2 has been considered to think about the conduct of the proposed model. eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e2 vishwas d b, gowtham m and gururaj h l 4 drain is a crude single-bounce grouping convention that spares a colossal measure of energy when contrasted with nonclustering calculations [18]. when the nodes are sent, sensors cluster together to shape groups with one ch in each group for information accumulation. the convention is executed in adjusts. groups are shaped with time and the cluster heads are chosen arbitrarily. every node in the cluster has equivalent chance to be chosen as ch which expects for balance the energy dispersal. the remaining energy is checked always by the sink until the lifetime closes, for example all beyond words their battery control. with each round, the ch changes dependent on the choosing likelihood which shows that every one of the nodes in the group have a similar opportunity to be chosen as ch regardless of its lingering energy. equal-likely ch election race procedure gives rise to the plausibility of choosing a ch with negligible leftover energy which will cease to exist rapidly when contrasted with the one with relative higher energy level. along these lines, the leftover energy of every node is incorporated into the condition of election decision likelihood of ch to such an extent that the nodes with higher energy level have a more prominent opportunity to be chosen as ch. this consequently guarantees equivalent conveyance of intensity in the system subsequently improving system lifetime. so as to battle this issue, a propelled calculation is proposed called v-leach. the calculation is partitioned into adjusts with each round comprising of cluster development and relentless state stages. fig. 3. flowchart of leach protocol. 4. proposed work the proposed convention speaks to a various leveled clustering calculation that includes two phases: set-up and relentless state stages. in the underlying set-up stage, the sensor nodes are sent in the system and are subpartitioned into clusters headed by a ch responsible for the accumulation of information from detecting nodes. the information is combined to decrease the volume by expelling any repetitive bits. genuine information directing happens during the enduring state organize, where the gathered information is sent to the bs by the chs of the system. 4.1. system arranges for the first round, the clusters and chs are shaped utilizing typical leach calculation, where chs are chosen utilizing condition (4). after information move, every node in the system exhausts some measure of energy which is distinctive for each node. the use of intensity relies upon the separation isolating the sending and getting nodes spoke to as‘ d ’ . subsequently for the following round, the ch is chosen utilizing an altered condition given as where residual is the rest of the energy level of the node and initial is the underlying allocated energy level. the ideal number of cluster kept can be composed as in [19]. 'm' speaks to the system width and e0 is the underlying energy provided to every node. when the chs for the current round are chosen, they send their ch declaration data to part nodes in the particular groups. the detecting nodes check the sign quality of the solicitation message and choose the chs it needs to join. the ch at that point communicates tdma (time division multiple access) plans for the part nodes to transmit information in diverse availabilities to stay away from information crash. the procedure at that point proceeds for the remainder of the rounds till every one of the nodes in the system exhaust all its energy. during the schedule opening relegated to every node, transmission of information to chs happens. just the transmitting node stays dynamic and every other node in the cluster will kill its radio to spare energy. after every one of the nodes in the group have wrapped up moving information, the ch will begin handling the information. the ch gets and afterward totals the information to evacuate any repetition and pack the data however much as could reasonably be expected for reasonable usage of transfer speed. the chs then advances the information to the sink or bs in either single-bounce or multi-jump correspondence. the whole procedure is portrayed in a flowchart as appeared eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e2 5 in fig. 3. 5. result the system parameters considered for ns2 recreation for the system model. the bundle size is viewed as 4000 bits. 50nodes are sent arbitrarily with bs put in the focal point of the arrange region as appeared in fig. 5. fig. 5. node deployment 5.1. system analysis the reenactment result in fig.6 shows the system life for both the leach and v-leach conventions. fig. 6. network lifetime. drain convention accept chs disseminates the same energy for each round that prompts wasteful ch determination and influences the system life expectancy. v-leach chooses chs considering the remaining energy of nodes and an ideal number of groups together accordingly upgrading the system lifetime to progressively number of rounds. the quantity of genuine information parcels sent to sink is appeared in fig.7. fig. 7. packets to bs. since the chs are chosen dependent on the remaining energy of every node, it successfully decreases the energy scattering in moving information. accordingly, information transmission recurrence increments and more parcels are effectively transmitted to the bs when contrasted with that in leach convention. the normal energy use of the system is appeared in fig. 8. fig. 8. average residual energy. the remaining energy exhausts quicker in leach than that of v-leach. since the energy for altered leach exhausts at a moderate rate, the system lifetime additionally reaches out to additional number of rounds. energy efficient technique for cluster-head selection in iot network eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e2 vishwas d b, gowtham m and gururaj h l 6 throughput speaks to the proportion between really transmitted information bundles to the effectively got information at bs or sink. the higher the proportion, the better is the presentation. fig. 9. throughput. fig. 9 show the diagram of the throughput of the two conventions clearly because of the change in the edge estimation of ch determination, the throughput is expanded by 60% for rleach. subsequently, it very well may be reasoned that the changed convention performs superior to leach convention and can be utilized widely for homogeneous systems. in leach, the ch determination is done in a randomized way prompting a limited capacity to focus the system. cbdas expends additional energy in chain arrangement and information transmission from header to rest of the nodes including extra burden to the battery life. ghnd and ighnd think about different parameters for zone head choice yet doesn't consider the number of regions or group in the system which impacts the organize lifetime. residual energy based cluster-head selection in wsns for iot application. 6. conclusion since energy and lifetime are two significant requirements in planning any directing convention for wsn, much research has been done to accomplish the objective. picking and energy proficient routing calculation that appropriates the heap in the system equally is a difficult procedure. drain convention guarantees versatile calculation yet at the same time has a few constraints. an altered ch determination calculation has been recommended in this paper intends to extend the system lifetime by controlling the energy dispersal in the system. the improved directing procedure can be utilized adequately in situations like ecological checking utilizing iot as the convention conveys a superior outcome for homogeneous arranges in contrast with leach. reproduction result shows improved system execution for measurements, for example, leftover energy, bundles sent to bs, throughput and lifetime. the present work can be reached out by thinking about additional parameters for ch choice in a system with portable nodes that changes its position much of the time. the proposed model can additionally be tried on various reasonable situations for a wsn based iot work. references [1] j. chase, “the evolution of the internet of things,” texas instruments, 2013. [2] d. bandyopadhyay and j. sen, “internet of things: applications and challenges in technology and standardization,” wirel. pers. commun., vol. 58, no. 1, pp. 49– 69, 2011. [3] l. tan and n. wang, “future internet: the internet of things,” in 2010 3rd international conference on advanced computer theory and engineering (icacte), 2010, vol. 5, pp. v5--376. [4] w. b. heinzelman, a. p. chandrakasan, and h. balakrishnan, “an application-specific protocol architecture for wireless microsensor networks,” ieee trans. wirel. commun., vol. 1, no. 4, pp. 660– 670, 2002. [5] j. gubbi, r. buyya, s. marusic, and m. palaniswami, “internet of things (iot): a vision, architectural elements, and future directions,” futur. gener. comput. syst., vol. 29, no. 7, pp. 1645–1660, 2013. [6] b. bhuyan, h. k. d. sarma, n. sarma, a. kar, and r. mall, “quality of service (qos) provisions in wireless sensor networks and related challenges,” wirel. sens. netw., vol. 2, no. 11, p. 861, 2010. 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[12] y.-k. chen, “challenges and opportunities of the internet of things,” in 17th asia and south pacific design automation conference, [13] a. ali, y. ming, t. si, s. iram, and s. chakraborty, “enhancement of rwsn lifetime via firework clustering algorithm validated by ann,” information, vol. 9, no. 3, p. 60, 2018. [14] c. wang, k. sohraby, b. li, m. daneshmand, and y. hu, “a survey of transport protocols for wireless sensor networks,” ieee netw., vol. 20, no. 3, pp. 34–40, 2006. [15] al-fuqaha, a., guizani, m., mohammadi, m., aledhari, m. and ayyash, m. , “internet of things: a survey on enabling technologies, protocols, and applications,” ieee communications surveys & tutorials, vol. 17 no. 4, 2015, pp. 2347-2376. [16] p. krishna, n. h. vaidya, m. chatterjee, and d. k. pradhan , “a cluster based approach for routing in dynamic networks,” sigcomm comput. commun. rev., vol. 27, no. 2, 1997, pp. 4964. sahil sholla et al.: clustering internet of things: areview 31. [17] y. p. chen and a. l. liestman, “a zonal algorithm for clustering ad hoc networks.,” [online]. available: citeseer.ist.psu.edu/chen03zonal.html. [19] [20] yogeesh seralathan, tae (tom) oh , suyash jadhav, jonathan myers, jaehoon (paul) jeong+, young ho kim, and jeong neyo kim, “iot security vulnerability: a case study of a web camera”, international conference on advanced communications technology(icact), ieee, vol. 13, issue 9, pp. 16-30, 2018. chalee vorakulpipat, ekkachan rattanalerdnusorn, phithak thaenkaew, hoang dang hai, “recent challenges, trends, and concerns related to iot security: an evolutionary study”, international conference on advanced communications technology(icact), vol. 7, issue 4, pp. 1433, 2018. [21] jesus pacheco, daniela ibarra, ashamsa vijay, salim hariri, “iot security framework for smart water system”, 2017 ieee/acs 14th international conference on computer systems and applications, ieee, vol. 9, issue 3, pp. 11-30, 2017. [22] se-ra oh, young-gab kim, “development of iot security component for interoperability”, ieee, vol. 12, issue 4, pp. 67-89, 2017. [11] u. m. mbanaso, g. a. chukwudebe, “requirement analysis of iot security in distributed systems”, 2017 ieee 3rd international conference on electrotechnology for national development (nigercon), ieee, vol. 5, issue 7, pp. 20-30, 2017. energy efficient technique for cluster-head selection in iot network eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e2 fig. 3. flowchart of leach protocol. fig. 6. network lifetime. fig. 7. packets to bs. fig. 8. average residual energy. fig. 9. throughput. wheelchair control and home automation using hand gestures 1 with the advancement of technology in recent times, mobility is one field which is not left behind. the difficulty and dependency for mobility is the major drawback of mechanical wheelchair. but in recent decades, there are many technologies which have been implemented to overcome different disabilities of people. the proposed system uses air gesture to control both home automation and wheelchair movement. arduino uno controls the movement of the wheelchair and to control specific electrical appliances at home. the video of hand gesture by user will be processed to obtain the input for arduino board. the proposed system is aimed at providing ease of use for disabled with minimal hand movement. wheelchair control and home automation using hand gestures nithya bg1, sanjay s1, thanush r1,*, thejas bk1, venugeetha y1 1department of computer science, global academy of technology, bengaluru, india abstract keywords: video processing, home automation, gesture navigation, smart wheelchair received on 06 march 2020, accepted on 15 may 2020, published on 21 may 2020 copyright © 2020 nithya bg et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.164663 *corresponding author. email: thanushr405@gmail.com 1. introduction over 65 million people out of the global population suffer from disability in mobility. the invention of wheelchair was a major milestone in this field. a wheelchair can be used for providing movability to physically disabled people. for the disabled, the road to locomotion was majorly built by the invention of a mechanical wheelchair. previously there was no option other than manual wheelchair which involved much physical effort and the dependency constraints made it not feasible to everyone. with the advancement of technology in recent times, mobility is one field which is not left behind. human computer interface (hci), as a great assistive technology, helps people with motor disabilities to ease their day-to-day activities. there are many interfaces that help in the movement of the wheelchair but are not ideal for independent mobility. there is scope for an interface with minimal time delay and user-friendly features for navigation and portability of the wheelchair for physically disabled. accessing home appliances without dependency is just as necessary as self-reliant mobility for basic independent life style. home automation is the process of automating and controlling all the home appliances like fans, lights, tvs among others, using a single interface. bluetooth and wi-fi technology are predominantly used in home automation. an interface that provides easy-to-use features for home automation with mobility using wheelchair is essential for physically disabled people in order to be self-sustained. this paper provides a brief study on various interfaces used for gesture recognition, home automation and wheelchair navigation. gesture recognition techniques include video processing, image processing and sensors. this study provides an overview of methods that can be used to provide an optimized interface that facilitates physically disabled people. 2. problem definition independent mobility is crucial for development of physical, cognitive, communicative and social skill for physically impaired people. in addition, the high price of the electric wheelchair makes it infeasible for most of the people. the problem of the wheelchair is the type of aid needed by a disabled person to move about is dependent, to a large extent, on the level of his incapacity. people in wheelchairs eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e3 http://creativecommons.org/licenses/by/3.0/ mailto:10.4108/thanushr405@gmail.com 2 nithya bg et al. encounter accessibility issues with doors every day. it is difficult to get a door to open. in addition, the high price of the electric wheelchair makes it infeasible for most of the people. thus, we chose to investigate whether we could develop a wheelchair that is cost effective and user friendly. 3. review in nobuyuki otsu [9], the paper demonstrates how the image is segmented using automatic thresholding. here a selection of optimal threshold increases the separability in levels of gray in the obtained result. this method from the discriminant examination, provides practicability for evaluating the edge associated mechanically choosing a best threshold. at the start, only the 0th and 1st order accruing moments of the gray level histogram are preserved. an ideal threshold is selected automatically, based on the integration and not on differentiation. in julian balcerek et. al. [7], a video processing approach is used to help pedestrians in vehicle detection. the system proposed detects the vehicle by a video camera placed on the back of the pedestrian and then notifies them by sending a signal. video sequences are analyzed using histograms. the efficiency of this system is very high else the delay would not help the pedestrian in moving quickly. the system mainly uses the video processing technique and machine learning. in jochen triesch et.al.[6], a vision system was developed which is used for recognition of hand posture. the model is based on elastic graph matching (egm). computer science has many techniques to recognize patterns. one of which is elastic matching (em). em is also recognized as nonlinear template matching, deformable template, or flexible matching. em is explained as an idealization problem of 2d distorting identifying respective pixels between targeted images. main concepts covered are image processing and video processing. in b.g.lee et. al.[2], a glove kind of device is used to detect and interpret sign language. the device consists of 5 flex sensors, 2 pressure sensors and a 3-axis inertial motion sensor to differentiate the features in the asl alphabet. these sign languages are converted into text and sent to the receiver. a mobile application which can run on android was built with a text-tospeech feature that interprets the received text into voice output. research outcomes indicate that classification of correct sign language is 65.7% accurate in the 1st version with no pressure sensors. a 2nd version of the approached glove kind of system with the mixture of pressure sensors on the center finger maximizes the classification accuracy rate drastically to 98.2%. the implementation mainly relies on gesture recognition, ml and android application. in francesco camastra et. al.[5], the system provides a hand identification using learning vector quantization (lvq). lvq consists of 2 modules. the 1st module is used for feature extraction from a data glove. the 2nd module is the identifier implemented by lvq. this test is performed on collection of 3900 hand gestures performed by diverse human beings. gesture recognition and ml are the domains which are under focus. in arathi p.n. et. al.[1], most of the home devices are automated and simply handled by gestures. the patterns are captured by the image capturer and are used for processing. programming part of the implementation is done using algorithms based on matlab. the proposed work is said to use an algorithm for object detection. initially, the picture is captured by the image capturer and matlab is used for processing, if the existing pattern is matched with the given gesture the data will be forwarded to the microcontroller, then the home devices are controlled. the project mainly works on image processing, ai and ml. in rakib hyder et. al.[11],the paper uses recursive circular hough transform (rcht) to demonstrate pupil movement detection which automatically tunes the sensitivity and radius. it uses a low-resolution mobile phone camera to take pictures, from which pupil point is detected. this wheelchair could be controlled by people with working eyes only. here video is continually captured, and the data is forwarded to the personal computer for execution. then picture frames are drawn from the video frequently. it then converts resized rgb image to grayscale image. image adjustment is done to increase the contrast of the output image. in celia shahanaz et. al.[4], the paper demonstrates the necessity for automated electric wheelchairs for disabled people. here an electric wheelchair is implemented, where the device cost is decreased for a large group of people. there are also different features such as rough surface detection, torque adjustments, slope and obstacle detection and hence safety is guaranteed. the system receives input from a microphone, joystick, sonar sensors, and rotary encoders and then processes these using a microcontroller and substantially drives the motors with the help of a motor driver. automatic speed control is implemented which can gradually increase and decrease the speed. there is also a sonar enabled for obstacle detection. in keerthi kumar n et. al.[8], a wheelchair was developed that moves based on the user's brain wave. systems like brain computer interface (bci) are used for transactions between the physical devices and the human brain. it uses a concept called electroencephalography (eeg) to acquire the brain waves and pass it on to the physical device for processing the input and moving the wheelchair accordingly. the data acquisition can be done only when the person is wearing the specified headset. it works on machine learning, brain computer interface and electroencephalography. in prannah dey et. al.[10], this project introduces an intelligent wheelchair which will move with respect to various head gestures. micro-controller is used as the main control part. it also makes use of micro-controller, accelerometer sensor, ldr and ultrasonic sensor. accelerometer sensor is used to navigate the wheelchair in 5 various directions according to the various head gestures by the user. eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e3 3 the wheels use two dc motors to move in different directions. relays are used has driver motor in arduino uno for wheelchair directions. it makes use of solar panel. a photon detection sensor is used which would facilitate the user to navigate in dim light. ultrasonic sensor identifies the hurdles, ldr releases the light and sends the indicator to the microcontroller. sensor for seat belt is used as a provision to provide secure movement. in biswajeet champaty et. al.[3], a wheelchair was developed using eye signals. this machine was developed for people with very minimal movements. an eog signal detection system was first built and then signals received were processed to give the control signals to the wheelchair based on the amplitude and timing of the signals. electrooculogram signals are preferred in this system as it has a unique pattern for each eye movement. it mainly concentrates on the field electro oculography (eog). in abhijit m et. al.,[13] the home automation is done using a hand gesture. the gestures are recognized using the gyroscope, magnetometer and accelerometer on the 3 dimensional axis. the user needs to wear a removable glove for the gesture recognition. a hub is used to control all the home appliances. the input is sent to the hub through a wireless channel like the bluetooth. in siri. t. bhat et. al.,[14] the wheelchair is controlled by the use of hand gestures. the user wears a glove called as sparsh gloves which consists of sensors to analyze the user input. the wheelchair seat height is also made adjustable. this wheelchair is also used to warn the users when there is an obstacle in front of the tire and also behind the wheelchair. in ms. s. d. suryawanshi et. al.,[15] voice commands are for the movement of the wheelchair. these voice commands are compared with the prestored voice commands and respective actions are performed on the wheelchair. an arm processor is used for the control of the wheelchair. the main domain on which this wheelchair works on is voice recognition. in sayeed shafayet chowdhury et. al.[12],the proposed wheelchair can be useful for the people with disabilities making use of easy finger actions on a small white background paper. a sturdy scheme of finger motion detection is proposed for the direction control of a wheelchair. concept of background subtraction and morphological operations are used to acquire the finger-tip area using a finger-motion detection scheme. the method used in this paper is able to figure out finger motion in real-time from photos taken. images are taken using simple cellular phone cameras and fingertip is detected using image processing techniques. the control operation among the cellular-phone and wheelchair is completed wirelessly with the help of bluetooth era. appropriate control indicators are dispatched via bluetooth to the wheelchair control board which helps the users to control the wheelchair in different directions with the help of voice commands. this paper specifies humanitarian applications such as control of flexible bed for patients and even helps in home automation for ease of life. 4. comparative analysis in prannah dey et. al.[10], this project introduces an intelligent wheelchair which will move with respect to various head gestures. head gesture is impractical because many people might feel nauseous while moving their heads around. when ever the person wants to travel for a long distance, he/she needs to either keep moving their head or keep their head in still position which might be difficult. in rakib hyder et. al.[11], the paper uses recursive circular hough transform (rcht) to demonstrate pupil movement detection. since this approach uses a low resolution camera to obtain the pupil movements, the person should always have an eye contact to the camera. if there is no direct eye contact, then the wheelchair could be uncontrollable. this wheelchair could be controlled by people with working eyes only. 100% efficiency cannot be provided in dim environment. if any other person has a direct eye contact with the camera, then the wheelchair might be in a dilemma. in keerthi kumar n et. al.[8], a wheelchair was developed that moves based on the user's brain wave. this interface is that it is very costly and a slight change in concentration also makes the wheelchair to move haphazardly. the person can be able to control the wheelchair only if the person is wearing the specified headset. this is a very sensitive approach and hence if there are any other thoughts occurring in the brain, it may cause problems in movement of the wheelchair. table 1 gives a brief description of how our proposed system overcomes the challenges faced by the existing systems. sl. no existing system disadvantages proposed system 1 head gesture movement nauseous / sickness feeling after a period of time. hand gesture movement 2 pupil movement detection blocks the actual view of the person. hand gesture movement 3 home automation using sensored gloves difficulty in remembering all symbols. user defined patters for home automation. table 1. comparative analysis 5. proposed system the air gestures made by the disabled person are recorded by the camera. the air gestures can be made either using only fingers or complete hand where in the arm of the person will rest on the wheelchair. the person sitting on the wheelchair should just wave his/her finger or hand and hence no additional efforts are necessary. the person can draw the wheelchair control and home automation using hand gestures eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e3 4 gestures without using any gloves. the web camera sends the live video frames to the video processor that houses an algorithm that can understand the air gestures. if the gesture corresponds to wheelchair motion, this information is sent to motor control board and it controls the wheel, while, if the gesture corresponds to controlling home appliances, then the home appliances are controlled through a bluetooth interface. specific home appliances are controlled with the help of a relay. inside a relay there will be a coil, when the voltage is applied through the coil, electromagnetic field is generated and the coil starts to act as a magnet, pulling the armature towards itself which drives the home application. here, designing a video processing algorithm using software as specified below which will identify the air gestures. finally, patterns recognizable by the camera help in the moving the wheelchair, controlling the home appliances and opening/closing of doors. 6. methodology 6.1 existing system figure 1. 3d printed wearable device that holds the hardware components, which include an android pro mini microcontroller, a flex sensor, a motion sensor, and a bluetooth low energy (ble) module.[2] here a wearable hand device [figure 1] is used for sign language detection and interpretation. the device consists of five flex-sensors containing two pressure sensors and a three-axis inertial motion sensor to distinguish the characters in the american sign language alphabet [figure 2]. figure 2. 3d printed finger holder using a flexible filament that can accommodate different finger sizes, providing flexibility: (a) front view, (b) back view, and (c) holder with a flex sensor.[2] figure 3. overview of sign interpretation system that consists of three modules, namely, sensors module, processing module, and application module.[2] the entire system [figure 3] mainly consists of three modules: a wearable device with a sensor module and a processing module, and a display unit mobile application module. sensor data are collected and analyzed using a built-in embedded support vector machine classifier. the recognized alphabet is further transmitted to a mobile device through bluetooth. an android-based mobile application was developed with a text-to-speech function that converts the received text into audible voice output. (b) (a) nithya bg et al. eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e3 5 wheelchair control and home automation using hand gestures figure 4. improved version (second prototype) of 3d printed wearable device (see fig. 1) with fusion of pressure sensor added to the middle finger.[2] the results [figure 4] indicate that a true sign language recognition accuracy rate of 65.7% can be achieved on average without pressure sensors. a second version of the proposed wearable system with the fusion of pressure sensors on the middle finger increased the recognition accuracy rate dramatically to 98.2%. 6.2 proposed system figure 5. block diagram of air gesture interface for wheelchair motion fig 5 gives the outline of our proposed system. once the video is captured, it is processed and sent to the arduino board. based on the type of input, it is sent to the motor control board for wheelchair movement or sent to another arduino board which are connected through bluetooth. these signals are then sent either to motor control board for door control or to relays for accessing home applications. 7. conclusion this paper exhibits different interfaces developed for the movement of wheelchair, gesture detection and home automation. as the researchers are working and making systems better compared to the previous versions, yet there is scope for improvement. the independent mobility is not sufficient for independent lifestyle. accessing home appliances without dependency is just as necessary as independent mobility. this paper has the proposed idea of an interface for the wheelchair that can support wheelchair motion and home automation with door controls. the proposed gesture interface would ease the lives of disabled. references [1] arathip.n, s.arthika ,s.ponmithra ,k.srinivasan, v.rukkumani “gesture based home automation system”, ieee international conference on nextgen electronic technologies – 2017 [2] b. g. lee, member, ieee, and s. m. lee, “smart wearable hand device for signlanguage interpretation system with sensors fusion”, doi 10.1109/jsen.2017.2779466, ieee sensors journal, december 2017 [3] biswajeet champaty, jobin jose, kunal pal, thirugnanam a, “development of eog based human machine interface control system for motorized wheelchair”, international conference on magnetics, machines & drives (aicera) – 2014 [4] celia shahanaz, ahmed maksud, shaikh anowarul fattah and sayeed shafayetchowdhury,” low-cost smart electric wheelchair with destination mapping and intelligent control features”, ieee international symposium on technology in society (istas) – 2017 conference proceedings [5] francesco camastra and domenico de felice, “lvqbased hand gesture recognition using a data glove”, doi: 10.1007/978-3-642-35467-0_17 – may2012 [6] jochen triesch and christoph von der malsburg, “a system for person-independent hand posture recognition against complex backgrounds”, ieee transactions on pattern analysis and machine intelligence, vol. 23, no. 12, december 2001 [7] julian balcerek, adam konieczka, tomasz marciniak, adam dbrowski, krzysztof mackowiak, karol piniarski, “video processing approach for supporting pedestrians in vehicle detection”, ieee september 2014 [8] keerthi kumar m, chaitra rai, manisha r, priyanka c b, syeda saniya anis, “eeg controlled smart wheelchair for disabled people”, international journal of engineering research & technology (ijert) ncraces 2019 conference proceedings. [9] noboyuki otsu, “a threshold selection method from gray level histograms”, ieee transactions on systems, man, and cybernetics, val.smc-9, no.1, january 1979 [10] prannah dey, md.mehedi hasan, srijonmostofa, ariful islam rana, “smart wheelchair integrating head gesture navigation”, 2019 international conference on robotics,electrical and signal processing techniques (icrest). [11] rakib hyder, sayeed shafayet chowdhury and shaikh anowarul fattah, “real-time non-intrusive eye-gaze tracking based wheelchair control for the physically challenged”, ieee embs conference on biomedical engineering and sciences (iecbes) 2016 [12] sayeed shafayet chowdhury, rakib hyder, celia shahanaz and shaikh anowarul fattah, “robust single finger movement detection scheme for real time wheelchair control by physically eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e3 6 challenged people”, ieee region 10 humanitarian technology conference (r10-htc).,2017 [13] abhijit m. ,anjana nair, jikhil john, shabasbasheer, munna basil mathai, "hand gesture based home automation", international journal of advanced research in electrical, electronics and instrumentation engineering, doi:10.15662/ijareeie.2017.0603127 [14] siri.t.bhat, b. surekha, shreesha raghavan, "sparsh glove: a gesture-based hardware control for a multipurpose wheelchair", international conference on computer science and technology allies in research-march 2016 by ijcse, e-issn: 2347-2693 [15] ms. s. d. suryawanshi, mr. j. s. chitode, ms. s. s. pethakar, "voice operated intelligent wheelchair", international journal of advanced research in computer science and software engineering, issn:2277 128x nithya bg et al. eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e3 abstract 1. introduction 2. problem definition 3. review 4. comparative analysis 5. proposed system 6. methodology 6.1 existing system 6.2 proposed system 7. conclusion references big data in telecom industry: effective predictive techniques on cdrs big data in telecom industry: effective predictive techniques on cdrs sara elelimy and samir moustafa∗ computational and data science and engineering, skolkovo institute of science and technology abstract mobile network operators start to face many challenges in the digital era, especially with high demands from customers. since the mobile network operators have considered a source of big data traditional techniques are not effective with new era big data, internet of things (iot) and 5g, as a result handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution(lte) to 5g therefore, there is an urgent need for sufficient big data analytic to predict future demands, traffic, and network performance to fulfill the requirements of the fifth generation of mobile network technology. in this paper, we introduce data science techniques using machine learning and deep learning algorithms: the auto-regressive integrated moving average(arima) bayesian-based curve fitting, and recurrent neural network(rnn) is employed for a data-driven application to mobile network operators. the main framework included in models is an identification parameter of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. these models are applied to telecom italian big data challenge call detail records (cdrs) datasets. the performance of these models is found out using specific well-known evaluation criteria that show that arima (machine learning-based model) is more accurate as a predictive model in such a dataset as the rnn (deep learning model). received on 20 april 2020; accepted on 29 may 2020; published on 04 june 2020 keywords: big data analytics, machine learning, cdrs, 5g. copyright © 2020 sara elelimy et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.13-7-2018.164919 1. introduction operators of mobile networks began to move to the fifth generation from the fourth generation, which is an upcoming and promising solution for meeting the requirements of wireless broadband. additionally, they have started looking for some innovative solutions for facing challenges and providing a satiable customer ∗corresponding author. email: samir.mohamed@skoltech.ru experience with the management of the complex network by efficient backhaul resource handing [1]. telecom organizations and researchers have been studying a diversity of techniques for big data management adequately for discovering unknown knowledge and patterns from the collected information obtained from operators and help organizations in providing smart services for achieving reduced expenditure and resources. 1 eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e1 http://creativecommons.org/licenses/by/3.0/ mailto:<samir.mohamed@skoltech.ru> with the fast uptake in mobile applications and services, requesting demands for infrastructures in wireless network. for 5g requirements and kpis are to support exploding in mobile traffic, provide low latency so this raised need for real-time decision and network resources management and optimization to maximize and increase customer satisfaction and enhance user experience. using traditions methods to achieve these requirements and overcome different problems become a challenge to telecoms. tradition techniques start to be useless in this area so industry and academia start to search and create more effective new techniques to deal with this tremendously increase of data and raise the question of how the telecoms deal with: 1. enormous data sizes (various systems generated a huge amount of log data and reached giga-tera byte). 2. different sources (generated from different sources e.g., routers, switches, applications, operating systems, etc.). 3. heterogeneity (different format, structures, terms of terminology, etc.). these questions and challenges are the main problems statement for this work, and how telecoms benefit from applying ml/dl on different datasets, and what kind of application can be achieved using these techniques that are exiting and traditional ones. in this paper, we are investigating the analysis and application-driven by big data in the telecommunication industry concerning operators of mobile networks for the fifth generation and current networks in their operational and business aspects, implementing different ml/dl techniques driven by big data on data gathered from a telecommunication network and applying different models of prediction for predicting traffic. moreover, in the end, how different results and applications are brought by big data analytic in comparison with traditional methods. also, it will be discussed how they are beneficial for business and operational activities, companies, and how this can be utilized and in which types of applications. 2. analytic tools and data sources for telecoms 2.1. telecom data sources operators of mobile networks form a source and carrier of big data because of the penetration of mobile users have increased significantly [2], and organizations utilized traditional techniques before transactions from the analytic of big data. these techniques pay less attention to operational data, and they do not concentrate significantly on transnational data. the analytic of big data is essential in several ways in comparison with traditional methods. for instance, the compressor transmits data, and useful data are defined by the analytic of big data [3]. in large part of an application, decision-making in real-time is a benefit of using analytic of big data by monitoring the development and infrastructure of network performance. several smart services will be supported and provided by mnos with the analysis of sources and types of data [4]. classifies sources of data for telecoms as operator and subscriber data, external and internal data sources [3], core network levels, cell, subscriber, and kpi deep classification for different networks [5]. when it comes to analytic tools, some of the main tools, as defined by the previous studies, include methods of machine learning modeling, data mining, and statistical modeling [6]. actually, with current development and improvement in data analytic, networks based on big data have formed an attractive area of research for numerous researchers around the globe [7], [8]. additionally, in the industrial sector, researchers recently developed and studied frameworks for big data management in an efficient manner in mobile networks. 2.2. contribution of cdrs or call details records in mobile operators, cdrs were considered essential in for finical aspects. however, in the period of big data, applications driven by it are obtaining attention by researchers in industrial and scientific aspects because datasets of cdrs are full of information associated with communication among numerous users along with how, when, and with whom they are communicating. the analysis of cdrs datasets has become quite a significant and exciting research area [9] because 2 sara elelimy and samir moustafa eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e1 numerous uses associated with these datasets provided by it for different purposes of research resulting in the improvement of dataset management techniques, development of analytic techniques, and analysis types from several perspectives with the use of bigdata methods. when it comes to telecom operators, orange is recognized as one of the biggest, and the first challenge, "d4d challenge" was launched in 2013. they invited different candidates through this challenge from around the globe.addition to it, and access was provided to massive datasets of cdrs for developing objectives of their customer satisfaction and infrastructures as a source of gaining more revenues. successful outcomes have resulted in scientific work, which encouraged the organization to launch a second challenge during the mobile conference of net in april 2015 [9]. in europe, telecom italian is also a recognized mobile operator that faces the same challenges of big data, and2014, big data challenge’s first edition was launched by its [10]. 3. techniques and methodology in the analysis of these datasets, different techniques and methods are utilized. some of the techniques utilized in this work include data visualization, prediction, and clustering. we followed the framework for obtaining the optimum outcomes from datasets. pre-processing is the first step, and it is considered an essential step while using massive data, and in understanding the hidden patterns existing in the data. the next step is concerned with defining analysis type and necessary tools for it, the application type is driven by it, and which type of information might be needed for it. finally, based on the results, the best applications are determined for this analysis. 3.1. data set millions of records are included in a dataset between december and november 2013. in 2014, these datasets were a component of the big data challenge of telecom italian. it was quite ironic and included different types of telecommunications, including electricity data, weather forecasting, news, and social networking. telecom italian has formed an original dataset with the connotation of some specific labs. the institutes included in them are: • fondazione bruno kessler. • eit ict labs. • trento and trento rise institute. • milan polytechnic university. • mit media labs. before the first dataset is released, the attention of partakers is considered. the demand is nevertheless being increased at the competition’s end for datasets, which has become an initiative or measure towards "open big data." datasets, following [10], were freely published for improving the dataset used in the society. telecom italian generated a dataset that is a consequence of evaluation or calculation upon the call detail records for subscribers of milano city. cdrs record user activities for billing and network management, but our research focuses on the use of dataset for different applications rather than utilizing it for traditional activity. information included in dataset described in [10], it consists of main eight variables: • square id: the square id, which is the portion of milan grid. • time interval: the start of the time interval can be stated as the number of milliseconds passed till 1st january 1970 from the unix epoch at utc. in addition, of 10 minutes (600000 milliseconds) to this value, the time interval can be achieved. • country code: it is the local code of a country for phones. • sms-in activity: the sms activity is receiving the inside square id throughout the time interval • sms-out activity: the sms activity is sending the inside square id throughout the time interval. • call-in activity: the calls activity is receiving the inside square id throughout the time interval. • calls-out activity: the sms activity is issuing the inside square id throughout the time interval. 3 big data in telecom industry: effective predictive techniques on cdrs eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e1 • internet traffic activity: the internet traffic activity is issuing the inside square id throughout the time interval and by the state of the user all these activities are recognized from the country code. we have a few types of call detail records for generating the datasets which are related to these activities: before the first data-set is released, the attention of partakers is considered. the demand is nevertheless being increased at the competition’s end for data-sets, which has become an initiative or measure towards "open big data." datasets, following [10], were freely published for improving the dataset used in the society. information included in dataset described in [10], it consists of main eight variables: • received sms: every time when a user receives an sms. • sent sms: every time when a user sent an sms. • incoming call: every time when a user receives a call. • outgoing call: every time when a user issued a call. • internet: every time when a user starts or end an internet connection. throughout the similar internet connection one of the below restrictions is reached : • 15 minutes after producing the final cdr • 5 mb after producing the final cdr this data-set was formed by accumulating the above stated records, to deliver internet traffic, smss and calls activities. the level of collaboration between users and mobile network is calculated through this. for instance, more sms sending by a user results in more activity of the smss sent by the user. the smss and calls activities are having the similar scale of sizes “therefor they are analogous to each other”. according to (data telecom, 2014), data-sets are combined in four-sided cells gird, as shown in figure 1. figure 1. “the area of a milan is composed of a grid overlay, which is 1,000 squares having the size of 235*235 meters.” the grid is probable with wgs84 (epsg:4326) standard 3.2. methods and models in these sections, the adopted methods are explained: • data visualization: using the right type of visualization brings insight into the data analysis process. explanatory data analysis(eda) executed in a proper order to study and expound the dataset. the aim of conducted data analysis, to discover the restriction of data, data patterns, and which unavailable or missing variables. • clustering: clustering procedures, in the data mining field, constitute some important methods [11] due to their significant-high abilities for deducing connections among different data objects. scientists have primarily utilized them for investigating datasets for the tracing of mobile. on different networks acquired from mobile networks, k-means is implemented the most, and in other works, including [12] and [13], it provides satisfactory results. the techniques of clustering are accepted, either a separated approach or hierarchical approaches. hierarchical techniques arrange items into a 4 sara elelimy and samir moustafa eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e1 figure 2. diagrams to show the explanatory data analysis(eda) relations. hierarchical structure, which can visually be represented diagrammatically. hierarchical algorithms can follow an organized method or separated one. however, partitioned clustering algorithms e.g., isodata and kmeans, directly group objects into numbers of categories k.a relevant comment is that hierarchical algorithms can also be used in categorizing objects into a definite number of categories, which can be finished by ending the algorithm at the required point/level. in all instances, there is no stipulated rule to determine the definite number of categories, the decision still remains either ascertained definitely relying on the accordance to certain clustering quality measures or knowledge about the data. innercluster distances. • standardization: standardizing a vector most often means subtracting a measure of location and dividing by a measure of scale. for example, if the vector contains random values with a gaussian distribution, you might subtract the mean and divide by the standard deviation, thereby obtaining a “standard normal” random variable with mean 0 and standard deviation 1, so standardizing the internet traffic before modeling will help in prediction. table 1. show the arima model parameters. white noise arima(0,0,0) random walk arima(0,1,0) with no constant random walk with drift arima(0,1,0) with constant auto-regression arima(p,0,0) moving average arima(0,0,q) • prediction: for mobile operators, it is considered necessary in making decisions associated with network optimization, and as a part of ml. arima model is one of the most renowned algorithms of prediction, as explained in [14]. it is significant for time series data in both static and practical manner. yt = c + p∑ i=1 ϕiyt−i + εi (1) the following are special models from arima: yt−i and εi are respectively the actual value and the random error at the time t, ϕi(i = 1, 2, 3, . . . , p) are the model parameter and is a constant, the integer is known as the order of the model [15]. rnn model is another adopted model, model with many layers on the basis of short and long-term memory is referred to as lstm. a common lstm unit is composed of a cell, an input gate, an output gate, and a forget gate. the cell remembers values over arbitrary time intervals, and the three gates regulate the flow of information into and out of the cell [16]. it consists 5 big data in telecom industry: effective predictive techniques on cdrs eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e1 outputs to next layer ymc (τ + 1) youtm(τ + 1) output gating h(x) smc (τ) smc (τ + 1) cec 1.0 memorising yinm(τ + 1) input gating g(x) yv(τ) yi(τ + 1) figure 3. a standard term short memory (lstm) memory block, and the cell output is calculated by multiplying the cell state by the activation of the output gate. of memory blocks, and it can be trained with the use of black propagation. in this model, the issue of the gradient is gradually decreased [17]. ft = σ (xt ∗uf +ht−1 ∗wf ) (2) ct = tanh(xt ∗uc +ht−1 ∗wc) (3) it = σ (xt ∗ui +ht−1 ∗wi) (4) ot = σ (xt ∗uo +ht−1 ∗wo) (5) figure 4. daily activity. ct = ft ∗ ct−1 + it ∗ ct (6) ht = ot ∗ tanh(ct) (7) xt = input vector , ht−1 = previous cell output ct−1 = previous cell memory,ht= current cell output , ct = current cell memory. w,u = weight vectors for forget gate (ft), candidate (c),i/p gate (i) and o/p(o) [18]. both arima and rnn are performed in a better manner in comparison with others for time series prediction [19]. 3.3. analysis of data and prediction process generally, the base of our analysis is the data-intensive approach, and different techniques of machine learning are applied on datasets of cdrs because it contributes to the value of both business and scientific aspects. three analyses have been performed in our work: first analysis : the highest daily activity is identified in this analysis during a specific day. in addition to it, peak hours within a day are also identified. the first analysis’s results were derived concerning total and time activity, while peak hours are 11, 10, and 9 am, while 3 am is not a peak activity hour. in business aspects and network development, this result is quite beneficial because it will aid in the identification of which areas needs to be developed or requires more resources. it will also help in determined which country code or square grid develops more traffic due to which companies gain more revenues by targeting customers based on their geo-location. additionally, with resource management, it decreases its costs and expenses. 6 sara elelimy and samir moustafa eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e1 figure 5. analysis of residuals second analysis: this analysis compares and illustrates the weekly usage of the internet in november for three id cells portraying different areas for categories in the city of milan. it also included nightlife area, university area, and downtown area. it was indicated by the results that the downtown area’s peak is earlier than that of nightlife, phone calls are less in universities area on the weekends, and a decrease was experienced in the volume of calls. in optimization and resource allocation, these observations will help by defining which area is fully loaded and at what time, and it can help in defining temporary solutions for different peak hours, such as the deployment of pico cell. certain tests were carried out on the dataset to identify and select the proper and effective models for time series data. it is essential to discover trends, seasonality, and stationary of data. residuals analysis provides an indication if data is statistically stationary if the data is truly random noise, it can be classified as statistically stationary from figure 5. another testing method is the dickey-fuller stationary test, which is a quantitative test for residuals analysis; its null hypotheses represent that residual is not statically stationary. findings and results showed that the test statics is about -7, confirmed that residuals are statistically stationary. third analysis: in this analysis, three methods are implemented for prediction and modeling based on table 2. statistical tests to show dickey-fuller stationary test. result of dickey-fuller test: test statistic -7.405407e+00 p-value 7.367220e-11 # lags used 1.000000e+00 number of observation used 1.660000e+02 critical values(1%) -3.470370e+00 critical values(5%) -2.879114e+00 critical values(10%) -2.576139e+00 figure 6. arima hourly prediction of internet traffic for cell id 4456 internet usage. arima model is the first one, lstm is the second model, and the last model is developed on the model which was utilized in the kaggle competition. this model was validated on different types of data weekly for determining if modeling for a week is efficient enough for having similar results and whether it can be implemented on datasets that are collected at different time intervals. • arima for the datasets of one week, the applied model is arima (2, 1, 0). three id cells will be focused upon first for the central regions, and the obtained results are portrayed in the figures 6 and 7. moving on, 9998 cells were the target, as illustrated in figure 8. • lstm one input is included in this model for four blocks and a visible layer in the hidden layer. meanwhile, in the output layer, there is a single input. internet traffic prediction is shown in figure 9 for 4456 cell id every week. 7 big data in telecom industry: effective predictive techniques on cdrs eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e1 figure 7. arima hourly prediction of internet traffic for cell id 5060. figure 8. for all cells, internet traffic hourly prediction using arima figure 9. for 4456 cell id, internet traffic hourly prediction using arima • third prediction model in the kaggle competition, this model was utilized where it was implemented on several periods in contrast without information. generally, it is figure 10. downtown area results of internet traffic figure 11. nightlife and downtown areas and internet traffic data figure 12. universities area and internet traffic data based on many datasets which are periodically set every twenty-four hours. meanwhile, sin behavior is exhibited by internet traffic, as portrayed in figure 10. moving on, this model is implemented in three areas, which are categorized from our analysis. prediction results for nightlife and downtown are represented in figure 11 for the area of universities in figure 12. three models were applied for the prediction internet traffic based on hourly and weekly data results explained that the prediction model of arima is precise for the selected cells and with a 3 percent 8 sara elelimy and samir moustafa eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e1 test set and 70 percent data set. it recognized that 21 percent of test sets and 69 percent training sets were not sufficient enough in cell/data id. the obtained results, for the third model, it was indicated by the obtained results that this model is accurate and suitable for all the selected datasets with the university area being an exception. this area still has some issues, and it might be associated with the mobility of community patterns. the same conclusion as previous works was obtained for different dataset periods. thus, it was determined that this model was suitable for all datasets. results have indicated that the application of predictive models and intelligent data analysis for the prediction of traffic are considered significant, and they play a vital role for mobile operators, which will be quite useful in the routing of traffic. it can indicate yearly prediction as well for supporting network optimization, resource allocations, self-organizing networks, and investment planning. 4. discussion for mnos, this research is dedicated to big data management and applying ml/dl techniques in an efficient manner in the sector of data-driven apps and the telecommunication sector. comprehending the available data, which analytic tools are eligible and must be implemented, and which type of information or data should be collected are significant for any provider of service for harvesting the best results from the data. big data is selected and applied in this work, and t is vital to recognize that techniques of machine earning and deep learning contribute significantly to both the industrial and academic sector and playing a significant role in wireless network application like network traffic prediction using different clustering techniques, it is possible to cluster mobile users based on cdr records and generate location-based recommendation system. cdrs mining using these techniques then existing one expands its role and applications not only for finical usage, but also by extracting huge and important knowledge from this dataset introduces different application for telecoms: 1. analyzing cdrs data can be provided demographic about genders and age where we can use rnn or cnn to predict these features of mobile users. 2. rnns are employed to determine the metro density from massive cdrs data, they propose to identify the trajectory of the customer as a sequence of locations as input to rnnmodel to handle this sequential data. 3. from code number information in cdrs, it is possible to predict tourist‘s locations and make business packages. it has been proven by this practical work how benefits in the business and operational aspect of the telecommunication industry can be obtained with the effective application of techniques of big data instead of traditional techniques. models like lstm and arima was applied for the prediction of traffic, and it was explained that results were quite beneficial in strategic and short plans for the operator. for the performance of our practical part, cdr database selection was based on the significance of the dataset for the mno since it is indicated by our results that cdrs analysis has much significance beyond and currently in different areas like investment plans on the basis of optimization network, fault detection traffic prediction, network optimization, and resource allocation. for future work, we will apply ml/dl techniques on different unlabeled datasets since mos-generated data in wireless network systems have these challenge able features, which required specific techniques. acknowledgement this research is developed on the basis of a master thesis “methods to efficiently handle big data in 5g networks” 20181, double degree erasmus + program between higher school of economics and uas technikum wien. i would like to express my sincere gratitude to my academic supervisors and the professors and lecturers at the big data systems program. improvement is made during study at skoltech. 1https://www.hse.ru/en/edu/vkr/219430036 9 big data in telecom industry: effective predictive techniques on cdrs eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e1 references [1] zeng, d., gu, l. and guo, s. (2015) cost minimization for big data processing in geo-distributed data centers. in cloud networking for big data (springer), 59–78. [2] bi, s., zhang, r., ding, z. and cui, s. (2015) wireless communications in the era of big data. ieee communications magazine 53(10): 190–199. [3] he, y., yu, f.r., zhao, n., yin, h., yao, h. and qiu, r.c. (2016) big data analytics in mobile cellular networks. ieee access 4: 1985–1996. [4] zheng, k., yang, z., zhang, k., chatzimisios, p., yang, k. and xiang,w. (2016) big data-driven optimization for mobile networks toward 5g. ieee network 30(1): 44–51. [5] imran, a., zoha, a. and abu-dayya, a. (2014) challenges in 5g: how to empower son with big data for enabling 5g. ieee network 28(6): 27–33. [6] boccardi, f., heath, r.w., lozano, a., marzetta, t.l. and popovski, p. (2014) five disruptive technology directions for 5g. ieee communications magazine 52(2): 74–80. [7] ramaprasath, a., srinivasan, a. and lung, c.h. (2015) performance optimization of big data in mobile networks. in 2015 ieee 28th canadian conference on electrical and computer engineering (ccece) (ieee): 1364–1368. [8] samulevicius, s., pedersen, t.b. and sorensen, t.b. (2015) most: mobile broadband network optimization using planned spatio-temporal events. in 2015 ieee 81st vehicular technology conference (vtc spring) (ieee): 1– 5. [9] blondel, v.d., decuyper, a. and krings, g. (2015) a survey of results on mobile phone datasets analysis. epj data science 4(1): 10. [10] italia, t. (2015), telecom italia big data challenge. url https://dandelion.eu/datamine/open-big-data/. [11] xu, r. and wunsch, d. (2005) survey of clustering algorithms. ieee transactions on neural networks 16(3): 645–678. [12] soto, v. and frías-martínez, e. (2011) automated land use identification using cell-phone records. in proceedings of the 3rd acm international workshop on mobiarch: 17–22. [13] liu, j., chang, n., zhang, s. and lei, z. (2015) recognizing and characterizing dynamics of cellular devices in cellular data network through massive data analysis. international journal of communication systems 28(12): 1884–1897. [14] zhang, g.p. (2003) time series forecasting using a hybrid arima and neural network model. neurocomputing 50: 159–175. [15] adhikari, r. and agrawal, r.k. (2013) an introductory study on time series modeling and forecasting. arxiv preprint arxiv:1302.6613 . [16] hochreiter, s. and schmidhuber, j. (1997) long shortterm memory. neural computation 9(8): 1735–1780. [17] sundermeyer, m., schlüter, r. and ney, h. (2012) lstm neural networks for language modeling. in thirteenth annual conference of the international speech communication association. [18] staudemeyer, r.c. and morris, e.r. (2019) understanding lstm–a tutorial into long short-term memory recurrent neural networks. arxiv preprint arxiv:1909.09586 . [19] ho, s.l., xie, m. and goh, t.n. (2002) a comparative study of neural network and box-jenkins arima modeling in time series prediction. computers & industrial engineering 42(2-4): 371–375. 10 sara elelimy and samir moustafa eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e1 https://dandelion.eu/datamine/open-big-data/ 1 introduction 2 analytic tools and data sources for telecoms 2.1 telecom data sources 2.2 contribution of cdrs or call details records 3 techniques and methodology 3.1 data set 3.2 methods and models 3.3 analysis of data and prediction process 4 discussion performance analysis on popularity based, content based and collaborative filtering utilizing recommendation framework 1 performance analysis on popularity based, content based and collaborative filtering utilizing recommendation framework deepkiran munjal1,*, anju gera2 and pawan kumar singh2 1 master of computer application, g. l bajaj institute of technology and management, greater noida, india 2 computer science and engineering, g. l bajaj institute of technology and management, greater noida, india abstract in today's computerized world, it has become an irritating undertaking to locate the substance of one's loving in an interminable assortment of substance that are being devoured like art, education, media and so on. then again there has been a developing development among the computerized substance suppliers who need to connect the same number of clients on their administration as feasible for the most extreme time. a tune proposal is significant in our public activity because of its highlights, for example, in building smart cities recommending a lot of melodies to clients dependent on their advantage, or the popularity of the tunes. in this paper we are proposing a song suggestion framework that can prescribe song to another client just as the other existing clients. we use popularity based, content based separating, and collaborative filtering, which is a blend of application of communication systems, to develop a framework that gives progressively exact proposals concerning melodies. *corresponding author. email:deepa.munjal@gmail.com 1. introduction concerning a huge informational collection over the web, where the quantity of administrations are given, than in order to improve the issue of data over-burden, it is expected to channel, organize and effectively convey pertinent data, which has made an idle issue to numerous internet clients. so as to convey clients with customized substance and administrations recommender frameworks take care of this issue via looking through huge volume of enthusiastically created data. this proposition investigates the various attributes and possibilities of various expectation strategies in suggestion frameworks so as to fill in as a extent for research and practice in the field of proposal frameworks. give c a chance to be set all things considered and let s be set of all conceivable recommendable things. give u a chance to be an utility capacity evaluating the value of component s to client c, i.e., u: c x s→r, where r is a completely requested set. for every client c є c, we need to pick things s є s that expand u. the primary assignment is to appraise an utility capacity (u) that by configuration predicts how a client will like a thing. in light of past conduct, associations to different clients, item similarity, context and so forth. with the ascent of advanced substance appropriation, individuals presently approach music assortments on an exceptional scale. business music libraries effectively outperform 15 million tunes, which monstrously surpasses eai endorsed transactions on smart cities research article keywords: art education and media recommender system, popularity based, content based filtering, collaborative filtering, smart cities, application of communication systems. handling editor: akshat agrawal (amity university gurgaon, india) received on 24 july 2020, accepted on 13 august 2020, published on 25 august 2020 copyright © 2020 deepkiran munjal et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.18-8-2020.166001 eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e2 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ mailto:author@emailaddress.com deepkiran munjal, anju gera, pawan kumar singh 2 the listening ability of a specific individual. with a large number of melodies to browse, individuals some of the time feel overpowered. therefore, an effectual music recommender framework is basic in light of a legitimate concern for both music specialist co-ops and clients. clients will have no more agony to settle on choices on what to tune in while music organizations can keep up their client gathering and draw in new clients by improving client's fulfilment. the fundamental goal of this paper is to give customized proposal, to build the degree of fulfilment of the client and to assist the clients with searching and listen the tunes in compelling and responsive way. 2. related work there is hazardous development in the measure of existing advanced data and the quantity of guests to the internet have made a potential test of data over-burden which hampers opportune access to things of enthusiasm on the internet. data recovery frameworks, for example, google, devil finder and altavista have in part tackled this issue however prioritization and personalization (where a framework maps accessible substance to client's inclinations and inclinations) of data were missing. this has expanded the interest for recommender frameworks like never before previously. recommender frameworks are gainful to both specialist co-ops and clients. they lessen expenses of finding and choosing things in an online music portal. recommendation frameworks have additionally demonstrated to improve basic leadership procedure and quality. in online music portal, recommender frameworks improve incomes, for the way that they are successful methods for selling more items. in logical libraries, recommender frameworks bolster clients by enabling them to move past inventory look. in this way, the need to utilize proficient and exact proposal strategies inside a framework that will give significant and trustworthy suggestions to clients can't be over-accentuated. engineering of requirements is one of the most basic phase of a product improvement process and inadequately actualized prerequisites building is one of the significant explanations behind venture disappointment [10]. center prerequisites building exercises are elicitation and definition, quality confirmation, exchange, and discharge arranging [17]. these exercises can be upheld by suggestion advances, for instance, the (cooperative) proposal of prerequisites to partners taking a shot at comparable necessities [11] and the gathering based suggestion of necessities prioritizations [12]. model: content-based recommendation based on content requirements. in the accompanying, we will represent the use of substance based separating [13] with regards to necessities designing. a recommender can bolster invested individual, for instance, by prescribing prerequisites that have been characterized in effectively finished programming ventures (necessities reuse) or have been characterized by different partners of a similar undertaking (excess and reliance recognition). table 3 gives a diagram of necessities characterized in a product venture. every necessity is described by a class, the quantity of assessed individual days to execute the prerequisite, and a printed depiction. persuasive innovations [18] plan to trigger changes in a client's dispositions and comportment based on the ideas of human pc collaboration. the effect of enticing innovations can be fundamentally expanded by moreover coordinating proposal advancements into the plan of persuasive systems. such a methodology pushes enticing advances ahead from a one-size-fits all way to deal with a customized domain where client explicit conditions are taken into translation while creating convincing messages [19]. instances of the use of proposal innovations in the viewpoint of enticing frameworks are the execution of physical action while playing pc games [7] and moving programming engineers to improve the nature of their product modules [8]persuasive systems games. games concentrating on the inspiration of physical exercises incorporate extra reward systems to urge players to perform genuine real exercises. berkovsky et al. [7] show the effective utilization of collaborative filtering recommendation innovations [6] for assessing the individual trouble of playing. 3. proposed system music recommendation system utilizes popularity based, collaborative filtering based and content based recommender to discover relationships among clients figure 1.1. recommendation system methods popularity recommender collaborati ve filtering recommen der content based recommend user recommended song song tabl e album table usersong relationsh ip table profile table eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e2 performance analysis on popularity based, content based and collaborative filtering utilizing recommendation framework 3 and tunes. each of this recommender has certain preferences and impediments. this implementation is attempted to make a coordinated recommender which is blend of all these recommender to give better suggestions. to defeat this, top spilling administrations utilize a mix of calculations to shape recommender framework. our first approach is to make a proposal system using content examination. first assignment is to remove the dataset suitable for desire. for this, we have taken the fma and million tune dataset from columbia.edu and github. our recommender system is a cross breed approach between collaborative isolating, popularity based, and content based separating the dataset was pre-processed using r and python. the groups used for in r were readr, dplyr and catools while pandas and numpy were used in python. the recommendation algorithms mainly follow collaborative filtering, content-based and filtering approaches: 1. popularity based : the most trifling suggestion calculation is to just present every melody in relative request of its prevalence bouncing those tunes previously devoured by the client, paying little mind to the client's taste profile. 2. content based filtering: use highlights of the two items just as clients so as to estimate whether a client will like an item or not. 3. collaborative filtering: it can be either client based or thing based. in client based underwriting, clients who tune comparable interests and will most likely tune in to similar tunes in future. in the thing based suggestion technique, melodies that are regularly tuned in by a similar client will in general be comparative and are bound to be listened reserved in future by some other client. on basis of popularity based, content based and collaborative filtering the data is filtered and recommend the music for users. by combining the three evaluated result is filtered through and provide better recommendation. 4. result and analysis the result outcome module is shown in this paper. it is implemented in python with the separate results of each filtering. this evaluation is shown for popularity based recommender analysis. figure 1.2. showing the correlation between features for song to simply present each song in descending order of its popularity skipping those songs already consumed by the user, regardless of the user’s taste profile. 4.1 popular songs scoring formula score = ([non_unique_user_listen_count* non_unique_users_weight] + [unique_user_listen_count * unique_users_weight]) / song_ age whereunique_users_weight:1 non_unique_users_weight:0.25 table1.1 popular songs score evaluation: song_ title listen_ count unique_ users song_ age score set fire to the rain 5 3 2 1.75 eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e2 deepkiran munjal, anju gera, pawan kumar singh 4 figure 1.3. showing the values of various features of corresponding songs it very well may be either client based or thing based. in client based suggestion, clients who tune in to similar melodies in the past will in general have comparative interests and will presumably tune in to similar tunes in future. in the thing based proposal procedure, tunes that are regularly tuned in by a similar client will in general be comparable and are bound to be listened together in future by some other client. by controlling the informational collection, changing the learning set and testing set, changing a few parameters of the issue and breaking down the outcome, we acquire a great deal rehearsing aptitudes. figure 1.4. showing the song co-occurrence matrix eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e2 performance analysis on popularity based, content based and collaborative filtering utilizing recommendation framework 5 figure 1.5. showing the summation across columns in song co-occurrence matrix figure 1.6. showing the normalized song recommendations 5. conclusion in music recommender system there are various ways to deal with this issue and we become acquainted with certain calculations in detail and particularly the models that we have clarified previously. by utilized the informational index, changing the learning set and testing set, changing a few parameters of the issue and breaking down the outcome, we win a great deal rehearsing abilities. we have confronted a great deal of issues in managing tremendous dataset, how to investigate it in a superior way and we likewise experienced issues in some program configuration subtleties. in any case, with parcel of efforts, we have conquered these. as far as research, despite everything we have a ton to do to make our examinations a superior one. music recommender system is such a wide, open and intricate matter that we can take a few activities and do significantly more tests in future. we likewise got the chance to understand that developing a recommender framework is certainly not a unimportant errand. the way that enormous scale dataset makes it troublesome in numerous perspectives. right off the bat, suggesting pertinent tunes out of large dataset for various clients isn't a simple errand. also, the metadata incorporates gigantic data and while investigating it, it is hard to dig important highlights for melody. thirdly, in fact talking, preparing such a tremendous dataset is memory and cpu serious. every one of these troubles because of the information and to the framework itself makes it all the more testing and furthermore increasingly appealing. 6. future work in future, firstly we want to work upon segmentation of data set. there is a huge set of data available. to classify and segment data is the toughest job. we will work on this area to make data set clear and segregated. this will increase the performance of recommendation system more fast and accurate. for this we can apply many clustering algorithms. in future the proposal framework can be utilized for different applications like in restorative field for directing the best medicinal analyse for fix of a patient and in future ( in medical field ) this will be relevant to work in space of man-made consciousness. building capable suggestion set of rules and the comparing uis requires a profound comprehension of human choice procedures. this objective can be accomplished by investigating existing mental plans of human basic leadership and their impact on the development of recommender frameworks. references [1] book: schafer, j.b., konstan, j.a. & riedl, j. ecommerce recommendation applications. data mining and knowledge discovery 5, 115–153 (2001). 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[15] conference: hinde u., and shedge r. comparative analysis of collaborative filtering technique, iosr journal of computer engineering, volume 10, 2013. [16] conference: jiang, c., & he, y. (2016). smart-dj: context-aware personalization for music recommendation on smartphones. 2016 ieee 22nd international conference on parallel and distributed systems (icpads) [17] journal article: haruna k, akmar ismail m, damiasih d, sutopo j, herawan t , a collaborative approach for research paper recommender system. plos one 12(10): e0184516, 2017. [18] conference: pirkka åman, lassi a. liikkanen, interacting with context factors in music recommendation and discovery, computer science international journal of human–computer interaction, 2017. [19] conference: åman, pramila m. chawan int. journal of engineering research and application www.ijera.com issn : 2248-9622, vol. 8, issue5, may 2018 eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e2 https://www.semanticscholar.org/author/pirkka-%c3%85man/31680990 https://www.semanticscholar.org/author/lassi-a.-liikkanen/1732403 assesing the feasibility of smart grid technology on electrical distribution grids 1 assesing the feasibility of smart grid technology on electrical distribution grids tatenda kanyowa1,*, rindai p. mahoso1 1harare institute of technology, po box be277 ganges road belvedere, harare, zimbabwe department of industrial and manufacturing engineering abstract this paper gives a critical analysis framework on the impact of smart grids on electrical distribution grids. it highlights the discrepancies between the developed and developing countries on the adoption of this technology. the concept of smart grids is gaining appreciable recognition in the developed world’s electricity networks. the need to assess the impact of this new technology is critical as the laws of infrastructural clearly show that this is the direction to go if speedy and efficient development is going to be achieved in the developing world. a case study of developing countries was cited as a reference base and compared against developed countries. as developing countries still have the majority of their people still without access to power, the paper shows that the capacity for the implementation of smart grid technologies is ripe for implementation, albeit at a rather high fiscal cost. keywords: developing country, developed country, smart grids. handling editor: akshat agrawal (amity university gurgaon, india) received on 09 july 2020, accepted on 24 july 2020, published on 28 august 2020 copyright © 2020 tatenda kanyowa et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.18-8-2020.166008 *corresponding author. email: tkanyowa@hit.ac.zw 1. introduction as the technology advances and the demand for electricity increases, it has become imperative to implement methods that address the generation, distribution and storage of electrical power. the development of electrical grids globally has been very slow over the years especially in africa and with the everincreasing energy demands it has led to economic, environmental and political unrest. due to these concerns, there has been an ongoing global discussion on implementation of smart grids with first world countries showing a great deal of commitment. smart grids offer a great deal of benefits when it comes to revamping and making strides in the electric network structure and most work carried out in this area has been centred on developed countries. to comprehend smart grids one has to know its perceived characteristics which include facilitation in the generation, distribution and storage, optimizing asset utilization and real time monitoring. [1] smart grids synchronize across the value chain from end users to investors all the way to shareholder by significantly reducing the associated costs that come with environmental impacts and at the same time manipulating high system performances, consequently this a critical piece of infrastructure in the big data matrix. [2] recent studies have shown that developing countries have the highest urban growth population which has seen power needs showing a positive correlation as well. this urban migration is also ironically in the population following the more developed urban areas with electricity. statistically is has been shown that the majority of the world experience the scourge of power outages or lack of power therefor, with 17% of the global population without electricity and 40% still using non-renewable sources for cooking and space heating. a global survey has also shown that by 2050, seven out of ten people are expected to live in cities. however the repercussions of this newfound access are frequent blackouts that will leave eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e3 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ tatenda kanyowa , rindai p. mahoso 2 many people in the developing countries with at least 20 hours per day with the average urbanite zimbabwean already going through long period per day of power outage. these effects are already evident as the power grid is burdened with cities overpopulated and infrastructure development of the grid only at 30% of potential development. india which has one of the largest population in the world faced the largest blackout in history when the electrical grid crushed. this caused a cease in many operations that supported the economy and as a result the economy experienced the effects of the blackout. this is another example of how the energy grid suffers when it is over-powered by the population and there are no backup structures to curb the effects. as developing countries evolve into modern metropolises, it is clear that the best solution for developing countries hinges on the development of efficient and reliable generation and distribution systems for the advantage of the general populace. [3] in this light, the timing is perfect as the band wagon of data manipulation (big data) has officially turned its stare of intent towards energy generators and distributors to make them more viable and reliable. what this means is that, smart meters in every household that allow energy measurements and control energy consumptions. for developing countries that have an exponential city growth and an unbalanced mix of energy supply and demand and theft, the changes could be transformational. india loses 25% of its electricity during distribution, usa loses 8% and zimbabwe loses 14% which translates to $40 billion, $25 billion and $250million respectively in monetary terms. the smart grid is still very much in its infancy stage but a lot of capital is being invested each year into the industry and is expected to reach higher figures globally by 2030. the south american number one player brazil alone will invest $36 billion in smart grids to substitute 63 million energy readers with smart meters. india is expected to pump $10 billion and one of the biggest economies in the form of china outmatched the united states in 2013 with $4 billion investment. these are however very high figures for the developing countries of africa. this then sets up an intriguing paradox for the developing nations. [4] smart grids need to be monitored meticulously in developing countries and guesstimated delicately especially when it comes to financials to safeguard the narrow equity available in these countries. expense recovery for smart grids investment is challenging in developing countries due to the limit on the figures by which tariffs can be surged and still remain in an affordable range. when synergistically mixed with renewable energy capacity and enforced efficaciously, smart grids result in a plethora of advantages such as reduction of power outages and transmission losses. [5] table 1. associated betterment for investing smart grid technology in developed and developing countries. advantage beneficiary downsized outages end users scaled down electricity losses energy distributor lessened carbon dioxide emissions surrounding community decreased additional service costs energy distributor delayed investments for distribution energy distributor minimized equipment failure energy distributor extensive research and studies have indicated the area of interest has been exhausted even though the technology has been in its infancy in terms of implementation. however the current studies be they similar in nature or dissimilar do not clarify and highlight a visible plan for both developed and developing countries. most studies either focus on one of the two, either developed or developing countries. the question remains are the conditions for implementation still the same for the different areas. what are the areas of focus, what are the cost benefits for each area, what are the challenges to be faced in each area amongst other questions? the novelty of this article hinges on critically giving an insight and answers these questions in a meticulous manner. the article or research is based on recent findings from both developed and developing countries so that a clearer conclusion could be reached on the feasibility of this technology without a one sided view. the article commences by analysing the types of smart grid technologies available and then goes on critically compare the issues faced in developing and developed countries in trying to adopt this technology. a roadmap to expedite and facilitate the adoption of smart grids is then highlighted and the article concludes by explaining the eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e3 assesing the feasibility of smart grid technology on electrical distribution grids 3 challenges experienced by both developed and developing countries. 2. objectives/ rationale of the study • to analyse the stages of development and research of smart grid systems in developing and developed countries. • t conduct quantitative and qualitative research on smart grids. • to study the roadmap or future of smart grids. 3. smart grid technologies wide area monitoring responsible for assessing performance in real time and subsequently showing the result of system elements crosswise the linkage and throughout the massive geographical areas. these state of the art operations scale down on blackouts and merges with a mix of renewables. progressive technologies generate data which informs decision makers mitigate disturbances and improve transmission capacity. 3.1 renewable and distributed generation integration a synthesis of renewable and various energy sources which are distributed encapsulate all the scale levels from large to medium to small scale. this means we are looking at commercial and residential buildings which pose different challenges when it comes to quickness and manageability. 3.2 advanced metering structures allows the dispatch ability of a mix of technologies to already existing modern smart systems which permits an exchange of data in two directions, giving end users and distributors information on pricing and usage as well the timeline of power used and the quantity. 3.3 customer side systems probably the most improved and sophisticated system which aids in power usage at all levels. the information is generally shown on a dashboard and usually it comes in the form of power peak demand and power or efficiency gains. this kind of system synergizes manual responses from the end user and the automated responses on pricing. [6] 4. smart grids and renewables the ultimate goal of every nation is to run on sustainable energy sources and in particular we will mention renewables. the increase of renewable energy is a fundamental ingredient in accomplishing the global power mix and such an action will require an upgrade from old grid systems to new robust energy systems, case in point smart grid systems. smart grid systems when incorporated with renewables need to possess some of the following characteristics; 4.1 distributed generation smart grids facilitate the precise pricing and valuation of renewables as appropriated energy generation has several effects on distribution systems. smart grids provide comprehensive data on related output and performance and aid the operators in putting accurate figures on the cost of generated renewables. it should also be noted that the information and control is useful in several ways which include but are not limited to reducing output or disconnecting distributed energy. 4.2 variability the principal challenge in electricity systems is always maintain the match for demand with supply be it nonrenewables or renewables. traditional fuel powered plants operate on set points and operators rely on them to produce a steady output with less fluctuations. however with renewables such solar or wind which are intermittent in nature, there is always going to be variations in output resulting in an unmatched demand and supply. when smart grids are incorporated they make it achievable to combine a broad spectrum of renewables. 4.3 capital investment smart grids diffusely highlight on the issue of equity required for renewables by supporting private financing in power systems. in past times the power generators were responsible for enacting power plants. with the ever changing times policies and governments have given support to private investors to finance their power plants along the regulated guidelines. [7] 5. developed versus developing countries smart grid technologies present a premium of chances for both developed and developing countries. a study shows that the pushing elements for the approval of smart grid technologies in developing economies revealed that these often vary in analogy to the drivers in developed countries. as indicated by figure 1, the comparison eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e3 tatenda kanyowa , rindai p. mahoso 4 indicates that while bettering system efficiency is crucial for both developed and developing countries, increasing system reliability and achieving secure revenue collection has a higher priority. it can be clearly seen from figure 1 that developing countries need to focus more on reliability and system improvements and they focus more revenue collection whilst developed countries have improved their supporting policies to enable renewable energy generation and new products introduction in conjunction with system efficiency improvements. [8] figure 1. an analogy of the main drivers for investments in smart grids (developing and developed countries) due to these different contrast drivers for smart grid investment, developing countries also have different technological priorities when it comes to smart grids. figure 2, indicates the contrast in the technological priorities for smart grid installation for developing and developed countries. figure 2 highlights how developed and developing countries prioritizes technological improvements and this can be attributed to the differences in economical advantages between the two. figure 2. an analogy of the technological preferences for installations of smart grids (developing and developed countries) moreover, table 2 also indicates some of the problems experienced by the electricity network in many developing countries and their corresponding quick fixes which can be used to address these issues. the problems are similar in nature for both developed and developing countries which means an action to implement would also mean these issues have to be tackled. distributed generation from renewables, limited generation capacity, costs and ageing infrastructure are some of the challenges which can be resolved by balancing demand and supply, load management and efficient generation among other solutions. [8] eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e3 5 table 2. problems that are faced in the electricity network and the complementary solutions existing problems in the energy system solutions for smart grid renewable and distributed generations matching supply and demand with existing business models restrained output capacity managing load and minimizing on peak loads and times ageing infrastructure implementation of automatic systems that avoid power outages value and emissions of energy supply reliable output levels in terms of supply and demand revenue losses accountability of all power generated and distributed via automated systems 6. methodology the authors work is purely a research article which focused on the impact of smart grids on electrical distribution grid for both developed and developing countries. the research approach was a combination of both qualitative and quantitative data gathering to understand the differences and similarities between the developed and developing countries. for quantitative data gathering it was purely based on recent studies of research papers and journals on the subject area. the research stemmed from the need to understand the challenges experienced in implementing smart grids. recent research studies and supporting journals were guidelines for the quantitative data for both developed and developing countries. as for qualitative data, a few interactions with management in energy sectors aided in formulating some of the conclusions. it was a constraint though in this section as the authors were dealing with people who have not yet implemented the technology but with a roadmap. the analysis of the gathered data was however a success as it was near accurate and a mixture of current studies, implementation and near implementation. 7. success of smart grids implementation 7.1 distribution of a mix of generation technology in a bid to minimize the carbon footprint correlated to power supply, a plethora of variable generation technologies have been deployed. the escalation is expected to expedite in the distant future with most countries incorporating these technologies in their electricity systems; zimbabwe included. the zimbabwean government has encouraged the development of independent power generation companies with an emphasis on renewables. as the growth accelerates, it will become challenging to establish a steady and decent management of energy systems supply depending on conventional grid architectures and limited flexibility. smart grids will however will give strength to deployment of a mix of generation technologies by providing operators with real time information that enables management of generation, demand and power quality thus increasing system flexibility and maintaining stability and balance. spain initiated a global pioneering to monitor and control these variable renewable energy resources by allowing the maximum amount of production to be integrated under secure conditions. [9] 7.2 electrification of transport a statistical survey indicates that due to the increase of electric vehicles and hybrid vehicles, the transport sector will consume 10% of electricity consumption. charging of electric needs meticulous monitoring or it may result in a surge of peak loading on the electricity infrastructure which consequently leads to current peak demands. smart grid technology allows prioritized charging in cases of low demand exploiting the use of both low cost generation and extra system capacity. in the long term there is a possibility that vehicles could give stored electricity in the batteries back into the system when needed. the netherlands engaged in a project that established a network of electric car recharging sites using smart communication and communication technology assesing the feasibility of smart grid technology on electrical distribution grids eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e3 tatenda kanyowa , rindai p. mahoso 6 applications to enable distributors to deal with additional power demands. [10] 7.3 hurdles to overcome in smart grid adoption the electrification of developed countries has spanned over a couple of years and continued financial support is required to maintain a consistent power supply. with growing energy requirements and changes, ageing distribution and transmission infrastructure will need replacement and updating. the downside of this action is that technology investment will be obstructed by current market and regulatory policies which have been enacted for long periods and overlooking the perks of new innovative technologies. smart grids offer a way to maximize existing infrastructure through better monitoring and management. fast emerging economies like china have a different assortment of smart grids infrastructure needs from developed countries and its response to its high growth in demand will result in newer distribution and transmission infrastructure. europe and america have the highest number of ageing infrastructure especially at the transmission level. japan has been successful in deploying the smart grids which operate at high reliability levels and now focusing on distribution levels. [11] 7.4 peak demand the variation in energy demand is high across the day periods and throughout the seasons. the distribution systems are tailored to cater for high demand periods and during non-peak hours the system is under-utilized. enacting systems which meet erratic peak demand requires huge investments that would not be needed if the demand curves were flatter. smart grids can reduce peak demand by providing information and incentives to consumers to allow them to shift consumption away from peak demand periods. the management of peak demand enables improved system planning throughout the entire electricity system, increasing options for new loads. these benefits are essential for new systems where demand growth is very high and for existing and ageing systems that need maintenance. [12] 7.5 capital expenditure all types of smart grid will require major investment and the actors investing will face investment risk accordingly. the more advance types that promise greater benefit require investors with different interests to join forces and to at least coordinate their investments. three factors which determine investment include; dealing with new risks and uncertainties, dealing with new decision making arenas in which investment plans need to be defended and dealing with the new power position of the electricity consumer and prosumer. each factor need to be analysed with respect to the market forces. [13] 7.6 tailoring smart grids to developing countries and emerging economies first world countries have advanced contemporary systems for smart grids whilst the majority of existing grids that do not operate constantly over a lengthy period, and other have no infrastructure at all. developing countries and upcoming economies are classified by steep expansion in energy demand, high commercial and technical losses in a context of rapid economic growth and development. such areas often present important issues and probabilities concerning the subject area. smart grids play a crucial role in the distribution of new electricity infrastructure in developing countries by allowing more competent action and minimized costs. minor peripheral systems not networked to a centralized electricity asset and initially employed as a price effective approach to rural electrification might be later connected easily to a national or regional infrastructure. as a means to access to electricity in sparsely populated areas, smart grids could enable a transition from simple, one off approaches to electrification to community grids that can then connect to national and regional grids. the deployment stages go from battery based and single household electrification to micro, mini or standalone grids to national grid and regional interconnection. these stages require standardisation and interoperability to be scaled up to the next level with higher amounts of supply and demand. each successive step can increase reliability and the amount of power available if managed in a way that allows seamless variation from the community. ultimately the end point of smart grid deployment is expected to be similar across the globe but the routes and time to get there could be different. 8. recommendations • cultivate research to enhance smart grid programs where the general objective is to achieve dependable and effective grids to cope with the ever changing outlook. • foster dissemination and knowledge initiatives with the end objective of allowing grid operators to have a central role and allow them to providing the largest number of security requisites. • improve the regulatory and policy framework in which this legal framework would aid in harmonizing existing policies which would be considered as a reference with which to align policies and regulations on other aspects. eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e3 assesing the feasibility of smart grid technology on electrical distribution grids 7 • a key element is to allow the revamp of the existing infrastructure which is of old age. the result in to enact systems which will have a long life span and provide efficient output and robustness • development of roadmaps for standardisation and interoperability which allows for devices to communicate and operate seamlessly across all levels of the grid. • initiate innovation in business models where the government, regulators and utilities should define roles and operational boundaries. government should collaborate with manufacturers, network owners and operators to create sandbox environments in which new distributed energy business models can be operated in real world conditions to identify least cost integration options. 9. the future current market systems are coupled with hurdles that hinder the proper implementation of smart grids. it is imperative that regulatory and market models that address investments, prices and end user involvement advance as new technologies offer new options. most typical markets offer vertically integrated utilities which own and operate infrastructure assets across the generation, distribution and transmission. therefore roadmap for the developing countries to achieving the feat of smart grids is divided into seven actions and these actions are sequential in their implementation. the first action is the challenge faced with grids and the associated advantages that grids offer. second action explains the trending status of smart grids coupled with combined expenses and profits. third action is a future perception for smart grid distribution. the fourth and fifth action examine smart grid technologies and policies and milestones. the sixth action analyses current trends and the outlook of international collaboration and the seventh presents an action plan and identifies future steps. these steps will encompass the full system from generation, transmission, distribution and management for the system. [15] 10. conclusion this research article has articulated the adoption of smart grids and the constraints to be faced by both developed and developing nations. in advanced countries, strides have been made in adoption and implementation of these systems with developing countries still lagging behind. the major achievements have been efficiency, reliability and productivity through the use of smart grids. power generation is not limited to engineering problems, it is multi-dimensional and affects the infrastructure and exchange of information between systems. the following points can be drawn from the study; • smart grids can be seen as a basal asset that give the capability to replace adequate use of data to form more effective investments in the electricity systems. • smart grids have the potential to change the outlook of how energy generation devising is carried out and how large scale electricity markets are planned. the data gathered will give users the liberty to control their energy use as well as allow utility companies to better comprehend customer needs. • smart grid technologies clearly come at a high investment cost and fiscal cost especially to the developing nations which are inherently poorer. however it can also be argued that going for outdated infrastructure in trying to reduce costs may inherently cost a higher running cost, as well as a cost to upgrade. it can also be seen that the cost upgrading old infrastructure to smart systems is evidently higher as many components become redundant and new components are needed altogether, a position which puts developing countries at an advantage as the grid expansion projects and capital power projects can be planned with the smart grid in mind and thereby working efficiently to make the design of the new grid less capital intensive to a point of affordability. references [1] l. lo schiavo. smart metering and smart grids: the italian regulatory experience. [2] presented at the kasct smart grid workshop 2011. riyadh, saudi arabia 2011 [3] bazilian, m. and welsch, m. et. al (2011), smart and just grids: opportunities for subsaharan africa, imperial college london, london. [4] iea (2010), energy technology perspectives 2010, oecd/iea, paris. [5] boots, m., thielens, d., verheij, f. (2010), international example developments in smart grids possibilities for application in the netherlands (confidential report for the dutch government), kema nederland b.v., arnhem. [6] s. kalogirou, k. metaxiotis, and a. mellit. "artificial intelligence techniques for modern energy applications". intelligent information systems and knowledge management for energy: applications for decision support, usage, and environmental protection. igi global, 2010, pp. 1-39. [7] smart grid projects in europe: lessons learned and current developments, jrc reference report. 2011: european union eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e3 tatenda kanyowa , rindai p. mahoso 8 [8] the future of the electric grid, an interdisciplinary mit study. 2011; massachusetts institute of technology 978-09828008-6-7 [9] p.s fox-penner. smart power: climate change, the smart grid and the future of electric utilities. 2010; island press: washington, dc [10] j. cardenas, a. garcia, j. l. romeral, and j. urresty, "a multi-objective ga to demand-side management in an automated warehouse," in etfa2009, the ieee 2009 conference on emerging technologies and factory. [11] c. clasters. smart grids: another step towards competition, energy security and climate change objectives. energy policy 39 2011; 5399-5408 [12] h. slootweg. smart grids. the future or fantasy? smart meteringmake it happen, 2009 iet. 2009; 1-19. [13] r. harley, j. liang. "computational intelligence in smart grids."ieee symposium series on computational intelligence (ssci) 2011 ciasg, april 11-15, 2011. [14] s.d.j. mcarthur, e. m. davidson, v.m. catterson, a.l. dimeas, n.d. hatziargyriou, f. ponci, t. funabashi. "multi-agent systems for power engineering applications — part ii: technologies, standards, and tools for building multi-agent systems". ieee transactions on power systems, vol. 22, no. 4, pp. 1753-1759, nov. 2007. [15] p. mcdaniel, s mclaughlin. security and privacy challenges in the smart grid. security& privacy, iee. 7 (may-june 3): 200ppp9; 75-77 [16] national institute of standards and technology (nist). nistir 7176: system protection profile industrial control systems. decisive analytics. 2014. eai endorsed transactions on smart cities 04 2021 08 2021 | volume 5 | issue 15 | e3 a systematic review of blockchain-based services for security upgradation of a smart city eai endorsed transactions on smart cities review article 1 a systematic review of blockchain-based services for security upgradation of a smart city noushaba feroz1,* 1department of computer science and engineering, sest, jamia hamdard university, new delhi india. abstract the concept of smart city has gained popularity in recent years. the elementary concept refers to promoting the uninterrupted sharing of data and services within and across communities by the application of emerging technologies. smart cities strive for cost reduction, optimal use of resources and the development of a more sustainable environment. considerable advances in modern technologies such as iot and wireless communication have enabled sharing of data between remote devices which are geared with open data, hence a smart city is susceptible to a number of security threats. it is important to identify these threats, analyze iot data to improve privacy and security and identify the corresponding consequences. blockchain has emerged as a promising solution to resolve these challenges. blockchain is a peer-to-peer shared database technology that cannot be modified once a transaction is recorded and validated. this study explores the contribution of blockchain to smart cities in terms of decentralized security, immutability, transparency and privacy to provide intelligent, customized and context-aware services to smart city dwellers. a brief overview of this novel technology has been given along with its deployment in a smart city setting, the open issues discussed and prospective scope of blockchain application has been presented. keywords: smart city, blockchain, iot, decentralization, security. received on 29 january 2020, accepted on 22 march 2020, published on 24 march 2020 copyright © 2020 noushaba feroz et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.163840 *corresponding author. email:noushaba.feroz@gmail.com 1. introduction smart city is defined as an urbanized area with information and communication technology (ict) central to its framework. in order to enhance the quality of life, smart cities provide various novel and specialized services to their citizens. a smart city must include state-of-the-art technology, essentially the internet of things (iot), to offer these services in compliance with privacy and security (verma, a. et al., 2019). moreover, smart city policies have gained significant attention and support lately. it is apparent that these policies favor urban economic growth (caragliu and del bo, 2018). smart city literature highlights the need for a local context in which large-scale funding in cutting-edge technologies is fully exploited (caragliu et al., 2011). the notion of smart city has evolved significantly over the last decade with the emergence of the internet of things (iot) as a new trend in promoting sustainability. the world urbanization prospects report (united nations, 2018) reports that 55% of the global population resides in urban areas, a percentage that is expected to rise to 68% by 2050. moreover, it is estimated that by 2050, approximately 2.5 billion people will be additionally led to urban areas as a result of the steady transfer of people from rural to urban areas. the increasing congestion, carbon dioxide concentration, greenhouse gas emissions and waste disposal in the urban areas will gradually affect living conditions of the people. consequently, the consolidation of billions of devices and services under a smart framework is imperative in the near future, ranging from user devices to smart travel, business, buildings, hospitals, energy and ecosystem. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e1 http://creativecommons.org/licenses/by/3.0/ noushaba feroz 2 fig. 1. components of a smart city the prevailing technology revolution has prompted a number of cities around the globe to make huge investments in the design and implementation of smart city plans and proposals to address the critical challenges of rapid urbanization and climate change (sharifi, a., 2019). in the midst of global urbanization developments, local authorities are posed with pressing issues to satisfy swiftly advancing citizen requirements while tackling the crucial intricacies of world-wide sustainability (clarke,r., 2013; nist, 2018; stratigea et al., 2015). smart cities are built on an integrated, self-governing and distributed architecture that involves many sensors that capture and send data to base stations, and numerous internet-enabled devices that provide connectivity for the processing of data. every individual device produces significant data uninterruptedly to be sent to data centers for processing via heterogeneous networks and subjected to subsequent analysis for decision-making (albino, v. et al., 2015). data is, for any individual in the modern world, the most valuable asset. this data may include personal details such as credit card numbers, contact information, bank account details, location coordinates or medical reports including many others. these details are managed by hardware and software modules that might be susceptible to unauthorized access (popescul, d. and genete, l.d., 2016). the advanced technologies incorporated in smart cities must resolve the public concerns regarding privacy and security, especially regarding the data deemed as significantly sensitive (van zoonen, l., 2016). privacy and security is a paramount challenge with regard to technical issues, together with other concerns such as interoperability and technological expenses (naphade, m. et al., 2011). safeguarding data from malicious attacks, viruses, frauds and other vicious actions is a fundamental task of information security (ijaz, s. et al., 2016) and any adverse impact of information security greatly affects the society's economic aspects (anderson, r., 2001). a smart city is an instance of an infrastructure that facilitates people and organizations to collaborate, at any level, for public welfare. a robust approach of achieving this is to effectively decentralize any mechanism which can evade the control of a single and centralized administration without requiring any involved party to trust the other. gartner's study estimates the prevalence of 20 billion connected devices by the year 2020 (panetta, k., 2017). the massive amount of data generated by these devices would pose serious data management and security challenges. in case this saturation affects the central server or database, all the connected devices will be affected consequently. a fair and transparent data sharing environment may be set up by utilizing blockchain in which unauthorized data alterations can be monitored and traced. blockchain allows distributed storage of data and essentially autonomous peer-to-peer communication between iot devices. hence, fault in one device doesn’t impair the operation of the other devices. moreover, blockchain offers encrypted data management and access control in its deployment (fan, l. et al., 2018). blockchain, though originally developed to assist cryptocurrency, can be used without an intermediary in any kind of transaction. blockchain offers flexible access for maintaining anonymity by providing viable features such as the use of alias accounts (zyskind, g. and nathan, o., 2015). the advantage of blockchain is that an attacker must compromise 51% of the systems (51% attack) in order to surpass the target network's hashing power. therefore, attempting to target a blockchain network is computationally unrealistic (biswas, k. and muthukkumarasamy, v., 2016). smart city, with aggregate elements including but not limited to smart resource use, transportation, healthcare, governance and economy, is the most prospective domain for blockchain application. blockchain can be leveraged to provide realtime verification, permission, transparency, security and privacy that are not effective in smart city environment via a centralized system (kshetri, n. and voas, j., 2018). a smart city aims to create greater social value, as well as to support administrative performance, citizen flexibility and technological development by the application of novel technology and organizational methods. the blockchain system meets the basic requirements of a smart city as a distributed data storage and mutual communication framework (sun, m. and zhang, j., 2020). this manuscript is divided into five sections. section 2 presents a brief overview of the blockchain technology and its deployment in a smart city, section 3 discusses 15 recent works in this domain, section 4 depicts open issues in current blockchain implementations and section 5 discusses the prospective scope of this technology in a smart city setting. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e1 3 2. blockchain overview and smart city deployment a blockchain is characterized as a distributed ledger (database) that holds the transactional data indefinitely and immutably. the use of a peer-to-peer network renders a blockchain fully decentralized. more specifically, a duplicate of the ledger is maintained at every network node to prevent a single failure point. all the copies are modified and audited concurrently (hammi, m. t. et al., 2018). blockchain facilitates communication among nontrusting parties without the need for a trusted authority (christidis, k. and devetsikiotis, m., 2016) fig. 2. blockchain structure satoshi nakamoto, the anonymous individual/group behind the bitcoin cryptocurrency, stated nearly a decade ago that blockchain technology, a decentralized peer-topeer connected system, could be utilized to address the challenge of preserving transactional sequence and to prevent the double-spending issue (nakamoto, s., 2019). in bitcoin, transactions are ordered and those with the same timestamp are grouped together in structures of restricted size called blocks. network nodes (miners) link the blocks to each other in a temporal sequence, with each block holding the hash of the preceeding block for blockchain creation (crosby, m. et al., 2016). thus, a reliable and auditable database for all transactions is included in the blockchain architecture. as part of a security matrix, blockchain mechanisms (bcms), play a role in protecting multiple iot-based applications. blockchain architecture and design inherently offers advantages such as security, verifiability, robustness and transparency (greenspan, g., 2015; christidis, k. and devetsikiotis, m., 2016). blockchain technology has six elements at its core, viz. autonomy, decentalization, transparency, anonymity, immutability and open source access (niranjanamurthy, m. et al., 2019). blockchain has garnered significant attention due to its ability to facilitate relaible transactions through networked computation replacing human supervision and control (casino, f. et al., 2019). consequently, it has emerged recently as a new form of data and service organization, supporting the operations of diverse fields beyond its originally intended application area, such as finance, governance, iot, healthcare, business, education, energy and other miscellaneous domains. depending on the target audience, three generations of blockchains exist (zhao, j. l. et al., 2016): blockchain 1.0 (supporting digital cryptocurrency transactions), blockchain 2.0 (involving digital finance) and blockchain 3.0 (covering digital society such as government, health, science and iot). governments are responsible for maintaining and storing official records of citizens and/or organizations throughout years. blockchain-enabled technologies may alter how local or state governments function by eliminating the need of intermediataries for recordhandling (reijers, w. et al., 2016; hou, h., 2017). blockchain provides liable, autonomous, secure and transparent record-keeping that would ultimately inhibit corruption and increase the government performance. blockchain could serve as a secure framework for the physical, social and organizational incorporation into a smart city environment. the surmounting data generation rates are likely to rise with the emergence of iot and the ongoing population explosion (i. w.stats, 2019). although blockchain and iot already have vast application areas of their own, their intrinsic relationship gives birth to endless possibilities. the growing interest and funding for deploying decentralized iot systems (samaniego, m. and deters, r., 2016; zhang, y. and wen, j., 2017; novo, o., 2018) is largely driven by the development of blockchain and its innate abilities (christidis, k. and devetsikiotis, m., 2016) aiming to ensure secure and verifiable transactions. moreover, blockchain interoperability facilitates the improvement of conventional transportation and commerce by incorporating secure and autonomous real-time payment services (christidis, k. et al., 2016). 3. literature review sun, j. et al. (2016) have discussed how blockchain-based sharing services can contribute to smart cities based on a hypothetical structure. to understand the impact of evolving blockchain technology on the development of smart cities, the authors have suggested examination perspective to determine the fundamental components of smart cities. they have proposed a three-dimensional theoretical framework, comprising of human, technology and organization, based on available literature and discuss a number of core factors that make a city smart from a sharing economy viewpoint. the authors have used this a systematic review of blockchain-based services for security upgradation of a smart city eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e1 noushaba feroz 4 framework to examine the effect of blockchain on smart cities and aim to comprehend the meaning of ‘smart’ in the term ‘smart city’ from a sharing economy perspective to understand the needs of smart cities and how new technology might support them. biswas, k. and muthukkumarasamy, v. (2016) have introduced a fourlayer blockchain-based security arrangement that allows the institutions of a smart city to connect without risking privacy and security. they have classified smart city threats into five groups, viz. availability threats (unauthorized resource maintenance), integrity threats (unauthorized data modification), confidentiality threats (sensitive information disclosure), authenticity threats (unauthorized access to resource and sensitive information) and accountability threats (denial of transmission or reception) and propose a secure framework based on blockchain to address these threats in a smart city setting. the authors in (ibba, s. et al., 2017) have proposed a solution to the problem of storage and management of sensor data using blockchain technology. they have applied scrum methodology, characterized by flexibility, adaptability and iteratation, to develop the blockchain-based system “citysense”. the proposed system encorgages proactive collaboration of the people and creates the city's health map to acquire real time data and formulate real time remedies. the authors in (rivera, r. et al., 2017) have presented a comprehensive analysis to compile all the available research of digital identity on blockchain technology in a smart city setting. the findings of their study reveal that the use of blockchain for digital identity is at its initial stage of development. the authors have endorsed the forthcoming deployment of blockchain as a digital identity tool and for the verification of citizens in a multitude of digital services that are available currently. hammi, m.t. et al. (2018) have proposed a novel decentralized system “bubbles of trust” which guarantees robust identification and verification of devices. the system leverages the security benefits offered by public blockchains to protect data integrity and availability so that devices can communicate in a fully secure way. moreover, the authors have built a threat model that complies with the required safety parameters and is robust against threats. sharma, p.k. and park, j.h. (2018) have introduced a novel hybrid model “distblocknet” for smart city network that exploits the combined capabilities of innovative technologies of centralized software defined networking (sdn) and decentralized blockchain. the model guarantees privacy and security, and prohibits intruders from accessing data on a secure smart city network. the authors in (pieroni, a. et al., 2018) have presented a review of the smart environment aspect of a smart city setting, specifically the deployment of smart energy grid for smart city residents. they have proposed incorporating blockchain in the grid and using the blockchain granting ledger for information sharing and transactions between citizens and energy providers. the authors have also introduced a mobile application to facilitate access to the blockchain network. minoli, d. and occhiogrosso, b. (2018) have discussed several iot scenarios where blockchain mechanisms (bcms) are significant but also suggest that bcms are just component of the iot security (iotsec) solution. they have summarized and advocated the general use of bcms for security in iot with specific focus on e-health and intelligent transport systems (its). the authors have indicated that the application of a complete blockchain protected network in all iot applications is not realistic due to the general constraints of iot nodes. they have further asserted that bcms (firewalling, encryption etc.) must be paired with other security mechanisms for indepth protection. michelin, r.a. et al. (2018) have proposed a flexible and private data sharing infrastructure so that the massive amount of sensor data generated by smart vehicles could be leveraged to facilitate a broad range of services in a city. the authors have proposed a framework called “speedychain”, which utilizes blockchain technology to allow smart vehicles to exchange their information in a decentralized and secure manner, while preserving anonymity, essence and transparency. unlike traditional blockchain implementations, this novel architecture incorporates a blockchain mechanism to decouple the data stored in block header transactions so that data may be added to blocks swiftly. kushch, s. and prieto-castrillo, f. (2019) have discussed the deployment of blockchain technology as an iot component in sensor networks. the authors have introduced the notion of "rolling blockchain" intended for building wireless sensor networks together with smart cars and can be applied to iot and smart city sensor networks. citing the estonia blockchain service case, noh, j.h. and kwon, h.y. (2019) have advocated that the blockchain technology is more efficient than 4g technology with a super-low latency of 0.001 seconds, when applied to 5g-based smart city infrastructure. the authors have proposed the simplification of authentication process and the standardization of overall development platform to enhance user experience. furthermore, they have advocated for the establishment of a code of conduct and insurance policies to facilitate accountability of service providers for any damage due to compromised data. aggarwal, s. et al. (2019) have discussed the applications of blockchain technology in a smart city setting, with an emphasis on core blockchain components. a comprehensive application taxonomy, process models used and communication infrastructure support required to run different applications have been provided. additionally, the authors have identified various potential challenges and opportunities for research with focus on the need to develop a lightweight blockchain system, especially for constrained applications, and the assurance of interoperability across different blockchain frameworks. the authors in (khare, a., et al., 2019) have built and deployed decentralized distributed ledger technology (dlt) based technologies such as “bigchaindb” for sensing, collection, storage and use of data in the real-world smart city deployment, “#smartme”. they have proposed a trust-free strategy for the collection, storage and use of sensor data generated in eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e1 a systematic review of blockchain-based services for security upgradation of a smart city 5 a smart city to deal with the issues of completeness, availability and non-modifiability of accessible datasets produced by sensing operations. rahman, m.a. et al. (2019) have proposed a blockchain-based framework to facilitate secure and confidential spatial-temporal smart contract services that support a sustainable iot in smart cities. the proposed infrastructure is a sharing economy system based on mobile edge computing (mec) that uses blockchain and off-chain structure to store unmodifiable data, allowing protected smart city infrastructure, including sharing economy, smart contracts, iot and blockchain connectivity, to be enabled. sun, m. and zhang, j. (2020) have conducted a survey of the function of smart big data platform and have analyzed the development of the smart city of hefei. the authors have suggested the use of blockchain technology to build a decentralized peer-to-peer security network combined with the current public key infrastructure/certification authority (pki / ca) security system to develop a novel model. based on this model, the authors have designed the architecture of blockchain smart city for information sharing and communication. table 1. summarizes the proposals/findings of the papers discussed above. table 1. proposals/findings of literature review s.no. author (year) proposals/findings 1. sun, j. et al. (2016) three-dimensional theoretical framework (human, technology and organization) to examine the effect of blockchain on smart cities from a sharing economy perspective. 2. biswas, k. and muthukkumarasamy, v. (2016) four-layer (physical, communication, database, interface) blockchain-based security arrangement. five groups of threats classified (availability, integrity, confidentiality, authenticity, accountability). 3. ibba, s. et al. (2017) blockchain-based system “citysense” developed on scrum methodology 4. rivera, r. et al. (2017) deployment of blockchain as a digital identity tool for the verification of citizens in a multitude of digital services. 5. hammi, m.t. et al. (2018) decentralized system namely “bubbles of trust” for robust identification and verification of devices. threat model complying with required safety parameters and robust against threats. 6. sharma, p.k. and park, j.h. (2018) hybrid model namely “distblocknet” for smart city network based on centralized software defined networking (sdn) and decentralized blockchain. 7. pieroni, a. et al. (2018) incorporation of blockchain in smart energy grid and mobile application to facilitate access to the blockchain network. 8. minoli, d. and occhiogrosso, b. (2018) blockchain mechanisms (bcms) for security in iot with specific focus on ehealth and intelligent transport systems (its). 9. michelin, r.a. et al. (2018) framework called “speedychain”, utilizing blockchain technology to allow smart vehicles to exchange their information in a decentralized and secure manner. 10. kushch, s. and prieto-castrillo, f. (2019) concept of “rolling blockchain" for building wireless sensor networks together with smart cars applied to iot and smart city sensor networks. 11. noh, j.h. and kwon, h.y. (2019) simplification of authentication process and the standardization of overall development platform to enhance user experience. 12. aggarwal, s. et al. (2019) blockchain application taxonomy, process models and communication infrastructure support to run different applications in smart city. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e1 noushaba feroz 6 13. khare, a., et al. (2019) decentralized distributed ledger technology (dlt) based technologies such as “bigchaindb” for sensing, collection, storage and use of data in the real-world smart city deployment, “#smartme”. 14. rahman, m.a. et al. (2019) blockchain-based framework for secure and confidential spatial-temporal smart contract services. 15. sun, m. and zhang, j. (2020) blockchain-based decentralized peer-topeer security network combined with public key infrastructure/ certification authority (pki / ca) security system. 4. open issues in current blockchain implementations there are at least three major hurdles to blockchain deployment in a smart city setting which are prevalent in all implementations and have not been addressed effectively yet, viz. scalability, privacy and interoperability (tapas, n. et al., 2018). although a number of it experts contemplate the use of blockchain in almost all ventures, they do not fully understand the key reasons for its use, especially in terms of data management. as an example, blockchain will not add any value to current technical solutions if no data has to be stored at all. likewise, when only one writer is required in a given system, blockchain is not a guaranteed better option compared to traditional database from the perspective of efficiency (greenspan, g., 2015). it is important to examine the appropriateness of blockchain technology against the application specifications before implementing blockchain-enabled solutions (lo, s.k. et al., 2017). the wastage of mining network resources is one of the key drawbacks of blockchain technology, which particularly affects public blockchains. china-led bitcoin mining (blockchain hashrate distribution, 2020) uses more energy than 159 countries worldwide (digiconomist, 2020). nonetheless, actual power usage may be far worse as users might be mining unknowingly owing to malware infections (malwarebytes, 2017). there is a rapid increase in blockchain-based implementations, producing an enormous amount of heterogeneous solutions. the wide array of functionalities and deployments implies interoperability challenges that prevent standardization (casino, f. et al., 2019). data protection and confidentiality is still a concern for blockchains, since data is stored as a public archive. transactional privacy is a prominent blockchain issue (rahman, m.a. et al., 2017). the traceability of transactions and smart city processes distributed across the network worries both individuals and businesses. additionally, the use of aliases does not necessarily ensure transactional data to be secure (kosba et al. 2016). while blockchains preserve confidentiality and privacy, asset safety depends on the security of a digital identity, the private key. no third party can retrieve a private key if it is compromised or lost. therefore, it is almost impossible to identify the perpetrator and all the assets that a person owns in the blockchain will disappear (xu, j.j., 2016). furthermore, decisions stored on a blockchain cannot be reversed and there is the threat of an impending majority attack (51% attack) (zhu, l. 2019). 5. conclusion and future scope ensuing technological advances envisage a superconnected world. in this anticipated super-connected setting, the technologies that can most securely and effectively implement an exponential growth of big data for a service are required. to this end, blockchain is a viable option. innovative technologies such as cloud computing, big data, iot, edge computing artificial intelligence, machine learning, together with urban planning, construction, maintenance and functioning are integral elements of a smart city. this demands a framework of innovation, collaboration, sustenance, transparency and security to promote healthy urban development. with vital characteristics including security, immutability, transparency and decentralization, blockchain has emerged as a promising candidate for consideration in a smart city environment. it will ultimately promote the sustainable and healthy growth of smart cities. future research should, among other things, focus on identifying which smart city applications are best suited to implement blockchain safety mechanisms on a practical level. furthermore, researchers need to explore how to deploy a revocation mechanism for compromised smart devices. references [1] aggarwal, s., chaudhary, r., aujla, g.s., kumar, n., choo, k.k.r. and zomaya, a.y., 2019. blockchain for smart communities: applications, challenges and opportunities. journal of network and computer applications. 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[55] zyskind, g. and nathan, o., 2015, may. decentralizing privacy: using blockchain to protect personal data. in 2015 ieee security and privacy workshops (pp. 180-184). ieee. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e1 1 a comprehensive study on highly sensitive photonics based acoustic sensors for under water applications hareesh kumar1,* and m. n sreerangaraju2 1 research scholar, vtu-belagavi , bit research centre, dept. of ece, bangalore institute of technology, bengaluru 560004, india 2 professor, dept. of ece, bangalore institute of technology, bengaluru 560004, india abstract by referring few researcher works which is related to the work of optical sensor and able to detect the acoustic signal, this review paper provides the detailed study of acoustic signal in under water. researchers has worked with the optical sensor and emerged as great promising sensing device. from various research papers it is observed that the detection of acoustic signal is done with the help of various optical sensors. the various sensors are fiber bragg grating (fbg) sensor, fiber optic interferometric sensor and mach zehnder interferometer (mzi) sensor. so this review paper covers all these sensors and their application with a particular focus on the different structure of optical sensor. the structure of the various sensors and their application is discussed from the different research paper. the overall work is reported and corresponding result is demonstrated. from the demonstrated work it has been observed that with good quality and proper sensitivity in all optical sensors are able to detect the acoustic signal for under water due to their compact size and able to provide accurate results. keywords: optical fiber acoustic sensing, mach zehnder interferometer, fiber optic interferometric sensor, piezo electric sensor, fiber bragg grating (fbg) sensor, photonic crystal fiber (pcf) received on 10 march 2020, accepted on 25 may 2020, published on 10 june 2020 copyright © 2020 hareesh kumar et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.165235 *corresponding author. email:hareevlsi@gmail.com 1. introduction the ofas (optical fiber acoustic sensing) system is popular to monitor the acoustic wave which is generated by the external sources. acoustic wave is kind of mechanical wave which is very important to carrying the information. with different frequency band the detected acoustic wave can be applicable for various fields such as ultrasonic medicine, underwater acoustic monitoring and aerospace. since few decades the development in acoustic sensing domain, this optical sensing devices has been observed and provides the detailed information. the advantage of this optical sensor is anti-electromagnetic interference and less loss for long distance transmission. due to their high sensitivity, compact size, these sensors are applied in different field of applications. eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e6 http://creativecommons.org/licenses/by/3.0/ hareesh kumar and m. n sreerangaraju 2 another most important and popular sensor is mach zehnder interferometer. it was demonstrated as temperature sensor and pressure sensor. the mechanism of this mach zehnder interferometer is that it uses laser source as source. this light beam will be decoupled by the two arms and recoupled at the receiver end. because of its high sensitivity mzi can be used as acoustic sensor. when sensing arm of mzi is conveying the acoustic signal and include a change in optical path and then introducing phase shift at receiver end. ian f. akyildiz et.al has worked with sensors which has potential to unexplored application and to enhance ability to observe and predict the ocean. so authors worked with sensors, which are related to network and gathered information about under water environment. in this paper they worked with underwater acoustic sensors which constitute a basis from shengye huang discussion of the challenges associated with the underwater environment. tao fu et.al, they worked with different sensor such as two dimensional sensor networks, three dimensional sensor network.[1]. problem can be observed from this paper in approaching of different network layer under water is difficult. geoffrey a et. al. focused on work of detection of acoustic signal under water using fiber-optic interferometric sensors. this sensor is electro ceramic transducers. xiaohong bai et.al, the authors discussed about this sensor array. work has been done by a hydrophones installed named as the fiber-optic bottom mounted array, which is large and time division multiplexed architecture. in military sonar and seismic survey system this sensor can be used [2]. the designed hydrophone is used to get consistent with the good acoustic resolution but it should be specified depth. there should be proper frequency response with the operating frequency range of interest. the mechanical properties of the materials and the geometry of the design factors which can influence the above design matter. the design of hydrophone is very important and design should be such that mechanical properties of the material frequency are higher than operating frequency. so choosing of material is crucial part to demonstrate this kind sensor. so another approach can be proposed to detect the acoustic signal in under water are photonic crystal sensor, fiber bragg grating sensor or mach zehnder interferometer can be proposed for the experiment. shengye huang. et. al [3] worked with optical fiber hydrophone which responds with temperature compensation package and able to provide improved sensitivity with a frequency from 2.5 khz to 12 khz. this acoustic sensor is one kind of transducer which is able to convert pressure into elastic vibration as shown in resultant output. graham wild et. al. has done experiment with fiber bragg grating (fbg) sensors to detect the acoustic signal. there are numerous advantages of fbg sensor so it can be useful for detecting of acoustic signal in under water. authors observed the advantages of fbg and have done experiment on fbg sensor. the merits of fbg as sensing elements, which can be either, stress or temperature. in this work we also showcase recent outputs. optical fiber grating have been immerged in optical platform to detect chemical and bio chemical elements as sensor. by inducing this interaction in the transmission spectrum along the fibers so there will be change in the measurement of refractive index. there will be combination of optical fibers, based on this approach the optical fiber gratings are considered because of its advantages and limitations [5]. figure 1. basic configuration of optical fiber gratings a) standard fbg b) standard long period grating c) tilted fbg d) etched fbg another way to approach the fbg sensor is to detect the dna sequence. fbg is inscribed and the inner surface of a microstructure fiber has been functionalized by covalent linking of a peptide nuclei acid probe targeting a dna sequence bearing a single point mutation implication in crystal fibrosis disease. the essential part of new, fast and lowest price technology for healthcare, medical platform and detection of any chemical and organic, inorganic substances. sensor which is used to detect of bimolecular in an aqueous solution. many researchers have put effort to implement a sensor for bio-applications. fluorophorelabeled dna is inserted in the air holes of the microstructure part of a pcf. in the presence of the target eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e6 a comprehensive study on highly sensitive photonics based acoustic sensors for under water applications 3 bimolecular, the transmission peak located in the fluorophore revealed [5]. for a many applications in various areas optical fiber gratings have developed including physical sensing for temperature, strain, acoustic waves and pressure. the fiber bragg grating is etched as the sensing element by a narrow bandwidth [6].optical refract metric type biosensor (ortb) based on the fbg to determine the octane number of gasoline. for a number of sensing applications, fiber grating sensors are of significant. but this fiber bragg grating (fbg) sensor can used to detect acoustic signal in under water. hill et al. in 1978 demonstrated the optical fiber bragg grating (fbg)[9]. meltz et al developed this method which is called as transverse holographic fabrication method. after that, fbg has become very much popular. there is a very important advantage of optical fiber sensors compare to other sensors that is small in size, good quality sensitivity and immunity to emi. the advantage of this fbg is sensitive to a number of measured while being multiplexed. by discussing about application of fbg acoustic sensor, many researchers worked on the fbg and represent the detection. kavya v. ullal, et al. in this paper authors explores the movement of the micro optical elements, which manipulates the light passes through all the dimensional spaces for micro opted-electro mechanical systems (moems). these are used to detect stress, strain and other mechanical parameters based on the displacement using photonic crystal sensors for detection of acoustic signals[8]. t. zouache et al, in this work the two-dimensional photonic crystal waveguide coupled to a point-defect resonant micro cavity. the resonant wavelength will shift when pressure variation induces change in the refractive indexes of the structure and these sensors have compactness, high sensitivity, and various choices of materials[28]. 2. review of literature table 1. comparison of different types of optical sensors classifi cation advant ages disadvanta ges challeng es applicati ons signal proces sing metho d rejectin g noise and interfere nce, improve s snr it will reduce computation al requirement, restrict the frequency band shifting and isolates the signal frequenc y band to be centered at zero frequenc it is used for exploiting of all the known characteris tics of the signal like dimension of time, y frequency and space highly sensiti vity therma lly stable acousti c fiber sensor high sensitivi ty bandwidth relaxes the constraint on sensors operating wavelength light incident on the photonic crystal cannot propagat e at normal angle it is used to get maximum reflectivity around the target wavelengt h of operation( 1550 nm) optical refract metric type biosen sor high accurac y and high resolutio n can be achieve d sensing is inefficient in ability to provide quick feedback different method of frequency modulatio ns of higher frequencie s and microwave ranges match zehnde r interfer ometer high sensitivi ty it works only for the laser light . the light beam will be decouple d by the two arms and recouple d at the receiver end it can be used as temperatu re and pressure sensor optical fiber acousti c sensin g (ofas) anti electro magneti c interfere nce and less loss for long distance transmis sion efficiency is less with different frequenc y band the detected acoustic wave can be applicabl e for various field due to there high sensitivity compact size these sensor are used in different field application piezo electric sensor (pzt) small size, light weight piezo electric sensor is not suitable for use with in a polymer bonded explosive material, it can generate heat are spark or shot circuit during operation it is only commerc ially available acoustic emission sensor, which is driven by electricity it can be used in acoustic sensor fiber bragg grating sensor improve d sensitivi ty, by inducing chemical and biochemical it is complex to develop it is used for detection of acoustic eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e6 hareesh kumar and m. n sreerangaraju 4 efficienc y. light weight, compact size,hig h sensitivi ty. large bandwid th. interaction in the transmission spectrum along the fiber, so there will be change in the measureme nt of refractive index. it is very expensive. detection systems is difficult. usable measure ment systems using fiber optic sensors signals in particular ultrasound . it is used in optical platform to detect chemical and biochemic al elements as sensor. it is used in underwate r communic ation underwat er navigation and tracking. weather and climate observatio n structured health monitoring 3. fundamental theory of fiber bragg grating a fbg which is a spectrally reflective element and consist of core of an optical fiber. the fbg is consisting of various refractive indices with alternating regions. the difference in refractive indices and as results in fresnel reflection at each interface which is named as the bragg wavelength, λb. the wavelength of bragg is , where the effective refractive index of the grating in the fiber core is and is the grating period. strain is applied for measuring the acoustic and ultrasonic signal. if there is change in grating period which means strain is applied and change in refractive index then resultant effect is on strain optic sensor. figure 2. basic principle operation of fiber bragg grating the alternative method is to detect the acoustic signal using fiber optic sensor, because this kind of sensors is extremely sensitive. their size is small and it as oil-well monitoring where space is constraint [9]. for measuring sound in water a hydrophone is simply a device [10-11]. a fiber hydrophone is an acoustic sensor used for sensing the element. 4. fiber bragg grating acoustic emission this sensor is used in various fields. the sensing principle is co-ordination between the ae wave and the sensor is introduced based on an fbg ae sensor. for fbg sensor, on the surface of the sensor, a thin polymer bonded explosive material is used. in order to improve the accuracy of the sensor the time coefficient location method is proposed. there are different applications which come underwater such as oil exploration, underwater pollution examination, and so on. in order to work on the application such as under water wireless sensor grids are involved in such case [12]. sub aquatic sensor involved to provide sensitization. but there will be problem with wireless sensor network application for sensing. so fbg can diploid for this research work. much other work is carried out for sensing research work [13]. eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e6 5 figure 3. experimental setup for photo acoustic tomography with mach zehnder interferometer as acoustic line detector. researcher’s works on another approach to detect the acoustic signal and the method is three-dimensional photo acoustic imaging method. this method uses a mzi sensor for calculation of acoustic waves generated in an object. with short laser pulses. fig 3 shows that basic working principle of interferometric [27]. researcher worked on that interferometer and explained the working principle in detail. figure 4. fiber optical interferometer setup to detect the acoustic signal considering conventional solid core fiber and hollow core photonic crystal fiber (hcpcf), higher sensitivity was reported. another way to utilize the fiber bragg grating sensor is to detect the octane number of gasoline and the presence of organic compounds in biological fuels. fiber bragg grating sensor is using π shifted etched. the π phase shifted fbgs which as narrow resonance bandwidth dimensions with the size of a grating and a good sensitivity to changes in the refractive index [14]. so this fbg with π shifted is used as fuel detection sensor. figure 5. π shifted fiber bragg grating figure 6. the special characteristic of π shifted of fbg 5. interferometric ultrasound detector the above fig. 3. shows the experimental setup of the mzi the continuous laser beam is separated into signal beam and reference beam is incident on an arm of a mzi sensor. object is placed near to the signal beam and both beams travers a water tank. to improve the temporal resolution of the sensor, the diameter of the beam near the object is reduced. the output of the differential amplifier as a function of path length difference is a sine wave [15]. in order to monitor low frequency underwater acoustic signal, the pcf based acoustic sensor was reported by dnyandeo et al. [16]. a comprehensive study on highly sensitive photonics based acoustic sensors for under water applications eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e6 hareesh kumar and m. n sreerangaraju 6 figure 7. cross sectional diagram of pcf fiber 5.1. fbg construction: the construction of fbgs which is able to reflects required wavelengths of light and transmits remaining all others. it depends on bragg condition which means the bragg reflected wavelength changes depends on pressure, temperature, strain etc. this physical parameter changes refractive index which in turn affect the reflected wavelength [17-19]. 5.2. pcf-fbg sensor: it is constructed on to the core of the photonic crystal fiber. this sensor has a fiber optic sensor system which is capable of distinguish the effects of physical parameters [22]. the improved sensor system as power, energy scaling and discrimination of cross-sensitivities with good snr [20, 21]. figure 8. pcf fbg sensor there are many advantages for fbg sensor and this sensor is applicable in numerous fields. based on its advantages and good characteristic fbg sensor can be applicable for detection of acoustic signal. 6. temperature sensing fiber bragg grating can be used as temperature sensor. by changing the temperature of the fiber which can produce a shift in the bragg wavelength due to thermal expansion and that can change the grating spacing. if there is change in temperature resultant change in index of refraction. for temperature change the fractional bragg wavelength will be changed [23,24]. the detection of acoustic signal is difficult and very crucial for marine fields. by demonstrating mzi hydrophone using polarization maintaining pcf, operated at 1550 nm source with these data will be compared. figure 9. a) low frequency detection sensor set up b) mach zehnder interferrometer schematic c) smf(single mode fiber ) and hc pcf(holo core photonic bandgap fiber) spliced region. eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e6 7 figure 10. acoustic frequency response the market of optical sensor is growing very fast and essential. the number of advantages is required for fiber optic technology which is compared with conventional piezoelectric hydrophone techniques [25,26]. 7. merits and demerits merits • fiber optic sensor does not have any disturbance from emi (electromagnetic interference) and rfi (radio frequency interference). • it is safe and suitable to be used in extreme vibration and harse environments. • it is tolerant against high temperature (i.e. >1450oc) and corrosive environments. • it offers good sensitivity • it is less weight and small in size. • it offers wide dynamic range and large bandwidth. • it offers multiplexing and remote sensing capabilities. • it can be used in multifunctional sensing capabilities for mechanical measurement, electric measurements, magnetic measurements, chemical & biological sensing. • it can measure nearly all of the physical measurands. demerits • it is very expensive. • detection system is difficult. • it is complex to develop usable measurement systems using fiber optic sensors 8. conclusion the review paper demonstrated the reported work and corresponding results. observation is done with characteristic of fiber bragg grating sensor with good sensitivity. fbg sensor is applied in different field. the structure and properties of this sensor is described in detail. the knowledge about structure and working principle of fbg sensor and broaden their idea about this sensor and can provide new solution for further exploit the potential of fbg sensor. the technology of fbg and mach zehnder based sensor will be controllability and integration and the exploration on new mechanism and new method. acknowledgement. the authors wish to thanks to the anonymous authors for their valuable comments. authors wish to thank dr. preeta sharan, r&d head, department of ece, oxford college of engineering, bangalore for her constant support and timely guidance. references [1] tao fu et.al. “application of fiber bragg grating acoustic emission sensors in thin polymer-bonded explosives”, 13 october 2018; accepted: 31 october 2018; published: 5 november 2018, www.mdpi.com/journal/sensors. [2] xiaohong bai et.al. “a submerged optical fiber ultrasonic sensor using matched fiber bragg gratings”, received: 13 october 2018; accepted: 31 october 2018; published: 5 november 2018 www.mdpi.com/journal/sensors. [3] shengye huang1, xiaofeng jin1, jun zhang2, yi chen2, yuebin wang2, zhijun zhou1, and juan ni1, “an optical fiber hydrophone using equivalent phase shift fiber bragg grating for underwater acoustic measurement” 1department of information science & electronic engineering, zhejiang university, hangzhou, 310027, china 2hangzhou applied acoustics research institute, hangzhou, 310014, china photonic sensors (2011) vol. 1, no. 3: 289–294 received: 27 october 2010 / revised version: 5 december 2010. [4] jincy johny, thomas smith, kaushalkumar bhavsar, radhakrishna prabhu, “design of optical fiber based highly sensitive acoustic sensor for underwater applications”, 978-1-5090-5278-3/17/$31.00 ©2017 ieee. 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[21] s.m. murphy, p.c. hines, examining the robustness of automated aural classification of active sonar echoes. j. acoust. soc. am. 135(2), 626–636 (2014). [22] j o. gaudron et al., “long period grating-based optical fiber sensor for the underwater detection of acoustic wavesj”, received in revised form 16 july 2013 sensors and actuators a: physical jo ur nal homepage: www.elsevier.com/locate/sna. [23] geoffrey a et.al., “large-scale remotely interrogated arrays of fiber-optic interferometric sensors for underwater acoustic applications”, ieee sensors journal, vol. 3, no. 1, february 2003 1530-437x/03$17.00 © 2003 ieee. [24] muller-karger, f.e.; hestir, e.; ade, c.; turpie, k.; roberts, d.a., “satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems” ecol. appl. 2018, 28, 749–760. [crossref] [pubmed]. [25] yamashita, k.; nishiumi, t.; arai, k.; tanaka, h.; noda,m, “ intrinsic stress control of sol-gel derived pzt films for buckled diaphragm structures of highly sensitive ultrasonic microsensors”, eurosensors 2015, 120, 1205– 1208. [26] meng, l.; yi, j.; tan, x.; cai, l. study on phase shifted fiber bragg grating spatial sensing properties to ultrasonic wave at arbitrary excitation angle. ieice electron. express 2017, 14. [27] guenther paltauf et.al. photoacoustic tomography using a mach–zehnder interferometer as an acoustic line detector”, received 22 may 2006; revised 14 december 2006; accepted 2 january 2007; posted 2 february 2007 (doc. id 71188); published 15 may 2007, ocis codes: 110.5120, 110.6960, 3352 applied optics _ vol. 46, no. 16 _ 1 june 2007 [28] t.zouache,a. hocini, a.harhouz, r.mokhtari,” design of pressure sensor based on two dimensional photonic crystal”,acta physica polonica a, no1, vol 131, pp68-70, 2017. eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e6 http://www.elsevier.com/locate/sna food supply chain management using blockchain in food traceability the objective of the project is to avoid the food adulteration in public society. people want awareness on food chain management. the blockchain is used to trace the food items can be identified by the packet backside is packing date, expiry date, packing place, ingredients are added etc like that each and every things can identified. a detailed network security of blockchain analysis is performance of the investigation to capture the vulnerability of tamper proof of the digital database in proposed architecture under different types of attacks called hackers. the organisation as decided that to create the food safety on the public society. the company will collect the product from farmer then the manufacturer will produce the product then the distributer will buy the product from manufacturer. the consumer will buy the product from distributer through the online transaction with the help of blockchain. scanning the qr code will get the details of the food product. nowadays people are suffering from the food borne illness. to avoid the food borne illness we are tracing the food in many items starting from the farmer to the consumer. to trace the food items are updating in the blockchain. food supply chain management using blockchain in food traceability d.lekha1,*, s.chakaravarthi2, p.visu3 1p.g student, department of cse, velammal engineering college, surapet, chennai, lekha.doss9327@gmail.com 2professor & head, department of cse, velammal engineering college, surapet, chennai, chakra2603@gmail.com 3professor, department of cse, velammal engineering college, surapet, chennai, pandu.visu@gmail.com abstract keywords: food supply chain, block chain, food traceability, database, mobile phone. received on 22 april 2020, accepted on 30 january 2021, published on 30 june 2021 copyright © 2021 d.lekha et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.30-6-2021.170253 1. introduction food is a vital role in our life. many of us are working hard for the food in day today life. for avoid the food adulteration to create the transparent food supply chain management using the blockchain concept. to trace the food starting from the farmer producing the product till the consumer will collect product in between the transaction the product. all aspect of food product is cultivating from one place and is exporting from one place of local station to another place remote station. from exporting it is then shifted to local station to manufacturer company. while tracing the food we can see product details like packing date, expiry date, and ingredients are added, flavor added, sugar added checking the product through the online transaction. when the mobile is start for scanning the product will display in the screen. to transfer the food details in the blockchain should be very confidential in the network transaction. by collecting the food details will updated in the blockchain system. where the possibility to improve the interactions between human and machines may generate unprecedented technical and economical opportunities. eai endorsed transactions on smart cities research article 1 eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e6 mailto:lekha.doss9327@gmail.com mailto:chakra2603@gmail.com mailto:pandu.visu@gmail.com mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ fig. 1. food supply chain management fig:1. gathering information about environments and processes will increase the capabilities to control complex systems and to predict events, thus optimizing the production, the security, and the overall efficiency of the food system. 2. existing work in existing system, the food packages does not contains the proper details like food ingredients, packers details, package date and expiry date etc.. so, the end user or customer does not have any awareness of that product details. that product have product id and shop information only. real-time food products are monitoring the food quality and visibility of that quality check index will prevent the outbreak of the food-borne diseases, economically the healthy way of producing and motivated food adulteration, food contamination, food wastage due to the total misconception of the labeled expiry dates, and losses due to spoilage, which have created the broad impacts on the whole food products security. 3. proposed work producing the food products are well sophisticated in the surrounding. in behalf of the rfid to improve the complete healthy and safety food product to prevent the wastage, kit based technologies are required to monitor the food product quality and increase the visibility of food product level to be in monitored data. sensing techniques are high level compatibility in the food product with existing tracking system and tracing system infrastructure are currently proposed for monitoring healthy food products. these sensors can be invasive or non-invasive in monitoring the physical or chemical properties of food such as ph, conductivity, and permittivity or the packaging environment such as temperature, humidity, moisture or aroma. in general, these sensors are aimed to prevent defective products from reaching the consumers. we should add the all details in blockchain. all details like food product buying place and date, product ingredients, buying date, expiry date, product packaging date etc. blockchain technology was proposed recently to improve the quality level of traceability in the food product. and most important we should use qr code scanner wireless sensor for scan the product and create sensorid. each food product with an barcode travels through many stages of transactions at different terminals starting from packaging through transportation, storage and finally to a consumer for purchasing the product. a datadase in blockchain is updated the information about the food package at each and every valid network transaction. once the transaction is verified, the transaction of the sensorid is converted into a block of information and appended to its pre-existing data blocks thus forming a chain of information blocks and thus a blockchain. 4. overview of the description in tracing starting from the supplier for each product it contains the barcode number and its number will be passing through food api then ingredients will be taken out by using barcode number. first registration. the registration form contains supplier details. then login. supplier sells the products to all manufactures what they produce. the manufacturer initially creates the account. they will analyze the raw food product with the kilograms and the manufacturer will request the quantity of raw food product to the supplier. the manufacture will send the food product details like in the packet backside that is product id, expiry date, number of packets, etc to the block chain and then the ready product will be added to manufacturer shipment cart to trace the packet[1]. from the block chain the supplier and manufacturer will get the product details. then the distributor first registration. the registration part contains distributer details. and login. the distributor will search the product in the manufacturer shipment cart and then buying product with the help of request and response the distributor will be added to the block chain. at last the consumer first registration. the registration form contains user details. in addition to the food supply chain management produce the details in the block chain. it based technologies are required to monitor the food quality and increase the visibility level of the monitored data fig:2. its number will be passing through food api then ingredients will be taken out by using barcode number. block chain technology was proposed to improve the traceability of a food product. by connecting through the network topologies. to monitoring the food product from the supplier to the customer keep on checking the product to observe the quick transaction of the food supply chain product. d.lekha, s.chakaravarthi, p.visu 2 eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e6 fig. 2. tracing the food level the consumer scan the barcode with the help of mobile camera and then view the product in the mobile such as manufacturing date, packing date etc [2] and [3]. the consumer will check the product and they will buy the product by using online transaction. 4.1 concept of blockchain blockchain is concept of ledger. it has only to view the blockchain the hackers will not overwrite in the blockchain. the part of the product is to run in the blockchain only with the help of java intendedfig:3. to open the blockchain first it will run at the back side of the blockchain home page then tomcat software will open it at the another side of the page. in that the tomcat as manager apps in that open the food supply chain management. if we type the worng url the blockchain will not open and update. blockchain technology was proposed to improve the traceability of a food product. these sensors can be invasive or non-invasive in monitoring the physical or chemical properties of food such as ph level, temperature, water level, conductivity, and permittivity or the packaging environment such as temperature, humidity, moisture or aroma in encryt format. fig. 3. blockchain jar file the blockchain home page is open in that there will be many option. first one is admin and then sign up and then login like that these option will display on the top right corner of the home page. 4.2 admin account first admin as login the page with help of username and password. the username is admin and the password is also admin to open the admin account. in that admin will have some product to prepare like lays, oreo biscuit, noodles, etc like that many product will display in the screen fig:4. only the foreign product will capable or prepare the products in blockchain. indians products like shakthi masala, achi masala these kinds of products are not allowed because the blockchain is not invented in india. by seeing this admin block what are the products are asked to prepare the supply and manufacturer will ready to prepare the products[4]. in database what are the products for lays needed, what are the products for oreo biscuit needed like that many product are updated in the database. not only one farmer many farmer like potato farmer, salt farmer, vegetable oil farmer, chilli powder, etc like that many ingredients are needed for the lays product. these product will add the what are the product needed it will shown below by this supplier will start cultivating the raw materials. these raw materials will update in the blockchain by seeing this manufacturer company will collect the raw materials from them to prepare the food product [5]. this admin will only ask to do the product food product in the online shoppers and online customers buyers in the network system. food supply chain management using blockchain in food traceability 3 eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e6 fig. 4. admin page by default all the suppliers should follow the blockchain concept and they supplying the product. where ever you buy the product need the product details to update that product in each and every time in everywhere places. 5. registration for the supplier account in registration process first the username, email id, place, phone number, what product that you are having, how many kilograms that you have, what is price of the quantity, picture of the product like this details will be registered in the supplier account. once complete the registration process like already registered it will open a page called supplier login page. in that username and password have to mentioned then click login. supplier page will open it will have a all product, add product, request product. in all product you have to update the product what you have, how many kilograms you have , what is the price of the product, it will shown in the display. in add product if you have another product like chilly powder, vegetable oil, etc fig:5 like that also will update in the add product content. at last the request product is if manufacturer will give the request to supplier it will shown in the request product page. supplier will update all the details in the blockchain [6] and [7] . fig. 5. supplier login page supplier will have the request/response button while clicking the button it will display how much of quantity is available in the supplier store. with the amount of quantity the product rate will be increased. the supplier will add the products in the admin list by seeing this page manufacturer will give the request and later the supplier will accept the request then the transaction o poducts will exchanged with the accurate rate in the market. it will display on the screen in encryption format. 6. registration for the manuacturer account the manufacturer initially creates the account. they will analyse the raw materials and the manufacturer will request the quantity of raw materials to the supplier. then suppliers will accept the request from manufacturer and raw material will be added to the manufacturer inventory. it will have the username, password, email id, phone number and register the account. then click the already register then you will find the login page.fig:6 open the page and give request and again open the supplier account in that accept the manufacturer request and complete the process. d.lekha, s.chakaravarthi, p.visu 4 eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e6 fig. 6. supplier request/response page the manufacture will send the product id, expiry date, number of packets, etc to the block chain and then the created product will be added to manufacturer shipment. from the block chain the manufacturer will get the product details of starting to end.fig:7 manufacturer will update all the details in the blockchain with the encryption format[8]. for that no one will understand the transaction between the blockchian and manufacturer. fig. 7. manufacturer product tracking page while tracking the manufacture details will came to know that the product is good or not in the society. 7. registration for the distributor account first select the account as distributor account. then register the account username, phone number, email id, place then register the account. distributor will purchase the product in the manufacturer list what are the items are needed like that those items are purchased fig:8. fig. 8. distributor login page for each items has unique code and price for the item. the price will be higher than the manufacturer price. before that select the manufacturer name automatically it will generate the product id and place of the manufacturer.hen the shipment will trace the product starting from the farmer to manufacturer and distributor will update all details in the blockchain. if we not registered can’t able to buy the product from manufacturer fig:9. with the help of request and response only the transaction will done on the bases. the network security are needed in the transaction to obtained the products in the market rate of the current manufacturing system. the distributor want to sell the product in the market rate. the customer will check the product in the market rate, places of the manufacturer, place of the supplier cultivating the raw materials in the market rate of the online transaction.while buying the product will scan the qr code will automatically will display the product details in the screen. food supply chain management using blockchain in food traceability 5 eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e6 fig. 9. distibutor request page 8. registration for the consumer first select the category to register the process of login.then select the grocery items to click the product what you want.the distibutor will have the poduct in the grocery list. the consumer choose the grocery items what he needs put in the cart and he will scan the product qr code through the mobile devices automaticall it will generate the poduct details starting from the farmer till the consumer. to check the method of tracing in each and every step in the process [11] and [12]. for example admin needs a lays packet below that lays packet what are the ingredients ae needed it will mentioned below by seeing this farmer will cultivate the potato, chilly powder, salt, vegetable oil, etc like that many farmer will start cultivate the ingredients and farmer will update in the blockchain. with the manufacturer will give the request to the farmer and farmer will accept the request to collect the potato in a rate and start preparing the lays product [9] and [10]. mentioning the expiry dates, packing date, rate of the single packet, what are the ingredients are added like that inormation it will added. by seeing this distributor will buy the product before buying he will give the request the manuacturer will accept the request and then purchase the product from the manufacturer to put in the cart then update in the blockchain. by seeing this conumer will buy the product with the help of blockchain then the payment mode is started. it will ask that credit card pament or debit card payment or cash payment or net banking payment like these kinds of payment is available. through the types of payment can pay the amount transaction on the delivery date. 9. request and response transaction by defaultly all the mobile computing devices are in communication through the personal networks. the database management system are in the request and response transaction in client the the exclusive periodic process are well managed in the structure query language database in mysql language. the total cost of the devices are very high or low in nature of hardware and software in the applicant software system. it has security key usage while transmitting the data information from request to the server system fig:10. the personal computer will have the normal configuration to use the process in the block chain step by step [13]. this cloud process will have tree structures to have the share market invest in bit coins. it is created like node using this node only block chain will create and update. the storage of data in system characteristics in mainframe of network system computing and the client server data are stored in request response connectivity of the storage[14]. it has the request server software application in that many process can stored the data information [15]. in this the mobile devices are used in the form of hardware based technology and moreover the complexity of hardware is mainframe computers. fig. 10. request/response transaction the pronix in the data base has the product is noodels, lays, oreo biscuit has the american product only will update in blockchain not has like achi masala, shakthi d.lekha, s.chakaravarthi, p.visu 6 eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e6 masala are indian product will not update in the blockchain. this client and server transaction will be high secure in the network system. 9.1 network bank transaction while tracking the food product from supplier store to the distributor store with the help of barcode in the product. it has created the account. only the bank account customers will buy the product through online. the customers username, address, phone number, passport size photo, account number etc like that many details will ask to eister on the account. then payment is going to happened like credit card or debit card like that it will ask click on the payment to access the card details in the payment mode. then click the payment it will receive the amount transaction successully in the food supply chain management system. through our mobile phone can able to see the product details from the blockchain. through the online transaction we can buy the product from the home itself no need to go outside to buy the product. 9.2 system network computing the software and hardware system in computing the network transaction is widly compareable to the opeating system.the software system in that operating system is major play in: jdk 1.7 j2ee tomcat 7.0 mysql it will send the client/server of the request and response tansaction through the client server computing of networked monitoring system in the advantages of low (or) high level of personal signals in the computers. it plays the role of linux , unix windows and application in server database. microsoft windows are another operating system in the mobile devices.the hardware system in that operating system is major play in : hard disk : 80gb and above ram : 4gb and above processor : p iv and above through the sense of internet computing the personal computers and mobile devices are highly farmable. appendix a. texture of the features from the above mention scenario many cases of food taceability in the system development are proposed very high performance through the internet computing by the usage of software development . it has network security keys features of technology used in:j2ee (jsp, servlets), javascript, html, css, ajax. hibernate framework mvc pattern through the transcation of the food product cost and food packing date and food product expiry date, food ingredients,etc. through the blockchain all information are shared in it .blockchain are shared the networks space to the biometrics. this blockchain will updated in the encryption format that nobody can able to understand the transaction is done betwwen the product buyers and sellers. appendix b. system organization of the food network the storage of the food data in system characteristics are occuring the mainframe computer of network system computing and the client, server data transaction are stored in the request and response connectivity of the network storage. it has the request server software application in that many process can stored the data information and the response server will also produce the software application. the total cost of the devices are very high or moderate or low in nature of the hardware and software in the application software system. it has the security key usage while transmitting the data information from request to the response server or client system. the network is fully manual in somewhere and automatically in transaction places. 9. conclusion food is the major part of the system in the world. it survives many modern technology cameras, gps, rfid tool kit. next generation has to follow the standardized tasks of the healthy food trend appear in the smart cities. to keep tracking the food items many of them will buy the product by seeing the ingredients and expiry date of the product, packing date of the product with the help of the blockchain technology. mobile technology has disabling scanning devices of the food product details should display in the screen. the rising cost of hospitalization is decreases the elder and younger population in the food borne illness and the food adulteration through the better lifestyle environment will be designed. the monitoring platform exploits the combined processing of the product. this will allow to all over the world because every year people are suffering from the food borne ill diseases to avoid that many government organization must take action to avoid the food borne ill diseases. the architecture enables a flexible and easily reconfigurable monitoring of a complex space as well as it permits to capture the user’s interaction with specific nearby products. food supply chain management using blockchain in food traceability 7 eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e6 references [1] “a new approach to integrate the rfid in the internet of things using the mqtt protocol and 6lorfid framwork” mohamed taouzari, ahmed mouhsen, hanane nasraoui, ieee conference paper-january 2019. [2] “application of rfid technologies in the temperature mapping of the pineapple supply chain”, cecilia amador, jean-pierre, emond, maria cecilia do, nascimento nunes, march 2009. [3] “networked rfid for use in the food chain”, in ieee conference on emerging technologies and factory automation (etfa) p. jones, 2006. [4] “bitcoin: a peer-to-peer electronic cash system” satoshi nakamoto, march 2016. [5] “karma : a secure economic framework for peer to-peer resource sharing” vivek vishnumurth,sangeeth chandrakumar and emin gun sirer, ieee publication january 2017. [6] sl900a,http://ams.com/eng/products/uhfrfid/uhf -interface-and-sensor-tag/sl900a [7] “bitcoin mining and its energy footprint” karl j.o’dwyer and david malone, ieee transaction june 2014. [8] “internet of things: a survey on the security of iot frameworks” giovanni russello, mahmoud ammar, bruno crispo, journal publication of 2018 in journal homepage : www.elsevier.com/locate/jisa [14] http://www.thingmagic.com/index.php/fixed rfidreaders/mercury6 [15] e.d. giampaolo, f. fornì, g. marrocco, rfid network planning by particle swarm optimization. aces j. 25(3), pp. 263–272 (2010). [9] “privacy information security classification study in internet of things” qi li, xiaofeng lu, pan hui, zhaowei qu, international conerence paper 2014. [10] “testing improvements in the chocolate tracability system : impact on product recalls and production efficiency” saltini , rolando, akkerman , renzo,food control:doi:10.1016/j.foodcont.2011.07.015-2012. [11] “an overview of privacy and security issues in the internet of thing 20th tyrrhenian workshop on digital communications”, alex, carlo maria medaglia, ru serbanati, 2010. [12] “ouroboros: a provably secure proof-of-stake blockchain protocol” aggelos kiayias, roman oliynvkov, bernardo david, alexander russell, july 20, 2019. [13] g. marrocco, s. caizzone, electromagnetic models for passive tag-to-tag communications. ieee trans. antennas propag. 60(11), 5381–5389 (2012) d.lekha, s.chakaravarthi, p.visu 8 eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e6 http://ams.com/eng/products/uhfrfid/uhf http://www.elsevier.com/locate/jisa http://www.thingmagic.com/index.php/fixedhttp://www.thingmagic.com/index.php/fixed d.lekha1,*, s.chakaravarthi2, p.visu3 abstract 1. introduction 2. existing work 3. proposed work 4.1 concept of blockchain 4.2 admin account 5. registration for the supplier account 6. registration for the manuacturer account 7. registration for the distributor account 8. registration for the consumer 9. request and response transaction 9.1 network bank transaction 9.2 system network computing appendix a. texture of the features appendix b. system organization of the food network 9. conclusion references review on drowsiness detection eai endorsed transactions on smart cities research article 1 this paper relates the street mishaps that happen because of driver's drowsiness. recent studies state that more disasters are caused due to doziness. drivers can feel drowsiness due to sleep deprivation, continuously driving, drugs and medicines, and so on. accidents caused due to doziness are more than drink driving. this paper traces many methods to detect drowsiness and alerts the driver. there are two approaches to detect drowsiness. first is physiologically based and another is behavioral-based. also there are other approached used. many technologies are used for detecting the weariness of the driver. it is a review paper of numerous advancements utilized by various scientists. in addition, human conduct can also be studied. also, the discovery of drowsiness with eyes open is conceivable. in countenance detection technology, driver weariness recognition is one of the major possible businesses uses. here how drivers can be alerted using different methods is discussed. review on drowsiness detection apoorva1,*, d khasim vali1 and rakesh k r1 1computer science & engineering, vidyavardhaka college of engineering, mysuru, india abstract this paper relates the street mishaps that happen because of driver's drowsiness. recent studies state that more disasters are keywords: svm, drowsiness, ecg, eeg, emg, driver fatigue monitoring, adaboost. received on 26 june 2020, accepted on 08 july 2020, published on 10 july 2020 copyright © 2020 apoorva et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.165517 1. introduction shutting eyes, sagging, is one of the behavior patterns of doziness. the term dozy means falling asleep. it occurs because of a lack of sleep, medicines and drugs, and weariness. driver's doziness is the prime aspect of grave street mishaps. so as to fulfill the client ever expanding interest, the degree of subjective weight on drivers is likewise expanded. driver with recklessness level in understanding, detecting, and administrating the vehicle, accordingly represents a genuine risk to their own lives and other's lives. for this purpose, adapting procedures that observe the driver's degree of sleepiness and heeding the driver of any unreliable driving circumstances is crucial. to measure highlights, for example, mind waves (eegelectroencephalogram), eye developments (eogelectrooculography) and pulse (ecg-electrocardiogram) by connecting anodes to the driver physiological estimations are made. this methodology is both meddlesome and unfeasible as anodes must be connected to driver, making it as principle disadvantage. on partitioned roadways and territories liberated from roadway intersections, has higher chance of accidents. driver fulfillment with an attention on the vehicle conduct is portrayed as carefulness of driver’s condition. be that as it may have procedures that are dependent upon restrictions like vehicle type and qualities of street. the highly developed technology proposes a strategy to prevent this kind of mishaps. the accidents caused by drowsiness are graver. the driver's face is consistently recorded utilizing a camera in the proposed idea. in the field of mishap shirking frameworks, improvement of innovations for identifying or forestalling sluggishness of driver is difficult. awakening is significant in directing awareness, consideration, and data preparing, it very well may be seen by complex varieties of physiological estimations, and for example, mind and heart exercises, furthermore, outward appearances. to extricate visual attributes which commonly portray driver’s cautiousness level from video pictures, computer vision methods are utilized. numerous methodologies have been proposed to enhance driver safety. however strategies are delicate to outer factors, for example, luminance or presence of the driver. vehicle speed, parallel position, turning point and moving course are considered by *corresponding author. email:apoorvaradhakrishna500@gmail.com eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e7 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ apoorva, d khasim vali and rakesh k r 2 strategies that screen the conduct of the vehicle. to the driver these procedures are non-meddlesome, forms them to be reasonable for useful frameworks. for example, the driver experience, driving conditions and vehicle type are constraints for these strategies. 2. literature review real time drowsiness detection using eye blink monitoring “in this paper, a strategy was proposed to detect the drowsiness by using eye state detection with eye blinking strategy”. to start with, the picture is transformed to dim image and algorithm of harris corner detection is utilized to detect corners that are at curve of eyes and on both sides. upon drawing the dots, a straight line eill be drawn between the upper two dots and mid-point by calculating the line, and mid-point will be connected to the lower dot. for each image, the same process is performed and distance ‘d’ from the center to the bottom is calculated for determining the condition of eye. ultimately, based on distance ‘d’ calculated, the eye state’s intent is made. the eye status will be listed as “shut” if d is zero or close to zero, otherwise the eye status will be “open”. they may have invoked time intervals or to know whether the individual is tired or not. this takes 100-400 milliseconds to complete a normal flicker by an individual. drowsiness detection on eye blink duration using algorithm a strategy was proposed that recognizes sleepiness in 2012. 640x480 resolution webcam is utilized that performs continuous eye flicker identification. each eye squint is estimated against a mean worth that are distinguished from each casing. enlightening at each flicker with a standard mean worth that framework looks at and an alert is activated if the educational surpasses this incentive for a specific measure of successive edges. the proposed strategy is support vector machine algorithm. an exactness of 99% has been recorded by the creators. for ongoing conditions, in 640×480 resolution the framework runs is substantial. in this calculation, the framework needs to hold data about the past edges in light of the fact that the eye squinting estimations from an aggregate measure of edges are utilized to screen languor. driver fatigue monitoring system based on eye state analysis in this paper doziness detection is categorized into three major classifications that are biological indicators, vehicle behavior, and face analysis. visionary, heart rate and pulse rate are measured by indicators. speed, lateral position and turning angle are measured by behavior. head posture, yawning, eye closure, eye blinking are measured using face analysis. for example, mit smart vehicle [7] is delegate venture. for sensor affirmation visual data are utilized from a vehicle in which few sensors are installed. toyota directed the excellent security transport venture [8]. pulse is estimated when driver wears the wristband. utilizing hard hat or contacts [9] to screen eyes and stare gesture by other procedures. the conduct of the driver, including head posture, gaping, shut eyes, eye flickering, and so forth estimates the conduct by observing from camera, if any of the laziness indications are distinguished [10][11][12], then it generates the alarm. the fatigue monitoring system established is composed of three key phases: identification of the face and eyes, extraction features and support vector machine, for classification of fatigue. real-time nonintrusive monitoring and detection of eye blinking in view of accident prevention due to drowsiness in this paper, 18% of mishaps including drowsiness are the primary factor stated in review done in 2007 [3]. drowsiness caused 20% of genuine street mishaps in britain. essentially, road and traffic authority expresses has done review in the year 2007, exhaustion added to 20% of mishaps caused on street [4]. to identify fatigue state of the driver so as to avoid mishaps system was introduced that catches face and eyes to gain blinking rate. utilization of computer vision techniques help extricate unique features from recorded images and videos accomplishes facial recognition. in this paper, a driver sharpness recognition framework was proposed dependent on weariness. the proposed strategy effectively identifies the eye flicker and the sluggishness. in this algorithm, a decent estimation of the squint rate was gotten. by showing the driver utilizing a signal pointer and vibrator engine, safe driving will be guaranteed. facial features monitoring for real time drowsiness detection in this paper, utilization of keen algorithms in vehicles has grown extensively in ongoing years. to screen what's more, transmit the state of the vehicle and the driver frameworks utilizes wsns. to improve the nature of driving shrewd vehicles utilizes programming procedures to control motor speed, guiding, transmission, brake and so forth. in driver’s choice time is prime factor. observing the state of being and outward appearances of the drivers is another technique to check the driver weariness. remote sensor systems can't process and transmit these data with satisfactory accuracy and a decent review. in offered method, firstly video is captured by camera then it is broken into parts in proposed method. first face is detected, and then the skin is segmented. after segmentation the system tracks the eye using edge detection algorithm, k means algorithm is used for detection of yawning. then it is trained using support vector machine. the system offered accomplishes exactness of 94.58% at four test cases compared to other techniques. driver drowsiness monitoring based on yawning detection in this paper, identifying or screening the driver to intent whether driver is tired or not is significant in this framework. tiredness is distinguished on three: physiological, social and execution based estimation. there eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e7 review on drowsiness detection 3 are three strategies that are proposed in this area. the first strategy focuses on tiredness recognition by recognizing the face and mouth for identifying yawn. the subsequent technique recognizes face dependent on layout coordination, then mouth using shading condition for identifying yawn. the last technique utilizes viola-jones hypothesis for recognizing face and mouth. identifying yawn led to exploration of three strategies. finding driver's face and mouth were subject to shading division under various enlightenment conditions in both first and second strategies. human countenances has exceptional shading therefore various skin shading data was utilized. the lip shading is the focal point in mouth recognition. rapid object detection using a boosted cascade of simple features in this paper, there are three commitments that depict them into resulting segments. integral image is the new image representations that quickly assess features is the principal commitment of this paper. utilizing adaboost classifier chooses significant highlights are the second commitment of this paper. to focus attention on promising regions of image complex classifier are combined such that it increases the speed of detector is third commitment of this paper. the proposed methodology is 15 times faster than other methodologies as it takes less time to identify object with high exactness. this has bought insights about new algorithms and representation in computer vision algorithm. real-time system for monitoring driver vigilance the general design of framework comprises of four significant modules: picture obtaining, student discovery and following, visual practices and driver carefulness. microcamera is vulnerable close to ir as it is low cost gadget that captures the image. for segmentation and image processing tracking state and eye detection is accountable. in this paper, two kalman filters are utilized for tracing eyes in real time. a few boundaries from the pictures so as to distinguish some visual practices effectively discernible in individuals encountering weariness: slow eyelid development, littler level of enlightening, visit gesturing, flicker recurrence, and face present are calculated in visual, conduct stage. every individual boundary got in the past stage is combined for utilizing a fluffy framework under driver vigilance evaluation stage that results the driver heedlessness level. if the level surpasses a certain edge then the driver is alerted. driver fatigue detection based on eye state analysis an efficient innovative drowsiness detector for driver is presented in this paper. first is the interframe difference that is utilized to identify face by binding color details. the area of face is segmented from the picture if existed, dependent on mixed skin tone. then the process is stimulated for obtaining eye location in face area. for analyzing condition of eye ratio of width to height and pupil height is utilized. precise eye location can be located through screenings. two eyes identified produce average pupil height and ratio of width to height for analyzing condition of eye. the proposed method shows accurate results for drowsiness identification of driver under real time conditions. detection of drowsiness based on hog features and svm classifiers this paper provided method that detects drowsiness of low resolution image. haar cascade classifier for eye tracing is utilized for detecting drowsiness of driver by combining histogram of oriented gradient (hog) highlight with support vector machine (svm) classifier for blink detection. perclos is calculated when eye blinking is detected. the different procedure of an algorithm includes utilizing camera to capture video frames, detection of face then extracting highlight, eye area extraction and identification of eye, identifying blink, then perclos is calculated and detecting drowsiness. there are various stages in drowsiness a) extremely sleepy, fighting sleep b) sleepy, some effort to be alert c) sleepy, no difficulty in being alert. it depicts a method that detects drowsiness of low resolution image. haar cascade classifier for eye tracing is utilized for detecting drowsiness of driver by combining histogram of oriented gradient (hog) highlight with support vector machine. perclos value is calculated after blinking is detected. if the value edges more than 6 seconds then the individual is drowsy. by contrasting the outcome with human rater observations the program has been expanded. it produces 91.6%. real-time nonintrusive monitoring and prediction of driver fatigue in this paper, it portrays a real time online model and driverexhaustion is screened. to attain video picture of the driver, it utilizes charge coupled gadget cameras outfitted with dynamic infrared illuminators which are remotely found. various viewable signs that regularly describe the degree of readiness of an individual are partitioned progressively and efficiently consolidated to induce the driver weakness. the obvious signs utilized portray growth of the eyelid, look development, head development, and facial articulation. a probabilistic model is created to show human weariness and to anticipate depletion depending on the obvious signs. the simultaneous utilization of methodical mix between different clear prompts gives a considerably more hearty and precise exhaustion than utilization of a solitary visible signal. this framework was approved under genuine exhaustion conditions with human subjects of various ethnic foundations, sexual orientations, and ages; with/without glasses; and under various enlightenment conditions. it was seen as sensibly hearty, dependable, and exact in exhaustion portrayal. smartwatch based wearable eeg system for driver drowsiness detection the reason for mortality in auto collisions around the world is sleepiness of the driver. to recognize driver tiredness numerous physiological signs have been proposed. eeg signal (electroencephalographic) is among these signs, which mirrors the mind exercises, is all the more eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e7 apoorva, d khasim vali and rakesh k r 4 legitimately identified with laziness. these models just gauge discrete marks is one impediment of these examinations. in addition along these lines didn't take into consideration evaluating relative seriousness of driver languor. there are three stages in drowsiness that includes alert, early warning, drowsy. support vector machine based back probabilistic model (svmppm) is proposed for this examination for ddd (detecting driver drowsiness) focused on changing the sluggishness level to any estimation of 0~1 rather than discrete names. to build up this model twenty subjects are utilized. to build model fifteen subjects and to test model five subjects are utilized. it gives precision of alert: 91.25% early-warning: 83.78% drowsy: 91.92%. 3. comparision sl. no / paper title comparison parameters 1. driver fatigue monitoring system based on eye state analysis techniques face detection for eye state analysis algorithms viola-jones face cascade of classifiers support vector machine dataset 5 subjects accuracy 93.5% 2. driver drowsiness monitoring based on yawning detection techniques i. camera installed at front mirror: face detection mouth detection yawn detection ii. camera installed on the dash: face detection mouth detection yawn detection algorithms color segmentation active counter model viola-jones method dataset 342 videos accuracy i. 85% 40% 40% ii. 95% 85% 60% 3. eye detection for a real-time vehicle driver fatigue monitoring system techniques eye detection using image processing algorithms artificial neural networks (ann) support vector machines (svm) adaptive boosting (adaboost) dataset 1295 eye and 1363 noneye images accuracy svm: 98.1% adaboost: 97.95%. 4. real-time nonintrusive monitoring and detection of eye blinking in view of accident prevention due to drowsiness techniques face and eye detection eye blinking detection warning system design algorithms viola-jones object detection haar cascaded classifier dataset not specified accuracy not specified eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e7 review on drowsiness detection 5 5. real time drowsiness detection using eye blink monitoring techniques face and eye detection for eye blink detection algorithms viola jones algorithm adaboost haar classifier dataset not specified accuracy 94% 6. facial features monitoring for real time drowsiness detection techniques face detection and skin segmentation eye detection yawn detection algorithms viola jones algorithm k-means algorithm svm dataset 100 templates accuracy 94.58% 7. rapid object detection using a boosted cascade of simple features techniques feature extraction from integral image algorithms adaboost algorithm dataset 4916 faces accuracy not specified 8. real-time warning system for driver drowsiness detection using visual information techniques face detection eye detection algorithms viola-jones object detection adaboost algorithm neural networks support vector machine dataset not specified accuracy not specified 9. detection of drowsiness based on hog features and svm classifiers techniques eye tracking using haar based classifier algorithms haar based cascade classifier histogram of oriented gradient (hog) support vector machine (svm) dataset not specified accuracy 91.6% 10. smartwatch based wearable eeg system for driver drowsiness detection techniques wireless eeg acquisition device algorithms support vector machine(svm) dataset 20 subjects accuracy alert: 91.25% early-warning: 83.78% drowsy: 91.92% eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e7 apoorva, d khasim vali and rakesh k r 6 4. conclusion various methods have been utilized to detect drowsiness. some of these methods give high accuracy. most of these methods used computer vision algorithm for detecting face from photo or videos, detecting gesture of closing eyes and detecting mouth. computer vision algorithm gives high accuracy. after detecting face, eyes and mouth various algorithms are used on this to detect drowsiness and alert the driver. many methods give high accuracy. some methods have disadvantages such as wearing sunglasses, skin color, insufficient lighting, night time and day time. only single metric that is face detection is considered to detect drowsiness. hence multiple metric can be considered to achieve more accuracy. references [1] real time drowsiness detection using eye blink monitoring by amna rahman department of software engineering fatima jinnah women university 2015 national software engineering conference (nsec 2015) [2] s. motorist, driver fatigue is an important cause of road crashes, smart motorist. [3] driver fatigue and road accidents: a literature review and position paper, the royal society for the prevention of accidents, 2001. [4] road and traffic authority (rta) annual report, sidney, 2008. [5] m. singh, g. kaur, ”drowsiness detection on eye blink duration using algorithm”, international journal of emerging technology and advanced engineering , volume 2, issue 4, april 2012. [6] p. viola and m. jones, “rapid object detection using a boosted cascade of simple features”, in conference on computer vision and pattern recognition, 2001. [7] j. healey and r. picard, “smartcar: detecting driver stress,” in proc. 15th int. conf. pattern recognition, barcelona, spain, 2000, vol. 4, pp. 218–221. [8] a. kircher, m. uddman, and j. sandin, “vehicle control and drowsiness,” swedish national road and transport research institute, linkoping, sweden, tech. rep. vti922a, 2002. [9] anon, “perclos and eyetracking: challenge and opportunity,” applied science laboratories, bedford, ma, 1999. [online]. available: http://www.a-s-l.com. [10]. f.xiao, c.y.bao,f.s.yan, “yawning detection based on gabor wavelets and lda,” journal beijing univ. technol. 35, pp.409–413, 2009. [11]. z. zhang, j. zhang, “a new real-time eye tracking based on nonlinear unscented kalman filter for monitoring driver fatigue,” journal of contr. theory. applications, 8, pp.181–188, 2010 [12]. b.c.yin,x. fan,y.f. sun, y,” multiscale dynamic features based driver fatigue detection,” int.journal. pattern recogn. artif. intell. 23, pp. 575–589, 2009. [13] r. coetzer and g. hancke, “driver fatigue detection: a survey,” ieee africon conference, september 2009. [14] s. abtahi, b. hariri and s. shirmohammadi, "driver drowsiness monitoring based on yawning detection," 2011 ieee international instrumentation and measurement technology conference, binjiang, 2011, pp. 1-4. [15] l.m.bergasa, j.nuevo, m.a.sotelo, r. barea, m.e. lopez, “real-time system for monitoring driver vigilance,” ieee trans. intelligent transport system, 7, pp. 63–77, 2006. [16] r. c. coetzer and g. p. hancke, "eye detection for a real-time vehicle driver fatigue monitoring system," 2011 ieee intelligent vehicles symposium (iv), baden-baden, 2011, pp. 66-71. [17] a. punitha, m. k. geetha and a. sivaprakash, "driver fatigue monitoring system based on eye state analysis," 2014 international conference on circuits, power and computing technologies [iccpct-2014], nagercoil, 2014, pp. 14051408. [18] p. viola and m. jones, “robust real-time face detection,” international journal of computer vision, vol. 57, no. 2, pp. 137–154, may 2004. [19] h. rowley, s. baluja, and t. kanade, “neural networkbased face detection,” ieee transactions on pattern analysis and machine intelligence, vol. 20, no. 1, pp. 23–38, january 1998. [20] k. u. anjali, a. k. thampi, a. vijayaraman, m. f. francis, n. j. james and b. k. rajan, "real-time nonintrusive monitoring and detection of eye blinking in view of accident prevention due to drowsiness," 2016 international conference on circuit, power and computing technologies (iccpct), nagercoil, 2016, pp. 1-6. [21] b. n. manu, "facial features monitoring for real time drowsiness detection," 2016 12th international conference on innovations in information technology (iit), al-ain, 2016, pp. 1-4. [22] du, yong, et al. "driver fatigue detection based on eye state analysis." 11th joint international conference on information sciences. atlantis press, 2008. [23] l. pauly and d. sankar, "detection of drowsiness based on hog features and svm classifiers," 2015 ieee international conference on research in computational intelligence and communication networks (icrcicn), kolkata, 2015, pp. 181-186. [24] qiang ji, zhiwei zhu and p. lan, "real-time nonintrusive monitoring and prediction of driver fatigue," in ieee transactions on vehicular technology, vol. 53, no. 4, pp. 1052-1068, july 2004. [25] g. li, b. lee and w. chung, "smartwatch-based wearable eeg system for driver drowsiness detection," in ieee sensors journal, vol. 15, no. 12, pp. 7169-7180, dec. 2015. eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e7 various methods have been utilized to detect drowsiness. some of these methods give high accuracy. most of these methods used computer vision algorithm for detecting face from photo or videos, detecting gesture of closing eyes and detecting mouth. com... implementation of decentralized blockchain e-voting 1 implementation of decentralized blockchain e-voting saad moin khan1, aansa arshad1, gazala mushtaq1,*, aqeel khalique1 and tarek husein1 1department of computer science & engineering, sest, jamia hamdard, new delhi, india abstract keywords: e-voting, blockchain, smart contracts, ethereum cryptocurrency. received on 29 january 2020, accepted on 21 may 2020, published on 03 june 2020 copyright © 2020 saad moin khan et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.164859 *corresponding author. email: gazalamushtaq188@gmail.com 1. introduction an election is the procedure of espousing a candidate to hold a public office or an official position in order to establish a government through the voters. elections are considered as one of the founding pillars in any democratic society where the citizens make a decision by voting for the competent candidate to form a healthy democracy. the history of election dates back to ancient greece, rome and across the medieval period to select the pope and the holy roman emperor. in india it dates back to the early vedic period where the ‘raja’ (king) was elected by the ‘gana’ (people). the modern day elections emerged only after the 16th century across europe and north america. modern approach of voting system or evm replaced the traditional method of voting, which was a monotonous process, demanding arduous and taxing efforts, resulting an ample scope of error and miscalculations. with the techno-advancement, the mechanical system of voting proved far more fluent, serviceable and reduced the human effort, thereby increasing the reliability and accuracy. the proposed system employs the technologies like e-voting, blockchain and smart contract to provide more security and convenience. e-voting: e-voting refers to the process of casting and compiling votes using an electronic system. votes are stored in tape cartridges, diskette, smart cards and sent to a centralized location for compilation process. the various forms of evoting are der (direct electronic recording) touch screens, optical scanners. the two main types of e-voting are: on-site e-voting where electronic voting machines are placed / present in the polling boots with some government official who will supervise the voting process and people have to be in queue for casting the vote. remote e-voting; where people need not be present at the polling station instead can cast their vote from any remote location using computers, mobile phones, etc. through internet, sms, or kiosks. the security community found electronic voting machines inaccurate and untrustworthy based on security issues. the software can be undermined when the device is physically reached which affects the votes on the machine. elections need to be secure and unimpeachable irrespective of the e-voting reduced the cost of election and provided convenience to some extent as compared to the traditional approach of pen and paper but it was considered to be unreliable as anyone having access to the machine physically can obstruct the machine and alter the votes. also in order to control the entire procedure from electronic voting to electoral results and tracking the outcomes, a central system is required. voters are not completely secure as vote can be targeted easily. it also possesses a great threat to the right to vote and transparency. this paper provides a solution for removing inconveniences from conventional elections using blockchain that has emerged as an exciting technology for various application due to its unique characteristics that outperform other technologies. the goal of this research is to establish a system for e-voting that is decentralized rather than centralized by using blockchain technology that guarantees protection to electorate’s identity, data transfer privacy and verifiability by an open and transparent voting process. eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e4 http://creativecommons.org/licenses/by/3.0/ mailto:corresponding%20author.%20email:%20gazalamushtaq188@gmail.com 2 organization. people’s privacy and voting protection must be secured but it should not take too long for votes to be counted, as it upraises concerns. blockchain: blockchain proved to be a substitute for the conventional approach by making system unalterable and transparent. blockchain is an organized data structured that includes blocks where each block is connected to every other block through a chain. the first block is called as genesis block. each new block will be stacked to form a stack called a blockchain. each block consists of data, hash and hash of previous block. if any change is being made to the data available in a particular block, consequently the hash of the block also gets changed but the next block will have the same unchanged hash of the previous block which invalidates this block and all other succeeding blocks. this is to avoid tempering because making change in one block you will need to calculate hash for every other following block however hackers now a days can compute hundreds of thousands of hashes in a matter of seconds. in order to avoid this problem it makes use of proof-of-work concept that delays the pace of forming a new block. moreover it make use of a distributed peer to peer network where no central entity is present. whenever a new block gets created it is sent to all other nodes present on this network where each node makes sure that no tempering is done by verifying the block after which the new block is added to every other node’s blockchain. every node on the network agrees on whether the block is valid or not by creating a consensus which makes blockchain so secure, safe and reliable. smart contract: a smart contract is a self-imposed contract that is embedded in a blockchain managed computer code. this code includes a set of rules governing the communication and decision on the contract between the parties, the contract will be enforced automatically once the already defined rules are met. smart contract gives a framework for efficient control between two or more parties of tokenizes assets and access rights [1]. fig 1 [1]; shows the working principle of smart contract. blockchain is just a database that cannot be altered, without smart contract, which expands and leverages blockchain technology [2]. figure 1. smart contract working principle. there are various aspects of smart contract including technical aspect, legal aspect, economic aspect, that can be seen from the figure 2 [2]. figure 2. various aspects of smart contract. self-verification of the conditions in a smart contract is done by data interpretation. each network node will guarantee the proper execution of a single contract, which relief the contract creators from tracking the execution of the contract. smart contracts are self-executing, where the conditions of the agreement between different parties are written into the code. this means that legal obligations can be mapped using smart contracts into automated process. the execution of the contract can be automatically invoked by a trigger like expiration date. in this paper, we implement blockchain based e-voting system which overcome the problems encountered in e-voting and builds trust among voters for legitimate voting. moreover, it will also be a helpful step towards the development of smart governance. this paper contains various sections; section 2 presents recent related work in block chain technology and evoting system, section 3 presents proposed e-voting system based on blockchain, section 4 gives implementation details and results. finally, section 5 concludes our work 2. related work e-voting system was a great advancement over traditional pen and paper approach and became very popular in many countries. several countries introduced e-voting system in their election process. although it provided a number of advantages like increased voter turnout, auditability, low cost, convenient and accessible elections, etc. but there were several important challenges and issues associated with it. abdelwehab et al. [3] in their study discussed a number of challenges in e-voting system including legal challenges, social and cultural challenges, technical challenges, attacks, etc. diego f. aranha et al. [4] in their work identified an experiment to test the validity of election results and to enhance transparency and voter participation within electronic elections. this proposal was based upon two aspects i.e. distributed collection of pole tape, made by mobile devices by voters and crowdsourcing election data saad moin khan et al. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e4 3 verification by electoral authority. kristian gjosteen and anders smedstuen [5] believed that if voters make use of voting protocol correctly then there will be no chance of attack on results of elections and they give a statistical method to improve the security of evoting. budurudhi et al. [6] explores how to properly develop voting machine interfaces to promote the role of electors and electoral administrators and then use such interfaces for complex elections. the problem of relying on a remote voting device is said to be firmly linked to the interface provided which in turn influences votes as verification of voting is an important issue. much of the work in remote– electronic voting involves cryptography voting protocols design and verification to safeguard desired property. neumann et al. [7] states that in order to make specific recommendations on the type of voting system that is best suited to that particular context, they introduced a model for the comparison of voting schemes in any given electoral setting and the model was applied to the specific context of estonian internet voting. as there were various problems with electronic voting especially related to physical security, people began to look for solutions to the problems that’s when blockchain came into the field of e-voting, initially blockchain was used for bitcoin. ahmed ben ayed [8] in his work discusses how to take the advantages of blockchain technology in the process of e-voting to make it safe, secure, anonymous, etc. jen-ho hsiao et al. [9] in their work make use of smart contracts in decentralized blockchain technology for e-voting to engage all voters in evaluating and recording ballots. it increases the trust of electorate and decreases the misuse of election capital. jonathan alexander et al. [10] in their study used netvote for user interface of the program, it uses decentralized application. the dapp admin helps electoral administrators to decide electoral policy, generate voting, register rules, opening and closing of voting. identification of voters is done by other applications like biometric readers. to test and check the results of election tallydapp is used. this netvote reinforce three kinds of elections: private election, open election, token holder elections. there are many problems in current e-voting system which acts as a hindrance in accomplishing the accurate results like: a. prone to hacking. b. inefficient auditing c. misinterpretation of voter intent. d. political biasness on behalf of the manufacturer. e. tempering of software programs. f. inefficiency in securing the casted votes. g. hardware malfunctions, etc. the main aim of this research is to develop an electronic voting system based on blockchain technology that meets the legislation’s longstanding challenge. this model can be implemented at various levels including school, college, offices and even at national level voting. because elections are always challenged with fraudulent practices like infiltrating machine, alter votes, organization of information campaigns and more. all of these problems will be addressed by our model. 3. proposed system the proposed system utilizes several tools namely ganache, truffle framework, npm and metamask. truffle imports the smart contracts on the blockchain while as ganache operates the internal blockchain and it will be accessed by using metamask. with some ether i.e. ethereum’s cryptocurrency is required by a user for an account with wallet address. to write the transaction to blockchain, user needs to pay a certain transaction fee which is called as gas. once votes are cast the process is completed by a number of nodes on the network called as minners. these miners compete with each other to complete the transaction. the miners who succeed in this transaction is awarded ether paid by users to vote. instead of node we will be using ganache software for mining purpose. figure 3. proposed e-voting system based on blockchain preliminaries: our proposed model can be implemented by using 64-bit hardware/ machine, windows 7 onwards, nmp dependencies, truffle framework, metamask, solidity toolkit and ganache. 1. dependency npm(node package manager) 2. truffle framework 3. ganache 4. metamask 5. coding language; solidity, html, javascript, css npm (node package manager): npm is package manager that manages, installs, updates or uninstalls the node.js packages in an application. it is a command line based tool. it operates in two modes: local mode implementation of decentralized blockchain e-voting eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e4 4 and global mode. in global mode all node.js application are affected and in local mode only particular directory of an application gets affected [11]. truffle framework: truffle is a powerful tool to work with ethereum smart contracts. it is used for compilation, deploying and linking of smart contracts, provides testing platform for automated contracts, manages networks and packages, etc. [12]. ganache: it was previously known as testrpc and comes in both forms command line and ui. a virtual blockchain establishes ten standard ethereum addreses with all and private key preloading them with simulated hundred ether each. with ganache there is no mining rather it automatically confirms every transaction. it is convenient for operating systems like windows, linux and mac [13]. metamask: metamask is an open source, user friendly tool having a graphical user interface for doing transactions in ethereum. ethereal dapps can run without having a complete ethereum node running your system browser. metamask is essentially a bridge between browser and blockchain ethereum [12]. solidity: solidity is a high-level language with javascript style syntax for contracts. it is a method for generating evm machinelevel code and converts it into simple instructions. it has four value types namely: boolean, integer, address and string but has same operators as that of javascript [14]. working: the voter can log on to the voting website, then he has to log in with the chrome extension of metamask to connect with the local blockchain. once the user is connected, the page is refreshed and the user can see the candidates and the current votes. below that is the option to select the candidate to vote, the voter selects the candidate and click on vote, a metamask pop-up comes up which tells the ethereum transaction that has to be made, once the user clicks on vote, the vote is given to the selected candidate provided that the voter hasn’t voted before. if the user has already voted and attempts to vote again, a failed transaction will occur and vote will not be accounted. a local blockchain is deployed using ganache and metamask is set up to connect with it. truffle framework allows to migrate the smart contracts created on solidity to the local blockchain. when the user clicks to vote, metamask allows to move ether from one account to another. every user is given a unique id that is ethereum address and a private key and exact amount of ether is distributed to all the voters’ accounts. once the user votes, the ether is transferred from the voter’s account to the candidate’s account, and all the transactions goes through the blocks, all the transactions will be visible to everyone once we launch the project. this will give voters complete transparency and they can cross-check their votes. once the user has voted, the address will not contain the same amount of ether, therefore if the user attempts to vote again, the transaction won’t be completed and the vote will not be accounted. mining is performed by all the other nodes but here, we have given ganache the power to auto-mine on behalf of other nodes. the flowchart below explains the voter side of the process. figure 4. flow model of the e-voting system based on blockchain saad moin khan et al. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e4 5 4. implementations and results 1. setting up: the first thing that we need to do is run local blockchain by starting up ganache. figure 5. screenshot of setting up ganache. figure 6. snapshot of no transaction. after setting up ganache there will be not any transaction as we have not done any transaction yet. as we can see from the snapshot below there is no transaction. implementation of decentralized blockchain e-voting eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e4 6 now we use truffle framework to transfer the smart contract to the blockchain by giving command on the command line. we have also used npm directory by cmd. following commands are being used for this purpose: figure 7. snapshot of command line for truffle framework. after migrating the smart contract, we start the project using npm directory by cmd. saad moin khan et al. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e4 7 figure 8. command line of npm directory 2. user interface: user interface is through which users can interact with the e-voting system. the picture bellow is how user will see the interface. the loading screen will continue to display loading until the electorate login through metamask. figure 9. snapshot of loading screen. below secreen will be displayed when the electorate is logging in through metamask implementation of decentralized blockchain e-voting eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e4 8 figure 10. constituency logging in via metamask. after the user has logged in, main screen comes up with zero vote, the user cannot vote until they import their account by entering private key. figure 11. main screen the private key is given in advance to the user that will look like figure 12. saad moin khan et al. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e4 9 figure 12. private key. voter imports their account by entering the private key above. figure 13. snapshot of importing account. the electorates choose candidate of their choice, the metamask pop-up gets open when clicked on vote to confirm the transaction implementation of decentralized blockchain e-voting eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e4 10 figure 14. snapshot of confirming transaction. once confirmation is done, the voter gets redirected to the main page where only results are visible but now you can’t vote. in the similar manner, others can also vote by importing their account. figure 15. snapshot of result on main page. 3. checking the transactions: the transaction list will be available publicly to provide the user with convenience to tally their votes respectively. the users can check their votes given by them by looking into the transaction list. an entire transaction list will be like one given in fig 16. saad moin khan et al. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e4 11 figure 16. snapshot of transaction list. 4. conclusion the recent development in the area of voting system includes blockchain technology, which not only proved to be time and cost efficient but is also safe and secure, hence is more reliable and precise than the earlier approaches. in this paper we have used blockchain based evoting using smart contract which includes a set of rules governing the communication and decision on the contract between parties. various tools like ganache, truffle framework, npm and metamask were used for implementation purpose. as blockchain technology is decentralized due to which tempering and alteration in such system is quite attainable. our proposed system provides convenience to the voters by allowing them to connect to the system having easy-to-use user interface, through which they can cast their vote by importing their account and can easily review their vote. it creates a sense of trust among voters, that there vote is being computed and kept in a safe custody. references [1] https://shermin.net/token-economy-book/ [2] zhang, s., wang, l. & xiong, h. int. j. inf. secur. (2019) chaintegrity: blockchainenabled large-scal e-voting system with robustness and universal verifiability. international journal of information security. https://doi.org/10.1007/s10207-019-00465-8 [3] e. elewa, a. alsammak, a. abdelrahman, t. elshishtawy, "challenges of electronic votinga survey", advances in computer science: an international journal, vol. 4, no. 6, pp. 98-108, 2015. [4] aranha df, ribeiro h, paraense alo (2016) crowdsourced integrity verification of election results. annals of telecommunications:1–11. doi:10.1007/s12243-016-0511-1 [5] gjøsteen k, lund as (2016) an experiment on the security of the norwegian electronic voting protocol. annals of telecommunications:1–9. doi:10.1007/s12243-016-0509-8 [6] budurushi j, renaud k, volkamer m, woide m (2016) an investigation into the usability of electronic voting systems for complex elections. annals of telecommunications pp 1–14. doi:10.1007/s12243-016-0510-2 [7] neumann s, volkamer m, jurlind b, prandrini m (2016) secivo: a quantitative security assessment model for internet voting schemes. annals telecommunication pp 1–14 [8] ayed, a.b. (2017). a conceptual secure blockchain based electronic voting system. international journal of network security & its applications (ijnsa) vol.9, no.3, may 2017 [9] hsiao jh, tso r., chen cm., wu me. (2018) decentralized e-voting systems based on the blockchain technology. advances in computer science and ubiquitous computing. cute 2017, csa 2017. lecture notes in electrical engineering, vol 474. springer, singapore. [10] jonath alexander, steven lander and ben howerton (2018). netvote: a decentralized implementation of decentralized blockchain e-voting eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e4 https://shermin.net/token-economy-book/ 12 voting network available at: https://netvote. io/wp-content/uploads/2018/02/netvotewhite-paper-v7.pdf [11] https://www.tutorialsteacher.com/nodejs/whatis-node-package-manager [12] https://www.edureka.co/blog/developingethereum-dapps-with-truffle [13] https://www.codementor.io/@swader/developi ng-for-ethereum-getting-started-with-ganachel6abwh62j [14] https://www.edureka.co/blog/solidity-tutorial/ saad moin khan et al. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e4 https://www.tutorialsteacher.com/nodejs/what-is-node-package-manager https://www.tutorialsteacher.com/nodejs/what-is-node-package-manager https://www.edureka.co/blog/developing-ethereum-dapps-with-truffle https://www.edureka.co/blog/developing-ethereum-dapps-with-truffle https://www.edureka.co/blog/solidity-tutorial/ abstract 1. introduction 2. related work 3. proposed system 4. implementations and results 4. conclusion 5. references smart environment monitoring system using unmanned aerial vehicle in bangladesh smart environment monitoring system using unmanned aerial vehicle in bangladesh md. al-farabi1, muntasir chowdhury1, md. readuzzaman1, md. rafat hossain1, saifur rahman sabuj1,2,∗ and md akbar hossain3 1electrical and electronic engineering, brac university, bangladesh 2department of electronics and control engineering, hanbat national university, south korea 3department of it and software engineering, auckland university of technology, new zealand abstract greenhouse gases have influenced in enormous ways to global warming and climate change. the alarming rise of the toxic gases poses a serious threat to the future of mankind. traditionally wireless sensor based monitoring systems have been used to monitor the concentration of greenhouse gases in the environment. it is not always possible to access the area of interest to deploy the sensor node or even do maintenance in case of failure. therefore in this paper we proposed and implemented unmanned aerial vehicle (uav) based greenhouse gases monitoring system which assembles humidity sensor, gas sensors and temperature sensors. the proposed uav system equipped with sensors collect data from the atmosphere and predicting future humidity, temperature and gasses. in this paper, we collect these data from three different areas uttara, aftabnagar and mirpur in bangladesh. our analysis shows that air quality is better in aftabnagar, though it is variable depending on the different time of the day. for automatic collection of environmental sample, our proposed system mainly features high precision of aerial platform. received on 02 may 2020; accepted on 18 august 2020; published on 19 august 2020 keywords: arduino nano, environment monitoring, regression model, sensors, unmanned aerial vehicle. copyright © 2020 m. a.-farabi et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.18-8-2020.165995 1. introduction greenhouse gases are essential for the survival of all living beings on earth.these gases warm the atmosphere of the earth by holding some of the sun’s heat energy and steadies the rate at which the ultra violate (uv) rays are reflected back into space. this is known as the greenhouse effect.since the time of industry revolution which happened back in between 18th to 19th century, there has been a constant rise of the concentration of greenhouse gases and it caused an increase of the average global temperature around 1oc in earth atmosphere [1]. with the current climate policies in the play, projected temperature rise will be 3.1 − 3.7oc by 2100 and can be 4.1 − 4.8oc if no polices are applied [2]. besides the rise in average global temperature, the greenhouse effect causes the increase of the sea level by 19 cm from 1901 to 2010 ∗corresponding author. email: s.r.sabuj@ieee.org by melting the sea ice approximately 1.07 × 106 km2 per decade [3]. the primary greenhouse gases in earth atmosphere are carbon dioxide (co2), nitrous oxide, water vapor, methane and fluorinated gases. according to data published by us environmental protection agency the main proportion of greenhouse gas emission is co2. compared to all the continents in the world, asia is highest (53%) in the carbon emission, north america is the in second highest (18%) followed by eu (17%) and rest 3-4% are from africa and south america [2]. the concentration of the co2 is rising gradually since the industry revolution and considered as one of the instrument to aggrevate environmental hazard for living beings on earth [4]. like many other countries of the world, bangladesh is also facing this disastrous calamity directly. we all know that bangladesh is 10th densely populated country in the world. for keeping up the pace with the modern world the number of mills, factories are increasing rapidly and in an unplanned way. the 1 eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e1 http://creativecommons.org/licenses/by/3.0/ mailto:<s.r.sabuj@ieee.org> m. a.-farabi et al. figure 1. carbon dioxide equivalent emission from various industries in bangladesh [6]. increasing number of vehicles such as cars, buses and other diesel engines are contributing to the rise of greenhouse gases which led the country to become 135st in the list of all livable countries in the world [5]. figure 1 shows the co2 equivalent emission in bangladesh from various industries. to control and mitigate the impact of emission of the greenhouse gases, monitoring the environment is an essential activity. there are number of studies conducted to monitor the emission of greenhouse gases in the environment using wireless sensor networks [7] where a sensor node is deployed in an area of interest to collect the data.later, the data collected by the sensors is sent to a base station where the data can be stored for analysis and processing. however, it is not always possible to access the area of interest to deploy the sensor node or even do maintenance in case of failure. therefore in this paper we proposed a smart environment monitoring (smartem) method by using an unmanned aerial vehicle (uav) to collect and process the data. uav-based data acquisition is an effective solution for retrieving sensor data, even from inaccessible locations. a uav can move over the sensor network and retrieve data from the sensor nodes. this reduces energy consumption and avoids long transmission distances and redundant transmissions. an uav is built with few sensors dampness sensor (dht11), gas sensors (mq2, mq7, and mq135) and temperature sensors (tch11, tch22) to gather the information of temperature, dampness, level of co2, carbon mono-oxide (co), methane, nitrous oxide and different gases. hence, by gathering this information for certain days a mathematical model can be formulated to forecast the condition of the region. furthermore, by observing the outcome for a zone, some mitigation techniques can be planned such as planting trees, removing the factory or environment friendly manner and so on. the remainder of this paper is organized as follows. section 2 provides a brief review of related work. the working principle of the proposed smartem method is discussed in section 3. the architecture of the smartem given in section 4. section 5 presents the linear regression based forecasting method which is constructed on the data collected by uav. system implementation is discussed in section 6. results are given in section 7 followed by conclusions in section 8. 2. related works in recent years, uavs have been widely used in aerial photography, agriculture, plant protection, express transportation, disaster relief, wildlife observation, infectious disease monitoring, mapping, news reporting, power inspection, disaster relief, film and television shooting and other fields, and are becoming more and more popular. in [9], hybrid control methods for improving crucial areas of uav is proposed that both physical dynamics of the aircraft and mode switching logic are supervised under low level control. a wireless control system on uav was presented to test tension, rational speed also the wind field along with the proposal of wireless sensor network (wsn) for monitoring areas in [10]. spinka et al. developed angular rate stabilization [11], not to mention remotely operated aerial model autopilot was introduced. witayangkurn et al. introduced an uav monitoring system for remote areas by combining sos (sensor observation service) and ssg (sensor service grid) platform as a medium of collecting data from the sensor nodes and received data afterwards [12]. collecting data and demonstrating them with real time graph from sensor nodes were presented in [13]. having introduced drone as a monitoring system in [14, 15], ventura et al. and hostettler et al. made use of drone for taking images in coastal areas. a uav merging with internet of things (iot) system [16] was represented by hernandez et al. it became more responsive and accurate as a result of daq system present in it. aboubakakr et al. monitored both air quality and water quality in [17]. also, the proposed uav in [18] carries air quality sensors where real time analysis of software provides high resolution microelectronic data, information of location and data stream. in some cases uav is considered as a relay node to establish the communication between sensor node in remote location and the base station. hence the integration of uavs with other system such as wsns and iot can be a robust and efficient solution for data collection, control, analysis, and decisions in such specialized applications [19]. a review paper in [20] presented an integrated uav–wsn architecture for different applications by explaining the different 2 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e1 smart environment monitoring system using unmanned aerial vehicle in bangladesh 30a esc bldc 30a esc bldc 30a esc bldc 30a esc bldc ardupilot ublox neo-6m gps module gyroscope 6 ch an ne l t x /r x 93 3m h z t el em et ry 3s 8 00 0m a h li po b at te ry po w er s up pl y 3s 8000mah lipo battery power supply mq2 h2, ch4, smoke mq7 co mq135 air quality a rd ui no n an o at m eg a 1 68 p d h t1 1 te m pe ra tu re & h um id ity n od em cu es p8 26 6 d at a s er ve r tx rx figure 2. block diagram of proposed system model [8]. functional components of the system and collaborative techniques among them. an end-to-end platform based on integrated uav–wsn–iot system is presented in [21] for data collection from various sensors, cameras, and drones in agricultural applications. long range wide area network (lora wan) with low power wireless data communication was introduced in [22] by using iot technology to connect with the sensors for getting data. in [23] vhf, lora and 4g are chosen for different communication system to monitor natural environment by using drone and iot combined. however, in the above papers from [10] to [23] it contributed a lot in the segment of uav based data collection and processing segments by using various methods. the main contributions of this paper is to predict the future of a particular environment by processing the data that has been collected by the sensors of the uav. in addition, the sensors that has been installed in the uav will take the reading of temperature, humidity, air quality, level of co2 and co of a particular region within different time span. by processing these data that has been collected the future air quality can be predicted with a significant percentage of accuracy. this future prediction system could be a big breakthrough in case of environmental study. 3. smartem method:working principle unnamed aerial vehicle, more commonly called drone is actually an aircraft consisting of aerial control system, a ground station and communication medium. in order to give a very swift feedback uav works in some detached segments individually. this is four axis quad copter planned fundamentally for gathering information with the assistance of sensors and transfer it to the server. a 3s 8000mah lipo battery has been used as the power source which is directly connected to ardupilot and the 30a electric stability controller (esc). this 30a esc is directly connected to brushless dc motors (bldc) which is actually a motor that supplies the power to the propeller. here ardupilot behaves like the motherboard, which is connected to all the other components. likegyroscope, ublox neo-6m gps module, 6 channel transmitter-receiver, 933mhz telemetry. dji f450 quad copter frames are basically 2x6x10 inches in size and weights about 1.02 pounds which gives the uav better stabilization in the air. this drone is a reckoning of sensors and components so that it can ensure effective data collection, process as well as communication with the ground station. here ardupilot mega 2.6 (apm) is used as it provides multiple way points and an external gps support. mission planner (mp) is utilized to work as a graphical interface which is both stable and reliable. afterwards, all the following parameters of mp have been set likeaccelerometer and magnetometers. for both cases, individual calibration is monitored from mission planner platform. 3dr (air and ground) are checked for the communication process. all the motors and servo are matched from four axis diagram in ardupilot platform. taking the response from the receiver or throttle happen to be the last step before the drone is ready to fly. figure 12 shows the block diagram of the proposed smartem model and discussion on different blocks are as follows: 3 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e1 m. a.-farabi et al. node mcu clientclient mqtt broker uav sensor nodes arduino nano figure 3. communication model of the proposed system. 1. power: as a power source we have used 3s 8000 mah lipo battery which is connected to the drone’s body. this battery is highly recommendable as it gives a very good backup in case of the usage. 2. motor’s speed controller: in case of getting better stability and control over the drone we have used 30a esc which is a brushless motor controller. it controls the max current which goes to the motor, maximum output, distribution of the current to the motors, rotation of the motors and the calibration. 3. motor: we have used bldc which is basically brushless dc motor. from the power source through esc, power to the motors is supplied. the reason of using bldc are due to better the power to weight ratio, very high speed, electronic control, and low maintenance. moreover, the main advantage of this bldc is that it can rotate in both directions. 4. telemetry procedure: we have used 933mhz telemetry. it gives us information of the drone such as speed of the drone, altitude, the position of the drone. all these information can be derived via a software named mission planner. 5. stability: in order to get a superior stability and better performance we have also added gyroscope to the drone. gyroscope helps the drone to be balanced automatically. we have tried to limit our drone within lower weight (1.02 pound) so that it can help to maintain finer balancing in the air. 6. specifications: in this case, the maximum achievable altitude is 320 to 360 ft. the controlling range of the drone was 1.5 to 2 km. the continuous flight time we got was approximately 1 hour. the speed of this drone was 10km/hour. 4. architecture of smartem the smartem consists of two parts; one is data collection by using sensors. another one is the communication part. the data of humidity, temperature and the existing gases of environment have been collected. here two different approaches of communication is implemented in our smartem, which are server based communication system and radio communication. server based communication. the server based communication is functional from the sensor nodes to the virtual private server itself. here node mcu (node microcontroller unit) and lora get wi-fi hotspot as it recommends internet connectivity. however, as node mcu has only one analogue reading we have connected it to arduino nano and passed the data to node mcu through tx (transmission pin) and rx (receiver pin). in this case serial communication is applied. in nodemcu we get the information collected from arduino. meanwhile getting the data in nodemcu we started with the communication segment. we operated one of our communication through nodemcu and another through arduino. for transferring data to data server, we have 4 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e1 smart environment monitoring system using unmanned aerial vehicle in bangladesh used nodemcu since nodemcu has a built-in wifi chip for internet connectivity. before uploading the data to the server, we have used virtual private server which receives data from the nodemcu. after that, ip address is set and apache server software starts to operate. to receive the data node red is installed where mqtt protocols are followed. we have used mosquitto mqtt broker with username and password based authentication. we introduced the broker in our server and associated the broker to nodemcu using the server ip. when the connection is set up, we signed in to node red dashboard and made a flow to get data from nodemcu. while receiving all the data we have split them into different sections and upload them in database. radio communication. for radio communication system, we have used lora. by using lora module and broadcast transmission method we have transmitted the data via arduino to the drone. similarly for receiving the data we needed a ground module which is basically lora rx. so we have used two lora nodes. one was at the drone and another one was at ground station. this module receive data from the lora and respond according to the results. we have also built up a user interface with unity which gets the information from lora ground station. the collected information is exhibited using graphical user interface. moreover, we have separated the log record for each information. from the log we can easily use the data for the future. 5. forecasting method a regression model is the measure of average relationship between two or more variables in term of the original units of the data. again, a linear regression model takes input as a function of two values (one independent and one dependent) and forms a relation between them forming a line. as the independent variable is moving or changing the dependent variable also shifts in its direction. if both of them are are increasing we measure it as a positive relationship. however, in this case the dependent variable is decreasing and its taken as a negative relationship so the linear line has a negative slope. for the model to work we take observation points which are mainly output of gas parts per million (ppm) values and altitude in our model. with all the observation point taken linear regression tries to fit a straight line which fits between all the corresponding points. after finding the straight line with the help of linear regression method estimated value from equations (1) and (2), and actual value are compared and the error ratio can also be gained. in [24] the following equation for linear regression is provided: y = b0 + b1x + ε (1) where x denotes independent variable, y denotes dependent variable, b0 stands for y intersect and ε is the random error. to calculate the slope of simple linear line b1 the following equation is provided as follow b1 = ∑n j=1(xj − x̄).(yj − ȳ)∑n j=1(xj − x̄)2 (2) where x̄ represents the mean of all independent variables and ȳ represents the mean of all dependent variables. in our model we have also focused how sample data can be used for future prediction. for better accuracy of prediction linear regression gets the priority in our case. linear regression is often used to fit a predictive model to an observed dataset [25]. in future we can use collected data to compare different ml techniques such as multiregression or even classification. although mult-regression and non-linear regression can show given output as an over-fit, it is a good practice to compare the models. algorithms like trees and vector machine are suggested for better outcomes in case of classification [26]. in our model, scikit-learn library uses gradient descent algorithm for linear regression [27]. to evaluate the efficiency of linear regression model there are some error measurements like mean absolute error, mean squared error (mse), and root mean squared error. in our model we took mse values for evaluation. in most of the cases the outcome ranges from (0.04 1.12). scikit-learn metrics takes both test data and predicted data to give the outcome of mse. as the outcomes are close to zero in most of the cases it is a a clear indication that our regression model is very efficient. 6. implementation and measurement 6.1. equipment arduino. arduino nano is used as a microcontrollerbased cpu and it comes in a small size having analog input pins and digital output pins. nodemcu. nodemcu is made applicable to collect data from arduino which were collected previously from the gas sensors. besides, the built in wi-fi of nodemcu helped it to connect to other devices within its premises. lora e32-ttl-100. for communication purpose we have used lora which stands for long range communication. it generally uses ultra high frequency band for its communication having four different modes. moreover, lora is an ultra-low power consumption component and its another reason for us to use it for communication purposes. 5 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e1 m. a.-farabi et al. dht11. dht11 is used as a temperature and humidity sensor. this sensor gives the temperature data from 0 to 50 degree celsius and only 2 percent error rates for humidity data. gas sensors. various kind of gas sensors are used by us to detect the hazardous gases and the air quality index. we have used mq-2 gas sensor to detect co2, mq-7 for detecting co and mq-135 gas sensor to find out the air quality index. 7. results and discussion all the graphical presentations are output of pycharm software, where individual data points are imported from excel sheets. as regression model works in two functionone as input and other as output which demonstrates the relationship between independent variable and dependent variable. the graphical presentation provides different location of dhaka city which are uttara, aftabnagar and mirpur. x direction of each graph indicates the independent variable and y direction indicates the dependent ones. green, yellow and red lines represent the prediction lines. as these are function of two variables we can find the improvements from the prediction lines. for instance if x is constant and three values of y are y1, y2 and y3, we can find the improvement from the given equation. i1 = (y1 − y2)/y1 ∗ 100 (3) i2 = (y1 − y3)/y1 ∗ 100 (4) figure 4. altitude vs. air quality at uttara, aftabnagar and mirpur. in fig 4, the graph shows the relation between air quality and altitude in meter (m). x axis of the graph indicates altitude and y axis indicates quality of air. as the value in data of air quality increases it indicates deterioration of air quality. as a matter of fact we figure 5. altitude vs. co at uttara, aftabnagar and mirpur. figure 6. altitude vs. co2 at uttara, aftabnagar and mirpur. observe a negative slope in all three prediction lines. for example, the values for air quality are 60.34 at uttara, 59.21 at aftabnagar, 57.44 at mirpur when altitude is 30 m, which provides improvements of 1.87% and 4.81%. moreover, the values for air quality are 55.84 at uttara, 55.31 at mirpur, 51.09 at aftabnagar when altitude is 80 m that provides improvements of 0.009% and 8.51%. in fig 5, the graph demonstrates the relation between co in ppm and altitude. as the values of co increases the pollution and the effect of global warming is also increasing. interestingly from the prediction lines we observe a slight change in their characteristics as in aftabnagar area the line is nearly a constant and parallel with altitude but in uttara and mirpur co increases with height and the line follows nearly a linear direction. it is also mentioned that in all the three places the ppm of co gas are 3.854 at aftabnagar, 3.7152 at mirpur, and 3.6943 at uttara at 20.877 m for where 6 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e1 smart environment monitoring system using unmanned aerial vehicle in bangladesh figure 7. humidity vs air quality at uttara, aftabnagar and mirpur. figure 8. humidity vs co at uttara, aftabnagar and mirpur. the improvements are 3.6% and 4.14%. in addition, the values of co are 3.832 at aftabnagar, 4.064 at mirpur, 4.107 at uttara at 97.941 m for the same area where co drops 5.529% and 7.13%. in fig 6, the graph states the relation between co2 and altitude. from the prediction lines we see a slight change in their characteristics as in aftabnagar area the line is negative slope but higher than uttara and mirpur. it is also mentioned that in all the three places the ppm of co2 gas are 55.9884 at aftabnagar, 50.1806 at uttara and 50.0743 at mirpur at 29.0455 by the expressions we got improvement of 10.373% and 10.563%. again we took ppm of co2 as 50.8614 at aftabnagar, 45.5429 at mirpur, and 45.3727 at uttara where improvement of 10.4568%, 0.3737% and 10.7914% are found. figure 9. humidity vs co2 at uttara, aftabnagar and mirpur. figure 10. temperature vs air quality at uttara, aftabnagar and mirpur. in fig 7, the graph shows relation between air quality and humidity. as the value in data of air quality increases it indicates deterioration of air quality. moreover, we can observe a nearly constant line in aftabnagar area and positive slope lines in mirpur and uttara area. air quality of 56.5185 at uttara, 55.967 at mirpur, 55.8204 at aftabnagar when humidity is 91.9955 were taken and that provides improvements as 0.975% and 1.24%. in fig 8, the graph shows relation between co and humidity. with the help of prediction lines a negative slope is found in aftabnagar area and positive slope lines in mirpur and uttara area. in all these three areas the ppm of co gas varies. co of 3.8134 at aftabnagar, 3.8368 at uttara and 3.9166 at mirpur at humidity of 92.008 gives improvement that drops 0.615% and 2.71%. 7 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e1 m. a.-farabi et al. figure 11. temperature vs co at uttara, aftabnagar and mirpur. figure 12. temperature vs co2 at uttara, aftabnagar and mirpur. in fig 9, from the graph we can observe relation between co2 and humidity. with the help of prediction lines we find out a slight changes of the values such as in aftabnagar area the line is higher and has a slightly positive slope but in uttara and mirpur co2 increases with temperature and the line has positive slope as well. in all these three areas the ppm of co2 gas is 47.5427 at uttara, 48.5 at mirpur, 54.2865 at aftabnagar and from here we got improvement of 11.930% and 12.4226% at humidity of 91.9952. in fig 10, the graph shows the relation between air quality and temperature. as the value in data of air quality increases it indicates deterioration of air quality. as a matter of fact we observe a positive slope in all three prediction lines. for example, the values for air quality are 59.2305 at uttara, 55.7417 at aftabnagar, 53.1914 at mirpur when temperature is 18.028 which provides improvements of 5.89% and 10.195%. moreover, the values for air quality are 61.964 at uttara, 57.0067 at mirpur, 55.7927 at aftabnagar when altitude is 80 m that provides improvements of 8.001% and 9.9602%. in fig 11, the graph shows relation between co in ppm unit and temperature. as a matter of fact if the value of co increases it means the air quality is decreasing. with the help of prediction lines it is observed that the prediction line in aftabnagar area follows a negative slope whereas in mirpur and uttara it is a positive slope. taking ppm of co as 4.033 at uttara, 3.8442 at aftabnagar, 3.829 at mirpur and from here we got improvement as 4.68% and 5.0582% at temperature of 18.016. again we took ppm of co as 3.8307 at aftabnagar, 3.8669 at mirpur, 4.214 at uttara where improvement drops 0.9449% and 10.006% at a fixed temperature of 18.4723. in fig 12, the graph shows relation between co2 in ppm unit and temperature. in all these three areas the ppm of co2 gas varies but all the three prediction lines have positive slope. taking ppm of co2 as 53.903 at aftabnagar, 50.287 at uttara, 46.3726 at mirpur and that provides improvement of 6.709% percents and 13.971% for a fixed temperature of 18.0491. after that taking ppm of co2 as 54.5843 at aftabnagar, 52.7548 at uttara, 48.2873 at mirpur it provides improvement that increases 3.3516% and 11.5362% for a fixed temperature of 18.4725. after comparing all the data-sets, it shows that the air quality of aftabnagar is comparatively better than other two places while uttara gets the lowest air quality. in this procedure we have performed three different functions which include altitude, temperature and humidity. the analysis includes co2, co and air quality for the comparison. in uttara it is observed that the relationship between co2 and altitude is linearly decreasing. also, for the range of 80 to 90 meters we get the best fit. again, for co, it increases with height. in this observation we get the best fit in 90 m altitude. for air quality we can observe similar characteristics. when we compare the different functions for humidity a similar curve is observed which linearly deceases. for temperature there are discrete values obtained. in conclusion, it can be added that although there are random values in the graphs but for lower level of air around us pollution is heavy. as we move upward, we observe less pollution. all the random values from the fitted curve observed are nearly identical as a fixed function and also behaves accurately for a fixed range of the parameters. figs. 13, 14 and 15 are bar charts of humidity vs co in mirpur, aftabnagar and uttara where actual vs predicted data are illustrated based on testing data samples. a regression model needs splitting of train data and test data before prediction. here, we have used 8 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e1 smart environment monitoring system using unmanned aerial vehicle in bangladesh figure 13. actual vs predicted sample output at mirpur. figure 14. actual vs predicted sample output at aftabnagar. figure 15. actual vs predicted sample output at uttara. 0.2 test size which means our model used 80% data for training and 20% for testing. observing the charts, it is clear that predicted data set is very close to the testing data. sample 19 in both aftabnagar and mirpur have a significant amount of test error whereas other samples are nearly accurate. however, in aftabnagar we observe a consistent outcome in prediction having the least amount of error. 8. conclusion this research is aimed to monitor the quality of air of a particular region at different altitudes using a uav coupled with collective sensors. based on the quantitative and qualities analysis of the data derived from diverse test results of the uav in response to measure the condition of air by several parameters we can conclude that this system is effective to achieve potential remarks in the field of dealing with atmospheric changes. the test results are extracted in personal server through a wireless system. by exerting radio communication, the data were illustrated through regression model via gui. our proposed system is to use low-cost components but more constructive than other existing uav monitoring systems. references [1] q. ma, “greenhouse gases: refining the role of carbon dioxide,” nasa goddard institute for space studies. http://www. giss. nasa. gov/research/intro/ma, vol. 1, 1998. 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[24] x. yan and x. su, linear regression analysis: theory and computing. world scientific, 2009. [25] g. alipui, c. asamoah, r. barilla, l. a. clevenger, a. copeland, s. elnagdy, h. eng, m. holmes, s. jayaraman, k. khan et al., “big data machine learning algorithms.” [26] m. a. a. m. k. jain, “data mining techniques for the prediction of kidney diseases and treatment: a review,” international journal of engineering and computer science, vol. 6, no. 2, 2017. [27] s. sathyadevan and m. chaitra, “airfoil self noise prediction using linear regression approach,” in computational intelligence in data mining-volume 2. springer, 2015, pp. 551–561. 10 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e1 1 introduction 2 related works 3 smartem method:working principle 4 architecture of smartem server based communication radio communication 5 forecasting method 6 implementation and measurement 6.1 equipment arduino nodemcu lora e32-ttl-100 dht11 gas sensors 7 results and discussion 8 conclusion waste management in smart cities: a survey on public perception and the implications for service level agreements eai endorsed transactions on smart cities research article 1 waste management in smart cities: a survey on public perception and the implications for service level agreements a. mccurdy1, c. peoples1,*, a. moore1 and m. zoualfaghari2 1ulster university, uk. 2bt technology, bt group, uk. abstract introduction: waste management in cities has not advanced at the same rate as technology in general. furthermore, there is little evidence that citizens are satisfied with services in smart cities. objectives: the objective of this paper is therefore to capture citizen perspectives in relation to smart city services and, specifically, that of waste management. methods: an online survey was disseminated using google forms to twenty-five homeowners within the tourism ireland office in coleraine, northern ireland. the objective was to gather the typical citizen perspective of smart cities, their views on the meaning of ‘smart waste management’, and any features which they would like to experience with regard to their waste collection process and/or schedule in a future smart city. results: it was found that a common perception of a smart city exists, it being one concerned with efficiency and recycling; fewer citizens are, however, familiar with the term ‘smart waste management’. homeowners generally acknowledge that improvements to their current bin collection schedule are necessary. conclusion: the paper concludes with a discussion of the ways in which citizens believe that a bin collection schedule which they are in control of would be an improvement on a council-defined one. we correlate this with extensions necessary to service provisioning processes, and service level agreements (slas), to support future smart city services. keywords: smart city, waste management, citizen perspectives, survey, service level agreements (slas). received on 06 february 2021, accepted on 24 may 2021, published on 27 may 2021 copyright © 2021 a. mccurdy et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.27-5-2021.170007 *corresponding author. email: c.peoples@ulster.ac.uk 1. introduction published in 2018, it is noted in [1] that, “… the literature of iot still lacks studies on the behavioural aspect that explain the customers’ perception towards iot adoption and focuses more on technological aspect”. this is significant, recognising that we, as developers, do not generally know if citizen needs are being met in the solutions provided. this is compounded by the fact that, despite smart cities being put in place for citizen convenience, it is recognised that, “smart city initiatives are launched without the citizens’ evaluation of the improvements made to their city” [2]. this is also important, given that, “the most valuable resource of a city is its residents” [3]. the eden strategy institute acknowledges this and, when ranking the top 50 smart cities worldwide, they evaluate using factors which include, “a sincere, people-first design of the future city” [4]. “when people live in close proximity, everyone and everything must work together” [5]. it is therefore critical that the systems put in place respond to the needs of a city’s citizens. waste management in cities has not advanced at the same rate that technology has in general, and it continues to rely on a more traditional approach of collecting bins on a set schedule and route. given recent advancements in the use of technologies to make decisions in a more eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e4 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ a. mccurdy et al. 2 dynamic and responsive manner, there is clearly an opportunity to optimise this process. furthermore, citizens are diverse in their characteristics, and therefore in their use of city services – by responding to this in a more personalised way there is a further benefit of improving homeowner satisfaction. it subsequently became our aim to gain an appreciation of citizen perspectives on the concept of smart waste management, as one area of focus in smart cities. a survey with homeowners was performed, and the results capture views on the concept of smart cities in general, before focusing on smart waste management and limitations with regard to current waste collection processes. we also capture ideas on ways which citizens would like services to be improved in the future. it is our objective that the results collected through the survey will support us in our objective of understanding current perceptions so that smart city solutions may be more suitably targeted towards them. the research presented in this paper is explored within the context of waste management in northern ireland. this involves a black bin for general waste and a blue bin for recyclable waste. each bin is emptied on a fixed schedule, with the black bin scheduled one week, and the blue bin the next. there are opportunities to optimise the efficiencies of this process, in addition to improving the general satisfaction of homeowners. with a bin collection schedule on a fortnightly basis, there is the possibility of bins needing to be emptied earlier. homeowners are not however, in a position to request such a service, and if they need a more frequent service, they must take their waste to a remote collection point. furthermore, homeowners generally have very distinct characteristics, from the number of people living within a home to the average amount of waste generated. therefore, it is not logical to expect that every home is subject to an identical waste collection schedule. in the past, there have been few opportunities to personalise the waste collection process, however, the advent of smartness through modern technologies means this is now possible. it is pertinent therefore to discover not only how the technologies may be used, but also the ways in which citizens want them to be used. it is therefore in response to these objectives that the research presented in this paper is carried out. the remainder of the paper is organised as follows: in section 2, a literature review is presented on the variety of definitions of smart cities, with a view to help us to determine the extent to which our survey respondents have an accurate understanding of the concept. section 2 also contains a review the concept of smart waste management, together with a review of the way that a selection of smart waste management schemes, proposed in the literature and also in state-of-the-art deployments, operate. the research methodology supporting our survey is presented in section 3, and is followed in section 4 with a discussion of our survey results and summary findings. smart waste management challenges are discussed in section 5 and the ways in which service provisioning processes need to expand are considered in section 6. the paper concludes and considers future work in section 7. 2. literature review a smart city is one designed to operate in a manner which is optimised to the needs and behaviours of the citizens existing within it. optimisation in this context refers to systems which fulfil citizen needs and which make their lives more convenient; this includes pre-empting future needs. in line with a definition from the uk department for business, innovation and skills, this accommodates their definition of a smart city, as one which uses technologies to make a city “more liveable” [1]. it also takes into account a definition in [6], in which it is recognised that, “the anthropomorphism (attribution of human characteristics to the city) of the city is based on it being able to sense and respond to its challenges smartly”. this clearly considers a smart city as being able to adapt and continue to meet the needs of the citizens within the dynamic environment. boyd cohen classifies a smart city in six ways: smart people, smart economy, smart environment, smart government, smart living, and smart mobility [7]. cisco presents a more explicit, and perhaps less organised, classification, considering a smart city as one which incorporates technologies to influence air quality, communication architecture, environment, lighting, parking, public wifi, safety and security, transportation, urban mobility, waste management, and water management [8]. the itu-t study group 20 focuses their work on the internet of things and smart cities and communities [9]. this group is less explicit in categorising the core aspects of the iot and smart city, and instead describe it as supporting: “… increasing urbanization trends, smarter and more sustainable means of managing urban complexities, reducing urban expenditure, increasing energy efficiency and improving the quality of life for urban residents …” [10]. differences in these definitions from industrial players is important – the fact that a single distinct definition does not exist on the concept of a smart city means that it is open to variation in its interpretation. this is significant, particularly at this point in time, when the network landscape is becoming more populated and developed, and at a time when efforts are being directed into the difficult challenge of standardising this challenging environment: work is currently underway on this by the european telecommunications standards institute (etsi) [11], for example, and the european commission [12], as another. smart waste management, as one area where technology contributions can improve convenience in smart cities, can refer to the concept of dynamic waste collection, in the sense that the bin collection mechanism operates on the amount of waste as opposed to more strictly following a weekly schedule [10]. this scheme is also followed in [13], with the authors additionally eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e4 waste management in smart cities: a survey on public perception and the implications for service level agreements 3 proposing that waste stakeholders are informed of the type of waste which will be arriving at the plant in advance, such that they can plan for more effective management through recycling. while important and relevant, there is little evidence that this responds to citizen needs, or that citizen requirements have been taken into account. as a further example, ibm consider in [14] a component of smart waste management as informing others on the real-time waste situation across a city or country, and the impact of this financially and environmentally. again, it might be argued that this does not respond to the needs of citizens. in contrast, “solarpowered, iot-connected bins installed in uk borough” were reported in july 2018 by government europa [15]. the bins were deployed in pairs, with one for general waste and one for recycling. in addition to being solarpowered, with powering for the objective of communicating sensor data with a centralised data repository, the state-of-the-art bins also have a compaction system to increase bin capacity. waste levels are reported by the bin to the council for a collection strategy influenced by fill level. it is more likely that such an approach will respond to citizen needs, by avoiding situations where bins are full through reaction to customer activity. in [16], smart waste management is achieved using a route calculated on a daily basis for waste collectors, which has been optimised based on the bin levels recorded using sensors. the scheme is supplemented with ability to predict bin level using historical evidence. this information is combined with information on traffic congestion in an area to avoid situations of over-flowing bins and to achieve this in an effective and efficient manner. in an attempt to avoid an inefficient and nonoptimised solution, the authors explore effectiveness of the waste collector visiting only those areas where 70% of the waste bins have a level above a threshold. this avoids potential situations where, for example, only one bin in the region is full and the waste collector is sent to deal with to an individual bin. the smart cheap city is considered from the perspective of waste management in [16]. the efficiency of implementation here is in relation to the hardware components used, in terms of passive infrared sensors, which are a cheap way to detect motion and the voltage of the output, which means that the sensor can be connected directly with the board without the use of logical level converters. a persistent clock is also used to ease maintenance. in terms of the waste collection algorithm, the authors propose calculating the shortest path between the bins, and additionally taking into account the time to service each location. bins are categorised according to the level to which each is full. 50% capacity indicates that it can be collected in the next route planning, and is marked as yellow. 90% capacity indicates that it should be collected, and is marked as red. a collection will be scheduled when any bins are marked red, and any yellow bins will additionally be collected at this time. more recently, mahmood and zubairi (2019) describe a smart approach to waste management applied in islamabad, pakistan [17]. the system was responsible for influencing the path taken by waste collectors when considering time and distance constraints. technology supporting the end-to-end operation include range sensors, communication modules, an online dashboard, and a mobile navigation for use on collection trucks. the algorithm uses the bin waste level, which is communicated at periodic intervals to the central server. the route is calculated with a focus of minimising the number of trucks needed, and is based on where the load will be collected, where it should be transported to, and the need for any items to be off-loaded at different locations. the aim is to service a customer site once by a single vehicle, which is a challenge taking into account the variety of recyclables which might be collected. the approach positively demonstrates reduced cost and time associated with waste collection. a similar approach is described in [18], which supports bin monitoring. the proposed scheme uses rfid technology, sensors, and cloud technology. the bin weight is used to influence the decision-making process, and is provided by the rfid tag along with a timestamp, and detail on the bin location and bin owner. collecting information to influence the route collection strategy is one aspect of smart waste management. as another example, the authors in [19] identify that waste separation complicates collection processes, given that there is a need for different receptacles to hold each type of waste and that different collection trucks are needed for each type. in response to this inefficiency, they discuss the use of split deliveries for collections and for each waste stream to optimise operation. it is interesting, however, that, despite the variety of approaches in the literature which suggest similar approaches to managing waste collection, that there are few deployments in reality. developments in this area is mainly from the perspective of research, as opposed to those deploying and investing in this area. it is therefore relevant to examine the work of industrial players in this field: in terms of state-of-the-art in smart waste management schemes, the ibm intelligent waste management platform [14] collects information with a view to reducing waste management costs. waste management data collected includes the route frequency, the bin weight, and demographic information, such as income, age and building type. additionally, non-waste data can supplement this information, with relevant information including precipitation and population density. this can be processed to understand waste management finances, and an outreach portal communicates to customers on their waste management status. enevo [20] aims to overcome and avoid situations of poor waste management. this involves hourly waste management measurements. solutions are delivered by enevo to businesses, which involve training staff, deploying food waste programs, and consideration of eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e4 a. mccurdy et al. 4 alternative collection approaches for specialised items. approaches are considered for their applicability in cities, restaurants, retail, commercial real estate, and multifamily residences. big belly smart city solutions produces high-tech solar-powered bins with built-in compactors to accommodate five times the capacity of an equivalent bin. these bins are aimed to be used in public locations within a city as they can come equipped with built-in wifi access points and a range of sensors to measure pedestrian traffic walking past the bin, noise and pollution levels. the bins also have sensors to measure the fill level which is sent to their cloud-connected software clean – collection, logistics, efficiency and notification. when it reaches capacity after compacting applied, it triggers a notification to the local council, informing that it is now ready for collection. the clean software provides a visual representation of all the bins connected with their current fill level, with an emphasis on insights, analytics, and reporting tools. recycling waste streams, public space guides and route planning stakeholders not involved in the day-to-day operations instantly are able to see improvements of collections. cisco kinetic for cities waste management [21] involves real-time visualisations of waste bins for more informed decisions, and alerts about bins, in terms of fires or bin movement, to bring about citizen awareness in waste management issues. another feature of this scheme is route optimisation, with the goal of lower carbon emissions as a result of a reduced number of wastecollection vehicles needed. in an attempt to integrate the standalone solutions which have been deployed to date, cisco kenetic supports multivendor integration. this feature allows inputs into the waste management solution which are vendor agnostic. smart waste management is a relatively popular research topic, and deployment of show-case technologies can be seen. however, these are largely disjoint solutions, deployed on an ad hoc basis. in addition to the general lack of interoperability between solutions, this also results in a lack of transparency of the ways in which smart waste solutions are offered. as a consequence, there is a lack of consistency in smart waste management solution provision, and a confused understanding as to what this application involves. this work therefore seeks to understand the extent to which perceptions of smart waste management vary. 3. research methodology it is stated in [22] that, “cities are, in the end, about the people and not the systems within them”. the system must meet the needs of citizens, and be designed in such a way that the negative aspects of a society are minimised, such as social exclusion or poverty; if systems are designed ineffectively, they will exacerbate problems within a city. in relation to waste management, this could lead to overflowing bins which are unemptied or collections being organised for bins which do not justify emptying. both problems result in an ineffective use of waste management resources, from the perspectives of the bins and waste collectors, respectively. it is therefore important to understand the perspectives of citizens in general and, specific to the objectives of this paper, those who will be exposed to the smart waste collection strategy. citizens can have diverse understandings of the term ‘smart waste management’ because they may not have been communicated with in a consistent way or because they are not equally educated. we do not wish to suggest that this is a problem – instead, the objective of this work is to understand the ways in which smart city services are viewed and perceived so that solutions can be appropriately targeted to respond to these perspectives. an online survey was disseminated using google forms to twenty-five homeowners within the tourism ireland office in coleraine, northern ireland [23] from the coleraine, ballymoney, portrush and portstewart areas of northern ireland, united kingdom in 2019. seventeen people responded to our survey request. the objective was to gather the typical citizen perspective of smart cities, their views on the meaning of ‘smart waste management’, and any features which they would like to experience with regard to their waste collection process and/or schedule in a future smart city. the people who responded to the survey were within the 35-50 years old age range, with 60% male and 40% female, and living in family homes i.e., with a partner and children. qualitative analysis was used to process the survey results, which are presented in section 4. 4. survey on smart waste management the survey responses that are presented across tables 1 to 5 capture individual answers received from each respondent. the qualitative analysis of the survey responses presented in the tables discuss the issues which are agreed by the majority of participants. table 1 captures citizen perspective on the term ‘smart city’ by answering, “what does the term ‘smart city’ mean for you?” some respondents believe that a smart city is one focused on energy, efficiency and sustainability. according to these respondents, a smart city is: “a city with good recycling plans” (1.9) “eco-friendly” (1.10) “efficient in terms of energy” (1.14) this is not a surprising belief, with recognition in the literature of an overlap in the terms ‘smart city’ and ‘sustainable city’, as in [24] and [25]. a perspective which was originally more focused on sustainability has evolved to become smart city goals of a social and economic nature: “in recent years, there has been a shift in cities striving for smart city targets instead of sustainability goals” [24]. while sustainability may be part of what a smart city is about, other goals also exist, such as convenience, cost efficiency, and social inclusion. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e4 waste management in smart cities: a survey on public perception and the implications for service level agreements 5 table 1. what does the term ‘smart city’ mean for you? survey respondent id survey respondent comment 1.1 “a lot of functions are carried out online” 1.2 “a city which is up to date on technological advancements” 1.3 “a city that uses technology to better understand its needs” 1.4 “a city that anticipates your future needs” 1.5 “physical infrastructure like transport, water, waste management, lighting, etc., all connected to the internet and able to provide useful, real time information” 1.6 “i think that a smart city is an area that uses data to manage resources” 1.7 “city which uses technology to create a sustainable future for itself” 1.8 “using current data and technology to efficiently manage the running of a city/urban area – e.g., management of traffic, schools, hospitals, waste management, etc.” 1.9 “city with good recycling plans” 1.10 “eco-friendly” 1.11 “wi-fi enabled, sustainable and services all available online” 1.12 “not a term i’m familiar with before this survey” 1.13 “technology is used to manage the city” 1.14 “efficient in terms of energy” 1.15 “joined up thinking to maximise it and process across various aspects of public services” 1.16 “a smart city is an urban area that uses different types of electronic data collection sensors to supply information used to manage assets and resources efficiently” 1.17 “internet connected to the world and using data to plan and manage” this is not, however, the only perspective of a smart city, as indicated by other respondents: a number of respondent descriptions identify one aspect of smart city operation. merging the responses from multiple respondents therefore allows a more complete definition to be reached. by merging respondent responses, a smart city is: a city which is up to date on technological advancements (1.2), which can be used to better understand its needs (1.3) and to anticipate future needs (1.4) to manage the city (1.13). the physical infrastructure, like transport, water, waste management and lighting are connected to the internet and provide useful real-time information (1.5) which can be used to efficiently manage the running of a city/urban area (1.8). table 2. what does ‘smart waste management’ mean? survey respondent id survey respondent comment 2.1 “waste is sorted, weighed and recorded automatically” 2.2 “waste which is disposed of efficiently with the use of up to date software” 2.3 “waste management that uses technology to increase efficiency and help with recycling” 2.4 “that it’s easier to recycle and there’s no unnecessary packaging” 2.5 “unsure but maybe knowing how much waste is in your bins at any time, and the bin being able to schedule a pickup automatically when it gets to a certain level” 2.6 “i think it means using data to smartly control the amount of waste within a specific area” 2.7 “best systems and processes to reduce overall waste and increase recycling %” 2.8 “using data to ensure that proper waste management facilities are in place for respective city, urban and regional areas & that these waste management facilities are as efficient as possible” 2.9 “well planned recycling system” 2.10 “recycling rather than ‘conventional’ waste disposal” 2.11 “recyclable waste management” 2.12 “good recycling and waste minimisation in the first instance” 2.13 “managing waste using technology to save human time and energy” 2.14 “managing waste smartly!” 2.15 “i haven’t heard this before, but i presume it is about minimisation and collection at appropriate times” 2.16 “managing the level of waste within city bins through monitoring with sensors” 2.17 “reducing one way use of resources and having an internet enabled solution” in contrast, it is interesting to observe that fewer survey respondents are familiar with the concept of smart waste management within a smart city: “unsure, but maybe …” (2.5) “i think it means …” (2.6) “i haven’t heard this before but i presume …” (2.15) responses to the question, “what does ‘smart waste management’ mean” are presented in table 2. the responses provide evidence that society, in general, is unclear on the meaning of the term ‘smart waste management’. a number of responses are vague and do not clearly describe smart waste management. for eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e4 a. mccurdy et al. 6 example, respondents indicated that smart waste management is: “waste which is disposed of efficiently” (2.2) “waste management that uses technology to increase efficiency” (2.3) “managing waste using technology” (2.13) “reducing one way use of resources” (2.17) this provides evidence that citizens are not certain about what ‘efficiency’ means with regard to waste management, or how waste is managed using technology. several respondents consider smart waste management from the perspective of effort to reduce the waste amount: “best systems and processes to reduce overall waste …” (2.7) “i presume it is about minimisation” (2.15) this is a limited perspective of the concept of smart waste management. furthermore, this angle overlaps with the notion of a smart city being synonymous with sustainability and, essentially, recycling. a selection of the descriptions of smart waste management consider it more explicitly from the perspective of recycling. for example: “that it’s easier to recycle” (2.4) “well planned recycling system” (2.9) “recycling rather than ‘conventional’ waste disposal” (2.10) “recyclable waste management” (2.11) again, this is a limited perspective of what smart waste management involves. some respondents did, however, recognise the ‘correct’ meaning of this concept. we consider ‘correctness’ from the perspective of the state-of-the-art waste management solutions presented in section 2. descriptions which we consider to be more representative include: “knowing how much waste is in your bins at any time, and the bin being able to schedule a pickup automatically when it gets to a certain level” (2.5) “managing the level of waste within city bins through monitoring and sensors” (2.16) it is on the basis of these definitions that the research is presented in this paper. 5. smart waste management challenges from the survey, some interesting points are raised: in the case of the smart waste management scheme, which typically involves a sensor integrated in a bin and the bin level autonomously being communicated to the waste collection depot for collection once it passes a threshold level, this introduces new challenges. for example, the homeowner needs to be aware that their bin collection has been autonomously scheduled so that they may leave the bin outside the property for pickup. if this is not done, the waste collectors would need permission to enter the property to collect the bin. without permission, the bin will be unable to be collected. in both instances, the intended objective of improved efficiency of the smart waste management scheme will have failed. a further notable finding is that homeowners acknowledge improvements are necessary with regard to their current bin collection schedule, and would ideally involve collections with greater frequency. again, this does not indicate that the new scheme will operate with improved efficiency, as one goal is to optimize the need to collect bins on a set schedule. however, the fact that respondents made this comment confirms that there is scope for improvement of the current collection approach. influencing the collection strategy in a manner convenient for citizens and more efficient overall is one approach to provision waste management in smart cities. through the survey, we wished to identify any further ways in which waste management could be modified to respond to needs. survey respondents were therefore asked: “are you dissatisfied with any aspect of your bin collection schedule?” the responses in table 3 validate that citizens are generally unsatisfied with their waste collection service, as the majority have an opinion on how it could be improved. this also indicates that waste collection is relatively important in their lives, given the fact that so many have opinions on it. these citizens are not exposed to smart waste collection services; their feedback could therefore be used to help to understand the way in which smart city services could be put in place. there is a table 3. are you dissatisfied with any aspect of your bin collection schedule? survey respondent id survey respondent comment 3.1 “no” (x 5) 3.2 “recyclables could be broken further down” 3.3 “often too far apart, sometimes the bin is over capacity, other times there is plenty of room in it” 3.4 “it would be good if we had a bin for garden waste” 3.5 “yes, my bin is often not collected for unknown reasons” 3.6 “recycling/organic waste is only bi monthly and this is inadequate especially if you are grass cutting or have lots of cardboard to recycle” 3.7 “not all bins need collected as often as they are and some need collected more regularly than they are collected” 3.8 “generally it’s a good service, but recycling collections can be troublesome if you accidentally try to include something that’s not on the approved list” 3.9 “could do with being emptied more over holiday periods” 3.10 “remembering which bin on alternate weeks is mildly frustrating in this techie age” eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e4 waste management in smart cities: a survey on public perception and the implications for service level agreements 7 feeling in the citizen responses that personal scheduling of the waste collection schedule would be a benefit, given that “sometimes the bin in overflowing, other times there is plenty of room in it” (3.3), and “not all bins need collected as often as they are and some need collected more regularly than they are collected” (3.7). responses also indicate that citizens have dissatisfaction with the recycling collection service, in particular. for example, a feeling is that “recyclables could be broken down further” (3.2) and “recycling/organic waste is only bi monthly and this is inadequate” (3.6). there is also a feeling that technology could reasonably be expected to support the waste collection service, with an opinion that “remembering which bin on alternate weeks is mildly frustrating in this techie age” (3.10). given opinions in [10] which acknowledge that smart city services are generally launched without the approval of citizens, we wished to capture how our survey respondents believed that their waste collection service could be improved, such that recommendations could be made to provide a service which responds to society’s needs. respondents were therefore asked: “how could bin collection services be improved?” responses are presented in table 4. one of the responses to this question makes a particularly interesting point, which may become a larger problem once or if smart waste technology is deployed. this respondent recommends one modification to their bin collection service as, once the bin level sensor technology has identified that the fill level is above a threshold and has scheduled a collection, “could they … have permission to enter and remove so i don't always have to remember to put bin out and which color is being collected on which date” (4.11). in the case that a bin has been scheduled for collection autonomously, the homeowner may not be aware of this fact and they may not be at home in order to place the bin for collection – the bin may therefore not be positioned at the front of the house for its collection. if the bin collector has permission to enter the property to empty the bin, this will increase the time associated with a collection and therefore its efficiency. similarly, if the collector does not have permission to enter the property, the efficiency of the pickup will be reduced by not collecting at least one of the bins on the planned route. recycling is identified as a priority area: “recyclables could be better sorted” (4.1) “more information on recycling and bottle banks” (4.2) “incentives could be introduced to encourage better recycling” (4.8) several responses indicate concern with the frequency of collection, with respondents desiring: “greater frequency of collections” (4.1) “more frequency” (4.2) “perhaps a more frequent collection for black bins as these appear to be the bins that fill up the quickest” (4.6) table 4. how could bin collection services be improved? survey respondent id survey respondent comment 4.1 “greater frequency of collections, recyclables could be better sorted” 4.2 “more frequency and more information on recycling and bottle banks” 4.3 “i am not sure” 4.4 “don’t know” 4.5 “bins are collected when they are full, not when scheduled” 4.6 “perhaps a more frequent collection for black bins as these appear to be the bins that fill up the quickest” 4.7 “rename bins (black, green, etc.) in a way which relates to their impact on environment” 4.8 “it seems ludicrous that the same charges are applied to six person and one person households as the latter would generate much less waste. incentives could be introduced to encourage better recycling. also there should be fines imposed for those who stuff their bins to capacity and end up littering the general area as bins are too full.” 4.9 “no” 4.10 “a reason as to why a bin is not collected would be useful” 4.11 “could they know (by smart technology) when to collect and have permission to enter and remove so i don't always have to remember to put bin out and which color is being collected on which date.” 4.12 “collect some bins more frequent than others” 4.13 “collect slightly later in the day – after rush hour” 4.14 “would be better if the bin men didn't throw the bins around and break them into bits” 4.15 “identified days for electrical or bulky items” “collect some bins more frequent than others” (4.12) the fact that respondents desire their bins to be collected with greater frequency indicates that there are times when bins are full yet homeowners have to wait for the next scheduled collection. if bins are collected as soon as possible after they are full when a smart waste management mechanism has been deployed, there will potentially be a collection strategy which is executed with greater frequency than at present; this does not fulfil a smart waste management goal of improved efficiency. this is an aspect which needs to be managed separately. furthermore, in the collection of bins which are full, there may be less efficiency than if every bin in a street were collected, regardless of its fill level. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e4 a. mccurdy et al. 8 this inefficiency is acknowledged by respondents in their response to the question, “how do you think that a bin collection schedule which you are in control of would differ from the one which the local council has defined?” responses are presented in table 5. in terms of efficiency, respondents consider that a citizen-centric waste management mechanism: “would be more frequent but cost more” (5.1) and even that it might lead to: “inefficiency and chaos” (5.3) this response is interesting, in recognition of the fact that respondents realise the difficulties associated with the approaches they potentially desire from smart waste management solutions. other respondents do not have any expectations: “don’t know” (5.4) “not sure” (5.6) “would be similar” (5.11) another common opinion is the need to collect more types of waste, including “bulky items and garden waste” (5.12). however, it is also interesting, that beyond general inefficiency concerns, respondents do not identify any other challenges associated with smart waste management, such as a bin collection being scheduled when the homeowner is not expecting it, and the table 5. how do you think that a bin collection schedule which you are in control of would differ from one which the local council has defined? survey respondent id survey respondent comment 5.1 “would be more frequent but cost more” 5.2 “more frequency” 5.3 “inefficiency and chaos. one run of all the houses once a week is better than bin trucks coming and going every single day” 5.4 “don’t know” 5.5 “it would be much better and more environmentally friendly” 5.6 “not sure” 5.7 “more flexible and more things collected” 5.8 “you would decide when the bin needs collected and therefore not have to plan to a predefined schedule” 5.9 “more communal bins” 5.10 “i think sometimes i wouldn’t need rubbish collected, so actually it would decrease the amount of times i’d need them to collect” 5.11 “would be similar” 5.12 “more pick ups for bulky items and garden waste” 5.13 “there would be better recycling facilities and fines for contamination of recycling bins. costs would be determined based on household waste production rather than a general "one size fits all" fee.” subsequent impacts that this can have. this provides further evidence that respondents do not fully understand the term ‘smart waste management’. in this paper, it is our aim to gain an appreciation of citizen perspectives on the concept of smart waste management, as one area of focus in a smart city. our survey results indicate some degree of consistency in that citizens are largely unclear on the smart city concept, and what smart waste management involves. to summarise our findings: there is overlap in understanding in relation to what a smart city is and general sustainability concepts, with respondents believing that a smart city is one in which sustainability is prioritised. this misconception follows into understanding of the term 'smart waste management', with some considering this aspect of smart cities to be primarily involved with recycling. in general, homeowners acknowledge that improvements to their current bin collection schedule are necessary: some are dissatisfied with the recycling collection service, and some believe that technology could support the process in a more effective way. interestingly, citizens recognise the challenges of provisioning an improved smart waste management service, and are sympathetic to the fact that service improvements have not been made to date. to relate our findings to studies within the field: the literature examines the extent to which smart cities are citizen-focused, as in [26]; this is an obvious question to ask, given that smart cities are purported to be rolled out to improve the lives of citizens [27]. it is reported that smart cities in general are not citizen-focused; our findings concur with this, given the general dissatisfaction with current waste collection services. smartivists, a relatively recent term, describes citizens who take active steps to contribute to the smart city concept voluntarily [28]. while this is difficult to achieve in the case of waste management, given that it is the government who controls this service, we believe that our survey respondents have gone some way in demonstrating their ability to operate in this role, through their suggestions as to how waste collection processes may be made more satisfactory. it is also widely recognised that, “citizens must be involved in creating smarter digital cities” [29]. we believe that the results of our survey contribute a range of perspectives on the scope for improving the transparency of smart city and smart waste management concepts, in addition to opinions on how waste management can be improved. the survey findings can be applied in the field. they demonstrate that there is opportunity to improve transparency of the terms ‘smart city’ and ‘smart waste management’ to bring the general citizen perspective in line with the reality. the survey responses also give specific ideas on ways in which waste collection processes could be adapted to fulfil citizen desires across smart cities. this takes into account, for example, facilitating greater sorting of recyclables, in addition to having greater frequency of collections. application of the findings in another or a more general field can also be achieved through identification that citizens generally want more flexibly in their service, a fact which could be eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e4 waste management in smart cities: a survey on public perception and the implications for service level agreements 9 applied to most, if not all, iot domains. the smart city, enabled by iot technology, is one which makes the lives of citizens easier and more comfortable. the survey responses provide recommendations as to possible ways in which this could be achieved in relation to waste management, considering, for example, that some citizens would appreciate a greater service frequency and greater responsiveness from waste collectors. one respondent in particular noted a desire to move away from a “one size fits all” approach to waste management. the degree of personalisation which is possible as a result of iot technology allows this to be achieved across the supported domains. of course, there are associated challenges of operating in this way including, for example, increased costs. further investigation which considers how this might be accommodated within our programme of work is therefore presented in section 6. 6. implications of our findings on the service level agreement (sla) provisioning process without a common and realistic understanding of what smart cities and smart services involve, there is potential that customers will not participate as actively as they might otherwise, and they may take on a service plan which is inappropriate for their needs. our findings reveal that citizens want access to services which they are in control of. this may lead to a greater range of waste items being collected, being collected on a flexible schedule, and fines being charged for customers who do not comply with the terms of their sla. such a strategy leads to a need for sensor readings being passed from the bins to a centralised data repository, at a rate which might vary depending on the frequency of change in the fill level, or some personal characteristic e.g., age or location, which can be used as a proxy for a citizen’s waste disposal behaviour. service level agreements are typically defined today using a basic set of attributes, which can include the number of messages a user intends to send or the amount of storage space which they want to use. users who are participating in smart city services, however, may not have that technical expertise to know how their service should be personalised – they just know that they want certain outcomes from a particular service, such as ondemand collection. it then becomes the responsibility of the provider to understand this, to ensure that the user achieves a quality of experience (qoe) that they are satisfied with. this drives a need for slas which are flexible, with the option of adapting the terms of their agreement after a customer has agreed to it, for example, by scaling the volume of operations which a customer is involved in. this goes beyond the capabilities which exist in the sla provisioning process today. it might therefore become the case that an ontology is created to support the smart waste management process, which can be populated and subsequently probed by a service provider to understand the suitability of the service being provided in responding to customer needs. similarly, the data collected via the ontology can be probed by waste collectors to appreciate the customer needs for their waste collection, in addition to their satisfaction with the services provided. operating such an approach leads to opportunities for new business models to bill the parties engaged in this process – where we have a service provider, city council, homeowner, and potentially third parties involved in this process, this becomes a significantly more complex billing process than we see today. nonetheless, the smart city is in itself a business model, and it is for the purpose of revenue generation that partners engage. there are subsequently significant implications arising from making a decision to operate the smart waste management domain according to the opinions and perspectives captured in this paper through our homeowner survey. we are considering the range of aspects discussed in this section in our further work. 7. conclusions while waste management can be smart, it is not always obvious in the approaches described in the literature if they are truly efficient. the state-of-the-art in waste management does not go far beyond a route planning schedule dictated by the fill level of bins, which is identified using sensors deployed on the bin and is communicated back to the waste collection depot. this is intended to improve efficiency of the process by initiating the waste collection process only when bins are full and avoiding needlessly collecting bins which have been filled below this level. this does not, however, take into account the number of bins which have been filled above the threshold when scheduling collections, therefore ensuring that once a collection has been scheduled, that there is also a threshold number of bins being emptied to maximise the efficiency of the collection. there is therefore a challenge introduced in smart waste management by the variable rate at which bins are filled. if the bin collection does not take place within a relatively short time period after the fill being identified and the route has been dynamically determined, there is potential that the route will no longer be the most efficient. respondents to this survey reveal that, while waste management is an important part of their lives, they do not have a clear understanding of the concept of smart waste management, and that they do not fully appreciate its consequences. references [1] alhogail, a. improving iot technology adoption through improving customer trust. technologies 2018, 6(3). 64, jul. 2018, pp. 1-17. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e4 a. mccurdy et al. 10 [2] ceballos, g. r., larios, v. m. a model to promote citizen driven government in a smart city. proc. of ieee international smart cities conference, sep. 2016, pp. 1-6. [3] ceballos, g. r. and larios, v. m. a model to promote citizen driven government in a smart city: use case at gdl smart city. proc. of ieee international smart cities conference, sep. 2016, pp. 1-6. [4] eden strategy institute. top 50 smart city governments. 2018. available: https://www.smartcitygovt.com/ (last accessed: 25 jan. 2020). [5] iso. smart cities. iso focus+, vol. 4, no. 1, jan. 2013; issn 2226-1095. [6] liotine, m., ramaprasad, a. and syn, t. managing a smart city’s resilience to ebola: an ontological framework. proc. of 49th hawaii int. conf. on system sciences, jan. 2016, pp. 29352943. [7] cohen, b. the smart city wheel. may 2013 [online]; available: https://www.smartcircle.org/smartcity/blog/boyd-cohen-the-smart-city-wheel/ (last accessed: 25 jan. 2020). [8] cisco. what is a smart city. [online]; available: https://www.cisco.com/c/en/us/solutions/industries/smartconnected-communities/what-is-a-smart-city.html (last accessed: 25 jan. 2020). [9] itu-t. sg20: internet of things (iot) and smart cities and communities. [online]. available: https://www.itu.int/en/itu-t/studygroups/20172020/20/pages/default.aspx (last accessed: 25 jan. 2020). [10] itu-t. smart sustainable cities at a glance. [online]. available: https://www.itu.int/en/itu-t/ssc/pages/infossc.aspx (last accessed: 25 jan. 2020). [11] etsi. smart cities. [online]. available: https://www.etsi.org/technologies/smart-cities (last accessed: 25 jan. 2020). [12] joinip. smart cities / technologies and services for smart and efficient energy use. [online]. available: joinup.ec.europa.eu/collection/rolling-plan-ictstandardisation/smart-cities-technologies-and-servicessmart-and-efficient-energy-use (last accessed: 25 jan. 2020). [13] aazam, m., st-hilaire, m., lung, c-h. and lambadaris, i. cloud-based smart waste management for smart cities. proc. of 21st ieee international workshop on computer aided modelling and design of communication links and networks, oct. 2016, pp. 188-193. [14] ibm. ibm intelligent waste management platform. [online] ibm white paper, dec. 2015. available: https://www.govloop.com/wpcontent/uploads/2015/12/intelligent_waste_management_p aper_-_final_12152015.pdf (last accessed: 25 jan. 2020). [15] government europa. solar-powered, iot-connected bins installed in uk borough. jul. 2018. available: https://www.governmenteuropa.eu/solar-powered-iotconnected-bins/89545/ (last accessed: 25 jan. 2020). [16] marchiori, m. the smart cheap city: efficient waste management on a budget. proc. of 19th int. conf. on high performance computing and communications, 15th int. conf. on smart city, and 3rd int. conf. on data science and systems, 2017, pp. 192-199. [17] mahmood, i. and zubairi, j. a. efficient waste transportation and recycling. ieee electrification magazine, sep. 2019, pp. 33-43. [18] catarinucci, l., colella, r., consalvo, s. i., patrono, l., salvatore, a. and sergi, i. iot-oriented waste management system based on new rfid-sensing devices and cloud technologies. proc. of 4th international conference on smart and sustainable technologies, jun. 2019, pp. 1-5. [19] lu, j-w., chang, n-b., liao, l., and liao, m-y. smart and green urban solid waste collection systems: advances, challenges, and perspectives. ieee systems journal, vol. 11, no. 4, dec. 2017, pp. 2804-2817. [20] enevo homepage. available: https://enevo.com/ (last accessed: 25 jan. 2020). [21] cisco. cisco kinetic for cities waste management. [online]. available: https://www.cisco.com/c/en/us/solutions/industries/smartconnected-communities/kinetic-for-cities-wastemanagement.html (last accessed: 25 jan. 2020). [22] burdett, r. the heart of the city. financial times, apr. 2010. available: https://www.ft.com/content/102bd24a38d4-11df-9998-00144feabdc0 (last accessed: 25 jan. 2020). [23] tourism ireland homepage. available: https://www.tourismireland.com/. [24] h. ahvenniemi, a. huovila, i. pinto-seppa and m. airaksinen. what are the differences between sustainable and smart cities? elsevier cities, vol. 60, part a, feb. 2017, pp. 234-245. [25] greco, i. and bencardino, m. the paradigm of the modern city: smart and senseable cities for smart, inclusive and sustainable growth. proc. of the international conference on computational science and its applications, jun. 2014, pp. 1-19. [26] sánchez-teba, e. m. and bermúdez-gonzález, g. j. are smart-city projects citizen-centered? mdpi social sciences, 8, 309, nov. 2019, pp. 1-9. [27] wendorf, m. smart cities initiatives around the world are improving citizens’ lives. interesting engineering, available: https://interestingengineering.com/smart-citiesinitiatives-around-the-world-are-improving-citizens-lives (last accessed: 25 jan. 2020). [28] bee smart city. rise of smartivist. available: https://hub.beesmart.city/smartivists/rise-of-the-smartivistthe-importance-of-smart-citizens-in-smart-cities (last accessed: 25 jan. 2020.) [29] walker, a. citizens must be involved in creating smarter digital cities. infrastructure intelligence, oct. 2019. available: http://www.infrastructureintelligence.com/article/oct-2019/citizens-must-beinvolved-creating-smarter-digital-cities (last accessed: 25 jan. 2020). eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e4 a comparative study of challenges and strategic management: lessons learned from sars, mers, hiv & ebola outbreaks 1 a comparative study of challenges and strategic management: lessons learned from sars, mers, hiv & ebola outbreaks sweta saraff1,*, rishipal2, camelia bhattacharyya3, debangana brahma3 and sagnik nag3 1amity institute of psychology and allied sciences, amity university, kolkata, india. ssaraff306@gmail.com, ssaraff@kol.amity.edu 2skill faculty of applied sciences and humanities, shri vishwakarma skill university, haryana, india. rishipal_anand@rediffmail.com 3amity institute of biotechnology kolkata, amity university kolkata. abstract introduction: the challenges related to several viral outbreaks spanning over the centuries have exceeded human resources and capacities of the health departments to deal with the consequent adversities. each epidemic or pandemic faced has brought out the inequalities and gaps in our systems and infrastructure. objectives: the focus of the current paper is to do a comparative study of complex challenges faced and strategies adopted by governments during the sars, mers, hiv, and ebola outbreaks. methods: to achieve the objective, a comprehensive summary of the challenges that the world has faced, and lessons learned from the strategic management of these viral outbreaks were analysed. conclusion: an inclusive approach for the development of a multi-pronged strategic framework to benefit the concerned or affected stakeholders is discussed. these actions can guide health care workers and individuals to be aware of health hazards and complexities. keywords: virus, covid19, strategic management, public health, epidemics. received on 28 june 2020, accepted on 4 september 2020, published on 05 october 2020 copyright © 2020 saraff, s. et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.5-10-2020.166544 *corresponding author. email: saraff, s., ssaraff306@gmail.com 1. introduction in this study, some viral infections that have posed a threat to the community are examined. they are either communicable or have the capacity to spread rapidly through other media if left unchecked. the people directly involved in fighting or facing these illnesses have learned valuable lessons that need to be passed on and remembered for facing future epidemics or pandemics, like the year of 2020, with sars-cov-2, so that such viral illnesses can be controlled. it necessitates all the stakeholders, i.e. individuals, communities, local and central governments, international organizations, health care workers, scientists, and researchers, to remain vigilant about other novel or mutated viral illnesses take lessons from the past. an attempt was made to summarize the underlying aetiology of the different viruses (sars, mers, ebola, and hiv), their spread, the challenges faced in tackling them, and the lessons learned. if left unchecked, an epidemic can disable eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 http://creativecommons.org/licenses/by/3.0/ sweta saraff et al. 2 and scar entire communities for a very long time. the current work explores various strategies for public health policies to incorporate them in the provision of prompt and state of the art medical care. the viruses of interest in this paper, namely hiv, sars, mers, and ebola, are all epidemic in nature [1]. each of them has struck fear in the hearts of the global community and has unveiled the weaknesses or strengths of the public health care system, the respective governments, how active the global community is, and our flaws. each of these viruses has the capacity of turning into an epidemic or a pandemic the moment the health care system stops being vigilant, or we stop observing proper hygiene standards for ourselves [2]. 2. discussion on different viral infections 2.1. the ebola virus the largest and worst outbreak of ebola, of the 16 outbreaks [3], happened in west africa, march 2014, where 28,616 people were affected, and 11,315 died in 6 countries [4]. ebola directly attacks the immune system of a human. the virus first infiltrates the dendritic cells, the brain of the immune system -taking it hostage and causing all the other wbcs to die as it infects and replicates them. it then starts spreading and invading the host's lymph nodes and vital organs, like the kidney and the liver, causing them to lose function. ebola only exists in body fluids; that is, it cannot be transmitted through touch (e.g., chickenpox), surfaces (e.g., sars-cov-2), or the air (e.g., influenza virus), and can only be transmitted through saliva, blood, mucus, vomit or faeces. therefore, even an infected person is unlikely to transmit the illness until he shows symptoms [5]. there is mounting cell death in the body, and this triggers an immune system overload or a 'cytokine storm'-an explosion for an immune response that leads to both internal and external bleeding. the extreme fluid loss and body complication can prove to be fatal in 6-16 days of the first symptoms. ebola has a 100% death rate if the patients are not looked to properly. proper rehydration, symptomatic treatment, and care can significantly reduce the mortality rate from 90% to 25% [6]. 2.2. sars severe acute respiratory syndrome-related coronavirus (sars-cov) was believed to be the main reason behind the sars outbreak. to date, two strains of the sars have caused outbreaks in humans. there are several other strains, most of which have been found in horseshoe bats proving it to be the major, or we might say the main host reservoir for these viruses. these coronaviruses are among the largest among all rna viruses, being 30 kb positive-sense, singlestranded, and enveloped rna viruses [7]. 2.3 mers-cov middle east respiratory virus is classified into two clades (clade a and clade b). these are different from sars. there are about 1,813 cases of mers reported until 2016, with 645 deaths (mortality rate ~36%), in 27 nations worldwide [8]. mers was first found in saudi arabia in 2012. this virus is also noted to have come from bats. camels in oman are also known to have developed antibodies against this virus. ali mohamed zaki isolated the first strain from the lungs of the saudi patient, and it was identified as an unknown coronavirus [9]. cytopathic effects (cpe) were found in the isolated cells. these were round and of syncytia formation [10]. sars-cov uses the spike proteins (s-proteins) to bind with the angiotensin-converting enzyme 2 (ace2) of the host cells to invade it. in contrast, mers-cov uses the dipeptidyl peptidase 4 (dpp4) in place of the primary receptor [11]. the sars virus can lead to the lungs' failure by causing severe inflammation in the organ, finally leading to respiratory orders and fibrosis. the coronaviruses have made a massive impact on the mental health of the people affected by it and the people around them. both the viruses had been present in other mammals such as bats, camels, pangolins, etc. for years and strains had been isolated, but more research wasn't done before the situation went out of control. even when who had declared that the sars might become a pandemic which it has now in the form of sars-cov 2, there weren't enough measures taken, and research was mostly focused on the previously essential subjects. also, the health care alert wasn't imposed for a longer time. when the pandemic planning started back in the early 2000s, a better infrastructure to control a future outbreak was expected. still, it wasn't found, resulting in more deaths due to mutations in the virus genome. 2.4. hiv the human immunodeficiency virus, or hiv, at the primary level, strikes and knocks off the immune structure, exclusively the t cells. the active transmission of the deadly virus occurred mainly through bodily fluids like blood, semen, vaginal fluids, anal fluids, and breastmilk. traditionally, hiv has mostly spread through unguarded sex, the sharing of used and contaminated needles used for drugs/ medicines, and can pass from hiv infected mother to child. over time, hiv can obliterate many t-cells that the body can't brawl infections and diseases, ultimately resulting in the foremost relentless kind of an hiv contagion: acquired immunodeficiency syndrome, or aids [12]. someone with aids is incredibly prone to cancer and critical infections, like pneumonia. though there is no cure for hiv or aids, someone infected with hiv who receives treatment early can have a lifespan similar to someone without it [13]. there are majorly two types of human immunodeficiency virus found, namely hiv1 and hiv2, globally, hiv1 is mostly held responsible for the hiv outbreak rather than the hiv2 strain. this lethal strain of hiv1 is zoonotic, i.e., a pathogen transferred from an animal to humans. thus, it is closely related to a virus found in chimpanzees, which are of the subspecies pan troglodytes inhabited in the dense forests of eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 a comparative study of challenges and strategic management: lessons learned from sars, mers, hiv & ebola outbreaks 3 central africa. in 1999, the scientists came with the hypothesis of the origin of this viral strain that underwent a lot of genetic mutations to be the hiv that we know of today. they came with the idea that the virus might have transmitted from the african hunters who shot chimpanzees and ate their contaminated flesh [14]. 3. challenges faced by communities & public health department during viral outbreaks a pandemic could be a global conflict that impinges on all sectors of society and places virtually every individual in jeopardy, autonomous of societal or financial status, racial origin, or gender [15]. challenges emerging from epidemic infectious ailment outbreaks are more efficiently met if conventional public health is improved by sociology. the main focus is sometimes on biomedical facets, the surveillance and sentinel organization for infectious contagions, and what has to be done to restraint outbreaks. social factors linked with communicable disease outbreaks are habitually deserted, and therefore the repercussion is ignored. these factors can hit epidemic severity, pace, and degree of reach, influencing the wellbeing of victims, their kin's, and their communities [16]. 3.1. testing, tracing, and isolation through observation and continuous surveillance, the adequate information, required to contain a contagion menace is collected, and the general public is notified. it further provides early caveats, describes transmission incidence, attributes, frequency, occurrence, and supports a targeted rejoinder & response. fast diagnosis, isolation of infected cases, tracing the source, screening the contacts, medical reporting, contact tracing, contact listing, and active monitoring are its key features. usually, public health officials should collect an individual's consent before conducting any clinical tests, and focused education can help persuade susceptible to comply with discretionary testing. there are also exceptional times when obligatory testing is crucial to enhance the general public health care sector [17] [18]. communities that suffered from pandemics have closed public places (schools, colleges, malls, occupational centres, mass transit, airports, and ports) and avoided almost all public events (sports, extra-curricular activities, examinations, conferences, meetings). steps that are as coercive as selfquarantine, seclusion or confinement, should only be used when an ailment is acknowledged by substantial scientific study to be transmittable and may be limited to people that have been exposed to the ailment [19] [20]. 3.2. herd immunity herd immunity is the phenomenon of acquired immunity among at-risk populations due to few individuals becoming immune to the infection through vaccination or natural infection, thereby reducing the susceptibility of infection among high-risk individuals. if the population or individuals achieve acquired immunity, then the risk of infection is reduced significantly [21]. herd immunity against these viruses is critical since preparing every individual in a community to fight against such viruses would stop the spread [22] [23] [24]. while there is a vaccine for diphtheria, measles, mumps, pertussis, polio, rubella, smallpox, and influenza, ebola vaccines, although proven effective, are not being used due to questions on the effectiveness of the vaccine over a long period, and also the vaccination would be costly. several patients who were tried to be vaccinated in west africa during the ebola outbreak refused to vaccinate [25] [26]. there is also no vaccine developed to date for the coronaviruses like sars and mers. it is essential to educate people to save people against viruses by making a scheme and investing more funds for medical purposes. 3.3. availability crises of primary health care access to primary health care possesses significant challenges in saving lives. lack of coordination among concerned stakeholders at various levels of government brings out glaring deficits in primary health care in most underdeveloped & developing nations. limited medical supplies, medicines, ventilators, oxygen cylinders, masks, goggles, shields, ppe kits for front care providers of healthcare services, paralyzes the healthcare department due to constant exposure to viruses. proper infrastructure at primary health care settings is instrumental in reducing mortality rate and data collection for control of the disease. initial inadequate supplies of protective gear led to the spread of sars, and similar was the situation with other global pandemics [27] [28]. ebola virus paralyzes healthcare facilities in most affected african countries, continuously struggling with financial resources and advanced medical setups to provide accessible medical care at affordable costs. most of the patients in liberia faced a humanitarian crisis amidst pandemic due to the exhaustion of government health facilities [29]. 3.4. health crises-infection transmission in medical staff & sanitation workers there is an excellent chance for the healthcare personnel (hcps) to get infected with the virus. about 1 to 27 percent, 11 to 57 percent, and 2.5 to 12 percent of the hcps in the cases of mers, sars, and ebola are reported to have been affected [30]. the fatality rate is also high in most cases since the hcps have to stay close to patients of all stages. so, the early detection of those suspected of infection with these kinds of viruses, preparing against any outbreaks at both national and international levels, and publishing proper guidelines to fight against the infections is vital. 3.5. policy issues in public health eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 sweta saraff et al. 4 governments must share factual data to save humanity from virulent outbreaks. sharing such data at regular intervals by countries with vast populations and the shortage of resource centres can be a massive global challenge. there must be coordination between research and its implementation, as the time lag makes the research redundant and expensive. governments need to promote healthy practices that remove cartel formation among pharma companies and hospitals, leading to expensive life-saving drugs and vaccines. the deficit of public trust for government services is also a significant lacuna in public health policies [31]. 3.6. policy issues in mental health governments worldwide are scrambling to take whatever precautionary steps are required to keep the coronavirus from spreading and transmitting to more individuals. a global lockdown and calling in almost all medical and health care workers to the front line is one step that is common worldwide. however, with the global attention focused on the rising number of infected patients and the frontline responders, a silent illness spreads its roots in households and individual people's lives worldwide. the number of people suffering from mental health conditions in less developed countries is as high as 80% [32]. needless to say, that people suffering from mental health conditions are even more vulnerable now that they are away from their loved ones, friends, family members, caregivers and are unable to reach out to therapists effectively. even under normal circumstances, india has a scarcity of mental health professionals. there is > 1 mental health professional per 100,000 individuals in india [33]. therefore, it is evident that these services will become even scarcer during pandemics, causing these patients to spiral more profoundly into the web of debilitating mental illness as the governments around the world almost forget this collateral. apart from this, even those without a history of mental illness may experience mental health problems such as anxiety or even depressive disorders in extreme cases. it could be due to several reasons: isolation, shortage of money, loss of a month or more, loss of a job, stress, etc. [34] [35]. 3.7. policy issues related to socio-economic challenges the communication between commune stigma, consequences of isolation, the shortage of economic assets, and other blockades reveal that these factors must all be addressed collectively, to cut down their collective impact and perk up hiv/aids prevention and treatment in rural areas. certifying enhanced awareness in metropolitan & urban settings will necessitate a fresh accent on reinforcing capacities to handle outbreaks and other health emergencies and pandemics. countless efforts are pertinent across all settings, urban or otherwise, like having a decent indulgence of the neighbouring socio-economic and cultural milieu and a vigorous association of communities and native influential leaders in both scheduling, planning, and implementation [36][16]. lockdown creates several problems, not just for the citizens but also for the economy of the country. tourism and other exports and imports are put to a halt, which affects several people involved in trade and commerce and travel and tourism. a large number of families who were previously well settled, face a crisis of food due to a fall in the family income. while most of the ones from the below poverty level get help from the government and the rich ones already have enough, it's the middle class that suffers the most. 3.8. geographical barriers travel time is principally crucial in getting prompt medical help to at-risk populations [37]. it is vital to identify primary care facilities and hospitals near the vicinity for diagnosis and early treatment. most of the ailments can be cured if the patients can get medical help on time. countries and local governments with advancements in satellites and mobile location tracking apps should improve their plans to extend new treatment benefits to rural and remote areas where geographical barriers of landscape and climate limit building of permanent infrastructures. long-distance mobility is challenging for critically ill patients and pregnant women, thereby increasing the mortality rate. lack of intensive care units (icu) and trained staff put a spotlight on the severity of the situation. need for capacity –building in limited environments, training medical staff, virtual lab & critical care units, and adapting research-based international guidelines cannot be further ignored when humanity is fighting to survive against a novel virus [38]. 3.9. crises of lost employment human resource management is also a significant control measure to be followed. during epidemics, the economy of a country is negatively affected. thus, planning the recovery of human resources should be included in the control measures. pandemic results in loss of human lives, but a shrinking economy would aggravate the situation further due to hunger. private and public companies should take the initiative to inform its employees about any pandemic situations and any warnings from who on any pandemic situations. planning and management of the work should be present, and there should already be a system to handle works without meeting in person and to keep the salary of the employees stable. the primary sectors need more attention than the rest since the entire country's wellbeing depends on them. agriculture, fishery, and others should not stop because an imbalance in these industries might result in a more significant crisis. also, those involved with such industries mostly belong to the poverty level. while dealing with the pandemic, the system should pay attention to the patients and other citizens at the same time. eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 5 3.10. integration of information & communication risk communication and integrating adequate information has an imperative key role in curbing a future epidemic. the circulation of necessary information regarding the virus's pathogenicity, epidemiology, public health management, risk perception, and proactive control measures can reduce the incidence of a viral outbreak and significantly control the transmission rates. the framing of risk communication is such that it must be lucid, crisp, and timely and should deliver credible facts with utmost clarity, empathy, and accuracy. it must provide an insight into the underlying fears that are less spoken about, and should be strong enough to counterattack all the rumour shrouding it. the public's perception of the information depends on factors like ethnicity, literacy rates, awareness about the scientific principles and theory, etc. rumours, misinformation or half-information can slow down disease control and management. individuals tend to believe in the misinformation more than the correct information since it feeds into their pre-existing notion of an idea about the viral outbreak [39] [40]. 3.11. priority setting priority setting is also crucial in case of such outbreaks. often the lack of such measures leads to the infection is fatal. the early diagnosis and research on the control of the disease are vital to control the number of cases during such outbreaks. diseases like ebola are likely to occur suddenly without any prior warning, so the control safety of the infection must be followed to prevent any such outbreak. health care facilities should be ready to treat people as soon as the first case arrives [41]. for the sars and the mers, more research is required to maintain the conditions. in the case of aids, a multicriteria decision analysis (mcda) is advised to consider several criteria for resource allocation [42]. 3.12. access to health services for comorbidity treatment the majority of the viral outbreaks like hiv, ebola, influenza, and sars or mers worsen situations in individuals with comorbidities, i.e., existence and appearance of two or more ailments or conditions in an individual simultaneously due to pre-compromised immunity. complex medical management, psychological issues, poor quality of lifestyle, and inflated health costs add to the increased mortality rates. the four parameters for identifying the comorbidities in an individual, are the nature of the clinical health condition, the relative significance of the cooccurrences of the ailments, the chronological reappearance/presence of the ailment and expanded conceptualizations leading to a better understanding and analysing the clinical conditions. the hurdles in treating and impeding the transmission rates of a viral outbreak are the lack of adequate infrastructure, knowledge, and expertise in rural areas. the lack of a classification system having comorbidity indexing, morbidity burden rates, patient complexity, and other constructs pose a challenge to understanding the causes of co-occurrence of the ailments and its consequences on public health services [43][44]. 3.13. social beliefs & taboos: reports say that about 60% of the cases of ebola in guinea can be traced back to traditional burial practices. there were incidents where prayers were conducted by the high-ranking church members resulting in a gathering, leading to the spread of the disease. also, there were many reported cases where herbal medicines were tried or somewhat rubbed on the body of those infected with ebola, resulting in more complications since the traditional healers practicing such activities were themselves infected. these techniques involving religious and social beliefs failed to solve the matter and worsened the situation [45]. the practice of consuming bats by a particular community, even after some coronavirus strains were already found, is a significant reason for the outbreak of the sars and the mers. it has also been said that information was also not shared during the sars before it took a significant role in affecting other parts of the world. this secrecy and ignorance led to the social transmission of the infection [46]. in the cases of aids, it is mostly found that the communities are uneducated and unprepared to face such situations, thus ending up marginalizing and isolating the patients instead of providing proper care. also, the proper knowledge regarding the use of protection or rather sex-education is lacking in most of these cases. pregnant women face more problems due to social ignorance [47]. table 1. challenges faced during prior viral outbreaks challenges sars/mers ebola hiv 1.testing, tracing & isolation early identification of infectious cases to reduce the risk of super spreaders was vital [48]. unfamiliarity with the transmission patterns and clinical manifestations led to an outbreak in hong kong, mainland china, and other areas. a strong epidemiological surveillance system was required for early detection and control [49]. initial identification was made fairly quickly, however testing and tracing became difficult later due to growing social taboo, poverty, lack of infrastructure [5] and geographical barriers [50]. there are many tests to identify hiv, but back in 1985, the first commercial blood test was discovered [51]. the lack of proper awareness, adequate knowledge, infrastructure, economic constraints can also contribute to a barrier. a comparative study of challenges and strategic management: lessons learned from sars, mers, hiv & ebola outbreaks eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 sweta saraff et al. 6 2. herd immunity researchers are trying to make a vaccine, but the number of cases for coronaviruses was so less before the present year that priority was not being given to vaccination [52] [53]. the canadian government supported its scientific team's efforts in carrying out the clinical trials and sponsored the development of the "rvsv-zebov" vaccine for the ebola virus [54]. the progress in the development of vaccines for sti prevention (sexually transmitted infections) has been slow. due to heterogeneity in the spread of such infections, clinical trials of uninfected individuals may increase both expenses and scale of trials [21]. 3. availability crises of primary health care the sars & mers both spread quickly through contact & continuous exposure to aerosols. lack of infrastructure and specialized medical staff in infectious diseases increased the complexity of the situation [27 55]. congo (country of origin) has few hospitals and suffers from low quality of infrastructure 0.2% of the population are medical doctors [56]. inaccessible and unaffordable primary healthcare facilities was a significant factor in increased morbidity rates [57] in many african countries. the shortage of primary health care workers and inadequate clinical infrastructure are significant challenges in the treatment of hiv positive and aids patients, despite all the government's efforts. [58]. 4. health crisesinfection transmission in medical staff & sanitation workers the effect on the healthcare workers and the sanitation workers is vast since the virus that is present on surfaces might infect them as they are in regular contact with patients [59]. this virus transmits if one comes in contact with an infected person's body fluid. health workers dealing with patients and bodies of the infected tend to get infected easily as a result [60]. the viral transmission from the patient to the healthcare worker can occur through the exchange of bodily fluids, as they are the first person to be in contact with the patient. the clinical instruments like scalpel, scissors, and needles are at higher risk of contamination while treating an hiv positive patient. pregnant healthcare staff is at a higher risk of developing this viral contamination through body fluids, even saliva, and the baby is also at risk of getting infected. [61] [62]. 5.policy issues in public health acquiring reliable epidemiologic data on the transmissibility of deadly viral outbreaks are a global concern [63] [64] [65]. coronaviruses require a worldwide investigation on the role of wet animal markets in its pathogenicity [66]. the international support to the ebola crisis was lackadaisical due to limited capacity and expertise in handling epidemics. such situations require compelling efforts in policy overhauls and various humanitarian measures [67] [68]. inadequate training and insufficient knowledge is the primary barrier regarding public health. the preexisting policies and infrastructure do not allow frontline clinical and public health workers for consultation and counselling. [69]. 6. policy issues in mental health psychological stress was seen in the patients as well as their families. confusion, depression, excessive anxiousness, and even insomnia were seen. for friends, family, and survivors: facing stigma and taboo from society. for health care workers: watching the devastating effects of the virus first hand, worrying about contracting the disease themselves and high work stress, all of which compounded and resulted in severe anxiety, depression, or even ptsd [70]. depression, anxiety, and sleep disturbance are a few mental health disorders that the hiv infected person goes through due to discrimination from society. the healthcare workers near the hiv patient's vicinity sometimes go into a mental breakdown [71]. 7. policy issues related to socioeconomic challenges as we know, bats, camel, pangolins, and many such animals are the top carriers of the coronavirus, and consumption of these needs to be stopped. even after the two outbreaks of sars and mers and the carriers being known, people have continued consuming these animals [72]. transmission of the ebola virus becomes easier in places with low hygiene standards, mostly seen among those with poor economic or social backgrounds [73]. economically backward and resourceconstrained economies suffered more from the transmission of ebola than high ses communities. poverty, unemployment weakens family, and societal support systems. lack of participation of the youth in the educational and awareness programs leads to social crises and economic burdens [74]. eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 7 8. geographical barriers due to fast mutations and the virus being spread through surfaces if touched, there is a possibility of the infection crossing geographic barriers [75]. during an ebola outbreak, it was challenging to reach some towns/villages due to its isolation from civilization. it also gets difficult to trace the virus in such cases as dead primates are often found in forests, and the people usually maintain low hygiene [76]. rural communities and the individuals in remote areas have difficulties accessing the costly and specialized treatments of hiv provided by the medical care unit [77] [78]. 9. crises of lost employment the developing countries owing to overpopulation and limited resources, face more issues with unemployment. the private sectors facing huge losses tend to reduce the workforce, especially the travel & tourism industry [79]. an already weak economy now affected by ebola and coronavirus has caused a massive loss in employment 1 in 2 people are unemployed in liberia [80]. the hiv pandemic outbreak affects the people in the peak of their productive, earning, and reproductive stage. the years of productivity are lost, and unemployment grasps the family’s backbone [81]. 10. integration of information & communication both the outbreaks were a result of latency in information transparency and proper communication [82]. misinformation, fake news, and rumours can have grave consequences amidst viral outbreaks. they can be fearinducing or fuel social taboos. however, governments and public domain coders always endeavour to rectify it [81]. many taboos and facts had gone unchecked, leading to feeding the prejudices and ill-treatments towards the hiv positive patient. [84] 11. priority setting due to the vast number of patients requiring medical help during the sars outbreak, an increase in the hospitals and medical professionals' strength is needed to treat patients to stop the spread [85]. most affected countries also suffer from recurrent famines, terrorism, poverty, and other epidemics cooccurring [86]. in such a situation, it is difficult for the government to prioritize any one adequate information, knowledge, and resources are not available to develop an extensive and effective intervention for prioritizing care of critically ill patients [42]. grave event over another. 12. access to health services for comorbidity treatment the outpatient treatment capacity, availability of icu, ventilators, and emergency departments are overwhelming in dealing with a significant pandemic to extend resources for both grave and general illnesses. there is a shortage of medical staff, doctors, nurses, and laboratory technicians other than safety equipment and medicines leading to severe outcomes [87]. in an already stressed healthcare system, facing ebola cripples it and makes it unavailable to others who need it. however, in 72% of 90 patients, malaria, and another 2% of 90 patients, diabetes was found as a comorbidity with ebola [88]. the outbreak of hiv was usually associated with other disorders like aids, pneumonia, depression, alcohol abuse, neurocognitive disorders, cancer, etc. the access to health services for a comorbidity treatment is often blocked by poverty, lack of infrastructure, and expertise in many developing or underdeveloped areas [89]. 13. social beliefs & taboos it has been reported that the survivors and their families were treated poorly and isolated from society even after they have been cured of the disease; in some cases, even the shopkeepers denied to provide daily equipment to the family of former patients [90]. people often shun survivors of ebola virus, do not come up for check-up fearing social stigma, or even fear healthcare workers for they are afraid and link them to the spread of ebola. it made treating and tracing ebola even more difficult [45]. hiv has a stretched account of the stigma attached to it, much of which stems from the dearth of knowledge about the ailment and its spread [91]. 4. strategic management: lessons learned from sars, mers, ebola & hiv outbreaks the growing population in developing economies has led to a shortage of land, inequitable distribution of income, accessibility to reasonable, and good health care. incessant urbanization has led to the clustering of people in certain cities or states [92]. these cities or zones become hotspots for incubation or the spread of diseases. similarly, there are villages with remote access to quality healthcare, necessary facilities, or regular communication networks. taking lessons from the ebola viral disease (evd) outbreak in zaire (congo) and later the fatal second wave in guinea, liberia and sierra leone spiralling out of control, the lacunas of public health systems at local, the national and international a comparative study of challenges and strategic management: lessons learned from sars, mers, hiv & ebola outbreaks eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 sweta saraff et al. 8 level have been glaring. the responses from the global health community like who and red cross society had also been too little and delayed in the diffusion of medical equipment, masks, medicines, ppe kits for health care workers, ventilators, etc. and adequate monetary fund [93]. in the winter of 2002, sars was first reported in the guangdong province. due to a lack of awareness and complacency of the government, the infection spread to countries like toronto, vietnam, hong kong & singapore [94][95]. who issued a global warning around march to alert the general public about the risks of a fast-spreading virus [96] [97]. the governments and international organizations failed to develop public trust due to pneumonia's erratic findings on the lungs. the most vulnerable was that of health personnel due to aerosol droplets remaining in the ward's environment with infected patients. it activated the need for advanced protective measures and cooperation at the international level. 4.1. structured networks for management of public health systems stochastic models help in estimating the probable trajectory of the spread of infections in a community based on random variations in one or more inputs. the selection of network models depends upon the population under surveillance and their social behavior. it should also consider how the infection spreads through close physical proximity, transmission through sexual contact, or aerosols. the most common network model is the sir model, also known as susceptibleinfectious-recovered. an appropriate model studies diseases and their context to reduce the spread by various public health measures like community vaccination, testing, and treatment [96]. the two models "discrete-time model" and "the continuous-time markovian epidemic on a network" were discussed [98]. the "discrete-time model" randomly selects one case as infectious and considers the remaining population in the network as susceptible. in a specific period (period of spread of infection), most people then fall in either of the categories, i.e., susceptible or infectious. the other model, "the continuous-time markovian epidemic on a network," differs from the discrete model in taking the latent period between acquiring infections and becoming infectious. it also dynamically covers a time range, without affecting the final size or the last person to get infected [98] [99]. it also discusses the strategic inclusion of individuals with "global contacts" who are at higher risk of spreading infection (super spreaders). 4.2. social awareness programs many mathematical models have proved how awareness can change the risk perception followed by specific behavioural changes within a population that reduce their chances of susceptibility. news media, government programs, distribution of pamphlets fosters adherence to various initiatives taken by the public health department. social networking sites serve as an excellent platform for the collation of all the adequate information about an epidemic and related awareness, thus working upon lowering of incidence rate, increasing the risk perception rate, and, therefore, constraining the sickness [100]. social distancing norms should be followed strictly. the lessons learned from the outbreaks during the sars and the mers needs to be applied to stop any further outbreaks [101]. 4.3. testing and treatment testing and treatment of any viral outbreak is included under diagnostic virology. for successful viral detection and isolation, diverse disciplines like microbiology, serology, clinical biochemistry, pathology play an imperative key role. efficient viral identification is needed to prevent viral transmission, accurate screening of the pathogen, to monitor the response of the treatment provided which leads us to a better pandemic preparedness in the future with an insight on the aspects of resistance to therapy and immune escape profiles that might be due to rapid genetic aberrations in the viral genome. but in most cases, like, for example, during the hiv outbreak, due to lack of risk perception and stigmatization around or more than 60% of the cases were undiagnosed [102]. 4.4. identification of high-risk groups the population at higher risk of getting infected from an already affected person is termed high-risk. higher risk or vulnerability can be related to factors like the nature of the occupation, socio-economic deprivation, low-risk perception, ethnicity, compromised immunity, and others. public health care workers, pregnant women, infants, and individuals above 70 years of age fall under high-risk groups. this clear demarcation of the high-risk groups in a population is always used while constructing mathematical models that can be used to develop a healthcare infrastructure strategy for the ongoing outbreak and future lethal pandemics. health care workers are always under an ethical obligation to provide safe treatment to the ailing patients, though fully aware that they have a high personal risk of getting infected and passing that onto their family [103][18]. 4.5. management of traditional burial practices studying local traditions is necessary to understand the dynamics of transmission and, subsequently, control illnesses. they can be brought about by local religious leaders or even the government who should urge safe, hygienic and clean practices prohibiting/ discouraging large gatherings, usage of gloves, usage of materials that can be quickly disinfected, maintaining constant hand hygiene to not come in contact with any bodily fluids [45][104]. eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 9 4.6. identification of asymptomatic carriers individuals infected by a pathogen or virus but do not manifest any sign or symptom of that infection or disease is termed asymptomatic carriers. they are sufficiently potent of transmitting the disease to a healthy individual, although itself being unaffected. thus unintentionally participating in public gatherings or public places, they potentially boost the viral transmission cycle and are a dangerous viral source. they might later develop the symptoms but initially serve as a carrier or conveyor of the ailment. they have played a crucial role in the transmission and propagation of viral outbreaks, namely, hiv, influenza, sars, and mers. necessary curbs were placed on air and railway travel to interstate and international destinations to limit citizens' movement [105]. 4.7. contact tracing a close surveillance on the individuals who were in close contact with an infected patient (alive/dead) and providing them with clinical guidance, evaluation to prevent spreading the ailment onto other healthy individuals, since they are potent through intentional/unintentional means, is termed as contact tracing. systemic assessment and interviewing the people who were in direct/indirect contact with the infected patient is a targeted approach towards intensified pandemic control measures. it involves majorly three stepscontact identification (identifying the high-risk category of the contacts who were in direct or indirect vicinity of the infected person), contact listing (enlisting the high-risk group of contacts and notifying them on further details of what is to be done consequently and maintenance of social distancing norms), contact follow up ( a competent team of officials keeping a watch on the enlisted contacts, basically following them up for their basic needs, guidance and preventive measures). immediate evacuation and keeping the potentially infectious contacts under observation for more than 15 days is practiced [106] [107]. 4.8. availability of essential services the government should ensure that the public is provided with the necessary commodities so that they might not face difficulties or travel long distances for their daily needs. food and water, transportation, banking, healthcare, and other things should be taken care of for public convenience. essential workers like the medical staff and electric and water suppliers should also be on duty [108]. the vital services also include sanitation items. lifesaving medicines must be made readily available. the control of the pandemic should not lead to more deaths due to the unavailability of other necessary drugs. these drugs include opioid analgesics, midazolam, diazepam, and others [109]. 4.9. patient isolation and care the separation of patients is vital since they can spread the disease to others. the hospital and the wards having patients should be closed to other patients and should take a limited number of cases that can be treated with proper care, maintaining adequate distance [110]. the patients should not be treated with apathy. they should also have specialists to overcome depression since most patients during a viral outbreak suffer from frustration, anxiety, and depression, mostly in cases of hiv [111]. the patients and the family members should be kept under home quarantine for 14 days. 4.10. environmental measures-regular cleaning of exposed surfaces the environment plays a significant role in the spread of infections. for example, ebola might spread due to water pollution, while the sars and mers due to the harmful particles present in the air might damage the lungs. in a project taken up by the united nations, the focus has been made to a one-health approach to stop the spread of the virus from animals to humans. the idea is to keep the environment clean so that the waste from the infected human bodies cannot transfer the infections to the animals, which again moves it to another healthy human. the throwing of domestic wastes in the water bodies needs to be stopped, and there should be proper management of human excreta [112]. a study conducted in italy found that a high number of cases are directly or indirectly related to air pollution for 71 of its provinces [113]. 4.11. data collection and collating for informed research establishing and strengthening a global surveillance network for predicting, controlling, and assessing the ongoing outbreak or developing strategies for future viral pandemics [114] [115] is crucial. data needs to be maintained not just for the public health, but also about the health of the animals closely related to the people daily, for example, cattle, dogs, cats and other animals used for food. such data might help trace a pathway of the virus and its host (or hosts) [116]. a proper study of food chains or webs is essential. the use of better methods to identify a viral disease should be used. for example, nucleic acid amplification tests (nats) can be used in place of the antigen-based methods popularly used for the rapid detection of respiratory diseases caused by a virus [117]. 4.12. public-private investment in public health research dearth of investments in healthcare facilities and infrastructure in developing countries expose them to pandemic outbreaks and thereby scarring psychosocial ethos a comparative study of challenges and strategic management: lessons learned from sars, mers, hiv & ebola outbreaks eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 sweta saraff et al. 10 of the community. in the case of ebola, there was a failure to recognize the risk of an epidemic despite previous epidemics both by the global and local communities and an increase in transmission rate. investment for the development of healthcare systems, both mental and physical, should come in, as it will not only check the spread of this severe epidemic but also stop it from crossing national and international borders and communities. though some organizations are interested in rebuilding health systems in west africa, the global community must show commitment to building such health systems that are better prepared for the future [118]. for hiv, however, there has been considerable funding and research curated by major global health initiatives in public health research by organizations like who, gfatm, unaids, etc. even when who had declared that the sars might become a pandemic which it has now in the form of sars-cov 2, there weren't enough measures taken, and research was mostly focused on the previously essential subjects. also, the health care alert wasn't imposed for a longer time. when the pandemic planning was started back in the early 2000s, then a better infrastructure to control a future outbreak was expected but wasn't found, resulting in more deaths due to mutations in the virus genome. table 2. strategies for early prevention or control management during the recent viral outbreaks strategies/ planning sars/mers ebola hiv 1. structured networks for management of public health systems this type of approach can be used to target the identification of susceptible individuals and their immediate connections. it will connect more people and help those in remote areas who need it the most. the case history and the travel history of the patients are also critical [119]. proven success in the past, example: poliomyelitis epidemic, even for ebola, an active surveillance and response system will continue to be extremely useful for tackling the illness, more than expenditure on vaccine/medication research and treatment [120]. social networkbased strategies and interventions are significant to influence communities and populations that are unable to access the health services that combat hiv. it is a cost-effective approach to reach large masses with the correct knowledge and make the services accessible to the needful [121]. 2. social awareness program the who guidelines must reach the maximum population to educate people about the sars, the mers, and other coronaviruses. doctors, local health care workers, local leaders should promote awareness and advertisements should also be spread concerning public health and hygiene. social awareness programs in coordination with the ngos, schools impart a strong message towards precautionary measures about the sexually transmitted diseases, aids & hiv [122]. 3. testing & treatment a regular supply of testing kits and keeping the infected individual into quarantine for a minimum of two weeks is a must. constant surveillance by public health workers and government organizations is necessary they carry out tests on suspected cases and screen the population regularly [123]. the early testing and treatment intervention approach is the best way to screen the target population, where the diagnosed patients are cured at an early stage so that the spreading can be stopped much earlier [124]. 4. identification of high-risk groups the death rate due to such infections is high for children and those above 60. people with weak immunity and damaged lungs face critical problems, while for some, the symptoms might be very tough to be detected [125]. lack of infrastructure, reusing needles because of scarcity in villages, unavailability of healthcare centres nearby, etc. affect economically weaker sections the most. another aspect is the low hygiene standards maintained by these people the leading cause of transmission [126]. epidemiologists have hypothesized that age patterns mostly add up to the transmission of the hiv outbreak. age targeted intensified treatments, that may be primary or secondary, would yield better results in curbing the root of the problem [127]. eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 11 5. management of traditional burial practices there have been several rules related to burial practices that include gloves, proper clothes, masks, and so on. those making the kits associated with the burial should make sure that the materials should be made of products that can undergo easy disinfection [128]. specific and strict regulations are maintained while embalming and post mortem procedures by the morgue attendees. local religious/cultural leaders should be urged to bring about a change in practices that may unknowingly be the cause of further transmission of the disease [129]. disposable gloves, pants, gowns are worn to avoid any contact with the bodily fluids like blood or saliva, which can be responsible for transferring the disease, according to canadian centre for occupational health and services (ccohs) 6. identification of asymptomatic carriers although the asymptomatic carriers are known to affect healthy individuals, the effect is weak in most cases [130]. the carriers still can transmit the infection through sputum since it spreads through mucus. ebola is a severe illness, and till now, no study has been able to prove the existence of an asymptomatic patient [131]. the asymptomatic carrier stage is the most vulnerable in an hiv positive patient showing clinical latency, which can even last up to 10yrs in some patients. they are highly potent in transferring the viral infection to a healthy person through the virus is present in an inactivated state [132]. 7. contact tracing all the individuals in physical contact with the patient during the incubation time were traced to isolate them and stop any further spread of infections. through mathematical models, epidemiological and intervention parameters were studied to identify the susceptible individuals [19]. the measure used to trace and identify those that have been in contact with the patient through mobile health tools helped reduce the risk of transmission in the population. although a useful measure, its success ultimately depends on the trust developed between authorities and the public lest they interfere or block the work out of fear [133]. it offers the healthcare system to reach the patients that are likely to be affected for faster testing and clinical counselling without further transmission. from that list, the vulnerable persons who were at a chance of getting infected through the transfer of bodily fluids or unprotected sex will be monitored [134]. 8. availability of essential services essential services include proper food, medicines, and other daily necessities that should be available regularly at multiple outlets to avoid crowds. a steady supply of essentials at doorsteps was maintained to support people under isolation and quarantine [135]. it is difficult for people to get adequate food or essentials in places that are severely affected; hence the government should look to it. currently, several organizations like the who and unwep are working towards this goal [136]. hiv positive patients do not require strict isolation and quarantine precautions. thus the availability of essential services must be provided without any stigma or discrimination. [137]. 9. patient isolation & care the patient and family members are kept in complete isolation. the real treatment is still unknown, and the virus can cause multipleorgan failure, so existing procedures are based on vital signs and symptoms [138]. three-pronged strategies were used. the patients were isolated, and protective equipment was provided to health workers and members of the red cross society. the patient was educated to take ample precautions for themselves and their family [139]. body substance isolation (bsi) is also taken care of, i.e., no bodily fluids are allowed to contaminate the premises regardless of the patient being suspected confirmed being hiv positive [140]. 10. environmental measures regular cleaning of exposed surfaces disinfecting of the surfaces exposed should be done, and proper hygiene should be maintained to stay healthy against the virus [141]. sars or mers both may shed on to the dry surface and contaminate patients' or caregivers' hands. some scholars have detected the presence of ebola virus strains in the environment around patient wards. however, they were yet to determine if they were virulent and infectious. they encourage the usage of ppes and their proper disposal [142]. environmental pollution and degradation in the quality of air and water can bring upon air or waterborne ailments in hiv positive patients, thus making them susceptible to opportunistic pathogens [143] a comparative study of challenges and strategic management: lessons learned from sars, mers, hiv & ebola outbreaks eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 sweta saraff et al. 12 11. data collection and collating for informed research the current situation of the global pandemic shows that lessons of timely disseminating crucial information were not followed. however, measures related to patient isolation and quarantine, use of ppe kits were followed [144]. one of the most important aspects of dealing with an outbreak that is followed by doctors and scientists alike to trace the origin of the disease, collect samples, study patients carefully, and their culture and environment as well [145]. the goal is to reduce the number of deaths every year fewer than 500,000 by approximately 2020. the data systems must keep the clinical report documents at a patient level, build and promote an environment of quality assessment. [146]. 12. publicprivate investment in public health research the "one health" concept focuses on healthy, cyclical growth of the environment, animals, and humans. this approach was suggested during sars/ mers pandemic when the suspect virus was caused due to animal mutations. at the international level, socioeconomic investment is needed for regular monitoring and timely response to any such outbreaks [147]. international communities need to invest, send volunteers, and help african countries cope with the disaster they're facing in combating the disease, train their locals, and increase their skilled resources [148]. major global health initiative has curated increased capital collection, resource drives, and social awareness programs for the hiv outbreak. the scaling up of public health research has been working to overcome the equity concerns regarding the accessibility of health care to the most vulnerable and marginalized section of the society [149][150]. 5. limitations in public health management often people fail to maintain proper hygienic conditions, mostly from the overpopulated developing countries. so, population control measures should also be maintained so that the government and the healthcare centres can take proper care of the individuals. any communicable disease requires necessary steps to be taken while handling a patient. these measures are often ignored, and reusing medical equipment meant for one-day use, and improper disposal leads to more affected individuals. preparation for any pandemic is a responsibility that involves multiple collaborators, sectors, and different strata of the final public. training and skill among all stakeholders must be undertaken transparently and comprehensively, to certify equitable & impartial allocation and optimally benefit from regular supplies of antiviral drugs and vaccines. rising infection toll may disturb essential services across all sectors of the globe, and healthcare amenities are also besieged with gravely ailing patients. unless healthcare workers are protected, they'll suffer disproportionately, which could lead to shortages of trained healthcare professionals and aggravate the risk. the limitations of funds are also a significant barrier. the economic conditions worsen during these times, but the maintenance of healthcare systems and proper monitoring is much required to fight against the disease. in the developing countries, the problem is worse since the number of citizens depending on the government for help is enormous. proper distribution of funds is too important since, to provide one facility, the other cannot be put to danger. thus, the challenges during pandemic situations are many, which need both time and human resources. any warning regarding a pandemic situation should never be ignored, and socio-economic infrastructure should be equipped to deal with them. there is an urgent need to distribute the workload among the district and state levels of government. we often find a clash of ideas and rules imposed on the citizens by different government bodies. the services to be provided and the care given should be appropriately distributed among the district, community, and personal levels. there are techniques to avail of the local government's facilities while following the terms of the national government. not just on a national level but also steps should be taken from international levels. all the countries and their governments should join hands in making policies to fight against a common enemy, the virus, since it does not just harm the systems of a state in particular, but other countries related to it in trade and commerce as well. 6. conclusion the world is grappling with fears of covid 19 pandemic since late 2019. it is a universal consensus to develop national repositories for multiple types of meaningful data to provide timely public health support. a hybrid multiscale proposition consisting of timely and accurate data from various localities, including communities with different social practices, will enable the development of dynamic mathematical models. with an example of the ebola virus (ebov), the results suggested that the age & structure of the population, the distribution patterns & the mobility rate of individuals can be understood through eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 13 appropriate network generated models. these probabilistic algorithm models support the governments with a new and structured vigilance system to control the outbreak with minimum loss. identification of high-risk individuals among the community is crucial for control measures. a better realization and understanding of asymptomatic carriers is imperative towards pandemic preparedness and the public healthcare sector to mitigate the viral outbreak by designing the exact transmission routes. a systematic method of collecting data, collating it, and later analysing for public health surveillance is instrumental for diffusing critical information through media and social networks. engaging communities for management of viral outbreaks is one of the predictors in the successful handling and planning of 360-degree national health and safety policies committed at the rural and urban levels. an arrangement of social awareness drives on susceptible viral diseases (offline or on social media) does not only lower the rate of incidence of the ailment instead prevent it from turning into a global outbreak. cooperation, coordination, and communication among states and centre through multiple channels at regular intervals are required. states have to depend upon the centre for fair sharing of knowledge and resources. in contrast, central systems rely on the local, district level, and thereby state authorities for reliable and timely data sharing. various modes of transport and accessible traveling facilities have led to the surge of viruses at an unfathomable rate. 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(2020). role of the chronic air pollution levels in the covid-19 outbreak risk in italy. environmental pollution (barking, essex: 1987), 264, 114732. https://doi.org/10.1016/j.envpol.2020.114732 [114] funk, s., camacho, a., kucharski, a. j., eggo, r. m., & edmunds, w. j. (2018). real-time forecasting of infectious disease dynamics with a stochastic semi-mechanistic model. epidemics, 22, 56-61. [115] siettos, c. i., & russo, l. (2013). mathematical modeling of infectious disease dynamics. virulence, 4(4), 295-306. [116] o'brien, e., & xagoraraki, i. (2019). understanding temporal and spatial variations of viral disease in the us: the need for a one-health-based data collection and analysis approach. one health, 8, 100105. [117] fox, j. d. (2007). respiratory virus surveillance and outbreak investigation. journal of clinical virology, 40, s24s30. [118] talisuna, a. o., okiro, e. a., yahaya, a. a., stephen, m., bonkoungou, b., musa, e. o., minkoulou, e. m., okeibunor, j., impouma, b., djingarey, h. m., yao, n., oka, s., yoti, z., & fall, i. s. (2020). spatial and temporal distribution of infectious disease epidemics, disasters and other potential public health emergencies in the world health organisation africa region, 2016-2018. globalization and health, 16(1), 9. [119] adegboye, o. a., & elfaki, f. (2018). network analysis of mers coronavirus within households, communities, and hospitals to identify most centralized and super-spreading in the arabian peninsula, 2012 to 2016. canadian journal of infectious diseases and medical microbiology, 2018. [120] tambo, e., ugwu, e. c., & ngogang, j. y. (2014). need of surveillance response systems to combat ebola outbreaks and other emerging infectious diseases in african countries. infectious diseases of poverty, 3(1), 1-8. [121] junpo, h. i. v., & hiv, a. (2014). aids junpo: 90–9090: an ambitious treatment target to help end the aids epidemic. geneva: unaids. [122] chatterjee, c., baur, b., ram, r., dhar, g., sandhukhan, s., & dan, a. (2001). a study on awareness of aids among school students and teachers of higher secondary schools in north calcutta. indian journal of public health, 45(1), 27. [123] newman, e. n. (2015). what are the challenges associated with testing for ebola? a focus on the 2014 outbreak in west africa. future virology, 10(5), 469-471. [124] kretzschmar, m. e. (2013). schim van der loeff mf, birrell pj, de angelis d, coutinho ra. prospects of elimination of hiv with test-and-treat strategy. proc natl acad sci usa, 110(39), 15538-15543. sweta saraff et al. eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 17 [125] chen, y. c., huang, l. m., chan, c. c., su, c. p., chang, s. c., chang, y. y., ... & lee, y. t. (2004). sars in hospital emergency room. emerging infectious diseases, 10(5), 782. [126] world health organization. (2015). ground zero in guinea: the outbreak smoulders–undetected–for more than 3 months. a retrospective on the first cases of the outbreak. [127] bershteyn, a., klein, d. j., & eckhoff, p. a. (2013). agedependent partnering and the hiv transmission chain: a microsimulation analysis. journal of the royal society interface, 10(88), 20130613. [128] james, l., shindo, n., cutter, j., ma, s., & chew, s. k. (2006). public health measures implemented during the sars outbreak in singapore, 2003. public health, 120(1), 20-26. [129] sharma, a., heijenberg, n., peter, c., bolongei, j., reeder, b., alpha, t. ... & bocquin, a. (2014). evidence for a decrease in transmission of ebola virus—lofa county, liberia, june 8–november 1, 2014. mmwr. morbidity and mortality weekly report, 63(46), 1067. [130] gao, m., yang, l., chen, x., deng, y., yang, s., xu, h. ... & gao, x. 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(2014). ebola: learn from the past. nature news, 514(7522), 299. [140] series, w. a. (1991). biosafety guidelines for diagnostic and research laboratories working with hiv. who. geneva. [141] otter, j. a., donskey, c., yezli, s., douthwaite, s., goldenberg, s. d., & weber, d. j. (2016). transmission of sars and mers coronaviruses and influenza virus in healthcare settings: the possible role of dry surface contamination. journal of hospital infection, 92(3), 235250. [142] poliquin, p. g., vogt, f., kasztura, m., leung, a., deschambault, y., van den bergh, r., dorion, c., maes, p., kamara, a., kobinger, g., sprecher, a., & strong, j. e. (2016). environmental contamination and persistence of ebola virus rna in an ebola treatment center. the journal of infectious diseases, 214(suppl 3), s145–s152. [143] kim, y. j., woo, j. h., kim, m. j., park, d. w., song, j. y., kim, s. w., ... & choi, b. y. (2016). opportunistic diseases among hiv-infected patients: a multicenter-nationwide korean hiv/aids cohort study, 2006 to 2013. the korean journal of internal medicine, 31(5), 953. [144] mccloskey, b., & heymann, d. l. (2020). sars to novel coronavirus–old lessons and new lessons. epidemiology & infection, 148. [145] brown, r. (2014). the virus detective who discovered ebola in 1976. bbc news magazine. [146] rice, b., boulle, a., baral, s., egger, m., mee, p., fearon, e. ... & rutherford, g. (2018). strengthening routine data systems to track the hiv epidemic and guide the response in sub-saharan africa. jmir public health and surveillance, 4(2), e36. [147] zumla, a., dar, o., kock, r., muturi, m., ntoumi, f., kaleebu, p., eusebio, m., mfinanga, s., bates, m., mwaba, p., ansumana, r., khan, m., alagaili, a. n., cotten, m., azhar, e. i., maeurer, m., ippolito, g., & petersen, e. (2016). taking forward a 'one health' approach for turning the tide against the middle east respiratory syndrome coronavirus and other zoonotic pathogens with epidemic potential. international journal of infectious diseases: ijid: official publication of the international society for infectious diseases, 47, 5–9. [148] ling, e. j., larson, e., macauley, r. j., kodl, y., vandebogert, b., baawo, s., & kruk, m. e. (2017). beyond the crisis: did the ebola epidemic improve resilience of liberia’s health system? health policy and planning, 32(suppl_3), iii40-iii47. [149] murzalieva, g., kojokeev, k., manjieva, e., akkazieva, b., samiev, a., botoeva, g. ... & jakab, m. (2007). tracking global hiv/aids initiatives and their impact on the health system: the experience of the kyrgyz republic. context report. [150] semigina, t., gryga, i., bogdan, d., schevchenko, i., bondar, v., fuks, k., & spicer, n. (2007). tracking global hiv/aids initiatives and their impact on the health system in ukraine: interim report: context report. 10.13140/rg.2.1.4609.2402. a comparative study of challenges and strategic management: lessons learned from sars, mers, hiv & ebola outbreaks eai endorsed transactions on smart cities 08 2020 01 2021 | volume 5 | issue 13 | e3 i. introduction today, we are going to live the internet of things (iot) era, where objects become more and more communicative and need to be connected to disseminate the information they hold. the idate [1] announces 80 billion connected objects for 2020. their aim is to evolve in the years to come and spread in all sectors. these objects could be devices, automata, sensors present in our houses, our workplaces and also in public places. they can transmit information of type, temperature, humidity, the state of a door (open or closed), the parking place (occupied or vacant), and a multitude of other information such a type of connected object will be explained in details in this paper by highliting the possible uses areas..however, the connection of these objects to the internet network that we know requires a compatible and scalable infrastructure capable of absorbing the exponential evolution of the connected objects. it therefore raises a technical problem that will be investigated. the standardization bodies then quickly pushed the search towards infrastructures with wireless access network taking into account the technical specificities of the connected objects. there is now a multitude of radios technology capable of supporting connected objects but are they all capable of responding to the specificities imposed by the iot? we will describe the existing solutions by focusing on the low power wide area network (lpwan) which is the solution of low-energy wireless links. lora and sigfox, lpwan’s key players, will be presented and confronted as well as other players positioned on lpwan solutions such as the 3gpp for lte-m. this paper deals the specificities of deployment and implementation of the end-to-end interconnection of the lpwan system, taking into account the connected object itself, the radio infrastructure (or access network), interconnect gateways, cloud, lpwan backbone. moreover, a study of the physical layer for sigfox and lora and we propose a model to know which technology is more sensitive to the interference. then, we discuss the role of spread spectrum on the sensitivity of the receptors. evaluation of lpwan technology for smart city eai endorsed transactions smart cities research article hussein mroue1, guillaume andrieux1, eduardo motta cruz1, gilles rouyer2 1polytech nantes ietr laboratory la roche sur yon, france 2spie city networks saint herblain, france abstract—in this paper, we explore technologies for low power wide area networks (lpwan) serving the internet of things (iot). these networks are ded-icated to long-range and low-speed communication to ensure a good autonomy up to 10 years and a budget link up to tens of kilometers. the performance of two lpwa technologies is investigated, where the well known lora and sigfox technologies are evaluated according to their sensitivity to the interference and the impact of the spreading spectrum technique on the receptor sensitivity. numerical results are presented and discussed. received on 28 july 2017; accepted on 22 september 2017; published on 20 december 2017 keywords: low power wide area networks, inter-ference, chirp spread spectrum, ultra-narrow band, physical layer. copyright © 2017 hussein mroue et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.20-12-2017.153494 1 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e3 1 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e3 ii. lpwan : low power wide area network a. principles of lpwan lpwan has been proposed to be the solution to the internet of objects being supported by most media-driven technologies such as lora, sigfox and lte-m. this technology allows the sending and receiving of messages of very small sizes, over very long ranges up to 40km. the major advantage of this technology is that the equipment set up in its network is very inexpensive and does not consume much energy[2]. lpwan technology is perfectly suited to connect equipment that needs to send small amounts of data over a long range while maintaining their autonomy. some iot applications may only transmit small amounts of information, such as a parking parking sensor, which transmits only when there is a change in state (vehicle detected yes or no). the low energy consumption of such a device makes it possible to carry out this task with the least cost and little energy consumed. lpwan is often used when other wireless networks, such as bluetooth-ble and to a lesser extent wi-fi and zigbee, are not suitable for longrange performance. as well as m2m cellular networks are expensive, consume a lot of energies, and are expensive with regard to hardware and services. in order to identify the specifications and benefits of this technology, here is a brief comparison of current technologies: • gsm networks, 3g, 4g, 5g • zigbee (home automation technology) • bluetooth, ble, wifi b. emerging lpwan solutions the lpwan wireless network has emerged in recent years. the precursors of this lpwan technology are today sigfox, lora and lte-m, they will be detailed more in this sector. 1) sigfox network: sigfox is a french company founded in 2009 [3] whose goal is to build wireless chains to connect energy-saving appliances, such as electricity or water meters, alarm systems, which must be continuously lit and emit small amounts of data. sigfox has set up proprietary technology that enables m2m communication using the industrial, scientific and medical ism radio band which uses the 868mhz frequency in europe and 902mhz in the united states. this technology uses a broadband signal that passes freely through solid objects called ”ultra narrowband” and requires very little power. the network is based on a one-hop star topology and requires an access network connection from a mobile operator to carry the generated traffic. the signal can also be used to easily cover large areas and reach underground objects. sigfox has partnered with a number of lpwan industry companies such as texas instruments, silicon labs and stmicroelectronics[4]. although the ism radio band allows for bidirectional communication, sigfox supports only uplink applications limited to 15 bytes of traffic at a time and an average of 10 messages per day. on the technical side, sigfox is a connection hierarchy using signals in the ultra narrow band (unb) for the m2m system [5], this band allows to send signals to long ranges. the emitted signal can be inserted anywhere, even in enclosed areas. sigfox is present in a very wide area of coverage in the world. this company has a cloud system for its web interface as well as the management of its devices (api access point interface) and data configuration. the company offers a secure, responsive and efficient network with low throughput, but can support a wide range of products and sensors. the emission absorption for a sigfox modem can vary from 20 ma to 70 ma and its use is negligible when it is stagnant. the transmission power can be adjusted up to 14 dbm. the antenna radiation power should not exceed 25 mw. in the sigfox network, communication is two-way, meaning that devices send and receive data from a cloud platform. on this network, objects can send up to 140 messages of sizes equal to 12 bytes per day. this functionality is implemented as a polling, for which the object remains the leader, it avoids to remain permanently connected and allows him to ask the information system if there is information to download. this correspondence serves to dispose of a considerable time of autonomy in order to save energy from the batteries. objects exchange and share data and commands. in this case, we are talking about connected objects that are not very sophisticated such as coffee machines and the electricity meter. sigfox technology is easily incorporated into connected objects thanks to its miniature modem which allows the object to exchange information and data on the sigfox network. the data frames are transmitted over the sigfox network via antennas and then received by the proprietary server in the sigfox cloud[6]. this frames are directly retransmitted in a secure way thanks to the https protocol to the client server which can appropriate them on its software applications and then allows the use of the data to ensure that the appropriate services are used, namely that the information sent are difficult to hussein mroue et al. 2 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e3 decrypt in themselves. sigfox’s personal data protection system seems impenetrable, but it is different for customers thanks to the ip level security between the gateway and the cloud, as shown in the figure 1: the reliability of the information figure 1. sigfox network architecture sent over the network as well as the security of exchanges between the connected objects are ensured in the sigfox chain despite the use of the licensed frequency bands which are also exploited by other companies. the risk of interference does not exist between different companies operating the same frequency band in view of the new emission techniques developed in recent years. the waterproofing is therefore ensured in this context. the entire network is well protected against jamming. only device vendors are eligible to understand the nature and quality of the information exchanged between the computer sensor and the object itself. in other words, sigfox has good access control over its network. moreover, it is essential and very important to choose the location of the sensor because, like any radio signal, there may be a reception problem facing a thick concrete wall or a metallic surface. 2) lora network: the creation of the lora alliance[7] was announced at the ces in 2015. it is a consortium aiming at stripping a competing offer from sigfox. this open source (os) open system, based on lora technology, is certified by the french-based company cycleo in 2012. today, the alliance comprises 127 members including french players such as bouygues telecom, actility and sagecomm. the lora alliance is an open, nonprofit association of members who are confident that the internet of objects is the future of the communications world. it has been launched by industry leaders whose mission is to standardize the networks (lpwan) that are deployed worldwide to enable internet (iot), machine-tomachine(m2m), smart city and industrial applications. alliance members will cooperate in the global success of the lora protocol (lorawan), sharing knowledge and experience to ensure interoperability among operators in a single open global standard. lorawan is a network specification (lpwan) for wireless connected objects. lorawan targets the main internet requirements of objects such as secure two-way communication, mobility and location services. the lorawan specification provides seamless interoperability between smart objects without the need for complex local installations and gives the user, developer and enterprise the freedom to deploy the iot network. it’s open technology. this means that any company can create its own lora network and then exploit it, having purchased the necessary chips and gateways for network operation. lora is the designation attributed to the technology that relies on spread spectrum modulation of the lorawan protocol. the 3g and 4g cellular mobile networks are based on a communication protocol known by the abbreviation ip (internet protocol) whereas lora itself is based on its own lorawan protocol [8]. this technology is accessible (open source), allowing any company to design its own lora network and market it. to set it up, it is necessary to have an antenna connected to the internet by means of a wifi, ethernet or 3g connection or via a base station broadcasting at the frequency of 868mhz (band used in europe). the coverage capacity for a lora network is approximately 20km in rural areas and up to 2km in urban areas. the flow rate varies from 0.3 to 50 kbps and adapts with the power of transmission mechanically according to the need of the objects in order to optimize the bandwidth and to conserve as much as possible the use of the energy. the technology is not free, each component lora must pay royalties to the company sem tech, originally lora, to benefit from its use. the architecture of the lorawan network is generally presented in a star-shaped star topology in which the gateways are a transparent bridge connecting messages between the sensors and a central network server in the back end[9]. the gateways are connected to the network server via standard ip connections, while the sensors use wireless communication to one or more gateways. all communications from the sensors are generally bidirectional, but they also support operation such as multicast, allowing software upgrade on the air interface or mass message distribution to reduce the communication time on air. the communication between the sensors and the gateways is distributed over different frequency channels and data rates. selecting the data rate is a compromise between the communication range and the length of the message. using spread spectrum technology, communications with different data rates do not evaluation of lpwan technology for smart city 3 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e3 figure 2. lora network architecture interfere with each other, and create a set of virtual channels that increase the gateway’s capacity. lorawan data rates range from 0.3 kbps to 50 kbps. to maximize the battery life of the sensors and the overall network capacity, the lorawan network server individually manages the data rate and rf output for each terminal device by means of an adaptive data rate scheme (adr adaptive data rate). 3) lte-m: the historical ecosystem of cellular networks stands in the face of sigfox and lora. to do this, the 3gpp is studying the specifications to evolve the lte technology so that it can respond to lpwan networks sigfox and lora. this action will help mobile operators to evolve their existing networks to the iot-compatible network called ltem[10]. as most of the time, the standardization phase is a slow process that brings together equipment manufacturers and operators to unify their know-how and compete. major telecom leaders such as nokia and ericsson [11] support this combination of 3gpp. lte-m is the abbreviation for lte cat-m1 or long term evolution (4g), of category m1. this technology allows iot devices to connect directly to a 4g network, without going through a gateway. the strengths of this technology are price, battery life and the low cost of service for access to the lte network. this is not expensive because the devices can connect to the 4g network with much less expensive chips to manufacture, these chips operate in half-duplex mode and on a very narrow bandwidth. there are two types of modes that allow the batteries to keep a long life, the first is known as ”deep sleep”, psm power save mode as well as a receive mode (edrx extended discontinious reception), the sensors are periodically awakened while they are connected. the cost of the lte-m network access service is very negligible, because ltem sensors need a bit rate of about 100 kbps, which means that the 4g network will never be congested. the carriers (backhauling network) can offer service plans similar to the old pricing of 2g m2m technology and 4g prices. below is a table showing the specifications of this technology: deployment in the lte band range(max coupling loss) 156 db ; ≥ 13km downlink ofdma, bandwidth 15 khz, turbo code, 16qam, 1rx (half-duplex) uplink sc-fdma, bandwidth 15 khz, turbo code, 16qam bandwidth 1.08 mhz bit rate (ul/dl) 1 mbps for ul and dl duplex fd and hd (type b), fdd and tdd battery life (modes) psm (power save mode) and edrx (extended discontinuous reception) power 23 dbm, 20 dbm table i. specifications of lte-m iot technologies and m2m communications [12] are growing rapidly, lte, the 4th generation cellular technology known as the long-term evolution, is well placed to carry a lot of traffic for machine-to-machine communications and this is problematic because the lte is capable of carrying data at very high bit rates. to solve this problem, an extension of lte, often called lte-m, has been developed for m2m lte communications. new categories launched in the releases 13 of the 3gpp [13] standards known as lte cat 1.4mhz and lte cat 200khz (nb-iot narrow-band-iot). there are several features for m2m lte applications cite3gpp1 as well as requirements that make cellular networks viable: • wide range of equipment: any lte-m system must be able to support a wide variety of different types of equipment. this can be smart meters, vending machines and medical devices as well as safety machines. these different systems have many diverse requirements, so any lte-m system can be flexible. • low cost to purchase equipment: ltem must provide the benefits of a cellular system, but at low cost. • long battery life: many m2m sensors should be left unattended for long periods in areas where there is no power supply. maintaining batteries is expensive. this means that the lte-m system must be capable of draining very little battery and that the battery can last up to 10 years. • coverage: lte-m applications will need to operate in various locations and not just where reception is good. they must operate inside buildings, often in places where there is little access and where reception may be deficient. therefore, lte-m must be able to operate under all conditions. • large volumes low flow rates: the ltem must be structured in such a way that 4 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e3 hussein mroue et al. the networks can accommodate a large number of connected devices and require only small amounts of data to be transported at very low data rates. some updates are introduced in 3gpp rel 12 to meet ltem requirements. these updates require that the cost of an m2m modem should be about 40-50% cheaper compared to a conventional lte device (smartphone), making them similar to those of egprs (network enhancement gsm in the transport of packets). to meet these requirements, a new category of equipment has been implemented under the category lte category 0. these categories define the overall capabilities of the device so that the base station remains able to communicate properly in the network. in a lte-m network, m2m devices are low cost while having a limited capacity: • antennas: the ability to have a single receiving antenna, unlike other categories of devices • transport block size: there is a restriction on the size of the transport block. these low-cost lte-m devices are allowed to send or receive up to 1000 bits of unicast data per subframe. this reduces the maximum data rate to 1 mbps in the uplink and downlink • duplex: semi-duplex fdds are supported as an optional feature, which reduces costs by eliminating the rf switches and duplexers needed for full performance modems. this also means that it is not necessary to have a second phase-locked loop for the frequency conversion, although with only one pll the switching times between reception and transmission are longer. many features are proposed and prepared in the 3gpp release 13 standards, in terms of capabilities. we cite below the possibilities for improvement : • reduce bandwidth to 1.4 mhz for uplink and downlink • reduce transmission power to 20dbm • reduce support for downstream transmission modes • release requirements that require high levels of processing, such as downlink modulation. there is an additional improvement for lte-m under this release 13 with a reduced bandwidth option of 200khz in the uplink and downlink, often referred to as narrow band or narrow-band lte-m [14]. by reducing the bandwidth and also the data rate, an additional simplification of the modem can be obtained. the category is called cat 200khz. it is possible to compare different categories for lte-m systems. capacity rel8 cat4 rel12 cat0 rel13 cat1.4mhz rel13 cat200khz downlink (mbps) 150 1 1 0.2 uplink (mbps) 50 1 1 0.144 antennas 2 1 1 1 duplex mode full half half half bandwidth (mhz) 20 20 1.4 0.2 power (dbm) 23 23 20 23 table ii. comparaison of lte-m categories iii. sigfox and lora physical layer a. sigfox this technology uses bpsk as a modulation scheme for uplink. it uses the ultra narrow band with a bit rate is of 100 bps. b. lora lora uses a multitude type of modulation scheme (fsk, ook,..). it uses the wideband technology based on spread spectrum. using a scalable bandwidth (b) of 125 khz or 250 khz in europe and in addition of that, the bandwidth of 500 khz is using in us. a variable spreading factor (sf) can be chosen as function of received snr. sf adapts the length of a symbol, but also specifies the number of bits per symbol. so, changing the spreading factor results in a variable bit rate between 366 bps for the highest spreading factor (12) and 48 kbps for the lowest spreading factor (6) as shown in eq.1 rb = b 2sf × sf (1) iv. system model the system model used for measurements and comparison is based on an awgn channel model with only thermal noise with a noise temperature of 25 °c. in addition, we assume a distance dependent path loss with constant attenuation alpha = 2.5 db. for this model, the 2 base stations will be positioned at the same location and we assume the height of the base station at 100m and the nodes are mobile in an interval of [-200 m, 200 m] (fig 3) . here, only the uplink is considered, as the data in sensor networks generally flows in this direction. finally, the transmitter of the mobile device sends the maximum power allowed in most ism bands with a power of 25 mw (14 dbm). so we will 5 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e3 evaluation of lpwan technology for smart city calculate the signal-tonoise plus interference ratio (sinr) to know which technology is more robust to interference. figure 3. proposal model sinr = pr i +n (2) where pr is the received power, i is the interference and n is the noise. after this we will study the influence of spreading spectrum on the sensitivity of the lora receiver by comparing the sensitivity of receiver uses the fsk modulation and another uses the fsk modulation with direct modulation chirp spread spectrum dm css . the sensitivity is calculated according to the following equation : srx = snr×k × t0 ×b ×nf (3) where k is the boltzmann constant, t is the temperature at the input of the receiver, b is the bandwidth of receiver and nf is the noise figure. for lora, there is a gain of the processing belonging to the spreading spectrum where the parasitic signals are also reduced by the receiver process gain [15]: gp = 10log10( rc rb ) (db) (4) where rc is the chip-rate (chips/second) and rb is the bit-rate (bits/second) v. results the reason for having a ratio of 1000 is due to the fact that sigfox uses an ultra narrow band with a bandwidth of 100 hz, but lora uses a wideband with a bandwidth equal to 125 khz. in terms of robustness to interference, lora is more robust than sigfox. to date, there are not enough connected objects deployed running via distance (m) -200 -150 -100 -50 0 50 100 150 200 s in r ( db ) -10-6 -10-7 -10-8 -10-9 -10-10 -10-11 -10-12 sinr lora sinr sigfox figure 4. measurement of sinr lpwan networks, for this reason the probability of interference is very low. moreover, in the future, we must return to this model of simulation of interference with the densification of connected objects. bit rate (bit/sec) ×105 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 se ns iti vi ty ( db m ) -140 -135 -130 -125 -120 -115 -110 -105 -100 fsk with dm css fsk figure 5. comparaison of sensetivity the sensitivity is affected by the increase of the bit rate for the two cases fsk with dm css and traditional fsk. on the other hand, the sensitivity of fsk with dm css exceeds the sensitivity of traditional fsk by 10 db. this difference remains almost the same on the bit rate considered from 0.1× 105bit/sec up to 6× 105bit/sec. vi. conclusion in this paper, we explored the existing technologies for lpwan serving the internet of things. these technologies have characteristics like autonomy up to 10 years and carried up to tens of kilometers. in addition, we survey 3 lpwa technologies, ultra-narrow band solutions by sigfox, wide6 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e3 hussein mroue et al. band solutions by lora technology based on chirp spread spectrum (css) and lte-m technology by 3gpp. sigfox and lora were surveyed in terms of physical layer. we then proceeded to explore which of these two technologies is the more sensitive to interference. the role of spreading spectrum has be illustrated to improves the sensitivity of the receptor. references [1] internet of things a key pillar of digital transformation, idate research, octobre 2015. [2] petäjäjärvi, juha, et al ”evaluation of lora lpwan technology for remote health and wellbeing monitoring.” international symposium on medical information and communication technology ieee, 2016. [3] sigfox. [online]. available: http://www.sigfox.com/en/ [4] https://partners.sigfox.com/companies/chip-maker [5] lora alliance, https://www.lora-alliance.org/ [6] sigfox’s ecosystem delivers the worlds first ultralow cost modules to fuel the internet of things mass market deployment. [online]. available: https://www.sigfox.com/en/press/sigfox-s-ecosystemdelivers-world-s-first-ultra-low-cost-modules-to-fuelinternet-of-things [7] lora alliance defends tech against sigfox slur. [online]. available: http://www.lightreading.com/iot/iotstrategies/lora-alliance-defends-tech-against-sigfoxslur/d/d-id/722982 [8] lora alliance, https://www.lora-alliance.org/ [9] “lora technology.” [online]. available: http://loraalliance.org/what-is-lora/technology [10] d. flore, “3gpp standards for the internet-of-things,” february 2016. [11] ericsson and nokia siemen networks, lte evolution for cellular iot, 2014. [12] 3gpp tr 36.888, study on provision of low-cost machine-type communications (mtc) user equipments (ues) based on lte, v.12.0.0, june 2013. [13] “cellular system support for ultra low complexity and low throughput internet of things (release13),” 3gpp tr 45.820 v1.3.1, jun. 2015. [14] r1-157247, “nb iot – battery lifetime evaluation in inband operation”, nokia networks, ran1 83, anaheim, usa [15] an1200.22 lora™ modulation basics 7 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e3 evaluation of lpwan technology for smart city eai hricova_adamcik_corrections_smart cities ansactions analysis of publicly available business e slovakia 1 department of manufacturing management, faculty of manufacturing technologies with a seat in presov, technical university of kosice, bayerova 1, 080 01 presov, slovakia, romana.hricova@tuke.sk 2 stanislav@adamcik.sk abstract the paper analyzes publicly available e the problem of getting to the information, but getting to it as quickly as possible, the cheapest and, most importantly, getting it as accurately as possible. altho major shift has been made by launching the slovensko.digital platform. the aim of this initiative is to improve informatization in slovakia. the ambition of the article is ways to use it. keywords: e-data, consolidation, dataset, information. d o commons.org/licenses/by/3.0/ riginal work is properly cited. doi: 10.4108/eai.26-6-2018.154830 1. introduction nowadays, entrepreneurs, business entities but also private individuals do not have to deal with a lack of information, but instead choose from the overflow of information the right, relevant ones they need and which will be topical as well. especially for entrepreneurs, it is sometimes a problem to find information about business partners and to verify their credibility. truth is that every production unit that wants to be competitive in the present day should be characterized by a suitable combination of needed productivity, flexibility and quality. [1] obviously, if subjects can choose, they prefer official data sources, but those that are scarce, are not always in the form that individuals prefer or need, and most often are time-lag. that is why the resources provided by independent organizations are increasingly being searched for. even if they collect data from official sources, they often process, evaluate or link them, which will subsequently make it much easier for people to search. in 2000 was adopted act no. 211/2000 coll. on free access to information and on amendments to certain acts (freedom of information act). [2] the law stipulated which obligated persons must make the information t _____________ research article 1 analysis of publicly available business e-data in , stanislav ada,* romana hricová1 , stanislav adamčík2 department of manufacturing management, faculty of manufacturing technologies with a seat in presov, technical university of romana.hricova@tuke.sk ailable e-data that entrepreneurs need and use for their business in slovakia. today is not the problem of getting to the information, but getting to it as quickly as possible, the cheapest and, most importantly, getting it as accurately as possible. although data has been published in various forms and public institutions in the past, a major shift has been made by launching the slovensko.digital platform. the aim of this initiative is to improve informatization in slovakia. the ambition of the article is to point out what e-data is being provided today and what are the data, consolidation, dataset, information. accepted on , licensed rms of the creative http://creati e, distribution a reproduction in any medium so long as the nowadays, entrepreneurs, business entities but also private individuals do not have to deal with a lack of information, but instead choose from the overflow of information the right, relevant ones they need and which entrepreneurs, it is sometimes a problem to find information about business partners and to verify their credibility. truth is that every production unit that wants to be competitive in the present day should be characterized by a suitable combination of needed productivity, flexibility and quality. [1] obviously, if subjects can choose, they prefer official data sources, but those that are scarce, are not always in the form that individuals prefer or need, and most often are urces provided by independent organizations are increasingly being searched for. even if they collect data from official sources, they often process, evaluate or link them, which will easier for people to search. ed act no. 211/2000 coll. on free access to information and on amendments to certain the law stipulated which obligated persons must make the information available. these include state authorities, municipalities, higher territorial units as well as those legal entities and natural persons to whom the law confers the power to decide on the rights and obligations of natural or legal persons in the field of public administration, and only to the extent of their decisionfor the law arises because official information is much more valuable than unofficial because the data thus obtained is not only from the sample of respondents but from the basic set, i.e. all respondents who are required to publish this information. entities are also faced with the problem of comparing data for each period and thus monitoring economic developments, for example, supplier, competitor or other relevant business. very important precondition for a successful company application in the business environment is its ability to archive relevant data in the long term on the basis of management quality systems, exactly according to the requirements spec concrete conditions. [3] it is good if data are available for at least the last 3 years. it is true that the harder the history can be found, the better it is for the search person, because it can create a more comprehensive view. all these facts, plus the constant pressure on public administration, the growing demands accuracy of information in the shortest possible time, have research article data in department of manufacturing management, faculty of manufacturing technologies with a seat in presov, technical university of data that entrepreneurs need and use for their business in slovakia. today is not the problem of getting to the information, but getting to it as quickly as possible, the cheapest and, most importantly, ugh data has been published in various forms and public institutions in the past, a major shift has been made by launching the slovensko.digital platform. the aim of this initiative is to improve data is being provided today and what are the . this is an open access article distributed under the ), which permits unlimited available. these include state authorities, municipalities, her territorial units as well as those legal entities and natural persons to whom the law confers the power to decide on the rights and obligations of natural or legal persons in the field of public administration, and only to -making activities. the need for the law arises because official information is much more valuable than unofficial because the data thus obtained is not only from the sample of respondents but all respondents who are required to entities are also faced with the problem of comparing data for each period and thus monitoring economic developments, for example, supplier, competitor or other important precondition for a application in the business environment is its ability to archive relevant data in the long term on the basis of management quality systems, exactly according to the requirements specified in it is good if data are available for least the last 3 years. it is true that the harder the history can be found, the better it is for the search person, because it can create a more comprehensive view. all these facts, plus the constant pressure on public administration, the growing demands for transparency and accuracy of information in the shortest possible time, have eai endorsed transactions on smart cities received on 08 december 2017, accepted on 20 march 2018, published on 26 june 2018 copyright © 2018 romana hricová and stanislav adamčík, licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. ∗corresponding author. email: romana.hricova@tuke.sk eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e2 r. hricová, s. adamčík a. n. author, b. n. author and c. n. author 2 yielded results. in its way, 2016 became a breakthrough thanks to the launch of the slovensko.digital platform. 2. data providers publicly available data can be obtained from the following groups of providers: 1) state entities, 2) independent organizations, 3) enterprises. 2.1. state entities the most important sources of published data are: a) statistical office of the slovak republic the oldest source of published data is statistical office of the slovak republic. the history of organized statistical surveys on the territory of today's slovakia extends until 1715, when a whole-country census of the population was carried out in hungary. nowadays its basic missions are to provide statistical information on the state and development of the economy and on social development in the slovak republic to legislative and government bodies, state administration bodies, municipalities, the public and foreign users. the conditions for obtaining the necessary information are regulated by act no. 540/2001 coll. on state statistics, which entered into force on 1 january 2002. pursuant to this act, a legal entity or a natural person who is a reporting entity is obliged to provide free of charge, fully, truthfully and within specified deadlines, the data required by the state statistical surveys, which are listed in the state statistical surveys program. statistical office offers datacube the classification system of individual tables is based on maintaining the structure of domains and fields similarly as in the web portal. data from various statistical fields are presented in the form of multidimensional tables in monthly, quarterly or yearly time series and allow creating your own selections. at the end of the title of each table there is eight-digit code, which is the unique identifier. the outputs can be exported to file formats: pdf and xls. [4] in this context, it is important to note that the statistical office provides only very limited information on individual enterprises. by company registration number (ičo) or name, you can search for an organization. the following organizational information will then be shown: company id (ičo), business name, date of beginning, date of termination, address, district, municipality, legal form, main activity, institutional sector, type of ownership and size of organization. since no other information can be found, the only relevant figure is whether the organization exists or not. directly on this page is the opportunity to choose "open data". the statistical office of the slovak republic publishes the available data in open formats with a text description of the published data content, based on the government resolution of the slovak republic no 59/2015 of 11 february 2015 approving the open government partnership action plan of the slovak republic 2015. [4] figure 1. english page of statistical office of the slovak republic with link to open data [4] b) national agency for network and electronic services national agency for network and electronic services was created within the project: “electronic services of government office of the slovak government edemocracy and open government”, financed from the resources of the european union. [5] open data portal was created as a part of the initiative for open governance, which intention is to improve governance and public matters, through increasing transparency, effectivity and responsibility. the portal is a catalog containing various datasets published by obliged entities in the slovak republic. data can be collected from the web directly from the published links or by searching. open data portal is capable to store a copy of data or accommodate them space in database, along with standard visualization tools, according to the type of data (and the forms of use). [5] specific datasets can be found at https://data.gov.sk/dataset. there are 1243 different datasets from multiple organizations at present (december 2017). fig. 2 shows english homepage of the central public services portal for people. [5] these datasets can be searched for and filtered by organizations, keywords and expressions, file formats, licenses, and the specified sequence on the portal,. datasets are available in different file formats. the largest representation is csv and xml. eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e2 analysis of publicly available business e-data in slovakia 3 figure 2. english homepage of the central public services portal for people [5] c) commercial bulletin the commercial bulletin [6] is operated by the ministry of justice of the slovak republic. according to act no.200/2011 coll. on the business journal, the ministry of justice of the slovak republic, as the publisher of the business journal, also makes available the data published in the business journal in the form of structured data that allows search and their further automated processing. to download structured data, it is necessary to register for free and then download the data on working days from 7.00 pm until 7.00 am, on unlimited through non-working days. published texts are only informative and not legally binding. data are updating every working day. provides the following data: • commercial register • collection of documents • notices of initiation of winding-up or co-operation proceedings without liquida-tion • bankruptcy and restructuring • claims of liquidators • other announcements • specification of received share of income tax paid • auctions • sale of property • management reports • mandatory published contracts fig. 3 shows search page of the commercial bulletin. [6] figure 3. search page of the commercial bulletin [6] d) social insurance agency there is only a database of debtors in the page of the social insurance agency. [7] data is in two formats: txt and csv. figure 4. debtor database search page of the social insurance agency [7] e) the ministry of finance of the slovak republic maintains a register of financial statements [8]. the register of the financial statements was established with the aim of improving and simplifying the business environment and reducing the administrative burden of the business. simultaneously the register improves accessibility and quality of the information about the accounting entities. [9] it is possible to find complete accounts in the register by name, company registration number or tax id and if the company was required to disclose both the annual report and the auditor's report, these are also available. however, a more in-depth investigation will show that not every company is likely to upload the requested data or submit it in the required format as some data shows "data not available in a structured form." there is homepage of the register of financial statements on the fig.5. [8] figure 5. homepage of the register of financial statements [8] eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e2 r. hricová, s. adamčík a. n. author, b. n. author and c. n. author 4 f) central register of contracts the central register of contracts [10] is the website on which contracts concluded by the liable entity (pursuant to §5a of act no. 211/2000 coll.) are published. [2] a publicly disclosed contract involving the ministry, the other central state administration body, a public body and a budgetary organization or a contributory organization established by them, which are liable pursuant to article 2, shall be published in the central register of contracts; the liable entity shall immediately send to the office of the government of the slovak republic a contract for publication. the central register of contracts is a public list of mandatory contracts, which are maintained by the office of the government of the slovak republic in electronic form; register is a public administration information system. in this register is today approx. 1,496,696 contracts (december 2017). fig.6 shows english homepage of the central register of contracts. [11] figure 6. english homepage of the central register of contracts [11] 2.2. independent organizations these include organizations interested in giving the general public access to publicly available data in a transparent form or in the form of a suitable dataset for further processing. these organizations receive data from the state administration, trying to consolidate them. the most distinguished providers include: a) fair-play alliance the fair-play alliance is a standard non-profit and non-party civic association founded in 2002 by former journalist zuzana wienk [12]. the civic association manages the datanest.sk project [13], which offers various datasets (the english homepage of the datanest is on the fig.7). regularly updated datasets include the organization's register, which currently contains over 1,400,000 entries. figure 7. the english homepage of the datanest project managed by the fair-play alliance [13] b) platform slovensko.digital (slovakia.digital) slovensko.digital is a civil association aimed at enhancing the quality of digital services in slovakia. the members of the association are mainly it specialists. since the start of their foundation, they have launched more successful projects. in the area of public disclosure, this is the following: • ekosystém.slovensko.digital [14] (ecosystem.slovakia.digital) • verejne.digital [15] (public.digital) ecosystem.slovakia.digital [14] this project is so far the most significant that the slovak.digital platform has put into operation. includes services: datahub [16] the service provides access to consolidated and linked structured data via a simple rest api [17]. using rest api [18] is beneficial for businesses as well as individuals who can use this data in their information systems. the user no longer has to rewrite the published data from the internet; the service will be delivered automatically. however, the information system must be adapted to communicate with the web service. for advanced data analysis, it is also possible to access the sql database. registration is required here. open data & api open data are in this case sql databases that are really made available to the general public and are freely available for download. currently there are the following databases: • register of legal entities database of legal persons, entrepreneurs and public authorities. there are more than 1.4 million legal entities with complete history. source: register and identifier of legal entities, entrepreneurs and public authorities, statistical office of the slovak republic. • central register of contracts database of contracts of the central register of contracts since 2011. source: data.gov.sk, central register of contracts, office of the government of the slovak republic. eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e2 5 • bulletin of public procurement public procurement database from 2014. source: data.gov.sk, bulletin of public procurement, office for public procurement. • commercial bulletin – database of notices from commercial bulletin since 2011. source: commercial bulletin, ministry of justice of the slovak republic. • register of financial statements database of accounting units of the register of financial statements. source: register of financial statements, ministry of finance of the slovak republic. • debtors of the social insurance agency a database of social insurance debts from 2014. source: debtor lists, social insurance agency. • debtors of the general health insurance company database of debtors of the general health insurance company from june 2016 each of these databases is guided by practical and streamlined documentation (table and column descriptions). each of them is also available with the rest api, which makes available consolidated and linked structured data in the json format. [19] public digital [15] homepage of public digital is showed on the fig.8. the service is made available in the form of a website. its control is very intuitive and simple. the problem is that the data listed on the site is sometimes old (over 10 years old). by random check, it has been shown that e.g. the self-employed persons are looking for an address that has not only been out for years, but the trade has been abolished and the self-employed person died (a particular search the trade was cancelled 11 years ago and the selfemployed person died 5.5 years ago). within this project there are two more: • links.public.digital (prepojenia.verejne.digital) the purpose of the service is to search for links between businesses and people • procurement.public.digital (obstaravania.verejne.digital) the purpose of the service is to identify and notify tenderers who should be involved in public procurement. figure 8. homepage of the public.digital [15] 2.3. enterprises probably the most well-known private company that provides information on the company's finances is finstat, ltd.. this company was established in 2012 and the first release was launched the following year. the aim of the company is to help people simply and free to assess the financial health of slovak businesses. the effort is to connect the data sources to one location, to process and analyze their data. at the same time, it helps to create a picture of the whole market slovak enterprises as a whole, individual sectors and groups of entrepreneurs. finstat uses data sets from up to 14 data sources. among the most important are the following: commercial bulletin, business register, trade register, accounts list, bankruptcy register, insurers lists, financial reports, and court decisions. [20] company gradually adding additional data sources, but very important information is, that only a few of these resources are free. the free information that the interested person receives is in a simplified form, and even if they are processed graphically, there is no possibility of finding a more detailed structure. if person concerned would like to buy, for example datasets, price is not published on the internet, must contact the company. figure 9 shows english homepage. figure 9. the english homepage of the finstat [21] finstat uses data sets from up to 14 data sources. among the most important are the following: commercial bulletin, business register, trade register, accounts list, bankruptcy register. second private company which provides data about slovak enterprises is foaf ltd.. the name foaf comes from the english acronym friend of a friend and refers to the phenomenon of the small world networks. the project itself draws information on companies from the slovak commercial register, the business journal, the financial statements register, the database of debtors of the general health insurance company, the social insurance and union insurance company, the financial eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e2 analysis of publicly available business e-data in slovakia r. hricová, s. adamčík a. n. author, b. n. author and c. n. author 6 report, the public procurement bulletin and other databases. this information comes from publicly available sources, which are public administration information systems, accessible to the general public. [22] however, the main ambition is to search for and display deeper connections between people and businesses in slovakia using graph algorithms, so thanks to foaf.sk anyone can easily browse the social network of slovak businesses and entrepreneurs and see the relationships between them. as with finstat s.r.o. foaf provides only a fraction of the information for free, others have to buy the buyer, and the price list with the services to be paid is published on the internet. 3. the utility of publicly available business data as can be seen from the previous report, there are now enough public data providers offering information on business entities. on the one hand, there are state organizations, which by law have access to information and on the basis of act no. 211/2000 coll. on free access to information to the general public. the credibility of these data is high, so the entrepreneur gets the opportunity to verify the reliability of a potential partner by accessing the most common financial data, assets, liabilities, sales. the problem is that sometimes it is not possible to get to the freshest information as they are posted with a time delay. private companies that publish their data draw from official sources, so there is a certain time delay. on the other hand, the data is being processed (for example, finstat compares the development of the company's financial indicators also graphically), but for more detailed data, the bidder has to redeem it. as a second problem, it turned out that with private providers, data is not filtered and the consequence is that if someone needs to find the manager, the address or address of the entrepreneur will come across not only old but even outdated information. random search via public.digital showed that the real estate was still featured by the owners who died or the real estate sold and can still be seen, for example, self-employed persons who have been canceled for more than 10 years. therefore, data needs to be verified from multiple sources, and even if the provider states that it is drawing data from official sources, it is also necessary to check their timeliness. more detailed or processed data is payable because it is time consuming to consolidate them. a good solution could be to create software that would allow data to be edited and supplemented by notes. 4. conclusions the paper deals with the most well-known and largest providers of publicly available e-data from state-owned organizations on the one hand and private providers on the other. a closer look at the information provided has highlighted a number of data issues: not always current, they are mostly informative only, some are so old that they no longer correspond to the truth. thanks to the freedom of information act 2000, state entities were forced to disclose information that entrepreneurs need for their business. these data are from a reliable source, but they need to be verified or searched from multiple sources because the data found is not in the desired form. it is still true that the use of data acquired for business can be both time and costly. there remains an open space for finding the right form of processing and consolidating such data so that the user has the data as quickly as possible, most accurately and in particular as simple as possible. acknowledgements. paper originates with the direct support of ministry of education of slovak republic by grants kega 007tuke-4/2018 and vega 1/0614/15". references [1] monkova, k. et al.: newly developed software application for multiple access process planning, in: advances in mechanical engineering. 2014, p. 3907139071. issn 1687-8132 [2] zákon č. 211/2000 z. z. o slobodnom prístupe k informáciám a o zmene a doplnení niektorých zákonov (zákon o slobode informácií). [online] [22.5.2017] available at internet: http://www.zakonypreludi.sk/zz/2000-211 [3] monka, p. et al.: design and experimental study of turning tools with linear cutting edges and comparison to commercial tools, international journal of advanced manufacturing technology, 85 (9-12), 2016, pp. 23252343. [4] statistical office of the slovak republic [online] [24.11.2017] available at internet: https://slovak.statistics.sk/ [5] national agency for network and electronic services [online] [02.12.2017] available at internet: https://data.gov.sk/en/ [6] commercial bulletin [online] [21.11.2017] available at internet: https://www.justice.gov.sk/obchodnyvestnik/stranky/stru kturovane-udaje.aspx [7] social insurance agency [online] [21.11.2017] available at internet: http://www.socpoist.sk/zoznam-dlznikov-emw/ [8] register of financial statements [online] [21.11.2017] available at internet: http://www.registeruz.sk/cruzpublic/domain/accountingentity/simplesearch [9] register of financial statements [online] [21.11.2017] available at internet: http://www.registeruz.sk/cruzpublic/home [10] central register of contracts [online] [02.12.2017] available at internet: http://www.crz.gov.sk/ eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e2 7 [11] central register of contracts [online] [02.12.2017] available at internet: http://www.crz.gov.sk/index.php?id=114372 [12] fair-play alliance [online] [21.11.2017] available at internet: http://www.fair-play.sk/abouts [13] datanest project [online] [02.12.2017] available at internet: http://datanest.fair-play.sk/ [14] ecosystem slovakia digital [online] [02.12.2017] available at internet: https://ekosystem.slovensko.digital/ [15] public digital [online] [02.12.2017] available at internet: https://verejne.digital/ [16] ecosystem slovakia digital [online] [02.12.2017] available at internet: https://ekosystem.slovensko.digital/sluzby/datahub [17] wikipedia [online] [22.5.2017] available at internet: https://en.wikipedia.org/wiki/representational_state_transf er [18] ecosystem slovakia digital [online] [02.12.2017] available at internet: https://ekosystem.slovensko.digital/premiove-api [19] wikipedia [online] [16.10.2017] available at internet: https://cs.wikipedia.org/wiki/javascript_object_notation [20] finstat [online] [16.10.2017] available at internet: www.finstat.sk [21] finstat [online] [16.10.2017] available at internet: https://finstat.sk/information-of-slovak-companies [22] foaf ltd. [online] [02.12.2017] available at internet: http://foaf.sk/info/o-foaf-sk eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e2 analysis of publicly available business e-data in slovakia an application of iot and wsn to monitor the temperature of ac transmission line 1 an application of iot and wsn to monitor the temperature of ac transmission line rashmi s 1,*, shankariah 2, pooja h k 3 and upanya m 3 1associate professor, department of eee, vidyavardhaka college of engineering, mysuru, india 2professor, department, of ece, sri jayachamarajendra college of engineering, mysuru, india 3assistant professor, department of eee, vidyavardhaka college of engineering, mysuru, india abstract with the increase in demand for power with population, power quality issue is one of the challenging areas which needs utmost attention. it is a known fact that the transmission of power takes place through transmission lines which are bare conductors and are prone to many natural situations, which degrade the quality of power and also leads to sagging of conductors. variation in temperature is a commonly affecting parameter over these transmission lines and leads to deviation in the power flow affecting ampacity of the conductors and over a period of time leads to unwanted sag. monitoring the temperature of transmission lines is done continuosly using lm35 temperature sensor and an application of internet of things (iot) through thingspeak application platform to track the variations. an wireless sensor network (wsn) environment is created to transmit the temperature data from one node to another using ns-2 platform. keywords: sag, temperature sensor, internet of things (iot), wireless sensor network (wsn). received on 05 march 2020, accepted on 10 april 2020, published on 17 april 2020 copyright © 2020 rashmi s et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.163990 *corresponding author. email: rashmi.s@vvce.ac.in 1. introduction overhead transmission lines are thermally limited to the amount of electrical current it can carry, due to the physical properties of the conductor. in overhead transmission lines, resistance of the conductor is the main reason for losses. when the current in conductor tries to overcome the ohmic resistance of the line, the power is dissipated in the form of heat, leading to increase in temperature of the over head transmission line. one of the major contribution to the sagging is increase in temperature. increase in the sagging affects the physical property of the conductor. hence, monitoring the temperature in overhead transmission line plays vital role. lm35 temperature sensor is used for monitoring the temperature and wireless sensor network environment is used to transmit the data of temperature from one node to another using ns-2 platform. 2. literature survey the temperature sensor ds1820 is used to monitor temperature of transmission lines indoor and outdoor. the maximum current capacity of transmission lines changes with line temperature. however, the maximum current capacity can only be calculated by conductor temperature model [1]. monitoring of transmission line is required for efficient ampacity. the sag and the conductor temperature are the two parameters defines the ampacity of overhead transmission line [2]. on everyday basis the temperature of the transmission line conductor is typically 5℃ to 15℃ above the air temperature [3]. the temperature of conductor has a very significant impact on the power flow calculations. the power flow model has depicted significant changes with and without temperature considerations. in power flow calculation procedure, the line resistances are assumed to be invariable which does eai endorsed transactions on smart cities review article eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e4 mailto:https://creativecommons.org/licenses/by/4.0/ rashmi s et al. 2 not conform to the actual. resistance of transmission lines are changed with changes of external environment like temperature and power distribution.[4]. overhead transmission line conductor clearance is a key limiting factor. monitoring the conductor sag can be used for warning purposes to ensure that mandatory clearance limits are not violated [5]. there is a increasing demand for reducing accidents and speeding up diagnosis for overhead transmission line. some of the significant fault includes sag which poses serious concerns for continuous operation of overhead transmission lines under changing weather conditions [6]. temperature dependence can be determined as shown in below formula. rtc=rt0[1+α(tc-t0)] (1) where α = 0.0039 is the temperature coefficient for aluminum, rtc and rt0 are the resistances at temperatures tc and t0 correspondingly. increase in temperature leads to increase in the length of outstretched conductor. the amountof increase in length is given by δl =αt (2) α = the coefficient of thermal expansion t = the temperature increase in ℃ s = the span length in meters an overheating electrical transmission line sagging led to tree sparking causing greatest power failure in the western united states in 1996. a similar incident is suspected to have caused the recent east coast blackout [7]. based on the physical properties of the conductor, overhead transmission lines (tls) are thermally limited to the amount of electrical current they can carry. transmission line current carrying capacity is set to static or seasonally varying values based on a conservative assumption of the environmental conditions (e.g., low wind speed and high ambient air temperature) [8]. the carrying capacity of electric power cables decreases as ambient air temperatures increases. during summer, electricity loads increases due to increased air conditioning usage. higher ambient air temperatures may strain overhead transmission line by increasing peak electricity load. [9]. in overhead transmission lines, resistance of the conductor is the main reason for losses. when the current in conductor tries to overcome the ohmic resistance of the line, the power is dissipated in the form of heat, which is directly proportional to the square of the r.m.s current flowing through the line [10]. the optical current sensing devices provide wider dynamic range, lower weight, immunity towards electromagnetic interference and improved safety when compared to the heavy electronics for the same operation and this happens mainly due to high intrinsic insulating properties of optical fibers. an optical sensor with fibre bragg gratings(fbg’s) which can be used to measure temperature and current of transmission lines accurately [2]. a 9-bus, 3 generator power system to analyse the impact of temperature variation. the authors conclude that approximately 3.5% difference in power flows on the branches were observed. the effect of temperature cannot be neglected especially when the lines are closer to their maximum power handling capabilities according to the authors [11]. the changes in transmission line resistances due to temperature have non-negligible effect on state estimation accuracy. the more accurate allocation of transmission lossess, accurate power flow and network voltage profile is possible only when the state estimation results are accurate for which a more reliable representation of power system is to be considered, line heat balance equation and weather data is utilized [12]. the level of infrastructure utilization and the efficiency of informationization can be improved through iot as well control over high voltage equipments can be achieved with intelligent decision making and high degree of cognitive with iot communication among different objects, various entity and virtual body is made possible through the technology of iot. the redundancy in data can be eliminated from the collected mass of sensed and identified information [13]. an application of iot connected healthcare to monitor body temperature distribution and heartbeat is proposed by the authors of [14]. intercommunication between various heterogeneous objects, wearables, sensors and appliances are efficiently enabled through iot which offers high quality services [15]. a highly federating intelligent application for iot to distinguish and protect the public data as well as private data without cross reffering the information has been proposed by the authors of [16]. wsn technology can enhance many aspects of present electric power systems, which includes power generation, distribution and utilization. hence, wsn is an important aspect of electric power system. typically, wired communication is used for monitoring and diagnosing the electric power system, this kind of communication requires expensive communication cables. hence, there is a need for wireless monitoring of electric power system [17]. wireless sensor network has the ability to configure and organize into effective network for communication. wireless sensor network has the capacity to access data in difficult situations and large geographical area. wireless sensor network has better flexibility and mobility compared to wired network. [18]. 3. methodology methodology includes monitoring the temperature sag of overhead transmission line and block diagram representation for the proposed work. 3.1. monitoring the temperature sag of overhead transmission line the overhead transmission lines are constructed with minimum ground clearance and sag template which follows the electricity board specifications as per indian electricity rules., 1956, rule77. one of the major contributions to sagging is raise in temperature which has to be monitored regularly for human safety. an illustration of the conductor sag as shown in figure 1 is given an approach to be monitored with the help of eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e4 an application of iot and wsn to monitor the temperature of ac transmission line 3 temperature sensor lm35 and an equation based sag calculation as given in equations (3), (4), (5) and (6) is done by atmega avr microcontroller. figure 1. illustration of conductor sag d = sag (m) s = span length (m) l = line length (m) h = horizontal component of tension (n) t = total tension (n) w = weight per unit length of conductor. (n/m) x = horizontal distance from lowest point (m) y(x) = vertical distance from lowest point at x (m) where, 𝐿𝐿0 : initial length (𝑓𝑓𝑓𝑓). : length at high-temperature conditions (m). 𝐻𝐻0 : stringing (initial) tension( 𝑙𝑙𝑙𝑙𝑙𝑙). 𝑇𝑇0 : stringing temperature( ℃) εc : plastic deformation of the cable. 3.2. block diagram representation the block representation for sag calculation with increase in temperature is shown in figure 2 and its practical implementation is shown in figure 3 which works according to the flowchart shown in figure 4. the program is written in programmers notepad using embedded c and is transferred to the microcontroller using avr dude. the usb based programmer for the avr is usbasp. figure 2. block diagram representation 4. practical implementation figure 3 represents the practical implementation of the temperature sensor node. figure 3. practical implementation of the sensor node 4.1. flowchart representation the figure 4 represents the flowchart representation for the proposed paper. 4.2. internet of things the information regarding the transmission line temperature and sagging of the line is transmitted using internet of things. here things is the temperature sensor and the application platform for internet of things is thingspeak which include real time data collection, data processing etc. eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e4 4 5. results teraterminal is an emulator where the actual temperature and amount of sagging is displayed. cp2102 transmitter is connected between microcontroller and teraterminal serial port. figure 5 shows teraterm display on screen and figure 7 shows thingspeak application platform. it can be observed that the display showing 034054 for a 33kv line where 34 represents the amount of sagging in cm and 54 represents the temperature in oc. the output is also observed on lcd for sagging information and on led’s for temperature as shown in figure 6. 00100111 on led’s represent the temperature of 27oc. figure 8 represents the variation in temperature and figure 9 represents the sagging variation. figure 4. flowchart representation figure 5. tera term showing the sagging with temperature figure 6. lcd showing the sagging and leds the temperature rashmi s et al. eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e4 an application of iot and wsn to monitor the temperature of ac transmission line 5 figure 7. thingspeak application platform figure 8. graph representing temperature variation 6. conclusion in a over head transmission line, variation in temperature leads to deviation in power flow. the current carrying capacity of the conductor is also affected by variation in temperature, over a period of time leads to unwanted sag. monitoring the temperature of transmission lines is done continuosly using lm35 temperature sensor and an application of iot through thingspeak application platform to track the variations. wsn environment is created to transmit the temperature data from one node to another using ns-2 platform. acknowledgements. the authors would like to thank the management of vidyavardhaka college of engineering, affiliated to vtu mysuru, karnataka, india for supporting this research work. references [1] song nie, yang-chun cheng, yuan dai “characteristic analysis of ds18b20 temperature sensorin the high-voltage transmission lines dynamic capacity increase” energy and power engineering, 2013, pg 557-560. [2] nenad gubeljak, bojan banic, viktor lovrencic, matej kovac, srete nikolovski, “preventing transmission line damage caused by ice with smart on-line conductor monitoring”, international conference on smart systems and technology 2016. [3] dale a douglass, mohammad pasha, william chisholm, “realtime overhead transmission line monitoring for dynamic rating”, ieee transactions on power delivery january 2014. [4] lei luo, xingong cheng , xiju zong, wen wei , chao wang, ”research on transmission line losses and carrying current based on temperature power flow model”, 3rd international conference on mechanical engineering and intelligent systems (icmet) 2015. [5] satish m. mahajan, senior member, ieee, and uma mahesh singareddy, “a real-time conductor sag measurement system using a differential gps”, ieee transcation on power delivery, vol. 27, no. 2, april 2012. [6] arsalan habib khwaja, qi huang, zeashan hameed khan, “monitoring of overhead transmission lines: a review from the perspective of contactless technologies” sensing and imaging, article number 24 (2017). [7] oluwajobi f. i., ale o. s. and ariyanninuola a, “effect of sag on transmission line sag incident”, journal of emerging trends in engineering and applied sciences, 2012. [8] bishnu p. bhattarai, jake p. gentle, tim mcjunkin, porter hill, kurt s. myers, alexander w. abboud, rodger renwick, david hengst, “improvement of transmission line ampacity utilization by weather-based dynamic line rating”, ieee transaction for power delivery, 2018. [9] matthew bartos, mikhail chester, nathan johnson, brandon gorma , daniel eisenberg, igor linkov, matthew bates, “impacts of rising air temperatures on electric transmission ampacity and peak electricity load in the united state”, environment research letters, volume 11, iop publication ltd, november 2016. [10] ganiyu adedayo ajenikoko, bolarinwa samson adeleke, “effect of temperature change on the resistance of transmission line losses in electrical power network”, international journal of renewable energy technology research, vol. 6, no. 1, january 2017, pp. 1-8. figure 9. graph representing sagging variation eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e4 rashmi s et al. 6 [11] valentina cecchi and matthew knudson, “study of effects of temperature dependent electric power transmission line models on estimation of transfer capabilities”, 11th international conference on applications of electrical and computer engineering, march 2012, pp 64-69. [12] marija bockarjova, goran andersson, “transmission line conductor dependent temperature impact on state estimation accuracy”, ieee lausanne power tech july 2007. [13] ye cai, xiao-qin huang, and jie he, “high voltage equipment monitoring system based on iot”, international conference on wireless communications and applications, 2011, pp 44-57. [14] taiyang wu, fan wu, jean-michel redouté, and mehmet rasit yuce, “an autonomous wireless body area network implementation towards iot connected healthcare applications”, ieee, body area networks, 16 june 2017. [15] anderson augusto simiscuka, cristina hava muntean, gabrielmiro muntean, “a networking scheme for an internet of things integration platform”, ieee international conference on communications workshops (icc workshops), 21-25 may 2017. [16] chi-sheng shih, ching-chi chuang and hsin-yuan yeh, “federating public and private intelligent services for iot applications”, 13th international wireless communications and mobile computing conference (iwcmc), 26-30 june 2017. [17] vehbi c. gungor, bin lu, and gerhard p. hancke, “opportunities and challenges of wireless sensor networks in smart grid”, ieee transactions on industrial electronics, vol. 57, october 2010. [18] katarzyna mazur, michalwydra, bogdan ksiezopolski, “secure and time-aware communication of wireless sensors monitoring overhead transmission lines”. sensors, 11 july 2017. dr. rashmi s received her bachelor of engineering in electrical and electronics engineering from national institute of engineering, mysore, affiliated to visvesvaraya technological university, belgaum, karnataka, and obtained her master’s degree in the area of vlsi design and embedded systems from sri jayachamarajendra college of engineering, mysore, affiliated to visvesvaraya technological university, belgaum, karnataka. she completed her ph.d under the guidance of dr. shankaraiah in the area pertaining to wsn application to power systems. her research interests include embedded systems, vlsi and power engineering. she has 6 conference and 8 international journal publications to her credit. she is also the life member of iste and iete. at present she is working as associate professor in the department of electrical and electronics engineering at vidyavardhaka college of engineering, mysuru, karnataka, india. dr. shankaraiah received his b.e. degree in electronics and communication engineering from mysore university, mysore, india, in 1994, m.tech. degree in digital electronics and communication systems from mysore university in 1997.he completed ph.d. under the guidance of prof. p.venkataram, dept. of ece, iisc., bangalore. he has investigated a transactions based qos, resource management schemes for mobile communications environment. he has more than 20 years of teaching experience in engineering. he has published more than 20 papers in national and international journals and conferences. he is a reviewer and chair for many conferences. his research interest includes bandwidth management, quality of service (qos) management, topology management, and energy management. he is a student member of ieee and life member of india society for technical education (lmiste). he is presently working as professor in the department of e&c at sri jayachamarajendra college of engineering, mysuru, karnataka, india. pooja h k, received the bachelor of engineering degree in electrical and electronics engineering from shridevi institute of engineering & technology affiliated to vtu, karnataka, india, and the master of technology degree in power electronics from oxford college of engineering affiliated to vtu. currently working as assistant professor in the department of electrical and electronics engineering at vidyavardhaka college of engineering, mysuru, karnataka. india upanya m, received the bachelor of engineering degree in electrical and electronics engineering from cambridge institute of technology, bangalore, affiliated to vtu, karnataka, india, and m.e in control and instrumentation from university visvesvaraya college of engineering (uvce), affiliated to bangalore university. currently working as assistant professor in the department of electrical and electronics engineering at vidyavardhaka college of engineering, mysuru, karnataka, india. eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e4 an approach for rapid generation of interactive spider maps for public transport networks an approach for rapid generation of interactive spider maps for public transport networks sara santos1,∗, teresa galvão1,2, thiago sobral1,2 1faculty of engineering of university of porto, portugal 2inesc tec, porto, portugal abstract a spider map is a type of schematic map that allows one to answer questions like "from where i am, where can i go?", as it provides only the essential information for a given geographical area (hub), from which lines emerge, whilst keeping the geographic context. they are often designed manually for a limited set of locations, thus reducing its widespread adoption. moreover, spider maps should conform to several design constraints, which turns the automated generation into a complex problem. optimisation techniques have been applied to this problem, although existing solutions are time costly and require heavy computational power. this paper presents an approach to automatically generate feasible spider maps within a short execution time based on an algorithm that adapts state-of-the-art methods, producing adequate quality maps to be manipulated in interactive media, based on the areas selected by the user. we report the results of a case study for areas in the city of porto, portugal. received on 02 february 2020; accepted on 26 august 2020; published on 27 august 2020 keywords: spider maps, schematic maps, public transport, automation. copyright © 2020 sara santos et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.18-8-2020.166007 1. introduction major cities have complex public transport systems that are part of citizens’ daily commuting. such systems ought to be encouraged as an alternative to private transport. public transport maps provide simplified representations of their corresponding network infrastructure, thus they should be of easy interpretation, aiming to facilitate the user experience and to increase public transport ridership. public transport maps are often represented by schematic maps, since they fulfill the need for simple and effective representation of complex networks [1], with indication of the available services and navigation alternatives. schematic maps are subject to a number of generalisation and simplification processes so as to translate the mental representation of the network, depicting the services and commuting possibilities within the map range. a specific type of schematic map is the spider map, which can be used to represent ∗corresponding author. email: up201402814@fe.up.pt †co-authors. tgalvao@fe.up.pt, thiago.sobral@fe.up.pt complex areas like bus networks in city centres. for instance, figure 1 depicts a spider map for the city of porto, portugal which depicts the surroundings of st. john’s hospital (hospital de são joão). spider maps allow one to answer questions like "from where i am, where can i go?", as they indicate the travel possibilities from a small geographical area. they are useful during the pre-planning state of a trip as it provides better geographical context by eliminating the visual clutter derived from other information available in the map that is not relevant to that area, in contrast to schematic maps. the central element of a spider map is the hub – a rectangular geographic map – that introduces the spatial context from which the schematic lines emerge. the automatic construction of spider maps is a complex problem, as it is subject to a number of design constraints that should be obeyed, e.g. line angles, location of lines emerging from the hub, spatial constraints due to real-world features like rivers, bridges, etc. although spider maps are effective for providing passengers with public transport information, some factors impact their widespread adoption in transport 1 eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 http://creativecommons.org/licenses/by/3.0/ mailto:<up201402814@fe.up.pt> mailto:<tgalvao@fe.up.pt> mailto:<thiago.sobral@fe.up.pt> s. santos, t. galvão, t. sobral figure 1. the spider map for the st. john’s hospital (hospital de são joão) transport hub in porto, portugal. the map’s centre contains a tile image that represents the location of several bus stops (the hub). several lines emerge from the tile’s streets. [2] networks. firstly, the generation of such maps is frequently manual, and depends on the expertise of designers. the related studies provide a number of methods and techniques to automate the generation of spider maps, but current solutions based on multicriteria optimisation algorithms are time-costly and require heavy computing power. secondly, as an implication, spider maps are created for a few major locations of a city only. we argue that such a limitation undermines the potential of spider maps, as they can be useful to passengers from any location of a transportation network served by various lines. this paper proposes an approach to generate feasible interactive spider maps within a small timeframe, based on an algorithm that modifies and adapts some of the state of the art techniques. the goal is to tackle the complexity of the problem and present viable solutions with short execution times and using less computational power. thus, it aims at simplifying the traditional spider map generation process and potentially make an impact on the use of spider maps. bringing interactive capabilities to spider maps allows citizens to actively explore their transport network and a have map that is tailored to the desired geographic area, whilst introducing new challenges for generation of such maps within an acceptable time frame, especially if they are available for interactive displays like smartphones and tablets, and kiosks placed in stations and streets. users can leverage the potential of the proposed approach to generate spider maps for virtually any city area, and become aware of not only the nearby stops, but how far can he go from that area by boarding one of the available services. this paper extends the work described in [3] with the following contributions: a more comprehensive description of the state of the art; each phase of the proposed algorithm is described in increased detail, as well as the user stories that guided the proposed approach, and other practical aspects of the implementation architecture. the prototype was validated with another set of geographical areas of the city of porto. the remaining of this paper is structured as follows: section 2 defines the fundamental concepts related to spider maps, and describes the state-of-the-art methods for their generation. section 3 details the proposed algorithm. section 4 describes the architecture of the prototype, which is evaluated and discussed in section 5. section 6 concludes this paper. 2. related work transport maps support complex public transport networks by providing essential information, e.g. routes, stops and points of interest [4]. an important process associated with these maps is schematisation, where certain aspects are emphasised and unimportant information is removed. there are several methods for guiding this process. for instance, line generalisation methods, such as 2 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 an approach for rapid generation of interactive spider maps for public transport networks simplification, remove some line points, keeping only those that ensure the overall line shape; exaggeration amplifies certain portions of objects; enhancement elevate the message and importance of certain features [1]. another technique adapts the initial map (where points correspond to geographical locations) to a grid [5]. in this technique, line points are moved to grid intersections, while ensuring certain constraints, such as orientation and distance between points. the result is a map with a simpler overall shape, where incremental optimisation processes can be applied to improve the result. nonetheless, adapting maps to a grid can lead to very saturated areas, for instance, representing complex centre areas that have lines ending on city outskirts. sarkar and brown [6] proposed a method denominated fish-eye that applies different scales throughout the map, thus enabling magnification of crowded areas [7]. this is a focus+context visualization technique that aids the schematization process, as it emphasises important information while keeping the global context [8]. spider maps are an effective means of providing information about public transport networks, although few studies addressed this type of maps, in particular how to automate their generation. the majority of the developments in this area relate to the work of joão mourinho [8] in the development of techniques to automate the generation of spider maps. spider maps are based on spider diagrams [9] and combine elements from both geographical and schematic maps. these maps are often used to represent complex public transport network, for instance, bus networks in a city centre, and provide passengers information in the pre-planning stage of trips, answering the question “from where i am, where can i go?” [10]. these maps are characterised by a central area, a hub which represents the geographical context [11]. the schematic lines that represent the network routes emerge from the hub. along with the map, a route finder table is also provided to indicate the direction and route that are associated to each stop within the hub. the hub is generally depicted by a rectangular shape and details a geographic map of the location, proving the spider map a better spatial context. around there are located the points that connect the route lines with the stop inside the hub. this corresponds to the points where lines emerge from, hence, their location in the frame should consider route orientation and the stop location within the hub. similar to schematic maps, the schematic lines in the spider map do not follow the geographic layout, since they are the result of several simplification and displacement operations [8]. moreover, spider maps adopt the concept of map point, which describes a relevant point in the map, for instance, stops along the line route, located at a certain canvas coordinates that do not relate to the real geographical location. spider maps’ schematic lines are defined by a set of segments and map points, some of them shared with different lines, and a start and ending map point. shared segments are drawn parallel and lines only follow 0, 45 or 90 degrees orientation angles. segment nodes relate to route stops, however, some stops may be grouped together if they are geographically closed. moreover, to increase spatial awareness, geographical accidents, such as rivers or seashore, can be added to the map [8]. spider maps have several other design constraints that should be considered in the generation process. for instance, lines have a certain colour, usually defined by the transport provider, and position of stops and line labels. similar to schematic maps, spider maps generation is mostly a manual process. however, several techniques for simplification and generalisation can be borrowed from the schematic process. hence, joão mourinho [8] depicts a set of eight guidelines that spider maps should follow: 1. simplification of lines: generalise the line as most as possible, while maintaining overall shape. 2. group map points: if several map points are very close together and have similar names, most likely they are related; hence they can be grouped together. this step must be taken carefully, as it can eliminate relevant map information. 3. zoom in crowded areas: emphasise crowded areas by zooming, which increases readability. 4. remove or simplify environment features: for instance simplify the shapes of geographical accidents. 5. group segments that have the same start and end nodes: draw lines parallel if the segments share the same start and end nodes. 6. simplicity over completeness: depict only the essential elements on the map 7. symbol shapes and colours: use different symbols to emphasise or deemphasise certain map characteristics. 8. emphasise important aspects: direct the user’s attention to the most important map aspects, for instance, emphasise the hub to enable a better spatial context to the users. 2.1. automatic generation of spider maps to the best of our knowledge, very few studies tackled the challenge of automating the generation of 3 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 s. santos, t. galvão, t. sobral figure 2. example of spider map model presented in [8] spider maps. joão mourinho [8] proposed a method to automatically generate a spider map for a hub location, given a transport network with the same characteristics described above. since the current general generation process relies mostly on the design expertise and evaluation, the goal is to automatically generate a spider map that preserves topology and ensures the aforementioned restrictions (e.g., line angles). an important solution this method provides is a complete model representation for the spider map. the spider map sm is defined as sm = (p, v, h, e, l, a, gr), where p is a set of map points, v the vertices, h the hub, e a set of direct edges, l a set of lines, a a set of angles and gr a set of geographical restrictions. figure 2 depicts a spider map represented by this model. the initial algorithm state is a geographical accurate map, i.e., map points correspond to the accurate (or similar) geographic location, then a multi-criteria algorithm is applied where the decision variables are the spatial coordinates of each vertex and point belonging to the spider map. the goal is to minimise the objective function while ensuring a set of constraints and design guidelines. furthermore, two types of constraints are defined: soft constraints mostly related to visual qualities and should be followed if possible, and hard constraints that ensure a feasible solution and should be enforced. the objective function translates how soft constraints are followed, i.e., if all soft constraints are completely respected, then the objective function is zero, which means the solution is “optimal”. the solution successfully attained the proposed goals. however, this is a complex multi-criteria optimisation problem with great computational effort. for instance, for the default parameters results were obtained in execution times around 5 seconds for simpler maps and 12 seconds for more complex solutions. however, when testing the adjustment of parameters to increase quality, such as the search radius for possible map point displacements, the execution times obtained increased significantly. the quality of the obtained results increased and execution times averaged 14731 seconds [8]. thus, for a dynamic mobile environment, which has less computational power and should produce results in a shorter time span, this solution needs some adaption, for instance, discarding some constraints. ribeiro et al. [12] also proposed a solution to automatically generate a schematic map. even though it does not fully integrate all the constraints needed for a considerable feasible spider map solution, it proposes a fast solution for the schematic portion of spider maps, which can be an interesting technique for dynamic mobile problems. the proposed approach is based on the application of force-direct algorithms. force-direct algorithms are a class of graph algorithms that aim at drawing graphs in an aesthetically pleasing way. also, this algorithm is computationally lightweight and relatively quick to implement, providing acceptable results, though not optimal. the algorithm’s goal is to position nodes so that all edges are approximately equal length, there are as few crossings as possible and objects are distributed uniformly. the method is divided in three steps: initial dataset manipulation, force-directed iterative loop and final adjustments. force-directed algorithms apply forces to move nodes to better positions. the algorithm ends when the forces have reached an equilibrium. this approach uses coulomb’s and hooke’s laws to represent, repulsion and attraction forces between nodes, respectively. additionally, the algorithm implements a set of assumptions and rules, such as two lines intersect if at least a pair of edges intersect, or the flow of execution is dependent on the parametrization. an important step in this approach is the parametrization, since it influences the quality of the final result. several parameters are defined, concerning a threshold distance in which nearby nodes are merged, definition of k value constant for hooke’s and coulomb’s law and design restrictions, such as pinning start nodes that can be altered to improve the result map. to test and evaluate the solution, a prototype and an evaluation function were created. several tests were done with different parameters and total number of nodes. in general, with an average of 15.08 seconds, 95 nodes, 5 lines and 129 edges. the evaluation function combines criteria, such as displacement from original position, line length variation and line crossing variation. this approach presents relatively fast results and is able to simplify lines, merge close points and present 4 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 an approach for rapid generation of interactive spider maps for public transport networks an aesthetic schematic representation, while preserving the map’s topology. however, this solution does not consider many constraints of those spider maps: lines only follow 0, 45 or 90 degree orientations, merge stations (nodes) typically have close names and share the same geographic space and routes that share the same segment are parallel. furthermore, there is no explanation on how the initial graph is obtained and hub integration is also not considered. finally, results are linked with parametrisations that are manually provided and change depending on the initial graph. finally, in [11] an interactive application was developed that enable the user to select the area of the hub and then the map was produced automatically. even tough the resultant map could not be designated as a strict spider map representation, it provides a starting point for adapting automatic generation of spider maps with interaction techniques. 2.2. summary transport maps provide passengers an easy way of understanding the underlying network and wayfinding in cities. spider maps are a type of transport map that combine elements from both geographic and schematics maps. they provide all the travel possibilities from an area (hub) and are typically used in busy city centres where the networks are usually denser. such maps are not widely used in comparison with other existing map types. this may be due to the fact that spider maps are mostly manually generated and still rely on the expertise of the designer and stakeholders. notwithstanding, there are several techniques applied to line generalisation in schematic maps that can be adjusted to assist the spider map generation process. moreover, there is not much literature focused on spider maps, and the majority of the efforts made for automating the spider map generation process were done by joão mourinho [8]. mourinho’s solution is able to successfully produce spider maps, however, the goals focus on the quality over performance, making this a complex solution with great computational effort. 3. automatic generation of spider maps 3.1. problem definition the spider map generation process is a complex problem, since these maps have several design constraints as depicted in section 2. additionally, the process is mostly done manually, relying on the expertise of the map maker. even though some current solutions can automatically generate spider maps, they are complex and time expensive for producing results. thus, we aim to develop an algorithm capable of producing a spider map by creating, adapting and modifying existing techniques. the solution must take as input the spider map hub area selected by the user and generate as result a viable spider map. a result is considered viable if it satisfies the design restrictions of spider maps aforementioned in section 2. the goal is to develop a prototype that integrates the developed algorithm capable of producing spider map results in short execution times, since it will affect the prototype usability. along with automating the spider map generation process, the prototype should also integrate interaction and visualisation techniques, taking advantage of the benefits of digital maps over the traditional form and thus potentially achieve better usability. such techniques can be integrated before generating the map, for instance, during the hub selection process, and when visualising the map result, e.g. different levels of zoom and clickable items for additional information. the developed prototype is focused on porto city and all the public transport data was provided by opt1. the user is presented a geographic map of porto for choosing the hub area that will be used as input for generating the spider map. section 3.2 describes the algorithm for generating a spider map solution. 3.2. map generation algorithm the algorithm comprises a sequence of steps that apply displacement operations, to ensure conformance to the spider map restrictions. the pseudo-code of the several steps can be found in appendix a. the major restrictions are octilinear angles and maintain the topological relations, hence the biggest challenge of the algorithm is to find a location for every map point that ensures octi-linearity, while maintaining the topological relations between points. beforehand, the algorithm needs as input the coordinates of the hub, defined by the top left and bottom right corners. these geographical coordinates, i.e., a set of latitude and longitude, will allow querying the server for all the data needed for the spider map generation process. thus, the server will provide all information related to stops inside the hub and the lines that will belong to the spider map. the lines are defined by a sequence of map points, already established by the database and these will be the points taken into consideration in the algorithm. the goal of the algorithm is to find a location for all map points so that lines follow the spider map design constraints. nonetheless, the map points returned from the server are defined by geographic coordinates of their accurate location. hence, map points need to be projected onto the map canvas, being defined by an x and y instead of 1http://www.opt.pt/ 5 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 s. santos, t. galvão, t. sobral figure 3. determination of where lines should emerge from the hub. after hub insertion, the map state is depicted as in the left. the hub on the right demonstrates the calculation of the emerging points and the elimination of segments inside the hub. latitude and longitude. the map canvas is defined as an svg using the d3.js tool and map points coordinates are projected using the mercator projection centred at the hub centre. the projection process uses the d3.js geo plugin that provides map projection features. at this stage, map points have a similar location to their geographic representation, so lines also follow an approximation to the real geographic form. the next step is to insert the hub, defined by the four corners coordinates that represent the boundary area. these coordinates have also been projected so they are defined by an x and y in the canvas. after the hub insertion, the following step is to determine where lines should emerge from the hub and eliminate line segments inside the hub. therefore, the emerging points, i.e., the points where lines emerge from the hub, will be determined by the intersection of the line segment with the hub. this intersection point represents an approximation of the orientation and path of the line, since the hub is a geographical representation of the area and map points are still located at their original positions, i.e., a close representation of the geographic location. additionally, all segments positioned inside the hub are eliminated. figure 3 illustrates this process: the left image exemplifies the map state after hub insertion and the right image demonstrates the calculation of the emerging points and elimination of segments inside the hub. map points can be shared by multiple lines and lines can even share segments, thus duplicated information may exist. hence, the spider map is modelled as a graph g(v,e), where v represents the vertexes, i.e. the map points, and e the edges, i.e. route segments that represent the connection between two map points. each vertex and edge may belong to one or multiple lines, thus avoiding having duplicated map points or segments. vertexes have x and y coordinates, a list of lines they belong to, a name representative of the stop or area and an attribute that records if the vertex is an emerging point. it is important to register which vertexes are hub emerging points, since they should not be moved during the algorithm process. on the other hand, edges have two vertexes associated and a list of lines. the order of the map points in the lines is also recorded as well as the colour that lines should be drawn. spider maps have associated distortion, since their points do not represent geographical locations, but the product of multiple operations. furthermore, dimensions are altered, i.e., the hub area is usually augmented and distances between map points are reduced, resulting on a compression effect centred on the hub. however, at this point in the algorithm process, the map dimensions still resemble the real dimensions: the hub is small, and lines are very spread out. hence, the next step is to resize the hub, increasing its dimensions and translating the lines accordingly. the result of this operation causes the distortion and compression effect aforementioned. the resized hub dimension was set to 300 by 300 hundred pixels, however, hub selection may not follow this aspect ratio. hence, the final size of the hub is recalculated so the original aspect ratio is preserved. for instance, if the original hub width is 200 pixels and the original height 100 pixels, the resized hub will have 600 pixels of width and 150 pixels of height. nevertheless, after resizing and translating operations, some of the lines may end up intersecting the hub. thus, map points inside the hub are identified and the maximum distance to the hub boundary is calculated. then a translation operation corresponding to this distance value is applied, pushing the line out of the hub. at this stage, the map is similar to the original, but with distortion and with lines closer to the hub boundaries. the hub is a portion of a geographic map that depicts the area associated with the spider map. to obtain the geographic map image here api2 was used, providing services that return a map image of the specified area. the image already has the correct size, i.e., same size as the hub, thus it is placed on the hub coordinates. figure 4 illustrates an example of a hub of casa da música surroundings. the markers represent the stops in that area. furthermore, before beginning the displacement operations to satisfy the spider map restrictions, a matrix containing the topological relations between points is built. it is important to build the matrix before the generation process starts, since at this stage all the points relate to each other close to their real geographical location. thus, for each map point is calculated the relation to every other map point. a map point can be north of (no) or south of (so) and east of 2https://developer.here.com/ 6 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 an approach for rapid generation of interactive spider maps for public transport networks figure 4. hub example of casa da música area table 1. example of topological relation matrix between points p1, p2 and p3 p1 p2 p3 p1 inline, wo no, wo p2 inline, eo no, inline p3 so, eo so, inline (eo) or west of (wo) another point. when two points have an equal coordinate (x or y), they are defined as in line of each other. table 1 depicts the topological matrix of points p1, p2 and p3 relations. after this step is completed, the displacement operations begin in order to find a location for every map point that satisfies spider maps restrictions. first, a grid adaptation operation is done with the intent of simplifying the overall shape of lines. next, all angles are ensured to be octilinear and then the spider map is displayed, following the draw rules. the next sections depict these algorithm steps, that will displace map points trying to generate a viable map solution. 1) grid adaptation. the first step of the algorithm is to adapt the current map to a predefined grid, by assigning a grid intersection point to every map point. this step simplifies the overall shape of lines, leading to a closer solution where spider map restrictions are followed. the first task is to build the grid over the map, thus the maximum and minimum x and y values of the map points are determined which represent the bounds of the map and, subsequently, the boundaries of the grid. then, the grid is built with an initial grid cell size of 20 pixels by 20 pixels. it is important to note that the cell size will affect the complexity of the algorithm, since grid cells with smaller cell size lead to finer grid granularity, which increases the search for possible displacements. on the other hand, it may not be possible to adapt a map to a grid if cells have a large size, given that possible displacements will be scarce. after several tests with different sizes, this initial cell size was chosen since results showed that most maps could successfully adapt to a grid with this cell size, without the need of repeating the process by adapting the cell size. the final step in building the grid is to determine the grid intersection points. these points represent all the possible displacement for map points during the grid adaptation process and the subsequent algorithm steps. therefore, for every map point the nearest grid intersection points are calculated, i.e., the 16 surrounding and closest grid intersection points are determine. however, not every nearest grid intersection point is a valid displacement. a grid intersection point is considered for a valid displacement if it causes no hub occlusions, i.e., does not cause any segments to intersect with the hub; does not lead to any segment overlapping, i.e., segments do not pass through map points that do not belong to that segment; and the grid intersection point is free, i.e., it does not have a map point assigned. the grid intersection point selected for the displacement is the one with the smallest score, which represents the attribution of less penalties. the score combines the distance from the map point to the grid intersection point being evaluated (points with greater distance will be more penalised) and a score that translates how well topology relations are maintained, by giving a penalty to every topological violation. a displacement causes a topological violation if it changes the relation between two points. for instance, having p1 south of and east of p2, a displacement that leads to p1 being north of or west of p2 is considered to cause a topological violation. smaller penalties are given to displacements that cause relations to change to in line. this trade off by loosening the topological constraints leads to simpler line shapes, where lines become straighter which causes less non-octilinear angles. if no topological violation occurs, then the topological score given is zero. however, in some cases it may not be possible to adapt the map to the grid with the current grid cell size. this means that some map points may not have any possible valid displacements. hence, the grid cell size is decreased, the map points coordinates are restored to their original locations and the grid adaptation process is restarted. decreasing the cell size leads to a finer grid granularity, which in turn leads to more possible displacements. this processed is repeated until the grid adaptation is successfully completed or the grid cell size reached a defined minimum. in this last case, the grid adaptation process may not be possible, thus a map solution will not be produced. figure 5 depicts the grid adaptation process, illustrating initial locations in the top image and the displacement result in the bottom image. in the figure 7 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 s. santos, t. galvão, t. sobral (a) initial point locations (b) displaced point locations figure 5. grid adaptation process. the initial locations in (a) are displaced to new locations on the grid as in (b), yielding simpler shapes. some of the angles become octilinear as a result of this process. is possible to note that lines have a simpler shape and some of the angles already comply with the octilinear angle restriction. however, not all the nearest grid intersections are valid displacements. grid intersection points that will cause hub occlusion, i.e., will intersect the hub, and that will cause line segments to overlap or pass through map points that do not belong to that segment are removed as possible displacement locations. the addition of this restriction will lead to, in some cases, map points that will not have any possible displacements. when this happens, the graph is returned to the original state, the grid cell size is decrease and the grid adaptation process is restarted. by decreasing the grid cell, the granularity is increased which leads to more displacement options. this process is repeated until all points are displaced to a grid intersection or the grid cell size reaches a defined minimum. in this last case, the grid adaptation process may not be possible, thus a map solution will not be produced. 2) correcting non-octilinear angles. after the grid adaptation process is finished, the result is a map with simpler line shapes and where map points respect the topology relations. however, some of the lines may still not follow octilinear angles. just as mentioned in section 2, one of the spider maps restrictions is that angles should only be of 0, 45 or 90 degrees, i.e., only octilinear angles. hence, the next algorithm step is to identify and correct non-octilinear angles. the first step is to identify all the map points where two segments form a non-octilinear angle. map points corresponding to hub emerging points are not taken into consideration, since they will be approached using a different method to ensure the lines also form octilinear angles when intersecting the hub boundaries. afterwards, for each map point identified with an incorrect angle, the algorithm will try to identify a grid intersection point which displacement will correct the angle. the process is similar to the nearest grid intersection points search in grid adaptation, where the closest grid points are identified and invalid displacements are removed from possible options. a grid intersection is considered not valid for nonoctilinear angle correction if: 1. the displacement will cause octilinear angle to become non-octilinear; 2. the displacement will disturb topological relations between points (changes to in line are not considered as disturbance); 3. the displacement will cause occlusions with the hub, line overlapping or lead to segments passing through map points that do not belong to that segments; 4. that grid point already was a map point associated; 5. the displacement will cause the angle to remain non-octilinear. just as in grid adaptation, scores are calculated for every valid option and the map point is displaced to the best scored grid intersection point, i.e., the grid intersection point with the smallest score. figure 6 exemplifies the correction of a non octilinear angle by displacing a map point to another grid intersection point. nonetheless, some map points will not have any possible valid displacements that will correct the nonoctilinear angles, thus making them candidates for a break point introduction. a break point is a map point introduced in one of the segments of the incorrect angle to correct the non-octilinear angle without displacing any map point. this new map point is added to the graph representation and marked as being a break point. break points are introduced to correct angles and have no other meaning to the spider map, so they need to be represented differently. to introduce a break point, grid intersections surrounding the identified segments are searched and checked if the displacement will correct the angle. similar to the previous operations, a displacement is valid if causes no occlusions, and no segments overlap. a break point introduction will transform one segment 8 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 an approach for rapid generation of interactive spider maps for public transport networks (a) line shape with a non octilinear angle (b) line shape after point displacement figure 6. line shape before (a) and after (b) the correction of a non-octilinear angle by map point displacement in two new ones, allowing angles to be corrected. figure 7 illustrates a result of a break point introduction. figure 7. non-octilinear angle correction with segment break point although introducing a break point will correct most of the remaining non-octilinear angles, in some cases, mostly in very dense areas, it is not possible to find a valid location to introduce the break point. hence, two break points are introduced to correct these last cases. the introduction of two break points is very similar to inserting a single one. however, the goal is to find the best combination of two valid grid points that can correct the angle. the complexity of this problem is restrained by limiting the grid points search to the nearest grid points and by eliminating all the invalid grid locations. figure 8 depicts non-octilinear angle correction by inserting two break points. moreover, lines emerging from the hub should also make an octilinear angle with the hub boundaries and, just as aforementioned, the correction of these angles figure 8. non-octilinear angle correction with two break points is treated separately from the remaining map points. to correct the angles from hub emerging segments is established that those segments should make a 90º angle with the hub boundary. then, a break point is introduced in that segment, so the corresponding angle is 90º or, if not possible, 45º degrees. figure 9 depicts the correction of angles from hub emerging segments. figure 9. correction of non-octilinear angles of hub emerging segments 3) draw the spider map. after correcting the angles, the final map point locations are determined, and the drawing process can begin. the first is to obtain and place the hub image, that is a geographical representation of the area. the image is obtained using the api here3 that returns an image of the geographical map giving a boundary box. moreover, the stops are identified with markers. map points are drawn in the associated locations and do not need further processing. however, segments are shared between lines and need to be drawn parallel, thus making it necessary introducing an offset between shared segments. in order to introduce an offset that will lead to parallel segments, it is necessary to calculate the slope of the line. thus, identifying the correct orientation (vertical, horizontal or diagonal), is possible to introduce a correct offset to the x and y coordinates, just as illustrated in figure 10. the final step is to draw the labels that identify the map points. not all map points need to be labelled, only the last and the most important of 3https://developer.here.com/ 9 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 s. santos, t. galvão, t. sobral figure 10. shared line segments each line. nonetheless, the label’s position needs to be determined. thus, a score is calculated that translates how many occlusions will the label cause. for that, a bounding box of the label is placed at top, bottom, left and right of the corresponding map point and a penalty score is given for each line intersection. the chosen place will be the one with the smaller score. after this step, the generation process is finished and a valid spider map solution is presented to the user. figure 11 depicts the algorithm generation process in a flowchart. hence, a valid spider map solution is generated if all the aforementioned algorithm steps are successfully completed. in some cases the algorithm is not capable of producing a valid solution, for instance, if grid adaptation fails, no solution will be presented, or if not every non-octilinear angle is corrected, the spider maps will have errors. the developed algorithm is integrated in the developed prototype depicted in section 4 and results will be illustrated and evaluated in section 5. 4. prototype development for the purpose of testing how the developed algorithm performs in real situations, a prototype was created integrating the algorithm depicted in section 3.2 and taking advantage of digital map characteristics by combining visualisation and interaction techniques. 4.1. use cases and stories the main use cases consist of selecting the desired hub area, and generating the respective spider map. a set of user stories was defined (see table 2); they cover the main functionalities that such a prototype should implement. moreover, there is the ambition to integrate interaction and visualisation techniques to enhance the user experience. in the first screen, a map of porto city with interaction capabilities is presented to the user, i.e., the user can figure 11. algorithm workflow for the generation of a spider map. the corresponding pseudo-code can be found in appendix a. table 2. user stories defined for the functional prototype user story description (as a user, i would like to...) us01 see and navigate a map of porto city area us02 see a pre-defined grid that marks possible hub placements us03 choose one or multiple grid cells that define the hub area us04 clear current grid selections us05 check the stops inside the hub selection us06 check additional information about stops us07 generate a spider map given the hub selected in the grid us08 visualise the spider map resulted from my hub selection us09 check information about the hub stops and lines that belong to the spider map us10 interact with the spider map by zooming, moving and clicking on elements for additional information zoom and navigate through the map. furthermore, in the top right corner, the user can access control buttons illustrated in figure 12 left. in this controls users can 10 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 an approach for rapid generation of interactive spider maps for public transport networks figure 12. example of grid selection (left) and control buttons (right) show/hide the pre-defined grid, check stops inside the grid selection and finally generate the spider map. the pre-defined grid lays over the porto city corresponding to the boundaries of the available data. then, the user can select one or combine several grid cells to create a personalised hub area. as the grid has an arbitrary size, it could have been possible to previously generate a spider map for each grid cell in advance, to reduce the user’s waiting time for navigating a map. however, such assumption would imply that the user could not select more than one grid cell, thus limiting the user’s capability of defining a region of interest that may span a number of adjacent grid cells. figure 12 right shows an example of grid selection, where selected cells are shown in orange and markers depict stops inside the hub selection. after the user chooses the desired hub and selects “generate spider map”, the algorithm takes the hub coordinates as input and generates a spider map result. in the next screen the user can visualise and interact with the map result. the user can navigate, zoom and click on map points to check additional information. all these interaction features were developed using d3.js behaviour plugin that allow to catch and handle interaction events. figure 13 depicts an example of a portion of a spider map result where it is possible to check the additional information box when a map point is hover or clicked on. 4.2. architecture the developed solution follows a simple two-tier architecture or client-server, illustrated in figure 14. this architecture style is commonly used in distributed systems to separate operations into the client and server, where the server provides services to the client [13]. thus, the server is responsible for dealing with all the necessary data operations, while the client is responsible for the spider map generation and rendering operations. figure 13. interaction mechanism within the spider map: clicking on map points reveal additional information figure 14. solution architecture for the prototype the server was implemented using node.js4 and express.js5 for the rest api. moreover, the server establishes a connection with a mysql6 database that stores all the public transport data, that will be depicted in detail in the next section. hence, the server is responsible for gathering and processing all the data needed for the spider map generation. the architecture was built and tested on a mid-range 2019 laptop. the implemented api has two main models – routes and stops – with several endpoints for handling and retrieving information associated with each one of the models, as described in table 3. on the other hand, the client consists of a web application based on the two major use cases described in section 4.1. for the geographic maps and hub selection leaftlet7 and openstreetmap8 were used, while the spider map drawing and generation was developed using d3.js9 and javascript technologies. 4https://nodejs.org 5https://expressjs.com/ 6https://www.mysql.com/ 7https://leafletjs.com/ 8https://www.openstreetmap.org/ 9https://d3js.org/ 11 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 s. santos, t. galvão, t. sobral table 3. api endpoints for retrieving input data for the generation of a spider map endpoints parameters description /stops get all stops /stops/hub toplong; toplat; bottomlong; bottomlat get stops within a rectangular hub defined by two pairs of geographical coordinates /stop stopid get stop by id /stop/lines stopid get routes of all of the lines that go through a stop /line/stop stopid get all lines that serve a stop /line lineid get line by id /line/code code get line by code /line/route lineid get line route by line id figure 15. data model for the structural elements of a spider map 4.3. data model the data related to public transport network of porto was provided by opt and stored in a mysql database following the model depicted in figure 15. lines are characterised by a code, name and a line colour. stops are defined by a code, name and geographic coordinates (latitude and longitude). lines consist of several stops; each stop may belong to zero or more lines. nonetheless, routes are defined by the table "path" that define the sequence of stops identified by the attribute "order". the data provided already defines map points that may represent groups of stops. henceforward, when a stop is associated with a map point, it should be replaced when forming the path of a line. furthermore, stops and map points have associated geographical coordinates (latitude and longitude), which will represent the initial position of the points. moreover, lines and stops also have other attributes associated, such as names and line colours. 5. evaluation and validation current solutions are complex and take very long to produce spider map results. hence, the ambition is to tackle the complexity of the generation process of spider maps and develop a solution capable of automatically generate spider maps in real-time. thereby, the two variables taken into consideration during the evaluation and validation are if the map is correctly generated, i.e., the spider map follows the establish design rules, and the execution time needed to produce the result. a result is considered valid if it complies with the spider map restrictions aforementioned in section 2. 5.1. tests and results performed tests aim at testing if the solution is capable of generated valid spider maps at real-time using the prototype develop to select the input hub area and generate and evaluate map results. several tests were performed by choosing different hub areas as input and evaluating the results. even though tests were only performed for porto’s bus network, the number of possible hub inputs is extensive. hence, the tests focused on testing areas where the network is denser, i.e., areas served by many public transports’ lines like city centres. in porto, some of the busiest areas are aliados,casa da música, hospital são joão, castelo do queijo. tests demonstrated that the developed algorithm produces feasible spider map results for the city of porto. figures 16 depicts the initial map state for castelo do queijo, a coastal area, and figure 17 depicts the corresponding spider map. figure 18 also depicts a spider map result for aliados, a busy centre area in porto. the complexity of the generation process and, subsequently, the spider map is directly related to the number of map points, i.e., the complexity increases as the number of map points also increases, since more displacement operations and angle corrections will be needed to generate a valid map. hence, to control the continuous increase in complexity, a limit to the number of lines in the spider map was set, as well as a limitation on the hub size. this prevents the user to select large areas for the algorithm, preventing the exponential increase in complexity. there is not much literature in automating the generation process of spider maps, and most of the efforts made in this area were through mourinho’s [8] work. however, in his work the goal was to find the optimal spider map solution, hence the quality was valued over fast results. thus, the solution required great computational effort and long execution times. for instance, in tests accessing the quality versus the number of algorithm iterations, the average execution times were of 2797 seconds. 12 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 an approach for rapid generation of interactive spider maps for public transport networks figure 16. initial map state for castelo do queijo hub area figure 17. spider map result for castelo do queijo hub area even though is not possible to establish a direct comparison with the tests performed by mourinho, it is possible to conclude that the developed solution was able to produce results faster. the developed solution produced spider maps under 500 milliseconds for complex centre areas. table 4 depicts tests results for 13 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 s. santos, t. galvão, t. sobral figure 18. spider map result for aliados hub area valid solutions, describing the number of map points, the numbers of different lines of the map, hub area and the execution time (et) in milliseconds. in addition, table 5 depicts the success of test results, identifying how frequently a valid solution was obtained, the number of times where a solution was not possible and the number of incorrect solutions (i.e., spider map results that contain some non-octilinear angles). it can be concluded that the developed algorithm successfully produces results, i.e., the solution generates valid spider map results in real time, taking significantly less time compared to state-of-the-art solutions. thus, this work successfully tackles the complexity of the spider map generation process and contributes to the identified gap of current work. 5.2. limitations and future work the quality of the result depends on how and if all the stages of the algorithm are successful. in the grid adaptation stage, the algorithm will adapt the cell size until the initial map is successfully adjusted to the grid; however, in some cases, grid adaption may not be possible. in dense areas, a vast number of map points compete for a grid allocation. thus, even by increasing the grid granularity, it may not be possible to assign a grid point to every map point. moreover, since the subsequent algorithm steps depend on the success of grid adaptation, a solution may not be found. nevertheless, the introduction of a constraint to the table 4. tests results for generated spider maps no. map points no. lines hub area et (ms) 153 6 castelo do queijo 844.29 153 6 castelo do queijo 710 32 1 av. boavista 122.21 153 6 casa da música 419.23 144 1 casa da música 298.64 10 1 aliados 35.04 108 4 aliados 387.71 130 4 trindade 664.88 52 2 boavista 215.83 88 2 hosp. são joão 272.87 106 4 hosp. são joão 432.53 102 4 av. boavista 5445 32 1 av. boavista 102.67 105 4 praça da república 482.9 105 4 aliados 496.27 27 1 bolhão 95.45 39 1 campo lindo 177.45 66 3 marquês 244.62 177 6 marquês 599.46 37 6 passeio alegre 105.96 51 6 foz do douro 159.23 33 6 ramalde 102.33 79 6 parque real 194.93 14 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 an approach for rapid generation of interactive spider maps for public transport networks table 5. outcome of performed tests solution no. of results valid solution found 22 no solution found 3 solution with errors 5 maximum number of lines overcame this problem, and tests showed that the grid adaptation process is successfully completed even in complex areas, and with just one or two iterations. therefore, reducing the cell size in each iteration to increase the grid granularity was proven adequate. hence, it is likely that users may need to select one or more grid cells in order to define the desired geographic area. the next algorithm step that will influence the quality of the solution is the correction of non-octilinear angles. in the developed solution, the algorithm has several iterations that aim correcting the non-octilinear angles through several approaches. the first approach is identifying a valid grid allocation to displace the identified map points and correct the angle. nevertheless, in some cases is not possible to find a valid displacement that corrects the angle, thus the next iterations try to correct the remaining non-octilinear angles by inserting one or two break points. the integration of different approaches to correct identified non-octilinear angles was effective in producing valid spider map results. notwithstanding, in some cases the algorithm may not produce a valid spider map (i.e., some angles may not be corrected) or, in the worst-case scenario, not produce a solution. most invalid algorithm results derive from the non-octilinear angle correction, not the grid adaption as depicted in table 5. thus, even for invalid results, the algorithm can present a solution that may not be completely correct (some angles may not be octilinear). some errors are the result of incorrect map point coordinates, that lead to incorrect projections, which subsequently cause the failure of grid adaptation or angle correction. on the other hand, circular lines are viewed as a special case, since they sometimes lead to particular results. for instance, results with circular lines often cross themselves, which may be valid according to spider map restrictions, but is not aesthetically pleasing. also, scaling the hub may lead to undesired distortion, that in some cases may preclude the success of the non-octilinear angle correction. even though some limitations were identified and the algorithm may be improved so it becomes more robust to certain cases, results have proven that the developed solution was successful and provides enhancements in the current state-of-the-art solution. the solution is able to produce viable spider map solutions at real-time and taking in consideration the hub area as user input, whilst maintaining a feasible quality that allows users to explore the transportation network. furthermore, the prototype demonstrated the successful integration of the algorithm with the advantages of digital maps by incorporating visualisation and interaction techniques. finally, the spider map solutions can be aesthetically improved in a post-processing stage, with more line simplifications. nonetheless, the developed solution provides advances in the simplification of the generation process of spider maps, thus potentially making an impact on the use of spider maps in providing public transports information. through the developed prototype, the user is able to choose a desire hub area and visualise all the travel possibilities by the generated spider map. 6. conclusions spider maps are a type of transportation map that presents all the public transport possibilities available within a geographic area. these maps allow one to identify how far they can go by using the available transport network service within that area. however, their production is still mostly manual, and tailored to a restricted set of locations. some efforts have been made to automate the generation of these maps, but state-of-the-art solutions require great computational effort and long execution times to produce results. hence, the proposed approach aimed at developing a solution capable of automatically generating spider maps, tackling the complexity gap of current solutions. this work focused on two goals: developing an algorithm that automatically generates spider maps results in real-time and considering a hub that can be defined by the user according to the desired area, regardless of a cell grid size defined by the system’s implementation; developing a prototype that integrates the map generation algorithm, adding interactive capabilities to map results. the algorithm adapted techniques used in schematic maps generation, such as adapting a map to a pre-defined grid, and developed new processes that apply several operations to produce a spider map compliant to all the design restrictions. throughout the validation and evaluation process, the objective was to test if the solution could produce feasible spider map solutions at real-time, reducing the execution time needed to produce map results whilst correctly depicting the information about the bus network. the prototype and tests focused on the bus network of porto. performed tests showed that the solution is successful and can produce map results in shorter execution times than state-of-the art solutions. furthermore, the prototype developed validated that the algorithm can 15 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 s. santos, t. galvão, t. sobral be incorporated into a web or mobile application that provides an interface for passengers to interact and customise the map generation. future work may improve the map aesthetics in a post-processing phase by applying more simplification to the spider map schematic lines, which will increase the quality of the solution, and other algorithm improvements so it becomes more robust to complex network data. notwithstanding, the developed solution contributed to the identified gap in state-of-the-art solution, producing spider map solutions at real-time and considering user input. acknowledgements. this work is financed by the erdf european regional development fund through the operational programme for competitiveness and internationalisation compete 2020 programme and by national funds through the portuguese funding agency, fct-fundação para a ciência e a tecnologia within project ptdc/ecitra/32053/2017 and poci-01-0145-feder-032053. we also acknowledge opt10 for providing the data related to porto’s bus network. references [1] klippel, a., richter, k.f., barkowsky, t. and freksa, c. (2005) the cognitive reality of schematic maps. mapbased mobile services: theories, methods and implementations : 55–71doi:10.1007/3-540-26982-7_5. [2] sociedade de transportes colectivos do porto (2019), são joão hospital spider map, https://www.stcp.pt/fotos/spider_map. [3] santos, s., dias, t.g. and sobral, t. (2020) automatic generation of spider maps for providing public transports information. in martins, a.l., ferreira, j.c. and kocian, a. [eds.] intelligent transport systems. from research and development to the market uptake (cham: springer international publishing): 131–149. [4] international cartographic association (2019), history of ica, https://icaci.org/research-agenda/history/. 10http://www.opt.pt/ [5] klippel, a. and kulik, l. (2000) using grids in maps. theory and application of diagrams. first international conference, diagram 2000, edinburgh, scotland, uk, september 1-3, 2000 proceedings : 486–489. [6] sarkar, m. and brown, m.h. (1992) graphical fisheye views of graphs. proceedings of the sigchi conference on human factors in computing systems : 83– 91doi:10.1145/142750.142763. [7] baudisch, p., good, n. and stewart, p. (2001) focus plus context screens combining display technology with visualization techniques. proceedings of the international symposium on user interface software and technology (uist’01) : 31–40doi:10.1145/502348.502354, url http://doi.acm.org/10.1145/502348.502354. [8] mourinho, j. (2015) automated generation of contextaware schematic maps: design, modeling and interaction. ph.d. thesis, faculty of engineering of university of porto. url https://hdl.handle.net/10216/79324. [9] avelar, s. and hurni, l. (2006) on the design of schematic transport maps. the international journal for geographic information and geovisualization 41(3): 217– 228. doi:10.3138/a477-3202-7876-n514. [10] maciel, f. and dias, t.g. (2016) challenging user interaction in public transportation spider maps: a cobweb solution for the city of porto. ieee conference on intelligent transportation systems, proceedings, itsc : 181–188doi:10.1109/itsc.2016.7795551. [11] maciel, f.m.a. (2012) interactive spider maps for public transportation. ph.d. thesis, faculty of engineering of university of porto. [12] ribeiro, j.t., rijo, r. and leal, a. (2012) fast automatic schematics for public transport spider maps. procedia technology 5: 659–669. doi:10.1016/j.protcy.2012.09.073, url http: //linkinghub.elsevier.com/retrieve/pii/ s221201731200504x. [13] ibm (2019), the client/server model. appendix a. pseudo-code for the spider map generation algorithm 16 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 https://doi.org/10.1007/3-540-26982-7{_}5 https://doi.org/10.1145/142750.142763 https://doi.org/10.1145/502348.502354 http://doi.acm.org/10.1145/502348.502354 https://hdl.handle.net/10216/79324 https://doi.org/10.3138/a477-3202-7876-n514 https://doi.org/10.1109/itsc.2016.7795551 https://doi.org/10.1016/j.protcy.2012.09.073 http://linkinghub.elsevier.com/retrieve/pii/s221201731200504x http://linkinghub.elsevier.com/retrieve/pii/s221201731200504x http://linkinghub.elsevier.com/retrieve/pii/s221201731200504x an approach for rapid generation of interactive spider maps for public transport networks algorithm 1: resize initial map input : hub corners coordinates; map graph g(v,e) output: resized hub coordinates and graph g(v,e) calculate hub width, height and centre from coordinates; newwidth← 300 * width / height; newheight← 300 * height / width; scalingfactorx← newwidth / width; scalingfactory← newheight / height; for each v ∈ g(v,e) do if v is hub emerging point then calculate vector from hub centre to v; calculate new v coordinates applying a translation of the obtained vector with the scaling factor; else identify the corresponding line hub emerging point; apply same translation of the identify hub emerging point; end end lines← getlines(e); for each line ∈ lines do if line is inside then calculate maximum distance to hub boundaries; apply translation to every line map point; end end algorithm 2: adapt map to grid input : map graph g(v,e) output: map graph g(v,e) adapted to grid for each v ∈ g(v,e) do if v not hub emerging point then calculate nearest grid intersection points; for each nearest grid point do if grid point is valid then calculate grid point score; end end if valid displacements found then update v coordinates to grid point with best score; else if cellsize < min then solution not found; else decrease cell size; reset graph to original locations; restart gridadaptation; end end end end algorithm 3: correct non-octilinear angles with displacement input : map graph g(v,e) output: break point candidates incorrectvertexes← findnonoctilinearangles(v); for each v ∈ incorrectvertexes do if v not hub emerging point then calculate nearest grid intersection points; for each nearest grid point do if grid point is valid then calculate grid point score; end end if valid displacements found then update v coordinates to grid point with best score; else add v to break point candidates breakpointcandidates; end end end 17 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 s. santos, t. galvão, t. sobral algorithm 4: correct non-octilinear angles with break point insertion input : map graph g(v,e), break point candidates breakpointcandidates output: two break point candidates for each v ∈ breakpointcandidates do if v not hub emerging point then calculate nearest grid intersection points; for each nearest grid point do if grid point is valid then calculate grid point score; end end if valid grid intersection gridpt found then add break point gridpt to v; transform edge e(pt1,pt2) into e1(pt1,gridpt) and e2(gridpt,pt2); else add v to two break point candidates twobreakpointscandidates; end end end algorithm 5: correct non-octilinear angles with two break points insertion input : map graph g(v,e) output: map graph g(v,e) for each v ∈ twobreakpointscandidates do if v not hub emerging point then calculate valid nearest grid intersection points; for each nearest grid point do calculate two grid point combination; calculate score; end if valid two points grid intersection combination gridpt found then add break points gridpt1 gridpt2 to v; transform edge e(pt1,pt2) into e1(pt1,gridpt1), e2(gridpt1,gridpt2) and e3(gridpt2,pt2); else g(v,e) with non-octilinear angles; end end end algorithm 6: correct non-octilinear angles of hub emerging segments input : map graph g(v,e) output: map graph g(v,e) with correct hub emerging segments for each v ∈ g(v,e) do if v is hub emerging point then find grid intersection for 90º angle; if grid intersection not found then find grid intersection for 45º angle; end insert break point at grid intersection found; end end algorithm 7: generate spider map input : hub coordinates output: svg of spider map retrieve route information from database; build map graph g(v,e); adapttogrid(); if grid adaptation successful then correct non-octilinear angles; else reset graph g(v,e) to original coordinates; end drawspidermap(); 18 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e2 1 introduction 2 related work 2.1 automatic generation of spider maps 2.2 summary 3 automatic generation of spider maps 3.1 problem definition 3.2 map generation algorithm 1) grid adaptation 2) correcting non-octilinear angles 3) draw the spider map 4 prototype development 4.1 use cases and stories 4.2 architecture 4.3 data model 5 evaluation and validation 5.1 tests and results 5.2 limitations and future work 6 conclusions a pseudo-code for the spider map generation algorithm bike-sharing mobility patterns: a data-driven analysis for the city of lisbon eai endorsed transactions on smart cities research article 1 bike-sharing mobility patterns: a data-driven analysis for the city of lisbon vitória albuquerque1, francisco andrade2, joão carlos ferreira2,3,*, miguel sales dias1,2 and fernando bacao1 1nova information management school (nova ims), universidade nova de lisboa, campus de campolide, 1070-312 lisboa, portugal 2instituto universitário de lisboa (iscte-iul), istar, 1649-026 lisboa, portugal 3inov inesc inovação—instituto de novas tecnologias, 1000-029 lisbon, portugal abstract new technologies applied to transportation services in the city, enable the shift to sustainable transportation modes making bike-sharing systems (bss) more popular in the urban mobility scenario. this study focuses on understanding the spatiotemporal station and trip activity patterns in the lisbon bss, based in 2018 data taken as the baseline, and understand trip rate changes in such system, that happened in the following years of 2019 and 2020. furthermore, our paper aims to understand the covid-19 pandemic impact in bss mobility patterns. in this paper, we analyzed large datasets adopting a crisp-dm data mining method. by studying and identifying spatiotemporal distribution of trips through stations, combined with weather factors, we looked at bss improvements more suitable to accommodate users’ demand. our major contribution was a new insight on how people move in the city using bikes, via a data science approach using bss network usage data. major findings show that most bike trips occur on weekdays, with no precipitation, and we observed a substantial growth of trip count, during the observed time frame, although cut short by the pandemic. we believe that our approach can be applied to any city with available urban mobility data. keywords: bike-sharing system, urban mobility patterns, statistical analysis, cluster analysis received on 22 april 2021, accepted on 03 may 2021, published on 04 may 2021 copyright © 2021 vitória albuquerque et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.4-5-2021.169580 *corresponding author. email: joao.carlos.ferreira@iscte-iul.pt 1. introduction cities are becoming more predominant in modern societies, and citizens mobility is a raising problem concerning pollution and traffic. to overcome such challenges, shared mobility approaches have been developed. in this domain, bike-sharing is a rising active mobility modality, showing large growth rates worldwide. such demand, increased the number of bike-sharing companies operating in the world, becoming more effective and available in most developed cities. moreover, citizens are shifting towards more sustainable urban transports, such as bike-sharing, increasingly adopted and becoming more popular. hence, understanding how and when people use bike-sharing systems and their mobility patterns over time is thus mandatory towards improving the system’s efficiency. aligned with oecd sustainable development goal [1], [2] (sgd) 11 sustainable cities and communities, portugal national [3], regional [4] and lisbon [5] strategies for mobility, aim to integrate bike-sharing systems in the long-term public transport plans and daily commute. in 2017, lisbon implemented a fourth-generation bikesharing system (bss), which is currently expanding, under currently enforced development plans by the city hall. taking lisbon as a use case and our preliminary study [6], eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 mailto:https://creativecommons.org/licenses/by/4.0/ vitória albuquerque et al. 2 we have adopted a data mining approach to understand station and trip patterns in its gira bss and understand this service from a perspective of evolution throughout the years. to this aim, we have analyzed gira bss data and environmental data to derive the spatiotemporal distribution of travel distances, speed and durations and their relationship with environmental conditions, such as weather. moreover, we analyzed the evolution of the gira bss usage rate from 2018 to 2020 and the impact of covid 19 pandemic. 1.1 historical background in 2017 lisbon implemented its first bike-sharing system, gira. over a year, it expanded, and in 2018 there were already 81 bike stations across the city. there are future to expand lisbon bss, with more stations and bikes, since bike-sharing is an important strategy in the context of urban mobility policies approved by the city hall to achieve intelligent and sustainable urban mobility in lisbon. the deployed system includes a data collection feature that monitors spatiotemporal users’ behavior and trip patterns. by analyzing such collected data, we can learn about urban mobility, specifically on real-world bike-sharing system usage behaviors. additionally, monitoring and analyzing user behavior changes provides a broader lisbon public transportation network scenario, giving new opportunities and patterns for prediction and usability improvement. 1.2. our research approach in this study, we aim to collect spatiotemporal bike trip data, with trip id, origin and destination stations, trajectory, and time to identify spatial and temporal patterns. hence, to correlate bike mobility patterns with weather data and external events, such as covid 19 pandemic that affected urban mobility in 2020. our approach addresses the following research questions: rq1: what are the spatiotemporal station and trip activity patterns in lisbon bss in 2018? this question statement leads to the following subquestions: • what are the average figures for monthly and daily lisbon bss use? • what is the bike trip relation to weather conditions, specifically, to precipitation and temperature? • how can we group the lisbon bss origin and destination stations? • how can we group lisbon bss into clusters across the city? rq2: have lisbon bss trip patterns changed in 2019 and 2020 from 2018, given the covid 19 pandemics? this leads to the following sub-question: • how has covid 19 pandemic affected lisbon bss? three levels of analysis were performed to address these research questions: the first, bike trip and station usage in 2018, looking at historical data of bike trips (approximately 700,000 records), and portuguese institute of sea and weather – instituto português do mar e atmosfera (ipma) data with focus on finding usage patterns, towards service optimization. the second level regards 2019 and 2020 bike trips, monthly and weekday usage, in comparison with 2018 to investigate bike trip usage patterns over the three years. the third one regards the analysis of bike trip counts collected from 2019 to 2020 by a sensor in avenida duque de ávila. this paper is structured as follows: section 2 presents our state of the art survey. section 3 introduces our data mining methodology, which adopted cross-industry standard process for data mining (crisp-dm). in section 4, results, data understanding, data pre-processing and modeling are explained and presented with analysis and visualizations. in section 5, discussion, we discuss our results with a comparative analysis and identify research gaps and limitations. finally, in section 6, we raise some conclusions and draw lines for further research. 2. state of the art of bike-sharing systems the community agrees that bss improves urban accessibility and sustainability, and thus more cities in the world are implementing bss to tackle urban mobility issues and pollution problems. since 2016, over 1000 bss were implemented in 60 countries [7]. from bss third-generation smart card technology [8] was used, producing station-based and trip-level data and facilitating studies that enable the adoption of these systems in urban transportation networks [9]. evolving fourthgeneration bss, provided additional key data on users’ behavior and trip patterns. monitoring makes possible the identification of system performance and data analysis provides insights into users’ behavior [10], enabling to balance bike demand and improve bike network resilience and response. the latest bike-sharing systems technology [11] uses two configurations: a fixed number of bike stations to hire and return bikes, and a free placement scheme. bike stations can be monitored in real-time on online maps. application programming interfaces (api), accessing the network usage data, is supplied by operators and specified by external software developers. in europe, such access is governed by the gdpr – general data protection regulation [12], enforced since 2018, including provisions for personal data privacy and protection, including data anonymization. this scheme produces usage datasets, of critical importance in transportation research [11]. o’brien [11] first analyzed 38 bike-sharing systems in europe, the middle east, asia, australasia and the americas, identifying behavior patterns. metrics were applied to classify bss based on non-spatial and spatial eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 bike-sharing mobility patterns: a data-driven analysis for the city of lisbon 3 location attributes and temporal usage statistics, and a qualitative classification. the study also proposed applications such as demographic analysis and the role of operator redistribution activity. other authors have studied bsss mobility patterns resulting in insights about station and bike trip patterns analysis. one of the most sophisticated bss in the world is in copenhagen, reaching a ratio of 557,920 inhabitants for 650,000 bikes, with 48,000 bike stations and 429 km of cycle lanes [13]. overall, it is estimated that 1,27 million km are travelled daily with 5 times more bicycles entering the city than cars, resulting in 4/5 access to bikes. jensen [14] studied vélov bss, in lyon (france) and analyzed 11,6 million journeys resulting in a visualization map. characteristics, such as peak hour, peak usage and speed in commute were analyzed, showing that the highest speed occurs in the morning peak. the london bss network (santander cycles) is also expanding. in 2016 it reached 11,000 bicycles for 8,416,535 inhabitants, with 750 bike stations, 402,199 km travelled daily and 131,000 bicycle trips. london bss station data, analyzed by lathia [15] and jensen [14], observed usage peaks and significant weekday and weekend differences. spatial clusters with distinctive structures were found grouping intra-day usage patterns. studies show that longer bss trips are observed in larger cities such as chicago [16] and new york, although the latter differs between weekday and weekend usage [17]. caulfield [18] findings showed that most bss trips in medium-sized cities were short and frequent trips. weather conditions also had an important impact, meaning that good weather conditions corresponded to increased trips. el-assi [19] analyzed the variation of trip activity along the season, month, week and hour, establishing correlations between these variables. the authors found a positive correlation with temperature calculated for each season. other studies showed that morning and afternoon peak patterns are different in bss. han study [20] on san francisco spatial-temporal bike trip patterns, showed that ,in the hourly metrics analysis, most of the trips were between 8:00-9:00 am and 5:00-6:00 pm, meaning that most users use bikes to commute to work. el-assi [19] found similar results in toronto bss regarding day peaks. on the other hand, in montreal bixi bss [21], peaks occurs in the evening and weekends. clustering algorithms studies on bss data are applied by combining temporal and spatial attributes variables. more specifically, three clustering algorithms are the most common., namely, hierarchical clustering [16], [22], [23], community detection clustering [16], [24], and k-means clustering, [24]–[27]. according to caggiani [24], who analyzed the three clustering algorithms' performance, k-means has been proven to be the best algorithm to detect and rebalance bikesharing usage patterns. our previous study [6] focused in 2018 lisbon bss data, showing that 64% of trips are done in june, july, august and september, and 82% of the trips were done in weekdays, mainly in the peak hours (8-9 am and 6-7 pm). regarding trip correlation with weather, it showed 97% usage in nonprecipitation days and with temperature between 20º to 30º. moreover, in the clusters analysis [6] we observed four clusters in alvalade-saldanha, telheiras-campo grande, marquês de pombal-baixa and parque das nações. this study aims to take a step further and understand the evolution of lisbon bss mobility patterns from 2018 to 2020. although, having only access to the total daily trip count, and not having data on stations or origin and destination trips we aim to understand how mobility patterns changed in 2019 and 2020, from 2018 results, aiming also to correlate with 2019 and 2020 weather data, and understand how covid 19 pandemic affected lisbon bss usage. 3. methodology in our approach, we applied the cross-industry standard process for data mining (crisp-dm) methodology (see fig. 1). this method is structured in six phases, as follows: phase 1 business understanding: understand and decide what to accomplish with data mining and setting criteria for the data mining aims. phase 2 data understanding: data is collected and evaluated regarding data quality and suitability. phase 3 data preparation: data pre-processing transforms the data into useful information used for the next phase. it involves cleaning, reduction, transformation, and integration of data. phase 4 – modelling: modelling technique is selected and built the model. phase 5 – evaluation: the chosen modelling technique is evaluated according to its objectives according to the results produced in the process figure 1. crisp-dm methodology eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 vitória albuquerque et al. 4 crisp-dm ensures the quality of knowledge discovery in the project results [28], requires reduced skills for such knowledge discovery and reduced costs and time. in phases 1 business understanding, we identified the objectives and framed the business issue (research questions), gathering information. in this phase we perceived the collected data's characteristics to meet the users and business needs. in phase 2, data understanding, we investigated the collected data, understanding where the data comes from and what type of analysis could be done with it. in data preprocessing phase, we preformed data cleaning, removing noise in the data so that further analysis wouldn´t be affected by the data itself. we performed an adaptation of the etl methodology proposed in crisp-dm. our etl (see fig. 2) was used in the data cleaning phase, performing cleaning, conformance and normalization processes in the data sets, to obtain correct, complete, consistent, accurate and unambiguous data [29]. the model phase, allowed the application of statistical and machine learning techniques, enabling discovery of behaviors that could not be possible to observe before. it also includes data visualization, with diagrams, plots, and other graphical depictions that visually show us the found patterns and behaviors. figure 2. etl methodology 4. mining bike sharing data in this section we apply crisp-dm phases to our study, introducing first business and data understanding, looking at the aim and how to address the research questions and how to understand the different bss and weather datasets. this is supported by data preprocessing, cleaning and normalization, that provides new datasets to the model building phase, targeting the analysis and visualization of insights. our datasets include bike trip data of 2018, 2019 and 2020, which were analysed according to the data characteristics in different levels, with the aim to understand the evolution of bike ridership and the impact of built environment and pandemics. our data analysis and visualization were performed in python [30] using the jupyter notebook platform [31]. data cleaning, preprocessing, analysis and visualization were performed using different python libraries, according to the application's purpose. “numpy” [32], “pandas” [33], “matplotlib” [34], “seaborn” [35], were used for statistical analysis and visualization. “gdal” [36], “shapely” [37], “folium” [38], “fiona” [39], were used to visualize spatial analysis. our data science algorithms used “scikit-learn” [40] to perform k-means, train-test split and accuracy score. 4.1. data understanding data was provided in the scope of lisboa inteligente [41] challenges, namely challenges #4 “are there mobility patterns in lisbon bss”, and #49 “determine covid 19 pandemic impact in mobility and environment (https://lisboainteligente.cmlisboa.pt/lxdatalab/desafios/determinacao-do-impacte-dapandemia-por-covid-19-na-mobilidade-e-ambiente/). three levels of analysis were performed with the provided data: the first concerns the bike trip and station data from 2018, with a descriptive analysis regarding month, weekday, period of day and hourly usage rate of the service, following the geographical analysis of trips and stations and finally, a weather analysis. the second regards the 2019 and 2020 bike trips and the monthly and weekday usage rate comparison with 2018, to find and/or confirm behaviour patterns over the 3 analysed years. the third one regards the analysis of bike trip counts collected by a sensor in avenida duque de ávila, a central avenue of lisbon, from 2019 and 2020. lisbon bss data of 2018 different sources of data were provided by the lisbon city hall (cml), namely data on bike trips (from 25th january 2018 to 15th october 2018) and stations from the mobility and parking company of lisbon empresa de mobilidade e estacionamento de lisboa (emel) and, weather data from the portuguese institute of sea and weather – instituto português do mar e atmosfera (ipma). bike station data schema (table 1) includes information about stations: commercial designation id (desigcomercial), entity id (entity_id), planning id (id_planeamento), latitude, longitude and the station capacity (capacidade_docas). this data was collected from 76 bike stations in lisbon. transformation transforming and fusing the data for the analysis interest extraction extracting the data from their data sources visualization visualizing the insights and discovering the eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 bike-sharing mobility patterns: a data-driven analysis for the city of lisbon 5 table 1. lisbon bss station data schema characteristics description desigcomercial commercial designation entity_id entity id id_planeamento planning id latitude latitude longitude longitude capacidade_docas station capacity bike trip data of 2018 (table 2), is featured by origindestination (o-d) trip that includes id (column id), date_start (start date and time), date_end (end date and time), distance (distance in metres), station_start (start station id), station_end (end station id), bike_rfid (bike id), geom (geometry), num_vertices (number of nodes), and tipo_bicicleta (bike_type). the ipma weather data of 2018 (table 3) provides the total precipitation of 3 weather stations (id) located in lisbon: “1200535” lisboa geofísica (lisbon centre), “1200579” lisboa avenida gago coutinho and “1210762” lisboa tapada da ajuda. it is structured with the following features: ano (year), ms (month), di (day), hr (hour). table 2. lisbon bss trip data schema from 2018 characteristics description id column id date_start start date and time date_end end date and time distance distance station_start start station id station_end end station id bike_rfid bike id geom travel trajectory geometry num_vertices number of nodes tipo_bicicleta bike type (conventional or electric) table 3. ipma data schema characteristics description ano year ms month di day hr hour 1200535 lisboa geofísica weather station #1 1200579 lisboa avenida gago coutinho weather station #2 1210762 lisboa tapada da ajuda weather station #3 lisbon bss data of 2019 and 2020 bike trip data of 2019 and 2020 (table 4) is characterized by date (dd/mm/yyyy) and trips per day ranging from 1st january 2019 to 4th june 2020. table 4. lisbon bss trip data schema of 2019 and 2020 characteristics description data date viagens bike trip count the ipma weather data (table 5) is structured with18 variables in 2019, and 11 variables (table 5) in 2020. the variables marked with * are only provided for 2019 data, and the others both to 2019 and 2020. the data ranges from 1st january of 2019 to 30th october 2019, and from 17th january 2020 to 30th june 2020. it is important to highlight that data is missing 9th, 10th and 24th march 2019; 18th and 19th april 2019; 22nd september to 30th september; november and december 2019 and the first two weeks of 2020 (1st january to 16th january). in our analysis we used features, such as, date, weather station code (the codes are the same as 2018 with a new code, “1210783” corresponding to the alvalade weather station) and the temperature levels. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 vitória albuquerque et al. 6 table 5. ipma data schema of 2019 and 2020 characteristics description data_hora date entity_id* entity id entity_location* entity location (coordinates) entity_ts* entity_type* type of entity estaciones weather station code fecha fiware_service* fiware_servicepath* humidade humidity iddireccvento wind direction id intensidadedeventok m wind intensity position station position preacumulacada pressao atmospheric pressure radiacao radiation temperatura temperature validity_ts* avenida duque de ávila data of 2019 and 2020 bike count data of 2019 and 2020 (table 6) was collected from a sensor located in avenida duque de ávila. data provided features all trips count, from bsss bikes and bikes owned by users. it was collected from 1st january 2019 to 1st october 2020 and is structured as follows: “time”: entry of day, month and year (dd/mm/yyyy); “piloto lx” total of bike count (east and west) per day; “piloto lx ciclistas entradas”: bike count per day from the east; and “piloto lx ciclistas entradas”: bike count per day from the west. table 6. avenida duque de ávila bike count of 2019 and 2020 characteristics description time date piloto lx avenida duque de ávila total bike count piloto lx ciclistas entradas avenida duque de ávila bike count from east piloto lx ciclistas saídas avenida duque de ávila bike count from west 4.2. data preprocessing lisbon bss data preprocessing of 2018 lisbon bss data, a fourth-generation system, provides broad and extensive information. data extraction methods have not yet been extensively explored [42], therefore, there are limitations in the collected data, which need to be evaluated on its limitations and cleaned. data cleaning involves handling missing data and noise removal, thus generating datasets with accurate and validated data. the following data cleaning methods were applied to bike trip data: • removal of the not assigned (na) values of the bike type (1% of the dataset). • removal of the geometry and number of nodes with na values, corresponding to 50% of the data. • removal of the the variable speed in trips that were shorter than 1 minute. • the missing values in the distance were filled by computing the average speed times the duration. two datasets were generated for our analysis: one combining precipitation and temperature data and bike trips data (see schemas in table 2 and table 3), and another combining bike trips data and bike station data (see schemas in table 1 and table 2), to generate bike paths in the city and to visualize the stations chosen by the users. the first dataset was joined through a temporal basis, and the second one was joined via the stations field. to generate these datasets, we´ve developed an extract, transform and load (etl) process, loading data from external databases, transforming the data by creating common columns and joining the datasets, and finally loading the data into our project. as a result, from the 3 data schemas presented in tables 1, 2 and 3, we derived, via such etl process, 2 datasets, namely, the “bike trips-stations temporal analysis” dataset (table 7), the “bike trips-stations clustering” dataset (table 8). eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 bike-sharing mobility patterns: a data-driven analysis for the city of lisbon 7 table 7. bike trip-stations temporal analysis dataset characteristics description id trip id date_start start date date_end end date station_start start station station_end end station bike_rfid bike rfid tipo_bicicleta bike type duration trip duration speed trip speed hour hour date_key date key data_id date key rain precipitation (y/n) temp_media average temperature dia day mes month ano year semana week semestre semester trimestre trimester feriado holiday dia_de_semana weekday mês_dsc month description data date periodo_dia day period níveis_temp temperature levels table 8. bike trip-stations clustering dataset station station id n_trips number of trips designation station designation lat station latitude lon station longitude c_docas statio capacity after data cleaning, we retained 684,471 trips in 2018. the average number of trips per month, ranging from january to october, was 68,447 and by station, the average number of trips was 9,126. per day, there was an average number of trips of 2,602. data preprocessing of lisbon bss in 2018, 2019 and 2020 bike trip data of 2019 and 2020 did not require data cleaning and was ready to use. ipma data from 2019 and 2020 required data transformation since there were variables not relevant for our analysis. our final dataset included the date, weather stations and temperature levels variables. the date format included the hour, and in order to merge with our bike trip data, we had to compute the daily mean of the hourly values. this was processed with the grouper function from the pandas [33] library. this resulted in two datasets: one with all 2019 data (bike trip and ipma data) and the other with all 2020 data. a temporal variable was added to each of these datasets. data preprocessing of avenida duque de ávila bike count in 2019 and 2020 avenida duque de ávila bike count data from 2019 to 2020 did not require data cleaning and it was ready to use. 4.3. modelling modelling lisbon bss of 2018 studies in this field aim to understand user´s profile and travel behavior [43]–[45], activity patterns in stations [15] and the impact of the built environment in the bss [46]. the methods applied focus in statistical methods to analyze and visualize data. to understand bike trip patterns in the urban mobility network and trip models, studies have shown the importance to correlate transport mode and trip choices and built environment characteristics [47], [48]. many methods are applied to perform data mining, namely, to examine the relations between bike stations, bike trips and the built environment. the evaluation of bss success depends on these relationships, leading to users’ access to bike stations [49]. clustering algorithms combining temporal and spatial attributes variables are also data mining methods used for this analysis purpose. more specifically, k-means clustering [24]–[27], used by mckenzie [50] and zhong [51] to measure regularity at different scales and to measure spatiotemporal variation and cluster interaction. bike usage analysis to investigate the monthly bicycle usage frequency, we merged the “bike trip dataset” with the “bike temporal basis dataset” and obtained a new relation, with columns ano (year), mês (month), dia (day), feriado (holiday), semana (week), semestre (semester), trimestre (trimester), dia_de_semana (weekday) and mês_dsc (month description). this was our trips schema, with data spanning from january to october 2018. in the summer months (june, july, august and september), the more concentrated period (64% of all trips), there were a total of 439,176 trips, as depicted in fig. 3. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 vitória albuquerque et al. 8 figure 3. bike usage frequency per month the weekday and weekend usage were also analyzed to understand the preferences of using the bike-sharing service during the week. results are presented in fig. 4, where weekdays are ordered from 1 to 7. the weekend is represented by 1 (sunday) and 7 (saturday). our results show that most users (82%) prefer to use the service during the week, rather than during the weekend. figure 4. bike usage per weekday the distribution of trips throughout the different periods of the day was analyzed too. the column date_starts was transformed into a time format and the hour was extracted in order to create the column periodo_dia (day period). the day was broken down into three-hour groups: morning: 7am to 12am; afternoon: 12am– 8 pm and overnight: 8 pm– 7am. our analysis shows that most of the trips (56%) occur during the afternoon compared to the morning and overnight periods (see fig. 5). additionally, during working weekdays, after the afternoon, the morning period comes second. in the weekends, users still prefer to ride during the afternoon, but overnight rides come second, rather than morning ones. when analyzing the behavior and patterns regarding the distance and the duration of the bike trips, we addressed the differences between the weekdays versus bike type. regarding bike type (electric or conventional), we have observed no noticeable differences in terms of trip distance and duration during weekdays. there also no noticeable difference, in terms of speed and duration, across the different days of the week, in average. figure 5. bike usage (%) per weekday within the day period the hour rate was also analyzed. there was an extraction from the variable “date_start” of the hour and the creation of the variable “hour”. the higher usage rate corresponds to 6 pm (10%) following 5 pm and 7 pm (see fig. 6). there is also a high usage rate at 8 am, and 9 am (13% combined). also, it is possible to see that the citizens start to use this service from 7 am to 1 am, having no significant usage between 2 am and 6 am (see fig. 6). figure 6. bike usage (trip count) per hour bike trip weather analysis we conducted an additional analysis to find behavior patterns of bss users, influenced by the built environment variables, particularly weather variables such as atmospheric precipitation and temperature. in our analysis, in terms of atmospheric precipitation, we created a boolean variable “rain” indicating if it was raining or not in any of the three eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 bike-sharing mobility patterns: a data-driven analysis for the city of lisbon 9 weather stations. a new date_key field was generated from the date_start field of bicycle trips, to join the two datasets. from our analysis, we can conclude that the trips are mostly made when there is no precipitation (97%) (see fig. 7). regarding temperature analysis, the negative values were removed and we calculated the average values of the three stations. then, we divided the dataset into four categories: 0º to 10º, 10º to 20º, 20º to 30 and 30º to 42º, being 42º the maximum observed temperature value (see fig. 8). figure 7. bike usage frequency relation to atmospheric precipitation figure 8. bike usage frequency relation to temperature the trip speed was also analyzed in order to check if there was any observed change when raining, concluding that users are faster in their trips when it was not raining. bike station usage analysis our analysis approach on bike station usage was to identify the top 5 most popular stations, the top 5 stations with the highest outflow and highest inflow, and the frequent station pairs on weekdays and weekends looking at in 2018, for each month from january to october and for the whole period. this analysis only considered trips with a duration of over 60 seconds and less than 2 hours and 15 minutes. in 2018, there was an evolution of bike usage. table 9 shows trip increase throughout the year, where the months of july (115,857) and september (127,616) were the ones with more bike usage. station usage also evolved and almost doubled between january (43 stations) and october 2018 (74 stations). this might be related to the opening of new stations in scope of bss network expansion. table 9. trips and stations month trips stations january 6,326 43 february 23,324 43 march 25,872 56 april 47,122 58 may 80,417 72 june 93,296 74 july 115,857 74 august 94,007 81 september 127,636 74 october 58,459 74 jan oct 672, 316 81 the expansion of the bike station network in 2018 did not change the top 5 most popular stations pattern. as shown in table 10, the top 5 most popular stations correspond to stations 446 – avenida da república/interface de entrecampos, 481 – campo grande/museu da cidade, 417 – avenida duque de ávila, 421 – alameda d. afonso henriques, and 105 – centro comercial vasco da gama. these top 5 most popular stations are observed with different ranking in the analyzed months in 2018. the top 5 most popular stations are shown and numbered in figure 8, mapped with all the network bike stations. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 vitória albuquerque et al. 10 table 10. top 5 most popular stations month #1 #2 #3 #4 #5 january 446 105 481 417 403 february 446 417 481 105 403 march 446 417 481 105 403 april 446 481 417 105 420 may 446 481 417 420 421 june 446 481 421 417 105 july 446 481 421 417 105 august 446 481 421 417 105 september 481 446 417 421 105 october 481 421 446 417 443 jan oct 446 481 417 421 105 figure 9. lisbon bss stations map with the top 5 most popular stations id number identified this is also shown in the station trip heatmap (see fig. 10), where the orange color corresponds to a higher number of station trips in a gradient to yellow, green and purple lower station trips. figure 10. station trip heatmap. the orange color corresponds to a higher number of station trips, whereas purple, to a lower. if we look at the flow level (highest inflow and outflow), we observe similarities to the top 5 most popular stations. the top 5 stations with the highest inflow in 2018 (from january to october), are listed in table 11, as follows: 481 – campo grande/museu da cidade, 446 interface de entrecampos, 417 – avenida duque de ávila, 421 – alameda d. afonso henriques, and 105 – centro comercial vasco da gama. table 11. top 5 stations with highest inflow month #1 #2 #3 #4 #5 january 446 481 105 417 403 february 446 481 403 417 105 march 446 417 481 105 403 april 481 446 417 105 403 may 481 446 417 420 421 june 481 421 446 417 105 july 446 421 481 417 105 august 446 481 421 417 105 september 481 417 421 446 105 october 481 421 417 446 443 jan oct 481 446 417 421 105 the top 5 stations with the highest outflow in 2018 (see table 12) are: 446 interface de entrecampos, 481 – campo eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 bike-sharing mobility patterns: a data-driven analysis for the city of lisbon 11 grande/museu da cidade, 417 – avenida duque de ávila, 421 – alameda d. afonso henriques, and 105 – centro comercial vasco da gama. we conclude that although the highest inflow and outflow top 5 stations are the same, the first two are ranked differently. table 12. top 5 stations with highest outflow month #1 #2 #3 #4 #5 january 446 105 481 417 403 february 446 417 481 105 403 march 446 417 481 105 403 april 446 481 417 105 420 may 446 481 417 420 421 june 446 481 421 417 105 july 446 481 421 417 105 august 446 481 421 417 105 september 481 446 417 421 105 october 481 421 446 417 443 jan oct 446 481 417 421 105 looking at the top 5 most frequent station pairs on weekdays and weekend, we observe that in the weekdays (table 13), most trips take place in parque das nações and in the axis campo grande-saldanha. in parque das nações, the most used station pair from station 109 – alameda dos oceanos/rua do zambeze to station 105 – centro comercial vasco da gama and in the opposite direction. most frequent station pairs in weekdays are also observed in the campo grande to saldanha axis. this also correspond to top 5 popular stations as well as inflow and outflow stations, namely, from station 446 – avenida da república/interface de entrecampos to station 403 – avenida fontes pereira de melo, and from station 446 – avenida da república/interface de entrecampos to station 481 – campo grande/museu da cidade. table 13. top 5 frequent stations pairs in weekdays month #1 #2 #3 #4 #5 january 105-109 403-446 109-105 105-110 446-403 february 105-109 109-105 446-403 403-446 105-107 march 109-105 446-403 105-109 403-446 107-105 april 109-105 105-109 446-403 110-105 107-105 may 105-109 109-105 446-403 446-481 403-446 june 105-109 109-105 107-105 105-107 446-403 july 109-105 105-109 105-107 446-481 107-105 august 109-105 105-109 107-105 105-107 446-481 september 105-109 109-105 446-481 107-105 105-107 october 109-105 105-109 446-481 481-446 421-421 jan oct 109-105 105-109 446-403 107-105 446-481 the top 5 frequent station pairs in the weekends (table 14), can be found in parque das nações, like wise as in the weekdays from station 109 – alameda dos oceanos/rua do zambeze to station 105 – centro comercial vasco da gama and in the opposite direction. also, from station 105 – centro comercial vasco da gama to station 107 – rotunda dos vice-reis and in the opposite direction. another frequent station pair on weekends is from station 110 rua de moscavide to station 105 – centro comercial vasco da gama. table 14. top 5 frequent stations pairs in weekend month #1 #2 #3 #4 #5 january 105-109 109-105 110-105 105-110 464-464 february 109-105 105-109 105-107 446-403 403-446 march 109-105 105-109 107-105 110-105 105-110 april 109-105 105-109 110-105 105-110 107-105 may 105-109 109-105 481-481 484-488 110-105 june 109-105 105-109 105-107 481-481 107-105 july 109-105 105-109 107-105 105-107 421-421 august 109-105 105-109 105-107 107-105 208-208 september 109-105 105-109 105-107 107-105 481-481 october 109-105 105-109 107-105 104-102 443-443 jan oct 109-105 105-109 107-105 105-107 110-105 overall, in 2018 there was a total of 672,316 trips in 81 stations, where the most popular pair of origin-destination stations had over 1,000 trips, reaching a total of 5,000 trips (see fig. 11). patterns previously identified are highlighted in the origin-destination matrix (see fig. 11). eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 vitória albuquerque et al. 12 figure 11. origin destination matrix in 2018 looking at the months where most trips occurred, july, august and september, we observe that august shows different station patterns from july and september. this is due to august a holiday month and july and september are working months. a closer analysis of august and september station pattern shift, we observe that in august there was 94,007 trips in 81 stations (table 9), where the 5 most popular stations (table 10) are ranked: 446 avenida da república/interface de entrecampos, 481 – campo grande/museu da cidade, 421 – alameda d. afonso henriques, 417 – avenida duque de ávila/jardim arco do cego, and 105 – centro comercial vasco da gama. moreover, we observed that the top 5 stations with the highest outflow and inflow (see fig. 12) are the same as top 5 most popular stations. regarding the top 5 frequent station pairs in weekdays and weekends we found that most pair stations are in parque das nações, as we also observed in 2018 analysis. top 5 frequent stations pairs in weekdays (table 13) are 109-105, 105-109, 107-105, 105-107, and 446-481. the top 5 frequent stations pairs in weekends (table 14) are 109-105, 105-109, 105-107, 107105, and 208-208 (cais das pombas/cais do sodré). this shows that in august weekend cycling occur along the river in parque das nações and cais do sodré. figure 12. origin destination matrix for august 2018 in september, there was an increase of trips compared to august, with 127,636 trips in 74 stations (table 9) that might be related to work activity return. we identified that the 5 most popular stations (see fig. 13) are the same as in august but ranked as follows (table 10): 481 – campo grande/museu da cidade, 446 avenida da república/interface de entrecampos, 417 – avenida duque de ávila/jardim arco do cego, 421 – alameda d. afonso henriques, and 105 – centro comercial vasco da gama. the top highest outflow and inflow stations are the same but highest inflow is ranked as follows, 481 campo grande/museu da cidade, 417 – avenida duque de ávila/jardim arco do cego, 421 – alameda d. afonso henriques, 446 avenida da república/interface de entrecampos, and 105 – centro comercial vasco da gama; and highest outflow stations are 481 campo grande/museu da cidade, 446 avenida da república/interface de entrecampos, 417 – avenida duque de ávila/jardim arco do cego, 421 – alameda d. afonso henriques, and 105 – centro comercial vasco da gama. eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 bike-sharing mobility patterns: a data-driven analysis for the city of lisbon 13 most frequent station pairs in weekdays and weekends show similarities with previous analyzed months. in weekdays most station pairs are located in parque das nações, intercalated with campo grande and entrecampos as follows: 105-109, 109-105, 446-481, 107-105, and 105107. in weekends, station pairs are mostly located in parque das nações, 109-105, 105-109, 105-107, 107-105, and campo grande/museu da cidade 481-481. figure 13. origin destination matrix for september 2018 spatial cluster analysis in our research, we seek to understand bss users' behaviors, particularly the inflow and outflow of trips in each station and the frequency of stations’ usage. hence, we aim to perform clustering analysis identifying geographical patterns in lisbon bss. datum system of latitude and longitude coordinates was normalized and processed in world geodesic system 1984 (wgs84) regarding station trips data. geographic clustering was performed with k-means was performed and an additional data pre-processing step was required before performing it. to generate station trips cluster, we first counted all trips of every stations, irrespectively if a given station is the origin or destination of a trip. to this aim, we splited the original “bike trips dataset” in two, one with the ‘station_start’ variable and the other with the ‘station_end’ variable. then, the ‘station_start’ and ‘station_end’ variables were changed to “station” in the corresponding datasets. afterwards, both datasets were concatenated within the station variable and trip count was computed for each station. it resulted in a dataset (table 15) with six variables: station, number of trips, station designation, latitude, longitude and dock capacity. latitude and longitude variables were used for the geographical analysis. table 15. clustering dataset first row entry station n_trips designation lat lon c_docas 446 62600 446 – av. república/ interface entrecampos 38.744560 9.147730 40 to perform k-means, we used the elbow algorithm [52], to find the optimal k number through the sse (sum of squared errors) calculation. as shown in figure 14, the k value of four corresponds to the minimum sse of the k optimal value. the four spatial clusters of bike station trips (see fig. 15) are: first, in the center of lisbon, in the axis from alvalade to saldanha (in blue), second in the northwest side of lisbon from telheiras to campo grande/museu da cidade (in yellow), third in lisbon downtown area, from marquês de pombal to baixa (in purple), and a fourth, in northwest of lisbon, in parque das nações (in green). table 16 shows cluster centroids of the geographic clustering generated by k-means. figure 14. elbow method plot eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 vitória albuquerque et al. 14 figure 15. spatial clustering of stations where bike trips start and/or end (yellow: telheiras-campo grande/museu da cidade; blue: alvalade-saldanha; purple: marquês de pombal-baixa; green: parque das nações). table 16. cluster centroids latitude longitude 38.743263 -9.144271 38.772288 -9.095947 38.715984 38.759463 -9.143659 -9.168919 a second analysis was focused on station usage clustering. for that purpose, the variable n_trips was used for clustering, representing the number of station trips. then k-means was performed, with the same type of approach to find the optimal k number, as in the prior geographical cluster analysis. four clusters were computed (see fig. 16) and the four most frequently used stations (labelled in blue) are located in the city centre, while the fifth one is in the northeast. these stations correspond to the top five most popular stations, identified in the previous sub-section figure 16. spatial clustering by the number of trips that start and/or end on a given station (blue: first most used stations; yellow: second most used stations; purple: third most used stations; green: fourth most used stations). bike usage analysis of 2019 and 2020 the same bike usage analysis method implemented for 2018 data, was also applied in 2019 and 2020 data. we divided the 2019 and 2020 data, in two separate datasets by the year and merged each one with the temporal dataset. in 2019, data ranges from 1st january to 31st december, and we observe that in january, february, march, and october (see fig. 17), there were a total of 555,429 trips (40%). on the other hand, the months with the lowest usage rate are may, june, july, and august, corresponding to late spring and summer months, with a total of 363,343 trips (26%). figure 17. bike trip count by month in 2019 in 2020, data ranges from 1st january to 4th june, and we conclude that most users cycle in january and february with a total of 267,390 trips, representing 53% of all trips. there is a decrease in trips from march to april (see fig. 18) of eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 bike-sharing mobility patterns: a data-driven analysis for the city of lisbon 15 about 50% (meaning from 80,803 to 40,082 trips). afterwards, there is an accentuated decrease of trips in may and june, of 86%. this shows a strong impact of the lockdown on bss mobility patterns, due to covid 19 pandemic. figure 18. bike trip count by month in 2020 moreover, we performed a weekday analysis, applying the same method as in 2018. in 2019, the weekday analysis results show (see fig. 19) that users tend to use bss mainly in weekdays, representing a total of 1,134,365 trips (83%). figure 19. bike trip count by weekday in 2019 in 2020, we can see the same pattern (see fig. 20), as in 2018 and 2019, meaning that users mostly ride bss in weekdays. the total trips of the weekdays of 2020 was 395,103 (78%). figure 20. bike trip count by weekday in 2020 relation of bike usage frequency with temperature, in 2019 and 2020 bike trips count and temperature analysis for 2019 and 2020, are depicted in figures 21 and 22. data was preprocessed, where negative values were removed, and the average values per day (from the hour) were calculated from the four lisbon weather stations. using the same method applied to 2018 data, we divided the dataset into four temperature categories: 0ºc to 10ºc, 10ºc to 20ºc, 20ºc to 30ºc and 30ºc to 43ºc. results show that the maximum temperature observed in 2019 and 2020 were, respectively, 27ºc and 24,5ºc. overall, most users prefer to cycle with mild temperature. a bss users pattern observed in 2018, 2019 and 2020. figure 21. bike usage frequency relation with temperature (2019) eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 vitória albuquerque et al. 16 figure 22. bike usage frequency relation with temperature (2020) avenida duque de ávila bike count analysis from 2019 and 2020 our analysis shows that the number of weekly trips from east and west is remarkably similar. the average of total weekly trips is 815, where east and west ranges between 412 and 403. overall, this analysis (see fig. 22) shows a regular pattern of weekly trips in 2019 and 2020, where the most frequent trips took place during the weekdays. we observed two periods of decrease in the number of trips. the first, in 2019, between april and july, and although we do not have information, we can argue that there was a data collection misfunction. the second, from middle of march to may 2020, when the first lockdown restrictions were implemented, due to covid 19 pandemic, showing that such event had a strong impact in lisbon bss mobility patterns. figure 23. avenida duque de ávila weekly bike trip count east, west and total in 2019 and 2020 the monthly analysis (see fig. 23) shows an average of approximately 2,400 total trips. the two-trip count decrease phenomenon were confirmed with previous analysis results, the first drop observed between april and june 2019, and the second between the middle of march and may 2020, corresponding to the previous mentioned first lockdown. figure 24. avenida duque de ávila monthly bike trip count east, west and total in 2019 and 2020 5. discussion our study started with the aim to understand spatiotemporal station and trip activity patterns in lisbon bss in 2018, as stated in our rq1. our preliminary study [6] addressed our first sub-question on the average monthly and daily lisbon bss usage. the analysis showed that the total number of lisbon bss trips, from january 15th to october 25th, 2018 was 684,471 and, that the average number of trips per month was 68,447, while the average station number of trips was 9,126. moreover, we found that the daily average number of trips was 2,602. the analysis showed also that the months of june, july, august, and september had the most concentration of trips during 2018, of 439,176, representing 64% of all trips. we also observed that bss users mostly chose weekdays to ride in the city (82%) rather than in the weekend. another interesting fact regards the hourly usage rate that shows users ride bikes during weekday peak hours, from 8am to 9 am, from 4.30 pm to 6 pm, and at lunch time from 12 to 2 pm. we can affirm that users ride bikes in the daily commute from home to work and work to home and during lunch hours for short travel. our findings also show that during 2018, most of the trips are taken in the afternoon (56%), followed by the morning period and that in the weekend, users prefer to ride overnight. addressing our sub-question on weather conditions affecting lisbon bss mobility patterns, we found that precipitation has a strong impact in bike usage, showing that almost 97% of trips take place when there is no precipitation. this observation was complemented by a correlation with speed analysis showing that higher speed is reached when there is no precipitation. regarding temperature, most users prefer to travel when temperature ranges between 20º and 30º (52%), and a significant number of users cycle when the temperature is between 10º and 20º (42%). sub-question regarding lisbon bss origin and destination station groups, we have observed that the most used were observed in two axis: one from campo eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 bike-sharing mobility patterns: a data-driven analysis for the city of lisbon 17 grande/museu da cidade to saldanha and another in parque das nações, showing that bike demand start and end stations are located in lisbon office areas. moreover, most common stations pairs are in parque das nações both on weekdays and weekends, due to be a busy office area on weekdays and a leisure area at weekends. the most popular station in this area is 105 – centro comercial vasco da gama. most popular stations are located in the axis of campo grande/museu da cidade and saldanha avenida duque de ávila/jardim arco do cego. this area corresponds to a busy office area also surrounded by universities. we have also found that one of the most frequent station pair was between avenida da república/interface de entrecampos and campo grande/museu da cidade, corresponding to two transportation interfaces. we can raise the hypothesis that users are choosing to commute between interfaces by lisbon bss. still in rq1, and regarding the lisbon bss clusters subquestion, we found four major concentrations in the city for the number of station trips. the main areas where users unlock bss correspond to parque das nações (1), the city center: alvalade-saldanha (2), telheiras-campo grande (3), marquês de pombal-baixa (4) meaning that the center of lisbon is where the most trips occur. there is also a close relation of the number of trips with the station capacity. the station cluster with more trips is associated with the stations with the greater bike capacity. we also found a correlation of clusters with the origin and destination station groups. regarding rq2, on addressing how lisbon bss trip patterns have changed in 2019 and 2020 from 2018, our study shows that the total number of trips reached 1,374,751 in 2019 (1st january to 31st december) which is an increase of 101% compared to 2018. in 2020 (from 1st january to 4th june) the total number of trips was 501,037 and represents a decrease of approximately 64% from the previous year. this is highlighted by the average number of trips per month in 2019 that was 114,562 and in 2020 was 83,506. the daily trip average observed in 2019 was 3,766 and 2020 was 3,253. furthermore, in 2019 and 2020, the summer months are no longer the highest trip rate of monthly usage, as observed in 2018. february, march and october, in both 2019 and 2020, were the months where most trips took place. also, we can see that the usage is distributed over all months, and there is no discrepancy between the summer months and the other months of the year, as in 2018. findings show that users are shifting to bike ride during summer and winter, preferring to use bss to other transportation modes. meaning, lisbon bss is becoming a preferred transport mode to commute in lisbon especially for the last mile. regarding temperature, the usage pattern has changed between 2019 and 2020. users prefer to cycle when temperature is between 10º and 20º (56% and 67% respectively), confirming as well that users tend to ride all year long instead of just in the summer months. finally, we also found no significant difference regarding speed and duration of bike trips across the weekdays by bike type (electric or conventional). therefore, our research suggests that the type of bike is not a decisive factor in the bike trip analysis. avenida duque de avila bike count showed results with similar mobility patterns of weekly and monthly bike usage as in lisbon bss analysis. bike users are more active during weekdays and the counting is almost the same regarding its direction of origin and destination (east and west). on the impact of the covid 19 pandemics event, we observed a clear correlation with bss usage. in 2020, the trip decrease between march and april can be explained by the state of emergency lockdown declared in portugal from 18th march 2020 to april, and then renewed on 3rd april 2020 until 2nd may 2020. this explains the decrease in bike trips in 2020, compared to the same period of time in 2018 and 2019. the major limitation found in our study was the unavailability of bike usage features in provided data for 2019 and 2020 but made available in the 2018 datasets. in 2019 and 2020 data presents the aggregated total counting per day, not specifying either the origin and destination stations or trip time (hour, minute and second). this prevents the authors to understand and obtain insights, regarding the years of 2019 and 2020, such as the evolution of users’ mobility patterns, the most popular stations and stations pairs, inflow and outflow in the various stations and trajectories. 6. conclusions this paper provides new insights into lisbon bss, first implemented in 2017 and evolving till nowadays. it was interesting to analyse the evolution and strong bss demand in a city that did not have a cycling culture until recently. significant findings show that most lisbon bss trips in 2018 occur in weekdays during the afternoon, which correlates with the daily afternoon commute (6 pm – 7 pm). we also found that weather conditions [18], [19] had an important impact on travel behavior. no precipitation was consistent with ridership increase, as well as mild temperatures between 10º to 30º. in 2018 june, july, august and september trips represent 64% of all bike trips in 2018. the most frequent trip station pair origin and destination are along campo grande and saldanha axis, and in parque das nações, where most offices and universities are located in lisbon. the cluster analysis highlighted the previous results in four clusters located in alvalade-saldanha, telheirascampo grande, marquês de pombal-baixa and parque das nações areas. although limitations of 2019 and 2020 data did not allow us to perform a spatiotemporal analysis, we performed a monthly, weekday and weather correlation analysis. in 2019, the months february, march and october represent 40% of all trips since there is a high usage during all year. in 2020, most trips were taken in january and february representing 53% of all trips. this is a striking difference compared with 2018 when trips mostly occurred in summer months. meaning bss is becoming a frequent mode in lisbon commute. in 2019 trips doubled from 2018, with eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 vitória albuquerque et al. 18 good demand rates in 2020, although the complete year data is required to its analysis. avenida duque de ávila bike count data of 2019 and 2020 added a broader scenario to the analysis with a case study, and confirmed previous findings in 2018, 2019 and 2020 lisbon bss that trips are more frequent on weekdays. the impact of the covid 19 pandemics in urban mobility patterns has a clear correlation with lisbon bss usage but more data is needed to understand better the phenomenon along 2020. lisbon bss trip patterns are thus similar to other observed bss of medium-size cities [18] discussed in the state of the art section, such as patterns found in short and frequent trips and ride peak observed in the morning and afternoon, as in the case study of the city of cork (ireland) [18]. parallels with larger cities can be established as well. in canada, for instance, montreal’s bixi bss [21] is mainly used on weekdays, evenings and weekends. in toronto, bike trips are shorter on the weekdays mornings [53]. large usa cities bss studies [16], [17], [20] show frequent bike use in the morning and afternoon peaks [16] and different usage patterns between weekdays and weekends, identifying longer trips in the weekend [16]. in large european cities, weekday morning trips in the peak hour [14], [51] reach a higher speed than trips over the weekdays and weekends. as for the lisbon bss there is a strong possibility of overtime change, as future bss network expansion plans are implemented in the city in the coming years. further work needs to be conducted regarding lisbon bss in the scope of urban analytics [54] and parallel comparison with other bss implemented nationally and internationally. lisbon bss future work also requires bike data availability of 2019 and 2020 and coming years, with the same features as in 2018 data, to achieve the level of analysis regarding stations and cluster analysis. future work needs to be conducted regarding topics such as, bike station management models, prediction of potential network demand to improve network planning, optimization of stations and locations, bikes rebalancing 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[55] “summer school 2020 – iot for smart cities.” http://istar.iscte-iul.pt/summerschool2020/ (accessed aug. 03, 2020). eai endorsed transactions on smart cities 08 2021 10 2021 | volume 5 | issue 16 | e2 aspects of mechanism design for industry 4.0 multi-robot task auctioning aspects of mechanism design for industry 4.0 multi-robot task auctioning ajay kattepur1, sourav khemkha2,∗ 1ericsson artificial intelligence research, bangalore india. 2dept. of mathematics, indian institute of technology, kharagpur, india. abstract collaborative multi-robotic tasks are essential in complex industry 4.0 deployments, involving autonomous robots. as such autonomous robots work with minimal centralized control, analysis of strategies for effective cooperation in task completion are needed. this is specially crucial when automation tasks are outsourced to specialized vendors without centralized control. mechanism design techniques have been proposed to create scenarios among multiple autonomous (possibly selfish) entities to result in desired outcomes. in this paper, we study the effect of varying bidding auction mechanism design protocols to result in multi-agent task auctioning. we demonstrate this approach over a realistic use case of task allocation involving multiple pick and place robots in industry 4.0 warehouses. multiple realistic auction/bidding scenarios considered including selfish agents, erroneous estimates of temporal features, heterogeneous capacities and composite bids. the results demonstrate that effective mechanisms can lead to fair outcomes despite erroneous or biased bids for tasks from agents. received on 07 august 2020; accepted on 05 august 2021; published on 12 august 2021 keywords: smart things and smart objects, software defined networks and internet of things, smart homes, buildings and malls copyright © 2021 ajay kattepur et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.12-8-2021.170670 1. introduction industry 4.0 integrates the use of robotics, cyberphysical systems and intelligent automation [1]. this has led to increasing proliferation into manufacturing, supply chain, retailing and warehousing sectors. the key enablers for industry 4.0 include: 1. the ability to interoperate between computing, internet of things (iot) [2], robotics and human participants. 2. the ability to add information to physical systems, such as those provided by sensor data. 3. replacing human participants in technical tasks, specially those requiring repetitive automation or robotic precision. ∗corresponding author. email: ajay.kattepur@gmail.com 4. robotic systems performing tasks in an autonomous fashion, with minimal human intervention. a fundamental characteristic required in industry 4.0 deployments is the ability of autonomous robotic devices to self-configure in dynamic goal and deployment conditions. this requires autonomous goal evaluation, reasoning and task completion capabilities in agents. an industry 4.0 use case of interest is amazon’s warehouse 1 [6], wherein multiple kiva robots are used for pick and delivery tasks. tasks arrive at varying rates and may be be completed by robotic agents available in the warehouse. warehouse systems have been typically controlled using a centralized monitors, which track inventory and locations of agents on the shop floor. however, this is antagonistic to the principles of industry 4.0, requiring distributed, autonomous and decentralized participants. this also requires specific locations, states, 1https://www.amazonrobotics.com/ 1 eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e2 https://creativecommons.org/licenses/by/4.0/ mailto:<ajay.kattepur@gmail.com> https://www.amazonrobotics.com/ ajay kattepur, sourav khemkha task capacities of individual agents to be monitored and maintained in a centralized fashion, which is not scalable. the design of systems that have distributed, autonomous and (possibly) selfish agent interactions requires a careful analysis of desired goals. systematic techniques are needed to model the interactions, constraints and the resultant outcome of such system constraints. mechanism design [3][4] is concerned with settings where a policy maker faces the problem of aggregating the announced preferences into a systemwide decision. mechanism design solves a decision or optimization problem with incomplete information on agent capabilities. the most widely used mechanism is the vickery-clarkes-groves (vcg) mechanism [5][4], that can guarantee pareto optimality and promote truthful bidding as a dominant strategy. in this paper, we apply various mechanism designs to study coordination problems among multiple intelligent robotic agents [7]. we consider the industry 4.0 warehouse scenario where multiple picking, placing and inventory management tasks are to be completed via an auction mechanism. the agents are autonomous, may have incomplete information about the bids and heterogeneous capacities. the combinatorial auction is formulated with agents vying for tasks, in order to be rewarded with point scores. point scores gained due to completion of tasks are traded off with battery charging times, that may be used by agents (analogous to cash payments received to human participants). such a federation of agents is required for large scale deployments, with vendors and heterogeneous robots competing for common tasks. we integrate the vcg mechanism to enable task auctioning and coordination among the robotic agents in industry 4.0. through exhaustive simulations, nuances are studied in scenarios including heterogeneous agent capacities, individual task bids, combinatorial bids and collusion with erroneous estimates. we demonstrate how the mechanisms may be made robust enough to ensure fair and truthful allocation to auction participants. such a model ensures fair, scalable and efficient deployments of autonomous agents in industry 4.0 deployments. the principal contributions of this paper are: 1. porting the industry 4.0 autonomous agent task allocation problem into a game theoretic mechanism formulation. 2. evaluating the use of vcg auctioning mechanism designs for combinatorial auctions in cooperative tasks. 3. consider auctions under multiple scenarios with homogeneous/heterogeneous agents, single/combinatorial tasks and truthful/erroneous bids. 4. extensive simulation of the above mechanisms, to demonstrate efficacy of solutions in industry 4.0 context. the rest of this paper is organized as follows: a survey of the state of the art is presented in section 2. section 3 provides an overview of the automated task procurement processes in industry 4.0 warehouses. an overview of mechanism designs, combinatorial auctions and bidding languages are provided in section 4. mapping problems from industry 4.0 task allocation into mechanism design formalisms, with bidding, allocation and payment is provided in section 5. comprehensive simulations are examined in section 6, including use of heterogeneous agents, composite bids and erroneous estimates. this is followed by conclusions of the paper. 2. related work we provide an overview of the state of the art in combinatorial auctions, mechanism design and industry 4.0 warehouse automation. 2.1. mechanism designs and auctions auctions and bidding techniques have been proposed to allocate resources to parties in a fair manner. this has been extended in combinatorial auctions [8], where bidders propose bids on combinations of available items/tasks. as bidders are autonomous and may behave in individualistic manner, it is important to set up games that can result in desirable outcomes both to the auctioneers as well as the bidders. mechanism design [3][4] has been proposed to generate social interactions among agents, in order to meet certain goal objectives. it is the assumption of the mechanism design process, that the participants in the social interaction will hold private information and behave in a self-centered manner to maximize private goals. the most widely used mechanism is the vickery-clarkesgroves (vcg) mechanism [5][4]. a simple used case of the vcg mechanism is the vickery auction or the second price sealed bid auction, wherein each buyer submits a sealed bid, the buyer with the highest bid is declared the winner. the use of combinatorial auctions and mechanisms have been proposed in the logistics, autonomous robotic and vehicular transport segments. in [9], the application of single-round combinatorial auctions have been applied to home depot’s transporter handling network. the results indicate that the choice of auction mechanisms not only provided better rates, but many of the carriers also expressed increased satisfaction in the awarded tasks. in [10], the use of vcg auctions in multi-tenant autonomous vehicle scheduling is proposed, that would help improve the utilization of resources. in [11], the use of software actors interacting over mechanisms for 2 eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e2 aspects of mechanism design for industry 4.0 multi-robot task auctioning improved agility and scalability is proposed. in our work, we apply efficient mechanism design to autonomous robots deployed in industrial settings. 2.2. industry 4.0 automation industry 4.0 deployments [1] propose the use of autonomous robotic entities to complete complex tasks. commercial deployments have been used in warehouses [12] to improve throughput of automated tasks. amazon2 has deployed hundreds of autonomous robots to aid in reducing costs of warehouse logistics [6]. inspiration is drawn from the use of autonomic computing technologies [13], that allow robotic runtime reconfiguration and adaptation. architectures with selfaware, self-configuring and self-optimizing capabilities have also been proposed [14], that may be applied to such automation frameworks. for smaller scale deployments, coordinating robotic entities via a centralized cloud [15], could prove useful. in [16], a smart factory framework is proposed that incorporates industrial network, cloud, and supervisory control terminals with smart shop-floor objects such as machines, conveyors, and products. as the smart factory is characterised by a self-organized multi-agent system, an intelligent negotiation mechanism is proposed for agents to cooperate with each other. analysis done in [17] demonstrates that the system between the picking and storage area represents the most critical subsystem in automated warehouses. these requirements suggests the development of decentralized control solutions, involving coordination among multi-agent systems. in [18], a distributed optimization framework is proposed to handle task allocations in industry 4.0 warehouses. in [21], a decentralised multi-agent variant of robotic coordination in an open factory setting with multiple owners of robots as well as different owners of the items to be produced, both considered self-interested and individually rational are considered. this is solved using a multi-agent decentralised optimisation approach that is computationally efficient. in this paper, we apply mechanism design to the combinatorial auctioning of tasks in industry 4.0 warehouses. table 1 provides a detailed comparison with respect to the categories of papers. we have contrasted work using multi-agent optimization, game theoretic models and reinforcement learning. to the best of our knowledge, there is limited work in the intersection of combinatorial auctioning and industry 4.0 robotic task allocation. we consider auctions under multiple scenarios with homogeneous/heterogeneous agents, single/combinatorial tasks and truthful/erroneous bids. such an in depth analysis of mechanisms would bring us closer to practical deployments of autonomous entities in industrial settings. 2https://www.amazonrobotics.com/ 3. automated task procurement process in this section, we provide an overview of industry 4.0 warehouse automation, that makes use of multiple intelligent robotic agents for task completion. 3.1. intelligent agents traditional techniques to coordinate machines and robots in large warehouses involve centralized architectures. a typical use case could include data analytics and coordination performed over a centralized cloud repository [6]. however, there are multiple drawbacks of centralized coordination, including: (i) inefficient latency overheads to transmit large datasets to the cloud (ii) inability to reconfigure in real-time to changes, that is a requirement of multiple manufacturing and transportation scenarios (iii) lack of scale, dependent on a single computational node to optimize operations. an alternative to such centralized systems, is to make use of multi-agent systems [7]. multi-agent systems consist of multiple coordinating intelligent agents, that can perform task computations in an autonomous fashion. the intelligent agents posses perception/actuation capabilities to sense/act on the environment – however, this information may be restricted to a limited viewpoint. in order to perform more complex tasks, it is necessary for the agents to coordinate with each other. the data and knowledge captured by agents may be shared amongst the agents via hierarchical or peer-to-peer mechanisms. this information may be used to perform more complex sets of tasks, than would have been possible by individual agents. to model the robotic components in warehouses, we make use of the autonomous robot abstraction, inspired by intelligent agents [19]. typical activities, for instance with a pick & place robot in a smart warehouse, include: 1. goals: understanding goals of each task and subtask, such as, placing correct parts into correct bins within the given time constraints. 2. perception: object identification and obstacle detection using camera and odometry sensors that sense the environment. this aids the robot in object detection and identification. 3. actions: identifying granular actionable sub-tasks, such as, moving to particular location, picking up parts of orders or sorting objects. constraints may be placed on the robot capabilities, motion plans and accuracy in performing such actions. 4. knowledge base: using domain models of the world for goal completion, such as warehouse environment maps, rack type and product features. we further elaborate on task allocation in the industry 4.0 automation setting, next. 3 eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e2 https://www.amazonrobotics.com/ ajay kattepur, sourav khemkha table 1. state of the art comparison on industry 4.0 multi-robot task auctions. papers approach contrast with our approach. [13] [15] cloud/edge robotics for industry 4.0 techniques in this area largely rely on a centralized coordinator to orchestrate the tasks. the cloud, edge or master controller is responsible for allocating tasks to the agents and monitoring progress. in contrast, our approach makes use of an auctioning mechanism where the agents may bid for jobs and available tasks. any deviations in bidding or errors re handled by the system. the advantage is that multiple vendors / robot types may participate in the auctioning process. [16] [18] [21] distributed optimization, multiagent systems for industry 4.0 these category of papers consider an open and flexible deployment of agents within the factory floor. there may be variations in demands, heterogenous agents and agents incoming/leaving the system. unlike centralized optimization approaches, these rely on decentralized optimization approaches. this is in line with the area of this work. however, we make use of combinatorial auctions that are an alternative to optimization based approaches. the optimization happens at the bidding level rather than the task level. [11] [9] [10] game theory and auctions for autonomous agents these set of approaches make use of game theory, mechanism design and combinatorial auctions to solve problems in autonomous agents. however, the settings are in the case of autonomous electric vehicles and software, which have their own set of constraints. there is not much analysis of selfish agents and overbidding that has been done in this paper. moreover, industry 4.0 robotic coordination comes with its own set of challenges and bidding specifications, that are to be included. [22] [23] reinforcement learning approaches for multirobot coordination these approaches make use of machine learning and reinforcement learning to coordinate multiple robots. however, an extended training period is needed, which cannot be guaranteed in all cases. our solution is a higher level alternative to this, wherein coordination of autonomous agents is carried out via vcg auctioning. 3.2. industry 4.0 warehouse tasks industry 4.0 warehouse tasks require coordination between multiple autonomous agents. this is specifically needed in large warehouse set-ups where a “parts-topicker” model involving items on a conveyor belt has to be replaced by a “picker-to-parts” model, such as making use of autonomous mobile robots. to further elaborate we present the following realistic scenario: a large warehouse is presented, such as those managed by amazon or dell. orders arrive periodically and are retrieved by a fleet of autonomous robots. a set of server robots receive the orders and efficiently allocate them to the delivery robots. the delivery robots move along the warehouse floor and approach appropriate product locations. the delivery robots recognize the correct items and make use of robotic arms to pick the objects. there are constraints on the task completion times that must be met. the robots have limited carrying capacities and drain batteries as they perform tasks. there are also variations in order arrival rates. the scenario described above requires multiple aspects to be taken into account. first, there is a lack of a centralized control mechanism, requiring a protocol for coordination among the agents. second, rather than accumulating tasks in batches to be procured at a later stage, the processing must be done in a first come first serve basis. third, the number of agents and the tasks allocated should be appropriately scaled up in accordance with order rates. fig. 1 provides an overview of the warehouse automation model. specialized agents are used to schedule and procure products with minimal external control. server agents broadcast goal tasks to delivery agents. mobile delivery agents acquire a subset of tasks and execute them within the time constraints. they are provided with points for completion of tasks, that may be used to recuperate battery power at charging stations. the agents may be penalized for unfulfilled orders. the server agents keeps track of the increase/decrease in item inventory in the warehouse. do note that the tasks are typically complex, requiring coordination among multiple agents. a typical case would be products to be re-tried from disparate locations, that would be efficiently re-tried by agents 4 eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e2 aspects of mechanism design for industry 4.0 multi-robot task auctioning server agents batch product requests picking mobile agents inventory levels picking locations robot path storage racks battery charging stations figure 1. multiple agents deployed in warehouses. located in close proximity. the auctioning and allocation of tasks is typically limited by the following constraints: ◦ utilization – as every agents has limited load carrying capacity, the agents may choose to bid or abstain from tasks that would not maximize utilization. ◦ latency – every task has a time range that must be met, which might restrict the agents that may participate. ◦ battery limitation – the agents also must consider battery capacities, that must last throughput the task duration. further elaboration of how auction mechanism formulations may be ported to distributed settings are elaborated in the proceeding sections. do note that as there is autonomy involved in the process, there are relative estimates of latency and battery depletion entailed with completion of a task – these should be incorporated into the allocation model. 4. mechanism design and auctions in this section, we introduce combinatorial task auctions that may be applied towards multi-agent task allocation. mechanism designs that are responsible for generating scenarios where autonomous agents bid for tasks are also studied. 4.1. combinatorial task auctions auctions and bidding techniques have been proposed to allocate resources to parties in a fair manner. this has been extended in combinatorial auctions [8], where auctions of multiple non-identical items is performed and the bidding price may depend on compositions of other item bids. in general, as agents intend to bid for combinations of items, the combinatorial auctions may lead to superior allocations. however, due to the exponential number of combinations, typically a subset of combinations are allowed to make the complexity tractable. the four aspects to be specified in combinatorial auctions are: 1. bidding: as each bidder provides bids for a combination of items, the protocol to specify the bids are to be efficiently specified. 2. allocation: the allocation of items to various bidders will choose to maximize an utility function based on the bids. 3. payment: the rules of payment will be such that the auctioneers’ revenues are maximized, while ensuring fair allocation. fairness here refers to the ability of the mechanism to identify collusion or over-optimistic bidding among agents that could lead to tasks not being fulfilled. 4. strategy: as every bidding agent is autonomous, it is assumed that the strategy employed would be motivated by individual gains. the auction should be formulated such that despite individual motivation, the allocation would maximize overall utility. this paper considers only sealed bid auctions with a private value model for each bidding agent. the modelling is as follows: 1. a single auctioneer presents m items for sale. this is bid on my n bidders, having id i and individual valuation functions vi. 2. vi(s) is the valuation provided by bidder i for a subset of items s. 3. the auctioneer determines the winning bidders based on an allocation algorithm: find a pairwise 5 eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e2 ajay kattepur, sourav khemkha disjoint set s1, . . . , sn to maximize the overall utility ∑ i vi(si). as the combinatorial auctions must posses capabilities to express combinations of items [5], the following bidding combinations are typically employed: (i) atomic bids: the bidder submits a price p for a subset of items s. (ii) or bids: bidders submit a number of atomic bids (si, pi), with the subset of items si being valued at pi. the bidder may be awarded more than one subset. (iii) xor bids: this is similar to the or bids; however, only one of the subsets is awarded to each bidder. such bidding techniques are integral to designing suitable mechanisms for multi-agent task auctioning, described next. 4.2. mechanism design the main focus of mechanism design [3][4] is on on the design of social institutions that satisfy certain objectives, despite the fact that participating individuals hold private information. an instance would be in an auction setting, where the auctioneer would act in favour of increasing the price of items; on the contrary, the bidder would attempt to acquire the goods at the lowest possible value. formally speaking, for a finite set of individuals n = {1, 2, . . . , n} represented by i, the set of possible decisions are represented as d ∈ d. we define a few terms that are used in the mechanism design context [3]. definition 1. individual preferences the private information held by individual i is denoted by θi ∈ θi. the utility function representing preferences over decisions is denoted by vi : d × θi → r. the preference of an individual vi(d, θi) denotes the advantageous benefit from decision d ∈ d. if an individual prefers decision d over d′, it is denoted by vi(d, θi) > vi(d′, θi). definition 2. allocating a private good: in an auction, an atomic good is allocated to a bidder. the allocation is represented as d = {d ∈ {0, 1}n :∑ i di = 1}, where di = 1 denotes successful bidder. the successful bidder benefits by θi thus producing the valuation vi(d, θi) = diθi. definition 3. efficient decision a decision rule d(θ) is efficient if: ∑ i vi(d(θ), θi) ≥ ∑ i vi(d′, θi) (1) for all θ and d′ ∈ d. this presents the pareto optimal front of allocating the good. definition 4. mechanisms a mechanism is defined as a pair (m,g), where m is the message space and g is an outcome function dependent on the decision d. so, for a set of messages (m1, . . . ,mn), the resulting outcomes of decisions are represented by (gd(m), gt,1(m), . . . , gt,n(m)). a good mechanism is one wherein the participants individually choose messages dependent on their private information, yet leading to socially desired overall outcomes. dominant strategies are ones wherein the individuals have the best possible messages with respect to other participants in the mechanism. in other words, the dominant strategy is optimal irrespective of the behaviour of other participants. definition 5. dominant strategies for an agent i with private information θi, a strategy mi ∈mi is said to be dominant if: vi(gd(m−i,mi), θi) + gt,i(m−i,mi) ≥ vi(gd(m−i,mi), θi) + gt,i(m−i,mi) for all m−i, mi; m are the messages made public. as each agent holds private information θi, the mechanism must provide incentives to reveal this information truthfully. individuals are taxed or subsidized based on the revealed θi. this incentive is provided using a transfer function t : θ → rn . for every decision d, the social choice function is provided as (d(θ), t(θ). some typical desired properties of social choice functions, include: 1. pareto optimality: implementing an outcome that is not pareto-dominated by any other outcome, so no other outcomes make one agent better-off while making other agents worse-off. 2. maximized social welfare: implementing an outcome that maximizes the total utility across agents. this is often called the efficient outcome. agent i with type θi has utility vi(θi, o) for outcome o ∈ o, where o is the possible set of outcomes. we might wish to achieve efficiency in the system by maximizing the total utility gained across all agents, in which case: f(θ) = max o∈o ∑ i∈n vi(θi, o) (2) 3. budget balance: the total payment that agents make equals exactly zero (a strict budget balance), so money is not injected into or removed from a system. or, the total payment is non-negative (a weak budget balance), so the mechanism does not run at a loss. 4. individual rationality: we can consider individual rationality, in which an agent has non-negative utility in expectation to a given mechanism. the most widely used mechanism is the vickeryclarkes-groves (vcg) mechanism [5][4]. a simple used case of the vcg mechanism is the vickery auction or the second price sealed bid auction, wherein each buyer submits a sealed bid, the buyer with the highest bid is declared the winner. the winning bidder pays an amount equal to the second highest bid. it can be shown that the 6 eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e2 aspects of mechanism design for industry 4.0 multi-robot task auctioning mechanism is truthful – a mechanism where bidding the true valuation is a dominant strategy [3]. vcg mechanism 1. each agent reports a valuation v̂i. 2. the mechanism chooses the allocation (m1, . . . ,mn) that maximizes ∑ j v̂j(mj) and outputs it. 3. for each agent i: (a) the mechanism finds the allocation (m′1, . . . ,m′n) that maximizes ∑ j,i v̂j(m′j). (b) agent i pays pi = ∑ j,i v̂j(m′j)−∑ j,i v̂j(mj). we apply the vcg mechanism designs to evaluate auctions in industry 4.0 settings in the next section. 5. industry 4.0 automation task auctions we re-visit the scenario on industry 4.0 warehouses from section 3.2, wherein multiple mobile picker robots are deployed in order to complete a task. the pickup/delivery tasks can arrive at varying rates and may also differ in the number of agents/time-lines expected for completion. we formulate this problem as via decentralized bidding – the factory/warehouse can only publish tasks; agents that may be managed by multiple vendors bid on tasks. each agent is a potential bidder – bidders will place bids on any subset of tasks they want to complete. for each bidding horizon, we assume there are n agents and m tasks. agents charge a certain amount to complete a task – these points may be traded for charging times at stations (akin to remuneration provided to human agents for task completion). a central system receives all the bids, processes them and allocates the tasks in an optimal way. the charging mechanism ensures that bidders bid truthfully. table 2 provides the notations for the agents and tasks in the industry 4.0 warehouse scenario. agents are provided additional labels to specify their location coordinates, battery life, carrying capacities and bidding information. an important point to note here is that the agents will bid based on estimation algorithms, that determine the cost (in terms of latency, battery deletion rates) used for valuing the bids. there may be agents who provide gross under/over erroneous estimates of the valuations (akin to human agents lying). it is the ability of the mechanism to handle such cases that determines efficacy in practical deployments. on receipt of orders to be procured from the warehouse, the agents coordinate to ensure timely completion of the procurement process. this can be delayed by order congestion or unavailability of sufficient agent resources. the process of auctioning tasks among autonomous agents can be broken into three parts: (i) bidding process: the input given to the auctioning problem would be the vector of bidder’s valuation and the number of combinations permitted per bidder. (ii) allocation of the winners: an optimization problem that can be posed as a knapsack problem – relaxations in conditions may be needed to compute the allocation. (iii) paying the winners: the amount that a winner pays that is socially optimal must be determined by the mechanism. 5.1. task auctions the process for task auctioning starts by the server agents displaying the task, time constraints (if any) and baseline scores for task completion (fig. 1). if the delivery agents bid for a subset s of tasks (s1, s2, . . . , sk) then his true valuation of this subset is the sum of the distances between agent’s current location and each task’s location. the actual bid might be greater than the true valuation, when the agent is greedy to gain more point scores. depletion in the battery is a function of the task valuation to be performed. thus, each bid is of the type (si, bidsi) where si is the subset of the tasks considered for the ith bid and bidsi the value of the bid. as already mentioned we have a total of l bids. the python3 code snapshot of bid allocation to tasks is provided below: 1 def assign_bids (bids ,erroneous ,n,m): 2 cnt = 0 3 for i in range ( erroneous ): 4 for j in range (m): 5 if(i< erroneous ): 6 bids[cnt] = (int)(bids[cnt ]*(1+ abs( np. random . normal (0 ,1)))) 7 cnt = cnt +1 8 return bids 9 10 def solve (agents ,task , discharge_rate ,n,m, erroneous ) : 11 bids = [0 for x in range (m*n)] 12 dist = [0 for x in range (m*n)] 13 cnt = 0 14 for j in range (n): 15 for k in range (m): 16 dist[cnt] = ( agents [j]. pos). comp_dis (task[k]) 17 bids[cnt] = agents [j]. bidding_func ( dist[cnt] * discharge_rate ) 18 cnt = cnt +1 19 bids = assign_bids (bids , erroneous ,n,m) we notice that the bids are a function of the dist distance to perform the task and discharge_rate the battery discharge rate. bids that are provided by agents 3https://www.python.org/ 7 eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e2 ajay kattepur, sourav khemkha table 2. notations for task auctioning. n number of agents agent id agent identity bids a set consisting of all the bids v represent the true valuation to corresponding bid agent l total number of bids per task attributes n′error number of agents who provide erroneous estimates n′′light number of agents who can pick up only light objects score total amount charged/gained for a completed task life battery capacity remaining on the agent pos agent position m number of tasks task task id representing the task attributes pos location of the tasks type 0 if task if light weight, 1 if task if heavy weight with erroneous estimates are incremented by a normally distributed random value. 5.2. allocation of the winners given a set of bids in a combinatorial auction, the objective is to find an allocation of items to bidders that maximizes the auctioneer’s revenue. the bids are expressions in a bidding language (section 4.1), by which bidders report valuations for subsets of items the auctioneer’s revenue is maximized by choosing an allocation that maximizes the sum of the bidders’ valuations for the subset of items that they receive. definition 6. winner determination problem: given bids bidsi, i = 1, . . . , n, the winner determination problem is the problem to compute: x ∈ argmax ∑ i∈n bidsi(s)xi(s)|x is a feasible solution ) (3) we have a total of l bids of the form (si, bidsi), and the allocating the best bids could be thought of as a multidimensional knapsack problem [20]. we denote xi as binary variable which is equal to 1 if the ith bid has won else 0, and we also denote k as the maximum no of bids any agent can win. this is formulated as: min: ∑l i=1 xi · bidsi s.t.: ∑ i|j∈si xi ≤ 1 ∀j = 0, 1, 2, . . . ,m− 1∑ i|jthagent bids xi ≤ k ∀j = 0, 1, 2, . . . , n− 1 xi ∈ {0, 1} ∀i = 1, 2, . . . , l (4) the first constraint ensures that every task is allocated at most once as the tasks are indivisible, while the second constraint denotes that every agent can win at most k bids. since the multi-dimensional knapsack problem is np-complete, we use branch and bound heuristics to generate feasible solutions [20]. 5.3. winner scores we use the vcg mechanism to pay the winners (price scores), which ensures truthful bidding. we will later see that if bidders lie they would suffer relative losses, given this mechanism. the total amount paid to the agenti: (social welfare of others if agent i was absent) (social welfare of others if agent i was present) (5) where, social welfare of all players = ∑l i=1 xi · bidsi. the code snipped provided below with the winning agents provided a pricing score (agents[winner].score), updating the battery discharge rate (agents[winner].life) and current position (agents[winner].pos). 1 winning_bids ,s= knapsack (bids ,weights ,n,m) 2 print (s) 3 for i in winning_bids : 4 winner = i//m 5 new_bids =[0 for x in range (m*(n -1))] 6 c1 =0; c2 =0; 7 for j in range (n): 8 if j== winner : 9 c2=c2+m 10 continue 11 for k in range (m): 12 new_bids [c1 ]= bids[c2] 13 c1=c1 +1 14 c2=c2 +1 15 new_weights = assign_weights (len( new_bids ),n -1,m) 16 _,s1= knapsack (new_bids , new_weights ,n-1,m) 17 18 agents [ winner ]. score += s1+bids[i]-s 19 agents [ winner ]. life -= dist[i]* discharge_rate 20 agents [ winner ]. pos=task[i%m] the pricing score attained after multiple rounds may be used by agents to re-charge batteries at the battery charging stations (fig. 1). it would be advantageous for individual agents to secure maximum pricing scores for 8 eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e2 aspects of mechanism design for industry 4.0 multi-robot task auctioning minimal work done; it is the responsibility of a good mechanism to identify these scenarios and award scores fairly. multiple scenarios involving such multi-agent task auctions are analyzed via simulations in the next section. in the case of our mechanism design, the agents can bid for tasks using their estimates of bid valuations. an awarded bid results in payment in the form of point scores – this may be redeemed by agents to charge batteries (readers may notice similarity with prices paid to human agents for tasks). our approach is decentralized, wherein all the bidders compute their bids in parallel and then pass it to the central system. this is different when compared to a centralized task allocation process, where it would be the central system’s responsibility to compute these allocations in a sequential manner. if t1(m) denotes the time taken to calculate the bids (optimization problem for a particular agent) and t2(l, n,m) be the time taken to solve the winner determination problem, then the overall time complexity for the two approaches are : 1. centralized : n× t1(m) + t2(l, n,m) 2. decentralized : t1(m) + t2(l, n,m) thus, the computational time complexity reduces significantly for higher number of agents. 6. simulation results we study the effects of varying mechanism designs on the industry 4.0 warehouse demand auctioning process (fig. 1). we have considered a grid size of 100× 100 m. in all our simulations we consider 50 iterations(unless specified). in each iteration there are m task locations generated from a uniform distribution. the initial battery capacity is 100% and the discharge rate of the battery is 0.1/m. if there is a particular task which a agent will not be able to complete (due to its low battery), it does not participate in the auctioning process. only after exchanging obtained processing scores for re-charging battery station times can the discharged agent participate in the bidding process. thus, it is imperative for agents to have sufficient battery capacities to complete tasks. every simulated case has two sub-parts: (i) each agent bids the truthful valuation that is estimated – this is an estimate of the line of sight distance needed to move to the task location and corresponding battery usage (ii) some agents provide erroneous bids – under/overestimating the tasks so as to gain a foothold on the auction. it is the goal of the mechanism design to study and analyse varied situations that can occur in industry 4.0 autonomous task auctions. 6.1. case 1: homogeneous agent capacities – individual task bids. the first case considered is with homogeneous agent task capacities. the agents bid individually for all tasks, resulting in a total of m× n bids. fig. 2 (a)(b) show the final scores of 10 agents after 50 iterations of task bids. when all agents provide accurate bids, the final scores of all agents are uniformly distributed, and the difference between min-median-max agent’s cumulative scores are also uniformly distributed. on the other hand, in fig. 2 (c)(d) when there are 5 agents providing erroneous estimates. we notice that there is a clear separation in agent scores – the agents who provide erroneous estimates have a relatively lower score after 50 iterations. this clearly demonstrates the efficacy of the vcg mechanism – agents have an incentive to provide correct (truthful) estimates in order to obtain better scores. 6.2. case 2: heterogeneous agent capacities – individual task bids. in this case, we introduce heterogeneous tasks – there are two types of tasks, light-weight and heavy-weight. the agents are also divided into types one who can perform only light-weight tasks and the others who can do both. we consider that the first five agents can do only lightweight tasks, and others that can do both. we can see in fig. 3, the mechanism ensures that the agents who can do both tasks receive superior scores compared to agents who do less tasks. 6.3. case 3: homogeneous agents bids for combinatorial subsets of items. we now introduce bidding for a combinatorial subset of tasks. there are at total of m available tasks resulting in 2m−1 non empty subsets of tasks. for each agent we randomly choose 5 possible subsets, and make the agent bid for it. the vcg mechanism described in section 5 determines the winner. as seen in fig. 4 (a)(b), the total score of all agents provided due to the composite nature of bids rises, when compared to fig. 2. we also notice similar results when agents provide erroneous estimates in fig. 4 (c)(d), with overbidding agents provided lower scores. 6.4. case 4: erroneous estimates with collusion. there are scenarios where agents collude together to provide erroneous estimates [5]. this is akin to human agents inflating the market with higher rates for lower level of services. we see this in fig. 5, wherein differences between cases where there is accurate bidding vs. collusion – this implies that the the auctioneer has to pay more scores for similar tasks. by colluding, the agents 9 eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e2 ajay kattepur, sourav khemkha (a) final score of all agents. (b) max-median-min score. (c) final score of all agents. (d) max-median-min score. figure 2. homogeneous agent bidders with accurate estimates (a)(b) and erroneous estimates of 5 agents (c)(d). (a) final score of all agents. (b) max-median-min score. figure 3. heterogeneous agents with accurate estimates. receive higher scores for task, thus enabling them to recharge their batteries in order to prevent such a situation, we can set an upper-bound on the bidding value, and dismiss bids having a value more than the upper bound. an upperbound for a particular task could be calculated by taking the maximum distance from all the four corners of the map grid – any accurate estimate of the task should not cross this bound ub. while ub might not be a tight upper-bound, it should be reasonable enough to detect if all of them are colluding. we simulate the effect of three upper bounds in fig. 6 – ub, ub × (1 + x), ub × (1− x) where x is a random variable taken from a uniform distribution with mean 0 and standard deviation 1. fig. 6 simulates the failure rate (number of tasks that were not allocated) when 30% agent lie (provide erroneous estimates), 70% agent lie and all agents lie. fig. 6 demonstrates that an upper-bound of ub or ub × (1 + x) (optimistic values) may be preferable, as the pessimistic upper bound of ub × (1− x), that produces a high failure rate irrespective of the number of colluding agents. fig. ?? summarises the findings of the simulated cases under various mechanism design schemes. while the scores may vary based on the task distributions and rewards, the general trend may be applied to multiple use cases involving combinations of multiple agents in an auction setting. in summary, revisiting the principal contributions of the paper: 1. porting the industry 4.0 autonomous agent task allocation problem into a game theoretic mechanism formulation. the general structure of mechanism auctions have been described in section 4 with specific instances of industry 4.0 multi-robot task allocation covered in section 5. 10 eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e2 aspects of mechanism design for industry 4.0 multi-robot task auctioning (a) final score of all agents. (b) max-median-min score. (c) final score of all agents. (d) max-median-min score. figure 4. composite bids with accurate estimates (a)(b) and erroneous estimates of 5 agents (c)(d). (a) accurate estimates. (b) collusion of erroneous estimates. figure 5. final scores of agents. (a) upper-bound is ub. (b) upper-bound is ub × (1 + x). (c) upper-bound is ub × (1− x). figure 6. cumulative failure rates with varied upper-bounds of bids. 2. evaluating the use of vcg auctioning mechanism designs for combinatorial auctions in cooperative tasks. this has been evaluated in the simulations in section 6. 3. consider auctions under multiple scenarios with homogeneous/heterogeneous agents, single/combinatorial tasks and truthful/erroneous bids. figures 2 to 6 demonstrate the efficacy of the technique under a variety of scenarios. 11 eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e2 ajay kattepur, sourav khemkha figure 7. findings for various simulations on combinatorial task auctions. such a systematic evaluation of mechanism design theory would prove useful across multiple industry 4.0 robotic deployments. 7. conclusions the advent of industry 4.0 automation necessitates intelligent, autonomous and collaborative robotic agents. specially in task allocation amongst collaborative agents, there is a need to move away from centralized task allocation to decentralized multi-agent coordination. this is specifically needed when vendors are outsourced to manage specialized robotic agents. in this paper, we have made use of combinatorial auctioning mechanisms to allocate tasks to autonomous robotic agents. to ensure fairness in the auctioning mechanism despite heterogeneity, erroneous bidding estimates, agent collusion or combinatorial bids, we utilize the vickeryclarkes-groves (vcg) mechanism. these aspects are demonstrated over a realistic case study in industry 4.0 warehouses, where the use of appropriate mechanisms ensures appropriate allocation of warehouse pickup– delivery tasks. such a model for mechanism design with combinatorial auctions would prove useful across a host of deployments involving multiple autonomous robots. references [1] m. hermann, t. pentek & b. otto, “design principles for industrie 4.0 scenarios”, 49th hawaii intl. conf. on system sciences, 2016. [2] s. greengard, “the internet of things”, mit, 2015. [3] m. jackson, “mechanism theory”, optimization and operations research, encyclopedia of life support systems, oxford uk, 2003. [4] n. nisan, “algorithmic mechanism design: through the lens of multiunit auctions”, handbook of game theory with economic applications, vol. 4, pp. 477–515, 2015. [5] y. narahari, “game theory and mechanism design”, iisc press and the world scientific publishing, 2014. [6] p. wurman, r. d’andrea & m. mountz, “coordinating hundreds of cooperative, autonomous vehicles in warehouses”, aaai artificial intelligence mag., vol. 29, no. 1, pp. 9–19, 2008. [7] y. shoham & k. leyton-brown, “multiagent systems: algorithmic, game-theoretic, and logical foundations”, cambridge university press, 2009. [8] n. nisan, “bidding and allocation in combinatorial auctions”, hebrew university, 2000. [9] w. elmaghraby & p. keskinocak, “combinatorial auctions in procurement”, georgia tech, 2002. [10] a. lam, “combinatorial auction-based pricing for multi-tenant autonomous vehicle public transportation system”, ieee transactions on intelligent transportation systems, vol. 17, no. 3, 2016. [11] r. dash, n. jennings & d. parkes, “computationalmechanism design: a call to arms”, ieee intelligent 12 eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e2 aspects of mechanism design for industry 4.0 multi-robot task auctioning systems, vol. 3, 2003. [12] j. bartholdi & s. hackman, “warehouse and distribution science”, the supply chain and logistics institute, georgia institute of technology, 2016. [13] m. huebscher & j. mccann, “a survey of autonomic computing – degrees, models, and applications”, acm computing surveys, vol. 40, no. 3, 2008. [14] f. faniyi, p. r. lewis, r. bahsoon & x. yao, “architecting self-aware software systems”, ieee/ifip conf. on software architecture, 2014. [15] g. hu, w. tay & y. wen, “cloud robotics: architecture, challenges and applications”, ieee network, vol. 26, no. 3, pp. 21–28, 2012. [16] s. wang, j. wan, d. zhang, d. li & c. zhang, “towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination”, computer networks, vol. 101, 2016. [17] f. basile, p. chiacchio and e. di marino, “an auction-based approach for the coordination of vehicles in automated warehouse systems”, ieee international conference on service operations and logistics, and informatics (soli), 2017. [18] a. kattepur, h. kumar rath, a. simha and a. mukherjee, “distributed optimization in multi-agent robotics for industry 4.0 warehouses”, proceedings of the 33rd annual acm symposium on applied computing , 2018. [19] s. russell & p. norvig, “artificial intelligence: a modern approach”, pearson, 2015. [20] m. hifi, m. michrafy & a. sbihi, “heuristic algorithms for the multiple-choice multidimensional knapsack problem”, j. of the operational research society, vol. 55, no. 12, pp. 1323-1332, 2004. [21] marin lujak, alberto fernandez & eva onaindia, “spillover algorithm: a decentralised coordination approach for multi-robot production planning in open shared factories”, robotics and computer-integrated manufacturing, vol. 70, 2021. [22] c. amato, “decision-making under uncertainty in multi-agent and multi-robot systems: planning and learning”, twenty-seventh international joint conference on artificial intelligence, 2018. [23] h. hu, x. jia, k. liu and b. sun, “self-adaptive traffic control model with behavior trees and reinforcement learning for agv in industry 4.0”, ieee transactions on industrial informatics, 2021. 13 eai endorsed transactions on smart cities 10 2021 03 2022 | volume 6 | issue 17 | e2 1 introduction 2 related work 2.1 mechanism designs and auctions 2.2 industry 4.0 automation 3 automated task procurement process 3.1 intelligent agents 3.2 industry 4.0 warehouse tasks 4 mechanism design and auctions 4.1 combinatorial task auctions 4.2 mechanism design 5 industry 4.0 automation task auctions 5.1 task auctions 5.2 allocation of the winners 5.3 winner scores 6 simulation results 6.1 case 1: homogeneous agent capacities – individual task bids. 6.2 case 2: heterogeneous agent capacities – individual task bids. 6.3 case 3: homogeneous agents bids for combinatorial subsets of items. 6.4 case 4: erroneous estimates with collusion. 7 conclusions legeral-aise2015 an open agent-based model to simulate the effect of wom marketing campaigns poster paul leger manuela lópez carmen hidalgo-alcázar hiroaki fukuda escuela de ciencias empresariales, universidad católica del norte, chile shibaura institute of technology, japan {pleger, mlopezp, mchidalgo}@ucn.cl hiroaki@shibaura-it.ac.jp abstract word-of-mouth (wom) is the opinion of consumers about a product. there is currently a clear trend in the use of wom to diffuse information about a new product, known as wom marketing campaigns. marketing researchers are studying the impact of the different types of these campaigns has. the difficulty in getting data and isolating the effect that is analyzed limits the research of marketers in this topic. lastly, some simulation models based on agents have overcome previous difficulty. however, these models are ad-hoc and specific solutions for every study. this poster proposes an open implementation of an agent-based model to simulate different scenarios of wom marketing campaigns. through customizations, this proposal will allow marketing researchers to test wom marketing campaigns in different scenarios. categories and subject descriptors d.3.3 [programming languages]: language constructs and features; i.2.0 [artificial intelligence]: general; j.1.6 [computer applications] computer applications marketing. general terms languages, design. keywords word-of-mouth, agent-based models, open implementations. 1. introduction before purchasing a product or service, consumers usually ask their family or friends, or even consult other consumers’ opinions. in marketing, these opinions are known as word of mouth (wom), which has become the most influential and credible information source for consumers [1]. hence, companies are interested in using wom as a new communication tool to influence consumers’ decisions [2]. using the internet or through an offline channel, companies carry out wom marketing campaigns: give a message to a set of consumers (a.k.a. seeds) to spread the word about a product to other consumers [2]. the goal of these campaigns is to reach a fast and high diffusion of a message. figure 1. agent-based model components. in the state-of-the-art, we can find studies that have analyzed what message characteristics and type of seeds affect consumers’ intention to transmit a message in a network [2][3][4]. other studies have examined the reasons why a message has been highly diffused [5]. unfortunately, each study requires collecting a large amount of data from social network sites such as facebook or many questionnaires. in addition, it is difficult to isolate the effect that we would like to analyze by using the prior techniques. to overcome these difficulties, a simulation model based on agents can be used [6], which basically simulates the diffusion for a wom campaign. in this campaign a message is given to some consumers (agents), who make the decision whether spreading the message to their contacts or not. some simulation models have been proposed [6][7][8], specifically tailored to fit particular characteristics of a campaign, where it is not possible to customize these characteristics. thereby, for each new campaign, developers must a) modify in contorted ways an existing model or b) implement a new agent-based simulation model from scratch; bringing a slow development and prone-error implementations. this paper proposes omc, an open implementation [9] of an agent-based simulation model to measure the effect of a wom marketing campaign. with simple configurations or code extensions, omc will allow developers to instantiate existing models or create new ones that fit particular and unforeseen characteristics of a campaign. in omc, developers will be able to customize strategies in messages, seeds, network, and reporting outputs of a wom marketing campaign. 2. background we start this section discussing each component of a wom marketing campaign, and then we briefly explain how to use agent-based models to simulate these campaigns. 2.1 wom marketing campaign components to develop a successful campaign, this company has to make decisions on the following components: network. a campaign must work through a channel. the channel can be online (e.g., facebook) or offline. this channel will determine the network (with its features) in which the campaign will work. message. a message can consist of only information (text, url links, images, videos) or a product with the aim of spreading the word about it. companies can also give an incentive to encourage consumers in wom. recent research has examined the agent-based model components : action of a consumer : consumer (agent) bict 2015, december 03-05, new york city, united states copyright © 2016 icst doi 10.4108/eai.3-12-2015.2262533 characteristics that a message should have in order to be much diffused [5]. seeds. companies have a different number of seeds available. these seeds can have different characteristics: hubs (wellconnected consumers), opinion leaders (influential consumers), or bridges (connectors of two otherwise unconnected parts of a network) [3]. 2.2 agent-based model an agent-based simulation model simulates aggregate consequences based on local interactions between individual members of a population [10]. this kind of model consists of an environment, where a set of agents are in one of a finite number of possible states, updated in discrete time steps according to local interaction rules. figure 1 illustrates the main components of an agent-based simulation model: environment. the container where agents interact with others is the environment. depending on the scenario, the environment can simulate an online network (e.g., social network site, networks of email contacts) or offline network (e.g., neighbors of a city). agents. apart of internal states, agents have different properties and behaviors. for example, a type of agent can have a higher influence over other agent. action. using a set of local rules, agents take actions that potentially affect other agents in each discrete time step. for example, an agent can take the action of (re)sending a message. a variety of agent-based models have been proposed to simulate wom marketing campaigns [6][8]. each model sets up previous components to fit particular characteristics of a campaign. 3. problem statement the black box principle (expose the functionality but hide the implementation of a program) offers benefits like reuse, location of changes, and understandability. however, the application of this principle can bring issues of adaptability, performance, and reuse in unforeseen scenarios of a program. as a consequence, developers have to “code around” the program or end up creating an entirely different version of the same program [9]. existing implementations of agent-based models to simulate wom marketing campaigns follow (in an ad hoc manner) the black box principle. thereby, for each campaign with different characteristics, developers must “code around” existing models in contorted ways or create a new version from scratch. as a consequence, the development of these models becomes slow development and prone-error. 4. proposal this paper proposes omc, an agent-based model to simulate wom marketing campaigns that follows open implementation guidelines [9]. omc will allow developers to customize crucial components used to simulate these campaigns, and at the same time, still hiding details of its implementation. as agent-based model, we concretely propose using cellular automata (ca) [10] because its neighborhood concept (direct contact of a consumer in omc) allows an agent to make a decision only considering its neighbors. in addition, ca has been used in simulations of complex networks [11]. figure 2 shows a big picture the core open points of omc. in this figure, we can see that this proposal provides a user and metainterface. the user interface allows developers to select one of available strategies for message, seeds, network, and reporting outputs. the meta-interface offers the opportunity to customize and add strategies for these four components of a wom marketing campaign. as an example of adding a strategy, consider a new type of seed: fringe (a consumer with few connections) [3]. using the meta-interface, developers, for example, can define the average of connections of a fridge seed and its behavior when it receives a message. 5. plan the construction of omc depends on two tracks. first, we will study the literature in marketing to collect other crucial points that should be open in omc. second, we will define abstractions for the user and meta-interface. for the user interface, we will probably construct domain-specific abstractions (or –languages) according to the marketing concepts. instead, the meta-interface will use the full power of a turing-complete language (e.g., objects, first-class functions). among other languages, the scala language brings together needs of both interfaces because of its flexibility, expressiveness, and meta-programming power to define and create new abstractions. we plan to validate it through the emulation of some of existing agent-based models used to simulate wom marketing campaigns. references [1] j. arndt. role of product-related conversations in the diffusion of a new product. journal of marketing research, 4(3), 291-295, 1967. [2] r.v. kozinets, k. de valck, a.c. wojnicki, and s.j.s wilner. networked narratives: understanding word-of-mouth marketing in online communities. journal of marketing, 74(2), 71-89, 2010. [3] o. hinz, b. skiera, c. barrot, and j.u. becker. seeding strategies for viral marketing: an empirical comparison. journal of marketing, 75 (6), 55-71, 2011. [4] j. e. phelps, r. lewis, l. mobilio, d. perry, and d. raman. viral marketing or electronic word-of-mouth advertising: examining consumer responses and motivations to pass along email. journal of advertising research, 44(4), 333348, 2004. [5] k. swani, b. p. brown, and g. r. milne. should tweets differ for b2b and b2c? an analysis of fortune 500 companies' twitter communications. industrial marketing management, 43(5), 873-881, 2014. [6] s. delre, w. jager, t.h.a. bijmolt, and m. a. janssen. will it spread or not? the effects of social influences and network topology on innovation diffusion. journal of product innovation and management, 27(2), 267-282, 2010. [7] j. goldenberg, b. libai, and e. muller. talk of the network: a complex systems look at the underlying process of word-of-mouth. marketing letters, 12(3), 211-223, 2001. [8] b. libai, e. muller, and r. peres. decomposing the value of word-of-mouth seeding programs: acceleration versus expansion. journal of marketing research, 50(2), 161-176, 2013. [9] g. kiczales, j. lamping, g. murphy, c. v. lopes, c. maeda, and a. mendhekar. open implementation design guidelines. proceedings of the 1997 international conference on at the software engineering, 481–490, 1997. [10] j. von neumann, theory of self-reproducing automata. (a. w. burks, ed.). champaign, il, usa: university of illinois press, 1966. [11] d. smith, j. onnela, c. fan, m. fricker, and n. johnson. network automata: coupling structure and function in dynamic networks. advances in complex systems, 14(3), 317-339, 2011. figure 2. potential open points of omc. message seeds network user interface: selecting strategy for meta interface: adding strategy for message seeds network diffusion & acceleration ratio of a message reporting reporting spatio-temporal prediction of air quality using distance based interpolation and deep learning techniques spatio-temporal prediction of air quality using distance based interpolation and deep learning techniques k. krishna rani samal1,∗, korra sathya babu1, santos kumar das1 1national institute of technology, rourkela, india abstract the harmful impact of air pollution has drawn raising concerns from ordinary citizens, researchers, policymakers, and smart city users. it is of great importance to identify air pollution levels at the spatial resolution on time so that its negative impact on human health and environment can be minimized. this paper proposed the cnn-bilstm-idw model, which aims to predict and spatially analyze the pollutant level in the study area in advance using past observations. the neural network-based convolutional bidirectional long short-term memory (cnn-bilstm) network is employed to perform time series prediction over the next four weeks. inverse distance weighting (idw) is utilized to perform spatial prediction. the proposed cnnbilstm-idw model provides almost 16% better prediction performance than the ordinary idw method, which fails to predict spatial prediction at a high temporal period. the results of the presented comparative analysis signify the efficiency of the proposed model. received on 20 june 2020; accepted on 29 november 2020; published on 15 january 2021 keywords: air quality, deep learning, lstm, inverse distance weighting, spatio-temporal prediction copyright © 2021 k.krishna rani samal et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.15-1-2021.168139 1. introduction air pollution has become a severe problem for many developing countries in the world. india is one of them (brauer et al. 2019; pant, guttikunda, and peltier 2016). with the rapid growth of urbanization, global consumption of fossil fuels, and oil, air pollution can cause significant health issues and affect human body parts severely. high exposure to air pollutants and other gases can cause a severe asthma attack and many more diseases. due to the poor quality of atmospheric air, people are more vulnerable to suffering from asthma, lung cancer, and respiratory infections. commonly seen air pollutants such as pm10, pm2.5, so2, no2 and o3 are more responsible for heart attack, lung diseases, and respiratory problems. million of people are dying worldwide every year due to this type of disease. air quality in many indian cities failed to obey many international and national standards and cpcb (beig et al. 2020) effective pollution control ∗corresponding author. email: 517cs6019@nitrklac.in strategies. according to the ncap report, 43 smart cities of india are falling under 102 nonattainment cities of the country. more than half of the country’s population is exposed to particle matter, which exceeds the permissible limits. recent global air pollution research studies say that almost 600000 premature death per year occurs in india due to ambient air pollution level (hama et al. 2020). air pollution control in india has become challenging due to the high impact of meteorological factors and traffic emission (sharma, kharol, and badarinath 2010), which is very difficult to analyze. among all the polluted cities in india, odisha has six nonattainment cities. it has been observed seriously that many people of odisha are suffering from chronic diseases due to reduced air quality levels as it has become one of the polluted states in india. from a descriptive statistical analysis of health care data of this state, it is found that 11951 the number of females and 8454 males per 10000 population of khordha district affected by acute illness during 2012-2013 caused by air pollution. moreover, puri, jagatsinghapur, khorda, 1 eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e4 http://creativecommons.org/licenses/by/3.0/ mailto:<517cs6019@nitrklac.in> k.krishna rani samal et al. nayagarh, cuttack district people are mostly affected by asthma disease, whose primary source is environmental air pollution (samal, babu, santosh kumar das, et al. 2019). therefore, it became necessary to predict the air pollution boundaries and its spatial distribution to regulate it. concerning the severe negative impact of air pollution, the government has taken several smart initiatives, also working with different research institutions to take essential steps against ambient air pollution levels. the government has also developed many air pollution monitoring stations to collect air quality data, which can be utilized to forecast air pollution levels for the next hour, day, or week. the forecasting result provides timely information to take necessary prevention in advance. thus air quality modeling and monitoring can help to mitigate the impact of air pollution. several techniques have implemented to predict air pollution, i.e., deterministic, statistical, machine learning, and deep learning models. these are the widely used techniques for air quality prediction. commonly used deterministic methods are weather research and forecasting models (wrf) (saide et al. 2011), nested air quality prediction modeling system (naqpms) (z. wang et al. 2001). getting prediction results of these methods are expensive. these methods utilize the default parameters, so prediction results are also inappropriate in realtime scenarios. statistical models are another kind of prediction model which overcomes the limitation of deterministic methods by utilizing a large amount of observed dataset. statistical models such as arima (yenidoğan et al. 2018), sarima (samal, babu, santosh kumar das, et al. 2019; voynikova et al. 2015; m. h. lee et al. 2012; n.-u. lee et al. 2018), general additive models (gams), geographically weighted regression and multi-layer regression (mlr) (mckendry 2002) have been utilized in air quality prediction. these statistical models are based on data stationarity and data linearity. these models assume the linear relationship between the observed and predicted value and incapable of handling data nonstationarity. so these statistical models have limited predicted performance. to address these problems, researchers and policymakers adopted machine learning models such as support vector machine, random forest (zamani joharestani et al. 2019), artificial neural network (ann) (elangasinghe et al. 2014), fuzzy neural network (zhou, w. li, and qiao 2017; zahedi et al. 2014), linear regression, and xgboost (pan 2018; zamani joharestani et al. 2019). feed forward neural networkbased ann has shown better air quality prediction performance. though these methods have shown better accuracy in air quality prediction, these shallow neural network models fail to analyze the correlation among features of a multivariate air pollution dataset. the time series pollution dataset has long term dependency among all features. with the rapid development of artificial intelligence techniques, machine learning models no longer remain as the state of the art models. several researchers have conducted air quality modeling using deep learning techniques and have proven better prediction models than machine learning in terms of temporal analysis of the air pollution dataset. deep learning models have shown better performance in sequential modeling, human detection, medical image classification, and many more applications. deep learning models, i.e., recurrent neural network (rnn), lstm, gated recurrent unit (gru) (du et al. 2019) models, have also played an essential role in air quality prediction. few researchers added a convolutional neural network (cnn) layer with the shallow, deep learning models to capture the spatial features in the available time-series dataset, which give better prediction performance by analyzing both the spatial and temporal characteristics. most of the existing prediction models predict air pollution levels for the next hours for a particular site. predicting air pollution levels for the entire study area for a long term period can add an advantage to get better air pollution prediction results. usually, air pollution prediction performance for a long term period gives lower accuracy than for the short term period. this might be due to the small number of samples to perform long term air quality prediction. therefore, it is essential to develop air pollution prediction models that can effectively perform air pollution prediction for the entire study area at a more significant time resolution. to address this limitation, the current research study developed a methodology framework that follows a deep learning-based cnn-bilstm layer for feature analysis and time series prediction. on the top of the cnn-bilstm layer, the distance-based inverse distance weighting interpolation layer is developed to perform spatial prediction for the entire study area at a higher temporal resolution. so, predicting the spatial variability for the next few days will surely help to ensure public safety. following the introduction, the rest is organized as follows. section 2 represented related work. section 3 and section 4 include problem statements and study areas, respectively. section 5 and section 6 describes the proposed methodologies framework and results of the implemented experiments. section 7 consists of the conclusion part of this research paper. 2. related works it is unreasonable and cost-effective to establish air quality monitoring stations to analyze air pollution levels at each corner of the study area. so, it has become a crucial problem to identify the spatial distribution of 2 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e4 spatio-temporal prediction of air quality using distance based interpolation and deep learning techniques air quality level and predicts its value for the entire study area. to overcome this issue, the government has launched satellites to monitor the air pollution level for the entire area, which can also provide a full mapping of atmospheric air pollution levels (boys et al. 2014; s. chowdhury et al. 2019). much research has been conducted to predict air pollution levels using satellitederived remote sensing images. though satellite can capture the overall air pollution level for the entire study area, it can not capture a particular location air pollution level all the time. the captured remote sensing images are also blurred in nature due to cloud influence and movable satellites. therefore, identify the spatial distribution of air pollution levels could be limited due to satellite-derived air pollution data. considering this limitation of air quality monitoring using satellite data, few researchers experimented with statistical spatial prediction models to analyze air pollution levels spatially (gulliver et al. 2011). the spatial prediction model handles missing values of air pollution data obtained due to unavailable monitoring stations in a particular location. the spatial prediction model includes several deterministic models like inverse distance weighting (idw) and geostatistics models like ordinary kriging (ok) (feng et al. 2015; contreras-ochando and ferri 2016), simple kriging (cressie 1990), universal kriging (vorapracha et al. 2015), and empirical bayesian kriging (ebk) models (gunarathna, kumari, and nirmanee 2016). these models are efficient enough to predict air pollution levels for each monitoring station and also for unmeasured locations (cressie 1990) but these models have limited prediction performance due to default predefined parameter settings. to overcome these types of limitations of spatial prediction models, recently, many research studies have adopted machine learning techniques for spatial prediction of air quality data, such as radial basis function (rbf) (zou et al. 2015) and artificial neural network (ann) (nevtipilova et al. 2014). but their prediction accuracy could be limited due to lack of temporal analysis. due to the absence of temporal parameter analysis, these models can not predict the spatial distribution of air pollution for different period i.e., for short term and long term periods. though the discussed models are efficient enough to predict the spatial distribution of pollutants for the current time, not for the future, these are not so useful to make proper decisions and safety measures in advance. so, it has of great importance of temporal modeling for air quality prediction. to analyze the temporal component of air pollution data set, several machine learning based uni-variate air quality prediction models adopted. linear regression, support vector machine (svm) (suykens and vandewalle 1999; j. wang, niu, and r. wang 2017; shaban, kadri, and rezk 2016), random forest (rf) (zhu et al. 2018), decision tree (dt) (safavian and landgrebe 1991), xgboost, multi-layer perceptron (mlp) are the mostly used univariate time series prediction models. uni-variate prediction models failed to analyze the temporal and spatial components simultaneously. these univariate models also do not support correlation analysis among meteorological factors e.g., atmospheric temperature, rainfall, wind speed (ws), wind direction (wd), relative humidity (rh) and air pollution. to get rid of this issue, deep learning techniques evolved with the increasing demand of artificial intelligence techniques. initially, deep learning-based artificial neural network (ann) experimented for air quality prediction. ann was originated in the 1970s. usually, it has one input, one output, and multiple hidden states. in ann, the weight calculation of input data is treated as neurons for the next layer. however, when it comes to handling time series data set, the ann network is unable to handle longer sequence data, and can not relate the current and future data with historical data. to resolve these issues, research scholars developed a recurrent neural network (rnn) (fan et al. 2017), which is based on the ann network. it takes the output of the first layer as input to the next layer, so it is able to transfer weight as a neuron. however, when it comes to dealing with more extended sequential data, it can not deal with them. as sequential time series air pollution data has a longer dependency on past observation due to effect meteorological factors. it is better to use a model that can deal with this type of issue. but rnn can not capture the long term dependency of long sequential air pollution data. it is also very challenging to train the rnn model due to gradient vanishing and exploding issues. to address these problems, hochreiter proposed lstm model (fu, z. zhang, and l. li 2016; b. wang, kong, and guan 2019) in 1997, and kyunghyun developed gated recurrent unit (gru) (fu, z. zhang, and l. li 2016; tao et al. 2019) network to handle long term dependency in sequential time series data in 2014. though the gru model requires less parameter and less time to train, lstm is proved as a more accurate prediction model for longer sequential data. it is also seen that a combination of multiple models has better prediction performance than shallow prediction models. chioujye et al. (huang and kuo 2018) presented a spatiotemporal cnn-lstm model to estimate air quality prediction level, which can capture both spatial and temporal features available in time series pollution dataset. it can also capture long term dependency on the air pollution dataset. it combined the wind speed, rainfall, and pm2.5 concentration information to train the model for air pollution prediction. haofei xie et al. (h. xie et al. 2019) developed the cnn-gru model , which can automatically extract the spatiotemporal 3 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e4 k.krishna rani samal et al. components of multidimensional and multi-station data. it also analyzes the impact of meteorological factors on air quality concentration levels for short term air pollution prediction. despite the memory capacity, the self-learning ability of neural networks, these models failed to capture the dependency of historical pollution level and the supporting information from nearby monitoring stations. therefore, unable to analyze the temporal trend and spatial correlation simultaneously. based on the above survey, the present work tried to predict air pollution levels at a high spatial and temporal resolution without using real-time sensors everywhere of the study area to mitigate the limitation of existing work and take necessary preventive action against the dangerous condition of the air pollution. the main contribution of this research paper can be summarized as follows, • traditional interpolation techniques support spatial prediction for the present time. in contrast, the cnn-bilstm-idw model utilized past information to predict the spatial distribution of air quality for the future at better accuracy. • the cnn-bilstm-idw model can effectively perform spatial prediction of pm10 level over a long period, i.e., for the next four weeks. • the proposed spatial-temporal prediction method can effectively solve data imputation problems for air quality modeling by recovering missing attributes values. • arcgis online is utilized to develop mobile and web applications to access timely information. 3. problem statement much of the pollution data available for different locations are sparse. hence, there is a requirement for predicting continuous data from the available sparse dataset. in order to predict the interpolated surface with continuous pollution levels from variable data of different geolocations, the proper data analysis should be done with the efficient prediction model. the mathematical formulation of spatial interpolation can be expressed as follows: estimate the value of regionalized variable zi , {zi ∈ rn|i = 1, 2, 3.....n }, at discrete points mi = {(x1 i , y 1 i ), (x2 i , y 2 i ), ..(xdi , y d i )}, {mi ∈ r|i = 1, 2, 3...n } by considering n number of different existing neighborhood point values inside searching neighborhood area (r) with d-dimensional space. weight (w) assignment will be done based on their distance from neighborhood points or autocorrelation among those points which signifies the influence of neighborhood points in estimation of a particular point value. weight assignment is treated as function (f ) such that, f : rn → r f (mi) = zi 4. study area odisha, one of the polluted state of india (tripathy and dash 2018; nayak and i. r. chowdhury 2018), is selected as the study area for the research activity. it is reported that most of the industrial estate and smart cities of this state do not fulfill the air quality standard decided by the central pollution control board. the state is having very few numbers of continuous air pollution monitoring stations controlled by cpcb. most of the sites are manual air quality monitoring stations that collect air quality data on the daily granularity level. the past observation data includes air quality dataset from 2005 to 2015. the data set contains pm10, pm2.5, so2, no2 air pollutant details with sampling date, and sampling location geographical attributes. it has seen from the analysis that pm10 pollutants have maximum air pollution contribution among all the contaminants in odisha. so pm10 pollutant value is considered for experimental purposes in the study area. the figures are in one-millionth of a gram unit. the dataset includes 31 monitoring sites, but due to a large number of missing values, the research work considered only 16 monitoring sites for evaluation purposes. 5. experimental method to validate the usefulness of the proposed methodology framework, ten years (01.01.2005-28.12.2015) dataset are collected from odisha state pollution control board (odisha 2017, oct 16; samal, babu, and santos kumar das 2020; samal, babu, santosh kumar das, et al. 2019). after data collection, data normalization and linear interpolation techniques are applied in the prepossessing step to get useful information for training the model. 90% of data are used for training purposes, whereas other remaining 10% are utilized for testing purposes. adam and mean squared error are implemented as optimizer and loss function respectively to train the proposed model. each step of the proposed framework is presented in figure 1. each layer of the proposed methodology framework is discussed in the below subsections. 5.1. 1d convnet for feature learning the 1d convnet (o’shea and nash 2015) is usually used for feature learning. it allows us to extract features from inputs and improve data efficiency by reducing data dimensionality. the weight sharing feature of 1d convnet minimizes the number of parameters of the multivariate time series dataset by increasing the 4 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e4 spatio-temporal prediction of air quality using distance based interpolation and deep learning techniques figure 1. the proposed cnn-bilstm-idw architecture. learning of the model. a learned pattern at a particular point of a sequence can be captured at other locations due to the same input transformation at each point. so, the change in the local trend of multivariate features can be determined. after completion of 1d convnet, the max-pooling operation is conducted to extract the maximum value of sub sequences of the dataset further to reduce the dimensionality of the input data source. the cnn layer performs three operations i.e., convolution, activation, and pooling respectively, which can be computed as below (du et al. 2019), cln = ∑ m xl−1 m ∗w l mn + bln (1) xln = relu (cln) (2) xln = flatten(xln) (3) xl+1 o = fcl(w l+1 on x l n + bl+1 o ) (4) the convolution layer can be modeled using equation 1-2 where * , w l mn, bln represent convolution operator, filter and biases respectively. relu function is implemented as an activation function. xl−1 m and cln are the input, output vector to a convolution layer. the proposed architecture used two convolution layer for feature learning; l is used as the involved layer. the output of the preprocessing step is utilized as input to the cnn layer, where the learned representation of each segment is used as input to the next layer to model a hierarchical representation of features. after convolution operation, a flatten layer is added to transfer the hierarchical features representation into a feature vector. then a fully connected layer is added to reduce the dimensionality of the final output feature vector. 5.2. long term temporal modeling the temporal modeling layer’s goal in the proposed architecture is to predict pm10 concentration for the next 28 days in december 2015. the dataset for this particular duration is used as a test set and validates the model by comparing the prediction results of 28 days of december with the test dataset. in the temporal modeling layer, the input is the feature vector extracted from the cnn layer. the output of the cnn layer is treated as an input for long short term memory (lstm) network to conduct temporal modeling of air pollution data. lstm network is a long short term memory network that is suitable for dealing with the longer sequences time series dataset. lstm differs from rnn due to the addition of a processor, which is utilized to judge the usefulness of the information. the structure of this processor is known as a cell. usually, lstm contains three gates in a cell, i.e., input gate, forget gate, and output gate. the forget controls selectively how much information need to forget from the current cell. the output gate computes the output information, i.e., predicted pm10 concentration level. input, output and forget can be implemented by using the following formulas, it = σ (uih(t−1) + wixt + bi) (5) ct = ft � c(t−1) + it � tanh(uch(t−1)) + wcxt + bc) (6) ft = σ (uf h(t−1) + wf xt + bf ) (7) ot = σ (uoh(t−1) + woxt + bo) (8) ht = ot � tanh(ct) (9) where σ is the element-wise activation function. it , ft , ot are the input gate, forget gate and output gate respectively. ct , ht represents cell state and hidden state vectors. ui , uc and uo represents weight metrics for hidden state ht , whereas wi and wc, wo and wf are the weight matrices of other gates. bi , bf , bo are the bias vector for input gate, forget gate and output gate respectively. the basic structure of lstm is presented in figure 2. figure 2. lstm structure this paper utilized the bidirectional lstm (bilstm) model (verma et al. 2018; graves and schmidhuber 5 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e4 k.krishna rani samal et al. 2005; sun et al. 2019), which exhibits bidirectional properties of the lstm network, where both past and future data play an important role in time series analysis. two lstm units stacked over each other in the bilstm model (forward and backward). this model is capable enough to handle long-term dependencies without knowing prior information about past and future data. the stacked lstm layer helps to capture hierarchical features in the temporal domain very efficiently. the output of each bilstm layer fed into a fully connected layer. this is usually a dense presentation. this process continued for each time step. the output of the final timestamp will give the time series prediction results for each monitoring site. so implementing this model could provide better time series prediction accuracy. the basic structure of the bilstm unit is shown in figure 3. figure 3. bilstm structure it propagates the data through both directions i.e., called forward propagation and backward propagation. the forward propagation of time series data in bilstm layer where time t ranges from 1 to t , can be formulated as below, −→ it = σ (−→ui −−−−−→ h(t−1) + −−→wi −→x t + −→ bi ) (10) −→ct = −→ ft � −−−−→c(t−1) + −→ it � tanh(−→uc −−−−−→ h(t−1) ) + −→w c −→xt + −→ bc ) (11) −→ ft = σ (−−→uf −−−−−→ h(t−1) + −−→wf −→xt + −−→ bf ) (12) −→ot = σ (−→uo −−−−−→ h(t−1) + −−→wo −→xt + −→ bo ) (13) −→ ht = −→ot � tanh(−→ct ) (14) the left arrow denotes the forward process. during backward propagation of time series data in bilstm layer time, t ranges from t to 1. the backward propagation operations, represented by the right arrow, can be formulated using equation 15-19. ←− it = σ (←−ui ←−−−−− h(t−1) +←−w i ←−xt + ←− bi ) (15) ←−ct = ←− ft �←−−−−c(t−1) + ←− it � tanh(←−u c ←−−−−− h(t−1) ) +←−−wc←−x t + ←− bc ) (16) ←− f t = σ (←−−uf ←−−−−− h(t−1) +←−−wf ←−x t + ←−− bf ) (17) ←−ot = σ (←−uo ←−−−−− h(t−1) +←−−wo←−x t + ←− bo ) (18) ←− ht =←−ot � tanh(←−c t) (19) the final hidden element ht can computed by using equation 20 ht = −→ ht � ←− ht (20) where −→ ht , ←− ht denote forward out and backward output respectively. 5.3. spatial modeling monitoring air quality concentration level at each corner of a location and implement those data for further analysis to determine the air pollution impact on public health in a particular area are the essential steps in government initiated smart cities. the indian government could establish a few air quality monitoring stations due to the high construction cost of monitoring sites and low government budget. therefore, it is challenging to predict the air quality level at each location of a study area. it arises the necessity of spatial modeling of air pollution for air quality prediction. it helps to trace the harmful effect of pollution over a particular location. identifying the spatial distribution of pollutant concentration for the present time may not be useful all the time; instead, it will be helpful if it can be predicted for the future. hence, the idw layer is added to the top of the cnn-bilstm temporal modeling layer. cnn-bilstm layer predicts air pollution levels for the existing 16 monitoring sites for the next four weeks of december 2015. then the idw layer of the model could predict the spatial distribution of pollutants by utilizing that predicted output of the cnn-bilstm layer. this paper used a distance-based spatial interpolation, idw (bhunia, shit, and maiti 2018; gorai, tchounwou, and mitra 2017; x. xie et al. 2017; contreras and ferri 2016) layer on the top of the temporal prediction layer to get the prediction value of each spatial distribution. it can be formulated as follows: ẑ(st0 ) = ∑n i=0wisti∑n i=0wi (21) 6 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e4 spatio-temporal prediction of air quality using distance based interpolation and deep learning techniques where, ẑ(st0 ) is the predicted value for unsampled point st0 , wisti is the weight function and and sti is the sampled point value. in case of idw, weight is the function of distance and can be estimated as follows: wi = 1 d(st0 , sti ) p (22) where the distance between measured point sti and unmeasured point st0 denoted as d and the power factor as p. as closer points often have similar characteristics in space as per the first law of geography, those neighborhood points have more influence on interpolated point st0 values. the power value signifies the impact of neighborhood points on the interpolated point. the higher the power values, the more is the influence of neighborhood points on unsampled ones. the pseudocode of the cnn-bilstm-idw algorithm is presented in algorithm 1. the first part of the algorithm is meant to perform time series modeling followed by linear interpolation to handle missing values of the dataset. the second part of the algorithm conducts spatial modeling using idw interpolation. algorithm 1 spatio-temporal prediction algorithm for pm10 input: air quality pollutant time series dataset pm = [pm1, pm2.....pmt ], latitude and longitude ( x,y), data sampling time t output: pollutant prediction map initialization: training process of cnn-bilstm model with parameters φ. 1: for 1 ≤ x, y ≤ n do 2: for t = 1 to t do 3: if pm has missing value for duration t then 4: conduct linear interpolation 5: else 6: pmt+d ← (x, y) prediction of pm10 level for n number of monitoring sites by cnnbilstm model. 7: return pmt+d 8: end if 9: end for 10: end for 11: generate spatio-temporal prediction map of pm10 for study area: 12: if (m, n) are the latitude and longitude of nonmonitoring sites then 13: return p̂mt+d m,n ← n∑ x,y=1 w(x, y) ∗ pmt+d x,y 14: else 15: return pmt+d x,y 16: end if 6. results and discussions to evaluate the performance of the cnn-bilstm-idw model, we compared the performance of this model with ordinary idw (ya’acob et al. 2016), exponential kriging (ek) (son, bell, and j.-t. lee 2010), gaussian kriging (gk), spherical kriging (sk) (gong, mattevada, and o’bryant 2014), universal kriging (uk) (son, bell, and j.-t. lee 2010), radial basis function (rbf) (bhunia, shit, and maiti 2018) and empirical bayesian kriging (ebk) (krivoruchko and gribov 2019) models as shown in table 1. root mean square error (rmse) and mean error (me) indicators are utilized to evaluate the performance of the cnn-bilstm-idw model. rmse and me can be calculated using equation 23-24, rmse = √√√ 1 n n∑ i=1 [ ẑ(xi) − z(xi) ]2 (23) me = 1 n n∑ i=1 [ ẑ(xi) − z(xi) ] (24) where, ẑ(xi) is the predicted value at location (xi), z(xi) is the observed value at (xi) and n are the total number of monitoring stations. rmse value of idw, ek, rbf, gk, ebk, sk, uk, cnn-bilstm-idw model reduced (25.94), (24.64), (24.62), (24.48), (22.44), (24.38), (24.37), (21.71) respectively. table 1 shows that the proposed spatio-temporal prediction model has better prediction performance than the other spatial prediction models. table 1. model cross validation method type model rmse me deterministic idw 25.94 4.77 geostatistics ek 24.64 3.73 geostatistics gk 24.48 3.54 geostatistics sk 24.38 3.52 geostatistics uk 24.37 3.52 geostatistics ebk 22.44 3.53 machine learning rbf 24.62 3.80 deep learning cnn-bilstm-idw 21.71 3.50 prediction maps generated by cnn-bilstm-idw for the four weeks of december 2015 are represented in figure 4-7. color scale indicates the variation of air pollution levels over the study area. 7 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e4 k.krishna rani samal et al. figure 4. first-week prediction map. spatial distribution of average pm10 value in the first week of december 2015. figure 5. second-week prediction map. spatial distribution of average pm10 value in the second week of december 2015. figure 6. third-week prediction map. spatial distribution of average pm10 value in the third week of december 2015. figure 7. fourth-week prediction map. spatial distribution of average pm10 value in the fourth week of december 2015. 8 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e4 spatio-temporal prediction of air quality using distance based interpolation and deep learning techniques few conclusions are derived from the above prediction maps of odisha: as presented in figure 4-7, the eastern part of odisha is predicted as a highly polluted area during december 2015, where pm10 concentration ranges from 67132(µg/m3). that might be due to improper human activity, biomass burning, coal fields, and road transport emissions. it can be seen that the last week of december has the highest concentration level than the previous weeks. the results prove that the cnnbilstm-idw model predicts air pollution levels not only for the current time but also for the future and the entire area by solving data imputation issues. it can be essential information for smart city users to take necessary preventive steps. figure 8-10 presents the user-friendly designed mobile application and web application to show the spatial prediction map of pm10 at a different period in advance. the spatial prediction maps are generated using the proposed cnn-bilstm-idw model. these user-end applications can be accessed from anywhere to get alert about the air quality level. these user applications are developed by web app builder of arcgis software, which provides location-based service accessibility. these services can also be used to access location information of treatment facilities and emergency services (mbuh et al. 2020). the geoenabled, iot based dynamic end-user applications facilitate the decision-making process by improving situational awareness. 7. conclusion to conclude, this research paper proposed a new methodology framework that combines both deep learning and geostatistical approach to improve spatial prediction accuracy at a larger temporal granularity. the neural network layer improved the temporal prediction accuracy, whereas the idw interpolation layer improved the spatial prediction accuracy in the study area. this research work is conducted using only pm10 pollutant data due to proper data unavailability. analyzing the influence of meteorological and traffic parameters on the ambient air quality could further improve the model prediction performance. in the future, if more data will be available, then using multivariate interpolation technique is expected to improve the prediction results. 8. acknowledgment this research and product development work is financially supported by the ministry of human resource development and ministry of housing and urban affairs, government of india. figure 8. developed a mobile application to present the air pollution spatial prediction map. references beig, gufran et al. 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(2015). “spatial modeling of pm 2.5 concentrations with a multifactoral radial basis function neural network”. in: environmental science and pollution research 22.14, pp. 10395–10404. 12 eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e4 1 introduction 2 related works 3 problem statement 4 study area 5 experimental method 5.1 1d convnet for feature learning 5.2 long term temporal modeling 5.3 spatial modeling 6 results and discussions 7 conclusion 8 acknowledgment blockchain for smart citiesa review eai endorsed transactions on smart cities review article 1 blockchain technology and smart citiesa review shilpi1,*, mohd abdul ahad2 1department of computer engineering, jamia millia islamia, new delhi-110025, india 2department of computer science and engineering, sest, jamia hamdard, new delhi-110062, india abstract blockchain technology can be termed as a revolutionary innovation that has transformed the manner of data sharing by making it more secure and immutable. the existence of a mutual trust model which includes every participating entity makes it a widespread adopted technology in recent years. due to its impeccable application domains the blockchain technology is slowly becoming an essential enabling technology of modern day. smart cities ecosystem is one such domain wherein blockchain is finding numerous application and implementation avenues. due to the diverse nature of devices and heterogeneity of data involved in smart cities ecosystem blockchain is considered an apt technology. in this paper, the current status of “blockchain based smart cities” is discussed. the paper further systematically reviews the various existing proposals, frameworks and architectures which were developed by researchers in order to mitigate the issues and challenges in the implementation of smart cities by utilizing the blockchain innovation. keywords: blockchain, smart city, security, iot received on 29 january 2020, accepted on 26 march 2020, published on 27 march 2020 copyright © 2020 shilpi et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.163846 *corresponding author. email: july23shilpi@gmail.com 1. introduction in recent years, the economic growth and social changes have initiated the largest surge of urbanization around the globe and thus more and more individuals are moving towards urban communities. as of late the “united nations” has anticipated that “86% of developed nations and 64% of the developing nations will be urbanized by 2050” [1]. it has been indicated that more inhabitants stay in urban areas (54%) than provincial zones (46%) and this figure will increase to 66% by 2050 [2]. in order to adapt to these emergencies, urban communities focus on current advancements with a focus to minimize costs, use assets optimally, and make increasingly reasonable and feasible urban conditions.  the widespread adoption of iots and remote interchanges has enabled easier interconnection of gadget networks and uniform transfer of information even from remote areas and difficult terrains. such systems, however, are largely instrumented with open information and thus must be protected against security vulnerabilities [3-4]. in order to overcome these vulnerabilities, data dependent solutions must be created to give protection, trustworthiness, and confidentiality of information. gartner's report gauge that 30% of keen urban community’s social insurance applications will have mechanical technology and innovative machines and 10% of shrewd urban communities will utilize street lamps as the spine for a system of savvy urban communities by 2020 [5]. as of late, blockchain innovation has gained popularity in numerous fields and businesses for example horticulture, digital currency, inventory network and shrewd urban areas and so on. it is also reported that $3.1 trillion will be added to the world economy by 2030 [6].  as per “nelson rosario” [7], the blockchain technology is characterized as a "distributed ledger network using public-key cryptography to cryptographically sign exchanges that are put away on a distributed ledger, with the record comprising of cryptographically connected blocks of exchanges. this cryptographically connected blocks of exchanges structure is known as a blockchain." in simple words, it is a shared dispersed record innovation that “records exchanges”, “understandings”, “agreements”, and “deals” eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e2 http://creativecommons.org/licenses/by/3.0/ mailto:july23shilpi@gmail.com shilpi and mohd abdul ahad 2 [8]. primarily created to aid digital currency, blockchain technology can further be used for a variety of information exchanges using peer to peer networks. the requirement for any central authority between different parties executing budgetary and other information exchanges have been wiped out by blockchain by utilizing a transparent, immutable and a decentralized open record. this open record is a conveyed database that is shared with all the participating entities of the system. it is a sealed, cryptographically verified, and immutable record of the exchanges that at any point occurred among the members. considering the remarkable properties of blockchain which combine changelessness, acceptance, decentralization, and straightforwardness the blockchain promises to provide protection and safety to the information. therefore, the blockchain will aid varied developing applications including keen urban areas like sanitation, agriculture, supply-chain, industries, banking, transportation and the internet of vehicles [9-11]. a typical smart city is an urban framework where several smart prerequisites exist with every service, governance, policies and other information exchanges like a practical administration model of automated traffic management and open vehicle. it is a setting wherein residents can work remotely in almost all chores of events with the utilization of smart arrangements of energy, use of suitable innovation for saving energy and to minimize the ecological effect. the "smart city" idea includes a few parameters that interface with one another, which makes the quest for a precise definition a complex task. as per one definition it is defined as "the savvy use of innovation so as to gather, analyse, procedure, and execute a lot of valuable information legitimately from the previously working urban areas" [9]. the smart city ecosystem can be thought as an umbrella term where several modern day enabling technologies like ict, blockchain, ai, deep learning, machine learning , iot, cloud/edge computing etc are integrated and works in synchronization to provide solutions to the users. these solutions include automation of essential services, governance, smart transportation, smart agriculture and smart habitat. it involves novel energy efficient frameworks and models, smart grids etc [5], [12]. 1.1. manuscript organization the manuscript is divided into 6 sections. section 2 provides the systematic literature review of the recent researcher works. section 3 provides security threats and issues associated with the implementation of blockchain technologies. section 4 highlights the inherent challenges of blockchain based smart city ecosystem. section 5 reviews the existing security proposals for blockchain based smart city adoptions. section 6 summarizes the manuscript and provides the conclusion. it further highlights the future research directions of blockchain based smart city adoptions. 1.2. why blockchain? there are several unprecedented properties of the blockchain technology that makes it an appropriate solution for several critical applications domains like healthcare, transportations, agriculture, education and forecasting etc. some of these properties are given here in figure 1 [13-14]. • transparency: all blockchain trades are crystal clear, which implies an aggregate, obvious and constant record of any activity that exists. • immutable and non repudiation: this means that with blockchain there is no danger of illegitimate extraction and a blockchain agreement can’t be dropped by the sender when it sent and deleted. • speed: affirmations and transactions of blockchain based trades can happen much faster as compared to legacy methods. • secure: inherent security mechanism of blockchain makes it an appropriate solution of performing sensitive transactions in a distributed manner. • scalability and extensibility: the typical architecture of blockchain makes it flexible to extend and scale the existing infrastructure without much difficulty and overhead. • distributed and decentralized: at the core, the blockchain technology is a “distributed ledger” and follows a peer-to -peer architecture and thus eliminating the limitations of typical centralized systems. figure 1. properties of blockchain eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e2 blockchain for smart citiesa review 3 2. related works this section provides some of the recent development in the field of blockchain based smart cities proposals. the authors in [15] proposed a blockchain based mechanism for securely storing data from iot based sensors placed at multiple surroundings of the point of interest. they proposed to use ethereum blockchain and scrum technology for the implementation of their proposal. the authors in [16] provided a review of the existing literature on importance digital identity of the users and methods available for their protections. they primarily highlighted the blockchain based methods and discussed the issues and challenges associated with such systems. the authors in [17] proposed a blockchain based approach for securing and providing a transparent lottery management system. the specifically used “smart contracts and cryptograph blockchain model” in their proposal. in [18] the authors put forth a new “future living framework” based on blockchain technology to provide services and unique codes to the users. the applications domains and challenges associated in integration blockchain with smart living ecosystem is addressed. the authors in [19] proposed to apply blockchain and smart contracts in the real state sector. their proposal provides a secure and privacy preserved means for the financial transactions between landlords and tenants. in [20] the authors proposed to decouple the transaction data from the blockchain headers in order to enhance the transaction speed. the supported the proposal with empirical evaluation using network emulator. the results show the effectiveness of their proposal as compared to existing solutions. the authors in [21] provided the extensive review of researches on blockchain technology applied in smart cities. a comprehensive roadmap of the research was provided including motivation, background and need of the research conducted. finally some future aspects and scope were discussed. in [22], the authors provided privacy persevered svm based data training scheme using blockchain technology. their proposal eliminated the use of third party dependency and thus securing the data in transit. the authors in [23] proposed a lighter and novel security protocol using ethereum blockchain. the primary aim is to minimize the overhead of the network and provide better security. the source of the data origin can be authenticated using ethereum building blocks. the authors in [24] provided a mechanism for smart and sustainable economic services using fog computing and blockchain based storage. their proposed framework was supported with implementation details and results showing the effectiveness of the proposal. the authors in [25] provided a blockchain based mechanism called as “bis” for insurance industries in the smart cities. it uses poc based contract and data sharing mechanism. the primary aim of the proposal was to minimize the delay in processing of request and services of the insurance industries. in [26] the authors proposed a mechanism for sharing the data in a “secured and privacy preserved manner”. the main idea of the proposal is to distribute the blockchain network into multiple channels with each channel having a specific capacity and constrained to process only specific type of data and thus the overall network congestion is distributed to gain performance enhancement. 3. security threats & issues of blockchain technology one most appealing highlights of blockchain innovation is its security component, which depends on distributed consensus and a public ledger. this doesn't imply that it can oppose any sorts of extortion and hacking. in recent years, the blockchain technology has been put to test and several security vulnerabilities were found as shown in figure 2 [27-31]. figure 2. security threats and attacks on blockchain • 51% attack: they are the most regular assault on the blockchain based systems. they basically targets smaller networks and occurs when the hackers controls 51% of the nodes in the whole network. • double spend attack: the “double spend attack” comprises of spending a similar coin twice. • dos and ddos attack: the assaults like “denial of service (dos) or distributed dos” aim at flooding the network with fake requests such that the legitimate requests cannot be serviced by the network. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e2 shilpi and mohd abdul ahad 4 • man-in-the-middle attack: the aim of this attack is to hack the communication between two users and illegitimately relay spurious communication by altering the original contents. • eclipse attack: these attacks occur when the hackers tricks the nodes to chose the peer from the malicious nodes instead of legitimate nodes. • dao attack: categorized as one of the most devastating attacks in history of blockchain. here a bug was identified in the code and was used to illegitimately withdraw the money from users account. • sybil attack: here the attackers flood the network with malicious nodes in order to trick the legitimate nodes to choose peers. this attack is generally used to target a group of user or the complete network as a whole. as discussed in [2], other significant dangers to smart urban communities are: • threats to availability: this includes issues like unapproved and illegitimate asset retention. • threats to integrity: this incorporate unapproved and illegitimate information alteration • threats to confidentiality: it incorporates disclosure of sensitive data or impersonation. • threats to authenticity: it includes unapproved access to assets and sensitive data. • accountability threats: this incorporate forswearing of transmission or gathering of a message by the related substance . moreover, innovation advances with time and consequently new vulnerabilities and security threats are discovered. these newly discovered bugs and threats can further compromise open blockchains initiatives in near future.    the non-appearance of a focal position, the nonexistent stamping element, and subsequently the complete lack of control is an alluring and simultaneously hazardous quirk. numerous “private” and “permissioned” blockchain applications have been developed as of late to counter this. 4. challenges of blockchain based smart city compatibility barriers are the primary potential safety concern that still needs to be addressed. there are several other safety concerns that should still be handled [32], [45-49]. some of them are given below: • the absence of innovations that will have the option to process huge volumes of information. the 5v model of big data constitutes a core element of a smart city model. • use of iot would entail a huge concentration of administrations, software, and associated hubs. each one of these components may uncover the heterogeneity of their usefulness that will inevitably uncover vulnerabilities in security. • one of the biggest problems is the lack of predefined standard benchmarks. the way things are, there is no general security consensus that will be utilized as a rule on the most proficient method to capture, handle, process, and appropriate information. as expressed in [33-36], another set of difficulties include: • relying on a centralized cloud computing frameworks unavoidably acquires dubious latencies and dependencies on third party services. • although the fog/edge processing-based framework can meet the prerequisites raised by delay-sensitive, crucial applications but there is an acute shortage of skilled workforce [34-36]. new difficulties are additionally presented by the disseminated, cross-space highlights, for example, versatility, heterogeneity, and interoperability. a portion of the difficulties in a blockchain based smart city ecosystem addressed in [37] are: • structural versatility: structural adaptability should be addressed when planning the engineering for an integrated smart city. this property allows the construction of a structure when appropriate without requiring critical system design changes. • network data transmission imperatives: concentrated engineering-based arrangements are not fitting because of system transfer speed restrictions. • protection and security: the smart city system gives rise to numerous security and protection concerns and difficulties due to the exponential rise in the number of gadgets connected within the smart city ecosystem. • single point of failures: smart city ecosystem can have a large number of single-point-offailures as a result of heterogeneous nature of participating devices and data models. 5. different proposed security frameworks smart city ecosystem is centred around suitability, computerized administrations, instalments, and conditions, however, it ought to be improved.  various attempts in this area are the development of “open web application security project (owasp)”, “computer emergency response teams (cert)” , “g-cloud” for “cloud computer service provider (ccsp)” etc. [38-40].  security perspectives are talked about by biswas et. al [2], simona ibba et. al [15], theodorou et. al [32] and p.k. sharma [37] in their work. these works have been thought about as it examines the need for a particular security structure.  one such system is made out of four layers [2], [15]: eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e2 blockchain for smart citiesa review 5 • physical layer: smart city devices (e.g. “nest thermostat” and “acer fitbit”) are fitted with sensors and actuators that capture and forwards the information to the upper layers; these devices are helpless against security attacks and vulnerabilities due to lack of encryption and access control instruments [41]. • communication layer: the blockchain mechanism should be coordinated with this layer to provide security and protection to the transmitted information. mechanisms like bittorrent can be utilized for distributed correspondence through ethereum for providing smart agreement functionalities. • database layer: a “distributed ledger” in the blockchain is a kind of “decentralized database” which stores recording in steady progression. there are two distinct kinds of dispersed records practically speaking: i) permission-less and ii) permissioned. it is prescribed to utilize private records to guarantee versatility, execution, and security for constant applications. • interface layer: each layer contains a variety of apps that work together to settle on mutually agreed positive choices. in [32], a specialized methodology on how the innovation fills in rather than the conventional method for transferring and handling information has been introduced. despite the fact that the highlights that make a smart city secure are various, they centred uniquely around those regions that are regarded as critical, for example, information management and circulation, correspondence, protection, verifying outsiders, savvy agreements and conventions (method for dealing with information). in [37], a novel hybrid design by utilizing the quality of developing “software defined networking” and “blockchain advancements” has been discussed to address the difficulties of dynamic network management and security concerns. to guarantee security and protection in the model examined, argon2 based proofof-work plot is presented. the model was re-enacted over a private ethereum blockchain network. the consequence of the assessment shows the adequacy of the proposed model. to take care of the issue of the sensors information storage and the management was discussed in [32]. simona ibba et. al [15] proposed to build up a product dependent on blockchain and to apply the scrum philosophy as a result of its capacities of being adaptable, versatile and iterative system. like in [37], they have utilized the ethereum stage to record estimations landing from the iot system of sensors. lately, the “smart grid decentralization” has become a subject of research expecting to give an option in contrast to focal substances. in [42], the authors proposed a blockchain-based engineering for disseminating the management, control, and approval of interest reaction (dr) programs in low/medium voltage smart grids with a perspective on guaranteeing high unwavering quality and decentralized activity by actualizing identifiable and sealed vitality adaptability exchanges. the network has been demonstrated as a chart of peer nodes that can facilitate through a “blockchain-based framework” to aid “decentralized-energy” demand. a blockchain appropriated record is built and oversaw at the core framework level. the proposed approach was approved using a model actualized in an ethereum stage [15], [37] using appropriate utilization mechanism and creating hints of a few structures from writing informational collections. the outcomes have demonstrated that blockchain-based conveyed request side administration can be utilized for coordinating critical request and creation at shrewd lattice level. the adoption of the “blockchain” will convert the “smart grid” into a “popularity-based network” that never again depends on a central position rather it can take any choice through smart contract rules dynamically. dheeraj nagothu et. al [33] presented a new secure smart reconnaissance framework dependent on “micro-services design” and “blockchain innovation” which is inherently dependent on various levelled edge-haze distributed computing worldview. the ability of consistent improvement and ceaseless conveyance permit a progressively adaptable and versatile reconnaissance framework. to verify the information traded among micro-services, the blockchain enables the administrator to track the information and keep away from information altering. “smart contracts” have computerized the working of blockchain information and it gives the most significant level of information encryption for proficient and secure correspondence. the rising ad hoc system for vehicles using the smart city was inspected in [43] and presented a blockchaindependent circulated concept for the vehicle system to address difficulties. a “block-vn model”, dependent on blockchain arrangements for enabling smart transportation allows an increasingly productive and powerful improvement of the disseminated system of huge-scale vehicles. the block-vn model enables the participating entities (vehicles) to recognize and share their assets in order to create an iov system. 6. conclusion blockchain is a vital component for providing a transparent, secured and privacy preserved information storage and circulation. when it is combined with other enabling technologies it can provide an unprecedented mechanism of information exchange across the network. in addition, different lightweight cryptographic natives ought to be added to increase the degrees of execution of several interconnected nodes. the expense of implementing the execution of a protected smart city ecosystem could be divided into several sub tasks. sklavos and souras [44] provided a model of the classifications of expenses that ought to be considered. although there are several state-of-the-art solutions for realizing the smart city concept, yet a lot of scope is there eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e2 shilpi and mohd abdul ahad 6 for improvement in every aspect of the smart city model. the security of the system and the participating entities being the primary concern that needs to be addressed more holistically. the complex nature of the underlying infrastructural requirements is causing hindrances in the realization of a smart city in true sense. the cost involved and the scarcity of the skilled manpower are the other limiting factors to be considered. finally, it can be concluded that blockchain is an appropriate technology that can be used for providing a secured and privacy preserved mechanism of information exchange across the smart city ecosystem. references [1] merry h. population increase and the smart city. 2018 [available online] https://www. ibm. com/blogs/internetof-things/increased-populationsmart-city. accessed date 12 december 2019. [2] biswas k, muthukkumarasamy v. securing smart cities using blockchain technology. in 2016 ieee 18th international conference on high performance computing and communications; ieee 14th international conference on smart city; ieee 2nd international conference on data science and systems (hpcc/smartcity/dss) 2016 dec 12 (pp. 1392-1393). ieee. [3] madaan n, ahad ma, sastry sm. data integration in iot ecosystem: information linkage as a privacy threat. computer law & security review. 2018 feb 1;34(1):12533. [4] ahad ma, tripathi g, zafar s, doja f. iot data management—security aspects of information linkage in iot systems. in principles of internet of things (iot) ecosystem: insight paradigm 2020 (pp. 439-464). springer, cham. [5] panetta k. smart cities look to the future. 2018. [available online] https://www. gartner. com/smarterwithgartner/smart-cities-look-to-the-future. accessed date. 06 november 2019. [6] j. d. lovelock, et al. “forecast: blockchain business value”, worldwide, 2017-2030, 2018 [7] n. m. rosario, the emerging blockchain patent landscape, 2017 [8] christidis k, devetsikiotis m. blockchains and smart contracts for the internet of things. ieee access. 2016 may 10;4:2292-303. [9] mohanty sp, choppali u, kougianos e. everything you wanted to know about smart cities: the internet of things is the backbone. ieee consumer electronics magazine. 2016 aug 10;5(3):60-70. [10] puthal d, mir zh, filali f, menouar h. cross-layer architecture for congestion control in vehicular ad-hoc networks. in 2013 international conference on connected vehicles and expo (iccve) 2013 dec 2 (pp. 887-892). ieee. [11] pramanik mi, lau ry, demirkan h, azad ma. smart health: big data enabled health paradigm within smart cities. expert systems with applications. 2017 nov 30;87:370-83. [12] ahad ma, biswas r. request-based, secured and energyefficient (rbsee) architecture for handling iot big data. journal of information science. 2019 apr;45(2):227-38. [13] li x, jiang p, chen t, luo x, wen q. a survey on the security of blockchain systems. future generation computer systems. 2017 aug 23. [14] de leon dc, stalick aq, jillepalli aa, haney ma, sheldon ft. blockchain: properties and misconceptions. asia pacific journal of innovation and entrepreneurship. 2017 dec 4. [15] ibba s, pinna a, seu m, pani fe. citysense: blockchainoriented smart cities. in proceedings of the xp2017 scientific workshops 2017 may 22 (pp. 1-5). [16] rivera r, robledo jg, larios vm, avalos jm. how digital identity on blockchain can contribute in a smart city environment. in2017 international smart cities conference (isc2) 2017 sep 14 (pp. 1-4). ieee. [17] liao dy, wang x. design of a blockchain-based lottery system for smart cities applications. in2017 ieee 3rd international conference on collaboration and internet computing (cic) 2017 oct 15 (pp. 275-282). ieee. [18] marsal-llacuna ml. future living framework: is blockchain the next enabling network?. technological forecasting and social change. 2018 mar 1;128:226-34. [19] karamitsos i, papadaki m, al barghuthi nb. design of the blockchain smart contract: a use case for real estate. journal of information security. 2018 jun 28;9(3):177-90. [20] michelin ra, dorri a, steger m, lunardi rc, kanhere ss, jurdak r, zorzo af. speedychain: a framework for decoupling data from blockchain for smart cities. inproceedings of the 15th eai international conference on mobile and ubiquitous systems: computing, networking and services 2018 nov 5 (pp. 145-154). [21] xie j, tang h, huang t, yu fr, xie r, liu j, liu y. a survey of blockchain technology applied to smart cities: research issues and challenges. ieee communications surveys & tutorials. 2019 feb 15;21(3):2794-830. [22] shen m, tang x, zhu l, du x, guizani m. privacypreserving support vector machine training over blockchain-based encrypted iot data in smart cities. ieee internet of things journal. 2019 feb 26;6(5):7702-12. [23] reilly e, maloney m, siegel m, falco g. a smart city iot integrity-first communication protocol via an ethereum blockchain light client. inproceedings of the international workshop on software engineering research and practices for the internet of things (serp4iot 2019), marrakech, morocco 2019 apr (pp. 15-19). [24] rahman ma, rashid mm, hossain ms, hassanain e, alhamid mf, guizani m. blockchain and iot-based cognitive edge framework for sharing economy services in a smart city. ieee access. 2019 jan 30;7:18611-21. [25] sharifinejad m, dorri a, rezazadeh j. bis-a blockchainbased solution for the insurance industry in smart cities. arxiv preprint arxiv:2001.05273. 2020 jan 15. [26] makhdoom i, zhou i, abolhasan m, lipman j, ni w. privysharing: a blockchain-based framework for privacypreserving and secure data sharing in smart cities. computers & security. 2020 jan 1;88:101653. [27] eyal i, sirer eg. majority is not enough: bitcoin mining is vulnerable. in international conference on financial cryptography and data security 2014 mar 3 (pp. 436-454). springer, berlin, heidelberg. [28] abilash soundararajan, 10 blockchain and new age security attacks you should know, 2019. url: https://blogs.arubanetworks.com/solutions/10-blockchainand-new-age-security-attacks-you-should-know/. accessed on 12 december 2019. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e2 https://blogs.arubanetworks.com/solutions/10-blockchain-and-new-age-security-attacks-you-should-know/ https://blogs.arubanetworks.com/solutions/10-blockchain-and-new-age-security-attacks-you-should-know/ blockchain for smart citiesa review 7 [29] efanov d, roschin p. the all-pervasiveness of the blockchain technology. procedia computer science. 2018 jan 1;123:116-21. [30] khan ma, salah k. iot security: review, blockchain solutions, and open challenges. future generation computer systems. 2018 may 1;82:395-411. [31] karame g, androulaki e, capkun s. two bitcoins at the price of one? double-spending attacks on fast payments in bitcoin. iacr cryptology eprint archive. 2012 oct 16;2012(248). [32] theodorou s, sklavos n. blockchain-based security and privacy in smart cities. in smart cities cybersecurity and privacy 2019 jan 1 (pp. 21-37). elsevier. [33] nagothu d, xu r, nikouei sy, chen y. a microserviceenabled architecture for smart surveillance using blockchain technology. in 2018 ieee international smart cities conference (isc2) 2018 sep 16 (pp. 1-4). ieee. [34] nikouei sy, chen y, song s, xu r, choi by, faughnan tr. real-time human detection as an edge service enabled by a lightweight cnn. in2018 ieee international conference on edge computing (edge) 2018 jul 2 (pp. 125-129). ieee. [35] chen n, chen y, blasch e, ling h, you y, ye x. enabling smart urban surveillance at the edge. in2017 ieee international conference on smart cloud (smartcloud) 2017 nov 3 (pp. 109-119). ieee. [36] xu r, nikouei sy, chen y, polunchenko a, song s, deng c, faughnan tr. real-time human objects tracking for smart surveillance at the edge. in2018 ieee international conference on communications (icc) 2018 may 20 (pp. 1-6). ieee. [37] sharma pk, park jh. blockchain based hybrid network architecture for the smart city. future generation computer systems. 2018 sep 1;86:650-5. [38] owasp t. application security risks 2017. available (accessed november 16, 2019): https://www. owasp. org/index. php/top_10-2017_top_10. 10. [39] claycomb wr, nicoll a. insider threats to cloud computing: directions for new research challenges. in2012 ieee 36th annual computer software and applications conference 2012 jul 16 (pp. 387-394). ieee. [40] hm government, government cloud strategy, 1–24, 2011 [41] m. seliger,” test: fitness wristbands reveal data”, test avtest gmbh, klewitzstr, germany, 1–7, jun. 2015 [42] pop c, cioara t, antal m, anghel i, salomie i, bertoncini m. blockchain based decentralized management of demand response programs in smart energy grids. sensors. 2018 jan;18(1):162. [43] sharma pk, moon sy, park jh. block-vn: a distributed blockchain based vehicular network architecture in smart city. journal of information processing systems. 2017 feb 1;13(1). [44] sklavos n, souras p. economic models & approaches in information security for computer networks. ij network security. 2006 jan 1;2(1):14-20. [45] nakamoto s. bitcoin: a peer-to-peer electronic cash system. manubot; 2019 nov 20. [46] lazaroiu c, roscia m. smart district through iot and blockchain. in2017 ieee 6th international conference on renewable energy research and applications (icrera) 2017 nov 5 (pp. 454-461). ieee. [47] reyna a, martín c, chen j, soler e, díaz m. on blockchain and its integration with iot. challenges and opportunities. future generation computer systems. 2018 nov 1;88:173-90. [48] puthal d, malik n, mohanty sp, kougianos e, yang c. the blockchain as a decentralized security framework [future directions]. ieee consumer electronics magazine. 2018 feb 8;7(2):18-21. [49] sun j, yan j, zhang kz. blockchain-based sharing services: what blockchain technology can contribute to smart cities. financial innovation. 2016 dec;2(1):1-9. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e2 smartphone application for self blood glucose monitoring & disease managementa case report dr. moshe kamar md. department of acute care, wolfson medical center 62 halochamim st. holon israel 972 543301308 moshe@mydario.com categories and subject descriptors j. computer applications j.3 life and medical sciences subject descriptor: medical information systems general terms performance, measurement, management keywords glucose meter, glucose monitor, diabetes, t1 diabetes, type 1 diabetes, diabetes performance, hba1c, diabetes compliance, blood sugar, blood glucose, diabetes selfmanagement abstract self-management of blood sugar glucose, diet and control of daily activities are crucial in overall management of type 2 diabetes mellitus (dm). in order to better adjust insulin type and dosage, educate for better diet patients are seldom requested to conduct a diary of their glucose measurements and meals. in today’s era of smartphone widespread use, it has been suggested that using mobile technology for self-blood glucose measurement together with the ability to automatically capture other factors important to control dm, may be an important method for enhancing disease selfmanagement. the dario™ device and mobile application, is a self-blood glucose monitoring device using smartphone interface. the application accumulates data of measurements, insulin intake, meals and physical activity. users are also members of an electronic dm support group. we present a case of a 55 y.o. type 2 dm patient who reported using the device over a year period. the patient baseline hba1c before using the dario program was 7.4. he started using the dario device and application and over a period of one year he managed to gradually reduce hba1c to 6.2 by keeping his glucose measurements in range from 20% a week to 100%. conclusions the use of mobile technologies together with mobihealth 2015, october 14-16, london, great britain copyright © 2015 icst doi 10.4108/eai.14-10-2015.2262011 multidisciplinary approach may revolutionize dm disease management. 1.introduction type 2 diabetes mellitus (dm) is now considered an epidemic in both children and adults in the united states, it affects 18.2 million people or 6.3% of the population.1,2 estimated health care expenditures associated with diabetes include $91.8 billion in direct and $39.8 billion in indirect costs as of 2002. the cause of such high morbidity, mortality, and costs can be mostly attributed to long-term, chronic diabetes-related complications, such as renal disease, coronary heart disease, blindness, and neuropathy.3 it has been long advocated that aggressive control of patients’ blood sugar levels, together with lifestyle practices and adherence to prescribed interventions lowers morbidity and mortality associated with the disease. according to the american diabetes association, diabetes self-management is an integral component of diabetes care. improved glycemic control (hemoglobin a1c <7%) has been shown to minimize microvascular complications by decreasing the rates of nephropathy, retinopathy, neuropathy, and cardiovascular disease.4 disease control is a daily struggle in all aspects of lifestyle, diet, physical activity, mental status, sleep, adherence to medication regiment etc. in an era when smartphone are owned by almost everyone and social networking (i.e. facebook, twitter, whatsapp…) is present and active on every smartphone, the ability is created to monitor dm patients glucose levels, lifestyle, alert them of out of range results, automatic remind them of medication and other activities that are required. results can be sent to their treating physicians for better understanding and holistic care. the use of social networks connects people with the disease, caregivers and other professionals providing “support groups” and motivating channels. we report a case of a type 2 dm patient who used a dariotm (labstyle innovations ltd, israel) type self-blood glucose monitoring device (sbgm) who reported over the social media network, great results in disease management. dario’s diabetes management solution consists of a proprietary software component in the format of an ios (iphone operating system) and android based application where the user's data is saved and managed in one healthy lifestyle management system. dario sets a new standard for diabetes personalization by leveraging social network, medical alerts, insights and pattern recognition techniques in order to provide accurate and proactive analysis and recommendations for a pwd (people with diabetes) . the dario management application supports full diabetes lifecycle – blood glucose monitoring, food intake, insulin dosage and physical activity while allowing the pwd take a proactive role in managing his diabetes. in addition, the dario application incorporates basic features such as a measurement log (when connecting the dario glucose meter), data capturing, personal trend graphs, sharing and alert features. moreover, the dario management system can be accessed through the dario website portal where pwd can observe in more details their history and trends and share their reports with their physicians, caregivers and loved ones.5 2.case report p.b.* is a 55 y.o. type 2 insulin dependent dm patient diagnosed in 2006 and was put on short acting insulin. at the same time he was diagnosed also to have mild hypertension. after several years of uncontrolled disease with numerous episodes of severe hypo and hypers he was recommended to use a smartphone based glucose monitor in an attempt to better understand the confounders of his disease. he started using the dario diabetes management solution in june 2014 and was instructed to test his blood glucose four times a day. baseline hba1c when entering the program was 7.4%. together with a dietician p.b. was given a diet specifying the amount of carbohydrates he needs to consume daily which he recorded through his dario app. insulin type and treatment regimen were entered baseline visit and updated when treatment was changed. patient was instructed to have 4 measurements a day, and enter his meal contents every time he had one . he could also enter episodes of stress, illness, sleep disorders, travels and other situations which are out of his routine daily activities. after each meal carbs are automatically calculated, dario enabled the patient to receive the recommended dosage of insulin based on all the recorded measurements. patient was also entered into a designated online social community where he could share his experiences with other users, get support from professional and technical personnel as to how to manage the disease and utilize his dario in order to benefit his condition. for each glucose measurement device would categorize measurement as falling “in range” or “out of range” and feedback the patient on his progress by showing percentage of measurements falling in range over time. p.b. dario “in range’ screen shot before each monthly visit to the clinic cumulative data graphically displayed was sent to the clinic for us to assess his progress and tailor treatment accordingly. 3.results at the commencement of use, the patient’s weekly average glucose measurements were 9.4 mmol/l (169 mg/dl). at the end of the year weekly average glucose measurements were down to 5.7 mmol/l (102 mg/dl) a decrease of 60%(figure 1). initial “in range” results were in 20% of the measurements which came up to 100% at the end of the year. these results were reflected in his laboratory hba1c results as well as in device calculated a1c, demonstrating an improvements of 83% with reductions from 7.4 to 6.2. (figure 2) the patient reported overall great satisfaction from the device and application: “the app is so simple to use, take a blood sample, enter what food you are eating and it gives you the carb content then press the symbol and you get the correct dosage of insulin, i love it takes all the guess work out of carb counting. i love the display on the app it's so simple to read and vivid. i have the app on my iphone ipad and ipod i love it that i can use all these to do a test and all my results will sync” (taken from p.b.’s social network postings). figure 1: showing gradual decrease of up to 60% from baseline measurements in blood glucose values (mmol/l) figure 2 – showing 83% decrease in hba1c over 52 weeks period 4.discussion thriving with diabetes is a daily battle in which every patient is required to self-manage and control multiple variables. in order to tailor treatments and assist in construction of “the dm routine” patients are typically required to manage a diary. there is a constant “wild goose chase” to understand one’s food content, activities and other variables affecting blood glucose levels. it has been shown previously how integrated daily use is more likely if the self-management components are offered in a mobile phone app, and electronic diaries are thought to improve self-management.6,7 certainly the patient should be the primary “user” of that data, but even the most motivated patient needs a little guidance, a few reminders, and a lot of education to be maximally effective. the medical community is unprepared to collect or analyze all data 5 5.5 6 6.5 7 1 5 9 13 17 21 25 29 33 37 41 45 49 a1c week glu week requested. the logical step would be to streamline the process, automate as much as possible, and help each patient become as self-efficacious as possible. management of chronic disease, including diabetes, has passed the point in which quarterly visits with a quick review of daily home measurements is adequate to maintain optimal health. data collected should be used to be an effective tool. minimal action resulting from home monitoring destroys the motivation necessary to continue the collection of that data. certainly the patient should be the primary “user” of that data, but even the most motivated patient needs a little guidance, a few reminders, and a lot of education to be maximally effective. the medical community is unprepared to collect or analyze all data requested. the logical step would be to streamline the process, automate as much as possible, and help each patient become as self-efficacious as possible. the wide spread use of smartphones, internet and social networks open up the possibility for multimodal approach. from the patient side automated features reduce some burden of entering data, other data can be entered in an easy and friendly way. furthermore the device can notify the patient of activities/actions needed (i.e. medications, bg testing, doctor appointments etc.), compiling all data in real time assists the patient in determining insulin dosage and it can also alert the patient of significant changes which require special attention or action. the use of smartphone technology allows for a freer interchange between patients and the health care team. physicians are capable of understanding the data over time and effectively focus on events/ periods affecting patient glucose balance.8 studies of mobile phone-based interventions have had varied success in improving self -management and glycemic control in individuals with diabetes.9,10 one explanation is that mobile phones are a platform, not a solution in itself, and interventions vary widely. a major gap in the literature is the lack of behavioral models to explain how these interventions improve diabetes self-management.11 reviews of diabetes selfmanagement interventions studies of mobile phone applications to date have been largely theoretical. the prevailing theoretical assumption is that mobile phone-based interventions lead to behavior change through prompts and conditioning.12 however, barriers to self-management are complex, and it is unlikely that sustained behavior change can be observed through conditioning alone.13 this case report demonstrates the ability of new technologies to have significant impact on patient disease self-management. the availability, low cost, prevalence use of smartphone apps’ and interfaces increased the patient’s ability to control his disease and gradually for the first time take charge. together with the device, support group and health care provider he has managed to produce a routine that promoted him to maintain his blood glucose to a desired range, lower his hba1c and above all self-satisfaction from his freedom, to carry the device everywhere, getting real time information and feedback on the process. 5.conclusions smartphone based technologies for controlling diabetes, have a promising role in the holistic and multidisciplinary of disease management. *patient p.b. has given complete consent to utilize his measurements and information. 6.references 1. centers for disease control and prevention. national diabetes fact sheet: general information and national estimates on diabetes in the united states, 2003. atlanta (ga): 2. u.s. department of health and human services, centers for disease control and prevention; 2003. 3. hogan p, dall t, nikolov p; american diabetes association.economic costs of diabetes in the us in 2002. diabetes care.2003;26:917-32. 4. american diabetes association. standards of medical care for patients with diabetes mellitus. diabetes care. 2003;26:s33-s50 5. vuong am, huber jc, bolin jn, ory mg, moudouni dm, helduser j, et al. factors affecting acceptability and usability of technological approaches to diabetes self-management: a case study. diabetes technol ther 2012 dec;14(12):1178-1182 6. labstyle innovations; dario diabetes management solution. www.mydario.com 7. holmen h1, torbjørnsen a, wahl ak, jenum ak, småstuen mc, arsand e, ribu l. a mobile health intervention for selfmanagement and lifestyle change for persons with type 2 diabetes, part 2:one-year results from the norwegian randomized controlled trial rene wing health. jmir mhealth uhealth. 2014 dec 11;2(4):e57. 8. malasanos t. analysis: mobile phones integrated into diabetes management: a logical progression. j diabetes sci technol. 2008 jan;2(1):154-5 9. krishna s, boren sa. diabetes self-management care via cell phone: a systematic review. j diabetes sci technol. 2008; 2:509–517 10. holtz b, lauckner c. diabetes management via mobile phones: a systematic review. telemed j e health. 2012; 18:175–184 11. riley wt, rivera de, atienza aa, nilsen w, allison sm, mermelstein r. health behavior models in the age of mobile interventions: are our theories up to the task? transl behav med. 2011; 1:53–71 12. dick jj, nundy s, solomon mc, bishop kn, chin mh, peek me. feasibility and usability of a text message-based program for diabetes selfmanagement in an urban african-american population. j diabetes sci technol. 2011; 5:1246– 1254 13. nundy s1, dick jj, solomon mc, peek me. developing a behavioral model for mobile phonebased diabetes interventions. patient educ couns. 2013 jan;90(1):125-32. http://www.ncbi.nlm.nih.gov/pubmed/?term=holmen%20h%5bauthor%5d&cauthor=true&cauthor_uid=25499872 http://www.ncbi.nlm.nih.gov/pubmed/?term=torbj%c3%b8rnsen%20a%5bauthor%5d&cauthor=true&cauthor_uid=25499872 http://www.ncbi.nlm.nih.gov/pubmed/?term=wahl%20ak%5bauthor%5d&cauthor=true&cauthor_uid=25499872 http://www.ncbi.nlm.nih.gov/pubmed/?term=jenum%20ak%5bauthor%5d&cauthor=true&cauthor_uid=25499872 http://www.ncbi.nlm.nih.gov/pubmed/?term=jenum%20ak%5bauthor%5d&cauthor=true&cauthor_uid=25499872 http://www.ncbi.nlm.nih.gov/pubmed/?term=sm%c3%a5stuen%20mc%5bauthor%5d&cauthor=true&cauthor_uid=25499872 http://www.ncbi.nlm.nih.gov/pubmed/?term=arsand%20e%5bauthor%5d&cauthor=true&cauthor_uid=25499872 http://www.ncbi.nlm.nih.gov/pubmed/?term=ribu%20l%5bauthor%5d&cauthor=true&cauthor_uid=25499872 http://www.ncbi.nlm.nih.gov/pubmed/?term=a+mobile+health+intervention+for+self-management+and+lifestyle+change+for+persons+with+type+2+diabetes%2c+part+2%3a+one-year+results+from+the+norwegian+randomized+controlled+trial+renewing+health http://www.ncbi.nlm.nih.gov/pubmed/19885192 http://www.ncbi.nlm.nih.gov/pubmed/19885192 http://www.ncbi.nlm.nih.gov/pubmed/19885192 http://www.ncbi.nlm.nih.gov/pubmed/?term=nundy%20s%5bauthor%5d&cauthor=true&cauthor_uid=23063349 http://www.ncbi.nlm.nih.gov/pubmed/?term=dick%20jj%5bauthor%5d&cauthor=true&cauthor_uid=23063349 http://www.ncbi.nlm.nih.gov/pubmed/?term=solomon%20mc%5bauthor%5d&cauthor=true&cauthor_uid=23063349 http://www.ncbi.nlm.nih.gov/pubmed/?term=peek%20me%5bauthor%5d&cauthor=true&cauthor_uid=23063349 http://www.ncbi.nlm.nih.gov/pubmed/?term=developing+a+behavioral+model+for+mobile+phone-based+diabetes+interventions http://www.ncbi.nlm.nih.gov/pubmed/?term=developing+a+behavioral+model+for+mobile+phone-based+diabetes+interventions road traffic rfid pedestrians detecting system for vehicles 1 road traffic rfid pedestrians detecting system for vehicles michal balog1, angelina iakovets1,* and stella hrehova1 1technical university of kosice, faculty of manufacturing technologies with a seat in presov, bayerova,1, 08001 presov, slovak republic abstract safe road traffic, clean environment, environmentally friendly vehicles and eco-buildings are components of the world’s vision of immediate future supported by scientists and statesmen. aspiration for healthy environment and sustainable development of technologies give life for idea of smart cities which consist of all these visions towards modern world. the aim of research was connection pedestrians and alarm system of the vehicle to prevent road incidents with the help of rfid technology. there were proposed vehicle rfid system and tags for pedestrians. system was designed on the basis of scientists’ research in this area. the main factors influencing the construction of proposed system were working range of the system and coverage width of the reading devices. further were compared existent subsidiary systems for drivers versus designed system. the study represents the expected effectiveness of the proposed rfid system as well as the ability to implement it even in old vehicle control systems. keywords: rfid, smart city, vehicles, detecting systems, accidents, pedestrians, road traffic. received on 13 may 2019, accepted on 30 september 2019, published on 03 october 2019 copyright © 2019 michal balog et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.160601 *corresponding author. email: angelina.iakovets@tuke.sk 1. urban traffic in smart cities 1.1. visions of the urban traffic safety new or innovative visions need to brand new solutions, like a conception of information and communication technologies, iot and other smart technologies. the concept of a smart city dates back to the year 2006, but the most widely used has become in the last years. the idea of such cities is on track thanks to the modern state of environment and due to development of new technologies. the smart city strategy combines several basic aims are to move information technologies, to provide efficient traffic, to supply sustainable energy consumption and clean environment. modern view on the smart city concept is based on connection of the objects with the iot technologies, design and construction the smart buildings, modernization of the urban network and global collection data for establishment new real-time city logistic system. this concept has gained international support from a variety of international organizations, such as world health organization (who), united nations (un), the european innovation partnership on smart cities and communities (eip-scc), government, city and regional organizations, also by another projects and entities. in 2015 the united nations economic commission for europe began development of road safety model “safe future inland transport systems (safefits)” to support knowledge based on transport policy decisions related to road casualty reduction. the primary objective is to assist governments and policy makers in tailoring road safety policies in order to achieve more tangible results, in both developed and developing countries. safefits comprises a database with global data research article eai endorsed transactions on smart cities eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e2 http://creativecommons.org/licenses/by/3.0/ michal balog, angelina iakovets and stella hrehova 2 on indicators from all layers of the road safety management system and a set of statistical models fitted onto that database, with resulting outputs [20]. all these projects are aimed on solutions in government and information systems, on another hand they also support design smart buildings, vehicles, autonomous and selfgoverning object, which will not have a harmful effect on the environment. but on the other side, not every developing country is able to invest enough recourses to ensure fully implementation of such projects. in this regard, the aim of research was design technical solution of the accidents and will help to disseminate idea of a smart city. according to navigant research, global smart city revenue is expected to grow from $36.8 billion in 2016 to $88.7 billion by 2025 [1]. such information reflects the prospects of the study. 1.2. the real state of the european urban traffic a new report by the who indicates road traffic deaths continue to rise, with an annual 1.35 million fatalities [20]. the main part of the victims of the road incidents are 5-29 year aged people (according to who “global status report on road safety 2018” report). this segment of the people is strategically important for every country. it is a reason why experts create effective legislation, safer vehicles, safer roads, qualitative emergency care. it is expected that all proposals will be implemented and dis-cussed at the global ministerial conference on road safety in sweden in february 2020 [20]. the main traffic solutions, which are being implemented in many countries are self-driving cars, hybrid and electric vehicles, modern city logistic system and associated laws. all these solutions did not wholly fulfil expectations yet; it can be seen in who’s report of the traffic accidents (figure. 1). figure 1. road traffic injuries 2018 [20] the car accidents happen most frequently on: parking lots stop signs rural highways two-lane roads [2]. this fact should be taken as ability to research existing preventive systems of the road accidents at the automotive industry. 1.3. road traffic injuries prevention technologies modern and the most popular solutions proposed by automotive industry are self-driving cars and smart technologies that detects pedestrians and another participants of the road traffic, but the first one did not become widely used until nowadays [3]. manufacturers of unmanned vehicle claim that the artificial intelligence, installed in it, allows making its own decisions effectively. the imperfect of self-driving cars are approved by volume of internet recourses [4]. the scientists, who studied these accidents with such kind of vehicles, made the schemes of the crashes. all scenes of the accidents displayed the imperfection of intelligent vehicle system [5]. that is why automotive enterprises do not cease to produce ordinary cars, however their production was modernized by technology of detection pedestrians on the road. the first announcement of such a system was in 2011 by volvo in model s60 and was called the pedestrian detection system [6]. principles of pedestrian recognition systems: holistic pedestrian detection (moving object detection) analysis of histogram of shades partial detection of pedestrians (camera and radar lead around a contoured object) pattern recognition in the database recognition by multiple cameras. the most operative speed of the system is the speed of 35 km / h, only under this condition, automakers argue that avoiding of collision is almost 100%. the range of the camera and the radar, according to the manufacturer, is up to 40 meters. over this distance, recognition errors may occur. at speeds above 35km / h, the driver can-not avoid a collision [6], [7], [8]. due to scientific literature: from different accidents, as well as calculations of engineers, at a speed of 65km / h the probability of a pedestrian colliding with a car is 85%, and at a speed of 50 km / h the probability is 45%. it is also noted, while reducing speed to 30km / h the probability of a collision will be equal to 5%. automotive enterprises claim that to mitigate damage in an accident, they install special elastic bumpers and bonnets, as well as a pedestrian safety cushion hidden under the wind-shield and bonnet. referring to speed limits of the detection systems operation efficiency, a number of weaknesses arise, such as: high requirements for vehicle technical equipment, reduced reaction during bad weather and at night, eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e2 road traffic rfid pedestrians detecting system for vehicles 3 the quality of the system reaction due to the speed of the car, the high cost of the vehicles with this type of system [6]. as a result, the main lack of automotive systems is inoperability of the detection system at night time, as well as during bad weather (rain, fog or snow). in such conditions, camera and radar are unable to recognize the pedestrian and often give the false information. this is also influenced by location of sensors and camera, often they are behind central mirror or on the windscreen. pedestrian detection using infra-red cameras is integrated to the night vision system, but it does not have an active collision warning feature. together with the pedestrian detection system and night vision assist (nva) systems, auto industry introduced line assist and light detection and ranging system. to represent advantages and disadvantage of these systems was created comparison table (see table 1). table 1. comparative table of automotive security systems [6], [7], [8], [9] system name advantages disadvantages pedestrian detection system (pds) able to detect the pedestrian on the distance up to 40 meters at the vehicle’s speed 35km/h can stop the vehicle detection not only existence of the pedestrian, but also define him high requirements for vehicle technical equipment, reduced reaction during bad weather and at night, the quality of the system reaction due to the speed of the car (non-useful at the speed more than 35 km/h), the high cost of the vehicles with this type of system night vision system (nvs) the infrared camera sends infrared radiation up to 300 meters. high resolution cameras. cameras are triggered at a distance of 150250 meters. the system also has thermal cameras. at a vehicle speed of 45 km / h, it can detect an object at a distance of 80 meters high requirements for vehicle technical equipment, reduced reaction during bad weather and at night, the high cost of the vehicles with this type of system (price such of the sensor is 250$) line assist (la) -used not only on expensive car, but also on low-cost, -effects on driver by vibrations of the wheel, by sounds, by visual signals and also can stop car without involving driver, -analyses road (150° ) and the driver’s state the system requires clear road markings, system is sensitive to the dust road, efficient only for road markings light detection and ranging system (lidar) scanning range 180° efficient distance of detecting 250 meters speed of detection wide sphere of using can be installed on any place of the vehicle -optical sensor is sensitive to bad weather (rain, snow, fog and atc.) -uses only with another sensors in system, also install with pds and nvs. the systems are not suitable for all conditions of the environment, therefore there is an opportunity to develop alternative system, according to the table 1. 1.4. the radio-frequency identification (rfid) system in automotive industry the rfid system is well-known in most of economic activities. this system find place in transport, finance and safety, veterinary spheres, retail, medicine, manufacturing, sport, consumption goods, airlines, and so on. according to forecasts, in 2024 year the distribution of rfids by economic sectors will be in such way (see figure. 4) [21]. figure 2. rfid consumption by industry [21] eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e2 4 the biggest part of the pie chart accounts for transport, it let us to assume efficiency of rfid technology in this sphere. if we take a look on global distribution due to geographic regions it can be seen that europe is not on leader position (figure. 3) [22]. figure 3. geographic structure of the global market for rfid products [22] asian-pacific region and north america take leading positions, according to figure. 3, while europe is on the third place on the global market. this indicator can be increased by introducing rfid system in new context. such system can be used as pedestrians detecting system in automotive industry. the research shows that rfid system was proposed as solution for city management systems before. should be highlighted the research of soichi kubota, oisin morgan, d.f. llorca and their group of scientists [11], [12], [13]. their scientific articles were issued in 2006, 2015 and 2017 year. despite the fact that the studies were established at different times they have common features and their goal was prevention complex accidents on intersections. for example, the research of soichi kubota includes rfid tags for every participant of the road traffic, urban tag reader (repeater) and long frequency (lf) generators (see figure. 4) [13]. figure 4. system overview [13] these three studies undoubtedly have a significant contribution for development of urban infrastructure, but they were designed for city and as existent automotive systems these solutions should to prevent accidents on problematic areas as parking lots, intersections and stop signs. returning to the statistics of accidents [14], the area of rural highways is still dangerous area and existing auto systems are not efficient enough (table 1). to offer a suitable system, for these type of roads, should be considered features of movement on it. 2. design rfid pedestrians detecting system for successful providing long-range detecting of the vehicle rfid detecting system it is necessary to pick up eligible components. figure 5. braking distance of the car [23] significance of the long range system is approved by scheme of the car braking distance (figure. 5). designing useful system is based on selection of the most appropriate components. according to literature recourses, speed limit in european cities is 50 km/h and suburban medium speed is 90 km/h [23]. proposed article is aimed on problematic areas, mainly on single carriage ways and express ways, therefore was taken speed 90 km / h for further calculations. factors which effect on rfid pedestrian detecting system productivity are: tag antenna reader accommodation of the components. main types of rfid tags: passive low frequency (lf), passive high frequency (hf), passive ultra-high frequency (uhf) and active uhf. characteristics of these types are shown in below. michal balog, angelina iakovets and stella hrehova eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e2 5 table 2. types of rfid tags [15] rfid tag was selected as appropriate due to its ability to contain text and graphic information. high frequency tags are more efficient in conditions of long range reading (from table 2). for rfid detection system is feasible to pick up the components for participants of the road traffic and for vehicle (see table 3). table 3. components of the system [25], [26], [27], [28] elements detection range for pedestrian uhf tag opp130 up to 30 meters active locating tag cmc3606 up to 25 meters tag cmc3609l up to 100 meters for car system active rfid reader cmc195n up to 100 meters uhf rfid antenna 5dbm help to extend the range of the reader’s signal (1 antenna has 70°) for designing rfid system were proposed two types of rfid tags passive uhf and active uhf, it was caused by data from table 3. according to the table 1, the rfid system should cover area on 180°, to support detection of pedestrians on the footpath and to able the braking distance of the car (up to 73 meters) (see figure. 5). figure 6. the rfid detection system illustration the figure. 6 shows the possibility of the components placement. rfid reader will be hidden beneath bumper and it will send a signal to the on-board media player, which will signalize by sound alarm about appearance of the pedestrian on the road. the advantage of such reader based on its small voltage (12 volts) requires. this fact gives an advantage for the rfid system, since does not require additional components or design changes of the car. three antennas will provide wide angle of detection a hundred meters away (figure. 7). figure 7. detecting range of the rfid car system scheme (figure. 7) shows the ability of the system’s detecting range (red circles 1,2,3 are imagined pedestrians). every antenna provides 70° reading angle. such parameters of the system make this system more competitive than analogue automotive detecting systems. antennas are able to detect on more than 180° angle and on the long distance (figure. 7). expected that rfid road traffic rfid pedestrians detecting system for vehicles eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e2 6 system will approve the best features of the modern systems and exclude their weakness. testing of the speed abilities of rfid system was made by xiaoqiang zhang and manos tentzerisin [16]. scientists said rfid system is efficient at the speed 150 km/h, this fact approves opportunities of vehicle rfid systems. the brake distance of the car at the speed of 100 km/h is 73 meters (figure.5), so it is reasonable to assume that rfid technology will be effective due to its reading range (100 meters). cannot be rejected fact that rfid system should to fulfil the conditions of the tag charging. every rfid tag should receive energy from the reader and send the information signal back. this fact cannot be rejected, that is why should be determinate effective reading range (err) of the system. where err of the system represents equation bellow (err of the system, errr and tdt are in meters). where errr is err of reader and tdt is tag trigger distance. tr tderrerr −=systemtheof (1) according to (1) there can be quantified the err of the proposed components due to their technical parameters [25], [26], [27], [28], [29]. there were selected the uhf tag opp130 and active rfid reader cmc195n from table 2. the calculations enable assertion that err fulfils the requirements of the braking distance scheme. this statement is based on the european high speed restriction act for single carriageways (90 km/h) [24] and scheme of the braking distance (figure. 7). this speed limit was the main condition for calculations bellow, because the top places of the road traffic accidents are single carriageways and expressways [14]. due to the fact that roads have roughness, further research will be aimed on determination of the system effectiveness in conditions of road roughness as well as the efficiency of reading the number of pedestrians in real conditions of urban traffic. 3. conclusions the evolution of the technologies and innovations in the smart city concept encouraged researches on decrease of the road traffic incidents on problematic areas. the research has shown the bottlenecks of the modern preventive solutions of the road accidents. thanks to existent researches of the scientists, was proposed more mobile system, than existed before. the advantages of proposed vehicle system are: 180° readout detection at a distance of 80 meters mobility of the system pedestrian tag contains graphic and text information tags are less bulky than in previous versions the system is not difficult to install and is suitable for any vehicle with a cpu. the quality of such a system will not depend on weather conditions and should provide pedestrian detection at the braking distance at a speed of 90 km / h. there will be possible pedestrian detection not only at a crosswalk but also on a footpath. communication between media-player and reader will produce the sound and visual alarm (depends on player) when pedestrian will be funded on the detecting distance. expects that proposed rfid detection system not only decrease a number of the road accidents on studied type of roads but also will create new preventive solution for pedestrians and vehicles. further research will include testing the proposed system in real conditions with related measurements. references [1] navigan research: smart cities, smart technologies and infrastructure for energy, water, mobility, buildings, and government: global market analysis and forecasts (2016). [2] attorney b.: where do car accidents happen most frequently, babcoock, 2018. [3] dougherty c.: california d.m.v. stops short of fully embracing driverless cars, new york times (2015). [4] favaro m., nayarinn., tripp m.: examining accident reports involving autonomous vehi-cles, in: xiaosong hu, chongqing univercity, china, plos one 12(9): e0184952 ( 2017). [5] massino v.: why do unmanned cars hit cyclists and get into accidents, lenta.ru (2017). [6] mosenzov e.: pedestrians detecting systems: device, principle of operation, fastmb (2019). [7] mosenzov e.: how does a car's night vision system works, fastmb (2019). [8] mosenzov e.: lane traffic assistant, fastmb, (2019). [9] mosenzov e.: optical sensor, lidar characteristics, principle of operation, fastmb, (2019). [10] dogan, h., yavuz, m., caglar, m., goyel, m.: use of radiofrequency identification systems on animal monitoring, sdu international journal of technological science, vol. 8, pp. 38-53, no 2, august 2016. [11] oisin, m., robert, g., rodrigo, o., robert, s.: hybrid urban navigation for smart cities, 2017 ieee 20th international conference on intelligent transportation systems (itsc), issn: 2153-0017date, inspec accession number: 17632226, march 2018. [12] llorca, d.f., quintero, r., parra, i., izquierdo, r., fernandez, c., sotelo, m. a.: assistive pedestrian crossings by means of stereo localization and rfid anonymous disability identification, published in: 2015 ieee 18th international conference on intelligent transportation systems, inspec accession number: 15583099, doi: 10.1109/itsc.2015.223, publisher: ieee, conference location: las palmas, spain, 2015. [13] kubota, s., okamoto, y., oda, h.: safety driving support system using rfid for preven-tion of pedestrian-involved accidents, published in: 2006 6th international conference on its telecommunications, inspec accession number: 9365087, doi: 10.1109/itst.2006.288860, ieee, china, 2006. [14] attornay, b.: where do car accidents happen most frequently, comsomol, 2014. michal balog, angelina iakovets and stella hrehova eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e2 7 [15] scdigest editorial staff: supply chain graphic of the week: excellent summary of attrib-utes of different types of rfid tags, supplychaindigest, 2017. [16] xiaoqiang, z., tentzeris, m.: applications of fast-moving rfid tags in high-speed railway systems, international journal of engineering business management 3(1), doi: 10.5772/45676, 2011. [17] yeoman m., rfid tag reading and antenna optimization, comsomol, 2014. [18] hsieh et al.: key factors affecting the performance of rfid tag antennas, current trends and challenges in rfid, chapter 8, 151-170, prof. cornel turcu (ed.), intech (2011). [19] unece, saving lives with the safefits model, safety drives all aspects of road transport, http://www.unece.org/info/ece-homepage.html, last accessed 2019/04/06. [20] world health organization: the global status report on road safety 2018, https://www.who.int/newsroom/detail/07-12-2018-new-who-report-highlightsinsufficient-progress-to-tackle-lack-of-safety-on-theworld's-roads, last accessed 2019/04/01. [21] tadviser, radio frequency identification (rfid), http://tadviser.com/index.php/article:rfid_(radio_frequ ency_identification,_radio_frequency_identification), last accessed 2019/04/06. [22] json.tv: key trends in the global rfid technology market, http://json.tv/en/ict_telecom_analytics_view/the-globaland-russian-markets-of-rfid-tags-and-readers, last accessed 2019/04/06. [23] maximum speed limit worldwide, https://i.imgur.com/jtjuqw1.png, last accessed 2019/04/06. [24] speed limits in europe, travel by car, https://autotraveler.ru/en/spravka/max-speed-limits-ineurope.html#.xxptavazat_, last accessed 2019/9/9. [25] technotreid, http://uarfid.kiev.ua/products/uhf-metka-nametall-do-30-metrov-opp130/, last assecced 2019/04/07. [26] cmcid, http://rfid.cmc.foxconn.com/en/prods.aspx?id=cmc3606, last accessed 2019/04/07. [27] technotreid, uhf rfid tag opp130, http://uarfid.kiev.ua/products/uhf-metka-na-metall-do-30metrov-opp130/, last accessed 2019/04/06. [28] uhf rfid antenna 5dbi, http://bg.antennamanufacturer.com/news/uhf-rfid-antenna-5dbi5889836.html, last accessed 2019/04/07. [29] forward security systems, rfid technology, http://www.hundure.ru/rfid.htm, last accessed 2019/04/05. [30] rfid: from descriptions to actual applications, http://www.gaw.ru/html.cgi/txt/publ/other/rfid.htm, last accessed 2019/04/05. road traffic rfid pedestrians detecting system for vehicles eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e2 blockchain: a detailed survey to explore innovative implementation of disruptive technology 1 blockchain: a detailed survey to explore innovative implementation of disruptive technology tabish mufti1, nudrat saleem2,* and shahab saquib sohail1 1department of computer, science and engineering, sest, jamia hamdard, new delhi, india 2department of educational studies, jamia millia islamia, new delhi, india abstract blockchain technology is a major disruptive technology breakthroughs in the past two decade. this technology can be easily understood as a ledger of records which are irreversible and verifiable. the greatest impact of this application is in the massive generation of crypto-currencies. over the years, block chain has proved to be more comprehensive and beneficial in more ways than one; not just as an archive of records or virtual currency domain. this paper comes up with a survey done to bring out the key developments of block chain into other domains of practice. despite the most prevalent adoption of block chain happened to be financial and banking sector but there are researches and trials been done in many other sector by technology game changers. this paper will explore and present diverse uses of block chain in other domains, its impacts and the future course of implementation practices that may be tested. *corresponding author. email: researchscholarnudrat@gmail.com 1. introduction blockchain technology is one of the fastest growing technologies in recent years. a block chain is described as a list of growing records called blocks, cryptography technology is used in blockchain. in this technology, each block consists of cryptographic hash of the previous block, timestamp and transaction data. in other words, block chain can be defined as a chain consisting of various blocks and forming a chain along with the information in each block. block chain use secure transactions for money transfer, property, contacts etc. in 1991, a study on crypto-graphic block chain was published by stuart haber and w. scott stornetta. the goal was to invent and implement a technique which didn't alter the timestamps of the document. a year later, haber and stornetta implemented merkel tree format to improve the block chain design for efficiency. data recorded cannot be changed; updation is not possible [1]. this paper discusses a detailed review of block chain technology literature and its applications [2]. 2. blockchain – overview a blockchain is a network of separate, distributed and digital ledger which is maintained by more than one party using cryptography. it ensures security of transmission, access and storage consistency of data. distributed ledger technology (dlt) is used to record information that's distributed across a network. block keyword is been used to store data in block. each block holds cryptographic hash of the prior block in block chain. the blocks are linked to one another through chains [3]. during the phase of 1991-2008 the evolution of block chain technology took place. in 2008 to 2013, blockchain 1.0 and bitcoin emerged. then moving forward, 2013 to 2015 block chain 2nd version 2.0 was introduced and ethereum development took place, now from 2018 blockchain 3.0 was introduced and known as the future. keywords: blockchain, crypto-currency, disruptive technology, distributed ledger technology (dlt), minting, ledger layer. received on 24 january 2020, accepted on 21 may 2020, published on 03 june 2020 copyright © 2020 tabish mufti et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.164858 eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e3 t mufti, n saleem, shahab saquib sohail 2 figure 1. distributed ledger technology (dlt) source: whichblockchain.com the literature study for this survey comprises of various research papers, books and book chapters, journal papers, crypto-currency sites and wikipedia, conference papers, company povs and experiments published in white papers blockchain is the buzzword these days because it shot to fame through the famous crypto currency the bitcoin. public and private sector banks have taken the smart decision to implement block chain into their transactions. the potential and possibilities of his concept is tremendous which can change the way transactions are done in future to a great extent [4][5] 3. blockchain architecture a block chain is a chain of blocks which contain information. the data which is stored inside a block depends on the type of block chain[6]. in below block chain architecture [7] diagram we have various modules integrated and explained which are used in block chain architecture[8][9].the layers of architecture are a) infrastructure layer b) utility layer c) ledger layer d) consensus layer e) smart contract layer f) system management layer g) interface layer h) application and operation layer i) maintenance layer a) infrastructure layer – this layer provides physical resources, drivers and operating environment for block chain system. operating environment includes hardware like machines, cloud etc. storage resources includes cloud storage, hard disks storage etc., network resources include hubs, switches, routers etc. b) utility layer this layer is responsible for recording, verifying and segregate information. it is distributed system which is responsible for transmission, storage and verifying. c) ledger layer – this layer stores information of block chain system as well as transaction data and generate data blocks for validity. this layer embed the hash of previous node into the next node data structure to ensure integrity and authenticity d) consensus layer – the job of this layer is to coordinate and maintain the consistency of all records in nodes in entire network. this layer set rules and arrangements to carry out block chain operations. e) smart contract layer – the job of smart contract layer is to compile, deploy, and implement the business logic of the block chain system. smart contract consist of digital assets hence modification is not possible when the data is on block chain. f) interface layer – the job of interface layer is use for encapsulation of modules and make call for application layer. source:adeptia.com figure 2. blockchain architecture [10] [25-27] g) application & operation layer – the job of application layer is to present the result to the user. this layer calls smart control layer. the application layer is responsible for the user facing components, and the implementation layer refers to everything that brings the application to life, like protocols and code[11]. h) maintenance layer – it maintain block chain system on daily basis, including various types of libraries like log library, monitoring library, management library, extension library etc [12]. 4. characteristics of blockchain: block chain is rich in its features[13], in this paper few are functional characteristics are explore[14][15]. increase capacity –this feature talks about the capacity of whole network as n number of machines work together to offer great power then few devices hence all the things are centralized [16]. better security – highest security is achieved when block chain technology is used, as block chain network consist eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e3 blockchain: a detailed survey to explore innovative implementation of disruptive technology 3 of number of nodes (computers) hence transaction confirmation is done by these nodes[17]. immutabilitythis feature talks about the ability of block chain ledger to unchanged and changes in not applicable or unaltered. minting minting is defined as the computer process of validating information, creating a new block and recording that information into the block chain. fast settlement – block chain technology fasten the process of money transfer problem from number of days to few hours [18]. decentralized – block chain technology store documents, files etc. at servers or networks and one can access via internet from remote locations [19] figure 3. block chain | features source: dataflair.com 5. technological trends of blockchain technology in 2020 since recent times we have came across various new technologies which has emerge as a benchmark for users, industry and government organization [20]. block chain technology is also one of the technology which is been now used in various sectors which include social networks , financial services , artificial intelligence etc[21] below list of latest trends of block chain in due to[22-23] which this technology is ready to provide various job opportunities to young minds in various sectors in year 2020[28-30]. • baas blockchain as service • block chain solve social networking problems • financial services lead in using block chain technology • iot and block chain together • block chain in artificial intelligence • demand for block chain experts a. baas blockchain as service baas blockchain as a service is a recent trend in the industry, it is a cloud based service which is adopted by most of the start-ups and enable users to develop products [31]. b. blockchain in social networking around the world most of the people are connect with social media. as the users have increase rapidly the problems of social media related to security , data storage, content related issue, privacy etc has also increase, online social networks systems have become popular in recent time due the massive usage of users around the world. till date, 3.9 billion social media users in february 2020. so below so graphically [32] show the users across major social networking platforms and this trend will increase month after month and year after year. as by decentralization social network problems can be solved and block chain has the most sophisticated decentralized technique [33-35]. figure 4. social network users c. financial services lead in using block chain technology: block chain helps banks in processing transactions at faster rate, reduce transaction cost, reduce frauds, helps in known your kyc and removes fraud in trading sector eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e3 t mufti, n saleem, shahab saquib sohail 4 figure 5. blockchain bank source: hyperlinkinfosystem d. iot and blockchain together: iot sector is also one of the major booming sector in the industry [36]. the complexity of architecture design and security issue had led blockchain to cop up with safety challenges. as after some time iot networks will become a safe place for hackers to perform unethical task. till the end of 2020, 30 million devices will be connected [37] with internet which will be a new place for hackers. iot devices are expected to generate 79.8 zetabytes data till 2025. figure 6. blockchain bank source: medium.com e. blockchain in artificial intelligence: blockchain and ai have now been used as benchmarks in terms of adoption of innovative technology usage across industries. blockchain can be understood as a distributed network of computers that records and stores data which can be displayed chronologically by the authorized user at any point of time. by incorporating ai into the blockchain technology can reap higher benefits with [38] improved number of supported applications. according to the international data corporation (idc), the global investment on ai is expected to reach approximately $67 billion by 2020. it is also foreseen that 55% of the businesses will be focusing on integration of ai with blockchain for greater advantage. furthermore, technology experts believe that blockchain can also make ai more simplistic and comprehensive by enabling backward planning and better decision making since the ledger of blockchain records all the data and its variables that are used by machine learning while making a decision. figure 7. blockchain & ai applications source: bbvaopenmind.com f. demand for blockchain experts: in simple words, a blockchain expert is a person who is expert in blockchain concepts and solves problems, understands, analyse and knows programming languages. he has a complete knowledge about how to build blockchain application for real life problems. the demand for the blockchain technology is increasing which is creating job opportunities for block chain developers. by the year 2023 there will be high demand for the block chain developers in the market [39] figure 8. blockchain technology growth 6. applications of blockchain block chain technology is used widely in the different sectors as given in the following table. application areas utilization markets • bill generation, data eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e3 blockchain: a detailed survey to explore innovative implementation of disruptive technology 5 analysis and data transfer • supply chain management government organizations • internet protocol registration • polls and voting • smart contacts • tele-attorney service • tax services • notary services internet of things iot • smart farming • smart homes • smart city • smart cars • robots health • data management[8] • universal emr health databanks • medical billing • smart property • health token • testing • diagnosis / results finance & accounting • digital currency payment [9] • payments & remittance • loans payment & securities • kyc • record sharing [10] • clearing and settlement • payment transfer • journals and accounts • insurance payment keys for the success of blockchain technology:  secure  transparent  traceable  documentation  less intermediate  reduce cost  decentralized  empower users  high quality data  fast traction  reliability  durability reasons for failure of blockchain technology:  excess energy consumption  mining does not mean not security  not immutable  not scale able  inefficient  redundant performance  private keys  no control of enterprise  integration concerned  complex signature verification  high cost  privacy concerned future of blockchain technology:  gaming  e-commerce  digital media  healthcare  supply chain  cloud computing  cyber security  government banking  aerospace  defence 7. conclusion block chain technology is the concept behind most famous crypto-currency in virtual finances has been extended to be served as an immutable ledger for transactions through different channels. currently, blockchain based applications are implemented in varied functions like internet of things (iot) [40], financial services, retail reward systems, voting systems and so on. however, the scalability and security are still creating hurdles to use it as a permanent solution. this paper attempts to put forward a comprehensive summary on blockchain technology. this paper firstly provides an overview of the blockchain technology, its architecture, characteristics, uses, applications etc. lastly, the reasons for the failure of blockchain technology and future trend of this technology in major industries are also forecasted, keeping in mind its present growth trend and advancements. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e3 t mufti, n saleem, shahab saquib sohail 6 references [1] m. nofer, p. gomber, o. hinz, and d. schiereck, “blockchain,” bus. inf. syst. eng., vol. 59, mar. 2017. 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[38] s. malik, v. dedeoglu, s. s. kanhere, and r. jurdak, “trustchain: trust management in blockchain and iot supported supply chains,” proc. 2019 2nd ieee int. conf. blockchain, blockchain 2019, pp. 184– 193, 2019, doi: 10.1109/blockchain.2019.00032. [39] f. naser, “review : the potential use of blockchain technology in railway applications : an introduction of a mobility and speech recognition prototype,” proc. 2018 ieee int. conf. big data, big data 2018, pp. 4516–4524, 2019, doi: 10.1109/bigdata.2018.8622234. [40] v. kuchkovskiy and n. shakhovska, “information technology of blockchain: database, smart contracts, architecture,” ieee 2019 14th int. sci. tech. conf. comput. sci. inf. technol. csit 2019 proc., vol. 2, pp. 55–59, 2019, doi: 10.1109/stccsit.2019.8929885. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e3 a block chain is a chain of blocks which contain information. the data which is stored inside a block depends on the type of block chain[6]. in below block chain architecture [7] diagram we have various modules integrated and explained which are used ... research article 1 a dspl design framework for sass: a smart building example a. achtaich * 1,3 , n. souissi 1,2 , r. mazo 3,4 , o. roudies 1 , c. salinesi 3 , 1 univ. mohammed vrabat, emi, siweb team rabat, morocco. 2 ensmr, département informatique rabat, morocco 3 cri, université panthéon sorbonne, paris, france 4 giditic, universidad eafit, medellin,, colombia asmaaachtaich@research.emi.ac.ma, roudies@emi.ac.ma, souissi@enim.ac.ma, {raul.mazo,camille.salinesi}@univ-paris1.fr,raulmazop@eafit.edu.co abstract the internet of things is a land of opportunity for believers and supporters of smart cities. experience already shows that smartphones, smart appliances, wearables, sensors and actuators can be brought together to deliver advanced services like smart markets, smart parking, smart buildings or smart energy. but in order to do so in a complex, dynamic, rapidly changing and resource constrained environment, adapting fleets of devices to align with context fluctuations becomes a necessity. this paper describes the framework established to tackle the problem. it represents the dimensions for building self-adaptive fleets for iot applications, based on the foundations of the dspl paradigm and the re principles. the paper also allocates a model for each dimension of the framework, and through a preliminary proof of concept smart building example, confirms the usability of the proposal. keywords: iot, smart-building, dynamic software product lines, dspl, self-adaptation, context, environment, fleet, variability, received on 15 december 2017, accepted on 03 february 2018, published on 26 june 2018 copyright © 2018 a. achtaich et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.26-6-2018.154829 1. introduction the internet of things (iot) enables advanced services by interconnecting fleets of connected device. these smart devices can provide basic knowledge about an environment, but can also support complex tasks like business automation, real-time reporting, and optimization operations. smart health, smart energy or smart cities are examples of the applications that are today possible, thanks to the iot. connected objects can monitor and track environment indicators in real-time. this monitoring and tacking activity helps collect information about the surrounding, and prepare smart solutions that answer the needs of the affected customers. therefore, it is important to take into consideration the mutual dependency between objects and their surroundings (i.e., system and context): changes in the surrounding have repercussions on the proper functioning of devices and the reconfiguration of the fleet can change the state and behaviour of the surrounding. hence, three main dimensions are important to consider while designing an application for the iot: the (1) system, the (2) context and the (3) environment. (1) the system is the fleet, it is represented by the embedded devices and their configurations and is managed in a way that its outcome allows the achievement of goals specified by the domain expert. (2) the context is everything that surrounds the systems, and has an impact on it. context is represented by measurements captured by devices that surround the system. context data can also originate from the user, and it can be time or space bound. finally, (3) the environment illustrates knowledge related to a domain. it holds universal information that might not have a direct impact on the system at a time being. however, it could be significant in other dispositions. when a fleet is implemented, it bears a configuration that is characterized by the set of corresponding devices along with their respective configuration. however, the eai endorsed transactions on smart cities eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e1 ∗corresponding author. email: aachtaich@gmail.com http://creativecommons.org/licenses/by/3.0/ a. achtaich et al. 2 iot systems are complex; they are rapidly changing, highly variable, heterogeneous, prone to risks and failure, and extremely dynamic. self-adaptation capabilities are thus required. in other words, from design time, the dynamic properties of iot systems should be considered, specified and properly handled. dynamic proactive adaptation in particular is required to provide adjustments at runtime [1]. it is important to note that the three dimensions are dynamic as well. devices that form the system at a particular configuration might not be the same involved in another instance of the same fleet. they could become part of the context. similarly, information that had an impact on the system in a configuration, might become irrelevant in another, and be part of the environment instead. this confirms the need for variability management. undoubtedly, iot management platforms should provide engineers and practitioners with the necessary tools to define capture and reason about variability at different levels of concerns. until today, building similar platforms has been problematic, mainly for the lack of standards, reference architectures and design frameworks. in this paper, we intend to fill this gap by proposing a design framework which tackles the problem of dynamic variability, and takes into account the specificities of a fleet of iot systems. the usability of our framework was validated through a preliminary proof of concept case in which we used a smart building example to illustrate the main challenges discussed before, and how this framework tackles these challenges. the paper is structured as follows: section 2 overviews the mechanisms for self-adaptation and presents our dspl based framework for self-adaptive iot systems. section 3 presents a smart building motivational example, and identifies the requirements for the management of fleets of connected objects. section 4 depicts the specificities and steps of domain engineering, as it serves as inputs to the activities for engineering single products, discussed in section 5, as the focus of application engineering. and finally, section 6 presents the related works before concluding. 2. a self-adaptation framework building self-adaptive systems is not a completely new concern in research. in fact, several paradigms and approaches have been developed throughout the years to support the self-properties of complex systems. in this section, we overview the most notable -but not all approaches for designing self-adaptive systems in order to decide on the approach that best qualifies for smart cities. then, depending on the decided approach, we propose a design framework accordingly. 2.1. key requirements for sass an iot smart management platform is required to provide the necessary mechanisms to monitor iot devices, to propose best-fit adaptions, to manage different levels of variability and to support a large number of connected devices. therefore, to carry out these functions, the following properties must be taken into account.  variability management: in a fleet of connected devices, variability can be captured at different levels. the platform should be able to manage this separately throughout the system’s lifecycle.  context awareness: in order to support self-adaptation, iot applications should be aware of change in their surroundings. the events and circumstances that have repercussions on the overall performance of the application should be known and addressed.  uncertainty management: it is not always possible to predict the events that will trigger a reconfiguration. thus, the platform is required to evaluate the qualities the system offers in comparison with the ones requested by users.  smart proactive self-adaptation: the platform should provide the necessary mechanisms to analyze collected data and adapt the system in problematic situations. in a resources constrained environment like ours, every planned adaptation should be subject to validation to prove its necessity.  physical abstraction: the platform should support communication with heterogeneous devices and various technologies in order to monitor and actuate. this requirement will not be discussed in this paper. only preliminary concepts will be introduced. 2.2. dspl : a self-adaptation mechanism a self-adaptive software (sas) is a system that can automatically modify itself in the face of a changing context, to best answer a set of requirements. the selfadaption capacity can be provided by programming languages in the form of exceptions, parameters or conditions. however, adaptation through these mechanisms is application specific, error prone and poorly scalable. in contrast to these mechanisms, numerous external approaches contribute to the development of runtime adaptation of software, like architecture-based techniques which formulate and process changes in an architectural model [2] [3] [4], agent-based approaches which model systems as a collection of autonomous agents [5], reflective approaches, which can observe and modify the composition of a system at runtime [6][7], and modeldriven engineering (mde) which shifts the focus to the eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e1 a dspl design framework for sass: a smart building example 3 figure 1: the dspl process creation and use of domain models, to automate code generation [8][9]. dynamic software product line engineering (dsple) is under the umbrella of mde, as it uses models at runtime to address variability and context changes during system execution. dspl uses software product lines principles to build systems that can adapt to context fluctuation, new user requirements and variant qos states. these principles include software reuse, variability modelling and management, and automatic product derivation. we consider the dspl paradigm the most fitting approach to provide autonomic scalable support for a fleet of connected devices, from design to execution [10]. first, dspls provide a systematic and non-restrictive way to deal with sass [11], also they successfully realize the mape-k loop [12] as tested by bencomo et al. in [13]. besides, on the one hand, monitoring and controlling are the main activities for the fleet management. on the other hand, these same two activities are central tasks in dspls, which makes the paradigm a good fit for the selfadaptation of the fleet. also, with regards to uncertainty, the quality of a product can be measured against user requirements by the mean of goal-based approaches. goal models can represent the system requirements at the domain level of (d)spls, in the form of variable reusable components. furthermore, variability is a key challenge in the management of a fleet of connected things; it takes place at different levels. static variability is concerned with similarities and variations between fleets, while dynamic variability is dealing with the runtime reconfiguration, and temporal variability, describes the alterations of the three dimensions. dealing with variability is by far the greatest asset of dspl, since it adopts essential concepts from spl [14]. 2.3. design principles the first level in the process is the creation of assets. as described in figure 1, a meticulous study of the domain in question helps define the qualities the system should satisfy, while specifying the variability and the variation points. the result of a domain study is the specification of the fleet’s requirements (a). the second level is the creation of the final product. the requirements of each customer are described in formal language. the selection of features is carried out accordingly, and then adjusted to fit the exact needs of the customer. features are finally derived, linked, tested and deployed in order to instantiate the product—the fleet (d). dsple takes the spl process one phase further. each product is thoroughly monitored (c) to determine the structural or behavioural state that dissatisfies requirements. when these are no longer fulfilled, a new configuration is planned (b). this one achieves the optimal satisfaction of primary goals. features are then reselected, re-adjusted, re-derived and re-linked (re-tested and re-deployed) to create a new product—a new configuration for the fleet. this process is repeated whenever the system fails to fulfil requirements, in light of contextual change. d o m ai n l e ve l a p p lic at io n l e ve l (a) product line models (fleet’s reusable assets) (d) product (fleet) (c) device management platform requirements (b) configuration process n monitors & contols plans new configuration produce is subject to eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e1 4 figure 2: a dspl three-dimensional framework from one engineering process to the other, the fleet’s three dimensions, the system, the context and the environment, have different designations, as described and illustrated in figure 2. at the domain engineering level, each one of the concepts contributes to the creation of assets. with regards to the system (1), a domain expert thoroughly studies the domain in order to determine the functionalities the system should provide and qualities to comply with. in this sense, the system is where domains requirements are extracted, which are then translated to goals, features, components or assets. context (2) is where the events that can arise after the deployment of the fleet are abstracted, in order to determine when a reconfiguration is needed. environment (3) holds more generic information about domains and devices. it can contribute to the evolution and extensibility of the system by supporting an open marketplace. this one could supply the system with new components, device specifications, documentation, and other related information. at the application engineering level, deployment, monitoring and controlling aspects take place. in relation to the system (4), for each set of requirements, a product is derived. it reflects the nature of devices involved in the configuration, and their setup. context (5) on the other hand deals with internal change, events and stakeholders that surround the system, and that have an impact on it. devices are monitored in order to determine situations when reconfiguration is required. sensed or calculated information, feedbacks, battery level, computational performance, network and data accessibility, and other characteristics are relevant. devices that are not part of the system, but contribute to its activity are part of the context, user activity and logs also matter, the time and space of the fleet is also responsible of how it is configured. the environment (6), finally, is place to generic information about the surroundings of the system, that might, but still do not have an impact on the fulfilment of requirements. devices around the fleet can be in this category, laws, rules or conditions constrained by a time or place are too, part of the environment. monitoring the environment gives the platform proactive qualities, this helps avoid waste of resources in unnecessary adaptations. 3. a smart building motivational example to cope with the challenges that iot applications face, like heterogeneity, variability and resource constrained environments, the system should have the ability to adapt itself in order to continue offering the needed performance. this is illustrated through the following smart building example: the forester’s family owns a summerhouse, one to which they only go on vacation. the house is equipped with devices that help secure and maintain it in their absence, and provide comfort and convenience in their presence. some of the devices involved in this process work permanently, and others depend on the circumstances in the surroundings. the fleet is composed of the following: to detect and monitor events and changes within or in the surroundings, a collection of sensors are installed around the building. they include smoke detectors and motion sensors, which should always stay active, and temperature sensors, fall detectors and light sensors which are only active when the house is occupied. to react to changes, various actuators were also deployed. they include sprinklers, acs and a noise canceling devices. light that can be controlled manually or automatically, or by opening or closing curtains for natural light. the security is provided by an exterior camera, which can work permanently, or record when motion is detected. water and electricity consumption are also monitored using smart meters, and can be controlled thanks to the switch between the mains provider and the rainwater or battery bank, respectively for water and electricity consumption optimization. and, finally, a control panel is provided to administrators, on premise, locally in the house, or through the smartphone’s app. moreover, in order to serve the different needs of its users, under different circumstances, in a smart proactive system context environnement d o m ai n e n g in e e ri n g a p p li ca ti o n e n g in e e ri n g (1) represent domain requirements (2) update requirements (3) support an open marketplace (6) maintain related domain information (5) capture context data (4) determine fleet devices monitoring, mandatory devices, accuracy brightness, resources level, users new camera specifications forecast, city laws inside temp, elderly presence, user preferences camera on automatic mode, ac are disabled eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e1 a. achtaich et al. 5 manner, the fleet should be self-adaptive. the following scenario can be considered: a. the house is equipped with fall detection sensors, noise canceling devices and in-room cameras. they are not always needed, and should only be activated when the grandmother’s smartphone is detected in the house, in order to monitor her activity, and guarantee her comfort. b. if no one is in the house after coming back from vacation, the everyday features, responsible for adding comfort to the family, by automating certain tasks, are deactivated. only maintenance and security features should be kept active in the fleet. c. to preserve the overall consumption in the building, certain features can be deactivated when not needed, to avoid an overpriced bill. the fleet is considered as a dspl. each configuration of the fleet is a product that shares common characteristics with other configurations, but still answers the specific needs of the customer it serves. figure 3 highlights examples of the various products that can be derived from the dspl, which arise under the different circumstances described above. 4. domain engineering domain engineering (de) lays the groundwork for engineering single software systems. at this level, the requirements of the fleet are defined in terms of common and variable features (devices and their respective configurations). the result of this phase is the dynamic product line, meaning all the possible configurations the fleet can take, along with the rules to manage arising changes in the environment. this section introduces the de related models, and the nature of requirements that can be specified at this level, depending on the dimension they relate to. 4.1. variability model a variability model [15] is responsible for documenting and describing variability. it is an abstraction of the system’s requirements in the form of common and variable features. variability models can be represented in different forms: feature models, goal models, decision models, variation points or in the form of constraints. variability models are a pertinent choice in the context of iot applications, as they represent the (1) system dimension in our framework. they are responsible for describing the various devices that compose the fleet, as well as their configurations (the available options, the activated modes, the embedded devices or sensors, and the parameters and values that are important for its functioning). for instance, the configuration of each device in the smart building fleet is commanded by the following constraints: id (non) functional requirement req1 sensors should always monitor motion and smoke, and could monitor temperature and fall in particular setups. req2 the ac can only function if the temperature sensor is selected req3 the camera can record permanently, or it can be on hibernate mode and only be wakened when motion is detected. a camera installed in the guest room can be activated under certain circumstances. req4 the lightning in the house can either be controlled manually through light switches, or automatically. curtains can be selected, along with one of these modes to avoid unnecessary usage. req5 consumption control can be activated. in might include water control or energy control. req6 controlling the water involves choosing a water source; it can be provided from the mains or from the rainwater reservoir. for a more meticulous monitoring, the water control can track the exact amount through a water meter. req7 controlling the electricity involves choosing a power source; it can be provided from the mains or from the home battery bank. for a more meticulous monitoring, the electricity control can track the exact amount through an electricity meter. req8 the administrators can control the fleet through a local control panel or using their smartphone apps, or both. req9 the fleet should be energy efficient req10 the fleet should be efficient with water consumption req11 the fleet should provide accurate results table 1: variability constraints 4.2. context models context models [16] are central for building selfadaptive systems, as they characterize the status of the different entities that compose the pl. they are used to model the elements of the (2) context dimension of the framework. not only does a context model allow the acquisition and abstraction of context elements, but it also delignates the adaptation logic that links a context to its ideal configuration. today, thanks to the insight that smart sensors bring about their surroundings, we can realistically imagine scenarios like starting a car when the conductor’s smartphone is close or preparing the conference room for a meeting by turning on the lights, eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e1 a dspl design framework for sass: a smart building example 6 opening the curtains, and lunching the appropriate presentation when it is in the agenda. context models are a combination of all context variables, which are abstractions over a part of the system’s context. the values of a context variable are monitored at runtimes, by reporting on events, by sensing change in the context, or by catching device exception. in the case of the smart building fleet, several context elements have an impact on the final product. an example of context elements is presented in the following: id context requirements req12 the fall sensor and the noise canceller are selected when there is an elderly presence in the house req13 when smoke is detected, the sprinklers become part of the fleets req14 camera n°2 is on permanent mode when an elderly presence is detected the house req15 when the water control and water meter are selected, and water consumption is high, the source switches to rainwater req16 when the house is empty, only mandatory sensors and actuators are selected, only manual lightning is selected, only smartphone control panel is active, and consumption control is deactivate req17 when the source of electricity is mains, the electricity consumption is high and the date of the month is superior then the 20 th , battery mode is selected instead req18 when the battery bank level is low, the electricity economy should be switched on req19 the temperature sensor, the ac, lightning through curtains and permanent recording of the are energy consuming table 2: context constraints context models that include spatial and temporal constraints can be used to model the (3) environment dimension of our framework. other models like prediction models and forecast models [17] are also relevant. in the case of the smart building example, environment related information may include statements like: recording a street view is forbidden or water consumption should not succeed 400l per habitant in periods of drought. 4.3. asset marketplace services provided by the fleet are portrayed in the implementation model. they are represented as a collection of reusable programs that provide the functionalities described in the variability model. furthermore, in a fleet of connected objects, managed devices are unknown and unanticipated. therefore, to allow the extensibility of the system, it should be possible to introduce new functions by adding components from the outside, through a secure regulated platform. every operationalization is implemented through a collection of assets. they are reusable components that gather the logic for the implementations in the connected objects. however, in order to properly fit in the framework, this view should provide the means to link the operationalization to a collection of assets, in order to guarantee the extensibility of the system. different assets might correspond to different implementations of an operationalisation; different standards, different algorithms, or different languages. a developer’s open marketplace could host the various components responsible for enabling various services. and interfacing capabilities could link the modelled assets with their respective implementations. 5. application engineering application engineering (ae) starts with the elicitation of requirements for each customer in formal language. features and components are selected accordingly. the list of components is readjusted in case it doesn’t correspond to the exact demands of the customer. the final components are derived, linked, tested and deployed in the form of a product, which can change if and when any change in the context occurs. this section introduces the ae related activities, depending on the dimension they relate to. 5.1. configuration the configuration process corresponds to the selection of features and their corresponding components, in accordance with the users’ requirements. the list of assets is readjusted in case it doesn’t correspond to the exact demands of the customer (by adding or suppressing some of the automatically selected features), then linked. the final components are derived; tested and deployed in the form of a product, which corresponds to the new configuration of the fleet. 5.2. context data the context model is exploited at this level, along with a monitoring platform, which supervises the fleet, captures change that occurs in the surroundings of the devices, and analyzes it. furthermore, it keeps track of the state and physical conditions of devices individually; if an unusual behavior, a contradiction, or an unhealthy pattern is observed, the context model coordinates with the variability model, in accordance with the constraints that bind then, to plan and execute a new set of configurations. eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e1 a. achtaich et al. 7 likewise, a user context model and a behavior monitor could be used to observe the actions of users, and learn their routines and patterns. this learning process could update the requirements at the application level to propose configurations that are more aligned with the realistic preferences of the user. provided as input to the model implementation, context data are the instances that context variables take under certain circumstances. 5.3. environment data unlike context data, which represent information that has a direct impact on the fulfillment of user’s requirements, environment data refers to information and knowledge related to the domain. it does not have a direct impact on the system at a specific time, but might bright insight in particular situations. it is important to grasp and implement such information to make use of it when necessary. 6. model implementation in the following section, we propose an implementation of the models described in the previous section, in the form of a declarative constraint program. each feature in the variability model is defined as a boolean variable [18]. when selected in the final product, the value of the variable is 1, when it is not, the value is 0. %---------defining the reusable features lrc = [smartbuilding, sensor, smoke, temperature1, temperature2, temperature3, light, motion1, motion2, fall, actuator, ac1, ac2, ac3, noisecanceling, sprinkler1, sprinkler2, sprinkler3, lightning, manual, automatic, curtains, camera1, camera2, permanent, inmotion, off, controlpanel, local, smartphone, consumptioncontrol, watercontrol, watermeter, mainswater, rainwater, energycontrol, electricitymeter, mainselectricity, battery], fd_domain(lrc, 0, 1), the variables are constrained with expressions [19]; they translate the predicates expressed in table 1. the collection of variables form a constraint satisfaction problem that can be solved, in order to determine the valuable valid configurations. %---------constraints on features %the root is always selected smartbuilding #= 1, %defining the features related to the smartbuilding smartbuilding * 4 #= sensor + actuator + lightning + controlpanel, smartbuilding * 2 #>= camera1 + camera2, smartbuilding #=< camera1 + camera2, smartbuilding #>= consumptioncontrol, %req5 %the subfeatures of sensor sensor * 3 #= smoke + motion1 + motion2, %req1 sensor *5 #>= temperature1 + temperature2 + temperature3 + fall + light , %the subfeatures of actuator actuator * 1 #=< sprinkler1 + sprinkler2 + sprinkler3, sprinkler1 + sprinkler2 + sprinkler3 #=< actuator * 3, actuator * 4 #>= ac1 + ac2 + ac3 + noisecanceling %the subfeatures of lightning %req4 lightning #= manual + automatic, lightning #>= curtains, %the subfeatures of camera1 camera1 #= permanent + inmotion, %req3 %the subfeatures of camera2 camera2 #= permanent + inmotion, %req3 camera2 #>= off, %the subfeatures of controlpanel %req8 controlpanel *2 #>= local + smartphone, controlpanel #=< local + smartphone, %the subfeatures of consumptioncontrol consumptioncontrol * 2 #>= local + smartphone, %req5 %the subfeatures of watercontrol %req6 watercontrol #= mainswater + rainwater, watercontrol #>= watermeter %the subfeatures of energycontrol %req7 energycontrol #= mainselectricity + battery, energycontrol #>= electricitymeter %the traversal relations (rainwater #= 1 -> watermeter #= 1), (battery #= 1 -> electricitymeter #= 1), (ac1 #= 1 -> temperature1 #= 1 ; ac1 #= 0 ), (ac2 #= 1 -> temperature2 #= 1 ; ac2 #= 0 ), (ac3 #= 1 -> temperature3 #= 1 ; ac3 #= 0 ), non-functional requirements (nfr) are represented as variables that can take several values (from 0 to 4), each value represents a satisficing level, which corresponds to the importance of the nfr for the user. %---------non-functional requirements %req9, 10, 11 lnfr = [accuracy, energyefficiency, waterefficiency], fd_domain(lnfr, 0, 4), %---------constraints on nfr totnfr #= accuracy + energyefficiency + waterefficiency; context and environment models are also translated to variables. depending on the value they take during application engineering, they have various repercussions. %---------context variables lctxt = [elderlypresence, smokedetected, occupiedhouse, mainselectricity], fd_domain(lctxt, 0, 1), fd_domain(electricityconsumption, 0, 2), % 0 = low, 1 = normal, 2 = high fd_domain(waterconsumption, 0, 2), % % 0 = low, 1 = normal, 2 = high fd_domain(batterylevel, 0, 1), % % 0 = low, 1 = normal fd_domain(dayoftemonth, 1, 31), on the one hand, they can condition the selection of certain features, along with their effect on the realization of nfr. eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e1 a dspl design framework for sass: a smart building example 8 %---------claims lcl = [c1, c2, c3, c4], fd_domain(lcl, 0, 1), %---------constraints on claims %effect of features and context values on energyefficiency c1 #<=> (occupiedhouse #= 1) #/\ (temperature1 #==> energyefficiency #=< 2) #/\ (temperature2 #==> energyefficiency #=< 2) #/\ (temperature3 #==> energyefficiency #=< 2) #/\ (ac1 #==> energyefficiency #=< 0) #/\ (ac2 #==> energyefficiency #=< 0) #/\ (ac3 #==> energyefficiency #=< 0) #/\ (permanent #==> energyefficiency #=< 0) #/\ (curtains #==> energyefficiency #=< 3), c2 #<=> (elderlypresence #= 1) #/\ (light #==> energyefficiency #=< 2) #/\ (noisecanceling #==> energyefficiency #=< 1), %req12 , %req14 c3 #<=> (inmotion #==> energyefficiency #=< 4) #/\ (automatic #==> energyefficiency #=< 2), c4 #<=> (electricityconsumption #= 2) #/\ (dayoftemonth #>= 19) #/\ (battery #==> energyefficiency #=< 4), %effect of features and context values on waterefficiency c5 #<=> (rainwater #==> waterefficiency #=< 1) #/\ (mainswater #==> waterefficiency #=< 3), %req17 %effect of features and context values on accuracy c6 #<=> (occupiedhouse #= 1) #/\ (temperature1 #==> accuracy #=< 4) #/\ (temperature2 #==> accuracy #=< 4) #/\ (temperature3 #==> accuracy #=< 4) #/\ (ac1 #==> accuracy #=< 4) #/\ (ac2 #==> accuracy #=< 4) #/\ (ac3 #==> accuracy #=< 4) #/\ (curtains #==> accuracy #=< 1), c7 #<=> (elderlypresence #= 1) #/\ (light #==> accuracy #=< 2) #/\ (noisecanceling #==> accuracy #=< 1), c8 #<=> (inmotion #==> accuracy #=< 1) #/\ (permanent #==> accuracy #=< 4), c9 #<=> (watermeter #==> accuracy #=< 3) #/\ (mainswater #==> accuracy #=< 3) #/\ (mainselectricity #==> accuracy #=< 3) #/\ (electricitymeter #==> accuracy #=< 3) #/\ (curtains #==> accuracy #=< 1) #/\ (automatic #==> accuracy #=< 3), totc #= c1 + c2 + c3+ c4 + c5 + c6 + c7 + c8+ c9, on the other hand, they define how the satisfaction of nfr is bound by context and environment conditions. %---------softdependencies lsd = [sd1, sd2, sd3], fd_domain_bool(lsd), %---------constraints on softdependencies sd1 #<=> (waterconsumption #= 2 #==> waterefficiency #= 4), sd2 #<=> (electricityconsumption #= 2 #/\ batterylevel #= 0) #==> energyefficiency #= 4), sd3 #<=> (electricityconsumption #= 2 #/\ waterconsumption #= 2) #==> accuracy #= 4), totsd #= sd1 + sd2 + sd3, %constraints on the ensemble: {claims, nfr, softdependencies} all #= totc + totsd + totnfr. finally, after instantiating the context variables, and depending on the wishes of the user, which might be, for example, (i) any valid product, (ii) the best product, (iii) the product that satisfies most the nfr energy efficiency, a configuration can be obtained by lunching a function that solves all the constraints, and proposes (i) a random result, (ii) the best result or (iii) the result for a energyefficiency=4. 7. related works to face the growing complexity of iot environments, several researchers have identified the need for frameworks and architectures that support the management of fleets of cooperative devices, considering self-adaptation a core requirement. inox [20] combines iot and service architectures to provide enhanced application and service deployment capabilities. the architecture enables the service and network infrastructure with self-management capabilities. in [21], the authors propose an architecture, where agents collect data about protocol operations, measurement-based learning assess the optimality of the control parameter and if necessary, adaptation is realized by applying the new policies to agents. the focale project [22] introduces an architecture for orchestrating the behavior of heterogeneous distributed resources. data models support the derivation of different models from a core model, and ontologies reason about the change. the ace model, proposed in the cascadas project [23], defines a agent-based architecture that enables service components to dynamically adapt their behavior based on their context. in [24], a cognitive management framework finds the optimal way to deliver an application in different contexts by enabling the reuse of virtual objects. with the exception of the focale project, none of the above frameworks realize proactive adaptation. furthermore, in the discussed architectures, no mechanism was proposed to validate the need for intelligent adaptation. finally, variability is not considered a fundamental concern, thus not managed. several dspl based architectures can also be found in the literature. in [25], a dspl based architecture, combined with preference based reasoning, provides the necessary mechanisms for reasoning about change; this allows the realization of decentralized self-managed system. gaia-pl [26] is an extension of the gaia platform for the analysis and design of multi-agent systems in active spaces. a requirement specification pattern captures the behavior of a system in dynamic conditions, and reuses the software assets for future similar systems. in [27], the author proposes a multi-view blueprint architecture, a basis for future smart city projects, based on the soasple [28] framework for run-time variability management of service-oriented software product lines. finally, authors in [29] propose a spl based process for the development of connected devices, defined by the means of cvl, to provide reuse mechanisms for the development of a family of agents. in contrast with the aforementioned (d)spl based approaches, our framework introduces variability eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e1 a. achtaich et al. 9 management at different stages of the process, as explained previously, including static (devices), dynamic (configurations) and time-bound (dimensions alterations) variability. none of the proposed spl based approaches introduce the environment dimension, necessary for a smart proactive adaptation. 7.1. conclusion and future work the iot paradigm enables advanced applications by interconnecting multiple devices that interact with their environment, and coordinate to provide the needed services. the smart city is one of the major targets of the iot, as it gathers countless devices that constantly collect information, and thus can provide various cutting-edge benefits. however, the needs of end-users are divergent and the context conditions fluctuant. therefore, supplying connected devices with the necessary mechanisms to answer the complex needs of each customer, and readjust their behaviour in the face of resource shortage, internet interruptions or service unavailability becomes essential. implementing fleets of connected devices as sass is not completely new in research nor in industry, the design of such platforms however, remains problematic. this paper proposes a framework to design adaptable applications for the iot, in order to tackle the problem of dynamic variability. on the one hand, it takes into account the specificities of requirements for a fleet of iot systems, which can be related to the system, the context or the environment. and, on the other hand, it follows the fundamentals of dsple; domain engineering and application engineering. a preliminary proof of concept smart building example was used to illustrate the requirements concerned by each dimension of the framework. and finally, a constraint program implements the example, in order to demonstrate how each model can be analysed and resolved. nonetheless, some of the framework’s main concepts are still not represented using the existing models. prediction, behavioural learning, model auto-update, among other capabilities, are still not formulated. refas [30], is a goal-based modeling language implemented in variamos [31]. it allows modeling requirements for self-adaptive software systems as dspls, from different points of view. as it implements most of the concepts to instantiate our framework, our future work includes extending its notation, with the missing concepts that allow the specification of all the needed requirements. acknowledgements. this work was supported by the moroccan « ministère de l’enseignement supérieur, de la recherche scientifique et de la formation des cadres », by the « french embassy in morocco », and by the « institut français du maroc ». references [1] g. h. alférez, v. pelechano, r. mazo, c. salinesi, and d. diaz, “dynamic adaptation of service compositions with variability models,” j. syst. softw., vol. 91, no. 1, pp. 24–47, 2014. 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[26] j. dehlinger and r. r. lutz, “gaia-pl: a product line engineering approach for efficiently designing multiagent systems,” acm trans. softw. eng. methodol., vol. 20, no. 4, pp. 17:1–17:27, 2011. [27] m. abu-matar, “towards a software defined reference architecture for smart city ecosystems,” 2016 ieee int. smart cities conf., pp. 1–6, 2016. [28] m. abu-matar and h. gomaa, “an automated framework for variability management of serviceoriented software product lines,” proc. 2013 ieee 7th int. symp. serv. syst. eng. sose 2013, pp. 260–267, 2013. [29] i. ayala, m. amor, l. fuentes, and j. troya, “a software product line process to develop agents for the iot,” sensors, vol. 15, no. 7, pp. 15640–15660, jul. 2015. [30] j. c. muñoz-fernández, g. tamura, m. raúl, and c. salinesi, “towards a requirements specification multi view framework for self-adaptive systems,” comput. conf. (clei), 2014 xl lat. am., vol. 18, no. 2, pp. 1– 12, 2014. [31] r. mazo, c. salinesi, d. diaz, j. c. muñoz-fernández, l. rincón, c. salinesi, and g. tamura, “variamos: an extensible tool for engineering (dynamic) product lines,” in proceedings of the 24th international conference on advanced information systems engineering (caise forum’12), 2015, no. june, pp. 374–379. eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e1 a. achtaich et al. 11 figure 3: examples of the smart building configurations sensor smart building fall temperature smoke motion lighning curtainsmanual automatic actuator noisecanceling ac control pannel local smartphone watercontrol rainwaterwatermeter mains energycontrol batteryelectricitymeter mains camera permanent in-motion consumptioncontrol sprinkler 1..2 off requies 1..2 1..* 2..2 light 1..* requies requies excludes sensor smart building fall temperature smoke motion lighning curtainsmanual automatic actuator noisecanceling ac control pannel local smartphone watercontrol rainwaterwatermeter mains energycontrol batteryelectricitymeter mains camera permanent in-motion consumptioncontrol sprinkler 1..2 off requies 1..2 1..* 2..2 light 1..* requies requies excludes sensor smart building fall temperature smoke motion lighning curtainsmanual automatic actuator noisecanceling ac control pannel local smartphone watercontrol rainwaterwatermeter mains energycontrol batteryelectricitymeter mains camera permanent in-motion consumptioncontrol sprinkler 1..2 off requies 1..2 1..* 2..2 light 1..* requies requies excludes (a) (b) (c) optional alternative cardinality or-relation i .. j requires excludes mandatory sensor smart building fall temperature smoke motion lighning curtainsmanual automatic actuator noisecanceling ac control pannel local smartphone watercontrol rainwaterwatermeter mains energycontrol batteryelectricitymeter mains camera permanent in-motion consumptioncontrol sprinkler 1..2 off requies 1..2 1..* 2..2 light 1..* requies requies excludes eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e1 a dspl design framework for sass: a smart building example use of the cellular automatons (ca) for the discrete simulation of urban sound waves propagation in the smart cities context eloi bandia keita 1, bernard pottier2,∗ 1institute of technology (iut), paris descartes university and lab-sticc (laboratory , ubo), france 2university of brest, brest (ubo), france lab-sticc abstract this paper deals with the problem of sound propagation in urban areas, a real tool leading to smart cities design. it begins by studying the propagation of sound in order to determine and extract the physical parameters that direct this propagation. then it deals with the formalism of cellular automata and their relation to the specification of physical phenomena with discrete events, such as sound propagation. then, this technique (cellular automata) is used in a smart city context, to model the propagation of sound, taking into account buildings and other various city obstacles. an implementation is made in cuda, to simulate this phenomenon on shapefile cards. this work ends with the determination of the sound power in a given location and the geographic area covered by the sound wave. received on 8 august 2017; accepted on 10 october 2017; published on 20 december 2017 keywords: wireless sensor networks, cellular automata, sound propagation simulation, graphics accelerators, parallel programming copyright © 2017 eloi bandia keita and bernard pottier, licensed to eia. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.20-12-2017.153497 1. introduction physical world and information systems unification is a major achievement during this last decade. communication systems, especially wireless technology, and research in physical sensors field have taken a major part in this integration. the interface between the physical word and a computer can be used in two ways. first, from a local perspective, where such a system can control for instance a single object or provide a personal assistance. moreover, in a distributed system, this interface collects and analyze sparse data to make decisions, for instance about resource savings : to turn off streetlights, to guide to a parking spot. wireless sensor networks are part of this second category. thus, this thesis is focused on sound hdr. eloi keita is currently teaching at the institute of technology (iut), paris descartes university. he is an associate member of lab-sticc in the wsn unit of professor bernard pottier, in brest. ∗corresponding author. email: eloi.keita@laposte.net propagation simulation in urban environment, in a distributed manner. the key point of this work is a cellular representation of the city in order to model streets, gardens, ring roads, buildings, and rivers. geo referenced image analysis, complemented by database consultation, for example to retrieve elevation data, generates this cellular model. then, this model is converted into a system made of interconnected processes, that can reproduce many collective behaviors, whether physical or digital. we have developed a cellular automata that models sound propagation, including reflection and refraction, working on a graphics accelerator. finally, we have produced a coupling method between observation systems by sensor networks and physical systems. 2. background 2.1. sound propagation the displacement of a sound wave from one place to another is the transportation of energy, without the transportation of matter. during propagation, at any 1 eai endorsed transactions smart cities research article eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 http://creativecommons.org/licenses/by/3.0/ mailto:<eloi.keita@laposte.net> e. b. keita, b. pottier point reached by the wave, the air reproduces the state of the source with a smaller amplitude and a time delay related to the duration of the journey. the delay is a result of the speed of propagation and the distance separating this point from the source. the propagation of the wave implies: 1. that the surrounding environment is the source plastic, a vacuum does not allow propagation of the sound wave, 2. that the source is in a vibrational state: without vibration, there is no generation of sound propagation. in a compressible medium such as air, the sound propagates under the form of a pressure variation created by the sound source (figure 4). only the vibration, without displacing the material, is transmitted from point to point between the object that emits the sound and our ear. the sound wave consists of a fundamental and of harmonics that permit the differentiation of different sounds. sound wave also propagate through solids and liquids, (but not in a vacuum) in the form of the vibrations of atoms called photons. here also, only the vibration propagates itself and not the atoms which only vibrate around their equilibrium position. spatial properties of sound waves . the spatial characteristics of propagation are the following : • a wave propagates itself, from its source, in all directions possible, • the disturbance transmits from point to point, according to the current frequency • the transfer of energy operates without the transport of matter, the waves cross each other without disturbing each other • the wave propagation speed is a property of the propagation medium. all sounds (infrasound, sound, ultrasound, hypersounds) propagate identically on the same principle. several changes take place during the transportation of the sound wave: reflection, diffraction, refraction, interference, absorption and diffusion. parameters related to the architecture of the city as urban barriers to sound propagation such as: walls, streets, trees, parks, .... will generate modifications that we will detail. reflection when a sound wave encounters an obstacle, there is a reflection. the incident wave is reflected and creates a second wave identical to the first, but in a different direction. the phenomenon of reverberation or echo describes an exaggerated and unpleasant persistence of sounds linked to successive reflections bringing the incident wave back to its starting point. the generalized law of reflection reads: sin(θr) − sin(θi) = λ/(2πni) · dφ/dx, where θi represents the angle of incidence to be θr represents the angle of reflection we have dφ/dx representing the phase gradient introduced suddenly at the interface and n the normal vector of the incident plane. diffraction when a sound wave is close to an obstacle, it produces a bypass phenomenon. the terminals of the obstacle become sources of secondary waves, which are described as diffracted waves. intuitively, this is a bypass phenomenon of the obstacle. (a) reflexion of a wave (b) diffraction figure 1. diffraction reflection refraction the refractive phenomenon is due to a change to a medium of a different nature. the wave is deflected, its direction modified. one obtains a refracted wave because of the difference in propagation speed of the two medium. this modification also produces a reflected wave. a portion of the energy being absorbed by the obstacle, so these secondary waves are often less intense than the incident wave. the generalized law of refraction is therefore described thus: n2 · sin(θ2) − n1 · sin(θ1) = λ/(2π) · dφ/dx, où dφ/dx (meaning that: d(phi) / dx) represents the gradient of the phase introduced in a sudden fashion to the interface. absorption this phenomenon is related in part to the phenomena of successive reflections and refraction of the sound wave. an absorbing medium can be used to mitigate or even eliminate certain sound waves. similarly a denser propagation medium allows one to obtain a higher speed of sound waves. interference by generating multiple identical sound sources located at a certain distance from each other one observes a predictable interference phenomena from the equation of elementary sources. 2 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 discrete simulation of sound propagation in the city base on celullar automaton for the smart city diffusion three types of diffusion are observed when a sound wave propagates depending on the relationship of the wavelength / height and structure of the obstacle: • back-scattering: here the wavelength is greater than the size of the obstacle (when the wavelength is greater than the obstacle, the sound wave is reflected in multiple directions) • ante-grade: here the wavelength is equal to the size of the obstacle, • multidirectional: here the wavelength is smaller than the size of the obstacle. this latter multi directional diffusion is that which is the most common and most important during the propagation of sound waves in the city. these main phenomena related to the propagation of a sound wave usually occur when an obstacle is encountered by the wave. taking into account the complex architecture of a city, our simulations will simplify the parameters by only considering the walls of buildings, trees and open spaces such as streets or parks. in a city, the propagation of sound waves is constantly deflected because the wave is exchanging with the medium and regularly meets obstacles. propagation is dependent on the nature of the medium in which the sound wave is propagating. elementary metrics : frequencies, wavelength, amplitude, intensity . if we consider a sound wave q. the equation for its elongation x in relation to time: x = a.sin(ωt+ ϕ) a is its maximum elongation, ω is the pulsation, (ω = 2π/t = 2πf) in radian per second and ϕ s the phase shift ( in radian) at the moment t0. figure 2. element of evaluation of a sound wave. if the sound source vibrates in a sinusoidal manner, on the frequency f, the acoustic pressure, at any point p of the sound field (the space surrounding the source) is a sinusoidal function of the time of the same frequency f: pac(t) = psin(ωt+ ϕ) ou pac(t) = peff2sin(ωt+ ϕ) 2.2. discrete simulation a discrete-event simulation models the operation of a system as a discrete sequence of events in time. each event occurs at a particular instant in time and marks a change of state in the system. between consecutive events, no change in the system is assumed to occur; thus the simulation can directly jump in time from one event to the next. this contrasts with continuous simulation in which the simulation continuously tracks the system dynamics over time.instead of being event-based, this is called an activity-based simulation. time is broken up into small time slices and the system state is updated according to the set of activities happening in the time slice. because discrete-event simulations do not have to simulate every time slice, they can typically run much faster than the corresponding continuous simulation. so, in the discrete event simulation, something has to happen so that we can observe and make decisions. it is these moments of modification of the state of the system which is called the event. 2.3. cellular automata formalism cellular automata (ca) were originally conceived by ulam and von neumann in the 1940s to provide a formal framework for investigating the behaviour of complex, spatially distributed systems [1]. cellular automata constitute a dynamic, discrete space, discrete time formalism. space in cellular automata is partitioned into discrete volume elements called cells and time progresses in discrete steps. each cell can be in one of a finite number of states at any given time. the âăijphysicsâăi̇ of this logical universe is deterministic and local. deterministic means that once a local physics and an initial state of a cellular automaton has been chosen, its future evolution is uniquely determined. local means that the state of a cell at time t+1 is determined only by its own state and the states of neighbouring cells at the previous time t. the operational semantics of a ca as prescribed in a simulation procedure and implemented in a ca solver dictates that values are updated synchronously: all new values are calculated simultaneously. the local physics is typically determined by an explicit mapping from all possible local states of a predefined neighbourhood template (e.g., the cells bordering on a cell, including the cell itself), to the state of that cell after the next time-step [2]. 2.4. the characteristics of sound waves according to stanley a gelfand [3] sound is defined as a wave that travels through the air in the form of a pressure variation, without material displacement. an example is the vibration of the diaphragm in loudspeakers that transcribes a periodic electrical signal in successive compression and decompression of the air. sound wave 3 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 e. b. keita, b. pottier also propagates through solids in the form of tiny vibrations of atoms. there are several types of sound, with regard to human hearing and vibration frequency: • infra-sound : below 20 hz one encounters infrasound that we do not hear. some animals such as elephants, giraffes, whales etc ... may apply the emit and receive up to 10 hz. infrasound is a physical reality and can lead to massive destruction at certain frequencies [4]. • sounds of 20hz to 20 khz are inaudible to humans. according to [5] blauert, is a sound has a frequency that our ears can sense and interpret, the best sensitivity of human hearing is situated at around 3 khz with an intensity of about 10 db. • ultrasound from 20 khz up until megahertz: ultrasound lies beyond 20 khz and goes up to 1000 khz. bats, dolphins and other animals emit and capture ultrasounds of 50khz to 150 khz. • hyper-sound are defined by frequencies beyond several thousand mhz. sound frequency ranges figure 3. representation of different types of sound waves. definition of the physics of sound. sound is a longitudinal mechanical wave, a periodic disturbance resulting from the propagation of the vibration of material objects in an elastic medium such as air, water or a solid. it can also be decomposed into elementary sounds that give off wave "noises" that are perfectly periodic, and sinusoidal. the equation for the elongation of the sound wave as a function of time is x = asin(ωt+ ϕ) a is the maximum elongation, ω is the pulsation, (ω = 2π/t = 2πf) in radian per second and ϕ is the phase shift ( in radian) in the instant t0. physics of sound propagation figure 4. physical form of pressure waves. a. the wave equation and the law of evolution for propagation to one dimension the partial differential equation (alembert equation) is given by: ∂2u ∂x2 − 1 v2 ∂2u ∂t2 = 0. (1) for all "f" and "g" functions (assumed regular) there is a solution (with a speed v, but without amortizing or mitigation) which is a function of 2 unknown, "x"(spatial) and "t" (temporal): u(x, t) = f(x+ vt) + g(x− vt). b. common parameters of all sound waves these parameters are common to all wave phenomena. they 4 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 discrete simulation of sound propagation in the city base on celullar automaton for the smart city are: the wavelength, frequency, speed or velocity of propagation. the relationships between these three variables are also common: the speed is equal to the wavelength multiplied by its frequency. if one is interested in pure sinusoidal waves, it is possible to qualify several other characteristics: the original spatial direction, the intensity, also called volume or loudness. other properties related to perception and composition are tonal pitch and spectral pitch: the pitch of a pure sound corresponds to its vibration frequency (in hertz or hz, as the number of periodic vibrations per second) according to claude abromont and eugene de montalembert in "guide to music theory"[6]. in [3] by stanley a gelfand and in [5] by jens blauert, the authors consider that pitch perception relates to the domain of psycho-acoustic studies and highlight two types of perception of the pitch of a sound: • the perception of spectral pitch: audible sound oscillates roughly between bass and treble, we can classify all the sounds on a scale; • the perception of tonal pitch: fairly accurate differentiation of two sounds relatives heard, regardless of their content grading of bass sounds and treble sounds. note that the more rapid the vibration of the sound source, the more that the sound will be treble or high. in contrast, the slower this vibration, the sound will be more deep or bass; the rhythm: the rhythm, the sound field is the audible movement of the matter of a sound. the music is dependent on and linked to rhythm but rhythm also exists outside of the music [6]. when there is a succession of sounds and silences of different duration, there is rhythm, while there is not necessarily a melody. by contrary, there can be no melody without rhythm, a continuous sound is not musical. sound without rhythm is a meaningless wail, but a rhythm and a sound are sufficient to constitute an elementary form of music. the timbre: the timbre of a sound can be defined as the intrinsic colour of the sound, its identity. it varies according to the sound source, irrespective of the first three features. acoustically and psycho-acoustic the timbre is a very complex concept that depends on the correlation between the fundamental frequency and the harmonics (or partial, according to its relation with the fundamental frequency). the timbre of the human voice is defined as the set of features that help to identify it.[5]. the variation of only one of these parameters produces a perception of different sound. in acoustics, the strength of a sound is measured in decibels, it is a quality linked to a simple correspondence with that which the human ear perceives. this measure is relative to the noise [5], 0 decibel (0db) corresponding to the minimum audible to the human ear. one should note the psycho-acoustic study of theperceived sound intensity is in the light of a given sound physics. these sensations of strong, weak, soft or high sounds are linked to the effective value of the sound pressure. c. sound as a spatio-temporal phenomenon there is a direct relationship between space, time and sound: sound travels through space based on a variable time [3]. we recognize three main classes of sounds or acoustic signal: 1. impulsive: signals that are not repeated in time and have a fixed envelope. 2. periodic signals in which the form is repeated through time. 3. : aleatory : signals which are not periodic.. we will pay particular attention to the class of impulsive sound signals in another part of this study. (a) sound wave train (b) wave length figure 5. trigonometric representation of physical sound 3. related work in [2], authors discuss the formalism of cellular automata and their relation to the specification of discrete event systems. in this work, both the cellular automata(ca) and the devs(discrete event system specification) and parallel devs formalisms are introduced. then, a mapping between cellular automata and parallel devs is elaborated. this fills in the ca -> devs edge in the ftg(formalism transformation graph). the mapping describes ca semantics in terms of parallel devs semantics. as such, it is a specification for automated transformation of ca models into parallel devs models, 5 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 e. b. keita, b. pottier thus enabling efficient, parallel simulation as well as meaningful coupling with models in other formalisms. authors of [7] investigate several aspects for efficiently implementing a sound propagation processor as a nonlinear cellular network. starting from a partial differential wave propagation equation, they define an equivalent cellular array to simulate a certain 2dimensional scenario space where various obstacles and signal sources may be positioned arbitrarily. the defining equations in the initial model with 5 state variables per cell are redefined into a much faster model with 2 state variables per cell. in [8], authors deal with the sound event detection in a noisy environment and present a first classification approach. detection is the first step of their sound analysis system and is necessary to extract the significant sounds before initiating the classification step. they present three original event detection algorithms. among these algorithms, one is based on the wavelet and gives the best performances. they evaluate and compare their performance in a noisy environment with the state of the art algorithms in the field. then, they present a statistical study to obtain the acoustical parameters necessary for the training and, the sound classification results. the detection algorithms and sound classification are applied to medical telemonitoring. 4. towards an interweaving of urban sounds the first part of this paper presents partitioning techniques and a generation of cellular systems. these techniques can be applied to the urban environment and apprehended through electronic maps or aerial photos, or more directly by querying geographic information systems. these cell systems will represent elements such as streets, buildings, gardens, waterways, public or commercial facilities: schools, stadiums, shops and supermarkets ... the capture of physical information is also on the agenda although its mapping is less publicly present. the equipment related tosmart cities its development in recent years is: electronic parking management by wireless sensor networks, but also detection of air pollution or detection and control of night lighting .... the purpose of this paper is a proposal for modelling and simulation of the propagation of sound waves in urban areas and its implementation on parallel architecture. this proposal is of course based on the concepts outlined in the 3rd chapter of my thesis . 1 mapping sound is obviously more difficult than the analysis of more static data. sound is essentially a transient phenomenon linked to a 1http://faqbr.com/pub/modeles_physiques_et_perception_analyse_du_milieu_sonore_urbain_pdf.html physical cause, of which the duration may be brief (the passage of a motorbike), very short (a cry), recurrent (recreation in a school yard) or quasi-steady (road). the simulation of the sound can be used as a prediction for noise pollution and for the coupling of diagnostic or monitoring networks. some of these are already classified. the national gis propose thus some segments documentation of noise nuisance in proximity to circulation routes [9]. figure 6 presents two systems of cellular sounds calculated using official gis cartelie [9] in the proximity of the university of brest. (a) zone 1 (b) zone 2 figure 6. two joint sound cellular systems extracted from public mapping. one can recognize at the centre of zone1 a road intersection, at the extreme right side, a bridge which diffuses the pollution on a larger scale.. 4.1. classification of propagation elements sound mapping can therefore serve to improve wellbeing by permitting the reduction or isolation of pollution/nuisances. this mapping could also enable the follow up of exceptional/unusual or regular events and to intervene and advise regarding digital augmentation for the hard of hearing. for the analysis of noise, we can build on zones with differentiated features that we configure in cellular systems, for example: • obstacle free zones where the sound propagates freely, • wooden or vegetative zones that are able to reduce sound propagation • walls of buildings with the capacity to block propagation or otherwise to perform a propagation with particular physical characteristics or a reflection, • specific zones of activities, noise generators. for a given cellular system, for harnessing a propagation, the first task will be to determine the characteristics of the diffusion of a wave emitted by a source. a more complex situation is obtained by the composition of the different cellular systems that will 6 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 discrete simulation of sound propagation in the city base on celullar automaton for the smart city filter the sound by transforming it. these compositions derive from representations of urban structures or three dimensional topography in the zones of interest. this chapter will present results concerning the cellular modelling of sound and its simulation with regard to simplified features formed in urban areas conductrices (open air) and obstacles (walls). the bibliography concerning the cellular sound approach will also be used to explain how to simulate the propagation of sounds according to the parameters applicable to complex systems. from the simulation results, we can make several estimates. one can in this instance decide on: • the zones of perception : these zones correspond to surfaces on which a sound is audible from the sound source. these are areas such as car parks or sports grounds; • disturbances: these are disturbances related to the propagation of sound waves such as buildings, walls, metal structures; • parasitic propagation : here we envisage the detection and location of undesirable sound waves that are able to be superimposed on a sound. this detection can be done at the level of frequency differences, of intensity and location of the sound source; • reflections, refraction, diffusion : these are phenomena related to the propagation of sound waves in an environment not free of obstacles, which will be calculated here on the basis of the barriers to the propagation, typically buildings. 4.2. quantitative application motivation the upstream result of the specific deployment of physical sensors, several benefits are expected from this evaluation : • maps of noise pollution (for example usable for urban planning) : noise pollution/nuisance is an important social and health threat. this nuisance is often the consequence of human activities such as excessive urbanization, transport (figure6) industrial activity. by intervening in the planning of urbanization, it is possible to improve the impact of noise pollution in a significant manner ; • alerts regarding critical events: it could be repeated shouts, noise from accidents or explosions. . . it is then necessary to construct a means of automatic alert, integrating the location of the source and signalling to it the competent authorities. regarding extreme measures, it is also necessary to think of the disaster areas and the need to find victims using sound signals; • statistical observation: involves obtaining quantitative and eventually qualitative information, the physical sound itself being information that enables porter other information from a higher level. it is then captured and / or stored, possibly to convey information based on the use or need envisaged, in accordance with legal provisions. noise has always been a significant physical signal, the indian "listened" to the vibration of the rails or gallops. automatic perception enables similar diagnostics, perhaps at a level that is superior to vision. the flow of automobile traffic thus has certainly more sound signatures characteristics in the absence of vehicle, of normal flows or congestion. 4.3. social signification of sound the sound is a natural environmental phenomenon, a richly composed, multifaceted world. sounds tells the story of the city by drawing our way of living by other means than pictures or writing. it often signals the presence of life and many other things in space and time. this is data that can be interpreted in conjunction with other information, such as geographical, for example. sound can be considered as a critical element in an information system. one can list a few pointers here: traffic, passengers in public transport, public works machinery, factories, the tiny beating heart heard by the obstetrician, the ambulance sirens, children in a recreation yard, a square, a summer camp, passing aircraft, the domestic life of the inhabitants, markets, events, parties, mass movements, wild animals in the forests, birds, thunder, wind, ringtones, footsteps in the corridor, the rhythmic variations of urban transport, sudden braking on the asphalt ... a social environment sometimes bears startling acoustic contrasts depending on the moment, of the period or the place. these contrasts reflect difference organizational order and are indicative of a social environment. in making a geographical correlation in areas of interest with historic sounds, can lead one to observation of the sound mapping of this area and its identification. this map is a witness of a human geography, social behaviour, a living environment. we deal in this chapter with a new way of appropriating our environment through its sound identity. we will look at different aspects of city noise and the interactions with these sounds: sound capture for listening, for a virtual walk, based on the study of the propagation of urban or even rural or local sound waves. research new techniques for capturing and analyzing the sound identity of our environment, an environment with countless phonic signatures. 7 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 e. b. keita, b. pottier temporal and spatial location in the situation of the overall sound environment with the ability to stop on a detail, to amplify, affirm or refine a sound signature : sounds of natural elements, foreign languages in transitory or commercial environments. reality at any given time is thus interpreted to emphasize a particular event, an indication, a signal, an identity, etc. a social environment without noise would be to follow a televised musical concert with it sound cut. to be able to convey meaningful sounds in the city is an important element in the information society of the future. 4.4. physical propagation simulation approach we have chosen a cellular model proposed by radu and ioana dogaru in [7]. the proximity to the cellular automaton being used is a von neumann radius 1 with neighbourhood cells consisting of north, south, east and west. the variables of state of the cells include the presence of buildings, one or more source (s) sound (s), physical parameters specifying a sound. the transition function operates on the parameters of mitigation and diffusion of the sound wave, by reconstructing the local developments thereof. a practical realization has been constructed, including cellular systems integrating data from an image extracted from navigation on openstreetmap in the city of brest. each pixel is associated with a zone of a few meters wide depending on the scale of the map, eg 45m wide for each pixel for the first simulation shown figure 9. it has a map of the buildings in the city provided in the form of shapefile, file format, nearly 80,000 polygons (buildings) represent thus potential obstacles for sound. the simulation allows exploration fictive interactive through a virtual microphone that reproduces the sound simulated after propagation, and all this in arbitrary locations. before going into the details of the simulation, however, it is necessary to look at the physical nature of sound and its discrete data abstraction. 5. simulation of sound propagation by cellular automata cellular automata constitute a way to model complex systems such as the phenomenon of wave propagation, diffusion or gas flow. the reason is that the spatial influences are calculated locally like the real physical phenomenon. in a model of propagation simulation by cellular automata, we consider a spatial grid of cells that evolve according to their state and the state of their immediate neighbours. a complete cellular model is a scenario in which the spatial dimension integrates: • the existence of cardinal directions and positions reachable from the cells; the neighbourhood used for the sound modelling is avon neumann of radius 1. • changes in the state including the context, barriers, walls, trees as well as noise sources. regarding the discrete space, it will be necessary to give each cell a transition function to enable the description of its changes and evolution. the space is therefore represented by a planar array of cells. this grid could, however, be constructed in three dimensions. each cell can, at any given time, be in a finite number of states. the update rules are the same for all cells. each time the rules are applied to the entire network a new generation is produced. figure 7. cell matrices. 5.1. transition function: neighbourhood, pressure and speed conforming to the proposition put forward by radu and ioana dogaru in [7], we are assuming partial differential equations 8 representing the equations of sound waves, then we define the discrete sound propagation model. 5.2. interpretation of sound diffusion this interpretation is the target of a simulator which generates sound waves in an urban environment. these waves travel from place to place, are reflected or amortized. the findings of these changes are the subject of the simulation, for diagnosing the power of the sound, for example. several levels of explanation can be distinguished with respect to the simulation: 8 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 discrete simulation of sound propagation in the city base on celullar automaton for the smart city figure 8. partial differential equation (the alembert formula). figure 9. propagation simulation in brest: the map of the buildings is shown on the right, while the mottling to the left represents the pressure pockets of a sound source. this landmark has its concentric circles south of the centre of the cellular automata. 1. the parallel, abstract model, which is that of the cellular automata, 2. the sequential execution of this model where we pass from one plane at the moment t to the following plane at the moment t+ 1, with second plane being produced by scanning rows and columns, 3. parallel execution where transformations are performed on a parallel machine. it is of course interesting to observe the relative performances of the two executions, given the ambition in terms of the computational load. we have used various studies from the two procedures. 6. sequential implementation and validation 6.1. state of a cell and transition function the parameters of the state. each cell is updated at each discrete time step according to a rule of local interaction. first, the particle velocities in the four directions are updated as a function of time, in accordance with the pressure difference between neighbouring cells. the rule for updating is given by: [10] v ′a(x, t+ 1) = v a(x, t) − p (x+ dxa, t) − p (x, t) . is going to represent the particle velocity and p the sound pressure. the position of the cells is expressed as a vector (x) in steps of discrete time (t). the suffix (a) in dxa represents the index of the four neighbours. the particle velocity obeys also: v a(x, t+ 1) = (1 − d).v a(x, t+ 1) this formula expresses the linear energy dissipation mechanism [10]. this state integrates the sound pressure p. the update of this pressure during the cellular automaton stages is written: p (x, t+ 1) = p (x, t) − c2 a ∑ a v a(x, t+ 1) with ca = the speed of waves traveling in the ac area , va represents the particle velocity and p is the sound pressure. the absorption coefficient (or constant amortizing of the sound in the obstacle) is another parameter of the cell. in the case of air, one uses : d = 0.0001 this coefficient can reach up to 0.8 for current urban obstacles. in cfl conditions (current-friedrichs-lewy or richard current’s number), dimensionless numbers . according to toshihiko komatsuzaki in "modelling of incident sound wave propagation around sound barriers using cellular automata" we have : in the case of a one dimensional pattern: co = v∆t ∆x with : v (speed in the direction "x"), deltat (time interval) and deltax (dimensional interval). for dimensional patterns (n, here 2), the equation is written as : co = ∆t ∑n i=1 vxi ∆xi . the values of each dimensional interval can be chosen independently of each other. the speed of sound in air under normal circumstances at 20 degrees celsius: c = 344m/s for the cellular automaton, under cfl conditions the maximum wave velocity becomes: ca = 1/âĺž2. we can therefore take a speed, for reasons of applicability, inferior to 1/âĺž2 vca = 0,688 – (so, dx/dt = 500) with vca = the selected speed of the cellular automata . with this data, we propose that the code can be written as follows : void step ( i n t i , i n t j ) { double p , v0 , v1 , v2 , v3 ; 9 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 e. b. keita, b. pottier comparison :physical system ac model systems speed of sound steps of time size cells physical c = 344 [m/sec] dt = 1/344 [sec] dx = 0.001 [m] ac 2-dim c < 1/âĺž2 [cell/step] dt = 1 [step] dx = 1 [cell] table 1. parameter equivalence: comparison of the parameters defined in the automaton with those of the physical system [10]. i f ( s [ i ] [ j ] == 0) /∗ p = p[ i ] [ j ] ; // −−−−−−−−−−−−−−−−−−−// p r e s s u r e : p [h ] [w] a = a[ i ] [ j ] ; // −−−−−−−−−−−−−−−−−−−// a t t e n u a t i o n a[h ] [w] v0 = p − p[ i −1] [ j ] ; v1 = p − p[ i ] [ j −1] ; v2 = p − p[ i +1] [ j ] ; v3 = p − p[ i ] [ j +1] ; v0 = v0 ∗ (1−a ) ; v1 = v1 ∗ (1−a ) ; v2 = v2 ∗ (1−a ) ; v3 = v3 ∗ (1−a ) ; p = p − ( ( 0 . 4 0 ∗ 0 . 4 0 ) ∗ ( v0 + v1 + v2 + v3 ) ) ; ∗/ v0 = p[ i −1] [ j ] ∗ 0 . 9 7 ; //−−−−−−−−−−− // 0 . 9 7 (> 0 . 5 and < 0 . 9 9 ) = 1−a ( a lgor i thm ) v1 = p[ i ] [ j −1] ∗ 0 . 9 7 ; v2 = p[ i +1] [ j ] ∗ 0 . 9 7 ; v3 = p[ i ] [ j +1] ∗ 0 . 9 7 ; p = 0 . 5 0 ∗ ( v0 + v1 + v2 + v3 ) − pnmoinsun [ i ] [ j ] ; //−−−−− // p = current sound p r e s s u r e in a c e l l ptmp [ i ] [ j ] = p ; } e l s e i f ( s [ i ] [ j ] == 1) // −−−−−−−−−−−−// sound ’ s s o u r ce " s " { ptmp [ i ] [ j ] = s o u rc e ( t ) ; } e l s e // −−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−// obstac le to the spread { ptmp [ i ] [ j ] = 0 ; } } f l o a t so u r c e ( double t ) { r e t u r n 3 . 0 ∗ s i n ( 2 . 0 ∗ pi ∗ 10000.0 ∗ t ) ; } void majp ( ) { i n t i , j ; f o r ( i =0; i<hauteur; i ++) { f o r ( j =0; j<l ; j++) { pnmoinsun [ i ] [ j ] = p[ i ] [ j ] ; //−−−−−−−−−−−−−−−−−−−// pnmoinsun = the p r e v i o u s s t a t e ’ s p r e s s u r e p[ i ] [ j ] = ptmp [ i ] [ j ] ; //−−−−−−−−−−−−−−−−−−−−−−−−// ptmp = p r e s s u r e o f the " t r a n s i t i o n " ( template ) } } } 6.2. the cell modelled in the environment an average particle size for this simulation is a grid of 1000 x 1000 cells representing one million elements. to obtain a clear idea, we can assume a wave frequency to 10khz, corresponding to a period of 100 microseconds. the sound propagation speed is 344 m / s in an atmosphere under normal pressure conditions, and temperature to 20 degree celsius. the space occupied by a sound pulse is the wavelength of the value of 3.44cm. by measuring a cellular automata to 10,000 hz, a grid whose grain is 3.44cm would cross a cell of this size in each period. in figure 10, the propagation is observed from 3 sound sources composed of interference, diffraction and refraction. figure 10. simulation of propagation of 3 sound sources, with detectable wavelengths (blue stripes) and a red bar symbolizing an obstacle. the vertical bar illustrates a wall with a coefficient mitigation greater than 0.8 (resistance of the walls). it permits the observation of the phenomena : • of the interference when the waves trains from the 2 sources meet, • of the reflection during the contact of the waves with the âăijwallâăi̇. the period: t (period) = 1/f = 0,0001 sec. the wavelength λ is written as: λ = v t = v f this wavelength is observable in the figure: it corresponds to the distance between two blue circles. the pulsation or angular frequency is given by: ω = 2πf = 2π/t the sound pressure at a point thus calculable. 7. spatial aspects and parallel execution it is interesting to represent parallel behaviour by the parallel execution structures. sequentially encoded in a first step, the cellular automata has therefore been 10 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 discrete simulation of sound propagation in the city base on celullar automaton for the smart city transcribed for a nvidia graphics accelerator and programmed in cuda. at the same time, the structural data for the city has been translated to enable the cellular system to run. 7.1. geometry of the city and sound waves here, the physical dimension becomes important, because cellular systems represent real physical objects whose geometrical dimensions are known. depending on the scale of the overall geographical position of the area of interest or city, we observe different ac cells sizes whose granularity can also be varied. in figure 11, the geo-localization data presented on the top left of the interface conducts a coordinate of 1.586 metre per pixel. urban structures will behave both as filters and reverberation systems. figure 11. calculating the size of the cell with the integration of a geo-localized map of brest. (the tool is one of the projectors developed by pierre-yves lucas.) the instantaneous acoustic pressure is an integration of pressure over a period ti, it oscillates around the ambient pressure pa. we consider variations around a stable pressure : p ′(t0) = p(t0) − pa . = p(t0) − ∫∞ t=0 e − tτ p(t0 − t)dt τ to permit the determination of sound pressure frequencies. the effects of sound on the ear depend on the power of the sound waves which determines the volume level. the sound power is proportional to the square of the acoustic pressure. the effective value peff (t) of the acoustic pressure is calculated over an integration period ti : peff (t) = √ 1 ti · ∫ t t−ti p′2(t)dt the sound level meters allow the inclusion of the human perception of different sounds to its real sound level by performing a weighing of the results of noise measurements, by frequency [3]. figure 12 shows the relations between the pressure and the neighbourhood of a cell. 7.2. representation of the environment here, a preliminary scale calculation using data from the mercator tile projector adapts the scale of the map of a city to the size of ac cells. the meter pixel conversion formula is integrated with laboratory tools to directly give the real environmental space measured in meters per pixel. figure 12. pressure and speed in each cell 7.3. execution parallel on cuda __global__ void k e r n e l t r a n s i t i o n ( f l o a t ∗ t , f l o a t ∗ sv, f l o a t ∗ptmpv, f l o a t ∗pv, f l o a t ∗pnmoinsunv , i n t ∗d_matrice_y ) { unsigned i n t i = 2∗ blockidx . x + threadidx . x ; unsigned i n t j = 2∗ blockidx . y + threadidx . y ; f l o a t p , v0 , v1 , v2 , v3 ; f l o a t p i = 3.141592653589793238462643383; i f ( i >1 && i < (∗ d_matrice_y − 1) ) { i f (sv [ i ∗ ∗d_matrice_y + j ] == 0) 11 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 e. b. keita, b. pottier { // −−−−−−−−−−−−−−−−−−−−−− show s e q u e n t i a l content f o r : p , s , 0 . 9 2 , ptmp , e t c . . v0 = pv[ ( i −1) ∗ ∗d_matrice_y + j ] ∗ 0 . 92 ; v1 = pv[ i ∗ ∗d_matrice_y + ( j −1) ] ∗ 0 . 92 ; v2 = pv[ ( i +1) ∗ ∗d_matrice_y + j ] ∗ 0 . 92 ; v3 = pv[ i ∗ ∗d_matrice_y + ( j +1) ] ∗ 0 . 92 ; v3 = pv[ i ∗ ∗d_matrice_y + ( j +1) ] ∗ 0 . 92 ; p = 0.5 4 ∗ ( v0 + v1 + v2 + v3 ) − pnmoinsunv [ i ∗ ∗ d_matrice_y + j ] ; // −−−−−−−−−−−−−−−−−−−−−−show s e q u e n t i a l content f o r : pnmoinsunv e t c . . ptmpv [ i ∗ ∗d_matrice_y + j ] = p ; } e l s e { i f (sv [ i ∗ ∗d_matrice_y + j ] == 1) // s o ur c e { ptmpv [ i ∗ ∗d_matrice_y + j ] = 3 . 0 ∗ s i n ( 2 . 0 ∗ pi ∗ 10000 ∗ t [ 0 ] ) ; } e l s e // o b s t a c l e { ptmpv [ i ∗ ∗d_matrice_y + j ] = 0 ; } } } pnmoinsunv [ i ∗ ∗d_matrice_y + j ] = pv[ i ∗ ∗ d_matrice_y + j ] ; pv[ i ∗ ∗d_matrice_y + j ] = ptmpv [ i ∗ ∗d_matrice_y + j ] ; } void t r a n s i t i o n ( ) { dim3 dimgrid ( matrice_y /2 , matrice_x /2 ,1 ) ; dim3 dimblock ( 2 , 2 , 1 ) ; k e r n e l t r a n s i t i o n <<<dimgrid , dimblock>>>(dev_time , dev_sv , dev_ptmpv , dev_pv , dev_pnmoinsunv , dev_matrice_y ) ; // −−−−−−−−−−− add dev_ aux v a r i a b l e s ptmv, e t c cudamemcpy (sv, dev_sv , matrice_y ∗ matrice_x ∗ s i z e o f ( f l o a t ) , cudamemcpydevicetohost ) ; // −−−−−−−−−−−−−−−−−−−−−−sound s o ur c e copy to gpu (cpu −−> gpu ) cudamemcpy (pv, dev_pv , matrice_y ∗ matrice_x ∗ s i z e o f ( f l o a t ) , cudamemcpydevicetohost ) ; // −−−−−−−−−−−−−−−−−−−−−−sound p r e s s u r e copy from cpu (cpu −−> gpu ) manual determination of the parameters of interactions and visualization of a sound in a cell. it always considers two state variables placed in each cell cf figure: 12 the sound pressure "p" and the speed of particles "v". 7.4. statistical analysis of cellular plan after recovery of the cellular plan, it is possible to make some statistics or to represent the sound characteristics as volumes. figure 15 shows the distribution of the sound pressure over the map of the simulated site. we can recognize the source and areas susceptible to this pressure, or on the contrary, protected areas. 7.5. virtual microphones this plan can be produced, analyzed and displayed. preliminary data concerning the coverage of a sound figure 13. cell contents of 10khz, 20âţ sec figure 14. manual calculation of scale and granularity ... zone by the sensors. what we have done here is an investigation of the simulation results. it is interesting in the first place to consider how an actual establishment of the sensors would enable the capture of sound produce by the sound sources. each sensor provides physical coverage which is its ability to record the neighbouring sound. figure 16 presents the degree of coverage of a sensor network according to their number.. figure 17 presents a statistic for the number of cells in relation to pressure. one is able to connect the sensors next to several sound sources and to measure therein the noise levels through a 12 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 discrete simulation of sound propagation in the city base on celullar automaton for the smart city figure 15. 3d representation of the pressure in the cell figure 16. network coverage, number of sensors concerned sensor placed at the point representing the sound source, figure:18. 8. performance of sequential and parallel executions we want to have an idea about the performance and time (duration) of execution in various situations: thus one makes a comparison in terms of execution of speed, figure 17. distribution of the number of cells that have a pressure superior to 1pa tp 10000hz ... figure 18. graphic of the sound level from the sensors placed at the sound source by varying the number of iterations, the size of the grid cell or still yet, the frequency, etc .. between sequential execution (cpu) and parallel execution ( gpu), figure: 19. 9. conclusion and future works cellular automata are used as a discrete approximation of physical phenomena. by choosing the right time scale and good spatial grain, it is possible to represent a situation and its progress in a realistic manner. we applied this execution model to the propagation of sound in an urban context, showing how one or more sound sources may be controlled for transmitting signals that can be received and analyzed after propagation. the application value of this simulation approach is situated in the diagnosis of events, or in situations that affect social life. the parallel execution model is perfectly well suited to the execution of these simulations, and with a clear outcome, the gpu graphic accelerators. the composition of several simulations and their coordination 13 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 e. b. keita, b. pottier figure 19. general profile (vnprof vs gprof) depending on the number of grids and iterations. (a) sound coverage in sequential execution (b) sound coverage in parallel execution figure 20. sound coverage in sequential and parallel execution: sound intensity (loudness) in relation to distance: comparison of sound coverage to frequency and time equally (10khz, and 20µsec) between parallel execution and sequential execution. so, four microphones are placed at "distances (100 cell units) from the source. the nearest, micro1 (colour red), shows a wide coverage (amplitude) and micro4 at 400 cell of distance (colour grey) gives a lower amplitude. can be performed at the cellular level following a known standardized method high level architecture [11]. this paper focuses on the discrete simulation of the sound propagation in urban areas, in the context of the smart city. the practical applications of this work are numerous, in particular in the field of wireless sensor networks, which are an important element in the current digital landscape. one of the areas mentioned is smart cities. another of the most cited domains is that of communicating objects that promise important developments. the pervasive sound is an element of this context allowing for example to visit or to monitor distant sites in a diffuse way. the objects "talk to each other". the approach may be applied to other physical figure 21. comparison of sequential and parallel execution time figure 22. comparison of sequential and parallel average performances phenomena, such as light, radio waves (developing special aspects such as longitude and latitude), river pollution, urban noise pollution and in other contexts such as the city, the countryside, the human body (networked microrobos), etc. we propose in the following of: • addressing the problem of relaying sound in the city through sensor networks, to direct the propagation of sound to a specific destination. this will allow the development of local or regional warning sirens. • apply the propagation of sound for the detection of the propagation of water pollution in a river. 14 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 discrete simulation of sound propagation in the city base on celullar automaton for the smart city • ability to locate satellite sound sources. this would considerably reduce the time taken to pay for an event signaled by a sound source. references [1] j. von neumann, a. w. burks et al., “theory of selfreproducing automata,” ieee transactions on neural networks, vol. 5, no. 1, pp. 3–14, 1966. [2] h. vangheluwe and g. c. vansteenkiste, “the cellular automata formalism and its relationship to devs.” in esm, 2000, pp. 800–810. [3] s. a. gelfand, hearing: an introduction to psychological and physiological acoustics. informa fifth ed., 2010. [4] d. g. et son équipe (repris par gerry vassilatos dans ’lost science’), “infrasons (acoustiqua1966) le son silencieux qui tue,” nexus num 10, vol. vol.17, janvier 1968. [5] j. blauert, spatial hearing: the psychophysics of human sound localization. mit press, cambridge, ma revised ed., 1983. [6] c. a. et eugène de montalembert, guide de la théorie de la musique 610 p. paris, fayard (isbn 978-2-21360977-5), 2001. [7] r. dogaru and i. dogaru., “an efficient sound propagation software simulator based on cellular automata.” iseee 3rd international symposium, sept. 2010. [8] m. vacher and al., “life sounds extraction and classification in noisy environment.” sip, 2003. [9] cartelie, “http://cartelie.application.developpementdurable.gouv.fr/cartelie/ voir.do?carte=d29_carte_de_bruit_a1_2e&service=ddtm_29#,” en ligne; page disponible le 7-mars-2015. [10] y. i. toshihiko komatsuzaki1 and s. morishita2., “modelling of incident sound wave propagation around sound barriers using cellular automata,” institute of science and engineering, kanazawa university, kakuma-machi, kanazawa, ishikawa, 920-1192 japan, 2012. [11] t. v. hoang, “cyber physical systems and mixed simulation,” m2ri report, ubo, tech. rep., june 2015. 15 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e4 1 introduction 2 background 2.1 sound propagation spatial properties of sound waves elementary metrics : frequencies, wavelength, amplitude, intensity 2.2 discrete simulation 2.3 cellular automata formalism 2.4 the characteristics of sound waves definition of the physics of sound 3 related work 4 towards an interweaving of urban sounds 4.1 classification of propagation elements 4.2 quantitative application motivation 4.3 social signification of sound 4.4 physical propagation simulation approach 5 simulation of sound propagation by cellular automata 5.1 transition function: neighbourhood, pressure and speed 5.2 interpretation of sound diffusion 6 sequential implementation and validation 6.1 state of a cell and transition function the parameters of the state in cfl conditions (current-friedrichs-lewy or richard current's number), dimensionless numbers 6.2 the cell modelled in the environment 7 spatial aspects and parallel execution 7.1 geometry of the city and sound waves 7.2 representation of the environment 7.3 execution parallel on cuda 7.4 statistical analysis of cellular plan 7.5 virtual microphones 8 performance of sequential and parallel executions 9 conclusion and future works oil and gas supply chain optimization using agent-based modelling(abm) integration with big data technology 1 oil and gas supply chain optimization using agent-based modelling(abm) integration with big data technology jamal maktoubian1,*, mehran ghasempour-mouziraji2, mohebollah noori3 1international school of information management (isim), university of mysore, mysore, india. 2department of engeneering, islamic azad university of sari, sari, iran. 3zarghan branch, islamic azad university, zarghan, fars, iran. abstract the worldwide oil & gas industry is one of the world's most complex business networks, and is connected with almost every supply chain branch. it includes international and domestic transportation, materials handling, ordering and inventory visibility and control, import/export facilitation and social network, etc. traditionally, it has been influenced by big oilfield companies. however, in recent years the industry has been changing into a more heterogeneous and diverse network of businesses, and the oilfields are getting smaller and more diverse. one of the reason could be dwindling the oil reserves and growing specialized companies which are able to extract hydrocarbons; another reason is the restructuring and globalization of the entire business as well as some new technology implementing. using agent-based modelling and big data technology integrity, we are able to optimize supply chain in oil and gas industries. keywords: big data, agent-based modelling, oil and gas supply chain received on 10 ju ly 2018, accepted on 02 august 2018, published on 09 august 2018 copyright © 2018 jamal maktoubian et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.26-6-2018.155192 1. introduction the global demand of oil & gas followed by the ease of international trade and the inflexibility involved in the petroleum industry’s supply chain has made its management more challenging[1]. the oil and gas industry is principally a supply chain management (scm) industry, which involves the management of all steps in the delivery of a product or service to consumers. it consists of exploration, drilling, operation of pipelines, and operation of refineries for the production of fuel, plastics, and so on. trunk line or “transmission pipes” are the arterials that deliver refined products such as gasoline and aviation fuel to terminals at various locations. distribution refers to the sale and delivery of these products to consumers from storage terminals. forrest and et al[2], identified that the majority of oil industry still operates its planning, central engineering, upstream operations, midstream operations, downstream operations and refining, supply, and transportation units as complete separate entities. each part of these process provide huge amount of data and dealing with such them require a huge infrastructure. in view of this, systematic methods for efficiently managing the oil and gas supply chain as one continuous unit must be exploited. more efficient and cost effective scm practices in the oil & gas industry indicate critical issues for ensure the continuous supply of crude oil, lead time reduction, and lowering of production and distribution costs. due to the inflexibility involved in the petroleum industry’s supply chain network, cost containment, visibility, globalization, risk, information technology logistics, knowledge management and greening the supply chains are some of the challenges facing the scm in the oil marketing companies as advanced by other researchers. integrated process management(ipm), information sharing and management, variety and complexity of generated data by each sector, organizational restructuring, and cultural reorientation are crucial factors and equally important. research article eai endorsed transactions on smart cities ∗corresponding author. email: jamal.maktoubian@gmail.com eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e1 http://creativecommons.org/licenses/by/3.0/ jamal maktoubian et al. 2 a wide range of optimization models have been proposed in the oil and gas supply chains, often without taking the inherent risks and vulnerabilities from events, different routes and supply chain units/nodes into consideration. these uncertainties and risks often interrupt the supply chain operations, causing significant adverse effects in the energy sector. it is important to develop risk based optimization models using advance technology in order to predict, reduce or mitigate the impact of these uncertainties in the oil and gas critical infrastructure supply chain. although oil and gas supply chain has a simple procedure, a little optimization in each agent (storages, refineries, retailers, pipelines, suppliers, carriers, freight forwarders, tankers, to name but a few) could save millions of dollars in a month. moreover, visibility in the supply chain being the main issue, the key challenge lies in the process optimization of each enterprise. for the question of efficient supply chain for a mass production industry like that of petroleum industry, the solution lies in the adaptive supply chain, which make a more holistic approach to the supply chain optimization[3]. the integrity of big data technology, agent-based modelling(abm) and simulation is reliable and efficient methods for solving complex problems of today's world. many components of supply chain systems have been modelled utilizing an agent-based software. garcia-flores and wang constructed an abm to simulate dynamic behavior of cooperating agents along a single supply chain[4]. the specific operation of a warehouse system was designed by ito and abadi[5]. models of refinery supply chains have been used to determine optimal business processes and configurations in one specific plant[6, 7]. combining big data methodologies with particular, agentbased modelling first, would be employed to uncover new relationships and behaviour coping with agents in agentbased models that were not recognized by the traditional ones. secondly, it could be beneficial for extracting more parameters for agent-based models, as the size of data sets will be increased. and then finally, after providing the results, they can be utilized to validate and comparing simulation with existing agent-based models. by doing this, oil and gas supplier could take advantage of both approaches to identify agent behaviours and options in an unprecedented manner. to do that, we need big data and simulation frameworks, and visualization tools allow enduser access simulations without being notified of the operations. hopefully, these types of analyses and computational challenges are already covered by data science experts. 2. big data in supply chain management nowadays, it gets more and more important for oil and gas companies to manage and oversee their supply chains in an effective manner in order to reduce cost as well as to enhance and guarantee efficient operations. due to the incipient digital transformation process, expected to radically alter business ecosystems, change management practice and revolutionize supply chain dynamics, the management of data and information, being the raw materials of the digital age, is becoming increasingly important for businesses. the rationale is that the amount of data and information generated by, available to and collected through companies is growing at an unforeseen fast pace. the term big data analytics has been coined in this respect, reflecting the volume, velocity, and variety surge of digital data which increasingly poses a challenge for companies, as it complicates the identification and extraction of the most relevant and valuable information required for managing the business and ultimately the supply chain[8]. however, having access to accurate and up-to-date information is paramount for informed decision-making at corporate as well as supply chain level. in turn, not having access to up-to-date, accurate and meaningful information represents a risk for companies and subsequently for the supply chain, as decisions need to be made on a reliable, evidence-driven basis. other factors being the increased need for end-toend visibility along the supply chain, enhanced automation levels as well as required efficiency gains at the manufacturing level. apart from the analysis, machine learning is helping to improve the accuracy and efficiency of supply chain management. the evolution to using artificial intelligence and machines that learn in supply chain planning is inevitable. in fact, there are early examples of the potential of ai to improve both supply chain planner efficiencies and provide better or optimized supply chain decisions. oil & gas supply and trading aims to optimize commercial margins in a diverse, dynamic, and global market environment. data mining, machine learning, and predictive analytics solutions could be provided that empower decision makers to analyze trading risks. effective optimisation requires analysis of the interaction of several variables in supply chain datasets. in supply chain machine learning, we need to measure relationships between attributes to find hidden patterns among them. for instance, how different factors such as materials, ordering and inventory visibility and control, import/export facilitation, and transportation, etc. can influence oil and gas industry. 3. agent-based modelling (abm) in oil & gas industry abms are computational systems with dynamic behavior and special characteristics that define as “interacting autonomous entities which is called agents”[9]. using agents, we able to show and employ individuals at several levels, learning capability, and make best decisions in both space and time. having this features, researchers are able to examine complex systems and environments, such as oil and gas supply chain. cutting costs by using new information technologies and creating conditions for better collaboration is a very actual problem. abm is a computational approach to model eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e1 3 complex systems with numbers of agents such as oil and gas industries. it consists of modelers which define other parts with their behaviors and generate simulations of their interactions to identify how those sections influence the behavior of entire system. the main objective of this paper is to propose a framework using big data technologies to formulate principles for collaboration, develop tools for incorporation of all data into a single set and to visualize data for further analysis. to do that we need to investigate the relationships of different variables in oilfield data in risk and then develop a simulation to identify higher risks of this business. oil & gas organizations could employ analytics to optimize materials’ delivery, reducing inventory levels and supply chain costs to evaluate performance and optimize supply chain operations. one of the most flexible modelling methods is agent-based modelling. the basis for naming these methods is because agents play an essential role in the model. in this type of modelling, each of the real world agents is modelled as decision-making and fully automated entities, called agent. and repetitive competitive communication between agents and subagents are a feature of agent-based modelling which relies on the power of hardware to explore dynamics out of reach of pure mathematical methods. each of these factors has various sections for understanding the environment, analysing it, and ultimately acting. in fact, in modelling the underlying factor, i will attempt to simulate the decision making process in the real world by similar factors. in order to apply agent-based modelling, following procedure is essential: 3-1 data collection: first and most required data (major terminals, tanks, connectivity, commodity types, pools, defaults routes, business rules, batches in pipelines at any time, to name but a few) could be collected from online pages but the only factor in collecting data is the volume of information, complexity of the system as whole. secondly, detailed structured questionnaires could be designed to identify the way in which oil marketing companies manage their supply chain. and finally, data would be obtained through literature review of various publications of supply chain management and production and operations management which are related to oil and gas industry. 3-2 model the process: one of the most flexible modelling methods is agentbased modelling. the basis for naming these methods is because agents play an essential role in the model. in this type of modelling, each of the real world agents is modelled as decision-making and fully automated entities, called agent. each of these factors has various sections for understanding the environment, analysing it, and ultimately acting. in fact, in modelling the underlying factor, we try to simulate the decision making process in the real world by similar factors. all agents and subagents behaviour which are associated with oil & gas supply chain industry need to be designed and the challenges should be simulated. to analyse existing supply chain models and develop a risk model that will be used to categorize and derive the various types of risks from analyzing the impacts of prior events on the oil and gas supply chain and subsequently derive their ratings from the weighted risk. developing a risk based scm that will include a risk based network reliability analysis model using the modified minimum cut-set method to locate critical links/nodes in the network. also failure from some of events, activities and threats we are able to analyse their risk ratings and severely affect the supply chain networks. a risk based linear programming (lp) supply chain model (scm) for strategic and tactical planning in the oil and gas scm, by using the risk ratings obtained above to simulate different scenarios and alternatives, so as to get and incorporate the likely impact of these events and activities on the critical, links and nodes. finally, develop a fault tree and model based vulnerability analysis (fta and mbva) models that will be used to show how scarce resources can be allocated for optimum result in hardening/protecting these oil and gas sc nodes from failure because of the likely impacts of some of the events and threats analysed. however, agent-based models can also generate large amounts of data, which can be difficult to analyse and understand. hence the question arises whether agentbased models could be combined with big data methods in a way that helps address this problem. 4.how big data integrity oil and gas supply chain: oil and gas companies can analyse data streams from suppliers to evaluate performance and optimize supply chain operations. they can use analytics to improve “real-time” delivery of materials, reducing inventory levels and supply chain costs. in brief, this research project proposes to develop a framework(figure-1) to solve real-time big data management, storage, computation challenges, and predictive data analytics in oil & gas supply chain organization in order to predict and monitor different variables and customers’ behaviour. to deal with collecting real-time streaming data which is come from different agents, we need to use state-of-art technology such as apache kafka and flume[10] as a distributed messaging system to collect unstructured and semi-structured data. it is unrealistic to expect that data will be perfect after they have been extracted. before processing data, they should be go through different steps which is called “data cleaning”. data is cleaned through eai endorsed transactions on smart cities online first oil and gas supply chain optimization using agent-based modelling(abm) integration with big data technology eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e1 4 processes such as filling in missing values, smoothing the noisy data, or resolving the inconsistencies in the data. raw data need to be pre-processed in different steps including data-integration, data transformation, data reduction, and data discretization. since good models usually need good data, a thorough cleansing of the data is an important step to improve the quality of data mining methods. not only the correctness, but also the consistency of values is important. data preparation consists of techniques such as min-max normalization and standardizing or z-scoring or normalizing the data[11]. in many application areas, datasets can have a very large number of features. as the dimensionality of the feature space increases, many types of data analysis and classification become significantly harder, and, additionally, the data becomes increasingly sparse in the space it occupies which can lead to big difficulties for both supervised and unsupervised learning. cleaned data are delivered to spark streaming which is a distributed stream processing engine. in this stage, spark streaming breaks up the input data stream in small batches namely resilient distributed datasets (rdd). a continuous sequence of rdds pass through spark engine in order to be processed and could be used in machine learning libraries such as mllib for data analysis[12]. different clustering and classification algorithms could be applied to find disease pattern or predict risks. these analysis methods could help care sector to identify knowledge in order to predict various risk in real-time. in this research project, there is a lot of potential in delivering more targeted, wide-reaching, and costefficient healthcare by exploiting big data trends and technologies. figure 1big data analytics in optimizing oil & gas supply chain analytics is of course a very wide area; we would like to focus in this section on a technology that has not been implemented widely in supply chain until recently called machine learning and in particular how it can be combined with optimization to produce breakthrough results. a natural application of supervised machine learning in supply chain analytics is forecasting. they are poised to address important issues in areas such as capacity planning due to uncertainty in downstream capacities, inventory and supply-chain management by reducing uncertainities around material and part availabilities, and by reacting to (or anticipating) market and customer demand changes. 1. conclusion supply chain management could play a vital role in order to promote business profitability and decrease costs in every industry. recently, by emerging new generation of hardware(radio-frequency identification (rfid), different sensors, internet of thing(iot), tracking technologies, etc.) and new algorithm and its applications, managing supply chain of businesses could be much easier than before. due to the globalization, oil and gas supply chain has turned into one of the challenging industry as the number of agents and sun-agent involved in this branch, could generate huge amount of data. data-storage, process and management are critical concern in this era. in this work, agent-based modelling and big data integration have been demonstrated as one of the solution which could provide data availability, scalability and performance for this system. in the future research, collected data would be examined by implementing the architecture and the result will be published. references [1] morton, r., good chemistry in the supply chain. logistics today, 2003. [2] forrest, j. and m. oettli. rigorous simulation supports accurate refinery decisions. in proceedings of fourth international conference on foundations of computersaided process operations. 2003. [3] tompkins, a., chain challenge. european chemical news (december 23–january 12), 2003: p. 19-21. [4] garcía-flores, r. and x.z. wang, a multi-agent system for chemical supply chain simulation and management support. or spectrum, 2002. 24(3): p. 343370. [5] ito, t. and s.m.j. abadi, agent-based material handling and inventory planning in warehouse. journal of intelligent manufacturing, 2002. 13(3): p. 201-210. [6] srinivasan, r., m. bansal, and i. karimi, a multiagent approach to supply chain management in the chemical industry. 2006, springer. p. 419-450. [7] julka, n., r. srinivasan, and i. karimi, agent-based supply chain management—1: framework. computers & chemical engineering, 2002. 26(12): p. 1755-1769. jamal maktoubian et al. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e1 5 [8] giannakis, m., et al., a multi-agent based system with big data processing for enhanced supply chain agility. journal of enterprise information management, 2016. 29(5): p. 706-727. [9] jones, c., m. matarić, and b. werger, cognitive processing through the interaction of many agents. encyclopedia of cognitive science, 2002. [10] wang, c., i.a. rayan, and k. schwan. faster, larger, easier: reining real-time big data processing in cloud. in proceedings of the posters and demo track. 2012. acm. [11] duda, r.o., p.e. hart, and d.g. stork, pattern classification. 2012: john wiley & sons. [12] kaveh, m., etl and analysis of iot data using opentsdb, kafka, and spark. 2015, university of stavanger, norway. oil and gas supply chain optimization using agent-based modelling(abm) integration with big data technology eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e1 this is a title 1 residential buildings renewal towards to the smart concept julius golej1,* 1 slovak university of technology in bratislava, vazovova 5, 812 43 bratislava, slovakia abstract the current global trends lead to fulfilment of specified environmental and economic objectives in all sectors of national economies. buildings form a basic pillar of smart cities concept where all life processes and nerve centres of social life are read, in order to radically improve quality of life, opportunity, prosperity, social and economic development, thanks to the use of the new technology. the building sector has been identified by various studies as a sector that offers considerable potential for the cost-effective reduction of greenhouse gas emissions, making it an important field for climate protection action. a significant role towards realizing these objectives has in particular the implementation of the latest technologies and technical procedures in all processes at all levels. smart buildings are no longer considered individually, but as a part of complex ecosystem. they must be adapted to the expectations of future users if they are to be properly used. this paper deals with the problematics of current technological, environmental and economic trends in renewal of residential buildings. keywords: residential buildings, renewal, energy efficiency, economic assessment. received on 1 march 2017, accepted on 13 october 2017, published on 19 december 2017 copyright © 2017 julius golej, licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.19-12-2017.153477 *corresponding author. email: julius.golej@stuba.sk 1. introduction the real estate and construction sectors can play a critical role in shaping energy use. buildings now account for 40% of total primary energy consumption [1] and they are the biggest single contributor (approximately 36%) to european co2 emissions that amount to approximately 5 gigatonnes for all sectors. building renewal is crucial if the eu is to meet its ambitious 2020 energy and climate goals: improving energy efficiency by 20% and achieving a 20% reduction of greenhouse gas emissions from 1990 levels. [1] reaching the declared long-term target of reducing greenhouse gas emission levels by 80-95% by 2050 will therefore need a major effort to improve building energy efficiency. approximately 40% of europe’s building stock predates the 1960s and is in dire need of renovation. [1] given that the renovation cycle for buildings is approximately 30 years (probably less for commercial buildings) during which the performance of a building in principle does not change, it is necessary to ensure that new buildings and renovation measures on existing buildings optimize the energy saving potential. [2] nowadays attitudes towards climate change mitigation remain mixed across the globe. moreover, most of the sector’s energy efficiency investments are in new buildings rather than renewal, even though existing structures make up the biggest share of the world’s buildings. this makes the huge challenge of cutting the energy footprint of the global building stock; an extraordinary opportunity exists to scale up efficiency measures in the real estate sector. [3] anyway, these climate change targets will be nearly impossible to reach without industry’s full participation. according to some realized surveys (the economist, the buildings performance institute europe) the great majority of construction and real estate companies in the eai endorsed transactions smart cities research article eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e2 http://creativecommons.org/licenses/by/3.0/ julius golej 2 world are mainly focuses on the construction of new energy-efficient buildings instead of renovation of the existing stock. however, precisely old buildings create a huge proportion of energy consumption and production of emissions. this situation is quite understandable in emerging markets such as china or india. what is quite surprising is that even highly developed markets such as europe or the us, where the share of new buildings is relatively low compared to developing countries (share constitutes only 1%), focuses on the construction of new energy-efficient buildings before renovation of existing ones. this is problematic because less efficient buildings will continue to waste energy for a long time to come. the fact that companies are focused on new construction is somewhat understandable as the investment can be more easily amortized over the lifecycle of the building. fitting a structure with the latest energy-efficient heating and cooling systems, high-performance windows and insulation is far easier when starting on a new project than when dealing with an existing structure. moreover, in existing buildings, it may be necessary to work while parts of the building remain occupied. in 2012 the economist intelligence unit realized a global survey focused on energy efficiency, energy savings and the regulatory environment, of 423 senior executives from four sectors: residential real estate, building construction, commercial real estate and the industrial real estate sector. geographically, respondents were evenly split among the us, europe, india and china. organizations of all sizes were represented, and roughly half were from firms with revenue over us$500m. forty percent of us survey respondents from the building sector accept no business responsibility for carbon emissions. in europe, china and india, 84% of respondents cite emissions reductions as an important business responsibility. the attitude of us respondents is mirrored in the country’s political process and the relative weakness of energy efficiency legislation. [3]. 2. technological trends in residential buildings renewal more knowledge of energy use prompts companies to go further in their measures to reduce consumption, including rigorous measurement of a business’s energy footprint. according to building energy experts, heating and cooling account for between 20% and 60% of total energy use in a building, depending on a building’s efficiency. [3] new technologies and systems from the ability to adjust lighting levels for individual users to a range of automated and wireless controls mean companies can do more than reduce their emissions. they can also improve quality of life for building occupants. but if they do not look at how different systems interact and how to persuade users to change their behaviour, the building sector may miss both business and climate change mitigation opportunities. it-enabled energy systems can create buildings that are not only more efficient but are also healthier and more pleasant places in which to live or work. [3] 2.1. savings technologies requirements the maximum savings potential within the building sector has not yet been fully recognized. [4] both the quality of measures and the speed of implementation (especially in building renovation) demonstrate the scope for improvement. [5] so far, european member states have adopted different approaches and different ambitions in their building regulations, influenced by national political processes, building traditions and individual market conditions. [2] technologies to improve the energy performance of buildings, which should be taken into account, are: building envelope measures deal primarily with the reduction of heat transmission and improved air tightness of the building envelope with the intention of reducing transmission losses and losses from (too high) air-exchange. this includes: thermal insulation products (e.g. for insulating walls or roof); building materials (e.g. for walls) with low thermal transmission; measures to ensure air-tightness (e.g. sealants); measures to reduce the effects of thermal bridges (specific construction solutions for connections within facade and roof); high efficient glazing (e.g. triple glazing) and low energy window frames and doors (use of insulating materials, specific sealants, etc.). green facades in smaller amounts became a part of technological solutions in building’s regeneration processes. among their undoubted advantages can be included savings for heating. this is due to the ability of holding the air and prevent its circulation between the wall and greenery, especially in winter time. by contrast, in the summer it creates a pleasant climate in the building and as the leaves releases moisture in the air in the vicinity of facades there is a pleasant environment. another undeniable positives include: sound insulation, production of oxygen and carbon dioxide retention, absorbing pollutants from the air, filtering particles of dust and prevent its dispersion. another advantage is that climbing plants with its roots pumped out moisture from the foundation of the house (see figure 1). eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e2 residential buildings renewal towards to the smart concept 3 figure 1. example of green facade [16] roofs green roofs are not new or extraordinary in new construction of buildings, but this type of roofs are increasingly appearing also in the renovation of existing residential buildings. their undoubted advantages are: oxygen production and retention of carbon dioxide, absorbing pollutants from the air, filtering particles of dust and prevention of its dispersion, preventing overheating of roofs, reducing temperature fluctuations between day and night, the function of heat and sound insulation, fire resistance, mitigation of humidity fluctuations, unlimited service life (with proper design), aiding the sewage system because it slow down the runoff of rainwater, creating a habitat for insects, aesthetic and recreational functions, the possibility of creating gardens for growing flowers and vegetables (see figure 2). thereby green roofs slowing the drainage of rainwater, there is less burden on sewage system functions. while rainwater from these types of roofs can be drained into containers from which could be drawn (or by using a gravity system) and reused for irrigation of immediate vicinity of the building. figure 2. example of green roof [17] during the renewal processes on the roof could be placed alternative energy sources (e.g. solar panels or wind turbines). space heating an active system is usually necessary to meet the demand for heating. this demand can be met by efficient and/or renewable energy systems (e.g. condensing boilers, heat pumps or wood-pellet boilers) in conjunction with suitable storage and distribution systems. hot water domestic hot water is often produced with the same system used for space heating, but it can also be supplied by combined systems (e.g. when integrating solar energy systems) or separate systems. high efficient storage and distribution systems are crucial for reducing heat loss. ventilation systems mechanical ventilation systems help to achieve the necessary air-exchange rates and can also limit losses from air-exchange by heat recovery systems. cooling systems passive cooling systems such as shading devices can help reduce or avoid cooling loads. active systems can meet demand for heating. these are mainly electric systems but renewable systems are also available (e.g. solar cooling). lighting this includes applications to increase the use of daylight (e.g. tubes or mirrors) and active systems for artificial lighting (e.g. low energy light bulbs). a lighting control system can be used to switch lights based on a time cycle, or arranged to automatically go out when a room is unoccupied. some electronically controlled lamps can be controlled for brightness or colour to provide different light levels for different tasks. lighting can be controlled remotely by a wireless control or over the internet. natural lighting (daylighting) can be used to automatically control window shades and draperies to make best use of natural light. building and home automation and control other related measures include the implementation of management systems that introduce supervising/steering functions for the building. this may include centralized control of lighting, hvac (heating, ventilation and air conditioning), appliances, security locks of gates and doors and other systems, to provide improved convenience, comfort, energy efficiency and security. the concept of the "internet of things" has tied in closely with the popularization of building and home automation. home automation refers to the use of computer and information technology to control home appliances and features (such as windows or lighting). systems can range from simple remote control of lighting through to complex computer/micro-controller based networks with varying degrees of intelligence and automation. home eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e2 julius golej 4 automation is adopted for reasons of ease, security and energy efficiency. [6] home automation systems include: sensors to measure or detect things like temperature, humidity, daylight or motion; controllers such as a pc or a dedicated home automation controller; actuators such as motorized valves, light switches and motors; buses for communication that can be wired or wireless; interfaces for human-machine and/or machine-to-machine interaction. [7] other building-related measures with impact on thermal performance this can include, for example, external shading devices (see figure 3).and other active and passive systems not covered by the other groups. [2] automatic control of blinds and curtains can be used for: presence simulation; privacy, temperature control, brightness control, glare control, security (in case of shutters). [7] figure 3. external shading system [18] 3. legislative framework full execution of existing regulation is needed to promote both energy-efficient new builds and retrofits, the latter being where most gains can be achieved. indeed, most buildings present today in the eu will still be standing in 2050. yet, renovation rates across the eu are low, standing at approximately 1% of the building stock. to reach the eu targets, renewal will need to double to 2-3% of existing stock. only a minority of upgrades is substantial or what experts refer to as complex renewal. [1] government has a significant role to play in this process. since older buildings are generally less efficient than new structures, increasing the rate of retrofitting offers a substantial opportunity for policymakers to profitably advance low-carbon objectives. because retrofits get less attention than new, green buildings, however, this is not an easy goal to achieve. policymakers can help by implementing measures that remove obstacles to retrofitting projects. these might include facilitating the contracting out of renewal efficiency to energy service companies, streamlining project approval procedures or providing technical assistance. coming up with the right incentives will require careful thought, and measures may need to be adapted to individual markets and climates. [3] attracting large institutional investors in renewal finance will require energy efficiency project aggregators. aggregators can be public or private and can appear either as a result of regulation or client demand. to be effective, however, they require clear energy performance objectives, standardized contract structures that allocate responsibility for performance, and data collection and transparency about results. [1] monetary incentives are the most popular form of regulation. but while many companies favour tax rebates and grants, expedited permitting for energy-efficient buildings can be a significant nonfinancial incentive, particularly in the commercial segment. despite the general acceptance of regulation not all of it is considered effective. legislation can be a clumsy tool. for example, those mandatory building efficiency ratings are only effective if sub-metering is also introduced. when the efficiency in buildings is going to improve, it is necessary to understand at a primary level how buildings are operating. it’s mean that it is necessary to understand activities of individual tenants and landlord influenced areas of a building, for creating the complex report. absence of regulation can be as much of a barrier as poorly designed measures. the industry lacks a universal definition of what constitutes a green building as well as consistent data sources and metrics on green buildings. this makes implementation of green projects difficult and therefore the sector does not contribute as much as it should to controlling co2 emissions. governments need to understand how they can influence the market. there is clear evidence that legislation can in fact shape market behaviour. this is demonstrated most powerfully in europe, where strict standards have led a large proportion of companies to audit their energy use. the european experience suggests not only that policymakers can use regulatory tools to promote energy efficiency investment, but also that by combining mandates with incentives, they can facilitate competition for higher efficiency buildings. policymakers can play an important role in shaping energy use in the real estate and construction sectors. measures could include wider use of mandates, auditing, incentives for sub-metering and the introduction of building performance ratings systems. government can do more to raise consumers’ awareness of the social and economic advantages of lowenergy buildings, thus stimulating market demand. increasingly sophisticated technologies and systems can help to remove many of these barriers and increase the return on investments inefficiency. [3] 4. current approach eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e2 5 designing tomorrow’s buildings today inevitably means questioning the economic logic that will enable them to be funded. it is difficult to move from idea to realization, when the integration of renewable energies and new technologies increases construction costs by 2530%. on this front, all the players are unanimous: it will only be possible to finance projects if they take into account the entire life cycle of buildings. the overall cost approach is developing: social landlords are becoming more and more aware of their tenants’ costs and of the reduction in carbon footprint. [8] whatever the energy-saving strategy, energy management is as important as technology. as energy efficiency becomes more widely accepted, companies are seeing their investments in a more holistic way, taking a longer-term view of investments. when companies move beyond equipment upgrades and integrate energy management into their business models, the potential energy savings increase dramatically. companies have come a long way in their approach to energy efficiency. most are tackling their energy footprint with measures to improve heating, hvac and lighting. and many are going further incorporating energy consumption into their overall strategy, including it in risk management and taking a longer-term view of their investments. [3] to start, the buildings sector needs to better understand its energy consumption and potential reductions. this requires knowledge of the cost of energy investments, adoption of auditing and potentially the use of voluntary standards audited by third parties. companies also need to do more to enhance the efficiency of existing structures. the market needs clear long-term signals, rational expectations and opportunities for a reasonable return on investment. but with buildings responsible for such a large proportion of global greenhouse gas emissions, it is a task that should be embraced with urgency by both governments and the private sector. [3] 5. economic and environmental assessment of residential buildings 5.1. energy assessment of buildings the assessment needs to incorporate the following aspects:  calculation of the buildings net energy use;  calculation of the energy delivered (energy supplied to the building, e.g. natural gas from the grid; energy produced by the building itself and delivered back to the market is subtracted) to the building for heating and cooling, ventilation, domestic hot water and lighting including auxiliary energy;  energy generated by the building itself (e.g. via photovoltaic systems or combined heat and power);  calculation of the overall primary energy use. primary energy is the energy from renewable and non-renewable sources which has not undergone any conversion or transformation process. [2] the energy audit should include: 1. identification data on the owner of the building and about the energy audit processor. 2. the subject of energy audit. it shall indicate the basic information on the subject of energy audit: the purpose of processing energy audit; identification of the subject of energy audit (building name, street, descriptive / registration number, municipality, district); information on use of the base material (e.g. bills for energy supply, the available design documentation, on-site inspection, custom control measurements, thermal diagnostics, photographic documentation, the national technical regulations (standards) and others). 3. description of the status quo, which indicates the characteristics of the building (building category, a description of the building and building structures, geometrical parameters, total floor space, form factor, operating mode, etc.); description of the technical installations in buildings (technical systems, heating, hot water, ventilation, cooling, lighting), identification of deficiencies. 4. basic data on energy inputs and outputs of energy consumption in the building for at least the last three calendar years (including a description of the method of assessment); on energy costs. 5. thermal assessment of packaging structures of the building; energy assessment. assessment of building envelope and roof cladding from which will be identifiable at least the following data: area of construction, heat transfer coefficient; evaluation whether construction is suitable or not; the detailed structure of each building structures; overall rating of packaging constructions; assessment of buildings in terms of satisfying the minimum necessary requirements of heat for heating. 6. proposed measures to reduce energy by renovation of buildings through construction works and their economic and environmental assessment. it should take into account: the type and minimum thickness of thermal insulation, taking into account the quality of the original design envelope and influence of thermal bridges; heat transfer coefficient for windows and doors by the technical regulations. minimal output of environmental assessment for each proposed measure is the reduction in carbon dioxide (co2) and particulate matter and other selected pollutants (co, nox, so2). eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e2 residential buildings renewal towards to the smart concept julius golej 6 7. proposed measures to reduce energy use of technical equipment in the building. these include: heating system; domestic hot water systems, including energy services; the lighting system; the ventilation and air conditioning system. 8. energy evaluation of buildings, taking into account the expected state after the implementation of the proposed building modifications and replacement of technical equipment in the building. it proves the premise of satisfying the minimum energy performance requirements for buildings. energy audit has recommending character for decision making by the owner / operator of the building. it does not constitute a restrictive framework for the detailed design of measures to improve the energy performance of buildings, respectively to improve the energy performance of buildings. [9] figure 4. energy efficiency classification of buildings [19] 5.2. economic assessment of energetic systems in buildings economic evaluation is widely used: to assess the economic potential of energy efficiency measures in buildings; to compare various solutions to energy efficiency measures in buildings (e.g. types of equipment,; fuels); to evaluate the economic performance of the overall design of the building (e.g. a compromise between energy needs and energy efficiency of heating systems); to determine the effect of possible energy conservation measures on an existing heating system on energy consumption with energy-saving measures and without them. [10] when the economic assessment is based on a set of standard conditions, and current energy prices in determining the energy savings potential and the cost of its acquisition (the proposed measures). further from the preliminary estimate of investment costs according to current prices of construction products and construction works on the market without taking into account ancillary coerced costs taking into account the service life of the proposed measure, the calculation period of 30 years and the discount rate. the outcome of the economic assessment are the economic indicators, namely: 1. the simple payback period, 2. discounted payback period. 3. the net present value, 4. the internal rate of return. net present value although we know a few methods for the calculation of the economic evaluation of energetic systems in buildings, specified below in greater detail is a net present value (npv) because this method is most commonly used in practice. according the energy performance of buildings directive recast [5] as a method for an economic assessment suggests the net present value. the net present value is a standard dynamic method for the financial assessment of long-term projects. it measures the excess or shortfall of cash flows, calculated at their value at the start of the project. [2] the npv represents the difference between expenses and income of the investment project which relate to a certain period, usually at the inception of the project by discounting. [11] the npv is considered a basic criterion for deciding on acceptance or rejection of the investment project. [12] an appropriate calculation of npv can be performed by using the global cost calculation method, and can be described by the following formula (1): 𝐶𝑔 (𝜏) = 𝐶𝐼 + ∑ [∑ (𝐶𝑎,𝑖 (𝑗) × 𝑅𝑑 (𝑖)) − 𝑉𝑓,𝜏 (𝑗)𝑟 𝑖=1 ] 𝑗 (1) cg (τ) global costs referring to starting year τ 0; ci initial investment costs; ca,i (j) annual costs year “i” for energy-related component j (energy costs, operational costs, periodic or replacement costs, maintenance costs); rd (i) discount rate for year i (depending on interest rate); vf, τ (j) final value of component j at the end of the calculation period (referred to the starting year τ 0). here also disposal cost (if applicable) can be taken into account. [13] the global costs are defined by: the initial investment costs at the start of the measure, plus the present value of the sum of the running costs (e.g. fuel costs) during the calculation period, minus the net present value of the final value of components at the end of the calculation period. [2] investment costs eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e2 7 the methodology takes into account the investment costs of measures that are related to the energy performance of a building. these include: investments related to the efficiency of the building envelope: measures to reduce the thermal transmittance of building elements, low-energy windows and doors, measures related to air tightness; investment in energy supply systems for space heating and domestic hot water: fossil or renewable supply systems, including storage and distribution; ventilation/air conditioning: ventilation systems with or without heat recovery, active cooling systems; investments in lighting systems; other energy-related investments such as external shading devices, building automation/smart buildings; installation costs of systems and components. [2] annual costs annual costs include costs for energy carriers that cover the demand for space heating and cooling, ventilation, domestic hot water and lighting, including auxiliary energy. they also include operational costs, maintenance costs and costs for periodic replacement. income from produced energy (e.g. via photovoltaic systems or combined heat and power) can be subtracted from the costs for energy carriers. the lifetime (service lifetime) of measures should be set according to the information set out in european standards (e.g. en15459). energy prices have an influence on the final results of the methodology. the epbd recast specifies that the commission must provide information and guidance with respect to longterm energy price developments. possible sources of information might be price scenarios developed by the international energy agency (iea). [2] interest rates the choice of real interest rates (interest rate adjusted to inflation rate) is an important input for this calculation. [14] the assumed rates will differ depending on the perspective (private or societal). the final methodology should therefore include guidance on applicable interest rates. [2] the disadvantage of npv is that it is the absolute variable that does not reflect the exact rate of return. however, this problem is solved by profitability index, which is closely linked to the npv. another problem with this method can determine its determinants, such as expected cash flows and discount rates. despite these disadvantages, the method of net present value is considered accurate and reliable method to determine the economic efficiency of the project. [11] in assessing / designing the energy efficiency measures, respectively design of the building as a whole, it is necessary to consider the costs over the entire life of the building; the growth of various costs over time, including growth in energy prices; labour costs and price changes of materials. when comparing the different proposals of building it is necessary take into account synergies between considered systems. a comprehensive economic evaluation provides to investors objective information on investment opportunities (for the assumptions). comparison of different designs of buildings on the basis of an economic evaluation may motivate the owner to invest in buildings with low energy demand, which will be returned in the form of reduced energy costs. [10] 6. conclusion the complex renewal process could be very complicated and challenging. therefore, it should be noted that it is very important that all other stakeholders (industry, project developers, homeowner associations, ngos, scientific organizations, etc.) are actively involved to the process of buildings renewal. this ensures that the various perspectives are taken into account to make the methodology on cost-optimal requirements a useful tool for promoting smart and efficient buildings in europe. the eu has more than one hundred public financing mechanisms to promote energy efficiency in the building sector. most of them rightly focus on existing stock. the financing, however, largely comes through grants and subsidies which, in a context of cash-strapped governments still dealing with a public debt crisis, are not the most effective use of limited public funds. the implementation of energy efficiency-related directives varies by country, which limits the ability of property owners to achieve economies of scale across the region. therefore it is the concern for eu member states to implement to their own legislation laws and regulations for promoting energy-efficiently renewal, which should be sufficiently effective and flexible. through the enough effective mechanism could be then ensure the use of a resources public money should be used to leverage more private finance. [15] references [1] chachoua, e.; hulse, j. 2013. investing in energy efficiency in europe’s buildings: a view from the construction and real estate sectors. economist intelligence unit report, 2013. the economist, london. available on: https://www.tias.edu/docs/defaultsource/documentlibrary_fsinsight/the-eiu-report.pdf [2] cost optimality: discussing methodology and challenges within the recast energy performance of building directive. 2010. the buildings performance institute europe (bpie). available on: www.bpie.eu [3] murray, s.; gardner, b. 2012. energy efficiency and energy savings: a view from the building sector. economist intelligence unit report, 2012. the economist, london. available on: http://www.bpie.eu/uploads/lib/document/attachment/16/e iu_casestudy_report_2012.pdf [4] ecofys. 2007. u-values for better energy performance of buildings. report for eurima european insulation manufacturers association. available on: eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e2 residential buildings renewal towards to the smart concept julius golej 8 ecofys.com/files/files/ecofys_2007_uvaluesenergyperform ancebuildings.pdf [5] impact assessment for the energy performance of buildings directive recast. european commission 2008. [6] harper et al. (2003), pg. 17 and gerhart (1999), pg. 1. [7] home automation. 2015. available on: https://en.wikipedia.org/wiki/home_automation#cite_refharper17_4-0 [8] smart buildings: intelligence working for people. 2015. available on: http://blog.bouyguesconstruction.com/en/nos-innovations/smart-buildingslintelligence-au-service-de-lhumain/ [9] odporúčania na spracovanie energetického auditu verejnej budovy. siea. operčný program kvalita životného prostredia. [10] korytárová, k. 2012. postupy ekonomického hodnotenia energetických systémov v budovách. in: energetická efektívnosť a obnoviteľné zdroje energie podľa technických noriem. jasná. slovakia. [11] pelikán, r. 2011 hodnotenie efektívnosti investičných projektov. bankovní institut vysoká škola praha. česká republika. [12] máče, m. 2006. finanční analýza investičních projektů. 1. vyd. praha: grada publishing. 80 s. isbn 80-247-1557-0. [13] en 15459: 2007. energy performance of buildings – economic evaluation procedure for energy systems in buildings. reproduced by permission of din deutsches institut für normung e.v. the definitive version of the implementation of this standard is the edition bearing the most recent date of issue, obtainable from beuth verlag gmbh, 10772 berlin, germany. [14] ivanicka, k.; spirkova, d. 2013. challenges of real estate sector development in central european countries in the post crisis period. in: financial aspects of recent trends in the global economy, vol i. 300p. isbn:978-606-93129-9-5 [15] ivanicka, k., zubkova, m., sindlerova, e., spirkova, d. 1996. housing finance in the slovak republic and other cefta countries. emergo journal of transforming economies and societies. volume 3, issue 3, 1996, pages 102-123. [16] available on: https://pixabay.com/sk/budovaarchitekt%c3%bara-dom-okno-166619/ [17] available on: https://pixabay.com/sk/gulli-biela-domploch%c3%a1-strecha-349496/ [18] available on: https://pixabay.com/sk/okno-blackoutumenie-%c5%beal%c3%bazie-417926/ [19] available on: https://pixabay.com/sk/energetick%c3%a1%c3%ba%c4%8dinnos%c5%a5-energie-154006/ eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e2 this is a title 1 classification and analysis of spectrum sensing mechanisms in cognitive vehicular networks a. riyahi 1, *, s. bah 2 , m. sebgui 3 and b. elgraini 4 1 centre de recherche ersc, emi. université mohamed v de rabat. aminariyahi@research.emi.ac.ma 2 centre de recherche ersc, emi. université mohamed v de rabat, bah@emi.ac.ma 3 centre de recherche ersc, emi. université mohamed v de rabat, sebgui@emi.ac.ma 4 centre de recherche ersc, emi. université mohamed v de rabat, elgraini@emi.ac.ma abstract vehicular ad hoc networks (vanets) is an essential part of intelligent transportation system (its), which aims to improve the road safety. however, the main challenge in vanet is the spectrum scarcity which is more severe especially in the urban environment. in this view using cognitive radio (cr) technology in vanet has emerged as a promising solution providing additional resources and allowing spectrum efficiency. but, vehicular networks are highly challenging for spectrum sensing due to speed and dynamic topology. furthermore, these parameters depend on the cvns’ environment such as highway, urban or suburban. therefore, solutions targeting cvns should take into consideration these characteristics. as a first step towards an appropriate spectrum sensing solution for cvns, we first, provide a comprehensive classification of existing spectrum sensing techniques for cvns. second, we discuss, for each class, the impact of the vehicular environment effects such as traffic density, speed and fading on the spectrum sensing and data fusion techniques. thirdly, we derive a set of requirements for cvn’s spectrum sensing that takes into consideration specific characteristics of cvn environments. finally, we propose a new cvn scheme adopted in particular for urban environment where the spectrum sensing is more challenging due to dense traffic and correlated shadowing. keywords: cognitive radio, cvns, spectrum sensing, data fusion, dense traffic, correlation. received on 08 december 2017, accepted on 22 december 2017,published on 12 february 2018 copyright © 2018 a. riyahi et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.12-2-2018.154105 *corresponding author. email:aminariyahi@research.emi.ac.ma 1. introduction recently, vehicular ad hoc network (vanet) [1] has attracted a lot of interest from industries and research institutions, particularly with increasing number of vehicles on the road especially in urban area. vanet is a special kind of mobile ad hoc networks (manets) that are applied to vehicular context. they provide vehicle to vehicle (v2v) and vehicles to infrastructures (v2i) communications. on the opposite of manet, in vanet the movements of vehicles are predictable due to the road topology. besides, the high mobility leads to a higher probability of network partitions, and the end to end connectivity is not guaranteed [1]. the vanet applications can be classified into two categories: safety applications which provide the drivers with early warnings to prevent the accidents from happening, this represent the higher priority traffic, and user applications which provide road users with network accessibility which represent traffic with less priority. growing usage of applications such as exchanging multimedia information with high data in car-entertainment leads to overcrowding of the band and thereby giving rise to communication inefficiency for safety applications [1]. furthermore, the 10 mhz reserved in the ieee 802.11p standard as a common control channel is likely to suffer from large data contention, especially during peaks of road problem cognitive radio (cr) technology has been eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e4 http://creativecommons.org/licenses/by/3.0/ a. riyahi, s. bah, m. sebgui and b. elgraini 2 proposed [2]. the main role of cr is to allow the unlicensed users (a.k.a secondary vehicular users: svus) to identify spectrum holes and exploit them without interfering with the licensed users (a.k.a primary users: pus). this makes the spectrum sensing (ss) a crucial function in cr networks. even if spectrum sensing in cr networks is well studied, however the research solutions proposed in static cr networks may not be directly applicable to cvns due to high dynamic networking environment. the works in [3–5] provide comprehensive surveys about spectrum sensing in cvns. the authors in [3] review the existing studies related to ss in cvns and provide the open issues in this area. in [4, 5], the authors provide an overview of distributed and centralized cooperative ss for cvns and review some challenges and open issues in cvns. in this paper, we provide an overview of spectrum sensing mechanisms and we propose a classification for existing cvn schemes. in fact, four classes are presented: centralized, distributed, partially centralized and integrated schemes. indeed, the main characteristic that influences the spectrum sensing mechanisms used in cvns is the changeable topology of vehicular environment which may be urban, suburban or highway area. the common features of these vehicular environments are the vehicles speed, fading and traffic density. but, the effect of these features differs from vehicular environment to another. therefore, we analyze for each class the impact of the characteristics of each vehicular environment including speed, fading and traffic density on the spectrum sensing techniques and data fusion techniques used to combine the reported or shared sensing results for making a cooperative decision. this analysis allowed us to derive the main spectrum sensing requirements in cvns. in addition to the set of sensing and data fusion techniques that we recommend to use according to the specific characteristics of cvn environment, we develop a new cvn architecture that should be adequate with vehicular environment of the urban context. the rest of this paper is structured as follows: in sect. 2, we present background information on cvns and we present the most used spectrum sensing techniques. in sect. 3, we classify the existing cvns sensing schemes. in sect. 4, we analyze the environment effects on the sensing mechanisms used by these classes and we derive the corresponding spectrum sensing requirements for each environment. in sect. 5, we present our proposed cvn scheme for urban environment. finally, we draw final conclusions in sect. 6. 2. background on cvns and spectrum sensing this section provides some background on cognitive vehicular networks and the properties of vehicular environments that affects the spectrum sensing, followed by an overview of spectrum sensing techniques. 2.1. cognitive vehicular networks the cvns are composed of vehicles equipped with the cr system, allowing svus to change their transmitter parameters based on interactions with the environment in which they operate. similarly to the traditional cr, the execution of cvns is defined by a cycle which is composed by four phases: observation, analysis, reasoning and act [6]. figure 1.the cognitive vehicular cycle the observations phase consists of sensing and gathering the information (e.g. modulation types, noise, and transmission power) from its surrounding area in order to identify the best available spectrum hole. in analysis phase, after sensing, some parameters have to be estimated (e.g. interference level, path loss and channel capacity). in reasoning phase, the best spectrum band is chosen for the current transmission considering the qos requirement. the optimal reconfiguration is finally done in act phase. however, the main novel characteristic that differentiates cvns from the traditional cr is the nature of svus mobility. in one hand, due to road topology and usage of navigational systems, the vehicles can predict the future position and then it can know in advance the spectrum resources available on its path. on the other hand, the mobility increases spatial diversity in the observations taken on the different locations. this may influence the sensing performance. furthermore, fast speed increases the number of collected samples which improves the sensing performance and requires less cooperation from other svus [7]. but, when the high fading (i.e. correlated shadowing) and the presence of obstacles are taken into account, the correlated samples affect the performance [8]. besides, with faster speed the svus will have a higher probability to miss detect the pus, because the pu will be outside the sensing range of svu very quickly [9]. in addition, another parameter which can affect particularly the cooperation is the traffic density; the road topology becomes congested with dense traffic which declines the speed and the vehicles tend to be closer to each others, this decreases the performance due to correlation [8]. thus, the main features of vehicular environment which influence the sensing are speed, fading, traffic density and the obstacles. these parameters vary according to the area type (i.e. urban, suburban, or highway). reasoning observationanalysis act eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e4 classification and analysis of spectrum sensing mechanisms in cognitive 3 table 1. vehicular environment characteristics urban suburban highway density traffic very high light low vehicle’ speed low medium very high degree of fading very high high low to high the urban area is characterized by high fading, and dense traffic with low speed (around 50 km/h). the main features of suburban area are light traffic with medium speed, surrounded by some buildings which give rise to fading. the highway area is characterized with few surrounding structures which decline the fading effect, and vehicles can exceed 120 km/h [10]. 2.2. spectrum sensing techniques the spectrum sensing techniques are divided into two types local spectrum sensing (performed individually) and cooperative spectrum sensing [11]. depending on the availability of the knowledge about the primary users (pus), the local spectrum sensing techniques can be classified into two main classes: informed and blind spectrum sensing techniques [12]. 2.2.1. the local informed spectrum sensing techniques these techniques require the prior knowledge about pu’s features such as sine wave carriers, hopping sequences, pulse trains, repeating spreading, modulation type etc. [12]. in addition they are robust to noise uncertainties, but their implementation is complex. in the informed techniques, we mention matched filtering detection (mfd) [12] and cyclostationary detection (cd) [12]. the mfd could achieve the higher sensing accuracy with less sensing time, whereas sensing accuracy in cd requires long sensing time and it is not capable to differentiate the pus from the secondary users. 2.2.2. the local blind spectrum sensing techniques the blind techniques don’t require any information about the primary signal. among these techniques: energy detection (ed) [12], eigenvalue-based detection (ebd) [12] and the compressed sensing (cs) [11]. they present the advantage of requiring less sensing time. even if the ed is the most popular technique due to its simplicity, it is the worst performer technique, especially in the case of noise uncertainty. the ebd deals well with noise uncertainty than the ed, while the cs facilitates wideband ss, and reduces the channel switching overhead of narrowband ss. however the cs incurs additional hardware cost and computational complexity [11]. 2.2.3. cooperative spectrum sensing the cooperative spectrum sensing (css) has been proposed in [11] and [13] to improve the performance of ss under fading environment conditions which is especially in the case of vehicular channels characterized by a strong fading. the key concept of css is to exploit spatial diversity among observations made about the status of channel by multiple svus [11]. the process of css requires the use of some techniques such as: local observations using individual sensing techniques, cooperation models, eventually a user selection technique can be used, reporting, and data fusion [11]. however the gain of css is limited by cooperation overhead which includes: sensing delay, shadowing, energy efficiency, mobility and security [11]. table 2.summary of spectrum sensing techniques blind ss techniques informed ss techniques ed ebd cs cd mfd sensing time short medium short long short performance low high high high high 3. classification of the spectrum sensing schemes in cvns in literature, cvns are usually based on the cooperative spectrum sensing, but can also integrate a geo-localization database to assist the traditional spectrum sensing. hence, in this section, we classify these spectrum sensing schemes in cvns into four classes: centralized, distributed, partially centralized and integrated. and we identify the ss and fusion techniques used in these classes (table 3) figure 2.spectrum sensing mechanisms in cvns 3.1. centralized cvn schemes in centralized cvn schemes, a central node act as fusion center (fc) that controls the process of cooperation. in the case of v2i a fixed node such as rsu (road side unit) or bs (base station) acts as a fc [14, 15]. but, having a fixed fc may not be always possible in the case of cvns. thus, some works focus on a clustering strategy where the vehicles are selected to act as a fc cluster head [16, 17]. sensing mechanisms in cvns centralized distributed partially centralized integrated eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e4 a. riyahi, s. bah, m. sebgui and b. elgraini 4 the cooperation process is defined as follow: firstly, the svus sense the channels selected independently by the fc using compressed sensing (cs) in [14], eigenvalue-based detection (ebd) in [15] and energy detection (ed) in [17]. the fc combines the local sensing received from svus for making a final decision by using the data fusion techniques such as hard fusion (hf) [14, 17], soft fusion (sf) [15] or hidden markov model (hmm) [16]. using sf at fc provides better sensing accuracy than hf [11], because the svus report to fc the entire local sensing samples. however it incurs control channel overheads in terms of time and energy consumption especially with large number of cooperating svus. while, the hf requires much less control channel because the svus report to fc one decision bit (0 or 1), the performance can be decreased. while, the hmm is used to speed up the detection of pus by indicating to fc the observations’ number that should be received before making the fusion [16]. once the final decision is made, the fc broadcasts it to svus. figure 3.centralized cvn schemes 3.2. distributed cvn schemes works in [18–20] focus on using decentralized cvn architectures where svus are cooperating in a distributed way. in [18], a distributed scheme based on the belief propagation algorithm is proposed specifically for highway, where each svu senses the spectrum independently. then, each vehicle combines its own belief with information received from other neighbors and a final decision can be generated after several iterations. in [19] the road topology is taken into account, where the highway road is divided into equal short segments which can be recognized with a unique identifier. periodically, each svu senses the spectrum, stores the results in its internal memory and share it later to inform others vehicles about spectrum holes in their future segments. this framework is further enhanced in [20] by an experimental study. the measurements are undertaken from moving vehicle travelling under different urban conditions and vehicular speeds. and then, a cooperative spectrum management framework is proposed, where the correlated shadowing is taken into consideration. data fusion in [19, 20] is based on a weighted algorithm. figure 4.distributed cvn schemes 3.3. partially centralized cvn schemes the partially centralized cvn schemes [21, 22] are composed of two sensing levels. the first level is fast sensing (generally energy detection) performed by a central node [21] or by a set of selected nodes using cooperation [22]. in the second level, the requesting vehicles (rvs) rescan the list of holes received from coordinators using fine sensing such as cyclostationary detection [21, 22]. this may reduce the overhead of identifying all holes. besides, the rvs use the sensed holes without seeking permissions from the coordinator. this scheme is then a partially unshackle master/slave sensing relationship between fc and svus. figure 5.partially cvn schemes 3.4. integrated cvn schemes in cr the integrated concept is based on the use of a geolocalization database. this later is described in [23] as a spectral map of available channels in a given geographical eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e4 5 area, that can be provided to secondary users according to their location. however, its implementation may not be suitable for cvns when road traffic is congested which leads to many vehicles trying to query the database. thus, to mitigate the problems above, the use of database is combined with traditional sensing [24, 25]. in [24], in each segment of the highway, the vehicles should dynamically select their role (mode i, mode ii or sensing-only) according to the traffic load. in low traffic, vehicles choose the mode ii to access the spectrum database through an internet connection. in mode i the vehicles get informed from vehicles on mode ii. while in high traffic, the vehicles perform sensing-only and cooperate to detect pus. in [25], a bs is directly connected to a tv white space and database similarly to [24], the vehicles should dynamically select their role but this time according to the traffic load and the coverage of bss. figure 5.integrated cvn schemes table3.summary of classification of cvn schemes 4. derived requirements of spectrum sensing in cvns as seen in previous section each area has its own features including speed of vehicles, traffic density, and the surrounding obstacles. in fact, the spectrum sensing accuracy depends on the vehicle’s speed, traffic density and the channel fading. to the best of our knowledge, the conditions of the surrounding area are not taken into account in literature. in this section, we first analyze the impact of the vehicular environment (i.e. highway, suburban and urban), especially the effect of traffic density, mobility and fading, on both spectrum sensing and fusion techniques for each class. second, we derive the corresponding spectrum sensing requirements for each environment. 4.1. the impact of cvn environment on the local spectrum sensing the detection techniques for local spectrum sensing include cyclostationary detection (cd), matched filtering detection (mfd), energy detection (ed), compressed detection (cs) and eigenvalue-based detection (ebd). each of these techniques has its pros and cons in terms of sensing time and performance as shown in table 2. thus, the choice of the appropriate spectrum sensing according to the environment properties is very important. in highway context, high speed requires fast detection (ed, cs and mfd). however, ed could be used for open space but with high fading, it is better to use the fast and accurate detection (cs or mfd). in suburban context, the speed is light which can affect the sensing performance, and fading effect is more challenging than highway context. thus, in these cases the fast and accurate detection (cs or mfd) is favored. whilst in urban context, the fast detection is not necessary due to low speed, but the accurate detection classes ref. coordinator nodes sensing technique data fusion algorithm road topology centralized [14] base station compressed sensing hard fusion highway [15] base station eigenvalue-based detection soft fusion not specified [16] vehicle not specified hidden markov model not specified [17] three vehicles energy detection hard fusion highway/ suburban distributed [18] coordination is not needed not specified belief algorithm highway [19] energy detection weighted algorithm highway [20] energy detection weighted algorithm urban partially centralized [21] rsu or vehicle -energy detection at coordinator -fine sensing at requesting vehicles data fusion is not needed highway [22] three vehicles -cooperation among coordinators -fine sensing at requesting vehicles hard fusion (majority rule) highway/ suburban integrated [24] coordination is not needed dynamic detection: mode i, mode ii or sensing-only (local or cooperative detection) data fusion is not needed highway [25] hard fusion (majority rule) not specified eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e4 classification and analysis of spectrum sensing mechanisms in cognitive a. riyahi, s. bah, m. sebgui and b. elgraini 6 (ebd, cs, mfd or cd) is required due to strong fading. 4.2. the impact of cvn environment on data fusion of the centralized schemes generally, the cooperative spectrum sensing schemes are a composition of local ss and data fusion. as previously mentioned, each fusion technique in centralized schemes such as soft fusion (sf), hard fusion (hf) or hidden markov model (hmm), has its pros and cons in terms of delay and overhead. thus, we have to carefully choose the appropriate fusion techniques according to the environment properties. in highway context, the data fusion such as hf and hmm present the advantage of fast fusion, but due to low density, sometimes there will not be enough vehicles to cooperate for sensing, thus the sf is preferred. in suburban context, the traffic density effect is challenging than highway context. thus, it is better to use fast fusion. while in urban context, the fast fusion is vital due to high traffic. 4.3. the impact of cvn environment on data fusion of the distributed schemes the data fusion techniques which may be used in distributed schemes are belief algorithms and weighted algorithms. in belief algorithm, the data from different cooperating vehicles is merged considering the spatial and temporal correlation of different observations hence the performance of this algorithm will be affected by fading (i.e. correlated shadowing). furthermore, belief procedure is rather time consuming when larger number of svus participate in the process. while in weighted algorithm, the data is merged using weights and only if the correlation between the sensing samples of two vehicles are below a given threshold. besides, the performance of weighted algorithm degrades under low density. in highway context with open space, belief algorithm performs well under low density. but, if fading is considering this algorithm is not preferred. in both suburban and urban contexts, the data fusion techniques are affected by dense traffic and fading. hence in this case, it is better to use the selection of cooperating nodes (i.e. correlation selection) either to reduce the number of cooperating svus and to select the uncorrelated svus. generally, for both urban and suburban contexts, belief algorithm may not be suitable due to fading and high traffic density. while, weighted algorithm is required because it performs well under dense traffic. 4.4. the impact of cvn environment on the partially centralized schemes as mentioned in sect. 3, in the partially centralized, the first level (i.e. fast sensing) is based on the local sensing at the coordinator or at a subset of selected coordinators. at second level (i.e. fine sensing), it is possible to use cyclostationary detection (cd) or eigenvalue-based detection (ebd). in highway context, to speed up the detection at first level it is required to use fast detection or both fast and accurate detection according to fading effect. while in the case of cooperation at first level, it is possible to use fast fusion. at second level, it is better to use ebd because sensing time of ebd is less than cd. in suburban and urban context, it is favored to use at first level the cooperation among the coordinators to alleviate the problem of hidden pu due to presence of obstacles. at second level, it is required to use ebd in the suburban context because the effect of speed is considered, while in the urban context it is possible to use cd and ebd. 4.5. the impact of cvn environment on the integrated schemes for integrated schemes, an optimal ratio between querying the spectrum database and sensing according to the traffic density and bss coverage is required. in dense traffic the svus perform in sensing-only mode (local ss or cooperative sensing). the accuracy in this mode is also important; hence the choice of the appropriate sensing and fusion techniques depends on the environment requirements as mentioned above in subsects. 4.1, 4.2 and 4.3. generally, in highways, it is preferred to use mode i and mode ii due to low traffic density. while in suburban and urban context, it is possible to use sensing only mode due to high traffic density. however, as mentioned above, due to the hidden pu issue it is better to use cooperative spectrum sensing (css) at sensing-only mode. 4.6. summary of spectrum sensing requirements in cvns the main constraints in urban and suburban context are hidden pu, strong fading and dense traffic. the hidden pu issue requires css among svus, but due to fading and dense traffic a correlation selection is very important. the cooperation in highway context is affected by fast speed and low density, thus the accurate ss techniques with short sensing time at local ss are required such as matched filtering detection (mfd) or compressed detection (cs). the fusion techniques in css (centralized or distributed) should be adequate with the surrounding environment. for example, soft fusion (sf) and belief algorithm are favored in low traffic, while, hard fusion and weighted algorithm are required in dense traffic. in contrast, we can observe that these requirements are not always respected in literature, as in [14] where the cs with hard fusion (hf) is considered for highway. hence the effect of low density is not taken into account by using hf. in [17], the energy detection (ed) with hf is considered applicable for both highway and suburban, which could not be optimal since sf is preferred for highway and ed does not provide the required accuracy in urban context. furthermore, the schemes in [15, 16] are eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e4 7 considered applicable for all contexts, and in [16] the ss technique is not also specified. therefore, the real features of the surrounding area are not studied well in the literature either for centralized or distributed cvns. generally, it is important to use adequate spectrum sensing and fusion techniques according to the properties of the surrounding environment. furthermore the restricted and predictable mobility is not addressed for improving the spectrum sensing accuracy (table 4). table 4.summary of sensing requirements in cvns classes context highway suburban urban centralized fast and/or accurate local detection with soft fusion fast and accurate local detection with fast fusion accurate detection and fast data fusion. distributed fast and/or accurate local detection with belief algorithm fast and accurate local detection weighted algorithm accurate local detection weighted algorithm with correlation selection partially centralized first level :local spectrum sensing or css second level : ebd first level : css (fast local detection with fast fusion) second level: ebd first level: css (fast local detection with fast fusion). second level: ebd or cd integrated mode i and mode ii sensing-only mode (css) sensing-only mode (css) 5. proposed cvn scheme for urban context in addition to the set of sensing and data fusion techniques that we recommend to use according to the specific characteristics of cvn environment (table 4), we want to develop a new architecture that should be adequate for cvns especially in the urban context. we are mainly interested in spectrum sensing in the urban context because the spectrum scarcity is more severe, and secondly the spectrum sensing in urban context is not studied well. thirdly in the urban context, there are many challenging constraints that significantly deteriorate the performance of spectrum sensing. according to our analysis, in the urban context the strong fading and the pu’s hidden problem requires the collaboration among the svu to make more reliable decision [13]. but, its application in the urban environment which characterized by dense traffic and mobility of svus provokes significant problems. for instance, as the traffic density is always rising, the number of collaborating svus is increasing, and then the signalling overhead associated with reporting the sensing results tends to be considerably large. moreover, the svus tend to be closer to each other and then the svus are likely suffer from similar shadow fading which will reduce the performance of cooperative spectrum sensing. besides, due to the mobility of svus, the correlation between the svus varies over time and the svus need to join or leave the group of collaborating svus which increases the overhead in cooperative sensing [11]. thus, under the mobility condition, the connectivity among the collaborating svus should be maintaining for a long period of time. in this view the approach of clustering will be very helpful to stabilize a group of collaborating svus moving together along the road. in other hand, to minimize the overheads and the correlated shadowing associated with dense traffic, the svu selection based on the correlation should be taken into account in the clustering approach. figure 6.the main cvn requirements for urban context 5.1. the main components of the proposed cvn scheme for urban context our proposed cvn architecture is composed of the following entities as shown in the figure 7: the cluster head (ch): is local coordinator of a cluster; it has multiple roles such as:  ensuring the stability of cluster in order to maintain the collaborating svus in contact for a long period of time.  selecting among its members the uncorrelated svus that will participate in the cooperation. in this case, these uncorrelated svus are called by the active svus.  collecting and combining the local sensing results received from the active svus. the active svus: are the uncorrelated svus that will perform local sensing and participate in cooperation. the passive svus: are the correlated svus that don’t participate in cooperative spectrum sensing, but they can get the information about opportunities from ch. gateways: are used to exchange the sensing results between the chs. fading & pu’s hidden cooperative spectrum sensing mobility clustering strategy to stabilize the collaborating users dense traffic correlation svu selection to minimize overhead and correlated shadowing eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e4 classification and analysis of spectrum sensing mechanisms in cognitive a. riyahi, s. bah, m. sebgui and b. elgraini 8 figure 7.the main components of cvn scheme for urban context the general idea of our propose cvn scheme for urban context is that each ch can collect the information about the availability of the licensed channels at future location along its path. for example if it was said that the cluster c2 performs sensing in the space y, but due to the mobility, this cluster will enter another space z, and it will not be able to use the spectrum opportunities found in the previous space y. thus, the cluster c2 can benefit from the sensing results found by cluster c3 at the future space z, and the chs get these information by using gateways (figure 7). each entity (i.e. ch and its members: active and passive) in our proposed scheme has a specific role in cluster. hence for selecting the appropriate ch and its members, we need to define what metrics and specifications that should be available in each entity. therefore, in the next subsections 5.2 and 5.2 we define the metrics for ch selection and for active svu selection. 5.2. the metrics used for ch selection if we suppose that the svus have the same capability of sensing data fusion, it is not necessary to consider it as a metric. in fact, the ch has to be able to manage its cms by accepting or refusing the adhesion of new arrivals. besides, due to mobility the selected ch is expected to maintain the cluster stability to minimize the overhead associated with reclustering. hence, the svus which may be more qualified for winning the act of ch, are supposed to have a higher connectivity degree and a closer speed to the average speed of their neighbors. therefore, the metrics of ch selection are related to the nodal degree and the relative speed. the nodal degree the nodal degree 𝑑𝑁𝑖 is the total number of neighbors of a given 𝑆𝑉𝑈𝑖 . usually, svus broadcast their current state to all other nodes within their transmission range 𝑟. therefore, two svus: 𝑆𝑉𝑈𝑖 and 𝑆𝑉𝑈𝑗 are said to be neighbors if the distance between them is less than the transmission range 𝑟, and we define the neighborhood 𝑁𝑖 of a 𝑆𝑉𝑈𝑖 at time t as follows: 𝑁𝑖 = 𝑗, 𝑠𝑢𝑐ℎ 𝑎𝑠 𝑑𝑖 ,𝑗 < 𝑟 𝑑𝑖 ,𝑗 is the distance between 𝑆𝑉𝑈𝑖 and 𝑆𝑉𝑈𝑗 . thus, the nodal degree 𝑑𝑁𝑖 of 𝑆𝑉𝑈𝑖 is finding by counting their neighbors and it is deduced as the cardinality of the set 𝑁𝑖 as follows: 𝑑𝑁𝑖 = 𝑁𝑖 the relative speed the elative velocity 𝑟𝑣𝑖 of 𝑆𝑉𝑈𝑖 is calculated as follows: 𝑟𝑣𝑖 = 𝑣𝑖 − 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑣𝑒𝑙𝑜𝑐𝑖𝑡𝑦 the smaller the value of 𝑟𝑣𝑖 , the closer the velocity of the 𝑆𝑉𝑈𝑖 to the average velocity. procedure of calculating the score function of 𝑺𝑽𝑼𝒊 for being a ch each 𝑆𝑉𝑈𝑖 in one-hop have to measure its utility for being a ch while considering the aforementioned criteria 𝑑𝑁𝑖 and 𝑟𝑣𝑖 . we define the utility of each 𝑆𝑉𝑈𝑖 through a function called 𝑆𝑐𝑜𝑟𝑒 𝐹𝑢𝑐𝑡𝑖𝑜𝑛 that combines those criteria with each other. we can define the score function by the following formula: 𝑆𝑖 = (𝑑𝑁𝑁𝑖 )𝑤𝑑𝑁 ∗ (𝑟𝑣𝑁𝑖 )𝑤𝑟𝑣 where 𝑑𝑁𝑁𝑖 and 𝑟𝑣𝑁𝑖 are the normalized values of 𝑑𝑁𝑖 and 𝑟𝑣𝑖 respectively. we use the normalization in order to prevent the compensatory problem. to normalize the value of 𝑑𝑁𝑖 we use the value 𝑀, where 𝑀 is the maximal number of neighbors that a ch can accept as neighbors: 𝑑𝑁𝑁𝑖 = 𝑑𝑁𝑖 𝑀 to normalize the value of 𝑟𝑣𝑖 we use the value 𝐿, where 𝐿 is the difference between maximum and minimum allowed speeds on the road: 𝑟𝑣𝑁𝑖 = 𝑟𝑣𝑖 𝐿 the values of 𝑤𝑑𝑁 and 𝑤𝑟𝑣 are the relative weights of importance of 𝑑𝑁𝑁𝑖 and 𝑟𝑣𝑁𝑖 respectively. according to our problem description there are contracting criteria, such as we want to maximize the nodal degree and minimize the relative speed. therefore, we can assume that the 𝑤 values are in rang −1,0,1 , then our relative weights would be: 𝑤𝑑𝑁 = 1, 𝑤𝑟𝑣 = −1. therefore, the svu with high 𝑆𝑐𝑜𝑟𝑒 will be chosen as ch. 5.3. correlation-based member selection spatial correlation is a crucial factor that may affect the performance of cooperative spectrum sensing. thus, after ch selection, ch should select among their members the uncorrelated members (svus) that are supposed to perform sensing (active svus). the spatial correlation can be evaluated by correlation coefficients. it describes the correlation index between the samples observed by two vehicles 𝑆𝑉𝑈𝑖 and 𝑆𝑉𝑈𝑗 . we model the correlation function with the exponential decaying model proposed by gudmundson [26] as follows: 𝑅𝑖 ,𝑗 = 𝑒 −𝑑𝑖 ,𝑗 (𝑡) 𝑑𝑐𝑜𝑟𝑟 where 𝑅𝑖 ,𝑗 is the distance dependent correlation index and it is time-varying on account of vehicle mobility, and eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e4 9 𝑑𝑖 ,𝑗 (𝑡) denotes the separation distance between 𝑆𝑉𝑈𝑖 and 𝑆𝑉𝑈𝑗 at time 𝑡. and 𝑑𝑐𝑜𝑟𝑟 is the threshold distance which represents the correlated distance of shadow fading which usually varies according to the environment and it set to 20𝑚 for the urban environment. if 𝑅𝑖 ,𝑗 exceeds a given threshold 𝜂, then 𝑆𝑉𝑈𝑖 is strongly correlated with 𝑆𝑉𝑈𝑗 . the selection procedure based on spatial correlation our proposed algorithm for selection the active svu is as following:  at first step the ch computes the correlation coefficients 𝑅𝑖 ,𝑗 for all possible pairs of members.  a matrix m of size n*n is built. n is the total number of candidate cooperative members that belong to a cluster, {n} ={svu1 , svu2 , ….., svun}  a threshold of correlation is defined 𝜂  the diagonal elements of matrix m are auto-correlated coefficients 𝑅𝑖 ,𝑗 = 1. svu1 svu2 svu3 ….. svun svu1 1 r1,2 r1,3 ….. r1,n svu2 r2,1 1 r2,3 ….. . . . . 1 . . . . . . svun rn,1 rn,2 1 figure.8.the matrix m of correlation coefficients  the algorithm of selection of the active svus: we suppose that {𝐴} is the list of the active svus and {𝑃} is the list of the passive svus. at the beginning 𝐴 = ∅ and 𝑃 = ∅ // initialization to start the selection procedure, one svui is selected randomly from {n}. best  svu {n} {n}{svu} {a} {svu} while 𝑁 = ∅ do // the svus that are correlated with best will be removed from {n} to the {p} for each 𝑆𝑉𝑈 ∈ 𝑁 do if r(best, svu) > then {n} {n}{svu} {p} {svu} end if end for // selecting randomly one svu from {n} to be the new best best  svu {n} {n} {svu} {a} {best} end while compared with the existing works [16, 17] that are based on clustering, we don’t just describe the entities of our proposed cvn scheme for urban context but we also provide a set of metrics and procedure for selecting the ch and the active svus that participate in cooperation. in our future we will give more details about the process of clustering phase and the cooperative sensing phase 6. conclusion in this paper, we have analyzed the impact of environment effects (traffic density, speed and fading) on spectrum sensing and fusion techniques applied in cvns. and then, we have derived the main spectrum sensing requirements in cvns. this analysis enabled us to conclude that the real effects of vehicular environment are not studied well in literature for cvns, this motivate further research needed for practical implementation. thus, our discussions on the environmental effects on cvns are needed to be grounded in established empirical studies as a part of future directions pertaining to cvns. in addition to the set of sensing and data fusion techniques that we recommend to use according to the specific characteristics of cvn environment, we develop a new cvn architecture that should be adequate with vehicular environment of the urban context. references. [1] toor, y., muhlethaler, p., laouiti, a., de la fortelle, a.: vehicle ad hoc networks: applications and related technical issues. ieee commun. surv. tutor. 10(3), 74–88 (2008) [2] ghandour, a.j., fawaz, k., artail, h.: data delivery guarantees in congested vehicular ad hoc networks using cognitive networks. ieee iwcmc 2011, 871–876 (2011) [3] abeywardana, r.c., sowerby, k.w., berber, s.m.: spectrum sensing in cognitive radio enabled vehicular ad hoc networks: a review. in: ieee iciafs, pp. 1–6 (2014) [4] ahmed, a.a., alkheir, a.a., said, d., mouftah, h.t.: cooperative spectrum sensing for cognitive vehicular ad hoc networks: an overview and open research issues. ccece 2016, 1–4 (2016) [5] chembe, c., noor, r.m., ahmedy, i., oche, m., kunda, d., liu, c.h.: spectrum sensing in cognitive vehicular network: state-of-art, challenges and open issues. comput. commun. 97, 15–30 (2017) [6] singh, k.d., rawat, p., bonnin, j.m.: cognitive radio for vehicular ad hoc networks (crvanets): approaches and challenges. eurasip j. comm. netw. 2014, 49 (2014) [7] min, a.w., shin, k.g.: impact of mobility on spectrum sensing in cognitive radio networks. [8] zhu, s., guo, c., feng, c., liu, x.: performance analysis of cooperative spectrum sensing in cognitive vehicular networks with dense traffic. vtc spring 2016, 1–6 (2016) [9] zhao, y., paul, p., xin, c., song, m.: performance analysis of spectrum sensing with mobile sus in cognitive radio networks. ieee icc 2014, 2761 2766 (2014) [10] mecklenbrauker, c., karedal, j., paier, a., zemen, t., czink, n.: vehicular channel characterization and its implications for wireless system designs and performance. ieee trans. veh. technol. 99(7), 1189–1212 (2011) eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e4 classification and analysis of spectrum sensing mechanisms in cognitive a. riyahi, s. bah, m. sebgui and b. elgraini 10 [11] akyildiz, i.f., lo, b.f., balakrishnan, r.: cooperative spectrum sensing in cognitive radio networks: a survey. phys. commun. 4(1), 40–62 (2011) [12] axell, e., leus, g., larsson, e.g., poor, h.v.: spectrum sensing for cognitive radio: stateof-the-art and recent advances. ieee signal process. mag. 29(3), 101–116 (2012) [13] ghasemi, a., sousa, e.s.: collaborative spectrum sensing for opportunistic access in fading environments. in: first ieee international symposium on new frontiers in dynamic spectrum access networks, pp. 131–136. usa (2005) [14] duan, j.q., li, s., ning, g.: compressive spectrum sensing in centralized vehicular cognitive radio networks. int. j. future gener. comm. netw. 6, 1–12 (2013) [15] souid, i., chikha, h.b., attia, r.: blind spectrum sensing in cognitive vehicular ad hoc networks over nakagami-m fading channels. ieee cistem 2014, 1–5 (2014) [16] brahmi, i.h., djahel, s., ghamri-doudane, y.: a hidden markov model based scheme for efficient and fast dissemination of safety messages in vanets. in: ieee globecom, pp. 177–182 (2012) [17] abbassi, s.h., qureshi, i.m., abbasi, h., alyaie, b.r.: history-based spectrum sensing in cr-vanets. eurasip j. wirel. comm. netw. 2015(1), 163 (2015) [18] li, h., irick, d.k.: collaborative spectrum sensing in cognitive radio vehicular ad hoc networks: belief propagation on highway. vtc spring 2010, 1–5 (2010) [19] di felice, m., chowdhury, k.r., bononi, l.: analyzing the potential of cooperative cognitive radio technology on intervehicle communication. wirel. days, 1–6 (2010) [20] di felice, m., chowdhury, k.r., bononi, l.: cooperative spectrum management in cognitive vehicular ad hoc networks. ieee vnc 2011, 47–54 (2011) [21] wang, x.y., ho, p.h.: a novel sensing coordination framework for cr-vanets. ieee trans. veh. technol. 59(4), 1936–1948 (2010) [22] abbassi, s.h., qureshi, i.m., alyaei, b.r., abbasi, h., sultan, k.: an efficient spectrum sensing mechanism for crvanets. j. basic appl. sci. res. 3, 12 (2013) [23] pagadarai, s., wyglinski, a.m., vuyyuru, r.: characterization of vacant uhf tv channels for vehicular dynamic spectrum access. ieee vnc 2009, 1–8 (2009) [24] di felice, m., ghandhour, a.j., artail, h., bononi, l.: integrating spectrum database and cooperative sensing for cognitive vehicular networks. ieee vtc fall 2013, 1–7 (2013) [25] doost-mohammady, r., chowdhury, k.r.: design of spectrum database assisted cognitive radio vehicular networks. ieee crowncom 2012, 1–5 (2012) [26] m. gudmundson, “correlation model for shadow fading in mobile radio systems,” electronics letters, , 27(23): 21452146 (1991). eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e4 risk assessment model: roadmap to develop kolkata into a smart city 1 risk assessment model: roadmap to develop kolkata into a smart city sweta saraff1,*, raman kumar2, ayooshi mitra3, sayantani ghosh3, shrayana ghosh3, sulagna das3 1amity institute of psychology and allied sciences, amity university kolkata, india. ssaraff306@gmail.com, ssaraff@kol.amity.edu 2department of computer science and engineering, i k gujral punjab technical university, punjab, india, er.ramankumar@aol.in; dr.ramankumar@ptu.ac.in 3b.tech biotechnology, amity institute of biotechnology, amity university kolkata, india. abstract risk assessment is an analytical instrument used to measure a person's likelihood of certain diseases and disorders by quantitative risk factors in health (such as age, weight, living condition, literacy, the family history of a disease, etc.). a risk assessment model is a combined effort to identify and analyse potential events that can adversely affect individuals, assets, and the environment. since times immemorial, infectious diseases have been the leading cause of widespread mortality globally. new ones are materializing, and old ones are resurging. early identification of infectious disease and evaluating the risk factors are essential first steps towards executing successful disease intervention and planning control measures—various air-borne diseases like influenza, chickenpox, covid-19, etc. are candidates for such models. by customizing the risk assessment model for kolkata, we will monitor the factors responsible for the growth and spread of diseases. the current paper aims to focus on risk assessment based on the aggregation of various factors relevant to the prediction of disease transmission (raapdt). keywords: risk assessment, early identification, kolkata, pandemic/epidemic received on 15 june 2020, accepted on 14 september 2020, published on 05 october 2020 copyright © 2020 saraff, s. et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.5-10-2020.166545 *corresponding author. email: saraff, s., ssaraff306@gmail.com 1. introduction epidemics or pandemics are a public health emergency at the international level where the lives and livelihoods of millions are at stake. today experts have developed numerous models with different hierarchies that may be an artificial intelligence-based algorithm, machine learning methods, statistical modelling, or mathematical calculations based disease forecasting model. the lessons we have learned from current lockdown in different countries are that it is difficult to sustain until the disease is eradicated (91). though for their efficacy, these models need to integrate information right from block or local levels of each constituency as successful prevention of an epidemic depends upon community behavior at large. the role of governments, in-flow, and outflow of information through trustworthy and organized channels are instrumental in contact tracing and isolation of suspected infected individuals. the social and emotional behavior of different communities plays a vital role in a developing multicultural economy like india. health decision policymakers require models that integrate various perspectives, through timely and speedy dissemination of findings with different stakeholders (117). eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 http://creativecommons.org/licenses/by/3.0/ sweta saraff et al. 2 2. need for an early warning system for on-time prevention & control the role of climate in the dispersion of infectious diseases is substantiated with empirical evidence, leading to the escalation of mortality and morbidity in developing countries. (16). such diseases may reproduce at a faster rate to turn into an epidemic under the influence of climatic changes, promoting higher transmission rates: the rising requirement for early warning operational illness. it is only recently that inexpensive and open data and analytical methods have become popular, so ews (early warning system) is evolving at a relatively early stage. new studies are now being conducted at a swift pace. there was no consensus on good practice in developing predictive models or measuring their accuracy and lead time. as a result, the effectiveness of current models is also hard to assess. most research projects had relatively small funding and were therefore not conducted outside the original field of study (in this case, we consider kolkata) (45; 46). to deal with the outbreak of an epidemic, doctors need an early warning with sufficient time to plan the control measures. the purpose of an early warning system is to predict the upcoming development of disease case numbers, so that the health care professionals get adequate time to deal with unexpectedly high (or low) affected patients (27). generally, it proves to be more effective in health services when it predicts case numbers, two to six months in advance, and facilitating planned actions when the risk of disease may increase (92). longterm prediction is essential when calculated control of diseases is the objective (such as who’s onchocerciasis control programme to decrease onchocerciasis or river blindness in parts of west africa) (105). the business sectors also need proper planning to save the economies of the respective nations from crashing (77). it becomes possible only after having enough records for an evident understanding of the disease transmission dynamics (e.g. investigating the interaction between childhood diseases using data dating back to 1904 (139). in the case of infectious diseases (especially the vector-borne diseases), the predominant determinants would be spatial and temporal changes in environmental situations (27). pollen grains transmitted through the air may also serve as a vector for airborne infections (109). the role of climate in the dispersion of infectious diseases is substantiated with empirical evidence, leading to the escalation of mortality and morbidity in developing countries. (16). such diseases may reproduce at a faster rate to turn into an epidemic under the influence of climatic changes, promoting higher transmission rates: the rising requirement for early warning operational illness. it is only recently that inexpensive and open data and analytical methods have become popular, so ews (early warning system) is evolving at a relatively early stage. new studies are now being conducted at a swift pace. there was no consensus on good practice in developing predictive models or measuring their accuracy and lead time. as a result, the effectiveness of current models is also hard to assess. most research projects had relatively small funding and were therefore not conducted outside the original field of study (in this case, we consider kolkata) (45; 46). to deal with the outbreak of an epidemic, doctors need an early warning with sufficient time to plan the control measures. the purpose of an early warning system is to predict the upcoming development of disease case numbers, so that the health care professionals get adequate time to deal with unexpectedly high (or low) affected patients (27). generally, it proves to be more effective in health services when it predicts case numbers, two to six months in advance, and facilitating planned actions when the risk of disease may increase (92). longterm prediction is essential when calculated control of diseases is the objective (such as who’s onchocerciasis control programme to decrease onchocerciasis or river blindness in parts of west africa) (105). the business sectors also need proper planning to save the economies of the respective nations from crashing (77). it becomes possible only after having enough records for an evident understanding of the disease transmission dynamics (e.g. investigating the interaction between childhood diseases using data dating back to 1904 (139). in the case of infectious diseases (especially the vector-borne diseases), the predominant determinants would be spatial and temporal changes in environmental situations (27). pollen grains transmitted through the air may also serve as a vector for airborne infections (109) 3. airborne viral diseases pathogens transmitted through the air over period and distance by minor particles can give rise to airborne infections (118). these diseases spread when clumps of infectious agents are discharged into the air through sneezing, coughing, vomiting, spitting, talking, dust, or wheezing. these microorganisms cause diseases after entering the human or animal body through different respiratory passageways. airborne pathogens, also known as allergens, can cause inflammation and irritation of the nose, mouth, sinuses, and lungs. it triggers by inhalation of allergens, which on entering affect the respiratory system of a person or, in some cases, whole body (8; 114; 76; 116). these diseases typically occur through the respiratory system with an agent present in the aerosol. environmental factors encompass the potency of airborne disease transmission; the most noticeable factors being relative humidity and temperature (126; 106; 32). some candidate diseases are influenza, chickenpox, mumps, measles, and tuberculosis. 4. elements rudimentary for transmission of infectious disease eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 3 1. sources of infectious agents different vectors of infectious diseases (22; 10) found in human sources, spread either by coughing or sneezing. however, abiotic factors, like mist, dust, or aerosols, also play a significant role in the communication of infectious agents. the host, who may either be a patient (135; 21), or even health-care personnel (145), may either be in the incubation stage or the symptomatic stage or even be chronically colonized by the pathogen. transmission may also occur from an animal to a human body, where the animal plays the role of the primary host, such as fasciolosis (34). 2. susceptible host infection is a consequence of a complicated relationship between disease-causing pathogens and its conceivable host. according to osterholm et al. (2015, 2012) (97; 98), the severity of the disease caused, and its occurrence is directly related to the host organism. there are several possible outcomes following the susceptibility to a pathogen. some become severely ill after getting exposed, while others show no symptoms, whereas some become permanently colonized with the pathogens while remaining asymptomatic. there are chances of an increase in severity with aging and the presence of underlying diseases in the host body (130; 58). 3. virulent pathogensvirulence of a pathogen is the ability of microbes to cause damage to the host. virulent pathogens can be bacteria as well as viruses. virulence can help understand the severity of the infection. the pathogen virulence can vary considerably over space and time (131). this variation can be density-dependent or may be due to seasonal variation shifts. another study shows that when pathogens spread through a naive host population, the virulence rate increases (104). 4. environmental and social components environmental factors like water supply, sanitation facilities, food, and climate, play an essential role in the spread of communicable diseases that can cause epidemics. (world health organization. 2005). pavlovsky was one of the first researchers to study the interrelated components of disease occurrence in microclimate, flora, and fauna (102). as most developing infections are zoonotic, scientists are mainly keen to better understand the animal reservoir as a source of infectious diseases and how animal pathogens spill over into the human population and spread throughout the world (43). 5. modes of transmission various types of pathogens can induce infection. the modes of transmission differ based on the category of an organism. some are transmitted through infectious agents, whereas some through bodily fluids. influenza virus transmits through contact, by which fomites can cause the direct or indirect transfer of infectious secretions. the respiratory fluids travel through the air and deposit onto mucous membranes or aerosols; the droplets suspended in the air can scatter over long distances. they have a high risk of being inhaled (146; 13; 127; 128). the risk of infective droplets depositing on the mucous membrane (mouth or nose) or conjunctiva (eyes) is exceptionally high (26; 18). another possible transmission of droplets can occur through fomites (dishes, doorknobs, stethoscope, and thermometer). transmission through aerosol (< 5μm in diameter) is more dangerous as they stay in the air for long durations and can transfer to others over distances higher than 1 m. there are mostly three principal routes through which transmission occurs. these are 1. contact transmission it is further divided into two subtypes: a. direct contact transmission this mode of transmission takes place when the pathogen is directly transmitted from one infected person to another without any intermediate agent. b. indirect contact transmission occurs when the pathogen is transmitted from one infected person to another with the help of an intermediate agent (which may be both biotic and abiotic). 2. droplet transmission is a type of contact transmission where the disease is transmitted when respiratory droplets carrying harmful pathogens get carried from the respiratory tract of an infected individual to the mucosal surface of a vulnerable individual. these respiratory droplets are generated during coughing, sneezing, or even talking of an infected individual. 3. airborne transmission occurs when the infectious agents are circulated over long distances by air currents, which can then be inhaled in by any susceptible host, thus acquiring the infection. 6. current preparedness of disease management in india the coronavirus disaster has emphasized india’s willingness to cope with these devastating timeswith its high urban density, lack of hygiene and sanitation, and, more importantly, weak treatment capability. west bengal and north east indian regions share several international borders with coronavirus infected countries like china, myanmar, nepal, and bhutan. although the borders are under control, there are chances of existing unreported cases. also, as per the last census in 2011, an estimated 220 thousand people have migrated from west bengal to other states in search of work, and these estimates have exponentially grown over the last decade. west bengal ranks 4th in terms of outbound migrant labourers, after the states of uttar pradesh, bihar, and rajasthan, especially from the districts of malda, burdwan, nadia, hooghly, and murshidabad. the fact that a vast majority of these migrants are seasonal labourers and their preferred destinations are maharashtra, delhi, kerala, and karnataka (the most intensely infected states in india). they pose a severe threat of covid-19 risk assessment model: roadmap to develop kolkata into a smart city eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 sweta saraff et al. 4 transmission given the uncontrolled return of these migrants to west bengal induced by panic in the pandemic situation (84). the rapid urbanization that has increased mobility and led to higher density has raised new challenges to sanitation and healthcare. other environmental, demographic, and socio-economic factors put india at high risk for communicable diseases, including its large population that facilitates transmission of disease and changes in agricultural practices that introduce zoonotic pathogens (68). 7. indian urban agglomerations opportunities motivate individuals to shift to greener pastures, thus explaining the rate of increase in migration from rural to urban areas; this transit is more prominent in south asia (36). it leads to an entangled mess of problems despite opportunities and requires resources in finance, skilled labour, planning, sustainability issues, and nonetheless, socially empowered leadership. this migration generates clusters of urban slums that are unorganized, deprived of basic city amenities, and impoverished. urban settlements are the epicentre of power, finance, and infrastructure development (84; 119). the critical policy decisions must focus on civic amenities, housing, land-use, healthcare facilities, educational facilities, industry, and environment. kolkata, also famous as india's cultural capital, has a population growing at an increasing rate in suburbs and fringes as the core is saturated (88). it creates a discriminative distribution of wealth and civic amenities, and kolkata also suffers from the menace of exclusion, maintaining a loop of spatial poverty. this load on infrastructure reduces a city's potential to promote wellness and happiness among citizens. thus kolkata needs to be more inclusive and sustainable in its outlook for expansion and up-gradation as a smart city. 8. smart city and hybrid city a smart city is a city that uses a variety of internet sensors to gather data and then use it to manage properties, resources, and services efficiently. these include data collected from residents, transport facilities analysed and assessed power plants, power stations, water systems, waste management, crime prevention, information systems, schools, books, hospitals, and other services. they provide information obtained from public services (90). as proposed by norbert streitz (2019) (123), a hybrid city is a modern city with its citizens and physical structures, and a virtual alternative city of citizens and equivalents. however, the match between real and virtual entities will not be complete. the addition of a "traditional" city to an added digital city leads to what we call a "hybrid city." the paper's objective is to transition a traditional city into a "smart city" (123). 8.1. hybrid citya conglomeration of small towns we hope to deliver a new model of growth, a hybrid approach incorporating the best of rural and urban attributes. this model will inspire us to look beyond town and rethink our urban centres as we plan tomorrow's cities. it will suggest subduing the inferno and spreading pressures within megacities by bringing the countryside in, as it were. the hybrid city would be a sustainable community that focuses on citizen participation, equality, environmental soundness, and economic diversity. the hybrid city seeks to combine cultural sophistication, friendliness, conservation, flexibility in energy, sense of scale, location and self-reliance, and a sense of communion with the best qualities of cities like diversity, density, creativity, economic mobility and access to the means of human growth. 9. kolkata kolkata, the capital city of west bengal, is the dominant urban centre of eastern india. formerly known as calcutta, the city was chosen to be the capital of british india and hence was designed by the colonial british in the manner of a stately european capital (78; 9). however, it has now turned into one of the most overpopulated and impoverished regions of india. it has a land area of 205.00 square kilometres (87). 9.1. demographics the demographic details are as follows: population following the urban agglomeration (ua) of un world population prospects, kolkata has a population of 14.8 million (1.48 crores) in 2020 (23, 24), making it the third most crucial metropolitan city in india. according to haque, i., mehta, s., & kumar, a. (2019) (54), "the administrative jurisdictions of kolkata urban agglomeration (kua) and kolkata city district (kolkata municipal corporation / kmc; wards: 141; population: 4.5 million), covers an area of 1,886.67 sq. km and 205 sq.km, respectively." the provisional reports of census 2011 state that about 4.9 million people, which comprise about one-third of the total population of kolkata (70; 71), consist of slum dwellers residing in 2,011 3,500 unregistered slums in 141 various wards of the city (11). the population density of kolkata is 24000 per square kilometres spread over 185 square kilometres, with slum density being 2812 people per hectare (25). eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 5 literacy on the other hand, the literacy rate of kolkata hovering at 87.14% is better than the national average of 74%. age and sex-ratio the sex-ratio of kolkata currently consists of 899 females per 1000 males, which is far below the national ratio of 940 females per 1000 males. the given population pyramid (fig. 1) represents the gender difference between males and females of different age groups. the lowest population is in the age group of 70-80 years. the highest population is represented by the age group of 20-40 years. figure 1. population dynamics of kolkata, census (2011). ethnic groups the dominant religion of the city is hinduism (77.68%), followed by islam (20.27%) and christianity (0.88%). other minor religions include buddhism, jainism, and sikhism. bengalis represent the largest community in kolkata, with biharis, marwaris, and punjabis, constituting the other minor communities. administration and municipal services the city is a part of the kolkata metropolitan district (constructed to supervise planning and development on a regional basis). it falls under the jurisdiction of the kolkata municipal corporation (kmc). kolkata receives its main filtered water supply (260 million gallons daily) from the waterworks in palta, along with a few other water treatment plants and hundreds of other major and minor dams. additionally, unfiltered water is also supplied regularly for washing the city streets and the fire brigade. this water is often used by the slum dwellers for drinking purposes and is one of the major causes of the prevalence of cholera during the summer months. the garbage disposal system and maintenance of the sewers by the kmc is also unsatisfactory. 10. state of disease management of kolkata kolkata has about 48 government hospitals and 366 private medical establishments, consisting of more than 27,000 beds. it results in about 60 beds on average per every 10,000 people in the city. proper control measures are also taken by the kmc to tackle the common infectious diseases in the city (table 1). apart from these, routine immunizations are also provided by various health centres for many other diseases like diphtheria, tetanus, whooping cough, measles & hepatitis b. table: 1. treatments centres and control measures issued by kmc to deal with infectious diseases in kolkata (kolkata municipal corporation, 2020) (72) sl. no. diseases control measures treatment centres 1. malaria 1 early diagnosis and prompt treatment 2) vector control + information education and communication (iec) for improved artemisinin combination therapy (act) 60 clinics (in general) 3 malaria clinics 2. tuberculosis 1) early diagnosis and prompt treatment by sputum microscopy. 2) directly observed treatment shortcourse (dots) program. 3) an awareness campaign for the prevention and protection of the mass. 52 microscopy centres 10 x-ray centres 92 drugs distribution centres risk assessment model: roadmap to develop kolkata into a smart city eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 sweta saraff et al. 6 3. leprosy 1) early detection through tests 2) generation of awareness to report any suspicious skin lesions. 3) multi-drug therapy (mdt) as per the routine control program. 59 treatment centres 4. gastroenteritis 1) check on potable water by means of sample analysis 2) early treatment of affected through medicines and oral rehydration solution (ors) 89 treatment centres 5. poliomyelitis 1) routine immunization programs. 2) intensified pulse polio immunization (ippi) program. 98 centres for routine immunization 1378 booths for ippi mobile teams for house-tohouse visits. 6. cough, cold, fever, influenza and diarrhoea examination, diagnosis, and treatment 26 dispensaries 11. modelling and forecasting of infectious diseases 11.1. epidemiology modelling strategy the methodology used can vary depending on the intent of the research, how adequately a disease's epidemiology is comprehended, the percentage and characteristic of available data, and the modeller’s context and experience. depending on their treatment of variation, chance, uncertainty, and time, it can be divided into numerous groups (47). • population dynamic models: a study of modifications in the arrangement of population • ·risk models: describes the threat of introduction of disease into a population qualitatively • analytical models: utilized to recognize federations amongst the circumstance of disease and risk factors • economic models: considering monetary values and allocation of reserves (55). based on the flu-forecasting landscape (96; 29), there are four types of disease forecasting models: 1. mechanistic model these are models based on differential equation algorithms. they describe the transmission pattern of an epidemic (132). 2. agent-based model this type of model creates a simulated population that mimics a real population. it uses demographic information from various online databases to approximate disease transmission through such a population (50). 3. the machine learning or regression model follows the history of epidemic outbreaks and uses that pattern to predict future epidemics. these models employ various approaches like clustering statistical time series (121), nonparametric approaches (14), or regularised regression (5). 4. data assimilation or dynamic model this type of modelling approach involves implanting a mechanistic model into a probabilistic model (37). it enables explicit modelling of both the pattern of disease transmission along with observational noise (100). thus, this modelling approach combines both the parametric and random uncertainties observed in the models mentioned above. 11.2. climatic and non-climatic risk factors in disease forecasting the identification process of both climate and nonclimatic risk factors offers a crucial insight into the design of the early warning system (ews). many studies classify environmental risk factors associated with climatic vulnerabilities (143). two primary modelling methods are available: statistical and biological. the statistical models are used to estimate the association between forecaster variables (e.g., climate) and thereby study the chance of disease occurrence. biological models aim at providing an automatic process in which climate impacts pathogens and vector population dynamics. most of the past research used locality-based statistical analysis and vector distributions for particular historical disease steps. although biodiversity models may provide greater insight into mechanisms that lead to variations in the impact of diseases, they need to inform the climate's eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 7 impact on all aspects of pathogens and vector dynamics. it has led to the rare use of these models (107). irrespective of the modelling methodology, it would be irresponsible to ignore the impact of non-climatic factors. these include indicators of population susceptibility to outbreaks of disease, such as low immunity (for example, malaria), high hiv prevalence, malnutrition, drug, and insecticide resistance. failure to assimilate such influences may lead to incorrectly attributed variations in the incidence of disease due to climate effects and reduced predictive precision (142). 12. pre-existing models of disease forecasting disease forecasting is an approach to predicting the outbreak of an epidemic. a disease forecasting model provides information beforehand about the disease outbreak's geographical extent and its expected time of onset (129). early identification of an infectious disease contributes immensely towards executing successful disease intervention methods, efficient resource allocation, and planning control measures and saving more lives (99). disease forecasting models are developed by the combined efforts of computer science specialists and the mathematical community. these models propose an investigation of relevant literature describing diseases and their physiological phenomena (92). one such model formulated using differential equations is the sir model. compartmental models abridge the statistical modelling of infectious diseases. the population is reallocated by marking regions-for example, s, i, or r (susceptible, infectious, or recovered). people can make changes between compartments. traditionally, the directive of the labels indicates the flow arrangements between the compartments; for example, seis means susceptible, exposed, infectious, and susceptible. 12.1. sir model of disease forecasting sir stands for susceptible-infected-removed. the classical kermack-mckendrick sir model has an executable working algorithm and has been used to describe the transmission of the covid-19 virus pandemic (20). it is a mechanistic model that consists of both parametric and non-parametric methods (95). the model formulates the following quadratic equations (138): 𝑑𝑑𝑑𝑑 𝑑𝑑𝑑𝑑 = −βsi (1) 𝑑𝑑𝑑𝑑 𝑑𝑑𝑑𝑑 = βsi − νi (2) 𝑑𝑑𝑑𝑑 𝑑𝑑𝑑𝑑 = νi (3) re = 𝑑𝑑(0)𝛽𝛽 𝜈𝜈 = 𝑑𝑑(0)𝑏𝑏 𝜈𝜈𝜈𝜈 = 𝐷𝐷𝐷𝐷𝐷𝐷𝑑𝑑(0) 𝜈𝜈 (4) here, β is the rate of disease transmission, s is the number of individuals susceptible to be infected at time t, i is the number of infected individuals (both symptomatic and asymptomatic) at time t, r is the number of recovered individuals at time t and ν is the recovery rate. hence, the term βsi is the number of newly infected individuals per unit time t, corresponding to a homogeneous interaction between the infected and susceptible populations. similarly, the term νi is the number of recovered individuals per unit time t. the sum of the left-hand side of equations (1), (2), and (3) is the derivative of the total population size, and the sum of the right-hand sides is zero, and hence the total population size remains constant. also, as it is evident that the recovered individuals are equal to the total population size, which is neither susceptible nor infected (over a time t), thus, it is mathematically depicted as r(t) = n – s(t) – i(t). also, here, d is the duration of infection (thus, d = 1/ ν), n is the total population size, κ is the number of contacts (each with the ability of transmission) an infected individual has made per unit time; this parameter is independent of n (thus, κs/n of these contacts have susceptible individuals). τ is the fraction of contacts which results in transmission; hence it is called the transmissibility parameter, and re is the effective reproductive number. thus, here β = b/n where b =κτ. here, the actual reproductive number equates the timespan of the infection with the number of susceptible individuals that an infected individual has contacted, per unit time, and the transmissibility (i.e., the transmission rate). it evaluates the number of new infections; each infected individual can cause at the beginning of the outbreak. re is thus the degree of pathogen fitness. the sir model becomes a sirs, where the recovery does not give long term immunity, and the individual can become susceptible again. sir model becomes susceptible, infectious, and recovered. 12.2. sis model of disease forecasting (susceptible, infectious & susceptible) the sis model explains the spread of a solitary transmissible disease in a susceptible population of size n. transmission of the pathogen arises when infectious hosts communicate the pathogen to healthy vulnerable individuals (115). here, s stands for susceptible, i for infected. it deals with the fact that someone who was affected by a viral disease and later got cured can reencounter the same disease in the future. for example, individuals highly symptomatic with regular common colds and intermittent fever have weak immunity in the long run. these infections do not provide long term resistance after initial recovery, thus making them susceptible again. in this model, at any time, the susceptible and infected people are taken into consideration, which makes up the whole population. a risk assessment model: roadmap to develop kolkata into a smart city eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 sweta saraff et al. 8 logistic equation rules the dynamics of the infection. the sis model allows us to analyse how the infection continues to spread (and is possibly reintroduced) over time. the sir model is more appropriate to the disease awareness framework that the paper wants to implement (75). the reason why sis models are selected above sir models is that the sis model demonstrates the persistence of the disease within the population over a long period when individuals are re-infected, and the model maintains endogenous equilibrium. the sis model studies diseases where the extinguished infection resurfaces in a community, and the intensity of these reintroductions is looked into (51). 12.3. tdefsi model of disease forecasting theory guided deep learning based on synthetic knowledge epidemic forecasting (tdefsi) (137), is a disease forecasting system that combines the benefits of deep neural set-ups and high-resolution disease process simulations across networks. tdefsi produces precise, high-resolution spatiotemporal predictions using data from time series of low resolution. during the training process, tdefsi uses high-resolution epidemic simulations to identify patterns in urban-inherent spatial and community heterogeneity as one component of training statistics. a two-branch recurrent model of the neural network is trained to take low-resolution observations both within and between seasons as features and produce high-resolution, detailed forecasts. the resulting forecasts are influenced by the diverse financial, demographic, and geographic characteristics of different urban regions and mathematical disease propagation theories through networks. 12.4. bayesian model of disease forecasting bayesian model is a predictive and intuitivestatistical tool based on the theory of probability to identify the uncertainties in a particular model, in which probability expresses a degree of credence or the strength of our faith in the unit occurrence of a proposition. bayesian statistical methods use the bayes theorem to measure and update probabilities after new data gets collected. this approach uses sequential analytical methods to integrate previous experiments' effects into the design of the next experiment. bayes theorem is stated mathematically as: p(a | b) = p(b |a) p(a) p(b) where a and b are events and p(b) is not equal to zero. most bayesian methods assess sophisticated calculations, including the utilization of techniques for simulation. it provides a natural and principled way to combine prior information with data in a robust theoretical decision framework. it offers data-based and reliable inferences, without depending on exponential approximation. there are disadvantages to this model too. it may produce successive distributions that are heavily influenced by priors. it often generates additional computational costs, particularly in models with several parameters. we may apply the bayesian model described above to the various diseases forecasting in kolkata (63). 13. case study: coronavirus (covid19) coronavirus is a human-infected virus, usually causing an upper respiratory infection (uri). it was first characterized in the 1960s. the virus spreads through coughing, sneezing, close personal contact with viruscontaminated objects, etc. human coronavirus is known to cause acute respiratory syndrome, mers cov (beta coronavirus causing middle east respiratory syndrome), sars cov (beta coronavirus causing severe acute respiratory syndrome), and 2019 novel coronavirus (2019-ncov) which started in wuhan, china (64). timeline of covid-19(adapted from covid-19 dashboard by the centre for systems science and engineering (csse), 2020) (32) · • coronavirus disease 2019 (covid-19), caused by severe acute respiratory syndrome coronavirus 2 (sars cov-2), was identified first in december 2019 in wuhan, china. • gradually, the virus spread over all of china's provinces and over 150 other countries in asia, europe, north america, south america, africa, and oceania. • sars-cov-2 was published as a public health emergency of international concern by the who on 30 january 2020. • on 11 march 2020, it was declared as a pandemic by who. • by 20 may 2020, there had been 4,897,567 total confirmed cases of sars-cov-2 infection in the ongoing pandemic 14. customizing disease forecasting model for smart kolkata any information or data acquired needs to be quantitatively or qualitatively analysed to understand it in a prima facie broader sense and utilize it later for implementation in a project, either in vitro or in vivo. before diving into data analytics, it is crucial to understand the main differences between qualitative and eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 9 quantitative data. quantitative data are information on quantity, and therefore the number and definition of qualitative data and the phenomena which can be detected but not measured, such as language, are descriptive. whereas, the qualitative data focuses on a multi-method approach that requires an understanding of its fundamentals. it means that qualitative scientists study things in their natural environments and try to elucidate phenomena (113). 15. identifying hotspots in epidemiology of infectious diseases, the term "hotspot” signifies "red flag" regions of escalated disease burden or high order of transmission (74). in the case of malaria, it helps to identify clusters with increased incidence (7), which might either be a district (122) or even a country (59). there are various types of hotspots, defined as: 1. transmission hotspot – a region of elevated efficiency of transmission (4). 2. emergence hotspot – a region with a high frequency of emergence or re-emergence of drug-resistant strains (103). 3. burden hotspot – a region with increased occurrence or prevalence of a disease or a geographic collection of cases (6). emerging infectious diseases (eids) are a noteworthy problem for public health and global economies (85). various efforts to comprehend eid emergence patterns have emphasised the fact that because of its rapid nucleotide substitution rates, negligible mutationproofreading ability, and hence elevated capacity to adapt to new hosts (140), viral pathogens (especially rna viruses) are a significant threat (30). identifying hotspots provides a foundation for emerging a predictive model for the domains where new eids are most likely to originate. regression results from surveys about socio-economic, ecological, and environmental correlates of eids (62) identify the regions where new eids are expected to emanate (emerging disease 'hotspots'). to identify a hotspot of infectious disease, knowing just about the causal pathogens is not enough. factors that resulted in that pathogen being designated as an emerging disease, such as the climate, the chronological exposure of a pathogen within a human population, the increment distributions, the incremental frequency of incidence (or virulence), etc. (86). 16. contact tracing contact tracing is a well-accepted method to control infectious diseases by attempting to detect cases more efficiently by following chains of infection (38). its target is the identification and isolation of individuals who have been in contact with infectious or affected individuals (69). it aims to set a target for the various control measures such as prophylactic vaccination (2) or preemptive culling (66), to combat the spread of the infection or even totally eradicate it (40), more efficiently. contact tracing links the individual-level spread of infection to the network of potential transmission routes. the network is a very significant factor in contact tracing as it brings in to count the impact of social interaction, which can occur over a wide range of geographical distances, which in turn can determine the risk of infection (69). several types of contact tracing models exist, like models that consider randomly interacting models (61; 89) or network-based models that consider transmission pathways (53; 60). detailed pairwise equations associated with these models can deliver a precise mechanistic understanding of human interactions' distributed nature (39). the pairwise correlation models provide a robust mechanism for capturing spatial effects by framing equations for the number of linked pairs instead of calculating just the number of single affected individuals, thus linking individual-level behaviour to population-level dynamics in times of epidemics (133; 42). it offers a systematic framework and can be easily parameterized using the existing data and formulates consequences based on the transmission network (39). 17. rate of spread of diseases in a clustered population the human-to-person contact networks establish the substrate along which communicable diseases spread. most network-based studies of this spread concentrate on degree variations (the number of contacts and the number of individual contacts). however, other consequences, such as clustering, changes in infectiousness or vulnerability, or differences in the closeness of contact, may play an important role (82). edge weights (measuring proximity or length of contacts) affect even if there are similarities between different edges. besides, these effects can play a significant role in strengthening each other, with the more considerable influence of clustering when the community is maximally heterogeneous or when close connections are also densely clustered (82). the disease spike is one of the most substantial concerns in an outbreak, and its severity and duration are critical for health care providers. epidemic statistics are in the form of time-series such as p(1), ..., p(t), ..., p(t), where p(t) represents the number of current cases of infection reported in time t and t is the length of the epidemic season. the peak value is the highest value in the time series. in the framework of the epidemic, it corresponds to a high number of individuals that are newly infected in any given week during the epidemic season. seasonal diseases, such as influenza, typically remain latent and display a dramatic increase in the number of cases only before the season starts. emerging infectious diseases show a typical pattern of sharp rise. risk assessment model: roadmap to develop kolkata into a smart city eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 sweta saraff et al. 10 18. risk assessment based on aggregation of various factors relevant for prediction of disease transmission (raapdt) several methods are used to study the transmission of diseases. perhaps the most crucial decision in building a model is how the population's interactions are portrayed (73). the efficacy of agent-based modelling lies in its dynamic functioning based on customization capacities in heterogeneous populations. simulations based on fuzzy, complex logic are helpful in medical decision making as it is nearly improbable to objectify future human behaviour. though fuzzy logic and bayesian probabilities address different problems of uncertainty, probability theory predicts the frequency of occurrence or likelihood of an event, and fuzzy logic tries to find out /ascertain the presence of observation within a prior (approximately) defined set. the current model is more descriptive and exploratory in perspective, keeping different logical analysis models in perspective. it comprises synthetic population mapping based on specific attributes (136), contact tracing, and hotspot marking. almost all sophisticated strategies use agent-based models; each person's movements are tracked, as individuals in the same social cluster can infect each other. usually, to build these models, significant capital and institutional support are needed (81). 18.1. area-wise population density kolkata is approximately 205 square kilometres (54). north kolkata is known for 19th-century architecture and narrow lanes, including areas such as shyambazar, shobhabazar, chitpur, cossipore, baranagar, sinthee, and dum dum. these places are mostly clustered and high population density zones. central kolkata is inclusive of government officials buildings (the west bengal secretariat, general post office, reserve bank of india, high court, lalbazar police headquarters,etc.) and close conglomerates of businesses and old markets (burrabazar, central avenue, b.b.d.bag, esplanade and strand road). this area is densely populated and quite old. whereas park street, which comprises thoroughfares such as jawaharlal nehru road, camac street, wood street, loudon street, shakespeare sarani, and a. j. c. bose road, has a mixed density with mushrooming of both businesses, malls and residential apartments. south kolkata is an urban high socio-economic locality (ballygunge, alipore, new alipore, lansdowne, bhowanipore, tollygunge, jodhpur park, lake gardens, golf green, jadavpur, and kasba) with medium to low density, in comparison with other localities. the two townships also situated in kolkata region are salt lake city (bidhannagar) and newtown, these townships have their municipalities and have low population density. 18.2. age it is imperative to know about the different age groups in kolkata and control the future spread of airborne diseases. according to the census of west bengal (2011), people in the age group (05-14) -20% and (40-49) -14% years are much more than the other age groups. the least population is in the age group (81 +). but nowadays, due to better medication, the population density of the age group 81 + is gradually increasing. air pollution is a significant threat to children for both acute and chronic respiratory disorders. children are more prone to airborne diseases due to their immature respiratory organs. the population density of the children of age group (5 to 14) is very high in kolkata, so it is vital to monitor them in case of a pandemic. people in the age group above 81 + are also prone to such diseases due to weakened immunity. but it is advisory for all the age groups to be aware. it may be suspected that in future pandemics, the younger (5-14) and the older people (81+) are more prone to infection, and so, proper monitoring is necessary. 18.3. literacy the literacy rate of a city is a parameter of utmost importance in devising a disease forecasting model to prevent the outbreak of an infectious disease in that city. the higher the literacy rate, the higher the standard of living, the better the chances of fighting an epidemic. a literate individual is more likely to have a job and a secure financial condition. hence, it is more likely to be socially aware and have the means to follow the guidelines during an epidemic outbreak. the literacy rate of kolkata (as per census 2011) is 87.14%, which is higher than the state (west bengal) average of 77.08%. the male literacy percentage of the city ranks at 89.08%, whereas the female literacy ranks at about 83.79%. for administrative purposes, kmc has divided kolkata into 144 different wards. out of these, wards 1-33 lie in the north of the city, and the average literacy rate of northern kolkata is about 85.41% except for some wards like 23, 24, 29 and 32 covering the regions pathuriaghata, posta, ultadanga and kankurgachi, and narkeldanga respectively, where the average literacy rate is around 72.68%. in central kolkata, consisting of wards 34-65, the average literacy rate is about 83.33% (the zone with the lowest literacy rate in the entire city) except for the wards 36 and 60 covering the regions of beliaghata, sealdah, rajabazar, and park circus. these wards have meagre literacy rates of 66.34% and 44.16%, respectively. south kolkata, consisting of wards 66-141, on the other hand, has the highest literacy rate in the entire city with an average rate of around 88.79%, with the highest literate region being ward 96 with a literacy rate of about 96.57%. in case of an epidemic outbreak, the city's central region would be more prone to getting affected by the disease and would contribute in spreading it further. eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 11 simultaneously, the southern zone of kolkata would be the least prone region within the city. 18.4. sanitation hygiene and sanitation play the most significant role in controlling the spread of infection. globally, about 8, 27, 000 people, in underdeveloped and developing countries, die because of poor sanitation and hygiene, every year (who) (141). poor sanitary practices such as unsafe sewage disposal, lack of clean drinking water, open defecation, and usage of community washrooms (public toilets) perpetuate a vicious cycle of disease and poverty. surveys suggest that more than 75% of kolkata's slum dwellers do not have a personal supply of clean drinking water, and about 88% of them use public toilets (112). adding to that is the unacceptable levels of the potability of the supplied drinking water (125). additionally, a crowded living condition does not allow for proper sewage disposal systems to be built in the slums. studies suggest a high rate of childhood diarrhoea in the various slums of the different municipal wards under the kmc (101). i. water supply management in kolkata water and sanitation are the two most important criteria for a smart city as both give us an idea about poverty, economic growth, and sustainability. a watersmart city must combine urban planning and water management to create a green and robust infrastructure to cope with different challenges. it is designed to acquire meaningful and actionable data on flow rate, pressure, and distribution of the water (19). the issue of water being priced is controversial due to its physical, political, and economic aspects. rapid urbanization and population growth in many cities worldwide have contributed to scarcity and rising water costs (79). the government of india (goi) aims to cover the increasing number of homes with uninterrupted 24×7 water supply: piped-water supply with all metered household connections. the goi initiated another 100 smart cities mission in 2015 to integrate city services, allow more effective use of scarce resources and, generally, improve residents' quality of life. for a city to qualify as 'smart' in terms of water supply, it needs to build a 'smart and sustainable water network. thus, it depends on how well municipal water utilities manage distribution networks with available resources, raise awareness of efficient use, provide safe water, manage leakage, and generate income. kolkata currently faces a confusion of whether to choose a right path of valuing water or the typical path of not imposing any price on it (48). the highly unequal distribution of water in many parts of the city is due to the lack of infrastructure and weak financial conditions (65). the availability of water results in a change of population density; hence, it is an essential parameter for this model. ii. the drainage system in kolkata the principal features of the existing drainage basin were laid out in the master plan of calcutta metropolitan district (1966-2000). it was prepared by cmpo concerning water supply, sewage, and drainage. much of kolkata's core city (93) is covered by a hybrid form of underground drainage network in which both sewage and storm water flow into the same conduit (83).the drainage is raised and eventually discharged into the tidal river through outfall channels further down to the east (94). because of the city's unique physical characteristics (bowl-shaped), the centre is somewhat in depression, so that every drop of wastewater/rainwater needs pumping to relieve waterlogging (12). hence due to waterlogging in different parts of the city, the spreading of disease is very common. 18.5. social behaviour and habits of residents human behaviour plays a significant part in the spread of contagious infections (28). hence, understanding the impact of behaviour on the spread of diseases can be crucial in enhancing control measures (44). the lockdown period during the covid-19 pandemic and other epidemic breakouts over time has made it quite evident that in times of an epidemic outbreak with no significant pharmaceutical interventions, people tend to change their habits to avoid getting infected (49). different nonpharmaceutical measures such as social distancing, closing schools and universities, and a ban on mass gatherings (31; 80) have significant impacts on human lives. constant news updates about the spread of the disease and the numbers of affected and dead individuals also tend to make people follow hygiene more rigorously. population mixing is also an essential factor in the spread of a viral disease. information about social mixing is a significant parameter in devising intervention strategies, to control the spread of the disease, using social network epidemiology (108; 35). in kolkata, we see a variety of changes in people's behaviour and habits depending on their socio-economic status, level of literacy, and residence. in the case of the slum dwellers, consisting of about 33% of kolkata's population, who generally belong to backward socioeconomic classes and have a low literacy level, it is not possible to change their sanitary habits and practice higher levels of hygiene. also, they live in highly crowded and congested areas. thus their risk of getting infected and spreading the infection is much higher than those living in high rises. additionally, their lack of social awareness and unstable economic conditions prevents them from practicing social distancing. spreading of rumours and fake news through social media has become a menace and is a pandemic in itself. in this modern world, people are insensitive to the needs of others. selfish behavior leads to drift between people and their relationships. people become obsessed with themselves so much that they refuse to add to others' risk assessment model: roadmap to develop kolkata into a smart city eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 sweta saraff et al. 12 needs. since news channels sometimes exaggerate ordinary news, it can establish dark thoughts in the minds of the audience, hence terrifying them that they start believing in false rumours and start acting upon them. often, this fear-mongering causes people to be insensitive towards others and is a cause of increasing the crime rate. during a pandemic outbreak, working at the local and community level fosters public trust and better adherence to rules and preventive measures. calling for kindness and compassion by emphasizing the danger to higher-risk groups is an effective marketing tactic because it acknowledges that different individuals are at different risk. evolutionary theories suggest this may be due to the "grandmother effect," which liberated the group's younger members while the elders cared for the kids. one hypothesis indicates that kindness is advantageous because it causes people to feel superior to lower animals and increases the unity of communities. and it may be that when they're young people are generous to the elderly in the hope that as they get older, they can receive the same treatment. social networks can broaden the spread of harmful and helpful habits during an outbreak, and these effects can reach friends, friends of friends, and even friends' friends across the network. the virus itself spreads from person to person, and because people placed centrally in networks come into contact with more people, they are often among the first to become infected (134). it is not only the responsibility of government institutions to implement social distancing; the citizens are equally answerable and should be rational and sensible in their conduct. self-control and patience surmount the hurdles and provide the zeal to handle difficult situations. 18.6. power supply & network the availability of electricity and regular water supply, in particular, are essential factors in coping with any pandemic. as many countries believe, and in some cases demand, that people take the need for social isolation seriously to minimize the spread of the virus, there has been an exponential increase in pressure on service providers to maintain their services. according to smith, d. (2020) (120), "the key to maintain necessary utilities infrastructure' uninterrupted power supplies are 'only as reliable as the use of fuel." electricity companies often can speed up electricity restoration during non-health events, such as heavy storms, by bringing in more qualified employees from firms and contractors outside an emergency area. the proper power supply is a critical factor for the undisruptive functioning of a city. during a pandemic, physicians and primary workers' capacity to handle infected populations depends on access to adequate, uninterrupted, reliable energy in the clinic, medical equipment, and drugs (15). a pandemic requires a speed of deployment for solutions. for many vulnerable communities, off-grid decentralized renewable power can respond to this challenge. these energy solutions not only provide people with access to their current healthcare needs. they can also provide investment for these countries in the clean, sustainable energy infrastructure of the future (52). 18.7. socioeconomic conditions socioeconomic status is a combination of financial, educational, occupational, and locational influences (17). despite being somewhat related, each of these parameters reflects slightly varying individual and societal forces correlated with disease processes (110). education provides the skills and qualifications required for getting a job and earning a salary. this salary, in turn, provides the means to pursue education and the other necessities of life (like food, clothes, and shelter). it finally results in a positive social, psychological, and healthy lifestyle. a stable economic condition leads to functional social status and vice-versa. this cycle also impacts the health of an individual and their family. an individual (or a family), with a better socioeconomic status, has more chances of pursuing a healthy, hygienic lifestyle, and hence protect themselves from getting affected with an infection, than one without. 18.8. environmental factors the two significant environmental factors impacting infections are climatic conditions and pollution levels. climatic conditions west bengal has a tropical climate. summer, monsoon, shortfall, and winter are the main seasons. the wet-dry tropical climate exists in the southern region and the wet subtropical climate in the north. the state has a wide range of precipitation per year with 64 inches (1 625 mm) of rainfall, of which 13 inches (330 mm) are reduced by average in august and less than 1 inch (25 mm) per year by december. the average annual temperature is 26.8ºc (80.2ºf), and the average temperature range from 19ºc (66.20ºf) to 30ºc (86.0ºf) (3). the city faces temperature variance during the summer and winter months, ranging from 28°-42° celsius during the summers and a chilly 14°-26° celsius during the winter months. kolkata receives an average annual rainfall of 1605 mm. the weather is humid and sultry during the summer months but dry and pleasant during the winter. climate is an important environmental factor that can influence the spread of disease. temperature and other climatic conditions can indirectly have an impact on health (124). climate change results in changes to weather conditions and patterns of extreme weather events. the health effects of climate change (including climate change and extreme weather events) on human infectious diseases are affected by pathogens, hosts/vectors, and disease transmission. firstly, the number of infectious diseases is eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 13 limited by climatic variables, both spatially and temporally. changes in spatial and temporal climate variables affect pathogens, hosts, and their interactions with humans' development, survival, reproduction, and viability (144). climate change can weaken human immunity and disease-sensitivity, thereby influencing the transmission of disease. it could lead to the destruction of habitats and agricultural production strain, causing problems like crop failure, malnutrition, hunger, increased displacement of people, and conflict over land. these pressures may help increase the sensitivity of humans to infectious diseases. waterborne diseases can prevail in some areas if there is still a lack of clean surface water for climate change. south europe has enormous potential for the geographical spread of the malaria epidemic and other tropical diseases (56). during the monsoons, the fluctuating humidity levels and the moisture present in the air provide the perfect condition for the infectious agents, like bacteria, viruses, fungi, and other pathogens, to breed. different vectorborne diseases, like dengue, cholera, typhoid, influenza, and hepatitis-a, take over the rains and affect thousands of inhabitants of the city (111). the extreme temperatures during the summer months also pave the way for a range of diseases like heat fever, a viral infection of the upper respiratory tract, skin allergies, and gastroenteritis, which wreak havoc in the city (1). some pathogens are transmitted by vectors to complete their life cycle and require intermediate hosts. appropriate climatic and climatic conditions are essential for the survival, reproduction, distribution, and transmission of pathogenic diseases for vectors and hosts. climate and weather changes can, therefore, affect the spread of infectious diseases by affecting pathogens, vectors, hosts, and livelihoods. (41). pollution environmental pollution is a significant problem and impacts the health of the human population. pollution reaches its most severe proportions in the densely populated urban-industrial centres of the more developed countries—the unsustainable anthropogenic activities mixed with environmental pollution, which leads to significant problems with public health. thus we need to consider pollution as a possible parameter in this model (67). 18.9. morbidity morbidity refers to the signs of illness or disease within a population. it can also refer to medical problems arising from medical treatment. morbidity is also about the risk factors associated with diseases, comparing and contrasting health events between different populations. today, it poses a significant problem for all health conditions that can impact the population's general wellbeing (57). people with pre-morbid conditions or any genetic endowment concerning diseases like hypertension pressure, diabetes mellitus, cancer, rheumatism, etc. are more vulnerable to high-risk infections. they are always a cause of worry for healthcare professionals, and also the economic burden of disease increases manifold for them. 18.10. assimilation of data the data thus collected from varied sources, for example, primary health care centre, district collector's office, municipal corporation office, local police station, hospitals, clinics, etc. must be systematically organised in a national portal/ state portal for dissemination of accurate, reliable and timely information. this data must be collected regularly so that policymakers and citizens are aware of the current situation (136). the ground staff responsible for data collection must receive adequate training and be sensitive while dealing with private information. confidentiality related to data sharing should remain at the highest levels. conclusion observing human reaction is instrumental in the development of a decision model for disease forecasting. risk assessment and human reaction to the new stimuli form the basis for disruption in healthcare systems. pandemics can overwhelm healthcare systems around the world. humans are known to influence and adapt to changing environmental conditions. the critical factor in overcoming the pandemic is understanding how people behave in response to real and perceived risks that they face during the situation. the world health organization, too, recognizes the importance of human behaviour during a pandemic. according to who's "outbreak communications planning guide," responsible behaviour can reduce the spread of a virus as much as 80%. the public health care system, integrated with community engagement at the block level, is known to give fruitful results. it may not be to everyone's preference to interrupt one's daily routine for others' sake. still, throughout history humans have been willing to make sacrifices to protect others' safety. the readiness to do so appears to be a part of human nature. there is evidence from the prehistory of human communities helping aged people and people with disabilities who were unable to live on their own. also, a fine-tuning between central, state and local governments are required to disseminate information through trusted channels. the various forecasting models hold good, only if the warning signs are noted, and precautionary measures are taken. public health care systems in smart cities require multilateral cooperation, communication and coordination between primary healthcare centres, digital facilities, awareness campaigns through various media channels, and setting up of 24*7 counselling centres, staff training facilities, and emergency kiosks at hospitals. the practical application risk assessment model: roadmap to develop kolkata into a smart city eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 sweta saraff et al. 14 of stakeholders -behaviour based model points to the need for data management and analysis, through advanced and sophisticated techniques. these models have exploratory, predictive, and prescriptive capacities and guides on how a well organised and thoughtful data-driven modelling system can put both policymakers and modellers in an optimal position. references [1] agrawal, a. s., sarkar, m., chakrabarti, s., rajendran, k., kaur, h., mishra, a. c...,& chawla-sarkar, m. 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(2018). defining the sizes of airborne particles that mediate influenza transmission in ferrets. proceedings of the national academy of sciences, 115(10), e2386-e2392. eai endorsed transactions on smart cities 01 2021 04 2021 | volume 5 | issue 14 | e3 this is a title eai endorsed transactions on smart cities review article 1 iot applications to smart campuses and a case study d. minoli,* and b. occhiogrosso dvi communications, new york, ny abstract internet of things (iot) concepts are now being broadly investigated for actual deployment initiatives. although ecosystem-wide architectures and standards are still slowly evolving and/or still lacking, some progress is being made; standardization fosters flexibility, cost-effectiveness, and ubiquitous deployment. applications range from infrastructure and critical-infrastructure support (for example smart grid, smart city, smart building, and transportation), to end-user applications such as e-health, crowdsensing, and further along, to a multitude of other applications where only the imagination is the limit. this article discusses a specific example of an iot application supporting smart campuses. smart campuses are part of a continuum that spans cities at the large-scale end to smart buildings at the small-scale end, and encompass universities, business parks, hospitals, housing developments, correctional facilities, and other real estate environments. the specific use case example covered in this article relates to an actual project to automate some key functions at a set of large campuses, but the nature of the campus is not directly revealed. after a review of the applicable iot and control technologies, this best practices article describes technological solutions that were employed to support the requisite control functions and serves as an example for the applicability of iot to smart campus applications. keywords: iot, smart campus, scada, m2m, emergency generators, wireless, 900 mhz radio, ism. received on 23 november 2017, accepted on 29 november 2017, published on 19 december 2017 copyright © 2018 d. minoli and b. occhiogrosso, licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.19-12-2017.153483 1. introduction – what is the iot the basic concept of the internet of things (iot) is to enable objects of all kinds to have sensing, actuating, and communication capabilities, so that locally-intrinsic or extrinsic data can be collected, processed, transmitted, concentrated, and analyzed for either cyber-physical goals at the collection point (or perhaps along the way), or for process/environment/systems analytics (of predictive or historical nature) at a processing center, often “on the cloud”. applications range from infrastructure and critical-infrastructure support (for example smart grid, smart city, smart building, and transportation) [1-20], to end-user applications such as e-health, crowdsensing [21], and further along, to a multitude of other applications where only the imagination is the limit (noting that the references included are only a miniscule subset of the available literature). some refer to the field as “connected technology”. while the reach of iot is (expected to be, or become) all-encompassing, a more well-established subset *corresponding author. daniel.minoli@dvicomm.com deals with machine-to-machine (m2m) communication, where some architectural constructs and specific use cases have already been defined by the standardization community, including but not limited to etsi, the european telecommunications standards institute [22, 23]. a discussion of the ecosystem entails an assessment of the end-point sensors (their capabilities, cost, power supply, communication interfaces, security, and data reduction or computing mechanisms – if any), the local edge network (typically but not always wireless [4]), the aggregating network (e.g., a low power wide area network [lpwan]), and the advanced analytics engines needed for appropriate processing. figure 1 provides a logical view. many iot applications, especially m2m applications, require only low data-rate streams; however, some evolving applications involving real time multimedia (e.g., surveillance) entail higher data-rate streams and also specified quality of service (qos) goals. nearly all iot streams require the basic confidentiality, integrity, and availability (cia) security mechanisms encompassing the eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e4 http://creativecommons.org/licenses/by/3.0/ d. minoli and b. occhiogrosso 2 end-to-end environment. table 1 provides a high-level synthesis of the iot ecosystem. figure 1. a logical view of an iot ecosystem the use case example covered in this article relates to an actual project to automate some key functions at large (but geographic-confined) campuses. after a review of the applicable iot and control technologies, the article describes technological solutions that were employed to support the requisite control functions. this real-life case serves as an example for the applicability of iot to smart campus applications. table 1. a taxonomy of the requisite synthesis to achieve broad-scale deployment of iot area subdiscipline iot/m2m technologies sensors, including electric and magnetic field sensors; radiowave sensors; optical-, electrooptic-, and infrared-sensors; radars; lasers; location/navigation sensors; seismic sensors; environmental parameter sensors (e.g., wind, humidity, heat); pressurewave/presence sensors, biochemical and/or radiological sensors, gunshot detection/location sensors, and vital sign sensors for e-health applications. networking (especially wireless technologies for personal area networks, fogs, and cores, such as 5g cellular) analytics system architectures proposed iot architectures, e.g., arrowhead framework, internet of things architecture (iot-a), the iso/iec wd 30141 internet of things reference architecture (iot ra), and reference architecture model industrie 4.0 (rami 4.0) m2m architecture (etsi high level architecture for m2m) architectures particularly suited for scada-based legacy systems iot/m2m standards layer 1, wireless (ism, pan, lpwan) layer 2/3, ip, ipv6, mipv6 upper layers vertical-specific cybersecutity confidentiality integrity availability 2. smart city/smart campus/smart building there is a relatively small body of literature on the topic of smart campus; a few key references include [24-35]. in the context of infrastructure management, a subset of iot applications apply to the physical continuum that spans a smart city, a number of institutional campuses, and a plethora of independent smart buildings, as illustrated in figure 2. a campus is typically comprised of several buildings under one administrative jurisdiction, such as a (private) university or college, or a hospital complex encompassing of several structures in a small geographic area. some also consider a stadium to be a campus. a campus can also be seen as a group of clusters in various regions, but all managed by an oversight entity, for example a state university that may have a number of campuses (say two dozen or more) throughout the state, or a state prison system with a number of sites, each comprised of several buildings. an example of campuses in new york state (nys) is included in table 2, compiled from public sources. eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e4 iot applications to smart campuses and a case study 3 figure 2. graphical view of smart city, smart campus, smart building continuum typically, one building acts as an administration office where all the campus communications might terminate, e.g., if there is a control center, and where possibly there is a wide area network (wan) handoff. in multi-site campuses, there may be one centralized site where the various data (environmental parameters, control, video, and so on) is centralized to one, say state-wide or city-wide, control center for monitoring, processing, storage, or analysis. the in-campus connectivity may be supported by campus fiber, or may not be present a priori (or even if present, not usable for m2m/iot applications for various administrative, security, or technological reasons.) a newly built campus, e.g., a business park (for example, the capital one financial campus in goochland county, virginia) may well have interbuilding fiber connectivity, but older campuses may not have such wired connectivity. either way, a dedicated campus network for m2m applications may be needed, and it may typically be wireless in nature. while the applications that are being considered for smart cities are fairly encompassing, as seen in table 3, the applications that are typically considered for smart campus are somewhat more limited. these might include external campus surveillance; internal and external surveillance; building emergency generator, automatic transfer switch (ats) and digital meter (dm – aka smart meter) monitoring and control; elevator monitoring and control; and hvac monitoring and control. other campus-related applications include remote door control, water leak detection, washing machine scheduler, smart parking, smart trash cans, light control, and emergency notification [24]. energy efficiency and conservation are becoming more important, especially considering governmental mandates in many jurisdictions to reduce energy consumption by 20% by 2020 or 2025; iot-based capabilities can facilitate the achievement of these goals (e.g., tracking the electricity use of various systems and appliances in the building by monitoring the energy usage data from a smart meter). it goes without saying that smart building iot applications (e.g., occupancy, lighting, daylight harvesting, access control, fire safety, and so on) also can be considered to be part of smart campus applications [7]. table 2. example of ny state campuses new york state (nys) agency name no. of buildings total sqft metropolitan transportation authority 43 ~ 11,000,000 office of general services 22 ~ 19,000,000 office of mental health 24 ~ 19,000,000 city university of new york 14 ~ 20,000,000 dep. of corrections 71 ~ 38,000,000 state university of new york 35 ~ 86,000,000 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e4 d. minoli and b. occhiogrosso 4 table 3. typical smart city applications area examples public safety & security, intelligent transportation systems (including smart mobility, vehicular automation and traffic control) for example, traffic monitoring, to assess traffic density and vehicle movement patterns, e.g., to adjust traffic lights to different hours of the day, special events and public safety (e.g., ambulances, police and fire trucks). smart grids for example, advanced metering infrastructure (ami) and demand response (dr) lighting management control light intensity when area is empty or sparsely populate and/or when background light is adequate (e.g., depending on lunar phases, seasons, etc.). smart building for example, building service management, specifically for city-owned real estate to remotely monitor and manage energy utilization waste management for example, for disposition of public containers or cityowned properties sensing (including crowdsensing, smart environments, and drones) environmental monitoring, for example sensors on city vehicles to monitor environmental parameters. in crowdsensing the citizenry at large uses smartphones, wearable, and car-based sensors to collect and forward for aggregation a variety of visual, signal, and environmental data water management for example, to manage water usage or sprinklers, considering rain events surveillance/intelligence for example, streets, neighborhoods, ring-of-steel applications, gunshot detection smart services as an example, the new york city transit department of buses has recently designed a 700/800 mhz radio digital system to be deployed in up to 6,500 city buses and 1,500 non-revenue generating vehicles. applications include advanced computeraided dispatch automatic vehicle location to track the position of buses in real-time via global positioning system (gps) using cellular overlay mechanisms and provide advanced fleet management and next-bus time of arrival notification at bus stops throughout the region and on customer smartphones. goods and products logistics (including smart manufacturing) for example, optimized transportation, warehousing, goods tracking, trucks monitoring 3. early efforts automatic meter reading (amr) is a process for automatically collecting consumption information from energy metering devices or water meters and transmitting that information to a processing site, typically to process billing statements. some basic concepts and systems were developed in the 1970s and early 1980s [35]. as noted, meters that support data transition are known as dms or smart meters. the basic open systems interconnection reference model (osirm), is applicable in this context. at the lower layers one has physical and networking communication mechanisms. at the application layer (or beyond) one has a control protocol such as scada (supervisory control and data acquisition), although the layering may not be perfectly pristine with this early control protocol. at the lower layers, the issue of ubiquitous connectivity was a limiting factor. one of the design goals of the integrated services digital network (isdn) was to support a cost-effective packet-based “d channel” that not only supported out-of-band-signaling but also cost-effective distributed data collection for meter reading, home security systems, and telemetry, effectively an early version of iot/m2m [36]. for example, u.s. patent 5,452,343 (september 1995) states that “this invention relates to a method and apparatus for accessing customer meters and for controlling customer devices over a telephone line” [37]; a variety of related research emerged in the late 1980s-early 1990s (e.g., but not limited to [38] [41].) unfortunately, isdn proved too expensive, too complex, and not innovative enough to see broad deployment in the u.s., or for that matter in other parts of the world. more cost-effective solutions were sought, including wireless technologies that ranged from non-standard metro-level packet transmission, to 2 g and 3 g cellular. (two decades later, the currently-evolving narrowband-iot [nb-iot], a cellular technology connecting iot devices that replaces a gsm carrier with an nb-iot cell and provides ~25 kbps in downlink and ~64 kbps in uplink, and/or lpwan systems, may eventually play a key role in this arena.) eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e4 5 4. scada is an example of m2m effectively, scada is an example of an early m2m protocol [42-50]. scada is a well-known control system architecture for industrial process management. scada concepts have roots to work done in the u.s. in the 1940s. general electric and westinghouse advanced the concept in the 1960s and 1970s (with the advent of computers.) the term scada per se came into use after the utilization of a computer-based master station became common, by the mid-1960s (e.g. westinghouse prodac systems and ge getac systems.) scada has evolved through four generations: (1)"monolithic" systems based on minicomputers (e.g., dec pdp-11s) and the communication protocols used were proprietary. (2) "distributed” systems, where scada information and command processing was distributed across multiple lanconnected stations. (3) "networked” systems based on standardized components connected through internet-suite communication protocols. and, (4) “iot/cloud based” computing, where scada systems have progressively adopted internet-oriented transmission protocols and “utility computing” methods. scada system performs four functions: (i) data acquisition; (ii) networked-based data communication; (iii) data presentation; and (iv) control. these functions are performed by four kinds of scada components: 1. sensors (either digital or analog) and control relays that directly adjoined with the managed system. 2. remote telemetry units (rtus), effectively small computerized units located in the field at sites where the entity to be monitored/managed resides. rtus serve as local collection points for gathering information from sensors and delivering commands to control relays. 3. scada master units, high-power computer workstations or consoles that operates as the central processor. these units provide a human interface to the system and automatically manages the system under control in response to sensor inputs. 4. the communications network that connects the scada master unit to the dispersed rtus. for the purpose of this project, the campuses rtus are located the emergency generator, the ats, and the dm. modbus is a defacto protocol standard that defines how the scada data is communicated over networks. modbus was originally a serial communications protocol developed in the late 1970s for use with programmable logic controller (plc) devices; the basic machinery is currently utilized for connecting many types of industrial electronic devices connected on different types of networks. multiple rtus and/or intelligent electronic devices that supports the modbus protocol can be connected to the same physical network to create a modbus network. modbus uses a basic message structure: it transacts raw words and bits. more specifically, modbus-rtu and modbus-tcp are the specifications on how this scada data is packaged for transmission over specific types of networks: • modbus-rtu addresses transmission of data over serial communication networks, by adding a station id and cyclic redundancy check (crc) trailer to the scada data. this approach typically operates over serial connections (rs-485.) • modbus-tcp addresses transmission of data over ip networks, by adding an ip header and checksum trailer to the scada data. modbus-tcp is the more ‘modern’ solution; when usable, modbus-tcp approaches may be ideal and afford excellent flexibility and the ability to integrate, if desired, multiple (iot/m2m) campus applications. these environments are comprised of scada devices that support the modbustcp protocol and utilize 10baset ethernet (or faster) for their connectivity. in modbus-tcp the scada data payload is wrapped with tcp/ip; the devices then communicate over a modbus network structured with an ip infrastructure (e.g., an intranet, if desired.) in large or tall buildings, however, there may be distance limitations for the raw ethernet runs. modbus-rtu uses rs-485 links to connect the devices to the local controller. depending on the height, conduits, and cable runs of the building, the 100-meter limit of ethernet may be exceeded, and intermediary (active) switched may be required. rs-485 (also called tia-485) is a serial interface that allows up to 32 devices to communicate in a half-duplex mode on a single pair of wires (plus a ground wire), at distances up to 1200 m. all devices are individually addressable, allowing each device to be accessed independently. the rs-485 standard specifies differential signaling on two lines; the information is transmitted differentially to provide high noise immunity over the twisted pair medium. an rs-485 arrangement can be configured as "two-wire" or "fourwire." in the "two-wire" case the transmitter and receiver of each device are connected to a twisted pair, while "fourwire" arrangements have one master port with the transmitter connected to each of the "slave" receivers on one twisted pair (the "slave" transmitters are all connected to the "master" receiver on the second twisted pair.) only one device can actively drive the line at a time. two-wire rs-485 networks have lower wiring costs and the ability for nodes to communicate amongst themselves but transmission is limited to half-duplex; four-wire arrangements allow full-duplex operation, but are limited to master-slave setups where a "master" node must request information by polling individual "slave" nodes (“slave" nodes cannot communicate with each other.) 5. applicable radio technologies for campus wireless connectivity, typically, one wants to make use of license-free industrial, scientific, and medical (ism) bands. while a number of such bands exist, the ism unlicensed radio band at 900 mhz (specifically at 902-928 mhz) may optimally be employed due to better weatherrelated performance, due to the reduced congestion from wi-fi and other devices (operating in the 2.4 ghz or 5 ghz eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e4 iot applications to smart campuses and a case study d. minoli and b. occhiogrosso 6 region), and due to the support for “long distance links”, being that these links can span several miles. however, wireless services operating in the ism band(s) must intrinsically accept potential interference from other users since there is no regulatory protection from ism device operation: the transmissions of near-by devices using ism (e.g., including other similar radios, cordless phones, bluetooth devices) can give rise to electromagnetic interference and disrupt radio communication utilizing the same frequency. fortunately, there are power restrictions mandated by fcc to minimize interference and thus unlicensed low power users are generally able to operate in these bands without being impacted by or causing problems to other ism users. traditional spread spectrum techniques, where a radio signal generated with a particular bandwidth is by design spread in the frequency domain into a signal with a wider bandwidth, will reduce the interference (however, spread spectrum system are slightly more expensive than normal transmitter-receivers.) for the purpose of this use case we assume that the campuses in question are relatively small: 1 mile x 1 mile (or at most, 2 miles x 2 miles); the institutional campuses (universities, housing complexes, hospitals, business parks) fit this description. some of the transmission considerations to be taken into account include the following: • signal attenuation, such as free space loss (fsl) and atmospheric attenuation. fsl is due to propagation, according to the laws of electromagnetism; attenuation relates to the spreading of the wave front in free space (vacuum). this is ldb = 21.98 + 20*log10 (d/), where d is the distance and is the wavelength of the transmission [51]. for any given distance the free space loss at 2.4 ghz is 8.5 db larger than at 900 mhz. for small campuses (e.g., 1 mile x 1 mile), the fsl loss is relatively small. oxygen, water vapor, fog and rain will add to the fsl attenuation (their effects are worst at 2.4 ghz); however, the total attenuation is still fairly small and is usually no worse than 0.02 db/km. for small campuses (e.g., 1 mile x 1 mile) this attenuation a nonissue in most reasonable weather conditions. • trees and other obstructions can be a problem. 900 mhz transmission (and much more so at 2.4 ghz) mode requires line of site (los) (or at least near los) for proper and predictable operation (trees typically cause more higher attenuation at 2.4 ghz.) the expectation is that for small campuses (e.g., 1 mile x 1 mile) that have tall buildings (8-10-12-14 stories high), tree will not be an issue; however, intervening buildings will be an issue – to address this challenge, repeaters will be used in the appropriate topological configuration. regardless, the design goal is to elevate the antennas so that one clears all obstructions. • fresnel zone clearance. in order to obtain proper propagation conditions one typically need to clear 60% of the first fresnel zone (a long imaginary ellipsoid between the two end points). at 900 mhz, for a 1 km link one will need one to elevate the antennas 6.5 meters above the roof line on both sides to clear obstruction (e.g., another building), at mid-point. • effective transmit power limitations. the fcc part 15 rules limits the effective transmit power of transmitters in the ism bands to 36 dbm. the maximum transmitter output power into the antenna must not exceed 30 dbm (1 watt) and the maximum effective isotropic radiated power (eirp) must be less than 36 dbm (4 watts). • antenna gain. this relates to the amount of signal energy received. the gain of a reflector-type antenna increases as one increases the area of the parabolic surface. for a given physical size, the antenna gain at 2.4 ghz is higher than an antenna at 900 mhz (e.g., for a semi-parabolic grid antenna measuring 40x24 inches has a 15 dbi gain at 900 mhz and 24 dbi at 2.4 ghz). for small campuses (e.g., 1 mile x 1 mile), the use of a whip (omnidirectional) or yagi (directional antenna) may suffice, although both of these have low gain. these parameters (and some others) need to be fed into a link budget analysis calculation, to ascertain that there is sufficient transmission and reception margin. for small campuses (e.g., 1 mile x 1 mile) the expectation is that the margins are adequate when using typical off-the-shelf radio components. round-robin polling by the scada master allows a conflict-free management of the radio channel and transmissions. iot security (iotsec) in general, as well as and especially in the case of critical infrastructure and/or wireless links, is very important [52] – [54]. link encryption, encryption of data at rest, and trusted execution environments (tees) (also intel’s trusted execution technology [txt] and others) at the operating system (os) level are needed at a minimum. 6. case study this case study is drawn from actual deployment projects. it deals with interconnecting emergency generators on roof of buildings in institutional campuses, where the ats and dm is located in the basement. the campus may or may not have available fiber, therefore a radio network is needed to interconnect the various buildings to a designated administrative building. that building may have a control center, or in the case of a larger agency there may be clusters of campuses over a geographic region, with only one centralized city-wide or region-wide control center; in this case it is assumed that a wan network is present to interconnect the dispersed campuses to the control center. the electrical devices are scada controlled. there will be a need to connect the rtus in the basement and the rtu at the generator on the roof. because the building may be tall, the modbus-rtu (rs485) approach is used. these networks can be variously classified as campus area networks (cans), neighborhood area networks (nans), or even field area networks (fans). eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e4 7 figure 3 depicts an example of a deployment at the logical level. the actual project entails providing connectivity at 30+ campuses with an average of 8 buildings per site (but some campuses have a larger number of buildings.) these campuses are not greenfield. all buildings that do not have fiber will be equipped with radios. roof-top radios and equipment will be housed in a nema enclosure. omnidirectional whip antennas are planned to be used, but if directional yagis are needed (perhaps in very highdensity campuses), they will be used. the goal is to create star topologies with los links, as shown in an illustrative example in figure 4. if repeaters are needed due to building obstructions, they will be judiciously employed as illustrated in figure 5. strong link encryption is utilized for security. figure 3. logical view of iot/scada design figure 4. example of iot/scada design for a campus (los solution) eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e4 iot applications to smart campuses and a case study d. minoli and b. occhiogrosso 8 figure 5. example of iot/scada design for a campus (repeater solution) conclusion this paper described a real-life use case of an iot/m2m/scada application in a smart campus environment. references [1] a. al-fuqaha, m. guizani, m. mohammadi, m. aledhari, and m. ayyash, "internet of things: a survey on enabling technologies, protocols, and applications", ieee communication surveys & tutorials, vol. 17, no. 4, fourth quarter 2015 pp. 2347ff. 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[50] s. k. tan, m. sooriyabandara, and z. fan, "m2m communications in the smart grid: applications, standards, enabling technologies, and research challenges", international journal of digital multimedia broadcasting, volume 2011 (2011), article id 289015. [51] d. minoli, satellite systems engineering in an ipv6 environment, francis and taylor 2009. [52] d. minoli et al, “iot security (iotsec) considerations, requirements, and architectures”, ieee ccnc 2017, january 2017. [53] j. granjal, e. monteiro, and j. sá silva, "security for the iot: a survey of existing protocols and open research issues", ieee comm. surveys & tutorials, vol. 17, no. 3, 2015, pp. 1294ff. [54] c. lai, r. lu, d. zheng, h. li, and x. shen, "toward secure large-scale machine-to-machine communications in 3gpp networks: challenges and solutions", ieee communications magazine communications standards supplement, december 2015, pp.12ff. bios daniel minoli, principal consultant, dvi communications, has published 60 well-received technical books, 300 papers and made 85 conference presentations. he has many years of technical-hands-on and managerial experience in planning, designing, deploying, and operating secure ip/ipv6-, voip, telecom-, wireless-, satelliteand video networks for global best-in-class carriers and financial companies. over the years, mr. minoli has published and lectured extensively in the area of m2m/iot, network security, satellite systems, wireless networks, ip/ipv6/metro ethernet, video/iptv/multimedia, voip, it/enterprise architecture, and network/internet architecture and services. mr. minoli has taught it and telecommunications courses at nyu, stevens institute of technology, and rutgers university. benedict occhiogrosso is a co-founder of dvi communications. he is a graduate of new york university polytechnic school of engineering. mr. occhiogrosso's experience encompasses a diverse suite of technical and managerial disciplines including sales, marketing, business development, team formation, systems development, program management, procurement and contract administration budgeting, scheduling, qa, technology operational and strategic planning. as both an executive and technologist, mr. occhiogrosso enjoys working and managing multiple client engagements as well as setting corporate objectives. mr. occhiogrosso is responsible for new business development, company strategy, as well program management. mr. occhiogrosso also on occasion served as a testifying expert witness in various cases encompassing patent infringement, and other legal matters. eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e4 an event-driven health service bus despina t. meridou school of electrical and computer engineering, ntua, heroon polytechniou 9, 15773, athens, greece dmeridou@icbnet.ece.ntua.gr charalampos z. patrikakis department of electronics engineering, tei of piraeus, petrou ralli & thivon 250, 12244, egaleo, greece bpatr@teipir.gr andreas p. kapsalis school of electrical and computer engineering, ntua, heroon polytechniou 9, 15773, athens, greece akapsalis@icbnet.ece.ntua.gr iakovos s. venieris school of electrical and computer engineering, ntua, heroon polytechniou 9, 15773, athens, greece venieris@cs.ntua.gr panagiotis kasnesis school of electrical and computer engineering, ntua, heroon polytechniou 9, 15773, athens, greece pkasnesis@yahoo.gr dimitra-theodora i. kaklamani school of electrical and computer engineering, ntua, heroon polytechniou 9, 15773, athens, greece dkaklam@mail.ntua.gr abstract the enormous set of health and wellbeing data sources, as well as the diversity of the data, calls for an effective, time-aware integration paradigm that aids at the manipulation of the information by experts as a whole and not as individual pieces of knowledge. in this paper, we present the health service bus, a service-based platform built on top of the enterprise service bus architecture. treating new information, either humangenerated (e.g., doctors, dieticians, etc.) or device-generated (i.e., smart wristbands or connected scales) as events allows for in-time action and treatment. platform interoperability is ensured both on service level, since any service irrespective of its specification can be plugged into the health service bus seamlessly, and on data level, since health standards, such as hl7 fhir and loinc, are leveraged. categories and subject descriptors i.2.1 [artificial intelligence]: applications and expert systems – medicine and science; i.2.4 [artificial intelligence]: knowledge representation formalisms and methods – semantic networks; j.3 [computer applications]: life and medical sciences – medical information systems general terms management, performance, design, standardization. keywords health service bus; enterprise service bus; quad store; health and lifelogging data ontology. 1. introduction the increasingly vast number of health-related connected devices and applications has led to the emerging need for a data integration paradigm, enabling the overall processing of health and well-being data on the basis of remote healthcare and home recovery. at the same time, in order to ensure the completeness of the patient’s profile, the medical history, maintained by hospitals and medical centers, needs to be incorporated. in this paper, we present an enterprise service bus based platform, named “health service bus”, which is able to aggregate health data for a particular user/patient and maintain them in a semantic format, ensuring seamless homogeneity and interoperability. new data entering the platform are ultimately treated as events, achieving on-the-fly access by any interested application, service or medical center. we assume that data are transferred by applying the hl7 fhir standard and that they arrive at the platform expressed using the loinc standard and then they are transformed in rdf based on a target vocabulary. any interested party can take advantage of the initial and the transformed data by sending a request to the appropriate service of the health service bus. the rest of the paper is organized as follows: in section ii, work related to the health service bus is discussed. section iii presents the architecture of the platform, whereas in section iv the data storage and management techniques adopted in the health service bus are described. section v presents the client functionality offered by the platform and, finally, in section vi, we summarize the conclusions and remarks of our work, as well as issues for future study. 2. related work in this paper, our view is to examine the use of an intelligent enterprise service bus (iesb) [1] in the field of healthcare. the iesb used as a basis for the design of the proposed platform has been based on the service bus developed within the fp7 european project arum [2], focusing in production management. the iesb of arum is a service-based, multiagent platform for managing the production of highlycustomized products, such as aircrafts and ships, especially in the ramp-up and small-lot modes. the service bus is implemented on top of jbossesb, an open-source enterprise mobihealth 2015, october 14-16, london, great britain copyright © 2015 icst doi 10.4108/eai.14-10-2015.2261684 service bus in java programming language. the services that are deployed in the iesb provide scheduling and planning functionality, as well as functions of ontological data management and security. while in arum data are coming from the legacy systems of companies (e.g., mes and erp systems), we are arguing that the same architecture could be used to serve the needs of a healthcare management system based on the collection of data from wearable and other smart devices. the idea of using a service bus for healthcare management is not new: ibm has proposed in the past the use of ibm healthcare service bus [3], a platform for enabling the integration of multiple healthcare-related services. the deployed services may belong to the category of consumers, such as applications that request a service, or to the category of providers, such as applications that provide a requested service. each consumer or provider is assigned to a binding component, which collects all requests, transforms them to an internal format, understood by all the binding components of the system and then forwards it to a normalized message router, through which the message eventually arrives to the appropriate producer or consumer. the integration of heterogeneous services is accomplished with the use of the wsdl, soap, and hl7 standards. in [4], a health service bus, based on the mule open source esb, is presented. each application or service connected to the service bus is considered an abstract endpoint. the physical implementation of each abstract endpoint is called a service container and provides the interface of the service to the service bus. a translation service is responsible for transforming all health-related data in xml format. during the transformation process, from and to hl7 v2, hl7 v3 and openehr, an ontology-based mapping tool, named owlmt, is used. while the above described healthcare-related platforms are service-based and aim at the interoperability of heterogeneous health services, they do not leverage the major advantages of the semantic languages owl and rdf, which play a key role in the seamless integration of disparate data. even though ryan and eklund [5] make use of ontologies, their use is limited to the data transformation process. above all, in our approach, we can take advantage of the inference mechanisms supported by semantic languages and reason over the transformed healthcare and well-being data. 3. general description of the health service bus platform the health service bus platform has been designed having in mind three directives: (a) the idea of treating new data related to the health and well-being of a user of the platform as events arriving at a publish/subscribe endpoint, easing their effective handling and sharing within services deployed in the platform as well as within services and tools external to the platform, such as custom mobile applications, healthcare systems, etc., (b) the ability to easily connect and integrate with existing and future personal health monitoring systems and tools, including both single device solutions such as wearable devices that monitor specific living conditions and parameters such as calories burned, and middleware solutions capable of providing comprehensive personal health records and (c) the capability of easily extending the connectivity of the presented platform, and linking it to similar platforms, taking advantage of the capabilities of existing decision support systems for health, and allowing professionals and practitioners to connect and make use of it, through the development of the necessary tools and interfaces. the above have been reflected in a service-oriented platform, named “health service bus”, as depicted in figure 1. as described in the following sections, health and well-being data are collected for each platform user from wearable devices, such as smart watches, bluetooth-enabled toothbrushes, smart pills with edible microchips, etc. we assume that data collected from external to the platform devices are formatted on the basis of the universal code system defined by loinc. once the loinc data have entered the platform, they are semantically annotated on the basis of a well-defined knowledge base, namely the hld ontology described in section iv. data produced by the hsb services, such as alerts on elevated blood pressure, on the basis of the received data are treated as events and sent to a dedicated topic of the health service bus. all services are subscribed to this topic, named “health and well-being data events (hwde)” topic, this way receiving immediately and being able to process newly fetched information. the hsb services are able to communicate with each other with respect to internal issues in two ways. for point-to-point communication, a jms queue is defined for each service. for example, when the query service wants to send a sparql request to the semantic service, it has to “place” the appropriate message to the queue of the latter. for the services to be able to communicate in a publish/subscribe fashion, a second topic has been defined, namely the health service bus (hsb) topic. in this course, when new loinc data arrive at the platform, the loinc data handler, which acts as the entry point for the loinc data, sends a message to the hsb topic through the events manager service, notifying all the subscribed services. 4. data storage and management data storage in the platform consists of the loinc data warehouse (ldw), the quad store and the rules repository. as described below, the loinc data handler is handling the ldw, while the semantic service, the events manager service and the data analysis service have direct access and update rights with respect to the quad store data. finally, the rules repository is a jena-based data structure of semantic rules, which are exploited by the data analysis service for inference purposes. we assume that data arriving at the platform have the form of fhir messages, thus ensuring platform interoperability. even in the cases, where the data collected by devices or connected figure 1. the hsb architecture middleware do not comply with the fhir and loinc standards, translator modules from the proprietary format to fhir and loinc compliant formats will be used, making use of the device vendor’s api. these translator modules are implemented as part of the loinc data handler. the loinc data handler is the main entry point of the platform regarding new data. new data are collected directly from wearable and environmental devices and are assumed to be fully fhir and loinc compliant. the loinc data handler component stores the data in their initial form in a documenttype database. the motivation behind the selection of nosql databases was primarily performance and the semi-structured form of the data. once newly arrived data are stored in the database, the loinc data handler pushes a new event in the hsb topic of the health service bus via the events manager service. at the same time, it sends a message to the queue of the semantic service in order to inform the service of the new batch of data that is available for transformation. after the loinc data have been stored in the nosql database, they are sent to the queue of the semantic service by the loinc data handler. the role of the semantic service is twofold. on the one hand, once it receives the data in their initial format, it has to semantically annotate them by exploiting predefined mappings between the fields that a message may contain and the schema of the hld ontology. in this way, we are moving from raw to meaningful data. at the same time, ubiquitous and seamless integration of data coming from multiple devices of different vendors is achieved. this processing stage includes transforming the loinc data into rdf quads, this way organizing the rdf dataset in useroriented graphs. thereby, processing and querying the data for a specific user becomes faster and more effective. on the other hand, the semantic service is responsible for providing access to the semantic data, since not all hsb services have direct access rights to the data store (e.g., query service). once the transformation is completed, the semantic service stores the meaningful data in a jena-based quad store. access to the quad store is realized by means of an api, enabling the application of generic queries expressed in sparql, the query language for semantic data, as well as of more user-specific queries by leveraging predefined functions (e.g., api methods for acquiring a user’s medical history). finally, the semantic data are linked to the respective records of the loinc data warehouse, enabling, this way, to access and process the data in their initial form, when necessary (e.g., in case a third-party entity, such as a hospital, wants to get access to the health data of a patient). the target schema, according to which the semantic data are produced, is entitled “health and lifelogging data hld” ontology and is depicted in figure 2. the hld ontology defines concepts relevant to health and lifelogging data aggregated for a person by a specific device. in this respect, each individual piece of information arriving at the loinc data handler is represented by an individual of the observation class and is linked to the appropriate individual of the person class, denoting the data owner. each observation instance is linked to an observationtype, defining this way the semantic type of the observation (e.g., blood pressure, heart rate, etc.). an individual of the observationtype class is associated with up to three values, reflecting the defined lower, normal and higher value. the observation class is also linked to the collected value through the hasobservationvalue property, as well as the unit accompanying the value through the hasobservationunit property, a timestamp through the hastimestamp property and the alert class, which is instantiated in case of the need of an alert through the hwde topic. an observation is linked to the deviceagent that generates it and may happen while the data owner is occupied with an activity, such as running or sleeping. finally, the information captured for a given person includes any recorded symptoms through the symptom class and the hassymptom property, medical conditions (e.g., hearing impairment) that he may suffer from, the data owner’s age, sex and body measurements, as well as any goals they may have set, such as loss of weight, body fat or the total number of calories burned during a day. as far as the body measurement of a person is concerned, a value and a unit are recorded through the bodymeasurementvalue and bodymeasurementunit, respectively, and the semantic type of the body measurement, such as waist or hip measurement, through the bodymeasurementtype class. next in the conceptual flow of data within the hsb is the data analysis service, a service responsible for extracting additional information based on the transformed semantic data. the data analysis service takes advantage of a rules repository, filled with health and well-being-related rules. these rules have been extracted from recommendations of the american heart association [5] and other similar health-related organizations. by applying the semantic rules to the quad store data, the data analysis service can infer whether the blood pressure of a user figure 2. the health and lifelogging data (hld) ontology is low or high, if the amount of food and vegetables consumed within the day conforms to the ideal daily quantity based on the experts’ recommendations, if the amount of time spent on an activity qualifies them as “active”, etc. for instance, some experts’ recommendations that led to the formulation of the hsb semantic rules are the following:  the normal blood pressure values for an adult over 20 years old are 120/80 mm hg (less than 120 systolic and less than 80 diastolic). [6]  a user should take up at least 30 minutes of moderate-intensity aerobic activity at least 5 days per week for a total of at least 150 minutes of activity. [7]  a user should be involved in an activity for more than 10 minutes in order for this activity to be considered as exercise to boost their well-being. [8] overall, the data analysis service enriches the quad store with information about the condition, actions and habits of the data owner and publishes this information to the hsb in the form of events via the events manager service. events generated within the platform are sent to the queue of the events manager service, which ultimately publishes them to the appropriate topic after verifying their validity. in particular, the events manager service has to first parse the event and check whether the contained data do exist in the quad store, for example, in order to avoid references to wrong or obsolete object uris. then, the service has to make sure that such an event can originate from the sender of the event message based on internal security rules and logic. if all checks are successful, the event is forwarded to the appropriate topic, apart from this, the event is stored in the quad store for future reference. 5. client functionality of the platform the functionality of the platform is exposed to third-party applications by means of several apis. in this respect, three hsb services have been defined, namely the loinc data warehouse endpoint, the client service and the query service. the loinc data warehouse endpoint provides wellbeing data in their original form. its practical usefulness lies in the fact that third party apis of different organizations (hospitals or medical institutions) many times need data in raw format in order to process them according to their own needs. in a similar way, professionals that are authorized to access specific user data may need to access the medical history with respect to a particular metric so that they can perform a more thorough diagnosis. the data are retrieved directly from the nosql database, which is ideal for allowing the retrieval of big chunks of data. the client service provides client applications of the platform with updates. notifications and updates regarding user activity are retrieved by the client service. events from the hwde topic of the health service bus are constantly being pushed to any client application that uses the client service. client applications can range from specialized uis for professionals that are authorized to track the progress of a specific platform user to dashboards that can be used from users to control their data, devices and profiles. in any case, the client service is meant to provide data that correspond to progress updates, notifications (alerts) or combined knowledge that is extracted from the analysis of semantic data. overall, it acts as the “connection point” between the hsb and any other service or application that is not jbossesb-based. the hsb platform offers the capability of feeding external, custom-made applications with the loinc data in their semantically enriched and reasoned-over format. mobile application developers are able to send requests to the query service in the form of a sparql query, which is then forwarded to the queue of the semantic service. this way, developers are able to avoid the task of wearables data integration and homogenization and take advantage of the semantic data in the scope of building the functionality of their application. 6. conclusion and future work the enterprise service bus architectural paradigm provides an efficient way of integrating heterogeneous services and tools. in this paper, we examined the idea of adjusting a productionoriented esb to the needs of healthcare. in hsb, homogenization is achieved by means of ontologies and access to integrated health data is given via services having welldefined functionality. the health service bus can be exploited by a plethora of medical professionals as well as mobile application developers, facilitating this way tasks involved in the trending field of remote healthcare. 7. references [1] c. a. marín, l. mönch, l. liu, n. mehandjiev, g. v. lioudakis, d. kazanskaia, v. chepegin, “application of intelligent service bus in a ramp-up production context” in proceedings of the industrial track of the conference on advanced information systems engineering 2013 (caise'13), caise-it 2013: international conference on advanced information systems engineering (caise) industrial track; valencia, spain. ceur workshop proceedings; 2013. p. 33-40. [2] arum, adaptive production management. [online]. available from: http://arum-project.eu/. last accessed: 30/04/2015. [3] ibm, integrating healthcare services, part 1: using an enterprise service bus for healthcare. [online]. available from: http://www.ibm.com/developerworks/library/j-hsb1/. last accessed: 16/05/2015. [4] a. ryan and p. eklund, “the health service bus: an architecture and case study in achieving interoperability in healthcare”. studies in health technology and informatics 160: pp. 922-926. [5] american heart association. [online]. available from: http://www.heart.org/heartorg/. last accessed 26/05/2015. [6] american heart association, “understanding blood pressure readings”. [online]. available from: www.heart.org/heartorg/conditions/highbloodpressu re/abouthighbloodpressure/understanding-bloodpressure-readings_ucm_301764_article.jsp. last accessed 26/05/2015. [7] american heart association, “american heart association recommendations for physical activity in adults”. [online]. available from: http://www.heart.org/heartorg/gettinghealthy/physica lactivity/fitnessbasics/american-heart-associationrecommendations-for-physical-activity-inadults_ucm_307976_article.jsp. last accessed 26/05/2015. [8] mobihealthnews, “fitbit changes the way it tracks active minutes”. [online]. available from: http://mobihealthnews.com/42241/fitbit-extends-minimumtime-frame-for-active-minutes/. last accessed 26/05/2015. protecting and securing sensitive data in a big data using encryption 1 protecting and securing sensitive data in a big data using encryption praveen s. banasode1,*, sunita padmannavar2 1jain college of engineering, belagavi affiliated to visvesvaraya technological university, belagavi, india 2gogte institute of technology, belagavi, affiliated to visvesvaraya technological university, belagavi, india abstract the transaction data which contains a sensitive data, a program like a android app or a browser, does not adequately protect information such as unique values or related payment information, more or likely a privacy concern. in most of the cases, security breaches, which involve the unstructured data like documents and files, will reveal all sensitive information. to address this issue the transaction data can be processed across the nodes based on advanced encryption standard(aes) algorithm for generating keys and also by using mapreduce algorithm to check number of sensitive data, where we will partition the data based on set key value pairs, whereby protecting the raw data using real-time security monitoring. the data, which requires an extra protection, needs to be identified, based on that data can be encrypted. keywords advanced encryption standard (aes), real-time security monitoring, sensitive data. received on 05 march 2020, accepted on 08 april 2020, published on 17 april 2020 copyright © 2020 praveen s. banasode et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.13-7-2018.163991 *corresponding author. email: praveenb.jce@gmail.com 1. introduction big data mining is the capability of extracting useful information from these large datasets or streams of data, to maintain the confidential and privacy concern of individual person and there data is not compromised. transaction data are often analyses to support, for example, personalized web search, however such data contains a sensitive information about individuals, releasing them in their original from may lead to privacy breaches[8]. transaction services providers receive exabyte of data from their customers, as these data has commercial and legal information the company needs to maintain for a specified period of time. storing and managing the data is very challenging as it is growing minute by minute. the firm starts outsourcing the data for their profit this comprises the customers privacy. in this study map reduce may be used to achieve, protecting communications data in transit should be adequately protected to ensure its confidentiality and integrity. and what are the problems faced by the clients and which improvements are required for the big data service provider. the above facts thus leads to the importance of this study in identifying the sensitive data thereby creating control policy, confidentiality and protecting the data[8]. 2. related work the distance based encryption technique is applied for in biometrics where the threshold value can be decrypted with private key of another key[2]. many algorithms use encryption and decryption using a random key generator in iot communications ascii and xor operations are used[4]. data hiding of image, to hide extra information of different embedded layers the original image is encrypted with less loss of data[5]. data is encrypted and decrypted within the database by using 256 bits of aes encryption, the data is stored in database confidentiality data is retrieved efficiently[11]. aes algorithm generates a new key for each input of image where it constantly changes key while encrypting the data[12]. reverse engineering is applied for encrypted data analyzes plain text protocols uses pin to record executed eai endorsed transactions on smart cities review article eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e5 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:praveenb.jce@gmail.com praveen banasode, sunita padmannavar 2 instructions[13]. improvement of encryption data can also be implemented by using hybrid encryption algorithm[15]. an attribute based encryption(abe) only the matching attributes can decrypt it where data is encrypted with aes and the aes key is encrypted with abe[17].two layer encryption is used for issues related to securing encryption algorithm for securing data[18]. the paper is organized as follows: section 2 briefly outlines the backgrounddiscuses the main objective. section 3 provides a literature survey pertaining to security in hadoop. section 4 provides section 5 experimental results are presented. section 6 concludes the paper. 3. background when a user enters any information on a web application, it is based on the trust that the server will protect that sensitive data, but the data breaches occurring time and again results in doubts the truth of the value, exposure of the sensitive user data has increased[16]. these are leading into a serious violations of data privacy and information security. exposure of sensitive data can be caused by any form. an unauthorized person or third party poses more threat they have access to the information and have the power to sell it to the external users[7]. we have proposed a system based on a distributed parallel algorithm using mapreduce to identify pattern of sensitive data and non-sensitive data and its similarities. the mapreduce based search, sort, intersection of algorithm are used to identify the sensitiveness of data. to process, analyze and visualize the data points, building security in these applications from the beginning is beneficial in the long run[6]. 4. objective the present research work was under taken with prime objective of identifying the various problems of transactional data. • personal information like ssn/sin, dob, adharcardnumber. • banking information like account number, debit/credit card number, atm pin number, registered mobile number. • the main objective of this work is to protect sensitive data from threats using sophisticated secure algorithm in a distributed manner using hadoop technology. which takes care of the following parameters. • efficiently storing and retrieving the bulk data. • detect and protect sensitive information. • reliable security mechanism • robust and fault tolerant system an application encrypts debit/credit card number but also decrypts this data when retrieved. by designing a good algorithm we can protect the sensitive data so that the potential leaks can be controlled. 4.1 security goal to prevent attacks, some measure are required for security implementation like: • by encrypting the data: it is very important to encrypt the data, where the data is in the form of plain text. by identifying the data which requires an extra protection and limiting the accessibility. • authentication: encrypted data remains private by means of not disclosing the confidentiality of the user. 5. method a collection of data which is arranged in the form of sets, consisting of duplicate and unique values. there is more or likely a chances of duplicate data in sensitive data. by using the set intersection we can eliminate the duplicate value from sensitive data set. consider a set which is consisting of user information like name, ssn, debit_credit_number, email and in another set of sensitive a data of ssn, debit_credit_number sequence of data, like that many information is carrying, let us consider, two sets s1 and s2. s1={{abc,123,1234567890,abc@m.com},{bcd.234,2345 612312,bc@g.com},{azx,345,09 87654321,zx@g.com}, {wer,347,2314560987,x@g.com},…..} s2={{bcd.234,2345612312,bc@g.com},{wer,347,23145 60987,x@g.com},{abd,389,4534 567890,abc@m.com}, .................................... } each object is called an element of set. for two sets s1 and s2 is the number of elements present either of the set (s1us2). total number of elements present in both the sets s1 and s2 (s1∩s2)[1]. the sets which contain all the elements of a given collection is called the universal set which is represented by 'µ' [1]. µ(s1us2)=µ(s1)+(µ(s2)-µ(s1∩s2)) definition: let s1 and s2 be arbitrary given sets. by function f:s1->s2 from the set s1 into s2, a rule which assigns to each member x of x, a unique member f(x) of s2. the member f(x) is called data of x under the function(mapping)f or the value f at x. the set s1 is called the domain of f and the set s2 is called the co domain of f. the set of element f(x), x ε s1 is called range of f. thus, the range of f is a subset of s2. let f:s1->s2 be a mapping from the set s1 into the set s2. eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e5 mailto:abc%2c123%2c1234567890%2cabc@m.com mailto:abc%2c123%2c1234567890%2cabc@m.com mailto:bcd.234%2c2345612312%2cbc@g.com mailto:bcd.234%2c2345612312%2cbc@g.com mailto:bcd.234%2c2345612312%2cbc@g.com mailto:87654321%2czx@g.com mailto:wer%2c347%2c2314560987%2cx@g.com mailto:wer%2c347%2c2314560987%2cx@g.com mailto:bcd.234%2c2345612312%2cbc@g.com mailto:bcd.234%2c2345612312%2cbc@g.com mailto:wer%2c347%2c2314560987%2cx@g.com mailto:wer%2c347%2c2314560987%2cx@g.com mailto:wer%2c347%2c2314560987%2cx@g.com mailto:567890%2cabc@m.com protecting and securing sensitive data in a big data using encryption 3 if f(x1)=f(x2)=>x=x2 for every x1,x2εs1, if and only if the data of distinct points s1 are distinct, that is x1≠x2=>f(x1)≠f(x2). thus, from this definition we arrive to conclusion the data is protected and thereby removing the duplicates. same methodology of set theory will apply in processing chunks of data into the hdfs cluster the above sets are examples of unique identifier as well how these identifiers are carrying the sensitive data for processing the data from one end to another end and in between many transformation will take place and also how the real time data is protected and secured using encryption and decryption process. programs can directly access key value pair matching index and even made available on the network. the mapreduce algorithm is implemented to restrict information getting leaked to unknown sources using two interfaces as mapper and reducer by manipulation so the result will not violate the privacy of the clients. sample code is presented for preserving sensitive information of client. algorithm: class sensitivity: def mapper(key,_,value):(name,ssn,debitnumber,email)=line. split(‘,’) yield debitnumber, int(ssn) def reducer(key, debitnumber,ssn): totalnumber=0 numberdebit=0 for x in ssn: totalnumber+=x numberdebit+=1 yield debitnumber the data which is used to store more memory requires to be sliced to store in proper format and also it helps the functions to share widely on distributed platforms for any transactional purpose. the sensitive data is used wisely by checking all possible threats from the outside world with proper algorithm to process the data in a way it required for successful transactions. each tuple of value is having a multiple value for debitnumber and creditnumber, so this increases the task of protecting the data of a user in its best interest and also to be processed efficiently. by decomposing the data into two relation we can further reduce the cluster of work which stored on disk. some users do not have credit card number for them null values is assigned, they may not have or may not be available for the time being in that case a null is stored for such attributes. multivalued are decomposed into atomic value by properly arranging primary key and other keys. decomposing the data helps in experimenting the data in safer and we can have multiple set of data which is going to be more efficient. a mechanism is employed to secure the data which combines encryption and decryption when such things are implemented in the algorithm then framework need not do changes. table 1. a) nested relation of attributes within each tuple. b) normalised attributes of relation into two different relation. a) ssn name debitnumber creditnumber 123 abc 1234567890 7894561231 4563217890 234 bcd 2345612312 7456321456 1236547890 6611223355 5003412345 5500223344 456 qew 3344552200 8880001234 null 639 asd 7452316970 5544332211 5007800901 9600120013 4563214600 7452130011 9004455333 b) the collected information will be converted into a secrete key code which will not be understood until it is decrypted by hiding true information of its meaning. an advanced encryption standard (aes) is the symmetric key which uses of government standards of classified information. the key shared among system and the computing environment which uses the key to decrypt. import aes import base64 import os def data_encryption(privateinfo): block_size = 32 padding = '{' pad = lambda s: s + (block_size len(s) % block_size) * padding encodedata=lambda c, s: base64.b64encode(c.encrypt(pad(s))) ssn name ssn debitnumber creditnumber eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e5 praveen banasode, sunita padmannavar 4 secretkey = os.urandom(block_size) print 'encryption key:',secret cipher = aes.new(secretkey) encoded = encodedata(cipher, privateinfo) print 'encrypted string:', encoded the unauthorized person is not be able to access any data which is in an encrypted form, the sensitive data is made sure secured by encryption algorithm, all the digital data is stored and transmitted over the computer network. key figure 1. encryption operation architecture of computation14 figure 2. architecture computations i. focus is on real time data is, for new level of complexity to derive value from data. the margin of detecting and dealing set of data is vanishing and also risks around big data over time it will shift by focusing on the tooling system for storing and addressing in a more secured way by implementing the mapreduce algorithms. in short risks will perish using the above methodology. ii. failure of data is very less, here by applying the encryption policies for the data which is passed through some channels protects the sensitive data collected from the source. iii. duplication of data is reduced because the same data is collected in clusters on unique values which are been encrypted and during moving it may be that the same source data is required to process on multiple data stores and consuming applications, and these operations will give rise to expected results. iv. by using the selective descriptive analysis the real time data which is protected and secured in cluster will be decrypted based on use node policy and thereby the end user can access the data for further processing. v. similarly, the real time data which is available in abundance is a big challenge to control and secure the data and eliminating the duplicates by performing a proper set of analysis. figure 3. mapreduce distributed computing mapreduce and hadoop can partition this job and breaking up of this data into mappers most of them running parallel on different computers so imagine you have entire clusters of mappers and each responsible parsing chunks of data for input data and outputing the key value pair <k,v> for short cutting the data and then similarly that can be sorted and grouped together and reducer also run on one machine. now putting the result into result front machine and combining all together at the end. this illustrates how can the divide and conquer works on large dataset using mapreduce and hadoop to process datasets on an distributed computers. to process data which even unfit in personal computer machines on distributed task over cluster of wide computer system to achievable task by taking up large datasets. that is how the mapreduce plain text encryption algo. kjhls45a zxcv oiuyhg5 eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e5 5 works for scaling up to the bigdata on distributed environment. figure 4. time efficiency on large data set the experiment demonstrates that difference in timing is negligible, if more data are tested the time efficiency decreases exponentially with increase in testing data of reduced value to its sensitivities. 6. conclusion the bad data can be detected and dealt, and also margin of errors can be reduced thereby shaping up of data. the data quality can be addressed to the point of data acquisition by ensuring the data in terms of consistency and accuracy. the data is made sure end-to-end encrypted and secured. the algorithm will collect data-quality measures like dealing up of data drift and sensitive data for transaction processing on a distributed cluster of computers the key value pair is made sure the data is encrypted and data will be decrypted only to the destination. the mechanism helps the framework to be more robust and need not require much do changes and also secures the safety of data by giving more transparency and meaning to the data. name and value attribute have addressed the security concerns of data. the work is limited to a certain disjoint attribute and can be enhanced to large scale deployment by use of hybrid and public cloud services. references [1] babu ram “engineering mathematics” set theory and functions, pearson publications. [2] fuchun,willy,yi "distance-based encryption: how to embed fuzziness in biometric-based encryption" ieee transactions on information forensics and security ( volume: 11 , issue: 2 , feb. 2016 ). [3] jindan zhang, xu an wang, jianfeng ma "data owner based attribute based encryption" 2015 international conference on intelligent networking and collaborative systems. [4] iqra hussain, mukesh, nitin "proposing an encryption/ decryption scheme for iot communications using binary-bit sequence and multistage encryption" 2018 7th international conference on reliability, infocom technologies and optimization (trends and future directions) (icrito). [5] m. hemalatha, k. rajasekhar "multiplicative symmetric key generation based encryption for data hiding" 2017 2nd international conference on communication and electronics systems (icces)". [6] meiko jensen "challenges of privacy protection in big data analytics" 2013 ieee international congress on big data. [7] prof. elisa bertino "big data security and privacy " 2016 ieee international conference on big data (big data). [8] quang tran and hiroyuki sato "a solution for privacy protection in mapreduce" 2012 ieee 36th international conference on computer software and applications. [9] r.manjusha and r.ramachandran "comparative study of attribute based encryption techniques in cloud computing "international conference on embedded systems (ices 2014). [10] roger schell " security – a big question for big data" 2013 ieee international conference on big data. [11] than myo zaw,min thant "database security with aes encryption, elliptic curve encryption and signature" 2019 wave electronics and its application in information and telecommunication systems (weconf). [12] vasyl, ivan, roman, victoria "information encryption based on the synthesis of a neural network and aes algorithm" 2019 3rd international conference on advanced information and communications technologies (aict). [13] wei lin, jinlong fei, yuefei zhu, xiaolong shi"a method of multiple encryption and sectional encryption protocol reverse engineering" 2014 tenth international conference on computational intelligence and security. [14] web resources “fig. 5.2 architecture computation”, encryption achieved through filters. [15] xinqiang, lili yu,lihuan "the application of hybrid encryption algorithm in software security"2013 3rd international conference on consumer electronics, communications and networks". [16] xinhua dong, ruixuan li, heng he, wanwan zhou, zhengyuan xue, and hao wu " secure sensitive data sharing on a big data platform" tsinghua science and technology is snll1 007 0214ll0 8/ 1 1llp p 7280 volume 20, number 1, february 2015. [17] yanli ren, shuozhong wang, xinpeng zhang, zhenxing qian "fully secure ciphertext-policy attribute-based encryption with constant size ciphertext " 2011 third international conference on multimedia information networking and security. [18] yoshiko,hiroki,hayato "attribute-based proxy reencryption method for revocation in cloud storage: reduction of communication cost at re-encryption" 2018 ieee 3rd international conference on big data analysis (icbda) [19] zainab, mahmood "new fully homomorphic encryption scheme based on multistage partial homomorphic encryption applied in cloud computing"2018 1st annual 1 2 3 4 5 6 7 8 time 50 40 30 20 10 0 time protecting and securing sensitive data in a big data using encryption eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e5 praveen banasode, sunita padmannavar 6 international conference on information and sciences (aicis). eai endorsed transactions on smart cities 06 2020 07 2020 | volume 4 | issue 11 | e5 on a mobile phone contact list based on social relations pasteur poda1,∗, rashid ben amed charles zongo1, ibraïma dagnogo1, théodore tapsoba1 1ecole supérieure d’informatique, université nazi boni, 01 bp 1091 bobo-dioulasso 01, burkina faso abstract social relations are unquestionably the major provider of contacts in the mobile devices contact lists. however, they remain marginal in the literature of social software related to the contact list and are not at all integrated in its design. inspired by african social and cultural practices, this paper is about a design of the contact list that integrates the social relationships existing between people in the real life. a desktop prototype of the proposed contact list designing allows to validate it. illustrations of the developed application demonstrate the assets of the proposed contact list regarding issues such as contacts reminding/retrieval and homonymy resolving with respect to the real life. additional capabilities of the proposed contact list reside in the creation of groups of contacts for group communications needs. received on 04 december 2017; accepted on 09 january 2018; published on 12 february 2018 keywords: contact list, context-awareness-based applications, group communication, mobile recommendation, social relations copyright © 2018 p. poda et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.12-2-2018.154107 1. introduction one of the basic features available on mobile stations and user equipments is the contact list. the contact list is a database of contacts; a contact being most often a natural person and sometimes a legal entity. basically, the contact list is used to save the contact information (phone numbers, names and surnames, addresses, . . . ) of the mobile subscriber’s contacts. primarily, it is for allowing the users (i.e. the subscribers) to call their contacts without having to remember and dial the contacts phone numbers. nowadays, user equipments comprised of smartphones offer contact lists with advanced features including a diversity of input fields that serve to identify and remember a contact entry. ∗corresponding author. email: pasteur.poda@univ-bobo.bf some of the common input fields are for providing detailed information such as multiple phone numbers, names and surnames, electronic and physical addresses, organization membership, notes for inserting discreet and discretionary data about the contact, etc. however, none of these input fields is intended for clearly describe the relationship that could exist between a given contact and another one of the same contact list. simultaneously, it seems evident that relationships existing between people in the social life explain well how the contact lists are populated. social relations are defined in social sciences as any relationship between two or more individuals. a social relation is therefore a universal concept that depicts the social life from all over the world but it may be assumed that it is not experienced in the same way with africans 1 eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e6 p. poda et al. as with western people. indeed, in his investigations to formally explain how people construct social relations, fiske established [1, 2] that people in all cultures use the same relational models to generate most kinds of social interactions but he also noted that the moose1 implement the models differently, in different domains, and in different relative degrees, than americans. in the particular case of african societies, some social practices and behaviors make people contact lists to be rapidly and significantly populated. for example, a usually observed practice in african societies is that when a problem has to be solved, people use to resort to an acquaintance who, will in turn resort to his own acquaintance and so on until the right one who can actually help solving the problem. in that endeavor to solve the problem, several kinds of social relations (mainly family and friendly) are activated and can spontaneously give rise to the creation of new entries in the contact lists. consequently, a contact list can be easily “crowded” with hundreds [3] even thousands [4] of contacts entries causing the user not to be always able to efficiently match a contact entry to the individual of the real life that it represents. this is further true insofar the “crowding” of contact lists increases the number of the rarely contacted contacts and gives rise to more homonyms occurrences. in such a situation of the contact list “crowding”, the currently implemented contact information cannot be efficiently helpful whenever contact entries need to be matched to the individuals of the real life that they represent. it is also important to note that another habit in african social life is that the way people do to recognize someone is mostly based on social relations. an individual is sometimes identified by referencing one of his social affiliation. for instance, adults use to identify teenagers of their social environment by referencing the family affiliation (e.g.: a father, a mother, . . . ) of those latters rather than using their names or surnames. in the same vein, it is common for african people to identify married women by referencing their husbands or their father/mother in a certain way. 1the moose (or mossis) are the ethnic majority of burkina faso in west africa throughout these few examples illustrating some facets of african social life, it is clear that social relations play a major role in the process consisting of matching contacts entries to individuals of the real life, recognizing, remembering or identifying contacts of the contact list. this leads us to proposing a redesigning of the contact list by taking into account social relations. the proposed new vision of the contact list was introduced in [5]. it particularly aims at targeting african mobile users as it is inspired by their social and cultural practices. beyong the fact that it could help facing the problems (contact matching, recognizing/identifying, remembering) mentioned above, the proposed new vision of the contact list could also stand for facilitating communications within groups of communities. indeed, there are some events such as funerals, marriages, large family meetings which require a member of a group to share an information of social interest. in this case, if a group can be easily constituted based on the social relations, this could avoid a member of a group to, e.g., send as many short messages services as required to share an information. by this paper, the purpose is to provide a detailed description of the proposed redesigning of the contact list up to validate it with results of a desktop implementation. in the remainder, we deal in section 2 with a state of the art of works and inventions addressing the contact list. we present in section 3 the new approach of the contact list designing. in section 4, we deal with the technologies to be used for the proposed contact list implementation. in section 5, we show results of the developed contact list software. we conclude the paper with section 6. 2. related works the proposed new vision of the contact list design is strongly inspired by social relations as they are experienced in african social life and more specifically in the sub-saharan part of africa. ouoba et al. [6] proposed an approach that they called the toolé approach, an approach based on the cultural values of the peasants of sub-saharan africa, to design an opportunistic networking strategy that facilitates and automates agricultural information broadcasting. 2 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e6 on a mobile phone contact list based on social relations during the decade of the 2000s, the design of social software involving the mobile phone contact list has been an active field of research and innovation. several related research works and inventions covered systems built based on the concept of awareness and besides many other issues. lot of those systems are met under the vocabulary of recommendation systems and consist of making the mobile phone able to provide intelligent interactions with the users. various kinds of awareness cues such as the mobile location and status have been used to prescribe recommendations to the users. in [7], a phonebook that contains in addition to phone numbers the context information about the user was implemented. the context information consists of awareness cues such as details on the user’s connection status, his availability preferences or his location (e.g., at work, at home). the context information allows the potential caller to take the situation on the other end into account before setting up a call. these awareness cues about the user situation and environment were found to be very important when using a mobile phone. the smartphone contact list was extended [8, 9] to provide additional contextual information cues such as the time spent in the current location, the phone alarm settings and other cues that are useful to give information about the availability of the user. the design of the awareness cues of [8] was based on social psychological findings whereas that of [9] was inspired by eight hypotheses among which are efficiency of accessing contacts, differentiation of important contacts and contacts as social piggy bank. on the latter hypothesis, the authors were pointing out the need to take into account information that is related to the social relationships between contacts who are natural persons in the design of awareness cues. is also observed [10] the trend for active mobile phone users to add further information that can help reinforcing the context of the relationship between the user and one of his contact. in a study extending awareness to mobile users [11], a desktop prototype called connexus allowed to evaluate the role of awareness in a collaborative environment. a system named isocialize [12] was developed to implement and evaluate several kinds of awareness cues including activity, status, relation and vicinity. unlike, most of the systems based on awareness, fiendlee [13] merged most of the useful awareness indicators and was oriented toward amobile social networking application. the cues under consideration with friendlee include current location and time spent there, local time and weather, status messages and status indicators (e.g.: available, busy, phone on hold, engaged, . . . ). in [14], a social and personal context modeling method was proposed to support social networking applications of mobile devices. using bayesian networks, the user’s contexts are infered from uncertain logs stored in the mobile device. some of the user logs collected from the mobile device are geographical coordinates, day of the week, anniversary and type of scheduling such as friendship or business. a contact list recommendation system that recommends phone numbers according to the user’s current situation was implemented. with regards to social networking application, we can also mention that solution [15] which was proposed to take advantage of social relationships and context information to provide recommendations to users of social networks. in the proposed new vision of the contact list, social relations are intended to be useful as potential awareness cues for mobile recommendations. for instance, social relations can be combined with location for providing recommendation services to the users. they stand for being well adapted for systems that suggest friends (contacts) in social networking software. as about the context information sharing that the mobile awareness applications enable, a serious concern is that of privacy. authors of [16] found that people decisions of sharing their context information are based mainly on the identity of the recipient of the information. the study reported in [17] also concluded that people decide whom to share context information with based on their relationship (e.g.: spouse, friend, peer, . . . ) to the person. therefore, it comes that casual contacts are assumed receiving less context information than contacts with other kinds of relationships [17, 18]. we therefore expect people to be more confident while sharing their context information with the proposed social relations based contact list. indeed, the proposed contact list stands for being an efficient tool for contacts 3 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e6 p. poda et al. identifying with respect to whom they are in the real life. associating mobile awareness to initiation of group communications, a community-aware mechanism [19] was proposed for efficient creation of groups of contacts. mobile phones are thereby provided with a recommendation engine that helps an initiator of a group efficiently create a group from his contact list. hendrey et al. [20] invented a system for location-aware connections of telecommunication units involving group communications. they offer a way for automatically and/or selectively initiating communications among mobile users whenever the mobile users can be geographically located. in the proposed redesigning of the contact list, we deal with group communications to address some needs in african social practices and social relations are hereby used as criteria for groups creation. several other works, involving the contact list but with minor correlation to our proposal, addressed contact information update and exchange. methods for updating automatically mobile phone contact list entries [21] and improved systems for providing phonebook and bookmarked links to web sites for mobile users [22] were developed. a system [23] that proceeds with synchronization and updates enables the mobile phone to initiate, according to the circumstances, the appropriate form of communication with one of the contacts. examples of methods for exchanging contact information include a method [24] of sending contact list data from one mobile phone to another mobile phone within a group and a system that is able to locate the mobile device and gathers contact information for an information server [25]. more recent related works were oriented toward the issue of efficiently retrieve a contact from a “crowded” (hundreds or thousands of entries) contact list. for that, adaptive interfaces exploiting the mobile context led to context-aware algorithms that predict at any time the next callee. in [26, 27], were proposed contextaware algorithms that used frequency and recency of communication as context cues. in [28], physical location was examined as a context cue for predicting the next callee. in the same momentum, several other researches are found, e.g. in [29–31]. although our social relations based design of the contact list is not oriented toward prediction of the next callee, it can help retrieving efficiently a contact in a “crowded” contact list provided a social relation of his is known. 3. new approach of the contact list designing the contact list, also called phonebook, is a database of the mobile phone user’s contacts. it is generally stored in the subscriber identity module (sim) card and/or in an extended memory of the mobile equipment. each entry of the contacts database can be viewed as an object subjected to diverse transactions such as the classical crud (create read update delete) functionalities and the emerging mobile awarenessbased applications which are presented above in section 2. as an object, each contact entry of the contact list can be described by a set of attributes generally called the contact information. these attributes serve to identify the contact and include the contact identity information (names, surnames), his phone number(s), his physical and electronic addresses, etc. the new approach hereby proposed consists of modeling the contact list as a graph g = (c, e) of the contacts. each node cj ∈ c of the graph represents a contact and contains the currently observed contact information. each edge (ci , cj ) ∈ e ⊂ c × c of the graph is for registering the social relationship that exists between two contacts. as shown in the graph representation of figure 1, a contact list is therefore defined as a set of linked entities cj , 1 ≤ j ≤ n, each with its specific instance of the contact information and all sharing common treatments. the social relations, represented by the edges of the graph representation of the contact list, can be any type of social relation. however, can be considered more meaningful, when considering the african social context, the family category of social relations. in table 1, we provide a non-exhaustive list of social relations that can be considered. with this redesigning approach, the current treatments to which the contact lists are subjected will continue working. thus, the traditional crud treatments are preserved together with the emerging treatments regarding mobile awarness-based applications. beyong 4 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e6 on a mobile phone contact list based on social relations figure 1. graph representation of the contact list table 1. examples of social relations category social relation name family is_the_father_of, is_the_mother_of, is_the_son_of, is_the_sister-in-law_of, is_the_daughter_of, is_the_brother_of, is_the_sister_of, is_the_cousin_of, is_the_uncle_of, is_the_wife_of, is_the_husband_of, is_the_brother-in-law_of, . . . friendly is_the_classmate_of, is_the_comrade_of, is_the_buddy_of, is_the_friend_of, . . . professional is_the_colleague_of, is_the_collaborator_of, is_the_chauffeur_of, . . . these existing treatments, the proposed approach adds novel smart functionalities. indeed, the new approach of the contact list makes it an interesting instrument of reminder. let us consider a contact list with a rarely contacted contact cj0 and let us assume that the visualization of the classical contact information of cj0 fails to help remember who cj0 is in the real life. in these conditions, the proposed social relations based contact list can help remember cj0. algorithm 1 in table 2 formally describes this novel functionality of contacts reminder. a second novel functionality, given by algorithm 2 in table 3, is for homonymy resolving. let us assume that we are in presence of l homonyms cj , 1 ≤ j ≤ l, among which we need to select the right contact cj0 with whom we desire to communicate. so, for each homonym, his social relations with other table 2. algorithm for forgotten contacts reminding algorithm 1: given a contact list (c, e), find a social relation (cj0, cj1) that helps remember cj0 input: (c, e) read cj0 display d = {ci | ∃(cj0, ci ) ∈ e} for ci ∈ d if (cj0, ci ) = (cj0, cj1) break endif endfor table 3. algorithm for homonymy resolving algorithm 2: given a contact list (c, e), select the right cj0 among l homonyms input: (c, e) display d = {ci , i = 1 . . . l |ci like cj0} for i = 1 : l display di = {ck , k = 1 . . . l, | ∃(ci , ck) ∈ e} for k = 1 : l if (ci , ck) = (cj0, ck) select ci as cj0 i ← l + 1, break endif endfor endfor contacts are displayed and analyzed. based on the social relations, we are able to select the right homonym cj0. a third novel functionality is given by algorithm 3 in table 4. it consists of making a search for a contact cj0 for whom we assume not remembering the contact information (including names and surnames) and fortunately we remember one of his social relation (e.g.: cj0 is the cousin of cj1). a search operation on cj1 has to be executed first, then after filtering out display only the contacts who are linked to cj1 by the right social relation. the contact cj0 who is searched for is probabily among these latter contacts. in addition to the three novel functionalities that we have just presented, the proposed contact list offers perspectives to use social relations as potential cues to be integrated in the design of mobile awarenessbased applications. for instance, social relations may be combined with some contextual cues such as the geographical location in order to recommend services 5 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e6 p. poda et al. table 4. vague search for a forgotten contact algorithm 3: given a contact list (c, e), retrieve an unremembered contact cj0 knowing cj1 such that (cj0, cj1) ∈ e input: (c, e) read cj1, (cj0, cj1) display d = {ci | (ci , cj1) like (cj0, cj1)} for ci ∈ d if ci = cj0 select ci , break endif endfor (e.g.: visiting a relative) that can contribute to the users’ social relationships strengthening. in the context of african social life, it is current to see social events that involve systematically, by the fact of social relations, tens even hundreds of people. examples of such events are funerals (for which any acquaintance of the deceased or of his family should be informed), customary marriages (for which is invited any person linked by a family social relation with the fiancé), civil marriages (involving people with as well family, professional as friendly relations with the two persons getting ready for the marriage), social visits in case of happy events (e.g.: baptism celebration, congratulation of a newborn parents) or in other cases like visiting a sick person or presenting condolences to a person. in the case of social visits, the groups to be created can be guided by professional relations, friendly relations or any other kind of social relations. to address such events management, the proposed approach of the contact list can facilitate groups creation for the purpose of sharing information using for example short messaging services. in addition to groups creation based on social relations, the proposed approach also offer the possibility to develop recommendation systems that can work based on the social relations to suggest to the mobile user the contacts with whom the information about a given social event must be shared. 4. approach of implementation of the proposed contact list the scope of this study suits well with intelligent systems ingineering. to model social relations, a specialized language of artificial intelligence such as prolog can be used. as a language based on first order predicates logic for expressing knowledges, prolog formalism for writing facts and rules is well adapted to express the social relationship that exists between two contacts and for infering new knowledge. more precisely, prolog can be used to implement the proposed contact list in the form of a knowledge base comprising facts (social relationships between contacts) and rules (general laws applying to the social life domain). the prolog interpreter would play the role of an inference engine for the knowledge base management and exploitation. the user interface would be graphical and developed using java programming language. jpl (java interface to prolog), a java application programming interface would stand for interfacing java and prolog. however, this prologbased approach to implement the proposed contact list could be considered as out of date. indeed, emerging technologies namely those of the world wide web consortium (w3c) standards package for linked data are also suitable. with regards to the use of the linked data technologies to implement the proposed contact list, the approach consists of the system architecture of figure 2. the knowledge base is built upon an ontology populated by individuals. the ontology implements the graph representation of the contact list by defining the graph of the concepts related to social relations. a social relationship existing between two contacts is, in this approach, well mapped onto the model of triplets. the model of triplets represents a knowledge in the form of a triplet as (subject, predicate, object). using this model, a social relation can be represented by a predicate and the two contacts that it ties corresponding one to the subject and the other to the object. this model of triplets is used in the resource description framework (rdf) [32]. to efficiently represent the concepts intervening in the proposed contact list and enable reasoning on the knowledge base to build, web ontology language (owl) [33] or resource description framework schema (rdfs) [32] are part of the w3c standards stack of linked data that can be used. 6 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e6 on a mobile phone contact list based on social relations figure 2. technical architecture of the contact list software to validate the proposed contact list software, we propose to implement it using the desktop oriented architecture depicted in figure 2. in this architecture, three different features have to be distinguished. the presentation feature given by the graphical user interface and for the development of which java programming language is selected. the second feature is the knowlege base implementing the proposed contact list. it consists of an ontology describing the contacts and the social relations that connect them each other. the rules are part of the knowledge base. they are used by the inference engine, the third feature of the architecture, to deduce new knowledge (e.g.: linking automatically contacts on the basis of logical consequence). for the implementation of this part of the arhitecture, protégé, an open-source ontology editor [34] is selected together with the owl syntax. the inference engine is in charge of the reasoning. to implement the inference engine and make it possible to interface both the graphical user interface and the knowledge base, apache jena is selected. apache jena is an open-source java framework for linked data applications building [35]. for the queries management between the knowledge base and the user interface, the sparql protocol and query language [36] is selected. sparql is one of the w3c standards of linked data. 5. results of the developed contact list software we developed the proposed contact list application basing on the technical architecture of figure 2 and figure 3. demo sample of the contact list using the selected technologies previously presented. the developed application is provided with both the classical crud functionalities and the three novel functionalities regarding homonymy resolving, contacts reminding and identifying. it also offers possibilities for groups creation using criteria that are the social relations. for the purpose of the demonstration, we created a contact list in which eight contacts have been registered, hence the instance of the contact list graph depicted in figure 3. to add a new contact in the proposed contact list, the developed application allows the user to fulfill the input fields presented in the screen shot of figure 4. some mandatory contact information that are the user’s name, his surname and his phone number has to be provided. the social relation (i.e. the tie) that ties the new contact being created (i.e. “poda pasteur”) to an already existing contact (i.e. “zongo rashid”) is materialized with the selection of the appropriate social tie (i.e. “cousin of”). the button labeled “ok” allows the new contact information and social tie to be saved in the contact list. upon completing the new contact insertion, the inference engine automatically updates the contact list graph by running the inference rules. this updating can lead to the creation of one or several other social relations with existing contacts. 7 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e6 p. poda et al. figure 4. creation of a new entry in the proposed contact list one of the inherent novel functionalities of the proposed contact list makes it an effective reminder as explained through algorithm 1 (see table 2). to illustre this, figure 5 is given. we assume not remembering the contact “poda pasteur” (a rarely contacted contact for example) with respect to the real life. the proposed contact list application allows all the contacts of the unremembered contact to be displayed. in the example of figure 5, among the three contacts of the contact “poda pasteur” who are listed, the selection of the contact “zongo rashid” reveals that he is a cousin of the contact “poda pasteur”. knowing this social relation that ties the two contacts, the user is able to remember the contact “poda pasteur”. another inherent novel functionality of the proposed contact list is that described in algorithm 3 (see table 4). figure 6 shows a screen shot of how to vaguely figure 5. exhaustive listing of contacts of any social tie with a given contact search for a contact (e.g.: “dagnogo ibraïma”) whose contact information including his name and surname are forgotten. we assume that fortunately one of his contact (e.g.: “poda pasteur”) is known. knowing that latter contact and his social tie with the unknown contact, we can try by selecting both the type of social tie (e.g.: “is the brother-in-law of”) and the known contact (“poda pasteur”). then, vaguely searching in the list (in the example of figure 6 there is only one element in the list) of the contacts who have “poda pasteur” as their “brother-in-law”, there exist chances that the contact “dagnogo ibraïma” is retrieved. the third inherent novel functionality of the proposed contact list is homonymy resolving. we have introduced it through algorithm 2 (see table 3). we assume having a certain number of homonyms in the contact list and we need to select the right one for initiating a communication with him. homonyms possess identical contact information regarding their names and surnames but some other contact information (such as email address, phone number) can allow to distinguish them by the simple visualization. however, they 8 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e6 on a mobile phone contact list based on social relations figure 6. vague search of a contact cannot allow to recognize the right contact with respect to the real life. this is the case with the two homonyms occurrences of figure 7 and figure 8 regarding the contacts with name “dagnogo” and surname “ibraïma”. in fact, the email addresses can help distinguish them but remain unpowerful in helping recognize the contact “dagnogo ibraïma” that we desire communicate with. thanks to the proposed contact list, the social relationships between each homonym occurrence and other contacts can help recognize the one with whomwewant to communicate. in figure 7, we are about the contact “dagnogo ibraïma” who has “poda pasteur” as brotherin-law whereas in figure 8 the second homonym occurrence is about a different “dagnogo ibraïma” who has “dagnogo bamori” as father. the homonymy is thus resolved. to finish, let us now deal with group communications facilities that the proposed contact list enables. in section 3, we exhibited the motivations for using the social relations as criteria to constitute groups for group communications. in the developed contact list application, we are able to select one or more criteria that are social relations in order to create a group. figure 9 shows several possible choices of social relations as criteria for groups creation. it also let us imagine that the contact “dagnogo ibraïma” would like to create a group comprising of his sisters figure 7. a first homonym occurrence figure 8. a second homonym occurrence and brothers. after clicking on the button labeled “validate”, it results the creation of the group which members are displayed as shown in figure 10. once a group is created, a group communication channel can be identified. it can consist of, e.g., sending 9 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e6 p. poda et al. figure 9. social relations as criteria for groups creation a short message service to all the members of the group or establishing an interactive messaging service conference or a conference call within the created group. 6. conclusions strongly inspired by african social life, we proposed a redesigning of the mobile devices contact list based on social relations. we modeled the contact list as a graph of the mobile device user’s contacts where social relations are the edges. we built the proposed contact list application architecture on a system comprising a knowledge base, an inference engine and a graphical user interface. we implemented this system using technologies of the world wide web consortium standards of linked data and java application programming interfaces. results of the developed system allowed us to figure 10. group communication: created group members evaluate the proposed contact list as an effective instrument that brought to the user additional novel functionalities of social interest. beyond the classical crud (create read update delete) functionalities which are preserved, the proposed contact list furthermore allows contacts reminding, homonymy resolving, social relations based contact retrieval and group communications facilitating. the achieved redesigning of the contact list and its validation giving the results of the implementation open promising perspectives for the integration of social relations in the design of mobile social software including mobile awareness-based applications. this is further important as social relations can play a crucial role in the human well-being. indeed, the proposed approach can contribute much in relationships strengthening in the social life and bring happiness to people. in [37], the author noted that the evidence is substantial in psychology and sociology literature that social relations promote happiness for the individual and investigated in putting a financial value upon social relations and other life events. holder et al. also discussed whether aspects of social relations and children’s happiness are related [38]. 10 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e6 on a mobile phone contact list based on social relations references [1] fiske a.p. 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(2009) the contribution of social relationships to children’s happiness, journal of happiness studies, 10(3), pp. 329-349. 12 eai endorsed transactions preprint a proposed methodology for integrated architectural design of smart hospitals 1 eai endorsed transactions on smart cities research article a proposed methodology for integrated architectural design of smart hospitals mohamed helmy elhefnawy1,* 1assistant professor of architectural engineering, faculty of fine arts, assiut university, egypt abstract introduction: urgent need has recently emerged to transform hospitals from buildings that not only achieve functional requirements, but also comply with modern technologies. this is so that they are able to self-adapt to external conditions and change their behavior according to users. this is compatible with emerging trends to convert cities and buildings in developing countries to smart. objectives: to develop a comprehensive methodology for proper dealing with smart materials & systems when constructing and finishing hospitals, leading to defining principles of an integrated architectural design for smart hospitals. methods: the descriptive analytical approach included theoretical background on concept of smart hospitals, types of smart materials & systems and their role in hospital design. results: an integrated methodology for proper architectural dealing with hospitals to allow them to be smart, which the study recommends to follow and complement between smart materials and systems. conclusion: the research conceived a proposed methodology for the architectural design of smart hospitals and identified mechanisms for utilizing smart materials and systems in developing hospital designs keywords: smart hospitals, smart materials & systems. received on 27 march 2020, accepted on 24 may 2020, published on 28 may 2020 copyright © 2020 mohamed helmy elhefnawy, licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.5-2-2020.164826 *corresponding author. email:mhelmy1974@yahoo.com.au 1. introduction smart hospitals are essential components of smart cities which have received great attention in most countries of the world. the interest in establishing smart hospitals is due to the intense varying requirements of patients, workers, and visitors. this requires achieving response and self-interaction with the internal environment, in addition to achieving adaptation and compatibility with external conditions, without direct intervention[1]. moreover, it is an essential step for automating the health care field in light of the intensity of the various internal systems[2], which provides practical solutions for medical management and treatment by relying on information technology and building network infrastructure, such as mobile or remote health care and others[3]. also, this provides sustainable self-management of resources such as energy and water[4], [5], reducing pollution by emissions and waste[6]. thus, the hospital environmental performance is improved, and the operating environment is upgraded. this is carried in a manner that achieves safety, security, and user-comfort, as well as being in accordance with modern designs of hospital buildings, which focuses on transferring them from being only functional buildings to buildings that are designed, executed and equipped in a way that depends on artificial intelligence. this is as a part of computer sciences that are interested in producing smart technologies which give characteristics to buildings similar to these of human intelligence[7]. this approach is compatible with rapid technological advances and modern technologies which support interactive and integrated building construction and finishing materials (concrete, glass, etc.) in addition to supporting various systems (air conditioning, ventilation, safety and security systems, etc.). the concept of architectural design of smart hospitals and their importance will be defined below in addition to identification of smart technologies associated with their design which leads to setting up a methodology to allow for relying on these technologies in designing smart hospitals. eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e4 http://creativecommons.org/licenses/by/3.0/ mailto:author@emailaddress.com mohamed helmy elhefnawy 2. the concept of smart hospitals, importance and advantages the term "smart buildings" has appeared in the early eighties of the twentieth century to achieve integration between the environment, technology, and provide comfort in controlling electronic devices in buildings. initially, focus is given to the technological side and support of communication between building systems (air conditioning, ventilation, safety, security, etc.) to achieve the building user's requirements and increase productivity, smart buildings can be defined as buildings that are equipped in a technical manner that allows effective management of resources at the lowest cost [8]. this is to be able to interact with the internal environment and adapt to the external environment [9]. hence, smart hospitals can be defined as: hospitals that are able to continuously adapt and improve the internal environment to achieve the needs of its users by responding to external changes such as climate and security protection, and the interior changes in functional and surveying requirements in the building[10]. this is done at specified times, according to information collected from the internal and external environment [11] by means of inputs such as detectors [12]. they are buildings that change constantly as a result of the continuous interaction between their components (location, operations, users, administration), and the relationships between them[13]. this is done by using materials, systems and sensors that rely on self-interacting techniques with the environment to give the hospital additional features that are compatible with technological advances and medical requirements[14]. also, they are buildings capable of creating a good climate that helps to raise the efficiency of its users and effectively manage to reduce the cost of operation over its life span. this is carried out by integrating environmental systems (energy, lighting, sound, temperature, communications, information network, etc.) to achieve rapid communication with the outside world by computer, optical fiber and satellite[15]. the systems should be controlled and adapted by comprehensive integration and coordination without direct interference from the user[16], with the exploitation of technological systems and building control systems to achieve the highest functional and technological performance for it[17], so that the effective technology and architectural strategies related to global networks are formed to create comprehensive development and integration with users[18], also to complete integration between jobs and technological systems, face current or future requirements and needs, and inspire sustainable life for future cities[17]. smart hospitals are concerned with providing an effective environment that helps users to achieve goals related to cost and environmental comfort, " safety and security", suitability flexibility[19], [20], sustainable energy and water, reduce emissions and waste pollution[13], focuses on identifying the characteristics and capabilities of building an architectural hospital to achieve dynamic response to environmental factors and managing reactions in a manner that depends on anticipating environmental changes, and the use of renewable energy sources. the hospital-intelligence can be apparent in its internal functions, the services that it provides, the management systems, or all three aspects integrated[17]. it is also shows the correlation between its aims and modern design of hospitals, according to the following: 3. characteristics and types of smart materials and systems, and their role in hospitals managing smart hospitals depends on the use of smart materials that are used in the construction and finishing of the building [21], and smart systems through which the building is managed, according to the following. 3.1. smart materials in hospital buildings smart materials are capable of providing a unique beneficial response when specific changes occurs in the surrounding environment[22]. they are high-tech materials that have the ability to sense and respond to adaptation to environmental, internal and climatic changes[22]. they are able to perceive and respond to many external stimuli in an organized manner[23], stimuli that can be electrical, chemical or magnetic in nature[12]. the difference between smart and traditional materials is seen in the composition and interaction with external influences and response to external stimulus in order to control temperature changes or solar radiation [24]. such materials form a part of the smart structural system and have the ability to sense its environment and calculate changes to the building [25]. 3.1.1. smart material properties intelligent materials are characterized by the ability to return to their previous form, self-repair, strength, rigidity, ductility and high efficiency. in addition to the long life span, ease of manufacture, installation, aesthetics and environmental compatibility and the ability to respond quickly to hazards[11]. 3.1.2. types of smart materials according to the nature of intelligence, smart materials are divided into materials that change one of their properties (chemical, thermal, mechanical and magnetic) in response to a change in external conditions, and materials that transfer energy from one form to another directly, as in figure1. table 1 illustrates types of smart building materials that correspond to the requirements of smart hospitals. figure 2 shows some of type of smart materials mentioned in the previous table. also, table 2 shows types of smart floors, walls and ceilings finishing materials compatible with the requirements of the smart hospital [26], [27], figure3 also shows types of walls and ceilings finishing materials mentioned in the previous table. 2 eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e4 3 a proposed methodology for integrated architectural design of smart hospitals figure 1. types of smart materials [28] table 1. types of smart building materials that correspond to the requirements of smart hospitals type material name components the use b ui ld in g m at er ia ls lighttransmitting concrete it is a mixture of concrete and fiber optics it allows light to pass through it, and a view of the outside world transparent concrete concrete made from crushed glass and plastic materials that help to cohesion makes the building facade as a large glass window and withstands pressure aerated concrete aluminum powder is added to cement, lime and water to produce lightweight concrete it is used for high-rise buildings and interior walls pervious concrete concrete with a porous structure that allows rain water to pass through to the ground, and is durable it is used in sidewalks and floors luminous brick it is made of transparent or colored polycarbonate panels and can withstand more than ordinary glass it is used in high art buildings because it is glossy or matte smart brick stuffed bricks with sensors, processors, and wireless signal connections to warn of hidden pressures and damage in the aftermath of a disaster it provides important and necessary information for firefighters and rescue workers and provides safety for them smart cement magnesium carbonate is put in place of calcium carbonate and absorbs carbon dioxide from the air it is used to protect against pollution and airborne infection transmission light-transmitting concrete transparent concrete aerated concrete pervious concrete luminous brick figure 2. types of smart materials table 2. types of smart floors, walls and ceilings finishing materials compatible with the requirements of smart hospital [26] [29]. type material name components the use fl oo rs fi ni sh in g m at er ia ls electric energy floors it is equipped with a wireless transmitter to capture kinetic energy within people walk and convert it into electrical energy electric energy in lighting, etc., or stored excess energy in batteries for use at night floors equipped with advanced protection system they are tiles equipped with remote sensing devices as a protection system, so that people can be identified through the footprint. identify people, report to security systems, know people if they fall, and give an ultimatum electrostatic floors generates energy depending on pedestrians, and tiles are 50 cm x 50 cm, when people press them, they generate 0.1 watts clean energy that preserves the environment, reduces co2, and saves energy consumption phosphorous ceramics made of glass with phosphorous pigments, organic and inorganic materials to be able to absorb sun energy, that used as visible energy at night heat resistance and chemicals materials, easy to clean and do not require special maintenance narmada slices carbon strips surrounded by two polyethylene layers, and there are two copper strips on both sides of the strips that conduct electrical current, the it generates thermal energy and is installed and. it is safe and isolated and has no risks from short circuit eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e4 mohamed helmy elhefnawy type material name components the use current passes from one copper strip to another through carbon to generate thermal energy or water, transported easily from one place to another under carpet w al ls a nd c ei lin gs fi ni sh in g m at er ia ls reflective indoor coatings reflects the lighting, which increases the feeling of lighting, and reduces energy consumption suitable for areas with limited sunlight with intensity and duration dark painting super black coating to dim the light 10:20 times resistant to unwanted reflection shutoff valves it contains water flow sensors in case of leakage prevent infusion and its damage optical fiber orientation devices to wave and light signals for remote sensing application chromogenic glass its characteristics change according to the needs of the building give an aesthetic appearance and control of the light self-cleaning glass that is chemically treated and coated with titanium oxide pollution resistance and infection control coagulate glass it is placed between the two layers of the aerogel material, and responds to heat. it clots and changes to a semi-transparent mode it changes according to requirements of space, and achieve thermal insulation and privacy photochromic materials they are substances whose color characteristics change by exposure to light painting the elevation of building to interact with the sun and light formable aluminum sheets flexible and moldable protects the building from ultraviolet radiation and is lightweight decorating the walls due to its softness, and ease formation polystyrene acoustic panels made of cast polystyrene fibers and considered a sound absorbent material it is used to control sound in interior spaces hanging granule technology microscopic granules of a light-absorbing solid that between two glass plates coated with an electrically conductive material change of agglomeration of the granules changes the transparency of the glass, the entry outside light status variables (pcm) collect and store the thermal energy materials used to cool the vacuum in the summer or heating in the winter. its state changes when absorbing thermal energy or its release from a solid to a liquid state or vice versa aluminum coated panels they are aluminum panels with a rough surface, and these panels reduce energy consumption by 15%. used to store solar or wind energy and broadcast it in the building for heating and sound absorption fluoropolymer panels they are air-pressed transparent polymeric panels, one, two or three layers, which form the building sheath and are surrounded by a metal frame. it provides heat insulation and uv protection and is self-cleaning and anti-combustion microscope slides 1 mm strips of acrylic and glass have small holes, when the sound waves are joined to it, the sound energy converts to thermal one, decrease the noise it is used for acoustic insulation, and electrical energy for heating due to the heat produced aerogel glass porous, dry gel materials with little thermal conductivity. when exposed to heat, they quickly clot, the color of the glass changes to a semi state provides sound insulation and fire extinguishing ability, and reduces temperature. photovoltaic glazing transparent materials and when exposed to the sun, begins to disperse and reflection begins and turns to the visible spectrum at more rays. to reduce solar heat gain, and thus reduce the cooling load, it generates little clean electricity thermochromic glass change optical and thermal properties according to the ambient temperature and solar radiation intensity. achieves shading, the glass remains transparent at lower temperatures and becomes opaque when raised gasochromic glass the idea of its work depends on pumping the hydrogen gas h2 or o2 oxygen into the cavity between the glass plates, absorbing the sun's heat it absorbs the sun's heat, transports it to the internal space, and reduces the electrical consumption electrochromic glass variable properties of substances, able to change their color independently responsing to an external electrical catalyst it controls the gain of sunlight, controls daylight, and reduces the need for artificial lighting liquid crystal technology two layers of glass with a liquid crystal when electricity is shed on it is arranged regularly, the glass becomes transparent passing light control the amount of light transmitted through liquid crystals between the two layers of glass suspended particle glazing it includes needle-shaped particles stuck in a liquid at random between two double glazing panels. when electricity passes, the particles are organized to pass light. when the particles stop moving, the glass dims and blocks the light. it is used to protect against harmful uv rays when turned on or off and instantly controls the amount of passer by light and heat smart vital interfaces contain cells that resemble the lens it controls solar energy entry, 4 eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e4 5 type material name components the use mashrabiya of the imaging camera, to automatically reduce and enlarge the holes according to the light intensity. reduces air conditioners and allows light to enter without solar radiation sun break technology fiberglass, aluminum or glass-reinforced sheets are strong and flexible, which are used with elevations to open or close automatically as needed to reduce heat and energy. it is dynamics, changing its shape, composition and orientation to respond to environmental factors, and climate change solar cell coverage techniques solar capacitors are combined with the glass tiles and put them on the roofs over the solar cells to absorb and deliver energy while protecting them from external influence. solar energy absorption, storage and utilization in solar cells cira light suntrackers skylight they are roofs that take advantage of daylight, using solar powered gps. mirrors cover the building’s sunlight with a prismatic lens that distributes light regularly. clean lighting technology, sustainable solar-powered lighting solution to save energy optical fiber coagulate glass polystyrene acoustic panels aerogel glass glass of suspended particles figure 3. types of walls and ceilings finishing materials 3.2. intelligent systems in hospitals smart systems are defined as a set of inputs that are prepared in specific ways that achieve certain desired goals[15]. they compose of a group of interconnected elements such as sensors, motors, controllers, and computers that are managed together to control the main functions of buildings and control subsystems such as heating, ventilation, cooling, etc[30]. specific software are that linked to hardware such as switches, communication media, and connectivity materials such as wires, equipment, and data entry means[31]. this plays an important role in building economics and management[10], as well as energy conservation through various effective programs, to obtain optimum performance and help with operation and maintenance . 3.2.1. components of smart systems it consists of three components: input systems for collecting information on factors associated with the building, using reception devices such as internal sensors distributed in the rooms according to the type of sensor and the shape of the space[32], or external sensors that attach to the top of the rooms or on the exterior[31]. information processing is carried out to obtain information, data from input, analyze and process them to control other systems in an integrated manner[33]. then the outputs system includes the output of the data processing, through which clear decisions are enforceable. the response to this is either internal, such as responding to wind loads, or external as changing the intensity of lighting, or opening or closing doors automatically[33]. its role in the building can be determined in making it an architectural product capable of knowledge, decision-making and selfresponse[1]. 3.2.2. characteristics of smart systems intelligent systems are characterized by their high efficiency when using high quality insulating and conductive materials, the possibility of simultaneously combining several activities and controlling several services such as lighting, air conditioning. in addition to the ability to receive several variables from different sources in a highly complex way, such as lighting several rooms with varying degrees of lighting intensity. also this includes the ability to handle and manage peak periods by reducing loads, monitor and analyze internal and external environments and implement operational functions without human intervention. this is to remotely control systems via the internet [34]. with the importance of the role of automation in developing architectural environments by relying on technical equipments and communication devices[35], the effect of virtualization, communication technologies, the internet, and virtual reality . 3.2.3. types of smart systems smart systems include three types: control and access control systems, direct digital control systems, and communication systems, as shown in table 3. . a proposed methodology for integrated architectural design of smart hospitals eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e4 mohamed helmy elhefnawy table 3. types of smart finishing compatible with the requirements of the smart hospital [26] [29]. the system system name nature use a cc es s c on tr ol sy st em s identification systems invisible sensors are placed under tiles or in concrete, safe because the electricity that flows through them is very weak. it gives an alert when there are people who are not authorized to enter the place, and ensure that the person has access cctv & video surveillance live and direct surveillance devices in some places used at the entrances and corridors, monitored and recorded video and transferred by internet thermal imaging camera it detects and measures by temperature differences allows observation of what cannot be seen while ensuring quality and safety image recognition system it depends on the quality of the photos and the lighting and background it detects and encodes faces in videos and photos d ir ec t d ig ita l c on tr ol sy st em s smart sensors system for analyzing weather forecast, measuring potential environmental, fire alarm, and monitoring spaces used to monitor lighting, noise, humidity, temperature, and built-in control, proximity and touch sensors, for safety and fire control. heating, ventilation and air conditioning a control system consisting of a set of rings grouped together maintaining the environmental conditions required for vacuum and monitoring them, and improving the quality of indoor air energy efficiency monitoring it closes the systems at times of occupancy or with the schedule of works individual control in each room to conserve energy, monitoring energy consumption by user lighting control systems management in line with the needs of each building, according to its type, area and percentage of occupancy monitor bills, measure the amount of electricity consumption, and provide information and data directly to the consumer addressable fire alarm system each detector has a title and guides about the fire or smoke with a separate report instructs the fire zone to send signals if smoke reaches a certain level smart plumbing systems automatic devices with faucets to collect the used water and reuse it for irrigation it aims to conserve water through the use, detection of water leakage, and its location vertical communication associated with vertical communication between building elements it contains an alarm system, surveillance cameras and communication equipment c om m un ic at i on sy st em s addressing communications devices for converting traditional systems to addressing, with the possibility of linking them to traditional systems it is used to facilitate maintenance, reduces communication costs, and gives high quality connections network (lan) wireless networks check high speed small buildings are used network (wan) wireless networks achieve high speed data over a wide areas 4. modern design requirements related to smart hospital thought the link between smart hospital and modern hospital design shows the importance of achieving interactive functionality, technology, user desires, environmental needs, and security and safety. 4.1.1. requirements for functional interactivity recently, hospital design requirements are concerned with achieving: (a) flexibility and self-response to changing in functional requirements leading to an improvements in the internal environment of occupants, (b) functional expansion to accommodate future growth, (c) interactive management of operational cost control aspects, (d) adaptation to changes in uses, to achieve certain economic and technical aspects[36], (e) the possibility of adding security and fire protection systems according to the requirements[37], (f) moving towards the digital space, enhancing medical services, using a model that provides business requirements, information technology, and improving work flow, (g) integration of systems and technology to serve users, interact with functions and capabilities of remote communication, periodic maintenance works, facilitate work movement, and internal communication[17], (h) development based on information technology, (emr), and using of information regarding medical treatment and operation, as shown figure4 . figure 4. identification of smart assets in hospitals [40]. 6 eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e4 7 4.1.2. technological considerations hospital designs are concerned with the requirements of: (a) enhancing the participation of patients and companions in the medical process, by simplifying communication between them and service providers, (b) improving work flow using the internet and mobile technology, (c) reducing patient frequency rates on the hospital and waiting for them and sending notifications of service delivery times, (d) ease of access and finding the way to and within the building to meet the needs of users[17], (e) relying on "smart planet", using sensors and transmitting information using the internet of things and artificial intelligence[23], (f) providing electronic health records for patients[2], (g) avoiding paperwork to counter the abundant information that is newly produced by medicine[38], (h) automated operations dependent on information and communications[17], (i) use of radiofrequency identification (rfid) systems and the participation of doctors and nurses in parallel[39], (j) monitoring building elements and providing a comfortable environment for occupants, using data transmission infrastructure networks, (k) integration of technological systems for elevators, airconditioning, lighting, fire and security, and communication systems (telephone, fax and internet) [12]. (l) using internet and satellite communication for internal communication, automation, and building management[17], such as trinitas regional medical center, new jersey. 4.1.3. achieving environmental considerations the hospital is dealing with requirements: (a) compatibility with the environment and sustainability by exploiting renewable energy sources and controlling light, heat, and ventilation[41], (b) reducing the use of traditional energy resources, and their cost[42], (c) reducing environmental pollution by reducing noise, gas emissions, and providing indoor air quality[43], (d) achieving quality for internal environments including: physiological comfort (programming the temperature, humidity and type of required ventilation according to users), thermal comfort (providing comfortable thermal conditions with thermal balance between the body and the environment), visual comfort (changing the level of lighting automatically according to the function and without stress), audio comfort (outer envelope acoustic treatment and insulation of internal spaces), saving time and effort (supporting communications and technologies, monitoring, safe and safety systems, and communication with equipment) such as the university of missouri health care, columbia, longterm cost savings (construction, maintenance, operation, automatic control of lighting, and ventilation of unoccupied spaces) [44], (e) providing environmentally friendly materials and systems that achieve social, and technical goals[3], (f) reducing risk, use less paper, recycle and generate less waste[45]. (g) improving environmental performance by improving site capabilities and preserving water and materials[17]. 4.1.4. achieving users' desires hospitals are concentrated on the requirements of: (a) responding by changing the behavior of materials according to the needs of occupants, in terms of adapting to external conditions, (b) integrating electronic tools and means to provide comfortable environments and enhancing employee safety according to work changes[1], (c) managing resources automatically to increase the efficiency and satisfaction of occupants, (d) linking automated control systems with information systems, to address occupant requirements and make buildings responsive, (e) modernizing the building's electronic systems and equipment without the need to replace existing electrical connections to address future requirements[10], (f) providing climate control, energy, air-conditioning and ventilation systems for the users comfort[17], (g) electronic control of communication networks and fire-fighting systems according to the user’s desires[46], (h) application of technology in storing patient data, reducing traffic distances for workers to reduce stress, waiting, and stay times [47], (i) utilize mobile and internet of things technologies to provide effective communication between patients and caregivers such as the ohio state wexner medical center, columbus . 4.1.5. achieving the hospital is currently concerned with requirements: (a) electronic control of building systems in order to protect from fire, and mitigate dangers[17], (b) continuous monitoring of systems to achieve conditioning and dealing in emergency situations [48], (c) providing hospital automation systems and methods of control, monitoring of materials, and their internal installation[10], (d) electronic programming of hospital components and systems according to the expected possibilities which allows them to act and adapt accordingly, to overcome the negative effects of the environment[49]. (e) restoring building systems safely, quickly and easily, (f) making quick decisions with regards to energy management, maintenance, communications, fire protection, safety, etc., and achieve integration between systems to achieve maximum safety for its users[50], (g) the use of remote communication systems to control transmission of infection[17]. 5. a proposed methodology for the integrated architectural design of smart hospitals the methodology is based on five main stages, as shown in the figure 5. figure 5. a proposed methodology for the integrated architectural design of smart hospital buildings a proposed methodology for integrated architectural design of smart hospitals eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e4 mohamed helmy elhefnawy first stage: defining modern design requirements related to smart architecture thought in this stage, modern design requirements, previously identified in item 4 will be studied, and a reference to local conditions, operating policies, user requirements, and stability is required to utilize the premise of using smart materials and systems. second stage: facing the main challenges impeding hospitals to become smart at this stage, challenges encountered by designers when dealing with the design of smart hospitals will be identified, including: (1) conflict in priorities among requirements mentioned in the previous section (2) weaknesses pertaining to dealing with smart hospitals such as the system failures, human errors, natural disasters, failure to link devices to systems, insufficient physical security of components, noncompliance with regulatory standards and user behavior. these challenges are addressed by referring to officials, operating policies and future plans of services, in order to address weaknesses, using smart materials and systems in addition to achieving integration among them. third stage: defining the proper basics of the architectural design of smart hospitals this stage defines the principles of architectural design that meet the goals and requirements of smart hospitals and face the challenges associated with them, figure6, including: aproviding information in an adaptive manner that achieves interaction with the environment and changes functional requirements to suit user needs. bproviding high flexibility, and achieving information security [28]. c self-control and change of status of materials according to changes in the surrounding environment and users' desires. d coordination between hospital systems and devices in a way that allows for the integration and analysis of data [51]. eproviding information to patients under care during their stay. fsmart rooms in hospitals allowing patient and relatives to see medical information. gusing smart technology and mobility systems such as tablets and smart phones [3]. husing smart technologies like wifi, active rfid, sensors and integration platforms. i combining existing hospital technologies with new smart programs to reducing required time for providing services. jinternet of things (iot) applications for detection and follow-up, using artificial intelligence. kovercoming the disadvantages of the traditional information systems, and building the basic network environment [52]. lthe tele-care system, expanding hospital boundaries and reducing frequency of visits. midentification systems to track and document patients or employees and infection control. navailability of communication and integration of smart devices to provide the correct information in the right place and time. ousing building management software to monitor its services, energy conservation, operation and maintenance. p patient monitoring and automatic data transfer, with automation of special units such as intensive care (icu) [53]. qremote voice, video, storage, and forwarding technologies[53]. rintelligent automatic operations and task automation to achieve safety for patients and convenience for doctors. sreal-time location system (rtls), hand-washing monitoring, nurse call system, communication control, employee messaging, call-bell and notification of medical staff assistants on mobile devices, emails [20]. figure 6. the basics of architectural design of smart hospitals fourth stage: defining the role of smart materials and systems in the architectural design of smart hospitals at this stage, defining the contribution of smart materials and systems to achieve the basics of the architectural design of smart hospitals mentioned in the previous stage is determined, as shown in the following table4. fifth stage: achieving integration between smart materials and systems inside smart hospitals in this stage, ways to integrate the elements of the smart building (materials and systems) are specified to achieve functional compatibility and integrated buildings management. in addition to locating equipment and linking systems, devices and programs in a common structure and enhancing sustainability in buildings. this is done by referring to the schedule of requirements and types of smart materials and systems in the previous stage of methodology. then identifying alternatives for smart materials and systems necessary to achieve each of the architectural design standards. furthermore, determining the most appropriate systems according to operating policies and capabilities available in the hospital, then determining the mutual effect between smart systems and materials in the fourth stage in addition to stipulating its link with the functions of the different spaces in the hospital. furthermore, to determine the relationship between smart materials and systems according to modern design requirements, mentioned in the first stage, and ensure the integration between smart materials and systems that directly and indirectly affect the architectural design, as shown in the last cell at table4. this stage ends with a reassessment and testing of the methodology by returning again to the first step and making sure that modern design requirements related to smart architectural ideas are met . 8 eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e4 9 technology, security, safety technology functionality, environm ental needs technology functionality, environm ent technology, user desires-environm ent functiontechnology, environm ental needs environm ental needs technology environm ental needs a ll environm ental needs, and security and environm ental needs environm ental needs u ser desires technology function u ser desires technology -u ser desires technology -u ser desires technology u ser desires security and safety security and safety a ll functionu ser desires d esign requirem ents and achieve integration table4. r ole of sm art m aterials and system s in the a rchitectural d esign of sm art h ospitals ● ● ● ● lighttransmitting concrete b uilding m aterials ● ● ● ● ● transparent concrete ● ● aerated concrete ● ● pervious concrete ● ● ● luminous brick ● ● ● ● ● smart brick ● ● ● smart cement ● electric energy floors floors finishing m aterials ● ● ● ● ● ● floors equipped with advanced protection system ● electrostatic floor ● ● ● ● ● ● phosphorous ceramics sem i d irect effect ● ● ● ● narmada slices ● ● reflective indoor coatings w alls and ceilings finishing m aterials ● dark painting ● shutoff valves ● ● ● ● ● optical fiber d irect effect ● ● ● chromogenic glass ● ● ● ● self-cleaning glass ● ● ● coagulate glass ● ● ● photochromic materials m onitoring, recovery of building system s u pdating electronic system s and equipm ent v entilation and clim ate control for user com fort c ontrol and connectivity to electronic system s h ealth and safety prom otion and infection control b ehavior change according to the desires of the users r em ote control, m otion m onitoring and self-control r ecycling environm entally friendly m aterials save tim e, effort and reduce operating costs w ater conservation and sustainability principles the patient's audiovisual com fort reduce pollution r enew able energy use, energy efficiency c ontrol and adaptation in the external environm ent integration betw een electronic system s for m axim um safety sm art infrastructure find the w ay and ease of access to the hospital r educing frequency and w aiting for service effective com m unication betw een patients and service providers r em ote connection and m aintenance d igital space and electronic archive safety and control of fire system s im proving the efficiency of the indoor environm ent r esponding to change in job and future grow th b asics of the architectural design of sm art hospitals sm art m aterial, system s a proposed methodology for integrated architectural design of smart hospitals eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e4 mohamed helmy elhefnawy technology, security, safety technology functionality, environm ental needs technology functionality, environm ent technology, user desires-environm ent functiontechnology, environm ental needs technology environm ental needs a ll environm ental needs, and security and environm ental needs environm ental needs u ser desires technology function u ser desires technology -u ser desires technology -u ser desires technology u ser desires security and safety security and safety a ll functionu ser desires d esign requirem ents and achieve integration c ont. table4. r ole of sm art m aterials and system s in the a rchitectural d esign of sm art h ospitals ● ● ● formable aluminu m sheets w alls and ceilings finishing m aterials ● polystyre ne acoustic panels ● ● ● hanging granule technolo gy ● ● ● status variables (pcm) ● ● ● aluminu m coated panels ● ● ● fluoropol ymer panels ● microsco pe slides ● ● ● aerogel glass ● ● ● photovolt aic glazing ● ● ● thermoch romic glass sem i d irect effect ● ● ● gasochro mic glass ● ● ● electroch romic glass ● ● liquid crystal technolo gy ● ● ● suspende d particle glazing d irect effect ● ● smart mashrabi ya ● ● ● ● sun breaks technolo gy ● ● ● solar cell coverage techniqu es ● ● ● ● cira light sun trackers skylight m onitoring, recovery of building system s u pdating electronic system s and equipm ent v entilation and clim ate control for user com fort c ontrol and connectivity to electronic system s h ealth and safety prom otion and infection control b ehavior change according to the desires of the users r em ote control, m otion m onitoring and self-control r ecycling environm entally friendly m aterials save tim e, effort and reduce operating costs w ater conservation and sustainability principles the patient's audiovisual com fort reduce pollution r enew able energy use, energy efficiency c ontrol and adaptation in the external environm ent integration betw een electronic system s for m axim um safety sm art infrastructure find the w ay and ease of access to the hospital r educing frequancyand w aiting for service effective com m unication betw een patients and service r em ote connection and m aintenance d igital space and electronic archive safety and control of fire system s im proving the efficiency of the indoor environm ent r esponding to change in job and future grow th b asics of the architectural design of sm art hospitals sm art m aterial, system s 10 eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e4 11 technology, security, safety technology y, environm ental needs technology functionality, environm ent technology, user desirese i t u cto technology, environm ental environm ental needs technology environm ental needs a ll environm ental needs and security environm ental needs environm ental needsu ser desires technology function u ser desires technology -u ser desires technology -u ser desires technology u ser desires security and safety security and safety a ll functionu ser desires d esign requirem ents and achieve integration c ont. table4. r ole of sm art m aterials and system s in the a rchitectural d esign of sm art h ospitals ● ● ● ● ● ● identificati on systems a ccess control system s ● ● ● cctv & video surveillan ce ● ● thermal imaging camera ● ● image recognitio n system ● ● ● ● ● ● ● ● ● ● ● smart sensors d irect digital control system s sem i d irect effect ● ● ● ● ● ● hvac systems ● ● ● ● energy efficiency monitorin g systems ● ● ● ● lighting control systems d irect effect ● ● ● ● addressab le fire alarm system ● ● ● ● smart plumbing systems ● ● ● ● ● ● vertical communi cation systems ● ● ● ● addressin g communi cations devices c om m unication t ● ● ● ● ● network (lan) ● ● ● ● ● ● network (wan) m onitoring, recovery of building system s u pdating electronic system s and equipm ent v entilation and clim ate control for user com fort c ontrol and connectivity to electronic system s h ealth and safety prom otion and infection control b ehavior change according to the desires of the users r em ote control, m otion m onitoring and self-control r ecycling environm entally friendly m aterials save tim e, effort and reduce operating costs w ater conservation and sustainability principles the patient's audiovisual com fort reduce pollution r enew able energy use, energy efficiency c ontrol and adaptation in the external environm ent integration betw een electronic system s for m axim um safety sm art infrastructure find the w ay and ease of access to the hospital r educing frequancyand w aiting for service effective com m unication betw een patients and service providers r em ote connection and m aintenance d igital space and electronic archive safety and control of fire system s im proving the efficiency of the indoor environm ent r esponding to change in job and future grow th b asics of the architectural design of sm art hospitals sm art m aterial, system s a proposed methodology for integrated architectural design of smart hospitals eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e4 mohamed helmy elhefnawy 5. conclusions & recommendation the following are the most important conclusions and recommendations of the research. 5.1. conclusions (1) there is a close link between the premises and principles of smart architecture and fulfillment of design requirements of modern hospitals. (2) the use of smart materials and systems contributes to achieving functional interactivity, technological considerations, environmental considerations, user needs, and enhances security and safety. (3) the integrated architectural design of smart hospitals can be achieved by a proposed methodology consisting of 5 basic stages that start with defining design requirements and ending with ways of achieving integration between the elements of the, as shown in the figure5. (4) the concept of using smart materials and systems meets various design requirements for smart hospitals, according to their nature and characteristics, directly or indirectly, as shown in table3. (5) the use of smart building materials allows responding to changes in functionality, while smart floor finishing materials generate clean energy and control movement in special spaces. (6) the architectural designer must review operating policies and design requirements of the hospital for an appropriate selection of materials and smart systems used within it. (7) various types of smart glass are considered to have an influential role regarding the use of renewable energy and reducing energy consumption, thus reduce operating costs. (8) integration in the architectural design of hospitals is achieved by monitoring the operations of all the systems used and providing utilities to link them with smart materials and achieving an appropriate level of comfort, convenience, safety and efficiency for workers. (9) the use of transparent concrete, phosphorous ceramics, smart sensors and (wan) network contributes to achieving design requirements of smart hospitals in a way that exceeds other approaches. (10) integration between smart materials and systems is achieved by taking into account the characteristics of smart materials and systems, and determining their relationship with the design requirements of smart hospitals. (12) most smart materials and systems are concerned with improving the internal environment, and achieving thermal, audio, and visual comfort, as they affect energy, time, effort savings, and reduce costs. (13) the role of smart systems is apparent in achieving effective communication between smart hospital users and in self-controlled, systems according to their requirements. 5.2. recommendations through the study, analysis, and results of the research, the research recommends the following: (1) follow the proposed methodology when designing smart hospitals to achieve integration between elements of smart architecture. (2) promoting using smart materials and systems. (3) giving attention to achieving modern design requirements in hospital buildings, using smart architecture elements, including smart materials and systems. (4) encouraging studies and research that develop smart materials and invent new interactive materials to keep pace with technological development in hospital design. (5) when designing smart hospital buildings, focus is given to activating integration between smart materials and systems and taking attention to materials and systems that meet more than one design requirement without affecting on any other requirement. (6) activating the role of smart systems and materials in obtaining smart hospitals with responsive and interactive properties. (7) preparing methods for assessing smart buildings on an environmental basis, to know the extent of their impact accurately on the surrounding environment and its conservation. 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(2014) smart hospital technology, health informaticsan international journal (hiij), volume(3), no.(3). a proposed methodology for integrated architectural design of smart hospitals eai endorsed transactions on smart cities 07 2020 08 2020 | volume 4 | issue 12 | e4 https://www.researchgate.net/profile/saleh_ben_safar https://link.springer.com/bookseries/5661 https://link.springer.com/bookseries/5661 https://www.researchgate.net/scientific-contributions/2165181523_wenbo_yang https://www.researchgate.net/scientific-contributions/2165150879_peng_wang https://www.researchgate.net/profile/jehane_michael_le_grange https://arxiv.org/search/cs?searchtype=author&query=lennie%2c+a https://arxiv.org/search/cs?searchtype=author&query=sadigova%2c+p https://arxiv.org/search/cs?searchtype=author&query=such%2c+j+m https://www.researchgate.net/publication/258734399 https://www.researchgate.net/publication/321615252_smart_health_open_problems_and_future_challenges https://www.researchgate.net/publication/321615252_smart_health_open_problems_and_future_challenges https://www.sciencedirect.com/science/journal/13865056/77/3 https://www.sciencedirect.com/science/article/abs/pii/s1364032118302211#! https://www.sciencedirect.com/science/article/abs/pii/s1364032118302211#! https://www.sciencedirect.com/science/journal/13640321 https://www.scimagojr.com/journalrank.php?country=fi paper title (use style: paper title) i. introduction after starting full-scale vehicle life in the 1970s, society has required the development of transport system for safety and efficiency. automotive industry has obtained not only accelerating industrialization but also expanding of living area. but, behind the scenes, social costs were increased by traffic accidents. to prevent these situations, we need a more advanced its system then the current scenario. this paper presents the basic requirements of safety engineering infrastructure of roadside infrastructure in its for intelligent vehicles. intelligent vehicles has network infrastructure to communicate with vehicle-to-vehicle (v-tov), vehicle-to-infrastructure (v-to-i), lane correction system, and traffic information system etc. the intelligent vehicles has a good model for learning demands of infrastructure for its process because the system have a lot of use-cases and we must understand relationship between public institutions, people, companies in order to proceed its system. this paper has organized into sections as follows: section ii provides problem in intelligent vehicles and their challenges in v-to-v communication system. section iii, provides the requirement specifications of safe and secure engineering design architecture. in the section iv, we discussed the novel safe and secure engineering model for intelligent vehicles. finally, in the section v, we have concluded final remarks and impact of intelligent vehicles with the respect of social, technical and business. ii. problem statements and challenges current its technique optimize traffic management and highway capacity by introducing spatial-temporal distribution of traffic flow to provide information through various media such as vms, broadcast, internet, and etc. after its collects real-time traffic information through detection devices and cctv on the highway in 2,804km of 23 routes. however, republic of korea has operated highway traffic management system, since public infrastructure investment fig.2. vehicle-to-vehicle communication system. a. current infrastructure and challenges in its  information content: there is no condition of information exchange type between road and vehicle therefore we need to provide point-based traffic information (vms-oriented) and indirect information such as ars, internet, etc.  communications: there is no demand control function for preventing excess capacity. therefore lack of traffic flow distributed technology of whole road in case of emergency , lack of real-time sensing function in case of emergency, lack of estimated function of traffic, condition when delaying.  security: restrictive crackdown of unit point about violator's vehicles which are the main culprit of big accident passive management systems such as use of manpower when road maintenance management (safety issue)  others : interchange (ic) system that abnormally add to the etc, difficulty of differentiated services about the etc vehicle, limited payment structure (prepaid), uniform way to settle the charges on ic system, lack of velocity-based and high-tech traffic condition model, however, there is no information service for road manager. requirement engineering for intelligent vehicles at safety perspective eai endorsed transactions smart cities research article madhusudan singh yonsei institute of convergence technology, yonsei university, songdo, incheon, south korea abstract abstract— in the coming years, transportation system will be revamped in a manner that there will be more intelligent and autonomous vehicle phenomenon around us such as smart cars, auto driving system, etc. some of automotive industries are already producing smart cars. however, the main concern of this paper is on the infrastructure for intelligent vehicles, which can support such intelligent transportation. current transportation system lacks proper infrastructure to support intelligent vehicles. hence in this article, we have surveyed and analysed the current transportation system in developed and developing countries. in contrast, we are going to introduce secure intelligent transportation (roadside) infrastructure that is user centric (driver, autonomous driver etc.) for intelligent vehicles. in this paper we present the basic requirements of safety engineering infrastructure of roadside infrastructure in its for intelligent vehicles. intelligent vehicles has network infrastructure to communicate with vehicle-to-vehicle (v-to-v), vehicle-to-infrastructure (v-to-i), lane correction system, and traffic information system etc. the intelligent vehicle is a good model for learning demands of infrastructure for its process because the system having many use-cases and we must understand relationship between public institutions, people, companies in order to proceed its system. received on 13 june 2017; accepted on 03 august 2017; published on 20 december 2017 keywords: intelligent vehicles; requirement engineering; its copyright © 2017 madhusudan singh , licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.20-12-2017.153496 planning group to the president introduced its in 1993 [7]. however, its infrastructure has to consider road, it, and vto-v communication such as shown in fig.2. 1 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e2 the basic requirements of intelligent transportation world such as intelligent transportation system, infrastructure, smart vehicles, intelligent vehicles requirements and their challenges are given in fig. 3. fig. 3. specification of intelligent vehicles. iii. engineering model for safety the overview infrastructure of a secure intelligent vehicles in its has shown in fig. 4, where the communication tower collect the data such as traffic data, weather data on highway, car data on highway based on data of mobile device that mounted in the car, radio tower send data to main data normalization and event analyzers system. after the analysis of data, the information forwarded to the information storage cloud to mobile device again. then mobile device provides user interfaces to check easier with input value of the driver (user). fig. 4. telematics based safe intelligent vehicles. the major requirements of the telematics based safe and intelligent vehicles system are required mainly four words of system which is as follows  subject roadside: the subject matter of the information system.  system roadside information: charge, traffic jam and so on.  usage driver: the environment within which the planned system will operate.  network system: driver who use the high-way, and stakeholder who related on the high-way system.  system intelligent roadside: what the system does within its operational environment, what information it contains and what function it performs.  data management system: system manages all information related on smart high-way such as smarttolling, transfer information that make a more efficient system to driver. a. use case diagram of engineering modeling in its grasp related behavior between the driver and the smart highway group, we will find detailed in following use case descriptions about the action run which order and what’s related towards to each behavior. based on these, we expect to get final goal of analysis the behavior and purpose of each sub-goal on goal based approach. table i has shown description of use case of secure engineering design for intelligent vehicles. table i. usecase descripition of secure engineeirng use case name pre-condition post -condition uc1. smart-tolling connected successfully between mobile device in vehicle and main system calculate smart highway toll by minimizing decrease of vehicle speed uc2. preventing of car accident network between terminal application and command center application always should be maintained all of users are must enrolled in smart highway’s member prevention of car accident’s function provide intelligence information which can prevent car accident by integrating terminal application’s data and sensor’s data using in smart highway uc3. supporting information for emergency and disaster situation connected successfully between mobile device in vehicle and main system improve efficiency by checking information that is identified by sensor, and it builds a database uc4 weather forecast connected successfully between mobile device in vehicle and main system to prevent accidents due to bad weather uc5 urgent emergency notify the emergency vehicle enter the smart highway, and main system detect the entry of vehicle handle the emergency successfully, so decrease threat of smart highway uc6 using additional service in smart highway network between terminal application and command center application always should be maintained actor’s convenience and satisfaction arise by using additional service in smart highway madhusudan singh 2 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e2 iv. impact and final remarks in upcoming years transportations system will be completely modify. it will be more intelligent and autonomous vehicle around us such as smart car, auto driver, etc. some of automotive industries already produce smart car. but our main concern about infrastructure of transportation system which support intelligent transportation. current infrastructure will be not support intelligent transportation system. so, in this article, we are going to introduce secure intelligent transportation (roadside) infrastructure of user’s (driver, autonomous driver etc.) point of view. it’s called intelligent transportation infrastructure. the impact of intelligent vehicles in its will proved to be a break through on the existing infrastructure of transportation system. these are some of the following effects. a. social impact  provide better and effective transportation life.  provide safe and rapid transit information service under high speed driving conditions.  satisfy the driver's driving service and improve the quality of life  provide traffic information service that fuses with telematics  provide continuous its service in time and space through expansion and linkage of existing its technologies b. business impact  core technology pre-emption related to its service as next-generation growth power and synergy effect of technical  by exporting developed technology, be more competitive in the world market and exploit a way out of export with all technology that need to build test bed  expect creating a ripple effect of related industry: have direct and indirect influence on widespread industry such as vehicle, wireless communication, mobile communication terminal, internet, mcommerce and etc.  promote the national economy by reducing personnel and materiel cost in traffic congestion and traffic accidents that may occur in road under the goal of its technical development of ‘accidentfree’ and ‘nonstop’  inducement the creation of new employment about spreading industry related to its: by invigorating the its services, promote domestic industry and induce the creation of new employment c. technical impact  in high-speed driving environment, guiding role of technology related to real-time db processing technology development and middleware technology development  guarantee of technology caused by alliance of telematics services as part of the national policy and intelligent roadside infrastructure.  globally source technology secure caused by developing the domestic technology by designing the architecture related to developing a traffic monitoring and traffic information fusion technology under the high-speed traffic condition the domestic technology references [1] d. singh and m. singh, "internet of vehicles for smart and safe driving," 2015 international conference on connected vehicles and expo (iccve), shenzhen, 2015, pp. 328-329. [2] z. junping, w. fei-yue, w. kunfeng, l. wei-hua, x. xin and c. cheng, "data-driven intelligent transportation systems: survey", ieee transactions on intelligent transportation systems, vol. 12, no. 4, pp. 1624-1639, 2011. [3] d. singh and a. alberti, "developing novagenesis architecture for internet of things services: observation, challenges and itms application", international conference on ict convergence 2014. [4] woong cho, hyun-seo oh, byeong-joo park, “wireless access technologies for smart highway : requirements and preliminary results”, the journal of the institute of internet, broadcasting and communication, vol. 11, no. 2, pp.237-244, april, 2011. [5] d. singh, m. singh, i. singh and h. j. lee, "secure and reliable cloud networks for smart transportation services," 2015 17th international conference on advanced communication technology (icact), seoul, 2015, pp. 358-362. [6] sujin kwag, sangsun lee, “a survey of v2x communication technologies and project”, journal of the korea society of automotive engineers, vol. 33 no. 5, pp.24-31, may, 2011. [7] jung-hoon song, jae-jeong lee, seong-ryul kim, jung-joon kim, dae-wha seo, “design of u-transportation communication system for next-generation its services”, the journal of the korea institute of intelligent transport systems, vol. 12, no. 5, pp.61-72, october, 2013. requirement engineering for intelligent vehicles at safety perspective 3 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e2 application of real-time gis analytics to support spatial-intelligent decision-making in the era of big data for smart cities 1 application of real-time gis analytics to support spatialintelligent decision-making in the era of big data for smart cities mbongowo j. mbuh1,*, peter metzger2, peter brandt1, kelli fika1 and monica slinkey1 1department of geography and geographical information science, university of north dakota. 221 centennial drive, o’kelly hall, room 156, grand forks, nd 58202, usa 2minnkota power cooperative, an electric utility company in grand forks county, 5301 32nd ave s, grand forks, nd, usa 58201 abstract the rapid growth of the urban landscape from natural development, traffic congestion, crime, and waste management has become a challenge to the city dwellers and decision-makers, thus requiring smart and efficient ways to tackle these problems. the combination of big data and internet of things (iot) is guiding local communities in achieving the goal of building creative communities. this study aims to use real-time spatial analytics that integrates state–of–the art ict approaches with interdisciplinary synthesis for smart solution making process across different sectors of the community. the use of real-time data and coordination of information from multiple city agencies enable policymakers to adjust management strategies in near real-time and can also provide citizens with situational awareness on emergency and nonemergency conditions. using state-of-the-art technologies, and communication-based applications within the context of smart cities, three smart city examples were developed with the case study of grand forks, north dakota. using web appbuilder, a health resources inventory for the town of grand forks was designed with real-time integration of medical information and treatment facilities within the community. for emergency response and preparedness, we developed and deployed a solution that combines information from all the sectors of the city using survey123 for arcgis to collect data and display it on an operational dashboard with multiple visualizations for real-time monitoring of people, services, assets and analysis of events or activities.this operation offers real-time verification and can be an essential resource for team leaders and emergency operations centers. the information collected also provides the flexibility to show layers of information, and task force leaders have a view of their task forces and, consequently, the enrichment of life by making the community safe, healthy, and sustainable. keywords: smart city, ict, iot, real-time gis, big data, spatial analytics, and spatial intelligence. received on 04 december 2018, accepted on 24 november 2019, published on 12 december 2019 copyright © 2019 mbongowo j. mbuh et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.26-6-2018.162219 *corresponding author. mbongowo.mbuh@und.edu 1. introduction increased urban sprawl associated with social, environmental, and economic effects, has led to pollution, environmental destruction, poor land use management, unsuitable urban design. these problems have caused public disruption, ineffectual movement, transportation congestion, general well-being, and increase health risks. all these city problems are related to city infrastructures facing technical and physical issues (colldahl et al., 2013; bibri & krogstie 2017). less than 5% of the world’s population lived in cities in the 18th century (harrison, & ian 2011, jacobs, 2016), however, it has been estimated that by 2050, 60% of the world population will live in research article eai endorsed transactions on smart cities eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e3 http://creativecommons.org/licenses/by/3.0/ mailto:mbongowo.mbuh@und.edu mbongowo j. mbuh et al. 2 urban centers (weisz & julia, 2010, cohen, 2003, united nations, 2015, bibri & krogstie, 2017), adding pressure on the environmental and social sustainability of society (ness et al., 2007, seyfang & smith 2007, ageron et al., 2012). the economic and social activities of cities are inherently related since they consume about 70% of the world’s resources (bilgen, 2014). the focus of geospatial scientists and city planners has been the implementation of smart cities strategies to respond to considerable challenges facing the current urban landscape in an attempt to adopt plans for building a sustainable society (miaoxi et al., 2014, joss, 2015, un-habitat, 2016) that is effectively managed. there is increasing pressure in the way in which cities organize and operate their critical infrastructure, human services, ecosystem services, and administration due to severe challenges related to having a sustainable city (lovell & taylor, 2013, connolly et al., 2014, bibri & krogstie, 2017). these problems that threaten the economic, environmental, and social sustainability of cities (neirotti et al., 2014, al nuaimi et al. 2015, bibri & krogstie, 2017) have given birth to the use of holistic and long-term urban management approaches requiring spatial thinking. several communities have developed and are using innovative strategies for daily operations to overcome the challenges of urbanization (bibri & krogstie, 2017), where urban computing and use of information, communication, and technology (ict), like infrastructures, applications, data analytics capabilities, and services have become a conventional discussion community management use in addressing a variety of environmental challenges in modern city. this holistic thinking has been made possible by incorporating data sensing and information processing into city management using well-managed systems that require smart data and data-centric approaches prompted by the large-scale proliferation of wireless networks (batty, 2012, batty et al., 2012, bibri, krogstie, et al., 2017). in response to the challenges of urban society, city planners, urban geographers, and other scholars have developed the idea of the “smart city”, which is a broad term that promotes the use of innovative, technologybased approaches to make communities more safe, livable, well-run, healthy, prosperous and sustainable (kallerud et al., 2013, mccann & ortega-argilés, 2014). made possible by advances in information, communication and technology (ict), smart city strategies help intelligently manage urban systems so as to produce efficiencies and growth in the areas of transportation, economic development, energy, land use, communication, and service delivery (palensky et al., 2011, yu et al., 2012, bibri, & krogstie, 2017). cities that are well-run, livable, safe, healthy, prosperous and sustainable attain this objective through ict, and this has prompted other communities facing urban growth to seek and implement smart solutions to their problems (kallerud et al. 2013. mccann & ortega-argilés. 2014). modern societies use ict saturated with computation and intelligence for functions, services, and designs for daily operations, and ground-breaking solutions and sophisticated methods are needed to manage a modern urban community. advances in computing have shown that ict holds remarkable potential for assessing, monitoring, understanding, probing, and planning (bibri 2018), by making the environment smart (cook & schmitter-edgecombe, 2009, rashidi et al., 2011). urban population growth and rapid urbanization (united nations, 2015, hashem et al., 2016, bibri & krogstie, 2017), has resulted in numerous smart applications (hashem et al., 2016) which include including smart homes (li et al., 2011, jala et al., 2012), smart grids (lund et al., 2012, dörfler et al., 2013), smart healthcare (catarinucci et al., 2015), smart transportation (ju et al., 2013) and smart cities (batty et al., 2013, townsend, 2013). these smart environment applications have been made feasible by iot, where conventional devices are linked to network technologies (hashem et al., 2016) with advanced ict techniques leading to an increase in the magnitude of data, which is a service rendered by iot. while an established definition of a smart city is still to be considered (brenner & schmid, 2014, morabito, 2015, parnell, 2016, hashem et al., 2016), within the context of this study, we will define a smart city as one that will ‘invest in social and human capital and traditional (transport) and modern (ict) communication infrastructure to promote sustainable economic development and a high life quality, with intelligent management of natural resources, through participating governance.’(caragliu et al., 2012). this definition relies on six distinct classification systems based on smart living, smart environment, smart economy, smart mobility, smart people, and smart governance—through which smart cities can assess their development in the trend of smartness (bibri,& krogstie 2017). inventive and smart solutions that improve livability and enhance sustainability through the integration of digital technology and urban planning is an endeavor all smart cities seek. including the next generation of ict into all walks of life, including roads, railways, tunnels, water systems, bridges, appliances, hospitals, buildings, power grid, and transportation system is the primary focus of every smart city (su et al., 2011, kresl & daniele, 2016, jeena, 2017). we describe a smart city where innovative ict is combined with functional, operational, infrastructural, architectural, physical, and ecological systems at various spatial scales with city planning methods, to increase competence, safety, livability, prosperity equity and sustainability using big data analytics. the application of big data over the past few years in urban analytics has attracted massive attention among scientists, and big data is altering the way cities function and can be managed (batty, 2013, bibri & krogstie, 2017). big data has for a very long time characterized by velocity and volume, and there has been an increasing rate at which different data types have been created (hu et al., 2014, hilbert, 2015, gani, et al., 2016, hashem et al., 2016). big data has the perspective to provide useful information obtained eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e3 https://scholar.google.com/citations?user=ivfkokgaaaaj&hl=en&oi=sra https://www.sciencedirect.com/science/article/pii/s0305750x15002508#! https://scholar.google.com/citations?user=ivfkokgaaaaj&hl=en&oi=sra 3 through numerous sources and can transform the economy of the city (batty, 2013, hashem et al., 2016) and improve the living standards of its citizens through the implementation of significant data applications (jimenez et al., 2014). big data is used and managed with cloud computing platforms to monitor situations, events, activities, processes, behaviors, locations, spatiotemporal settings, environmental states, and socioeconomic patterns in real-time. obtaining a large about of data and in real-time can be very valuable for managing different sectors of the city. real-time data, analysis, visualization, and interpretation allow local governments and city planners to make smart and intelligent decisions regarding smart energy, street and traffic lights, grid, mobility, transport, safety, education, planning, healthcare, smart governance, and buildings at different scales (bibri & krogstie, 2017) with the aid of operational dashboards. ict provide smart solutions that improve community management and improve the lives of citizens (bibri, krogstie, et al., 2017), by being able to connect urban systems, reducing redundancy in operations, services, and facilities, and performance enhancement through effective integration and coordination of tasks using smart solutions. the ability of numerous cities to address complex problems to make the community smart and prosperous has primarily been attributed to progress in ict as a strategy to address the concerns and meet the urban development needs of the citizens (nam & theresa. 2011, angelidou, 2014). although at its infancy stage, there is considerable potential to improve smart city services with big data analytics (batty et al., 2012, al nuaimi et al., 2015, hashem et al., 2016), with colossal datasets currently being generated from computers, sensors, smart-phones, global positioning systems, cameras, social networking sites, commercial transactions etc. the continuous growth of these data sets prompted the development of data analytics platforms for storing and processing of the data generated to provide meaningful information (marr, 2015, hashem et al., 2016, ibrahim et al., 2016), which has been made possible through cloud computing and iot technologies (gretzel et al., 2015). with big data, the smart city retains spatial intelligence (gruen, 2013, gilfoyle & peter, 2016), where geospatial technology is used for information, cognitive processes, and problemsolving, through collective knowledge with real-time alerts, learning, and forecasting (gruen, 2013, consoli et al., 2017). the use of geospatial information science in the smart city has already transformed several cities at a more efficient management level. through the application of gis-based visualizations in smart cities, citizens are offered interactive and easy-to-use platforms by way of flexible devices and software applications based on modern technologies in the realization of the intelligent environment vision (hashem et al., 2016). this study aimed to use real-time spatial analytics that integrates state–of–the art ict approaches in current and future planning practices using an operational dashboard which presents a detailed analysis, critical evaluation, and interdisciplinary synthesis for smart solution making process across different sectors of the community. we also intend to show the vital role geospatial science has in providing real measures for data collection, processing, analysis, and representation with operational dashboard for a smart city operation mamgememt like for safety, health and emergency preparedness. our motivation behind this paper is because of advances in geospatial technologies and spatial thinking, the interdisciplinary nature of the concept of smart community, and the importance and relevance of the application of intelligent solutions to urban life. we show the significance of information technology in facilitating and shaping decision making in urban centers, and how they use of an integrated system can increase accessibility of information to better show how their cities work, allowing stakeholders to efficiently micro-manage the urban system with real-time data. the scientific contribution of this paper is the development of an integrated and innovative system that supports intelligent spatial decision-making justified by a data-centric system that uses real-time context-aware solutions to address the environmental concerns and socio-economic needs of the community. 2. method the growth of big data and the smart city has stimulated improvement and advancement of new intelligent applications (hashem et al., 2016). the use of big data for spatial intelligence for smart cites necessitates networks that connect all the components capable of conveying collected data from the sensing layer to the application layer and be able to process and transfer responses back to the different elements in the smart city that need them. this permits the sharing of information across platforms using a unified framework, attained through seamless, ubiquitous sensing, data analytics, and information representation using the combined structure of cloud computing to enrich different smart city services (gubbi et al., 2013, hashem et al., 2016). the focus of an intelligent community is applying next-generation information technology to all sectors of society, embedding sensors, and equipment in buildings, power grids, bridges, railways, dams, oil and gas pipelines, tunnels, roads, hospitals, water systems, and other universal objects, thereby forming the iot (su et al., 2011, al nuaimi et al., 2015, hashern et al., 2016). this era of iot has effortlessly connected sensors in the smart city environment leading to a more efficient and faster way of sharing information across different platforms (botta et al., 2014; chen et al., 2014; hashem et al., 2016). wireless communication adoptions is making iot become the revolutionary technology from all the prospects presented by the internet technology through which smart cities have been able to develop intelligent structures like smart homes, smart grids, smart water, smart retail, smart healthcare, smart energy and intelligent application of real-time gis analytics to support spatial-intelligent decision-making in the era of big data for smart cities eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e3 https://scholar.google.com/citations?user=ivfkokgaaaaj&hl=en&oi=sra 4 transportation (gubbi et al., 2013, hashem et al., 2016). the opportunities for the use of big data for geospatial intelligence in smart cities are boundless with the existence of innovative tools and technologies, and with the right tools and methods, proficient and competent data analysis embolden cooperation and communication between components of the smart city and can enable additional services and applications to boost the intelligent city (hashem et al., 2016). more smart towns/communities and other organizations are now using real-time gis to achieve operational cost savings and quality of life improvements. a real-time gis has made database management for solution-seeking necessary. the fast growth of the internet and the world wide web has also made it possible for several gis products to run on a web browser and through applications on mobile devices. we integrate a significant amount of data from several sources in a real-time application using geographic information systems (gis) widely used for mapping and analyzing spatial data, smart environmental monitoring, intelligent life, smart traffic, smart healthcare, smart public safety, and smart transportation, which until recently has been a challenge to accomplish (su et al., 2011, gubbi, & palaniswami, 2014). the integration of data from several sensors allows city planners to transform data into information, and this is very vital in decision making (hashem et al., 2016) in our technology and data-driven era. people have become increasingly connected through technology and smart devices, so for a city to communicate with the people within it; the city will have to adapt to address their needs and wants. gis data can be crowdsourced or generated in real-time by citizens, thus providing a more accurate picture of the urban system and allowing for quicker response times. our approach includes a cloud-based system made up of passive sensors, participatory information, and communication networks to collect and diffuse data to and from the sensor layer to the application layer and vice versa (figure 1). smart city architecture is diverse (wenge et al., 2014), the approach we adopt here has a four-layer architecture (liu &peng, 2014), made of sensing or data acquisition layer, communication or transmission layer, data storage, processing and visualization layer, and the application or service layer (figure 1). the sensing layer collects massive amounts of data through a set of iot nodes across an urban area about various activities in the physical environment and provides data to data hubs in the data layer. data obtained through these sensors can assist several segments of the city by delivering an improved consumer experience and service, and this can lead to increased performance in businesses (ostrom et al., 2010, dinh hoang t et al., 2011, hashem et al., 2016). the several billion iot nodes spread across every smart city system make it possible for data transfer from one sector of the community to the other, necessitating vigorous communication technology to handle a tremendous amount of data traffic. the data transmission layer guides the end to end communication services with the smart city layered architecture by transmitting data from the sensor and transport networks (gubbi et al., 2013, liu & peng, 2014, wenge et al., 2014). the collected data needs data storage, processing, and visualization before it can be disseminated to citizens and the stakeholders for smart decision making. intelligent data processing and mining are quite essential at this stage to reveal hidden and unknown valuable information (wenge et al., 2014). with the assistance of iot, it is nor possible for effective city management with systematically organized data, with data connected to the different data servers that are set to process different predictive, descriptive and statistical decision models help the city government to take proactive and data-driven decisions (nam & pardo, 2014, gil et al., 2016, molina-solana et al., 2017). the processed, visualized and stored data, need to be used to for intelligent solutions by combining the synergy of information technology and industry-specialized technology (liu & peng, 2014). this data can be managed through an operation center for the cross-department, where various sectors of the city like energy, health care, transportation, city government, police department, etc, can use in sharing information through web portals/mobile applications built on this layer. when a subset of the data is provided to the general public, services can be developed through crowdsourcing to enhance the operations of the city and influence the political, social, economic, and environmental needs of the community. the architecture (figure 1) used in our study exploits large amounts of data and information from different sectors of the smart city like home, health, and environment domain, and knowledge extraction (gubbi et al., 2013, gaur et al., 2015, suciu et al., 2015, gil et al., 2016). a real-time gis is applied to combine sensors from the environment and home aimed at efficient, transparent,sustainable, and intelligent community management, driven by ict and rendering a visual framework through an operational dashboard (shin’ichi, & roussos. 2016). figure 1. the architecture of the smart city and big data technologies adopted from ogc (2014). mbongowo j. mbuh et al. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e3 5 the real-time application integrates all the sectors of the smart city in the architectural framework, including smart environment, smart transportation, smart residential buildings, intelligent energy, smart health, smart security, smart services, and smart outcomes/policymaking. as demonstrated in figure 1, each of the smart city domains delivers the primary data source for the generation of various information required for intelligent decision making. satellite network is used in conjunction with smartphones, gps devices, and the use of the internet for pcs and other navigation devices for raw data collection with the aid of semantic web technologies, processing and analyzing the data in real-time (gubbi et al., 2013, gaur et al., 2015). the architecture provided by web technologies and gis offers an integrated cross-sectional platform to assemble, manage, gather, analyze and visualize spatiotemporal data for sustainable city planning, development, and management. the healthcare sector has generated a vast quantity of data in the past decade (chen et al., 2012; demirkan, 2013), with rapid worldwide population growth creating changes in how health services are made accessible to a majority of the population. with practical tools, both professionals and the general public can quickly have access to data and make treatment decisions based on available data and services offered. ease of access to information results in a faster rate at which an epidemic can be cured and prevented from spreading, thanks to spatial intelligent gadgets associated with dashboards that aid in monitoring services provided in the community. in an attempt to make the community healthier, offer greater access, efficient care, and increase the availability of health resources, we configured a health resource inventory that can be used by health and human services for an inventory of alternative medicine, drug drop off, drug treatment, health and social services, homeless services, hospitals and clinics, and mental health services in the community. the app can be configured to work both on the web and mobile devices can also be used as a remedy for substance use and mental health resource inventory. this inventory of health resources uses web appbuilder by arcgis, which provides a foundation for location-based application accessibility. this application can be used by the general public to locate health and human services in a designated area (esri, 2018). the health resource variables for this paper will include the locations of substance abuse treatment facilities, drug drop-off locators, mental health facilities, and homeless/emergency shelter services. one area where smart city strategies could prove beneficial is emergency preparedness. with the concentration of activity in cities, it is essential to have procedures in place in the case of an emergency and make sure people are educated on what action they should take. however, to gauge the knowledge and preparedness of the population, there needs to be a way of intelligently surveying residents and analyzing their responses. therefore, in keeping with the smart city concept, one of the objectives of this study was to develop a locationbased emergency preparedness survey for the city of grand forks, north dakota, using survey123 for arcgis (mantas et al., 2017). the application use esri’s survey123 for arcgis (kolvoord et al., 2017), which is a form-centric data gathering platform for intuitive and straightforward creating, sharing, and analyzing surveys (law 2017). the esri product enables the adoption of a citizen science approach (newman et al., 2010) through participation gis, using the public to gather data so that city officials can better assist the community’s preparedness for floods and winter storms. the survey was designed to collect an assortment of information from each respondent. in the state of north dakota, the two most prominent severe weather events for which people must be prepared are flooding and winter storms. some emergency preparedness principles apply to any disaster, while other disaster types may require specific steps to be taken, thus making it essential to take a multi-hazard approach (komendantova et al., 2014). by questioning residents about the condition of their residence, the items they have on hand, and their knowledge of emergency response, all while considering different hazard types, this survey can more efficiently help the community prepare for disasters like blizzards and floods. to respond to the needs of smart city management, we developed and deployed a solution that combines information from various sectors of the city using survey123 for arcgis to collect data, and displayed on an operational dashboard with multiple visualizations for real-time monitoring of people, services, assets and analysis of events or activities. the survey asks for their location (which gives the data spatial attributes that allow it to be mapped), includes questions about the characteristics of their home and household, a series of safety checks to assess their emergency preparedness, and a list of items that they should have on hand. the survey questions were developed by consulting literature from the federal emergency management agency’s ready campaign (ready 2018), the american red cross (red cross 2018), and the centers for disease control and prevention’s disaster resources (cdc 2018). survey123 has a variety of built-in tools for designing the survey (figure 2), including different question types such as single and multiple-choice and text and number entries. the survey also incorporates conditional questions, where specific items will only appear if accurate answers are chosen in previous questions. additionally, the survey also includes the option for the participant to upload a photo of their residence as shown in link below. https://survey123.arcgis.com/share/92dd674e577e49c28dfaa568 acac3969 once the survey is created, it can be filled out by anyone through a web browser on a computer or mobile device. additionally, the survey can be downloaded to the survey123 field app, where inquiries can be completed offline and then submitted later. as the data is collected, it can be analyzed by the survey creator. various charts, tables, and histograms for each of the questions can be application of real-time gis analytics to support spatial-intelligent decision-making in the era of big data for smart cities eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e3 https://survey123.arcgis.com/share/92dd674e577e49c28dfaa568acac3969 https://survey123.arcgis.com/share/92dd674e577e49c28dfaa568acac3969 6 viewed, and the data can be queried by date. the data can also be displayed on a map with survey answers tied to the user-selected locations. opening the data in the arcgis online map viewer enables changes to be made to the data’s symbology and pop-ups, and the map can then be shared as a web app from link below. http://nodak.maps.arcgis.com/home/webmap/viewer.html?useex isting=1&panel=gallery&suggestfield=true&layers=979973e21 39342b3bdca4724c72bcc7c we also use an operations dashboard to monitor realtime incidents through the integration of maps and customized widgets. the operations dashboard allows for quick decision making and accurate visualization of situations as they occur. the first step in creating an operations dashboard for emergency management services (goh et al., 2013, lee et al., 2015) in grand forks was to assemble data for fire stations, police stations, hospital, and clinic locations, emergency shelters, a police call log, and ambulance incidents. these files contained information such as name, address, hours of operation, and phone numbers. this data also included accident and ems call logs. using arcgis online the layers were individually edited with their unique symbology for local governments to represent the service locations (esri, 2018). the police and ambulance incident layers were enabled with editing and syncing capabilities, so police and ems personnel could enter data in real-time in the field. this function creates direct communication between the field and the office, and both sides can see the same visualization (esri, 2012). these layers were also set to “within the organization” so they could only be edited internally. this would ensure no outside people could interfere by modifying or deleting information. the incident layer’s editing and syncing capabilities also allowed the map to be used in apps such as collector, so workers could easily download the map and use it in places without network connectivity. by doing this, it would ensure data uniformity and efficiency in reporting information. the app included fields such as date, time, address, call nature, and incident status. all officers and ems personnel would have the same or a similar form, and there would be no discrepancies in how they entered information. for instance, a dropdown list could be created for the call nature, and they could select from a pre-determined agenda. as far as the general public, they could still have access to the map to see the locations of emergency services and incidents, but they would not be able to enter or edit any information. all data layers were imported into a web map viewer using an appropriate base map to allow users to identify surrounding buildings and streets as viewed on the link of a web map showing all the customized layers with unique symbology http://arcg.is/8a9ir from this point, “create an operations dashboard” was selected from the menu and automatically created with a default template. all the features on the map can be clicked on and will display a pop-up. the pop-ups for the service locations show information the public might need to know, like phone numbers or websites. the pop-ups for the incidents will display information entered in the field (esri, 2017). the header and sideboards were customized with different colors and titles. several widgets were also created, which were relevant to emergency management in real-time. the first was the “indicator” widget, which showed the number of total ems and police incidents. this number would go up or down in real-time, so emergency personnel or dispatchers could know how many full episodes were out there or how many required a response (esri, 2017). it could also possibly be used to show the total amount of time emergency personnel are taking to respond to incidents (esri, 2017). the color selections corresponded to the color in the symbology, so these would stand out and be easily understood. an icon for the police and ems were added, too, for precise identification. next, the “gauge” widget was created. the gauge widget can be used to display a value that is above or below a threshold (esri, 2017). in this instance, the gauge shows the number of incidents that are currently open. it is colored green as this is the color people typically associate with “open.” once it reaches the threshold, the gauge will turn red, and a warning will appear. as stated previously, this was a dummy number only used as an example. the indicator might also be created for emergencies to show how many people are hurt or how many people have been relocated to shelters (esri, 2017). a “bar graph” widget was also added to display multiple attributes of data as well as counts. in this case, the “call nature” field was selected to view the different types of incidents, and the total number is occurring. these include events such as accidents, suspicious activity, burglary, traffic stops, etc. in emergencies, personnel in the field and the office might need to know the types of incidents that are occurring, so they could visualize and understand patterns more easily (esri 2017). by doing this, they could identify which events require the most resources or are higher priority. the bar can be easily shifted up or down for a bigger or smaller view. finally, the “legend” widget was created, so anyone seeing the map could identify all the necessary symbols (esri 2017). they would not have to take time trying to figure out what a symbol meant or why it was included. the symbols were pre-determined based on the settings of the layers. the legend can disappear by sliding it to the left if it is not needed at any point in time. operations dashboard of emergency management services in grand forks, nd http://nodak.maps.arcgis.com/apps/opsdashboard/index.html#/0 62bb64a120d49ae81948106e463d94a the geo-enabled dynamic dashboard application provides the ability to access, query, and display real-time motion, improving situational awareness for at a glance decision making when shared with relevant city officials and the community and made available for desktop and mobile devices. 3. results application of real-time gis in smart cities mbongowo j. mbuh et al. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e3 http://nodak.maps.arcgis.com/home/webmap/viewer.html?useexisting=1&panel=gallery&suggestfield=true&layers=979973e2139342b3bdca4724c72bcc7c http://nodak.maps.arcgis.com/home/webmap/viewer.html?useexisting=1&panel=gallery&suggestfield=true&layers=979973e2139342b3bdca4724c72bcc7c http://nodak.maps.arcgis.com/home/webmap/viewer.html?useexisting=1&panel=gallery&suggestfield=true&layers=979973e2139342b3bdca4724c72bcc7c http://arcg.is/8a9ir http://nodak.maps.arcgis.com/apps/opsdashboard/index.html#/062bb64a120d49ae81948106e463d94a http://nodak.maps.arcgis.com/apps/opsdashboard/index.html#/062bb64a120d49ae81948106e463d94a 7 there is an abundant variety of smart city frameworks that have been established to facilitate the assessment and development of cities(bibri & krogstie, 2017). smart cities have been classified using six dimensions of urban life, namely smart economy (industry), smart governance (e-democracy), smart environment (efficiency & sustainability), smart mobility (logistics & infrastructures), smart living (security & quality) and intelligent people (education) (lombardi et al., 2012). these six dimensions are used in smart cities, with each using a set of factors to evaluate its success and make determinations on how to improve(lombardi et al., 2012; albino et al., 2015, bibri & krogstie, 2017). the framework adopted for this study uses the dimensions of safe, well-run, livable, healthy, prosperous, and sustainable by using gis to connect the community and combine crowdsourced information to assess all the systems of the smart city and build a friendly and livable city. 3.1. healthy city – health resource inventory the enrichment of life in a community starts with the health of the community. using real-time operations to integrate medical information and treatment facilities ensures fast, accurate, and consistent healthcare information across the district. this real-time application can also be used by the city to identify the right services that meet their health needs and safeguard that the best treatment and assistance is provided. the tool is tailored to allow the general public and the department of human services to crowdsource information for resource managers and the general public on the location of healthrelated facilities. one area where such an inventory can be very fruitful to provide information to the population is in battling the ‘substance use disorder’ (sud) ravaging our communities. the substances incorporated will include; tobacco, alcohol, cannabis (marijuana), stimulants, hallucinogens, and opioids (samhsa, 2015), as each of the treatment facilities in this health resource application treats clients with any one or more of the substances mentioned above. the consequences of substance use take an enormous toll on our nation. the combined healthcare, crimerelated, and productivity costs of substance use exceed $700 billion a year (nih, 2017), but the dollar amount does not approximate the overwhelming human toll of substance use disorders (national institue of drug abuse, 2017). the prevalence of substance use disorders has been documented as a significant public health burden and safety issue throughout the united states (u.s.) in recent years (hedegaard h, 2017). as of 2016, the average life expectancy in the u.s. has decreased for the second consecutive year (reidhead, 2018). substance use-related deaths, particularly deaths caused by overdoses are now the leading cause of accidental death in the u.s. (asam, 2016), with more than 115 individuals dying of an overdose on opioids every day (nih, 2018). reports show that sales, substance use disorder admissions treatment related to prescription and non-prescription opioid use as well as overdose death rates have simultaneously increased from 1999 to 2015 (asam, 2016). deaths related to a drug overdose in the united states in 2015 was 2.5 times more than the rate in 1999 (6.1 per 100,000) (centers for disease control and prevention (cdc), 2017). substance use disorders render complex and “continuously emerging challenges” that can be witnessed throughout the ongoing epidemic of prescription opioid substance use disorders in our nation (nih, 2018). furthermore, this epidemic is now contributing to a rise in heroin use as well as a rise in hepatitis c virus (hcv) and human immunodeficiency virus (hiv) outbreaks by the use of new drug delivery systems (national institue of drug abuse, 2017). substance abuse is often connected with homelessness and in a significant amount of cases, is both a cause and a consequence of homelessness, as substance use disorders often disrupt relationships with family and friends, as well as cause an individual to lose their employment. for these individuals who struggle with the financial obligations of bill paying, the exacerbation of a substance use disorder may ultimately cause them to lose their housing (national coalition for the homeless, 2009). for those struggling with substance use, mental illness can also be an issue. as of 2014, a reported 7.9 million adults struggled with both substance use and mental illness, side effects from drugs have been detected to cause mental illness symptoms in some cases as well (screening for mental health (smh), 2016). to examine an individual’s willingness to access available resources with specific demographic areas, a study by beardsley (2003), considered the association between approximate distance traveled to treatment, and treatment completion and length of stay, for 1,735 clients attending outpatient therapy in an urban area. the study found that clients who went less than one mile to participate in substance abuse treatment programs were 50 percent more likely to complete the program than those who moved more than one mile. they also found that clients who lived more than four miles away from a program were significantly more likely to have shorter lengths of stay in treatment than clients who traveled less than one mile. the considered factor is the distance from one’s home to the closest drug treatment center (in minutes); and the number of treatment services within a 10-minute range of driving from one’s home (nallamothu et al., 2006, kao et al., 2014, donohoe et al., 2016). locations of substance abuse treatment facilities, drug drop-off locators, mental health facilities, and homeless/ emergency shelter services icons. http://nodak.maps.arcgis.com/apps/webappviewer/index.h tml?id=f0c3bb7ce6f7490493c549a4e5513fa4 within each variable, a subset of additional information could be added, which would then appear in the pop-ups when a variable icon is clicked; an example is illustrated in link below:substance use health resource inventory app. additional information in pop-ups application of real-time gis analytics to support spatial-intelligent decision-making in the era of big data for smart cities eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e3 http://nodak.maps.arcgis.com/apps/webappviewer/index.html?id=f0c3bb7ce6f7490493c549a4e5513fa4 http://nodak.maps.arcgis.com/apps/webappviewer/index.html?id=f0c3bb7ce6f7490493c549a4e5513fa4 8 http://nodak.maps.arcgis.com/apps/webappviewer/index.h tml?id=f0c3bb7ce6f7490493c549a4e5513fa4 this health inventory allows the health department and community to have real-time access to health-related facilities and will enable patients to quickly and efficiently pick the facilities that meet their health needs. the local government can also use this information for a quick count of available services in the community. this reliable means of data transfer results in smart management and service and can help solve the problem of regional development inequality. by integrating data sharing and visualization for the general public, a serviceoriented government that promotes stability and harmony can be built (nam & pardo, 2011; de jong et al., 2015). smart health for a community also includes a system that is set up to manage emergencies and improve the safety of the city with other intelligent applications. 3.2. safe city – emergency preparedness here we develop a multi-hazard approach (komendantova et al., 2014) to efficiently help the community prepare for disasters like blizzards and floods by incorporating physical and social elements of the community to help the city adequately prepare for a catastrophe. using survey123 for arcgis, we adopted a citizen science approach (newman et al., 2010) through participation gis, where questions were used to assess the community’s preparedness for floods and blizzard. the survey would get the participant’s name and location and include questions about the characteristics of their home and household, a series of safety checks to assess their emergency preparedness, and a list of items that they should have on hand. the results show that survey123 for arcgis provides an easy way to design and administer surveys, which could be a useful tool for implementing public participation data collection in the development of a smart city. beyond emergency preparedness, these tools could be used to gather data about streets in need of repair, city assets that require maintenance, or users of different amenities. the completed survey was shared to make it publicly accessible, and it can be found at the following link: https://survey123.arcgis.com/share/92dd674e577e49c28df aa568acac3969 the survey includes 31 questions, with most about general emergency preparedness but also some that specifically address flooding and winter storm preparedness. the investigation would primarily be completed through a web browser, although it can also be downloaded to the survey123 field app for offline data collection. participants go through the easy to use interface and answer the straightforward questions from links below: the user interface for the survey. https://survey123.arcgis.com/share/92dd674e577e49c28df aa568acac3969 https://survey123.arcgis.com/share/92dd674e577e49c2 8dfaa568acac3969 the survey application could provide city officials with information about the preparedness of their citizens, revealing the effectiveness of public education initiatives. if there are specific questions where the responses indicate a lack of readiness, officials can tailor their programs and public education efforts to try to address those shortcomings. additionally, the location component of the survey could help inform which areas of the city are most prepared, and that can then be compared to which areas are most vulnerable to emergencies. it could also be used to inform where response efforts should be focused on the event of an emergency. overall, the survey’s usefulness is its ability to gather standardized data about the preparedness of a city’s residents in an efficient manner. this scenario provides a benefit to both citizens and government officials. those who take the survey become more aware of their level of preparedness and any areas where they may need to improve, while officials gain a sense of how well educated their citizens are and what areas may require better engagement with the public. the real-time data transmission using surveys completed in the field also has offline working capabilities, and anytime internet service is available, information entered in the form can be transmitted and viewed by stakeholders or the general population immediately. this real-time information is accompanied with customized operational dashboards to help filter information and provided the most relevant feedback for operation management 3.3. safe city – emergency preparedness the use of an operations dashboard and mobile application are useful tools that can be used in emergency management. the operations dashboard customized with a multitude of widgets enables ease of access to information. for dispatchers, this is essential because they can see everything on one screen. they can see what is happening without having to call and get an update from people in the field. they can more appropriately direct police or ems based on what they see. the mobile application can also be used when there is no wi-fi and updated when a connection is available. this is also great because personnel can still enter information electronically when they are in remote locations. the form will also alleviate the issue of people entering different types of information. with the use of dropdowns, people can enter a pre-determined set of data. if they choose to download the data as tables, all the data will be the same, and they will not have to perform extensive cleanup of data. this will also make their job less tedious and eliminate costs as well as the security of knowing they will be presenting the most accurate data possible. not only do these tools provide the ability to see information updated in real-time, but more extensive analysis can be performed. personnel could use the information presented on the map and might even be able to conduct quick hot spot analysis. this would help them mbongowo j. mbuh et al. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e3 http://nodak.maps.arcgis.com/apps/webappviewer/index.html?id=f0c3bb7ce6f7490493c549a4e5513fa4 http://nodak.maps.arcgis.com/apps/webappviewer/index.html?id=f0c3bb7ce6f7490493c549a4e5513fa4 https://survey123.arcgis.com/share/92dd674e577e49c28dfaa568acac3969 https://survey123.arcgis.com/share/92dd674e577e49c28dfaa568acac3969 https://survey123.arcgis.com/share/92dd674e577e49c28dfaa568acac3969 https://survey123.arcgis.com/share/92dd674e577e49c28dfaa568acac3969 https://survey123.arcgis.com/share/92dd674e577e49c28dfaa568acac3969 https://survey123.arcgis.com/share/92dd674e577e49c28dfaa568acac3969 9 identify critical areas where lots of incidents are occurring or where a particular type of event is more frequent. they might even be able to take this data and find out which time of day or day of the week most incidents are occurring. all of this would allow them to move resources more efficiently. officers could patrol those areas more frequently, or perhaps a city program is needed to try and combat whatever incident continues to be an issue in a particular area. this will aid in better city decision making. this will be the most cost-effective way for the city to deal with problems. they can have all their information and data stored in one place. not only that, but cities do not necessarily have to hire a person with extensive geographic knowledge as much of arcgis online contains basic operations. there are numerous ways to customize an operations dashboard or mobile app to fit a specific situation, but this was one example of how gis is making cities smarter. 4. discussion substance use disorders have increasingly become a significant public health burden and a safety issue throughout the united states. although the potential relationship between spatial accessibility of resource utilization is relatively new, the introduction of geographic information systems (gis) has now given researchers a broader range of spatial tools to assist in the analysis of individual health and behavior in their proximal environments. in the findings, studies have indicated mixed results of increased and decreased treatment adherence in correspondence to spatial availability, and the impact on resource spatial availability and substance use is not entirely clear. a substance use service that individuals can afford is culturally relevant and is in a demographic area that has higher rates of substance use that may play an essential role in promoting a change in an individual’s potential willingness to participate in a spatially available resource. since it is accepted that data is vital in planning treatment and prevention efforts for substance use, it should be incorporated at all levels of planning. the app creation, using arcgis pro and arcgis appbuilder was quick, simple and self-explanatory to use. our first objective aimed at examining the potential impact of spatial accessibility to the identified resources (e.g., substance use treatment facilities, prescription drug-drop offs, mental health facilities, and homelessness service) and how would they affect an individual’s willingness to access these readily available resources within specific demographic areas. to address the spatial accessibility, we developed a health resource inventory application for mobile devices for the grand forks, nd area. the environmental framework of substance use disorder is beyond complex and requires a multilevel and ecological perspective, not to mention, access to substance use disorder services is a multidimensional issue in itself (kao et al., 2014). according to kao et al. (2014), spatial accessibility focuses on the geographic location of services and its potential effects on an individual’s ability or willingness to access services. with the introduction of geographic information systems (gis) and similar technologies, researchers now have access to a range of spatial tools to assist in the analysis of individual health and behavior of their proximal environments. although the influence of geography and other environmental factors on the treatment of substance use disorders is still relatively new, the analysis of sud treatment locations and the use of gis to better understand and respond to substance use disorders has been a topic for ongoing research (kao et al., 2014). to attain our second objective which consisted of the development of an emergency preparedness survey using survey123 for arcgis, we showed survey123 and its different applications has the potential to be an alternative to collector, with the critical difference being that collector is a map-centric mobile data collection application while survey123 is a formcentric. survey123 is still location-based, with each survey response tied to a user-specified location, but the form-style layout can be more intuitive to members of the general public. survey123 can be accessed through a web browser or can be loaded onto an app for offline data collection. this can be particularly useful for field operations where network connectivity may not be guaranteed. when survey123 is used on a mobile device, the device’s gps coordinates can be used to automatically record the location, streamlining data collection, and acting as an easy way to track study area coverage, thus reducing sample duplication (andrade et al. 2017). survey123 has the potential to replace traditional clipboard and paper data collection with smartphones and surveys (hathaway 2018). this is another benefit of using survey123, as it standardizes data collection and allows the collection and analysis to be completed more quickly and efficiently (andrade et al., 2017). with survey123 field operations can integrate gis for a wide variety of applications (hathaway 2018). some examples include monitoring of immunization programs in developing nations (kakakhan et al., 2016), damage assessment following a disaster event (hathaway 2018), and in this project, it was used to address preparedness for floods and winter storms. while survey123 is not revolutionary or overly complicated, its simplicity and usefulness make it applicable to almost any field. its usefulness was demonstrated by the development of an emergency preparedness survey for the city of grand forks, north dakota. survey123 provides a simple yet powerful way to design and administer surveys and can be a useful tool for implementing public participation data collection in the development of a smart city. beyond the example of emergency preparedness, these tools could be used to gather data about streets in need of repair, city assets that require maintenance, or users of different amenities. utilizing technologies like survey123 for data collection can inform and improve decision-making, thus furthering smart city goals (kakakhan et al., 2016). application of real-time gis analytics to support spatial-intelligent decision-making in the era of big data for smart cities eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e3 10 there exist significant challenges with the implementation of current smart city approaches to sustainable development goals for the city (bibri & krogstie 2017). these challenges stem from difficulties, inadequacies, misunderstandings, and connections between smart, sustainable towns and cities’ concepts about management, operation, and urban system planning (marcuse, 2009; batty et al., 2012; lee et al., 2014; bibri & krogstie 2016). it is vital for each sector of the city to understand how they relate to each other in a smart city concept where, for example, there is an integration of hospital, accident, and emergency data about the place of violent crime to help law enforcement focus their patrolling approach. such strategy results in rapid response where the police could use the currently provided data to be present at violent crime scenes much quicker to prevent violence from escalating. using a smart city approach, the citizen receives better information and can make a better judgment on which decision to take regularly from real-time data. with real-time data, emergency managers and responders share a standard view of the state of affairs and can make better decisions together with other agencies responding to the same event. 5. conclusion cities will continue to expand, and emergencies will continue to happen. with a smart city management approach, cities can be more prepared for planning and responding to these incidents. cities can achieve faster response times and analyze on the spot. they can better allocate resources and time to the episodes which may be a higher priority. furthermore, they can enter information quickly, accurately, and uniformly even in intense situations. we aimed with this study to explore the use real-time spatial analytics with an operational dashboard for smart decision-making processes across different sectors of the community. we also intended to show the vital role geospatial science has in providing the theoretical context and real measures for data collection, processing, analysis, and representation. this paper is inspired by advances in geospatial technologies and spatial thinking, the interdisciplinary nature of the concept of smart community, and the importance and relevance of the application of intelligent solutions in urban life. the incorporation of data and technology in daily operations results in a safe, well-run, livable, healthy, prosperous city. using grand forks, north dakota as an example, we developed a health resource inventory, emergency preparedness scenario for natural disasters, and smart government response to public safety using an operational dashboard to monitor real-time data for city operations. to make the community smart and healthier, we built a health resource inventory that integrates medical information and treatment facilities of all kinds of illnesses with relevant information needed by city dwellers across the community in helping them make smart healthcare decisions. secondly, we used arcgis survey123 to efficiently gather standardized data about the preparedness of a city’s residents, which serves as a benefit to both citizens and government officials in natural disasters such as winter storms, blizzards, and floods. finally, to make the city government smarter, an emergency and non-emergency management app was created using an operational dashboard to help law enforcement and city managers manage operations in realtime. the dashboard shows updated information on incidents in real-time so personnel in the field and the office can better communicate. dispatchers will know the total events and types of activities occurring after they are entered, and emergency responders will be able to enter information on the fly. the public has a map with cohesive and integrated information all in one place, which could be particularly beneficial in an emergency. therefore, the use of information technology in smart city management provided real-time through different sensor networks plays a vital role and has excellent potential to produce more efficient decision-making in a community. the challenges facing intelligent cities have motivated researchers, developers, and decision-makers to work together and come up with new methods of restructuring and reorganizing municipalities through several spatial scales (nam & pardo, 2011). the goal of this approach to develop a more conclusive city model that accomplishes the requisite level of sustainability, particularly about incorporating its economic, social, cultural, and environmental dimensions. the use of innovative approaches to overcome challenges and issues facing cities of the 21st century require a real-time monitoring system that can be used for situational awareness, analysis, and city planning to aid smart decision and attain the vision of sustainability for urban operations. practical and intelligent decision making is vital for societal sustainability (yan et al., 2013; kitchin, 2014; zhuhadar et al., 2017). effective data management plays a crucial role in retrieving and using environmental information. management decisions that use data and technology require a means for real-time data retrieving and sharing. technology development has made sensors more intelligent, more efficient, cheaper and smaller (gubbi et al., 2013; jin et al., 2014; hashem et al., 2015). the potential of real-time gis has significantly evolved in the last decade. large amounts of real-time data are continuously collected; however, the value lies in the analysis and decision support that takes place afterward. one solution is using esri’s arcgis operational dashboard to integrate real-time data from many sources and compile and convert the input to an interactive tool for smart decision making. acknowledgements. we are thankful for the financial support provided through the north dakota atlas project (bradley rundquist) by the college of arts and sciences and the mbongowo j. mbuh et al. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e3 11 department of geographic and geographic information science. references [1] ageron, b., gunasekaran, a., & spalanzani, a. 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cazacu1,† and matthias rauterberg1 1department of industrial design, eindhoven university of technology eindhoven, the netherlands, 5612 az eindhoven abstract this paper explores the following research question: how to make the most of an academic community through norms, culture and practices within the academic environment? fifteen semi-structured interviews with stakeholders of the department of industrial design (id) from eindhoven university of technology (tu/e) have been conducted in a case study that aims to understand the approach knowledge workers have when navigating the university knowledge space to maximize benefits of their local community. thematic analysis has been performed and ten themes describing norms, culture and practices within the environment emerged. the findings indicate that the conditions needed to facilitate community building in the university are contextual planning, on-time rich information and serendipitous interaction. the paper expands the literature on university knowledge spaces by placing emphasis on community building and participatory communication in the context of smart city infrastructure. keywords: community building, academic community, knowledge space, knowledge worker, learning space, corporate real estate management, smart city infrastructure. received on 06 october 2019, accepted on 12 january 2020, published on 05 february 2020 copyright © 2020 silvia cazacu et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.5-2-2020.163044 1. introduction universities have expanded their role from educational centres of cities to focal points of the knowledge economy due to their increased connection to industry and private sectors [1]. however, many university campuses function in old-fashioned facilities that are unable to keep up with these fast societal changes; the vast majority of university buildings in europe are in a bad technical and functional state and date from the 1960s-1970s [2]. this situation creates many opportunities to develop better facilities into spaces that accommodate today’s knowledge workers students, staff and visitors [2, p. 167], as they make increasing use of new information and communication technologies (icts) and hold shared spaces in high demand [3]. * according to the building research establishment environmental assessment method [27] †corresponding author. email:s.cazacu@student.tue.nl the expectations of students regarding learning spaces have changed over the last decades: they require spaces that support both individual and collaborative activities, encourage informality and flexibility and put “a strong emphasis on social learning and advanced technology” [4, p. 140]. social learning is an important asset of university knowledge spaces because students develop creative thinking in social environments that foster learning through social interaction with peers and active guidance from teachers [5]. the knowledge economy requires professionals who have been trained in teamwork, cooperation and who care about others; for this, students nowadays must engage in selfassessing their own performance and be open to criticism, practice self-directed learning and reflective thinking. moreover, they must continuously adapt their learning style to engage in new practices that foster creativity and use new technologies for learning [6]. similarly, the large adoption of eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 http://creativecommons.org/licenses/by/3.0/ silvia cazacu and matthias rauterberg 2 icts has brought changes in the way people live and work; nowadays, workspaces must adapt to both remote and flexible work and offer possibilities to have fun, spark their employees’ creativity and make them feel at ease to express their feelings: “earlier the office used to be a place to work; now the office seems to have a more demanding role, as a place where people practically live, as well as work” [7, p. 333]. despite the large adoption of ict services by knowledge workers, universities require now (more than ever) the physical presence of both students and staff: while knowledge exchange can happen virtually, face to face communication and social interaction are vital to knowledge creation and innovative thinking [8]. by working together, learning from one another and engaging in creative and social activities within a shared place, university knowledge workers contribute to a knowledge space that is attractive, flexible, versatile and fosters trust, community and awareness [9]. communities provide a structural role for knowledge work by offering people direct access to knowledge and innovation and providing belongingness, influence, integration and emotional connections [10]. in this context where knowledge is being generated and exchanged daily by means of direct interactions between students, staff and visitors likewise, modern university knowledge spaces should encourage community related activities and behaviour to enhance knowledge work. according to tuulos [11] we can analyse how modern knowledge work is influenced by the design of the environment where it takes place if we consider its three components: physical space, mental space and social space. the physical space is represented by the designed construction and physical elements users recurrently interact with. as a result, they attach mental cues, rules and norms of behaviour which represent the intersection between their mental space with the physical one. a person’s mental space represents the user’s behaviour and state of mind which affect how they interact with the community and contribute to their ways of working, generating organizational culture and practices within that community. the social space in modern knowledge work is represented by the social interactions and community building activities that take place in the physical space, creating the environment of knowledge work. an overview of how the physical, mental and social space contribute to a knowledge space through a set of additional subcomponents – norms, culture and practices and environment is presented in figure 1, as featured by tuulos [11]. 1.1 norms the way people behave is impacted by the space where they engage in that behaviour. those with whom we use to share a space influence how we behave more than the people who are not as physically close, thus spatial proximity is an important factor in constructing social norms [12]. when we feel insecure of how to act in a certain space, we mimic other people’s behaviour to fulfil our need to assimilate, to feel part of a group [13]. a space that supports, guides and promotes positive behaviour will more likely contribute to activities beneficial for knowledge work. lastly, normative behaviour depends on a design that affords clear understanding of what is permitted and what is out of place [11]. when we are not familiar to what is expected of us in a certain place, we become disoriented and our whole experience in that environment suffers. figure 1. the components and subcomponents of an academic co-creation space, as presented by tuulos [11, p. 125] 1.2 culture and practices in the context of modern knowledge work, organizational culture determines work performance because the cultural context is connected to all aspects of work – knowledge creation, knowledge sharing and knowledge implementation [14]. bierly, kessler and christensen [15] define organizational wisdom as an important construct determining knowledge transfer and explain the importance of organizational culture in creating a wise organization: “the promotion of specific values that are in line with the strategic focus of one’s organization, for example creativity, quality or social responsibility, can significantly aid in the wise selection and translation of plans and objectives for organizational members” [15, p. 611]. in universities nowadays, knowledge creation and transfer have shifted from formal activities and rigid classroom environments towards informality and social interaction, direct experiences and real-life situations. the culture and practices that support a broader understanding of knowledge work which includes informal settings and community-oriented activities can increase people’s motivation to use a knowledge space [16]. 1.3 environment knowledge work calls for balance between social interactions and individual work time. to avoid cognitive overload caused eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 exploring opportunities for community building in atlas – the world’s most sustainable education building 3 by stress, increased workload and multitasking, workspaces should be designed to purposefully create conditions for awareness, collaboration and brief interaction without compromising personal space, concentration and privacy [17]. for students, the physical learning environment influences the learning process and they feel this influence later in life, even after the learning space is no longer part of their daily activities [18]. for nowadays learning spaces it is a substantial design challenge to provide an interactive learning experience comprised of place-bound knowledge creation through group engagement and enhanced, technology-mediated learning activities [19]. the integration of ict as an additional digital layer in learning spaces brings new affordances to this experience, as it encourages reflection, knowledge sharing, collaboration and flexibility [20]. the approach we take when we design a modern university knowledge space should take into consideration the type of behaviour it supports among users, the culture that it instils and the affordances for diverse knowledge related activities. this paper investigates the role of these three dimensions in creating enjoyable and easy-to-use spaces that respond to the complex needs of today’s knowledge workers in academia. the importance of this study lays in the paradox that most of nowadays ground-breaking work is conducted in outdated facilities that do not correspond to the needs of our modern society. this paper adds to the body of research concerning higher education spaces in relation to modern tendencies in knowledge work and brings a fresh perspective by deconstructing user experiences and expert insights into behavioural, social and environmental implications. the aim of this research is to explore the complexity of knowledge spaces in relation to modern day technological advancements and the consequences they have on academic knowledge work, by putting an emphasis on the people behind it. the study analyses the following research question: • how to make the most of an academic community through norms, culture and practices within the academic environment? the question is answered by investigating user experiences from a state-of-the art university knowledge space and combining them with expert insights involved in the process of accommodating the users from initial design to post-occupancy evaluation. the study uses a qualitative approach and analyses its findings by mapping them onto the framework proposed by tuulos [11], as shown in figure 1; in addition, we add digital space as an additional layer of the physical space component of this framework to reflect the latest trends in modern knowledge work where physical objects are often merged with digital technology. figure 2 presents the updated framework featuring the digital dimension of the space. in the next part of the paper we analyse a series of related studies which explore the balance between work-related tasks and community activities in different types of knowledge spaces. the setup of our study which analyses the academic knowledge space of the department of industrial design (id) of eindhoven university of technology (tu/e) is presented in the case study section together with the research methodology. next, our findings comprised of ten contextrich themes are thoroughly presented and are followed by a discussion where design recommendations for community building are proposed. finally, the paper concludes with a synthesis of the qualities necessary for an academic knowledge space to maximize benefits among users. within the scope of this research we explore how the combination of state-of-the-art icts and building infrastructure of the smart city can enable human capital and bring positive social change among users through purposeful design. therefore, we contribute to the theme of this journal by highlighting the implications of design decisions for creating liveable, inclusive and socially relevant spaces in the context of nowadays knowledge work. the study provides useful suggestions on supporting community building for corporate real estate management experts, as well as interaction designers, architects and planners. the study expands the literature on academic knowledge spaces by placing emphasis on community building in the contexts of hci and smart city infrastructure. figure 2. norms, culture & practices and environment that build an academic community space 2. related works as nowadays academic knowledge workers are becoming increasingly engaged in informal activities, social interaction and collaboration, university knowledge spaces have started to combine various features of collaborative work environments. we propose a series of related works that analyse user experiences in several types of workspaces focused on collaboration and fostering workplace community: coworking spaces, co-creation platforms, stateof-the-art office environments and collaborative makerspaces. tuulos [11] describes the environmental qualities that support knowledge work based on the impact they have on the knowledge community members. it presents the aalto design factory, a state-of-the-art university building eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 silvia cazacu and matthias rauterberg 4 designed for teaching, learning, research and industry cooperation, where social interaction and community building play an essential role in supporting experiential learning as pivotal part of knowledge work. the study utilizes a conceptual framework of analysis inspired by henri lefebvre’s triad of space which distinguishes between the local culture, attached norms and environment as key components of our surrounding space. on a similar note, nenonen analyses the balance between the “physical, social and virtual layers of spaces for knowledge creation” [21, p.237] necessary in nowadays knowledge work environments. the study shows that there are several types of spaces needed in different stages of knowledge work and that they typically enable explicit knowledge sharing but fail to support tacit knowledge exchange. such qualities can be easily met when the designed spaces carry some of the features accommodated by coworking spaces: networking with people from a variety of backgrounds, collaboration and individual work. bilandzic and foth [22] conduct an ethnographic research at the edge – a library space dedicated to coworking, social learning and collaboration through digital technologies to understand user behaviour and motivations. their study presents five personas that support and inform design strategies for spaces which foster shared learning and collaboration across physical and digital environments. likewise, sankari, peltokorpi and nenonen [9] investigate user experiences in higher education learning spaces to understand whether these could benefit from co-working principles. the results suggest that characteristics typically found in coworking spaces are positively experienced by users of academic spaces. these are community, multipurpose office design, high accessibility and workplace attractivity. windlinger, nenonen and airo [23] combine a qualitative interview study of an office relocation project in finland with a quantitative survey study of 43 office buildings in switzerland to explore workplace usability. they differentiate between usefulness and user-friendliness to provide a more accurate representation of office workers user experience. the findings show that this combination can be beneficial for the field of office management as usefulness refers to “workplace provisioning and workplace concepts as designed entities” while user-friendliness speaks about “user behaviour and the perception of comfort” [23, p. 660] both being valuable aspects to consider when designing usable office spaces. lastly, capdevila [24] analyzes 43 collaborative spaces from barcelona and paris in a qualitative study that explores user motivations to access such spaces. it provides a useful classification of different types of collaborative spaces where innovation, activity diversification, entrepreneurship, user participation and engagement are the main drives for maintaining user interest and commitment over time. these examples are only a few from an expanding domain of research into the qualities and design decisions behind collaborative spaces that support social interaction in modern knowledge work. they represent an increasingly popular tendency to bring forward spaces that are socially relevant, inclusive and connected to user needs for community. our paper adds to this body of research by investigating user experiences in a state-of-the-art facility for academic knowledge work through a qualitative study which provides deep insights into user behaviour, habits and perceptions of such a space. 3. case study: the tu/e department of industrial design move to atlas a unique opportunity to explore academic community building 3.1 research setting to achieve the goal of this research, we have taken advantage of a very rare opportunity to witness the first few months when an entire academic department moves its headquarters to a recently renovated facility. this building has been awarded the “world’s most sustainable university building” by the building research establishment environmental assessment method (breeam) [25]. we believe that this university unique setting combined with the timing of this study create the premises for a fresh perspective on community building for academic knowledge workers. the department of industrial design (id) from eindhoven university of technology (tu/e) has functioned since the inauguration at the beginning of the 2000s in the tu/e main building. this construction is comprised of 12 3400 sqm stories, out of which the id department has occupied 3 (and at times, 4). the building has been designed by the dutch architect van embden in a modernist style in the 1950s and was completed in the 1960s. at the moment of the tu/e industrial design inauguration, the building had already undergone a few renovation stages, but a major one only happened between 2013-2019. during this time, the department had been temporarily downgraded to a 2-storey office building (laplace) originating from the 1970s. laplace featured an open plan where all student spaces, laboratories and researchers’ offices have been organized around a central common area for both students and staff to share. although the allocated space was considerably smaller than the one in the main building, community thrived here around the central community space. at the beginning of 2019, id has moved back to the main building (now named atlas) which has undergone a complete renovation which only kept the initial concrete structure and the secondary circulation steel staircases from the old building. here, id shares facilities with another department – industrial engineering & innovation sciences (ie & is) and the university corporate facilities, following a scheme of vertical zoning. the two educational departments occupy together most of the building floor area from floor 2 to 9 and are located at the two extremities of the building floor plan, as shown in figure 3. the yellow area represents the id space, the blue area the ie & is space and the red area in the middle represents a transition space with classrooms, eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 5 informal work areas and meeting rooms used by both departments. as an additional feature, the red area is designed to afford flexibility and future reconfigurations within the two departments which can expand or contract according to the number of students and researchers they house. figure 3. a vertical section through the atlas building showing the main department areas the newly renovated building (atlas) represents the state-ofthe-art in sustainable university buildings as well as in community engagement policies [26] and has been awarded the breeam [27] award for the most sustainable education building. the renovation process of atlas is part of the tu/e campus strategic development masterplan (2010-2020) that proposes the transformation of a formerly closed and monofunctional campus into a broad ecosystem where education and research activities blend with business, cultural, recreational and residential activities [26]. following these principles, this building is considered a steppingstone into “the new way of working” (as translated from dutch by the authors), a strategy developed by the university to encourage multidisciplinary interactions, cohesion and collaboration amongst students and staff [26]. moreover, the building has been designed following principles of coworking [28]. the ambitions regarding building users – students, scientists and staff members for the academic space include cooperation, knowledge development and sharing and dynamism: “the working environment is closely interwoven with the educational environment. meandering through the educational landscape, scientists are in contact with students and science” [28, p. 9]. 3.2 method data collection the study builds on two main datasets emerging from user perspectives and experiences of the atlas building and expert opinions and strategies for community building within atlas and the department of industrial design. the first dataset stems from a diversity of data sources, comprising of 9 semistructured interviews and 15 qualitative questionnaires, participant observation of daily activities of different community members and a user generated map with preferred places for informal encounters. the questionnaires have been initially deployed to gain a rapid understanding of the workplace dynamic and to explore which questions trigger more in-depth responses. the survey contained 12 open questions about informal meeting preferences, meeting approach techniques, habits or cues employed by users. moreover, the questions asked about preferred types of information regarding other users, their availability and meeting preferences such as preferred time of the day, location and topic predilection. the survey has been deployed among bachelor, master, phd students and academic staff and after 15 responses we got enough information about the topics which require to be discussed more in depth. together with the daily observation and the user generated map, the survey pointed out that formal meeting habits must be taken into account as well because they contribute to the way users structure and access the informal interactions to fit in between work-related meetings. taking these into consideration, the semi-structured interviews have been designed around the following themes: • user interpretation of general rules for using the different locations and facilities of the department in relation to formal and informal meetings with other tu/e industrial design members; • user interpretation of common practices and tu/e industrial design organizational culture that contribute to the way members structure their schedule to fit community-related and work-related activities; • user experience and views on affordances of the physical and social environment for informal interactions and an enjoyable work atmosphere. given that the main researcher is a master student of the department of industrial design, the study has been continuously adapted to community life and data collection has been enriched with daily observation of culture and practices as well as community main events over a span of five months. the observations have been performed by the main researcher with the objective of understanding patterns, habits and behaviour in the different areas of the knowledge space and the recording method has been note-taking using a personal smartphone with a mobile application for notes. this comes with a study limitation as well because, although efforts have been made to avoid it, it builds the grounds for researcher bias. as bias cannot be entirely avoided when the person conducting the study is a user of the knowledge space as well, we trust that sufficient use of theory can help overcome this potential setback. the second dataset consists of 6 semi-structured interviews with experts on the tu/e industrial design academic community as well as the atlas design, renovation and moving process. first, to understand the discourse around the ambitions for the atlas building and implicitly for the tu/e department of industrial design, we interview three employees of the tu/e housing department: one communications adviser, the project manager of innovation @work, an initiative to introduce flexible working to the supporting staff working in the building (located in the upper floors) and the project manager of the recent atlas renovation. next, we interview the director of education for the department of industrial design and a lucid board member – the industrial design student association to get in depth knowledge about the strategies employed to encourage community building and social networking within the exploring opportunities for community building in atlas – the world’s most sustainable education building eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 silvia cazacu and matthias rauterberg 6 department and between the design department and other design communities. sampling in order to conduct expert interviews regarding the initial ambitions and ongoing strategies, we used the purposeful sampling technique. we identified people within the university who have experience with the atlas renovation and moving process, then we continued with those who work on establishing a working environment based on principles of coworking [29] and we ended with those who actively work on strengthening the industrial design community. we believe that after these meetings we have reached saturation on this part of the study. in order to explore how community members use and access the academic community, we approached members in different positions within this network: bachelor (bs##) and master students (ms##), phd candidates (pc##) and researchers (ap##). we used purposeful sampling for the first iteration which consists of a qualitative questionnaire followed by a second iteration with interviews which are a more in-depth version of the first. in the third iteration we look at finding people within the network who are recommended by others as paradigmatic (positive) cases [30] for the way they access and use the community network. because the department has a relatively small community, there were only 3 cases pointed out by other members and due to availability issues and the time limited nature of this student-led research, we interviewed 2 of them. regarding the user generated map with informal meeting spots, a poster containing an annotated floorplan has been placed on each of the 6 floors of the department shared by all categories of users. participants have placed stickers on the desired area over the span of two weeks. data analysis the data have been analysed qualitatively following a thematic analysis approach with guidelines provided by braun and clarke [31]. the approach explores shared topics and recurring ideas from participant stories as well as critical incidents or paradigmatic cases. the goal has not been to create a generalized image assumption built on everyday life moments, perceptions or community practices, but to paint a variegated picture of a specific academic context from which one can draw their own conclusion and build upon in further studies. the community member generated data from the openended questionnaire and following semi-structured interview have been used for identifying, analysing and reporting patterns that can be used to describe the reality of the tu/e industrial design academic community in rich detail. user reactions, stories, examples and remarks have been clustered in ten themes that describe the norms and practices within the academic environment which derive from the way a member utilizes the mental, social, physical and digital spaces in relation to their community. the user generated map has been used to clarify and shape a context for the analysis of the interviews and questionnaires. the expert discussions have represented a contrast agent in the classification process. we have operationalized the findings following the spatial triad theorized by the french philosopher henri lefebvre and interpreted in a contemporary approach by tuulos [11] which describes space as the combination of three components: social space, mental space and physical space. to the latter, we have added the digital space dimension to better describe modern knowledge spaces in the context of flexible working and the use of ict in many knowledge-work related tasks, as shown in figure 2. because the qualitative survey and the interview represent two iterations of the same data collection method, we have analysed their results collectively, as part of one user generated dataset. we have manually transcribed the previously recorded interviews and hand-written survey answers in an excel spreadsheet where each participant has received a unique code. the spreadsheet has been printed and the coding process has been done using analogue tools such as pen, paper, post-it notes following the method of braun and clarke [31]. ten themes emerged and are synthesized in a framework which can be further developed for other case studies and used to inform interaction design professionals and architects interested in hci, applications of icts in smart city infrastructure and participatory approaches to city making, community and facility managers likewise. a limitation of this study could be considered the analysis process done by one researcher due to time-constrains. however, we must take into account that the thematic analysis method used [31] specifically targets such cases through an exhaustive approach on all coding stages that builds on top of rich, accurate descriptions to generate the final themes. 4. findings table 1. 10 themes that describe the three components of the academic community theme no. spatial component theme name 1 norms cues and barriers for interaction 2 norms formal can lead to informal (and sometimes vice versa 3 norms strategies for planning formal meetings 4 culture & practices spontaneity as chance to practice skills, improve work performance & environment 5 culture & practices cultural differences 6 culture & practices peers flock together 7 environment limitations of the open space eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 7 8 environment opportunities in the open space 9 environment community building requires a community space 10 environment contextual planning & informed conversation starters figure 4. themes clustered following the three spatial components a total of 10 themes emerged from the thematic analysis, grouped around the three components that describe the academic community space: norms, culture, practices and environment, as previously shown in figure 2. an overview of the themes is presented in table 1, ordered by spatial component. each theme is individually explained in detail in the following section. figure 4 presents how the themes cluster following the three spatial components of the academic space: norms, culture & practices and environment. 4.1 cues and barriers for interaction members of the tu/e industrial design community proceed differently when they must approach other members: they “just sort of lean over and then…”, or they have indirect approaches such as “usually, i just send them an email”. they believe “sometimes context is important” and they prepare the meeting in advance: “i need to make an appointment instead of just going to the office” – ms#2 some rely on own assumptions about others’ availability “if the person is wearing headphones that is my cue to not disturb them”. some quickly assess the situation as they “look at how they are working: are they talking with other people or are they really into their laptop”. one member who is seen by others as a socially – connected individual (according to recommendations during interviews) has a high level of self-awareness as well as awareness of others and they make a constant effort to be perceived as an approachable person: “i actually look at them or try to remember what they do. so that goes for students it also goes from my colleagues. […] i think i’m quite approachable. i don’t have like a wall. or i don’t radiate any form of danger, i guess. or intimidation. which is good you know because it makes you quite approachable. […] i am very aware. […] i’m super alert.”ap#2. another person recounts that they look for generally accepted cues in the workplace culture that hint them towards other members’ availability for chat: “usually they are available, i think the universal sign for being at work is having headphones on or earbuds in.” ms#6 a member discloses that they rely on their personal interpretation of others’ behaviour, activity and state of mind before approaching someone else for a discussion: “when people want to chat, they look happy, they are eating, drinking, and not behind their computer, but elsewhere.”ms#5. location is considered an important factor in informal meetings, but also a deterrent depending on the activity that is linked to the location or the people who can be found there: “i feel like location is so specific. if i run into someone in the city, we are on neutral ground now so i am allowed to have dinner here and so are you and that wouldn’t make me feel awkward, but i am not going to go to a space that i feel is for the students and i feel they maybe feel the same way about walking over here because they feel it is for...”pc#1 exploring opportunities for community building in atlas – the world’s most sustainable education building eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 silvia cazacu and matthias rauterberg 8 similarly, elements of the physical environment such as doors, walls and furniture are being seen as barriers against other people who might interrupt one conducting focused work. people from neighbouring desks are perceived as a deterrent against interruptions as well: “i am just in my office if i do my own stuff. i think for many people is already quite the threshold to step into the room. and then there’s other people in the room too. so, i think there are plenty of barriers”ap#2. the lack of information about other members of the community can make people feel insecure and embarrassed to the point that they lose the initiative to approach others, one student explains: “honestly, i don’t know if i would initiate conversation. i also don’t know a lot of the staff; most people i have seen but i don’t know what squad they are in or projects they have so i feel kind of a bit of embarrassment of not knowing that, it would hold me back”-ms#1. furthermore, the absence of knowledge about others’ location and their availability on the spot can make these users reluctant to approach people for impromptu meetings: “often, i feel like even if i knew where someone’s desk is, i always feel like i don’t want to walk up and interrupt them. so, if in some ways i would know that this is an ok moment to approach, that would help a lot more and would happen more spontaneously.”-ms#1. lastly, one member reflects on their own experience of being interrupted from important work, which makes them doubt the legitimacy of their own actions: “it happened yesterday when i felt like talking to some people but then having these disturbance problems myself i asked myself <should i do that?> because they might be working on something very important, so it is give and take.”ap#1 4.2 formal can lead to informal (and sometimes vice versa) in relation to the way they access the tu/e industrial design community daily, members share that sometimes “you don’t know how to approach someone if you don’t have a specific reason”, or “honestly i don’t know if i would initiate conversation”. the opposite is equally true: “i think i met most of my teachers informally during breaks from the class”. their general opinion about the current social dynamic is that “there should be more interaction” while the recent atlas move created a situation where “i don’t talk to a selection of most of my colleagues anymore, let alone my students”. when they access their community, members need to establish formal ties before exploring informality. for staff members, this comes as a result of the organizational structure in the research groups which is enforced by everyday practices and embedded culture: “[about the people from another research group] – i know them less because we are not in the same labs, we don’t teach the same squads, so i have a little bit of less formal interactions with them.” (pc#1) students, on the other hand, explore informality gradually as they expand their social circle and do not necessarily consider the organizational structure, but the personal level of comfort around a particular person: “there would still be a difference between meeting a staff member i don’t know and meeting the squad teachers because i feel more comfortable around them, i know what kind of relationship some people have […] some people are informal, some are strictly business and it’s a bit hard to estimate how far you can go while with the students you can always be more casual.” -ms#1. informality stems from a strategy implemented by the tu/e industrial design community organization which aligns with the formal organizational structure of the department and is expressed by the floorplan layout distribution. according to the industrial design education director, the most interesting serendipitous encounters take place in the faculty’s labs and squad spaces as well as around the professors’ offices or desks because by design, these spaces attract people with similar projects, activities, interests. students consider that the opposite is similarly valid, because the squad spaces are determined first structurally by the people who are reunited by similar interests and then spatially by the area they occupy on a floor. “you kind of know what these people are doing, for example that’s why i’m in the x squad space because the people that work here are in the same topic or the same interest i am in.” (ms#4) 4.3 strategies for planning formal meetings members plan their formal meetings using a variety of methods to accommodate different meeting habits, schedules and personal preferences. some prefer finding their meeting partner somewhere in the building and talk to them in person or schedule in person a following meeting if necessary: “i just walk there and ask them a question; if they are busy, i ask when i can come back but that never happens.” bs#3 they rely on their social and spatial awareness to remember the details of every encounter: “i think i might come across as someone who does these things effortlessly, but i am very aware of everything i do at my job.”ap#2 some have a prolonged experience with the social culture and practices in the department: “i never send an email, i just go there; i think it is about studying here for 3 years already and i gained experience with this; my teacher coach never responded so i had to go and bother her.” – bs#2 others prefer more indirect approaches and utilize a variety of digital tools to launch and mediate both planned and quick, dynamic consultations. they use the tu/e outlook email service (“usually, i just send them an email and ask about t. with c., my coach i send an email and then eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 9 we schedule meetings on friday in general”-ms#1), slack [32] (“i like to work with digital tools slack, email is fine for many purposes especially when it comes to quick decisions.”ap#1), teams [33] (“with people that i don’t know, i would probably send an email before. i’d do the same with my colleagues. we use teams so when we meet on friday, i just leave a message if i want to talk for a bit”ms#1), wechat [34] (“we have this wechat group with all the chinese colleagues and ask who is for lunch and someone would always come.”ms#2), and the tu/e intranet service (“for the info about their expertise and stuff, i usually just check the website”-bs#3). there is a category of members who adjust their meeting approaches to the person they meet with or the type of meeting. they prefer combining a direct approach with the use of online direct messaging apps or email: “for my supervisor, i take these stairs right here, if i need a walk, i take the other route and then i go and find her. if she is not by her desk, i will text her or whatsapp her.” – pc#1 4.4 spontaneity as a chance to practice skills, improve work performance and environment when asked about the value they place on the time spent with other community members in brief, informal meetings, participants considered these “meaningful”, “like networking”, “very good”, “mutually benefitting”. students especially appreciate the opportunity to rehearse their “relationship building skills” or just to discuss new collaborations because informality can “lead to something else than just casual talk”. other students even notice that being part of a community can bring benefits over time because “a lot of people really helped me just from these small talks”. by having social interactions with other academic community members, the participants have experienced an increased social awareness and a better collaboration dynamic: “if i know the person better, i have a sense of how they might perform both professionally and in their personal life; they also get to know me. if you click, it is easier to get to work with someone. it can lead to something else than just casual talk.” ms#3 moreover, students appreciate the value that quick, unplanned meetings could have for testing their raw skills with the people who can provide expertise, council and guide them on their self-discovery journey. ”i think it would be really valuable (to have informal meetings) , it could help with relationship building skills but also in the department, because i don’t know everyone’s expertise […] and probably there are many more coaches than just the people from my squad who can give some good insight on my project or who i could talk to about my vision, my development or some questions i’m asking myself. “ms#1 for staff members on the other hand, time is a constraint which in many cases prevents them from accessing the community as much as they would because “usually, i don’t have time for that”, and “our time is super fragmented”. when they do find a window in their schedule to interact, it is “mostly with my colleagues that i sit with” and they “usually go to lunch together”. here, they might have “a discussion about the nature of design research” or “an interesting debate about the role of tu/e industrial design academia”. in such contexts, the informality brought by less constrained meetings creates opportunities to discuss organizational matters easily that bring about changes in the work environment. “i think a lot of the bottom up changes that happen in our faculty have their roots in informal meetings […] we started the x council because of discussions of phd students that were happening kind of informally and definitely they were about work-related things and culture here at the faculty and from that it grew a need.” pc#1 4.5 cultural differences according to a survey launched in november 2018 [35] the tu/e academic landscape is highly culturally diverse, comprising of 91 nationalities and the industrial design community is by no means an exception from it. although tu/e industrial design has a clear vertical organizational structure, the relations between community members are not bound by it. researchers and students work closely and sometimes collaborate on projects and students are encouraged to consider their teachers as mentors who guide and asses their progress, rather than their superiors. however, while this approach is aimed at encouraging proactive and independent learning, there are foreign students, especially the ones coming from asian countries who do not feel at ease within this context. in the context of community access and participation, one respondent explains how they sometimes feel inappropriate to the social context due to cultural differences: “in our culture if you talk to people older you should show respect but here people are more equal so it’s a bit weird when i talk to someone in a casual way and then i found they are a phd or professor”.ms#2 another person considers that cultural differences stand in the way of being proactive and approaching other members of the community: “from a place where we respect the seniors ...it’s really hard to approach them (academic staff); i feel i cannot really connect with them”. ms#4 on the other hand, there are people who turn cultural differences from boundaries that prevent community access to challenges they must overcome to become better social networkers: “i think maybe i have to cross some cultural barriers and talk with people from other cultures too.” – bs#2 exploring opportunities for community building in atlas – the world’s most sustainable education building eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 silvia cazacu and matthias rauterberg 10 4.6 peers flock together according to our respondents, both students and staff extend their work-related interactions to informal encounters by connecting preponderantly with their peers and direct social links. for example, during informal encounters they meet and “just catch up with a friend after vacation”. when asked to recount the last meaningful informal interaction they had with a community member, one student participant explained: “it was today with mostly people that i already know. people that walk by and see me sitting here and stop for small conversation or they have a problem that they want to talk about.” ms#5 for researchers, the situation is similar: “a colleague, he wanted to show me something and he showed me on his laptop. it was work related.” ap#2 the interactions they have, even the ones which happen in more relaxed circumstances, are on discussion topics that stem from the work environment: “during lunch today, with colleagues. we had an interesting debate about the role of tu/e industrial design academia.” -ap#1 one participant explained how collaborating on projects builds social relations that are fed by these repetitive activities and common goals fellow co-workers share: “mostly [i interact with] my colleagues that i sit with; there is 3 girls that we all started in the same year and going through the phases of trying to discover what a phd is and sort of getting the hang of it… we talk a lot firstly because we have a lot of the same work deliverables” – pc#1 similarly, another explains how sharing a specific space inside their work community daily forms bonds that extend over work-related activities: ” because we sit together, we usually go to lunch together and that becomes a more informal moment where we talk about more personal things.” – pc#1 4.7 limitations of the open space in relation to the floorplan layout from atlas, members describe it as “a very particular space very much unlike an office” where “there is so much going on”; they “don’t really like the open space to be honest” or “ have mixed feelings about the building” and a reason could be that they “ get disturbed by the professors talking there every day”. they consider that “in an open space you are easier approached” or that the current arrangement is “not in sync with how i typically like to use buildings” and they feel that the building “seems to have forgotten that people need to use it”. the user opinions and experiences regarding the use of space are variegated: they pendulate between anticipation regarding a newly founded community hub and an overarching sensitivity towards interruption from their work: “i feel like when i come to this building, i will probably meet people that i know, and you start talking and keep distracting yourself. so, if i want to do something with focus, i would go to metaforum because i am less likely to meet people i know.”ms#1 some blame the difficulty to concentrate on the inherent usage norms that come along with a typical open space, and not the users who employ them inappropriately in this context. “first of all, you need to know that i am sitting in the open space; this is a very particular space very much unlike an office; so, my assumption is that people feel that < he is sitting there, it is a bit noisy anyway, so he wouldn’t mind a chat>.”-ap#1 similarly, noise amplification is considered an inherent problem of the open space that makes some of the users feel unsafe to conduct meetings: “this building has an unexpected way to amplify sound. […] the people at the fifth floor can hear what’s being said on the fourth floor. and sometimes when you have a meeting in that corner, i can literally follow it into the other corner of the building so that is something that does not always make me feel safe.” -ap#3 moreover, they are continuously disturbed by others with whom they share the workspace and they blame the spatial design which affords intolerable user behaviour: “i received the newsletter and they say that we should keep quiet and not disturb the staff working. but i get disturbed by the professors talking there every day...i don’t want to disturb them, but don’t disturb me too. for example, this space is more open because it is near the door, the lab, the coffee machine […], you can talk and work, but at the back it should be quiet. however, every professor goes and talks there. if people could make this clear, then it would be better.”ms#2 4.8 opportunities in the open space there is a positive side to the transparency provided by the open space layout in relation to social connectivity. the open space offers “this opportunity for people to walk by” and some members consider the open space a good setting for serendipitous encounters: “because it’s open space you have this opportunity for people to walk by […] you are easier approached. in my opinion, when i don’t want to be bothered also sit in oneperson spaces or try to get a cabinet or a room.”bs#3 the open spaces from floors 2, 4 and 6 offer 6-person snack tables which are considered a good setting for informality during breaks: “i really like the idea of the pantry lunch location on my floor (4th) and i would like to see more of these informal lunch and meeting places.”bs#4. they consider that: “at the pantry, level 4 is where the most encounters happen because the teachers are there too” and that the pantry table location is a good indicator for approachability: eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 11 “obviously people are available when i encounter them at the lunch table. i guess sometimes context is important.”ms#2 a member describes the pantry area as a location that conveys the idea of break from focused work and leaves members open for interaction and unplanned social meetings: “if i am sitting over there [ the coffee machine] and heating my lunch waiting for the microwave to finish, i think that’s fine [to be approached for a chat.]”-pc#1 lastly, the pantry area is considered as a location in the open space that encourages social interaction without disturbing other activities that take place in the workspace because it affords a specific activity: “about the setting […] at the coffee machine might be better [for social interaction]; if i want to have a beer i prefer to do that off campus or in a location where i am not intruding on the other social climate that is happening ...i feel like location is so specific.”pc#1 4.9 community building requires a community space the tu/e industrial design community members consider that the newly renovated atlas hinders community building instead of facilitating it: “this building breaks it up because it doesn’t facilitate community building. potentially it does, but not how it is turning out. it sort of distributes facilities and ignores the actual use and it seems to inspire disparate communities.”ap#3 they wish a common meeting space that belonged to the department existed and do not consider the cafeteria from the ground floor services area a good choice because it is shared with other departments and it is expensive: “i don’t really meet people, there is not a big, fixed space for talking. because before, we had the canteen and the closed space only for id students but now the canteen is expensive, open to everyone, so i can’t really meet anybody.”ms#2. furthermore, when comparing atlas with the previous building which the department solely occupied during the renovation, users seem to long for a lost sense of identity: “i realized what i liked about the other building is that it was our building and it was friendly. and two floors nothing fancy. it was a good feeling.” – ap#2. moreover, it is not only the tu/e industrial design cafeteria users feel to have lost, but also the student association space lucid which used to be frequented by students and staff alike: “i hardly go there now [lucid]. probably because i need to take some more stairs because lucid is in the basement now. there was still much better in the old building or the laplace building.”ap#2. in atlas the two social hot spots of the department are no longer integrated in the daily routine of the users, making them have a limited success in coagulating community feeling: “in laplace, when you went to the canteen or you walked to lucid or there was always a chance of meeting teachers and seeing them at the lunch table and they were like really the same level kind of. this is not the case anymore.”ms#4. furthermore, as a result of the building failure to attract and engage users during breaks, users feel isolated from their peers: “in laplace if i wanted to meet someone, i took a round and easily found them. now in atlas, this is really difficult to be done. sometimes, i feel isolated from my fellow students.”ms#5 lastly, the members of the tu/e industrial design community feel that the department does no longer provide a common space of socialization and they express their need for new opportunities to be together with their colleagues: “i see other teachers smoke and that is the only space that we can share or do something else than work; they have their own spot for lunch, for everything; except for squad meetings, everything is separated. that is the only space where we meet but we don’t talk; there is still a distance. we need a space where everybody does the same thing that is not work.”-ms#3. 4.10 contextual planning & informed conversation starters this study has been conducted in a community of creative thinkers; therefore, we have considered appropriate to ask them to describe at least one improvement they would bring to the current situation in relation to their community. the first category of ideas originates from the inconsistency and discontinuity that the staff experience in relation to their work schedule, as one respondent explains: “over time i learned that the schedule for stuff members here is super fragmented. i already have very limited time and opportunities to do focused stuff and over the years i’ve come to understand this. and so, i also learned that people appreciate clarity.” ap#2 this clarity could be brought on by an organizational restructuring measure, another user adds: “it would be nice to organize things in a contextually similar way; for instance the fridays are relatively ok for me because i stay mentally in this student coaching space; i do it in the morning, then it is a short break or no break and then i continue in the afternoon like 1-8 meetings and then the day is done; but i don’t need to jump around and switch context.” ap#3 the problem with switching contexts has been similarly described by the tu/e industrial design education director, who explained in an interview that the community bonds between all members could be effectively improved if the staff would be able to contextually combine and adapt their weekly activities. he added that staff members have multiple roles within the department that emerge from a diversity of activities such as research, teaching, mentoring and for some, administrating and organizing. exploring opportunities for community building in atlas – the world’s most sustainable education building eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 silvia cazacu and matthias rauterberg 12 these roles are currently performed in a fragmented, almost chaotic manner over an entire week which causes task accumulation, increases stress and consequently, decreases the chance for spontaneity and informality between breaks. another participant describes this situation from the staff perspective, when asked to give their opinion on starting a community building activity on friday morning: “i can’t keep on stacking that up, and certainly not every friday. what for you feels as community building and as intrinsically valuable and i’m not arguing with that is also an organized thing that brings me every friday away from my family […]. everything i don’t do in the thirty-eight hours that in here i’m doing in the evenings. so, if i’m going for some community building for an hour or two every week, that means that i’ll work an hour or two more in the evenings”. – ap#1 the second category of ideas arises from the impracticalities the students experience when they want to access academic staff they are not acquainted with. a student characterizes the current situation: “i know most of the teachers as i know them from facebook… [laughs] but it doesn’t count, you need something else.”ms#1 they describe their needs and propose improvements in relation to information on availability and location of staff members: “the first obvious thought i have is the kind of app that would show you where people are and also if they are busy...like if my teacher is there and if i have a question and they are not super busy its ok if i come in to ask it...who is there and where and if it’s an ok moment to approach somebody.” – ms#2 they mention that their expertise is insufficiently detailed on the tu/e industrial design department website: “even if we have this staff description on the website where you find out their expertise and whatever, i find it a bit hard to really get valuable information from there and see who might be interested to talk.” ms#4 similarly, they would like to get more in-depth knowledge of past projects they might be interested in: “the projects they did, that is interesting to know as well. if i know the person and i know the interest they have, then i would start a conversation. i think you need to search sort of the same interests to start the conversation”. bs#4 lastly, the third category of community improvements regards the students’ active role in making their needs known and attracting valuable discussions. to stabilize the unidirectional flow of information that is currently available from the academic staff’ side, students should become proactive and start displaying their work in a similar way as their teachers. this idea has been initially described by the tu/e industrial design education director as “conversation starters” when he stated that “students should be cleverer about it” and confirmed by one of the participants interviewed: “the more proactive the student is and more go-getter they are... if they schedule a meeting request and already have a sketch and show you they read a bunch of stuff, that excites the staff here and then they are more open to spending more time.”pc#1 5. discussion 5.1 contextual planning (based on themes 2, 4) the tu/e industrial design knowledge space is divided into 6 floors with limited and onerous communication in between them which hinders accidental meetings between colleagues. this is especially the case of researchers whose daily activity is densely structured around formal meetings and focused, individual work. this situation does not leave many opportunities in their schedule for informal encounters. people cannot be motivated to contribute with time and knowledge to the academic community when their entire schedule is overloaded and fragmented. therefore, decreasing the burden of staff activities and tasks by contextually restructuring teaching and research and organizing smaller clusters of similar interests can improve knowledge work and community relations. this can be achieved by providing better alignment between student projects and research activities and arranging thematic areas within the building supported by online groups for fast knowledge exchange. 5.2 everyday navigation in a boundless physical & digital space (based on themes 1, 3) availability during everyday working hours is considered a piece of information with a high potential to either strengthen community bonds or break them even more. members rely on their personal interpretation of generally accepted rules of availability or common practices in knowledge workspaces to understand this information. they interpret digitally available information through the tu/e intranet platform or email exchanges. physical elements that display availability are used by staff members to enforce a distance from others during their work. these are construction elements or furniture pieces (doors, walls, desks) with general norms of use attributed by people through personal interpretations, experience and cultural practices. the norms and practices for the same element can be interchangeable, one taking priority in front of another as a result of everyday use. keeping clear boundaries and creating easy-to-follow rules in the physical environment as well as displaying online up-to-date information regarding the availability, location, work context, activities and interests of users could increase work efficiency and improve community experience. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 13 5.3 opening the open space (based on themes 7,9) the majority of tu/e industrial design users collaborate, learn, focus and socialize in the open space areas located on floors 2, 4 and 6. these spaces provide a mix of individual desks, shared working tables clustered in squad spaces, meeting spaces of different arrangements and sizes and a small pantry area for lunch and quick meetings. they are all positioned in an open space floorplan layout with very few space partitions to provide noise control and visual separation between the various types of activities happening at the same time. moreover, having multiple activities and interests combined in an open environment brings difficulties for those who want to conduct focused work. this situation can be regarded as a conflicting agenda between the intended use of the space and the daily practices which point to either a lack of communication or a design fault or both. creating a welcoming working environment that affords diversity can be achieved by increasing the number and types of space partitions, adding noise cancelling devices or considering remote work through an online realtime collaboration platform. 5.4 open space – opportunity to collaborate, socialize and interact in small groups (based on themes 6, 8) working in the open space does not only mean noise and interruptions from focused work, it is also an invitation to collaborate and to exchange ideas, to meet, to see and be seen or to just sit in the same space with others like you. even when they do not actively participate to a formal meeting or collaborate with others, members can still encounter moments of community [10] by observing others, identifying with their actions and appropriating cultural practices of the knowledge space. this is possible because the social environment is situated in a space with few boundaries, multiple seating possibilities and flexible furniture which afford in term multiple activities at the same time. therefore, we consider that combining possibilities for interaction within different group sizes and types will improve social connectedness and create the opportunity for socializing, pitching or venting. 5.5 when everything is accounted for, there is not any place left for surprises. and communities thrive on surprises (based on theme 10) community building in an academic knowledge space is a continuous effort that requires a balance between planned spaces, organizational measures and activities that cater to all members ‘needs and unplanned circumstances that leave room for uncertainty and togetherness [16]. the tu/e industrial design department is a vivid example of how a tight academic community can dilute in a matter of months when displaced to an environment which is unfit for community activities. in their everyday use of a workspace, people are more interested in solutions that allow them to work and socialize unhindered than in over-planned, cutting-edge, visually pleasing designs that fail to afford the simple joys of being alive (“there’s no surprises anymore and we thrive with surprises. and if everything is planned and fixed on, people will go home and work from there”). placing (seemingly) random events and hotspots in people’s way, such as a temporary lemonade stand, an art display area or an information panel can increase informal encounters, improve orientation and create joy. 5.6 cultural awareness (based on theme 5) in an academic community, social and cultural integration of students is important for a good academic performance [36], but being close to other members is not always an easy task for foreigners, especially for those coming from asian countries. according to a recent study conducted in nine academic institutions in the netherlands, this reality stems from the differences in power-distance [37] that students must adjust to when they start university courses. this reality has been confirmed by respondents to our study coming from eastern asian countries; according to them, the most prevalent cultural issue is the (lack of) seniority in the tu/e industrial design community. if normally, this would translate into lower thresholds for both informal and formal interactions, in their case it is an issue that makes them feel out of place. consequently, their own cultural values collide with the institutional culture and practices, leaving them with a hard choice to either ignore their own cultural identity and values or to ignore everyday academic conventions and thus, become gradually excluded from the community. culture is a sensible topic within academic communities. while a universal recipe for success does not exist, members who are aware of the cultural implications of their interactions already have an advantage over those who ignore them. similarly, if the academic institution would be more flexible in accommodating foreigners by actively encouraging cultural awareness [37], they could become more active members of the community. 6. limitations and future research recommendations this study has been performed in a recently renovated, state-of-the-art university knowledge space which has been designed to afford community building within departments through social learning and experimentation, as well as a flexible and enjoyable work experience for all knowledge workers involved. thus, we consider it representative of exploring opportunities for community building in atlas – the world’s most sustainable education building eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 silvia cazacu and matthias rauterberg 14 the research topic addressed. however, the research explores a singular case study which cannot provide generalizability of the findings. more research in other similar knowledge spaces is needed to generate a better understanding of how community building should be encouraged in academia. moreover, the exploratory nature of the study which builds only on qualitative data provides rich insights into the multi-faceted challenge of designing modern knowledge spaces. however, to support the validity of our findings a quantitative study that addresses the topic of user experiences of academic knowledge spaces in nowadays societal context is necessary. the main researcher of this study is a member of the community which is being studied; therefore, the data collection process has been strongly influenced by own daily experiences and insight. on one hand, this situation provided a better understanding of the context which in turn saved valuable research time. on the other hand, researcher bias could not be avoided entirely, and we are aware that several discussion topics have been brought up because of our familiarity with the environment. however, we trust that the data analysis process has been sufficiently supported by theory and bias has been removed from this subsequent part of the study. 7. conclusion following a qualitative stakeholder approach, this case study explores the community of the department of industrial design from eindhoven university of technology, the netherlands to understand how state-ofthe-art academic knowledge spaces foster community – building in today’s latest technological context. the findings are comprised in 10 context-rich themes which indicate that the analysed knowledge space does not meet the conditions required to encourage community building on three main aspects: providing rich-context information to users about their peers, a balanced combination of work and community activities among academic staff and a spatial design fit for serendipitous encounters, large-group gatherings and eventful routes. as suggested by the thematic analysis, the environment plays an important role in creating opportunities for community building, thus we recommend exploring this in more detail as further research on communities of knowledge work. the emergent discussion provides useful suggestions on ways to support community building for corporate real estate management experts, as well as interaction designers, architects, planners, or other professionals interested in applications of ict on academic knowledge spaces and smart city infrastructures. the study expands the literature on academic knowledge spaces by placing emphasis on community building and participatory communication in the context of smart cities. further research is needed to support our findings from a quantitative perspective as well as from other universities which undergo restoration and/or restructuring works on their facilities. acknowledgements. i would like to express my special appreciation to my advisor prof. dr. matthias rauterberg for his support, patience and guidance throughout this project which represents the start of my research journey. to all the members of the id community and tu/e experts who have participated in this study, i am grateful for your enthusiasm and valuable insights. finally, i am thankful to the reviewers of this paper for their constructive comments and suggestions which helped improve this manuscript. references [1] magdaniel, f. c. 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(2013) the role of cultural dimensions of international and dutch students on academic and social integration and academic performance in the netherlands. international journal of intercultural relations 37(2): 188–201. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e5 this is a title 1 federated cloud analytics frameworks in next generation transport oriented smart cities (toscs) applications, challenges and future directions md. muzakkir hussain 1,* , mohammad saad alam 2 , m.m. sufyan beg 1 1 2 department of computer engineering, aligarh muslim university department of electrical engineering, aligarh muslim university abstract electric, plug-in electric and plug-in hybrid electric vehicles (xevs) are receiving a global attention from automotive industries, vehicle vendors, r&d organizations, power sectors and policymakers in the intelligent transportation era. penetration of xev fleet into the contemporary charging infrastructure(s) in the absence of robust integration network imbalances the power grid and potentially jeopardize the execution of emerging distributed generation systems. however, smart grid technologies in collaboration with smart charging management strategies can circumvent such operational disparities, thus enabling a reliable, efficient, consistent and optimal electric energy management in the power system. this work employs the notion of cloud of things (cot) to propose a comprehensive cloud aware transport oriented smart city (tosc) framework intended to provide intelligent solutions to the contemporary transportation infrastructures in the emerging sustainable smart cities. the proposed work also demonstrates a commercially viable vehicle to cloud (v2c) fleet charging framework for charging management of xevs through micro grids/ smart grid. the unprecedented data breeding across v2c, cloud to grid (c2g) and grid to vehicle (g2v) bidirectional communication interfaces elucidates the need for computationally efficient analytics. a state-of-the-art big-data to knowledge (b2k) workflow structure is thus proposed for translating the generated data into efficient knowledge for noble decisions and inferences. finally, the substantial mobility as a service (maas) adoption challenges and data science prospects are outlined along with the emerging technologies that can co-work with the proposed framework to ensure commercial viability and optimal implementation in emerging toscs. keywords: big-data, cloud of things (cot), electric vehicle range anxiety (evra), smart grid (sg), mobility as a service (maas) received on 07 december 2017, accepted on 08 january 2018, published on 12 february 2018 copyright © 2018 md. muzakkir hussain et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.12-2-2018.154103 1. introduction with the advent of rigorous industrial research and development efforts and stringent protocols related to vehicle emissions [1], fuel economy, constraints in conventional energy reserves and the innate global warming, the electric, plug-in electric and plug in hybrid electric vehicles (xevs) have been receiving an utmost attention from automobile industries, government agencies, r&ds, vehicle vendors as well as consumers. the xev programs became a business motto for the automotive industries as they seem to serve as the sustainable and efficient powertrains for the emerging electrified transportation system. according to survey in [2], and [3], during the short span of six years from 2008 to mid 2014, a quarter million plug-in hybrid electric vehicles have been launched into us roads. as of 2013, more than 129,500 americans were driving xevs manufactured by all major automotive original equipment manufacturers (oems) [4], while the xev adoption process is still on fast pace in countries like china, france, germany, india etc. in 2015, the global xev population exceeded the 1 million threshold, closing at 1.26 million, a reflection and symbolic of achievements due to the joint efforts from governments, policymakers, r&ds, and automotive industry over the last decades [5]. the tremendous increase in the xevs count has created an alluring interest in the contemporary automotive eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e2 ∗corresponding author. email: md.muzakkirhussain@zhcet.ac.in http://creativecommons.org/licenses/by/3.0/ industry to invest their assets in profitable deployment of this emerging class of vehicles. to achieve this stringent goal, an immediate issue being addressed by the automotive industry in conjunction with the power sector enterprises is the “electric vehicle range anxiety (evra)” syndrome prevalent in the xev customer(s) that usually becomes acute during long drive scenario when the driver is deprived from accurate information of charging station statistics. while executing a fully electrified fleet, the uncoordinated charging of candidate xevs may pose serious impact on reliable and efficient operation of the associated electric utility [2], [6]. thorough study of literatures reveal that perforation of large scale xevs fleet can pose a huge challenge and will disrupt the operation of underlying power grid distribution network unless their operations are monitored and coordinated properly [7], [8]. the prominent side effects may be in the form of potential violations of statutory voltage limits, degradation in power quality, blackouts, incremental investment on the pre-existing network, etc. lack of coordinated charging strategies can also create demand peaks during rush hours which in turn put stress on the sgs [2]. however, use of data driven charging strategies will potentially circumvent significant proportion of burdens from the supporting smart grid architecture [2]. it has been empirically estimated that the current power system can withstand the power surge caused due to full xev rollout. provided that they are intelligently managed [9]. the current advancement in intelligent transportation technologies has favored progresses over existing data collection, storage and processing devices. vehicle on-board units (obus), roadside units (rsus), intelligent sensors and advanced metering infrastructure (ami) and vehicle to infrastructure (v2i) elements had revolutionized the transportation telematics. to ensure real-time processing, analytics and decision making, the utilities demand efficient synchronization infrastructure. as estimation discovers, the transactions of merely two million smart metering populations generate more than 20gb of data every day [10]. trends reflect that the vast scale roll out of smart transport system leveraged with advance metering infrastructures (ami), smart grid, smart charging stations and the innate smart xevs is still in its infancy. installation of such architecture requires robust and efficient analytics framework for collecting, storing, processing and managing the data originated from the candidate intelligent utilities. collaboration of distributed paradigms such as cloud computing technologies with transportation & data analytics modules will ensure robustness and resiliency in penetration of xev fleet of any size. hiring cloud services is envisioned to stimulate the development of storage, execution and analytics framework for the aforesaid components. the clouds can be virtualized to act as cache for the generated data. furthermore, the notion of internet of things (iot) ensures connectivity to all such entities, forming a connected transportation web (ctw) [11]. however, connecting such varying data sources directly to cloud data centers is inefficient and commercially impractical. the major issues with traditional centralized cloud models are associated with latency, network bandwidth, communication overheads, security and reliability [10]. under such circumstances an alternative approach is to inherit the notion of cot and employ multiple micro datacenters corresponding to dedicated stakeholders, interconnected via communication linkages of varying bandwidths. involvement of cot utilities with the prevalent transportation infrastructures triggers an unprecedented breeding of data, that further magnifies the exertion on the storage and processing elements. by 2020, the predicted size of iot enabled devices estimated to surpass by 200 billion entries across the globe [12], trend suggests that more than two and half quintillion databytes are produced per day from such entities [13]. however, voluminous datasets produced from these objects if properly mined have latent peculiarities to bestow pools of knowledge and decisions. there has been a consensus acquiescence in the automotive industries as well as research arena on the fact that an intelligent and duplex trading of data and control between the xevs and charging infrastructure through the optimal deployment of cot enabled v2c, c2g, g2v and v2i [14] communication interfaces would empower in prototyping strong decision making paradigms, as outlined in figure 1. fig.1: outline of the proposed model recent investigations for commercial deployment trends reflect that the contemporary cloud prototypes are not designed for the v’s of big data generated by cot utilities [15]. the need for fundamental restructuring is strongly perceived in existing cloud settings, to overcome the scalability, latency and security concerns [16],[17]. in response, analytics frameworks have been developed for validating massive datasets generated in cloud aware transport system execution and translating them to build meta-data models [18]. heavy investments from utility companies on big data analytics of smart grid data are in continuum from nations across the globe. figure 2 depicts the investment trend as forecasted from gtm research obtained from an exhaustive survey of electric utilities across specific regimes on sg analytics [19]. a as evident from the forecast, till 2020, the cumulative global investment on electrified transportation and sg analytics is expected to reach $16 billion, 40% of which is shared alone by us. in fact the annual global investment is estimated to reach $4.6 billion by 2022 which is more than a half of the cumulative amount from nine year span 2012-2020. 2 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e2 md. muzakkir hussain et al. 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 0 150 300 450 600 750 900 1050 1200 1350 1500 us eu ap la a m o u n t (m il li o n $ ) year fig.2: trends in investments on transportation and smart grid analytics motivated by the above-mentioned facts, challenges and opportunities, this work proposes a state of the art transport oriented city (tosc) framework based on the notion of cloud of things (cot). as one utility of tosc framework, the proposed work provides a commercially viable ready to be prototyped v2c model, incorporates cloud data analytics into the infrastructure claimed by proposing a smart v2c remote charging infrastructure for the electric/plug-in electric/plug-in hybrid electric vehicles (xevs). in addition this work also discusses data science prospects and challenges that will evolve in/during the implementation of v2c framework over toscs by proposing a big-data to knowledge (b2k) framework that defines control flow model for transforming information in transportation telematics into valued knowledge and rightful decisions. the major contributions of this work can be encapsulated as 1) proposed a state of the art cloud aware tosc framework using the notion of cot, where the “things” in cot comprises of intelligent entities like smart grid, smart charging station, smart car and smart meters, described in detail in section ii. 2) presented a commercially viable realization of v2c framework in toscs destined to smart charging management of incoming flux of smart xevs fleet satisfying three criteria namely (i) minimum charging tariff, (ii) shortest travelling distance and (iii) minimum queuing delay, in section iii. 3) formulated a prototype for b2k control flow for translating the produced big data into knowledge for rightful decisions, in section iv. 4) outlined the significant mobility as a service (maas) adoption challenges and data science prospects to realize commercial viability and optimal implementation of the proposed frameworks, in section v. section vi concludes the work. 2. transport oriented smart city (tosc) architecture intelligent transportation systems (its) play the strategic role for emerging smart cities. deployment of smart cities is envisioned to constitute an its based urban development for optimally managing the city’s assets while sustaining a green and clean environment for the citizens [20]. thus, policymakers as well as r&ds across the globe have joined the smart city development consortium engaged in employing relevant expertise and funds towards the deployment of transport oriented cities (tosc). these cities are uniquely distinguished by provisions for intelligent data connectivity. plenty of claims and proposals are found in the open domain which are being implemented independently in diverse its domains such as security in information management of smart grids [4], smart grid dynamic energy management (dem) [21], agent based simulation of electric vehicles fleet charging strategies and several other areas [1]. however, the said methodologies are localized in silos and yet to realize the synchronization aspects, management tractability and commercial viability of the complete transportation system. establishing a data driven analytics framework is the need of hour in current transportation architectures in the emerging smart cities through the notion of tosc. to realize the anticipated tosc objectives, a cloud aware transport oriented city frame work is proposed in figure 3. fig. 3: architecture of the cloud aware transport oriented smart city the prime ideology on which the proposed framework is established is remote accessibility and remote management. the framework manages the control and data trafficking through federated clouds namely grid cloud, xevc cloud, xev cloud and aec cloud. the grid cloud interfaces sg with the xev charging stations, ami and demand side management (dsm) utilities. the grid cloud is designed to support bidirectional data and power transport among these entities to ensure optimization of power system utilities in terms of efficiency, availability, reliability and sustainability. the objective of analytics involved in grid cloud is to establish a platform for supporting stakeholder’s services like dynamic energy management (dem), demand response (dr), integrating micro grids and any other renewable energy based 3 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e2 federated cloud analytics frameworks in next generation transport oriented smart cities (toscs) distributed generation system. the cloud applications serve as virtual communication platform for tosc components, thus ceasing the need for inter-entity communications. the data centers in sg install efficient virtualization mechanisms to ensure cost reduction, resource optimization, and server management. since the sg is interfaced to intelligent transportation devices such as smart meters, smart sensors, and privately managed charging station or aggregator cloud, scalable software as a service (saas) applications can be developed that facilitate rapid analysis and integration of data streams in order to shape the real-time xev flux and power supply curves. it also engage intelligent agents for successful integration of virtual energy sources such as micro-grid, nanogrid, smart homes etc, into existing energy storage and executes robust power exchange mechanisms to successfully meet the requirements of xev users. the xev charging hub in this framework acts on behalf of aggregators to participate in the real time power market operations. the charging stations hire hybrid cloud services from xevc cloud substructure where in public mode the resources and computation are shared with sg, xevs and other stakeholders. the xevc cloud is interfaced to smart grid and vehicular applications through dedicated datacenters. the public deployment mode also allows the charging station vendors to hire iaas infrastructure equipment like virtual machines, servers, storage and network hardware etc. through virtualization techniques, iaas reinforces computational and storage capabilities and enforces load balancing protocols to provide intelligent charging solutions to the xev users. the xevc clouds employ iot enabled intelligent recommender systems that collect multivariate attributes from varying road and vehicle telematics, metering information, state information of sg, forecasting & day-ahead status data etc, and provides charging recommendation to the vehicle users. it also employs application specific infrastructure and power management softwares modules for task scheduling and effective renewable integration respectively. the dynamic xev cloudlets formed from clusters of parked and semi-parked vehicles provide platform where corporate computing, sensing, communication and physical resources are shared, allocated and coordinated dynamically. the iot paradigm enables the design of mobile vehicular clouds that possess powerful storage and processing capabilities [22], where the “things” in iot includes vehicular components such as external sensors (gps, camera), internal automotive and cockpit sensors/actuators (brakes, steering wheels, xev battery state of health (soh) and state of charge (soc) monitor, accelerators etc, intelligent and autonomous vehicles, smart drivers etc. such xev cloudlets are formed autonomously from the road traffic (parked vehicles, vehicles in traffic congestion, platoons etc.) and employ “computing on wheels” approaches to offer smart transport services in toscs. besides the resources and services provisioned on demand from the generic public vendors such as amazon ec2 [23], the consumers can hire underutilized vehicular resources such as computing power, network connectivity, sensing capability, and storage through diverse business models such as storage as a service (saas), network as a service (naas), cooperation as a service (caas) etc. such self-organizing cloudlet infrastructures can work independently and can be complemented with conventional cloud vendors to offer intelligent utilities not only to xev users, smart passengers, pedestrians, traffic managers, tosc planners but also provide reciprocate advantages to xev cloudlets in terms of scalability, dynamic computation capacity and quality of service (qos). for maintaining the legislative and regulatory protocols across administrative regimes, the infrastructure employs hybrid aec cloud that provides services associated to authorities, emergency response corporations, service centers and customer care services etc. aec clouds have communication interfaces to the xevs, drivers, traffic management entities and other cloud-cloudlets to ensure realtime monitoring set up for the toscs. fig.4: service oriented architecture (soa) for toscs the objective of the execution strategy outlined for the proposed tosc framework is to granulize the traditional cloud paradigms into a hierarchical structure to multimodal execution setup. the decisions for offloading and analysis tasks are decided by the degree of service criticality and reliability. the operational modes of the miniaturized cloud versions also termed as cloudlets are defined to be dependent or independent based on the type of service it is intended to support for. in the former mode, the operation of such peer clouds are managed under hierarchical control of large master data center. in independent mode of service, the architecture relinquishes the centralized control and the federated datacenters were managed as one larger data center. distributing the cloud abstraction to deeper levels of control in toscs offers an extended range of advantages over the traditional cloud deployments architectures. the key advantages are but not limited to: 1. distributing the clouds to finer grained control in toscs will overcome the overhead and latency issues by offering proximate storage and computation service. 2. distributed data locality paradigms will improve the authenticity and privacy concerns that often occur with traditional single mega datacenters. 3. this paradigm shift in cloud computing fundamentals provide optimal feasibility to the transportation and power system architectures in the emerging smart cities that 4 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e2 md. muzakkir hussain et al. fig. 5: federated v2c framework for smart charging of xevs. encompass incongruent political regimes, multiplicity of cultures, psychology and stakeholders. 4. this also ensures greater business agility by invoking developers to adopt mobility as a service (maas) utilities for the toscs and deploy them according to stakeholder’s need. 5. the multimodal cloud infrastructure shall provide lower operating expenses and deeper insights through local storage and analytics instead of offloading the whole universe of datasets for cloud analytics. the tosc infrastructure once efficiently deployed will extend the smart city services to a new horizon by providing a reference for domain specific applications such as smart parking, smart traffic management, smart charging etc. fig.4 describes the modular service oriented architecture of typical cloud aware next generation toscs. in order to demonstrate the expediency of developed tosc infrastructure, in the next section an analytical vehicle to cloud (v2c) framework is proposed for coordinating smart charging management of contemporary xev fleet. 3. vehicle to cloud (v2c) framework for smart charging of xevs in this section a vehicle to cloud (v2c) remote charging management infrastructure is devised as one of the tosc package, to coordinate charging of xev fleet. the cloudcloudlet hierarchy and inter-cloud interaction for the v2c framework is shown in fig. 5. in the proposed v2c scheme, the entities involved in the vehicular infrastructures will have seamless interaction through the dedicated tosc data clouds. the federated clouds described in section ii will regulate the trade of control and data in v2c through robust network interfaces as shown in fig.6. the clouds will represent in varying interfaces each with the tosc entities such as xevs, the charging station, and the smart grid etc. the apis at the xevs end needs only to interact with the xev cloud, without any needed to communicate directly with the charging station or smart grid vendors. this requires implementation of efficient and secure communication as well as interfacing procedures [11]. the api at xevs end would be interfaced to the cloud mesh through authentication mechanisms. the peer data centers would be under the administration of master cloud and communicate with other stakeholders through appropriate and legal mechanisms. keeping a major portion of control under government administration ensures proper pricing schemes/power rates. at the same time, it also hides the implementation details from casual users by enforcing stringent protocols thereby assuring a secure infrastructure. the centralized control also removes redundancy in the computation. the application running at xev driver’s end has bidirectional information exchange with the cloud computing utilities to obtain real-time power system updates. such updates can be in the form of energy pricing status, state of charge of xev battery as well as smart grid, trip description etc. in turn, the real-time scenario information related to energy pricing status, state of charge of xev battery, optimal location of charging station, best route/ shortest route etc are fed by coordination and monitoring modules in the data centers to intelligently regulate the driving behavior of the xev fleet. the data center implements efficient algorithms on such scenario attributes to compute the degree of range anxiety in the xev user and correspondingly recommends charging option to the latter under the criterion triad’s namely minimum charging tariff, shortest travelling distance and minimum queuing delay in decreasing degree of criticality. 1. minimum charging tariff the prime motive of an xev user is to have charging services at the least possible rate. many a times the consumers have constrained alternatives with unaffordable charging options that further add to the range anxiety. the v2c application will communicate with various charging stations located in the vicinity of the xev to track the dynamic power pricing tariffs and recommend the one with optimum rate. it is discovered from the predominant charging strategies that in regulated power market, the consumers often have to endure the unrealistic power tariff caused due to vendor’s monopoly in the market. the distribution of dominion over several 5 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e2 federated cloud analytics frameworks in next generation transport oriented smart cities (toscs) dealers as in a deregulated power market will enhance competitiveness among them and the consumers could grab the edge. the application will also be equipped to surveil the forthcoming pricing agenda and correspondingly prepares the user to be managed for the trade. moreover, the system will offer varying incentivization schemes based on intra-brand or inter-brand charge transfers, mode of charging viz. fast, regular or slow charging rate and time of charge viz. off peak/ rush hour etc to extend the range of services sufficing a range of customers. the real-time cost optimization operations enforced by sg and charging hub clouds respect the power pricing interests of each power system stakeholders thus realizing a win-win climate for whole tosc infrastructure. equation (1) dictates a integer linear programming (ilp) based cost minimization strategy motivated to realize multi-location remote charging of xevs, with concentration on minimizing the xev battery degradation. , m in h i c 1 c o s ( . ) . ( ) . .( . ) h i h h i h i i i h t p h c d d p h         (1) subject to constraints:   1 . ( ) h h i h i i i i p h c d        , , d i n i n h h h     (2) , , 1 ,d i n i n i nh       (3) m in m ax , h i j i i j      (4) 1 h i d c  (5) the terms in objective function (1) shows the charging cost and xev battery degradation cost respectively under time of use (tou) price. equation (2) and (3) captures the stored energy dynamics of xev battery when the xev is in transit among three states defined by decision variables h i d and h i c showing charging and discharging events respectively, at a time slot h as described by (6). constraint (4) defines the inherent regulatory limits imposed on the xev state of charge (soc) while (5) enforces the integrity and synchronization mechanism by drawing the fact that charging and discharging of xevs are mutually exclusive events. , 0 / 1 , 0 d i n i nh i i f h h h d c o th e w is e        (6) 2. shortest travelling distance when the xev battery soc starts reaching below a threshold level and the xev user is driven by the fear of being stuck in the midway, the xev user opts for the shortest route. the v2c application recommends in accordance to the adopted shortest path first (spf) algorithms such as dijkstra's algorithm. further, every shortest route is not guaranteed to be the least time consuming one, thus the application dynamically adapts according to the forecasted traffic uncertainties. the application can also implement geometric planning strategies to obtain a optimal route under such adversaries [24]. fig.6. communication interfaces among federated clouds 3. minimum queuing delay here the driver has time constraints and it generally occurs during miscellaneous contingency hours viz. office hours, school hours etc. for such case, the road which is shortest as well as having least traffic is the ultimate option. many a times, the driver has to confront to useless delays due to infrastructure uncertainties such as at traffic jams, queuing at charging stations. the v2c recommendation system software can implement robust routing protocols to manage the charging schedules of xevs. it can further use the fundamentals of queuing theory to configure the stationary and non-stationary distributions of xevs incoming flux in a way that guarantee minimal queuing delay, maximum charging hub utility and curtail the burden from backend sg. however, the proposed v2c algorithm would undertakes all these criteria into consideration to achieve an optimal output termed as the state of “triangle equivalence”. there exist a range of xev consumers that often wish to get rid of the delays while the vehicle battery is plugged. to address such disputes the v2c recommender system (rs) will mine the fuelling, driving, social and psychological profile data of the xev user to predict the mode of charging that he shall adopt such as fast charging, normal or slow charging etc. for immediate actions, the cloud aware tosc proposed in this work augments the v2c services to another dimension where the xev user is alarmed of such uncertainties and advocated to undertake the pico-grid service offered by photoactive coatings on the vehicle panes. the rs can also implement risk averse solutions by efficiently quantifying the physical, social and financial uncertainties of the overall environment for optimal commercial viability. 6 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e2 md. muzakkir hussain et al. fig. 7: workflow model for big-data processing in tosc architectures 4. big-data to knowledge (b2k) framework the proposed tosc framework congregates the diverse transportation entities into a clique like structure through cot paradigm and enables a bidirectional flow of energy and data among the stakeholders in order to facilitate the assets optimization. the major data sources for a data driven tosc include: 1. sg data aggregation nodes such as supervisory control and data acquisition (scada) system and associated components viz. master terminal unit (mtu), remote terminal unit (rtu), programmable logic controller (plc) etc. 2. ami metering and sensing devices. 3. its objects such as xev obu, rsu, traffic sensors and actuators, gps devices etc. 4. web data for recommender systems, crowdsourcing, feedback modules. fig.7 depicts the big data to knowledge (b2k) work flow for translating the data generated from tosc infrastructures. the objective of the proposed b2k framework is to realize a range of data aware tosc services such as vehicle to cloud (v2c), vehicle to grid (v2g), vehicle to home (v2h), demand response (dr), demand side management (dsm), dem, xev charging management etc. in order to effectively meet these but not the least tosc objectives, the b2k framework defines a multi-tier tosc analytics framework that encompasses multidisciplinary efforts from data mining, machine learning, data fusion, predictive analytics, state diagnosis etc. it establishes a data driven big-data analytics platform for the cloud to infrastructure (c2i) interfaces and enable the xevs, sgs, micro-grids etc to act both as producers and consumers, are thus entitled as prosumers. for instance, the xevs are allowed to participate in power trading services such as v2g, v2h etc. robust data science and computational analytics synchronizes the active participation of sg entities in power market operations such as bidding, arbitration, unit commitment, forecasting, scheduling, ancillary market etc, and operates diverse energy management services such as dynamic energy management (dem), real-time wide-area situational awareness (wasa), home energy management systems (hems), demand response (dr), frequency regulation etc. use of machine learning techniques for toscs provides the utilities the ability to adapt to act, grow and change without explicit stakeholder involvement when exposed to time series datasets. efficient execution of such algorithms on the data generated in proposed tosc framework setup consistent decision making platform and makes the system reliable and adept to adversaries. the dynamic and time series data from such utilities create high dimensional datasets that create storage, scalability and flexibility concerns for the analytics at the data centers. the b2k framework defines the use of efficient machine learning techniques specifically dimensionality reduction algorithms such as random projection [25], principal component analysis [26] and kernel based algorithms such as support vector machines [27] etc. to develop an efficient storage and analysis platform for such voluminous datasets. the framework advocates the use of advanced dimensionality reduction algorithms based on graph kernels to intelligently summarize the data produced due to the nodal structure of iot enabled tosc components such as charging station network, the xev distribution and human social interaction etc. in addition, the tosc data centers are equipped with fast and massive storage and computational elements supporting high performance computing (hpc). the framework enables the use of summarization techniques for aggregation analytics and transforms the original tosc data streams into noble representations to remove the concerns related to scalability, complexity, event detection and process execution. besides, it also employs data mining tools and techniques such as anomaly detection, rule mining, regression analysis etc. the b2k framework implements data fusion (df) paradigms that primarily inherit algorithms from three broad domains namely statistics, probability and ai, essentially employ sequence of tools and techniques for aggregating 7 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e2 federated cloud analytics frameworks in next generation transport oriented smart cities (toscs) heterogeneous configurations of data from varying sources to acquire intelligence and inferences for the system. the tosc utilities and data centers are leveraged with efficient data fusion techniques that collate the multivariate and heterogeneous data from the contemporary transportation and road telematics such as obus, rsus, localization mechanisms viz. gps, information storage and processing technologies etc to conclude with a comprehensive inference. for tosc data, the proposed b2k prototype advocates the installation of comprehensive data fusion pipeline defined and implemented by us department of defence (dod), that involves five execution steps with human in the loop [41]. level 1 involves data pre-processing i.e. compression, normalization and formatting methods etc, the outputs of which are fed to level 2. in level 3, the real-time data obtained from appropriate sources in level 2 are mingled with standard databases to trace & analyze the possible causes for the events occurring in the data. in the next processing level the patterns, correlations and semantics of information are assessed and aggregated. level 5 extracts the feedbacks from previous steps and applies successive refinement strategies to predict, assess and evaluate the need for further improvement in the df methodologies. the overall performance is tuned up by involving human factor in the loop to interpret and utilize the output from the df pipeline. the significant correlations, patterns and trends in the transportation dynamics are mined efficiently to devise intelligent schemes for demand response and load balancing. such datasets can also serve as potential candidates for predictive analytics needed for load forecasting, dynamic pricing, optimal scheduling of resources and bad data correction. graph pattern mining for distribution statistics of the tosc elements such as xevs, charging stations etc and utility mining for the xev usage profiles allows the v2c to predict the future service adoption scenario, for use in shortterm and very short-term demand forecasting. for load classification (lc) purposes, efficient offline clustering algorithms such as artificial neural networks (anns), k-means, fuzzy c-means etc are executed to discover the latent distributions and groups in the tosc data. the analytics modules in the data centers also implement online clustering strategies such as xcsc [28], online k-means [29] etc, for effective harvesting and utilization of time-series tosc and v2c data. to ensure real-time responsiveness, the tosc implements efficient task scheduling algorithms to have an exact dissemination of resources across the data centers. the application programmers create or port iot application that assigns the xev cloudlets to analyse the time-critical datasets and offloads the less sensitive or historical data to data centers at higher levels of hierarchy. though v2c infrastructures in transport oriented cities offer great potentiality for data and energy management, switching from conventional power architectures cloud aware smart grid and xev charging utilities will introduce risk factors that needs to be carefully mitigated. the intensive use of sg’s physical components viz. supervisory control and data acquisition (scada), master terminal unit (mtu), remote terminal unit (rtu), programmable logic controller (plc) etc, roadside infrastructures viz. obu, rsu, v2i elements and ami coupled with underpinning information and communication technology (ict) utilities makes the whole tosc framework a cyber-physical system (cps). such cyber configurations can pose serious complications with respect to privacy, security and integrity of both physical as well as ict subsystems. moreover, the multiplicities of big data applications in contemporary cpss motivates to solicit the concept of big data networking, its formation, features, mathematical and statistical intricalities [30]. the b2k also defining the need for embedding risk analysis modules into design phase of security subsystem in a way that ensures transparency and understandability among the involved stakeholders and curbs the confidentiality, integrity and availability concerns in the transportation and metering utilities. the tosc software developers also execute robust intrusion and anomaly detection algorithms and install committed firewalls in order to tolerate the vulnerable security threats related to disclosures, power thefts, denial of service (dos), integrity and cloning. the millions of iot based network devices employed in toscs are managed through emerging software defined networking (sdn) technologies to reliable operation of the whole infrastructure. sdn upgrades the hierarchical networking configuration of power system that includes home area networks (hans), neighbourhood area networks (nans), and wide-area networks (wans) through the notion of network operating system (nos). the use of sdn cloud aware transportation and power system architectures provide alluring solutions to the tosc network management problem by enabling a software-defined centralized control that is flexible with respect to regular software updates, flow control, security patching, and quality of service (qos) [31]. the nos programming interfaces are intelligently programmed to remove the labour, cost and complexities prevalent in traditional network management schemes by updating the network elements from the central control plane [32]. as defined in b2k framework, the federated cloud data centers use predictive analytics that involves use of statistical, machine learning and data mining techniques to analyze historic and real-time datasets generate rules and predictive models to predict future events [43], [44]. in order to install tosc infrastructures from the scratch and to meet the regulatory constraints for renewables and xev penetration, the tosc utilities implement robust predictive planning and analytics that can optimize asset replacement expenses and enhance the execution efficiencies under stringent budgetary ordinances. through predictive forecasting and asset analytics, softwares and services are developed to make the utilities in tosc infrastructures aware of the potential events for outages and correspondingly execute workforce planning that can undertake proactive measures for event mitigation and routine maintenance. predictive asset analytics are intelligently used to improve the technological, productivity and business process engagements in a way that assures customer satisfaction, proper route planning, better safety and compliance, and optimized field crews. 5. adoption challenges and future prospects the proposed work identifies some of the computing needs for building a data aware management framework for 8 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e2 md. muzakkir hussain et al. next generation toscs. the proposed tosc infrastructure is potentially viable to bring a paradigm shift in the application specific cloud computing deployments and can co-work symbiotically with numerous intelligent transportation systems (its) domains. the work concludes as a wakeup call for multitudes of energy management ideas to develop transportation and sg utilities that not only demand scalability services bestowed by cloud computing but also have additional requirements such as real-time analytics, consistency, privacy, security, etc. that the current cloud computing paradigms doesn’t support. however, being the first of this genre, it will elicit proponents as well as skeptics to ponder on future enhancements. this section highlights some adoption challenges and requisites for research thrust in course of toscs realization. 1. scalability the federated clouds presented for toscs will seldom be developed from scratch, but the economics is to grow out of existing architectures. issues regarding how to best allocate resources and programs to a distributed cloud that can serve the analytics demand of emerging toscs remains open book problem. the effectiveness of v2c infrastructures in toscs depends on its scalability to handle the dynamically changing xev flux. the cloud architectures in toscs should be potent to tackle the traffic spikes and surges in the xev demand occurred under emergencies and adversaries. efficient mobile cloud computing strategies leveraged with data driven demand prediction algorithms can circumvent the scalability concerns caused due to continuous evolution in the xev network [33]. high performance computation paradigms can be developed to optimize the storage space utilization, coordinate the virtual machines and network bandwidth to shape the server workload. integrating the proposed tosc paradigm with next generation technologies such as internet of vehicles (iov), internet of energy (ioe) etc, for development of middleware for maas architectures is still a nascent research thrust [34]. analytics of dynamically generated voluminous datasets tosc architecture becomes very expensive under the pay per use computation paradigm. indeed, the computation expenses vary linearly with the task size and execution time, thus forcing the data scientists to incur heavy investments on storage and analysis. thus, it opens a doorstep for the industry research and development communities to perform progressive analytics using domain specific sampling strategies to ensure effective user control, determinism and provenance for optimal and commercial viable deployment 2. performance, reliability and qos the incentives of v2c framework is primarily dedicated to promote development of intelligent vehicular services and offer a range anxiety free drive to the naïve xev users. the tosc infrastructure assembles the distributed cloud platforms to co-work with each other for smooth and reliable operation of its entities. however, maintaining an optimal balance in the distribution of data, control and computation among the dedicated cloud-cloudlets decides the performance of the system. commercial realization of the notion of cot from billions of sensors and low power devices in a sensor network and connectivity with the data centers demand reliable and permanent sources of energy. efficient fabrication techniques can enable the sensors to generate onsite power from renewables and environment [35]. the v2c paradigm employs dynamic and adhoc data clouds, so intermittent vehicular networking will hamper the service quality. the mesh created by seamless communication among cloud-cloudlet utilities will create galactic volumes of information to flow across the interfaces and data centers, thus uncertain network & communication failure will adversely affect the execution of v2c infrastructure. intelligent controllers and gateways coupled with mobile networking paradigms can manage the connectivity control of distributed and networked cloud resources in toscs cyber infrastructures [36], [37]. for successful installation of the proposed tosc infrastructure, regular checkpoints can be established to assess the following objectives: 1. effect on business strategies adopted by tosc utility companies in case of fluctuation in performance and qos parameters. 2. quantifying the tolerance, response and adaptation of the v2c customers towards risk factors such as latency, variability, power outages, queuing delay etc. 3. development of real-time evaluation strategies to measure the performance, synchronization, reliability and service quality tosc data clouds. 3. cost uncertainty being numerous cloud utility offerings available on the market with varying pricing schemes, decisions on selecting the one commercially optimal to tosc entities needs to be standardized. a budding informatics thrust is to evaluate the complexity and financial viability of cloud service deployments in price diverse environments. the infrastructure assembles multiple cloud genres into a common platform, thus uncertainties in pricing models is obvious. the stakeholders if are aware of the future service tariffs and incentives, will allow them to ponder for the optimum. 4. security security is among the prime issues in a typical data driven tosc, as the transportation utility vendors may agonize for the repercussions if the privacy of entrusted cloud data is compromised. due to the dynamic nature of a transportation and sg infrastructures, it becomes nearly infeasible to create coherent cross-cloud trust relationships. further, existence of complex relationships and dependencies among varying range of stakeholders in contemporary smart cities hinder the compatibility and cost effectiveness of data clouds employed in toscs. global security standards are essential to cope up with such privacy and flexibility concerns. decisions regarding selective migration of information hosted in private clouds and vehicular cloudlets to the public storage space require rigor research. robust and fine grained authorization protocols and access grants should be defined to ensure multiple accesses to federated cloud repositories. the centrally managed access control policies adopted by sdns in can cause vulnerabilities and cyber threats for tosc network topologies. the infrastructures involved in controlling 9 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e2 federated cloud analytics frameworks in next generation transport oriented smart cities (toscs) flow dynamics can be susceptible to both active and surreptitious threats caused by method specific, target specific, identity specific and software specific attacks. the attack list can be control plane saturation attack, spoofing, tampering, repudiation, information disclosure, dos, and elevation of method etc [32]. thus the integration of sdns to toscs presents ample unique research prospects and challenges to security and networking scientists. 5. high performance analytics integration of human machine interaction (hmi) utilities into current intelligent transportation having an elegant communication and computational support opens a doorway for commercial and automotive communities to transform notions of emerging technologies viz. social internet of vehicles (siov) [38], social transportation [14], vehicular crowdsourcing [39], platoon research [40] etc, from concept phase to implementation phase. analytics in such domains will enrich the reliability of decisions obtained in toscs and extend the service range to infotainment, safety, traffic scheduling etc. the underutilized vehicular resources if pooled properly, will create realm of supercomputers which can act as beds for real-time as well as offline analytics [16]. predicting future trend from example data streams forms the basis for an online algorithm and is an efficient method for load prediction and monitoring. the federated cloud computing utilities when coupled to physical systems and cyber systems form cyber physical clouds (cpc). cpcs constitute “cyber” of cyber physical systems (cps) and their services can be adopted by sgs, aggregators, independent system operators (iso) as well as xev users in social environments as defined by [38],[41], to enhance the controllability, efficiency and reliability of the transport oriented cities. 7. conclusions in this work the notion of transport oriented cities (tosc) is established that comprises of intelligent entities like smart grid, smart charging station, smart car and smart meter and the interaction among these entities is coordinated through the deployment of a federated cloud-cloudlet infrastructure. the hierarchical cloud framework optimally control and monitor the components and entities involved in operation of a transport oriented smart city. a comprehensive and commercially viable realization of vehicle to cloud (v2c) model for smart and coordinated charging of the xev fleet is proposed. the cloud data centers are endowed with high performance computational elements and robust data analytics algorithms for delivering a real time solution to achieve smart charging management of smart xevs fleet supporting the criterion triad namely 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[41] m. nitti, r. girau, a. floris, l. atzori, and s. member, “on adding the social dimension to the internet of vehicles : friendship and middleware,” 2014 ieee international black sea conference on communications and networking (blackseacom), pp. 134–138, 2014. 11 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e2 federated cloud analytics frameworks in next generation transport oriented smart cities (toscs) smart grids and load profiles in the gcc region i̇slam şafak bayram12 1qatar environment and energy research institute, hamad bin khalifa university, education city, doha, qatar 2college of science and engineering, hamad bin khalifa university, education city, doha, qatar abstract the members of the gulf cooperation council (gcc), namely qatar, bahrain, saudi arabia, kuwait, oman, and united arab emirates (uae), are facing challenges to meet the growing electricity demand and reduce the associated hydrocarbon emissions. recently, there has been a pressing need for a shift towards smart power grids, as smart grids can reduce the stress on the grid, defer the investments for upgrades, improve the power system efficiency, and reduce emissions. accordingly, the goal of this paper is to delineate an overview of current smart grid efforts in the gcc region. first, we present a detailed overview of the current state of the power grids. then, we classify the efforts into three broad categories: (i) energy trading and exchange through gcc interconnection; (ii) integration of renewable resources; and (iii) demand side management technologies for shaping the demand profile. furthermore, we provide the details of our api object level real-time gcc power demand automated program that creates the database for the load profiles of the gcc members. accessing such information for research and development purposes is a critical step in the region, because due the conservative structure of the governing institutes, there is no publicly available dataset. therefore, the data provided in this paper is critical and will serve as a main reference for the future research efforts. received on 14 november 2016; accepted on 07 september 2017; published on 19 december 2017 keywords: smart grids, gcc region, load profiles copyright © 2017 islam safak bayram, licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.19-12-2017.153476 1. introduction over the last few years, the fast-growing energy needs in the gcc region has intensified a central challenge: how to reduce the cost power systems operations and minimize the hydrocarbon emissions. as the significant portion of the gcc economies relies on oil and gas reserves, the gcc governments show growing amount of interest to diversify their economies for the postcarbon era. moreover, the drastically decreasing oil prices have pressed the need for investigation of smart grid technologies and efficient usage of resources. overall, there are three primary group of interest: (1) energy exchange among neighboring states to improve power system stability; (2) integration of renewable resources to reduce carbon emissions; and (3) demand response programs to shape the load profile and lessen the cost of system operations. one essential element of such efforts is the gcc interconnection grid that connects the power systems of six member countries. ∗corresponding author. email: ibayram@qf.org.qa the integration is expected to transform the region into a significant energy hub, and the network is envisioned to expand to other parts of the world, e.g., sell electricity to north african countries and southern europe. the six gcc members are endowed with a significant portion of the world’s hydrocarbon resources: 33.9% of the proven crude oil and 22.3% of the proven natural gas resources reside in the region. owning such rich and abundant resources have boosted the economies and transformed the region within a mere of two decades into the world’s wealthiest nations (in term of gdp per capita as depicted in figure 1a). in addition to the economic boom, high fertility rates, increasing population of expats, and the desire for a better standard of living have lead to a steady rise in electricity demand. the population growth respect to year 1995 is shown in figure 1b. the results show that the population of qatar is almost tripled within the last two decades and there are similar patterns in the other nations. moreover, the trajectory depicted in figure2a shows the enormous energy demand in each country. moreover, gross domestic product per capita 1 eai endorsed transactions smart cities research article eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e1 http://creativecommons.org/licenses/by/3.0/ mailto:<ibayram@qf.org.qa> islamsafak bayram 1995 2000 2005 2010 0 20 40 60 80 100 120 years (1995−2013) g d p p er c ap it a (i n 1 0 0 0 u s d ) real gdp per capita in the gcc region qatar bahrain saudi arabia kuwait oman uae usa uk (a) gross domestic product growth over the years. 1995 2000 2005 2010 0 50 100 150 200 250 300 years (1995−2013) p o p u la ti o n ( % ) r es p ec t to 1 9 9 5 population growth of gcc members qatar bahrain saudi arabia kuwait oman uae (b) populationgrowthoverthe years. 1995 2000 2005 2010 0 10 20 30 40 50 60 70 years (1995−2010) c o 2 p er c ap it a em is si o n s (m et ri c to n n es ) co2 per capita emissions in the gcc region qatar bahrain saudi arabia kuwait oman uae usa uk (c) carbonemissions 1995-2010 [22]. figure 1. key indicatorsfor energy consumption. 1995 2000 2005 2010 0 50 100 150 200 250 300 years (1995−2013) e le ct ri ca l e n er g y ( t w h ) electrical energy generation in gcc qatar bahrain saudi arabia kuwait oman uae (a) aggregatedenergy generation. 1995 2000 2005 2010 0 10 20 30 40 50 60 70 years (1995−2013) in st al le d c ap ac it y ( g w ) installed electricity generation capacity in gcc qatar bahrain saudi arabia kuwait oman uae (b) installedgeneration capacities. 1995 2000 2005 2010 0 10 20 30 40 50 60 years (1995−2013) p ea k e le ct ri ci ty d em an d ( g w ) peak electricity demand in gcc qatar bahrain saudi arabia kuwait oman uae (c) peak powergeneration1995 − 2013. figure 2. increasingenergy demandin the gcc is an important determinant of energy usage. the gdp growth, not only increase the energy demand, but also rendered the region among the most carbon-intensive countries in the world. according to 2010 world bank data, qatar, kuwait, oman, and uae are the top four nations with the highest emissions per capita [22] and an overview of carbon emissions is depicted in figure1c. another primary driver behind the rise in energy consumption is that gcc governments provide substantial subsidies both in electricity and oil tariffs. this policy serves as a means to redistribute the wealth among the citizens. however, reduced tariffs have lead to several adverse impacts. first, low prices translated into overconsumption of energy resources. the majority of the residential energy is consumed for air-conditioning and potable water, the bulk of which comes from energyintensive desalination of sea water. second, the gcc governments are facing a fiscal pressure as the volatility in the international markets combined with the foregone export revenues due to over-consumption fuels represent a sizable portion of the national budgets [10]. third, the increasing levels of carbon emissions due to high consumption raises economic concerns. the aforementioned issues have pressed the gcc members to reform the power systems through smart grids. in order to provide the motivation for smart grids, in section 2 we give an overview of the current power grids. then, in the next three sections we present a systematic the overview of gcc interconnection grid, renewable energy integration efforts, and current demand side management programs in the region. 2. current power grid operations 2.1. overview the first gcc power grids were built in the early 50s when there was a need for electricity for oil drilling. with the incline of the oil prices, the region gained significant financial wealth, and the modern power grids were built in the 80s. compared to western grids, the gcc grids are younger and equipped with modern components. on the other hand, the region often experiences excessively hot days during summers. in such periods, the demand for cooling raises tremendously thus leading to regional blackouts and threatens the security of the supply. hence, system operators are continuously seeking ways to expand the system capacity to secure the supply. 2 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e1 smart gridsand load profile in the gcc region table 1. percentageof generationmixin the gcc. natural gas (ng)andoil are considered. qatar bahrain saudi arabia kuwait oman uae ng(%) ng(%) ng(%) oil(%) ng(%) oil(%) ng(%) oil(%) ng(%) oil(%) 1996 100 100 44.15 55.85 62.43 37.57 82.55 17.45 96.63 3.37 2000 100 100 46.03 53.97 32.92 67.08 82.83 17.17 96.91 3.09 2004 100 100 56.95 43.05 27.68 72.32 82.00 18.00 97.66 2.34 2008 100 100 48.83 51.17 35.65 64.35 97.83 2.17 98.29 1.71 2012 100 100 44.69 55.31 36.22 63.78 97.58 2.42 98.62 1.38 even though the region was served by vertically integrated utilities, typically owned by the governments, the gcc members are reforming the sector by unbundling the power generation, transmission, and the distribution segments. this will encourage private sector investments, which will allow the private sector to generate and sell electricity to the customers [6]. the primary drivers of this transformation are the need for improved operational efficiency and the fact that the private sector can quickly respond to economic and technological changes. the sultanate of oman is leading the privatization process. oman is the first member country that allows independent system operators to generate and sell electricity to government authority, which handles transmission and distribution lines. currently, in all members except kuwait, the generation sector is operated by private sector and independent power producers. in kuwait, the generation side is still operated by the government. the electricity dispatch curve is also an important parameter for the smart grid operations. since, the oil and natural gas reserves are abundant in the region, the power generation depends entirely on these two sources. in table 1, we present the generation mixture of the member countries over the years. the table reveals an interesting fact that the cost of producing electricity is quite different among the members. for instance, qatar and bahrain have plenty of natural gas resources, hence hundred percent of the electricity is generated by fossil fuels. however, relying entirely on natural gas reduces the ramping capabilities of the generation, therefore, these countries have to waste a sizable portion of their resources on not necessary lighting of skyscrapers. on the other hand, countries like saudi arabia and kuwait produce a significant portion of the electricity through diesel generators. considering the cost and negative environmental impacts of such generators, the interconnection of power grids would provide a good level of savings. for instance, kuwait and saudi arabia could purchase electricity from qatar and eliminate the need for running diesel generators. moreover, the gcc members are seeking ways to accommodate the growing demand in through diversifying their generation portfolio. united arabic emirates is building nuclear power plants to be operated by 2017 [23] in order to meet the 7% annual demand growth. according to dubai integrated energy strategy 2030, the utility of dubai is aiming to meet 71% of the demand from natural gas, 12% from nuclear power, 12% from clean coal, and 5% from renewables. also, qatar, saudi arabia, and uae have put goals to integrate gigawatt level solar farms. the details will be given in the next section. 2.2. pricing& customertypes the electricity tariffs are the primary control mechanisms to shape the customer demand profile. in the business of electric utilities, the unit electricity cost is calculated through locational marginal prices (lmp) that takes into account various factors such as generator type and cost, distances to load, etc. lmp reflects the marginal cost of supplying an increment of load at each node. lmp are determined in the wholesale market via a bidding structure and details can be found in [12]. the pricing in the gcc region, however, is lower than the marginal prices as the governments provide subsidies to redistribute the wealth to the citizens. for instance, according to [10] the total subsidies in 2011 for electricity exceeded 29 billion dollars in the gcc region. by considering the populations across the nations, the yearly subsidy per capita can be found as 556.5, 1510.1, 166.9, 1206, 522.28, and 770.81 us dollars for bahrain, kuwait, oman, qatar, saudi arabia, and uae, respectively. the current electricity prices are publicly available on the utility of each country, and we present an overview of the prices in figure3. in the case of saudi arabia, for example, the electricity cost is one-fifth of the average us prices. also, in the state of qatar, the power consumption of the local citizens are entirely subsidized by the government. in 2013 the subsidies for the energy (oil, gas, and electricity) accounted for 60 − 80% of the original cost. however, the decreasing oil prices in the last two years forced policy-makers to take drastic measures. for instance, uae removed the subsidies in transport fuel in late 2015 and other gcc members are expected to follow this new policy and introduce taxes. subsidized energy can, however, lead to a range of unintended adverse impacts, as 3 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e1 islamsafak bayram 0 2 4 6 0.01 0.02 0.03 0.04 energy demand (mwh) e le ct ri ci ty p ri ce ( $ /k w h ) electricity tariffs in qatar residential commercial industrial 0 2 4 6 0 0.02 0.04 0.06 energy demand (mwh) e le ct ri ci ty p ri ce ( $ /k w h ) electricity tariffs in bahrain residential commercial industrial 0 2 4 6 0.01 0.02 0.03 0.04 energy demand (mwh) e le ct ri ci ty p ri ce ( $ /k w h ) electricity tariffs in saudi arabia residential/commercial industrial 0 2 4 6 0.03 0.04 0.05 0.06 energy demand (mwh) e le ct ri ci ty p ri ce ( $ /k w h ) electricity tariffs in kuwait residential/commercial industrial 0 2 4 6 0 0.2 0.4 0.6 0.8 energy demand (mwh) e le ct ri ci ty p ri ce ( $ /k w h ) electricity tariffs in oman residential industrial−summer industrial−winter 0 2 4 6 0.075 0.08 0.085 0.09 0.095 0.1 energy demand (mwh) e le ct ri ci ty p ri ce ( $ /k w h ) electricity tariffs in uae residential/commercial industrial figure 3. electricity tari˙s obtainedfromqatar [15], bahrain[16]. saudi arabia [17], kuwait [18], oman[20], uae [19]. weight of subsidies on fiscal balances % of gdp % of fiscal expenditures bahrain ksa uae qatar kuwait oman source: international monetary fund 5 10 15 get the data created with datawrapper figure 4. the e˙ects of energy subsidies on fisca balances in year 2015. it distorts price signals for consumers, with serious consequences for energy efficiency and the optimal allocation of resources. low tariffs have lead to overconsumption of energy resources. the majority of the residential energy is consumed for air-conditioning and potable water, the bulk of which comes from energy-intensive desalination of sea water. moreover, the gcc governments are facing a fiscal pressure as the volatility in the international markets combined with the opportunity cost incurred of exporting overconsumption fuels represent a sizable portion of the national budgets [10]. figure 4 depicts that subsidies in the energy sector have started to represented sizable portion of the fiscal balances. traditionally electric utilities serve three different customer types namely, residential, commercial, and industrial. the customer types are differentiated by the amount of energy/power requirements and demand curves. at each member country, residential customers constitute the vast majority of the meters and we provide this is mainly because the industry is limited to oil and gas and severe weather and limited water resources restrict the agricultural activities. unlike industrial and commercial customers, the energy demand of residential customers has high variability. this behavior increases the power system operating cost and reduce system utilization. hence, this state of affairs contain an enormous potential for demand response programs for peak shaving. 2.3. qatar powergrid the national grid in qatar is operated by the qatar general electricity and water corporation (kahramaa) since year 2000. kahramaa manages more than 12000 substations, 2700 km transmission lines and 2000 overhead lines. the rating of the transmission and distribution network is 400/220/132/66/11 kv. over the last decade, kahramaa has taken bold actions to upgrade the transmission and the generation components to provide a quality performance to its customers. from the generation sector standpoint, even though the peak demand has been steadily increasing, e.g., from 5 gw in 2010 to 7 gw in 2015, the spare capacity is still in the order of 2 − 3 gw. moreover, the transmission network performance indicators are 4 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e1 smart gridsand load profile in the gcc region domestic (22.2twh) 57% bulk industrial (11.5twh) 30% transmission losses (2.3twh) 6% auxiliary (2.5twh) 7% qatar sectoral energy consumption in 2014 (a) energyconsumptionby sector in qatar (2014). 05/14 07/14 09/14 11/14 01/15 03/15 05/15 2000 3000 4000 5000 6000 7000 8000 9000 dates (mm/yy) q at ar p ea k s y st em d em an d ( m w ) qatar yearly load profile system demand installed capacity (2013) (b) qatar demandprofil in year 2014. qatar maximum and minimum demand (mw) in 2014 max day (7-sept-14) min day (12-feb-14) 0 :3 0 1 :0 0 1 :3 0 2 :0 0 2 :3 0 3 :0 0 3 :3 0 4 :0 0 4 :3 0 5 :0 0 5 :3 0 6 :0 0 6 :3 0 7 :0 0 7 :3 0 8 :0 0 8 :3 0 9 :0 0 9 :3 0 1 0 :0 0 1 0 :3 0 1 1 :0 0 1 1 :3 0 1 2 :0 0 1 2 :3 0 1 3 :0 0 1 3 :3 0 1 4 :0 0 1 4 :3 0 1 5 :0 0 1 5 :3 0 1 6 :0 0 1 6 :3 0 1 7 :0 0 1 7 :3 0 1 8 :0 0 1 8 :3 0 1 9 :0 0 1 9 :3 0 2 0 :0 0 2 0 :3 0 2 1 :0 0 2 1 :3 0 2 2 :0 0 2 2 :3 0 2 3 :0 0 2 3 :3 0 0 :0 0 2,000 4,000 6,000 get the data created with datawrapper (c) qatar hourlyload profile formaxandminusage days in 2012. figure 5. increasingenergy demandin the gcc maximum and minimum system load in qatar max min 2010 2011 2012 2013 2014 kahramaa statistics report 2014 2,000 4,000 6,000 (a) maximumandminimumenergyconsumptionin qatar. qatar energy consumption in 2014 (mwh) m o n th 2,056 j a n u a ry 1,882 f e b ru a ry 2,411 m a rc h 2,901 a p ri l 3,685 m a y 3,928 j u n e 4,419 j u ly 4,431 a u g u s t 4,179 s e p te m b e r 3,783 o c to b e r 2,725 n o v e m b e r 2,287 d e c e m b e r kahramaa statistics report 2014 1,000 2,000 3,000 4,000 (b) qatar energy consumptionper monthin year 2014. qatar key statistics 2014 system domestic industrial demand growth (%) from 2013 load factor (%) 20 40 60 80 (c) demandgrowthand load factor. figure 6. statistics of qatari nationalgrid in 2014 bahrain electricity consumption per sector (mwh) source: kingdom of bahrain central informatics organization 113 2,000 4,000 6,426 2002 ’04 ’06 ’08 ’10 2012 domestic commercial industrial (a) energy consumptionby sector in bahrain. bahrain energy consumption in 2013 (mwh) 745 j a n u a ry 688 f e b ru a ry 859 m a rc h 1,102 a p ri l 1,396 m a y 1,533 j u n e 1,786 j u ly 1,784 a u g u s t 1,688 s e p te m b e r 1,295 o c to b e r 990 n o v e m b e r 836 d e c e m b e r 500 1,000 1,500 (b) electricityconsumptionpermonthin bahrain. bahrain peak load in 2012 (mwh) 1,360 j a n u a ry 1,492 f e b ru a ry 1,786 m a rc h 2,193 a p ri l 2,988 m a y 3,040 j u n e 3,034 j u ly 3,152 a u g u s t 3,106 s e p te m b e r 2,674 o c to b e r 2,074 n o v e m b e r 1,509 d e c e m b e r 1,000 2,000 3,000 (c) peak load per monthin bahrain. figure 7. bahrain powergridstatistics also very positive. in 2013 and 2014, the cumulative number of minutes that the transmission system was compromised due to failures was less than 20 seconds at each month. next, we present the key statistics for qatar. in figure 5a, we show the energy consumption by sector. it can be seen that majority of the electricity is consumed by domestic customers due to high demand for cooling. the country load profiles, daily, monthly, or yearly contain valuable information on the applicability of the potential smart grid applications. in the case of gcc members, the load profiles reveal how much energy can be exchanged and determine the possible integration renewables and demand response technologies. currently, there is no publicly available load profile data in any of the member states. however, the electric utility of qatar regularly shares the peak system usage on their social media page. hence, we developed a simple data scraping software to collect the data for the last twelve months. we present the yearly load profile of qatar in figure 5b. it can be seen that the peak demand occurs in august when the school season 5 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e1 islamsafak bayram dubai power grid statistics installed capacity (mw) peak demand (mw) 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 source: www.dewa.gov.ae 2,000 4,000 6,000 8,000 (a) dubaipowergridstatistics. domestic (10.8twh) 27% bulk industrial (3.6twh) 9% commercial (18.4twh) 47% auxiliary (3.2twh) 8% others *3.2twh)8% (b) energy consumptionby sector in dubai (2014). peak monthly demand in united arabic emirates (2014) peak demand (mw) available generation (mw) j a n f e b m a r a p r m a y j u n j u l a u g s e p o c t n o v d e c 5,000 10,000 (c) uae peak demandstatistics (2014). figure 8. unitedarabic emirates powergridstatistics starts and there is a high demand for air conditioning. moreover, the work in [24] states that there is a linear correlation between the daily peak temperature and the daily peak consumption for days that are warmer than 22 celsius. moreover, the seasonal gap between the winter and the summer demand leads to unused system capacity that can be used trade electricity between neighboring countries. this is better depicted in figure 5c, where we show the half-hourly demand profile of two sample days from 2014: the first one is the day with the peak system demand (september 7, 2014) and the second is the day with the lowest customer demand (february 12, 2014). the results show that there is a high potential to employ demand response techniques to control electricity consumption, in particular for the air conditioning load. figures 6a, 6b and 6c depicts the further statistics for qatar, namely maximum and minimum system load over the years, energy consumption per month and load factor for each sector. it can be seen that the grid operations are mainly shaped by the human activities. 2.4. bahrain powergrid the power grid in the kingdom of bahrain is operated by the electricity and water authority. bahrain is physically the smallest (770 km2 of the six gcc members and contains the lowest number of inhabitants as well. according to 2012 statistics, the number of transmission substations and their ratings are as follows: there are 10 substations with 33 kv, 114 substations with 66 kv, and 21 substations with 220 kv. the physical length of the transmission lines are 775, 300, and 44 km for 66 kv, 220 kv, and 33 kv, respectively. the statistics of bahrain national grid is similar to qatar. the energy consumption is dominated by the domestic usage (depicted in figure 7a).the peak and the aggregated energy consumption is high at summer seasons as well. the related grid profiles are shown in figures 7b and 7c, respectively. 2.5. unitedarabic emirates powergrids the power grids in united arabic emirates is operated by five authorities, namely abu dhabi water and electricity authority (adwea), dubai electricity and water authority (dewa), sharjah electricity and water authority (sewa), and federal electricity and water authority (fewa) for northern emirates. uae is the second largest member of the gcc and the first member to deploy nuclear power plant in the region. in order to gain more insights, we provide details for the dewa because it is the largest utility in uae. according to 2014 statistics, the number of transmission and distribution substations for the 400/132/33/11 kv are 19, 201, 123, and 28874 respectively. the physical length of the corresponding overhead (ohc) and underground cables (uc) are 1142, 2075, 2487, and 26876 km, respectively. the number of customers in 2014 was 677751. the customer portfolio has also similarities with bahrain and qatar, as 73% of the customers are residential. 24.87% constitutes the commercial customers, just 0.37% is the industrial customers, and the rest is the non-commercial government buildings (e.g., hospitals, schools, etc.). as depicted in figure 8a, dewa has been expanding its generation capacity to keep up with the increasing peak demand. the performance of the dewa grid is also remarkable solid: the customer minutes lost was 5.62 minutes in 2013 and the power losses were 3.46%. the customer portfolio is presented in figure 8b for dubai and the peak generation (mw) is given in figure 8c. 2.6. kingdomof saudi arabia powergrid the kingdom of saudi arabia is the largest member of the gcc in terms of population, economy, and 6 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e1 smart gridsand load profile in the gcc region energy production by plant type 2013 (gwh) 2014 (gwh) diesel combined-cycle gas steam 0,000 40,000 60,000 80,000 (a) electricity generationby type (2013-2014). domestic (135.9twh) 50% bulk industrial (51.5twh) 19% commercial (42.2twh) 15% govermental (35.6 (twh)13% other (9.2twh)3% (b) energy consumptionby sector in ksa (2014). ksa peak demand (isolated & interconnected networks) interconnected (2013) interconnected (2014) isolated (2013) isolated (2014) total peak (2013) total peak (2014) peak demand (mw) 20,000 40,000 (c) ksa peak demandstatistics (2014). figure 9. nationalgridof kingdomof saudi arabia (ksa)statistics oman maximum and minimum demand peak load (mw) minimum load (mw) 2005 2006 2007 2008 2009 2010 2011 2012 2013 1,000 2,000 3,000 4,000 (a) minimumandmaximumdemandinoman(2005-2013). domestic (4.2twh) 48% commercial (2.3twh) 27% govermental (1.6 (twh) 19% other (0.5twh) 6% (b) energy consumptionby sector in muscot region (2014). system availability in oman (%) 97.7 2005 98.23 2006 95.99 2007 98.49 2008 97.76 2009 98.46 2010 99.33 2011 99.65 2012 99.23 2013 20 40 60 80 (c) omanpowergrid availability statistics. figure 10. omannationalgridstatistics the power grids. the power grids are operated by the saudi electric company which is a government owned monopoly. in 2014, the generation capacity of ksa was 65 gw delivering power through 554 254 km transmission and distribution lines to more than 7.6 million customers residing in 13 thousand cities and settlements. the changes from 2013 to 2014 suggests that the power grids in ksa are significantly growing: the generation capacity is expanded by 5.9%, the 6.4% increase in the number of customers has lead to 8.0% increase in the peak load. moreover, transmission and distribution networks are grown by 10.1% and 7.1%, respectively and the network losses (both distribution and transmission) added up to 7.5%. the power grid in ksa, more formally named as the national grid sa, is divided into four regions: central region, eastern region, western region, and southern region. figures 9a, 9b, and 9c provides more insights for the national grid sa. figure 9a shows the percentage of different power plant types in ksa. figure 9b shows the electricity consumption by sector, which is similar to other gcc members: the majority of the electricity is consumed by residential customers mostly for cooling needs. moreover, figure 9c shows the peak demand for domestic 60% industrial 20% commercial 14% govermental 5% agriculture 1% figure 11. kuwait customerprofil in 2009. interconnected grid and isolated networks. as given in the next section, ksa contains a considerable amount of scattered and remote settlements, which are not connected to the main grid. the peak demand for such electrified region reaches up to 2.4 gw, which puts additional financial burden on the utility operator. 7 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e1 islamsafak bayram 2.7. omanpowergrid the omani power grid serves 754 000 three distribution regions served by muscat, mazoon, and majan electricity companies. the transmission grid (220/132kv) is owned and operated by the oman electricity transmission co. and the 400kv connection to gccia grid is yet to be operational, as of january 2016 [1]. the performance figures for the transmission system in 2013 is as follows. the system availability was 99.23%, the average interruption time was 34 minutes, and the unsupplied energy accounted for 1418 mwh [2]. the statistics given in figures 10a, 10b, and 10c provides more insights. the minimum and the maximum demand between 2005 and 2013 is depicted in figure 10a, which shows the huge gap due to hot summer seasons. similar to other members, the majority of the electricity is consumed by residential customers. in muscat region, the biggest distribution grid operator, almost 50% of the electricity is consumed domestically. moreover, figure 10c shows the system availability of the entire power grid. 2.8. kuwaitpowergrid the power grids in kuwait are vertically integrated and they are owned and operated by a the ministry of electricity and water (mew). the grid is entirely dependent on two sources: oil and gas. the stateowned organization, kuwait petroleum corporation is the main supplier of these two fuels and the primary planning driver for the generation and network development are residential housing and commercial projects. the power grid is composed of five voltage levels 400, 275, 132, 33, and 11 kv. 3. gcc interconnected power grid 3.1. overview the interconnection of gcc power grids can be viewed as the first major smart grid activity. the main drivers of the interconnection grid are: (1) cost efficiency; (2) shared spinning reserves; (3) deferred and reduced capacity investments; (4) lower carbon emissions; and (5) development of power markets. the growing energy demand (almost 10% annually) and the sudden demand surges frequently threaten the supply thus requiring costly investments. for example, in figure 2b we present the steady increase in generation capacity expansion for each country. consequently, as shown in figure 2c the peak electricity demand increases and leads to higher operation cost. furthermore, according to the study conducted in [6], there would be a need to invest one hundred billion dollars to meet the growing demand of gcc over the next decade. on the other hand sharing generation and transmission resources can alleviate the upgrade requirements. hence, the interconnection is of paramount importance. the architecture of the gcc interconnected grid presented in figure 12a and the milestones of the project is given in figure 12b. currently, member states are in the phase of creating a power market for energy trading. the real challenge in developing this platform is to find right pricing schemes as the subsidies vary significantly across the region. the benefits of the interconnection grid summarized next. 3.2. benefit the benefits of the gcc interconnection grid is multifaceted. from an economic standpoint, the benefits include improved supply security, higher energy efficiency and savings through sharing spinning reserves. also, the interconnection will reduce additional investments, and operational and maintenance cost. for instance, if saudi arabia can reduce total installed capacity by 2gw, the total savings could be more than $309 million [6]. also, it is estimated that there will be a $180 million us dollars of savings in fuel operating costs from the entire region. moreover, in the case of emergencies the interconnection can provide energy supply. in fact, the security of power supply is one of the primary motivations behind the interconnection grid. according to [9], the gcc power network has prevented 250 sudden power loss incidents among the various member states. the gcc grid can also help to reduce the carbon emissions caused by the using crude oil. countries such as kuwait and saudi arabia can purchase electricity produced from natural gas, nuclear power, or solar from other countries. also, with the help of the proper regulations, independent power producers already started to generate profit through energy exchange. moreover, the member states are considering to create an energy market that can trade electricity with countries like egypt, jordan, iraq, lebanon, syria, and turkey. 3.3. currentstatus since 2009, the gcc members invested around $1.2 billion us dollars to build 900 km long 400kv transmission lines and 7 400 kv substations, and a 1800 mw three-pole back-to-back high voltage direct current (hvdc) converter stations. the connection with bahrain is made with a submarine cable [31]. the hvdc stations are being use to synchronize the 60 hz saudi arabia grid with the rest of the members who are using 50 hz. off note, the hvdc stations located in the gccia is the biggest back-to-back substation in the world that allows sharing of spinning reserves between 60 and 50 hz systems. since 2009, the gcc interconnection grid has been operational and it has improved the security and reliability of the network. according to gcc 8 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e1 smart gridsand load profile in the gcc region energy exchange in gccia export (gwh) import (gwh) qatar bahrain ksa kuwait uae 50 100 150 (a) energy exchange for systemsupport during2014. number of mutual support instances 35 2009 208 2010 178 2011 254 2012 197 2013 226 2014 50 100 150 200 250 (b) numberof mutualsupport instancesamongfiv members. figure 13. the operationof gcc interconnectiongrid forpowersystemstability. saudi arabia kuwait bahrain qatar omanuae 100km 90km 53km 3 1 0 k m 1 1 2 k m 2 9 0 k m 1 5 0 k m 1200mw 600mw 750mw 400mw 9 0 0 m w 1 2 0 0 m w 2 0 0 k v 2 0 0 k v 200kv 400kv 400kv 400kv 400kv 400kv 400kv (a) electricitymapof the gcc grid[21] gccia formation by royal decree2001 phase 1: initial contracts awarded2005 uae own reinforcement2005 gccia became operational2009 first energy exchange2010 phase 3: uae grid synch.2011 phase 3: oman grid synch.2011 power market establishment2015 (b) gcciamilestones. figure 12. gcc interconnectiongrid overview interconnection authority 2014 annual report, more than 1000 incidents occurred between 2009 and 2014. in figure13b, we present the number of mutual support instances among the member states. notice that oman is excluded from the lists as oman was not connected to the network until 2014. mainly, the interconnected grid ensured that the system operates at the right frequency and voltage standards. moreover, it prevented the system from demand disconnections. for this reason, member states exchange energy through high transmission lines. for instance in 2011, 680 gwh of energy was exchanged between the members and figure 13a shows the amount of energy exports and imports of each gcc member. 4. renewable energy integration the gcc region is endowed with one of the world’s most abundant solar resources and the integration of renewable energy has attracted systematic interest by the governments. the main drivers behind the solar energy are to minimize the electricity generation and reduce the carbon emissions. for end-users, solar generation is expected to have two applications. in the first one, consumers can install pv panels to their rooftops and generate electricity for domestic usage and sell the excess power back to the grid. recently, uae became the first gcc member to allow customers to employ solar rooftops. one key issue is that the region demographics include a significant number of remote scatters farms and villages. typically these locations operate off-grid and burn diesel generators, as the integration of the main grid is not economically viable. hence, the second application would be to run solar panels in off-grid mode that will eliminate the need for burning crude oil. 4.1. goals & potentialanalysis the global horizontal irradiance (ghi) defines the average electricity generated from photovoltaic systems. the measured ghi for the gcc members are 2140, 2160, 2130, 1900, 2050, and 2120 kwh/m2/year for qatar, bahrain, saudi arabia, kuwait, oman, and uae respectively. concentrating solar thermal power (csp) systems are also widely used for solar energy 9 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e1 islamsafak bayram generation. for csp technology, direct normal irradiance (dni) is used to define the average electricity generation. the measured dni is 2000, 2050, 2000, 1900, 2200, and 2200 kwh/m2/year for qatar, bahrain, saudi arabia, kuwait, oman, and uae respectively. the gcc governments have set solar penetration goals for solar integration. for instance, qatar has a goal of putting 1gw solar panels by 2020 using photovoltaic systems. kingdom of saudi arabia, on the other hand, is aiming to build 41 gw csp by 2032. according to international renewable energy agency, kuwait seeks to create 10 mw photovoltaic and 50mw csp. similarly, oman aims to put 700mw solar capacity by 2020. uae, on the other hand, seeks to generate 15% of the total demand from solar generation by 2020. 4.2. barriers even though the region has a high potential for solar integration, the aforementioned goals cannot be achieved without addressing the following issues. the first problem is with the materials of the pv panels. the efficiency of the crystalline silicon-based photovoltaic solar cells degrade with high temperature and the current technology does not perform well in the region. hence, there has been a growing research and development interests in the region to develop new materials for pv panels for in high-temperature conditions which will also improve solar economics in the region. another barrier to solar integration is the soiling of pv panels due to dust deposition. this is a significant factor as the region frequently experiences sand storms and the performance of the solar systems degrade significantly. for instance according to a study conducted at qatar foundation (qf) [25], the power loss is around 10 − 15% per month on average. similarly, research activities in qf include developing anti-dust technologies such as hydrophobic coatings, robotic cleaners, and electrical shields. currently, renewable energy integration is very limited in the region because the cost of renewable energy systems compared to conventional electricity generation methods is still very costly. hence, there is pressing need to create new policies and incentives to push the solar generation into mainstream acceptance. also, utilities need to create a common standards and regulations and need to consider the effects of solar integration once the gcc grid is fully operational. 5. demand side management demand side management (dsm) refers to a set of rules and policies that aim to optimize the energy consumption at the end-user side. the most popular dsm programs that have been used in practice include energy efficiency, differential tariffs (e.g., timebased tariffs, dynamic pricing), and demand response programs. such programs are also becoming popular in the gcc region, as dsm programs can shave the peak demand and reduce the cost of system operations. the aforementioned subsidies provided by the governments have been discouraging the investments to efficient infrastructures. nevertheless, the gcc members recently started to invest in energy efficiency programs in buildings and transportation systems. for instance, qatar has launched a new energy conservation program called tarsheed, aiming to improve the energy consumption in residential and commercial buildings. similarly, in 2012 saudi arabia launched the saudi energy efficiency program in order to enhance the consumption. similar efforts are carried out in uae: dubai initiated a demand-side management committee to reduce energy demand by 30% by 2030. similarly, sharjah of uae has started a peak load reduction program that enforces citizens to turn off non-essential appliances during peak hours. the gcc members are gradually transforming their transportation systems from oil-based to electric-based [27, 28]. dubai is installing 100 charging stations. qatar is considering to employ electric vehicles for public transportation for the fifa 2022 world cup. smart meters and advanced metering infrastructures are critical enablers of demand side management. qatar utility company kahramaa already started to deploy 17000 smart meters in doha teamed up with siemens for the smart meters [5]. for the case of oman, the work presented in [26] shows that the long-term benefits of load management outweighs the required investments. one essential characteristic of the region is that the vast majority of the energy is consumed at residential units, mostly for air-conditioning. hence, with the help of the communication and sensor technologies, utilities can employ direct load control mechanisms to adjust the load while providing a good level of comfort. also, the integration of social sciences could help to reduce the peak usage. peer pressure is one of the most effective methods of reducing electricity consumption. for instance, a social study in california tries to motivate customers to reduce their consumption by comparing the individual bills with the average consumption of their neighbors. this method enables customers to reduce their consumption by 1.5 to 3.5 percent. our final recommendation is for coupling the solar generation with energy-intensive water desalination process. 5.1. load profile the important part of the demand side management is to analyze the load profiles and assess the potential of demand reductions. one of the major roadblocks that refrains scientist to conduct deeper research on demand side management and smart grids is the lack 10 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e1 smart gridsand load profile in the gcc region qeeri database web service qeeri server gccia website qatar ksa uae kuwait bahrain figure 14. the real-time gcc power demand automated program. of available datasets for load profiles. the main reason for this is the fact that most of the grids are operated by government agencies which follow conservative policies on data sharing. nevertheless, in this section we provide an overview of efforts on creating the first data repository of load profiles in the gcc region. to the best of our knowledge this is first effort that makes such data publicly available. as shown in figure 14, the load profiles of the five countries are stored at the gccia website. our automated program collects nation-wide information at every minute and stores it to sql database. in figures 15a, 15b, 16a, 16b, 17a, 17b, we present the average load profiles for june, july, and august 2015 for qatar, bahrain, saudi arabia, kuwait, uae, and aggregated gcc, respectively. notice that oman is not in the list because the omani grid is not connected to the gccia yet. the results reveal several important information. first of all, the demand for electricity follows the average temperatures, therefore, demand increases from june to august. another point is that the summer peak occurs once a day in the afternoon around 3 pm and the lowest demand occurs around 5 am before the sun rises due to cooler desert climate. moreover, the load curves prove that there is a great potential to use solar generation, because there is a correlation between the solar generation and the customer peak demand. 6. conclusion in this paper, we provided an overview of the gcc power grid and smart grid efforts. we showed that the interconnection of the grid would improve grid stability, lead to efficient resource usage, and reduce the operation cost. the integration of abundant solar resources and the implementation of dsm programs can be very useful to substitute diesel generators at remote farms and villages. references [1] oman power andwater procurement co. (2015) opwps 7-year statement (2015-2021). [2] oman power and water procurement co. (2013) transmission performance report. [3] oman power and water procurement co. (2013) transmission performance report. [4] el-katiri, l., husain, m: prospects for renewable energy in gcc states-opportunities and the need for reform. oxford institute for energy studies. (2014) [5] abdalla, g..: the deployment of advanced metering infrastructure, ieee first workshop on smart grid and renewable energy, doha, qatar (2015) [6] al-asaad, h.: electricity power sector reform in the gcc region, the electricity journal, vol. 22, issue 9, pp. 58 -64, nov, 2009 [7] shaahid, s.m., el-amin, i.: techno-economic evaluation of off-grid hybrid photovoltaic?diesel?battery power systems for rural electrification in saudi arabia a way forward for sustainable development, renewable and sustainable energy reviews, vol 13, issue 3, 2009 [8] may, p., ehrlich, h.c., steinke, t.: zib structure prediction pipeline: composing a complex biological workflow through web services. in: nagel, w.e., walter, w.v., lehner, w. (eds.) euro-par 2006. lncs, vol. 4128, pp. 1148–1158. springer, heidelberg (2006) [9] al-ebrahim, a.: super grid increases system stability. in transmission and distribution world (2012) [10] charles, c., moerenhout, t., bridle, r., the context of fossil-fuel subsidies in the gcc region and their impacts on renewable energy development, international institute for sustainable development (2014) [11] foster, i., kesselman, c.: the grid: blueprint for a new computing infrastructure. morgan kaufmann, san francisco (1999) [12] kassakian, j., schmalensee, r., the future of the electric grid: an interdisciplinary mit study, 2012 [13] czajkowski, k., fitzgerald, s., foster, i., kesselman, c.: grid information services for distributed resource sharing. in: 10th ieee international symposium on high performance distributed computing, pp. 181–184. ieee press, new york (2001) [14] foster, i., kesselman, c., nick, j., tuecke, s.: the physiology of the grid: an open grid services architecture for distributed systems integration. technical report, global grid forum (2002) [15] qatar general electricity and water corporation, http://www.km.com.qa/ [16] electricity and water authority of bahrain, http://www.mew.gov.bh/ [17] saudi electricity company, http://www.se.com.sa/ [18] ministry of electricity and water of kuwait, http://www.mew.gov.kw/ [19] abu dhabi water and electricity company, http://www.adwec.ae/ 11 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e1 islamsafak bayram 0 5 10 15 20 4.5 5 5.5 6 6.5 7 hour of the day (0−23) q at ar h o u rl y l o ad p ro fi le ( g w ) june 2015 july 2015 august 2015 (a) qatar load profile 0 5 10 15 20 2.2 2.4 2.6 2.8 3 3.2 hour of the day (0−23) b ah ra in h o u rl y l o ad p ro fi le ( g w ) june 2015 july 2015 august 2015 (b) bahrain load profile figure 15. the operationof gcc interconnectiongrid forpowersystemstability. 0 5 10 15 20 42 44 46 48 50 52 54 56 hour of the day (0−23) k s a h o u rl y l o ad p ro fi le ( g w ) june 2015 july 2015 august 2015 (a) kingdomof saudi arabia load profile 0 5 10 15 20 8.5 9 9.5 10 10.5 11 11.5 12 12.5 hour of the day (0−23) k u w ai t h o u rl y l o ad p ro fi le ( g w ) june 2015 july 2015 august 2015 (b) kuwait load profile figure 16. the operationof gcc interconnectiongrid forpowersystemstability. 0 5 10 15 20 15 16 17 18 19 20 21 22 hour of the day (0−23) u a e h o u rl y l o ad p ro fi le ( g w ) june 2015 july 2015 august 2015 (a) unitedarabic emirates load profile 0 5 10 15 20 75 80 85 90 95 100 hour of the day (0−23) g c c ( e x ce p t o m an ) h o u rl y l o ad p ro fi le ( g w ) june 2015 july 2015 august 2015 (b) aggregatedgcc load profile figure 17. the operationof gcc interconnectiongrid forpowersystemstability. [20] electricity holding company , http://www.electricity.com.om/ [21] gulf cooperation council interconnection authority, http://www.gccia.com.sa/ [22] the world bank, data.worldbank.org/indicator/en. atm.co2e.pc [23] emirates nuclear energy cooperation, http://www.enec.gov.ae/ 12 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e1 data.worldbank.org/indicator/en.atm.co2e.pc data.worldbank.org/indicator/en.atm.co2e.pc smart gridsand load profile in the gcc region [24] gastli, a., charabi, y., alammari, r., al-ali, a.: correlation between climate data and maximum electricity demand in qatar. in: ieee gcc conference and exhibition, doha, qatar (2013) [25] guo, b., javed, w., figgis, w., mirza, t.: effect of dust and weather conditions on photovoltaic performance in doha, qatar, in: ieee first workshop on smart grid and renewable energy, doha, qatar, (2015) [26] malik, a., bouzguenda, m.: effects of smart grid technologies on capacity and energy savings e a case study of oman, energy, vol.54, pp.365-371 (2013) [27] bayram, i.s., michailidis, g., devetsikiotis, m.: unsplittable load balancing in a network of charging stations under qos guarantees, ieee transactions on smart grid, vol.6, issue 3, pp. 1292-1302 (2015) [28] bayram, i.s., tajer a., abadllah, m., qaraqe, k.: capacity planning frameworks for electric vehicle charging stations with multiclass customers, ieee transactions on smart grid, vol.6, issue 4, pp. 1934-1943 (2015) [29] mohsenian-rad, m. : optimal demand bidding for time-shiftable loads, ieee transactions on power systems, vol. 30, issue 2, 939-951 (2015) [30] california iso, http://www.caiso.com/1c78/ 1c788230719c0.pdf [31] aljohani, tawfiq m., and abdullah m. alzahrani. "the operation of the gccia hvdc project and its potential impacts on the electric power systems of the region." (2014). 13 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e1 http://www.caiso.com/1c78/1c788230719c0.pdf http://www.caiso.com/1c78/1c788230719c0.pdf 1 introduction 2 current power grid operations 2.1 overview 2.2 pricing & customer types 2.3 qatar power grid 2.4 bahrain power grid 2.5 united arabic emirates power grids 2.6 kingdom of saudi arabia power grid 2.7 oman power grid 2.8 kuwait power grid 3 gcc interconnected power grid 3.1 overview 3.2 benefits 3.3 current status 4 renewable energy integration 4.1 goals & potential analysis 4.2 barriers 5 demand side management 5.1 load profiles 6 conclusion analysis of rate-based pull and push strategies with limited migration rates in large distributed networks w. minnebo and b. van houdt department of mathematics and computer science university of antwerp iminds middelheimlaan 1, b-2020 antwerp, belgium {wouter.minnebo,benny.vanhoudt}@uantwerpen.be abstract in this paper we analyze the performance of pull and push strategies in large homogeneous distributed systems where the number of job transfers per time unit is limited. job transfer strategies which rely on lightly-loaded servers to attract jobs from heavily-loaded servers are known as pull strategies, whereas for push strategies the heavily loaded servers initiate the job transfers to lightly loaded servers. to this end, servers transmit probe messages to discover other servers that are able to take part in a job transfer. previous work on rate-based pull and push strategies focused on the impact of the probe rate on the mean job response time. in this paper we also limit the overall migration rate and show that any predefined migration rate can be matched by both the rate-based pull and push strategies. we present closed form formulas for the mean response time (as a function of the allowed probe and migration rate) and validate their accuracy by simulation. we also introduce and analyze a new pull strategy and show that under high loads it is superior to the push strategies considered, while the push strategies offer only a very limited gain for medium to low load scenarios. categories and subject descriptors c.4 [computer systems organization]: performance of systems; d.4.8 [operating systems]: performance keywords distributed computing, performance analysis, processor scheduling 1. introduction in order to optimally use the available resources in a distributed network it is desirable to be able to dynamically relocate jobs among a large number of processing nodes. jobs may enter the network via one or multiple central dispatchers (e.g., [4,10,12,14,15]) or via the processing nodes themselves (e.g., [2, 3, 8, 13]). a central dispatcher will distribute the jobs among the nodes using some load balancing algorithm. in a more distributed approach, the nodes themselves will arrange for jobs to relocate after they are scheduled. two approaches are common: push and pull. in a push variant (or work sharing) highly loaded nodes attempt to find lightly loaded nodes to migrate jobs to. pull variants (or work stealing) reverse the roles, so that lightly loaded nodes try to attract work from the highly loaded nodes. several authors studied the performance of push and pull strategies. a comparison for a homogeneous distributed system with poisson arrivals and exponential job lengths was presented in [1, 2] and extended to heterogeneous systems in [9,11]. these studies showed that the pull strategy is superior under high load conditions, while the push strategy achieves a lower mean delay under low to moderate loads. nodes typically communicate by means of probe messages, exchanging information such as queue length. for simplicity we assume that sending/receiving probe messages is instantaneous and does not incur an extra computational or bandwidth cost. when a node wants to push or pull a job, it probes a random other node to see if a transfer between the nodes would be allowed. under a traditional pull or push strategy a server sends a maximum of lp probes the instant its last job completes or the instant a job arrives when the server is already busy [1,2]. the fraction of queues sending probe messages is different, and as a result pull and push strategies achieve a different overall probe rate for the same load of the system. this makes a performance comparison biased, as sometimes the strategy with the higher probe rate is best [5]. in [5] rate-based pull and push variants are introduced that can match any predetermined probe rate r, allowing the comparison of pull and push strategies when they use the same number of probes. in these variants, probes are no longer sent at job arrival or completion times but at a fixed rate r as long as the server is idle (for pull) or has jobs waiting (for push). the main result in [5] showed that the rate-based push strategy results in a lower mean delay if and only if λ < √ (r+ 1)2 + 4(r+ 1)− (r+ 1) 2 , under the so-called infinite system model and that a hybrid pull/push strategy is always inferior to the pure pull or push strategy. valuetools 2015, december 14-16, berlin, germany copyright © 2016 icst doi 10.4108/eai.14-12-2015.2262564 in [6] the model was extended with an extra parameter t , where a node is considered highly loaded if it has more than t jobs. this allowed the construction of the max-push strategy that extended the range of λ values where the push variants outperformed the pull strategy. all prior work, including [5, 6], assumed zero cost for job transfers, which is not always realistic. when jobs are difficult to migrate, it would be desirable to be able to limit migrations to a predefined overall migration rate m , while not exceeding the predefined overall probe rate r. this paper makes the following contributions: 1. we indicate how to set the parameter r (and t ) of the push, pull and max-push strategy to match any predefined migration rate m . 2. we argue that setting t = 1 for the pull strategy is no longer optimal when an overall migration limit m is considered, as was the case in [6] and introduce a new pull strategy, called the conditional-pull strategy. 3. we show that the conditional-pull strategy is equivalent in stationary queue length distribution to the maxpush variant when the overall probe rate r tends to infinity, i.e., when only an overall migration limit m is considered. 4. we consider a system where both an overall probe limit (r) and an overall migration limit (m) are imposed. for this system we compare the performance of push and pull strategies. we find that even for moderate r the conditional-pull performs almost as well as the max-push for low to moderate loads, and performs significantly better for higher loads. the paper is structured as follows. section 2 summarizes the rate-based strategies considered in this paper. in section 3 we briefly summarize earlier work concerning ratebased pull and push strategies, and introduce an overall migration limit m for these strategies. also, we derive an expression for the corresponding maximum probe rate rboth|m for the rate-based push and pull, and rewrite the mean delay in an equivalent form. in section 4 we adapt the max-push strategy to match m by finding the corresponding probe rate rmp|m , after summarizing earlier work. section 5 considers pull strategies with t > 1, and introduces the new conditional-pull strategy. it is shown that the conditionalpull is equivalent to the max-push strategy in case there is no probe limit r and only a migration limit m . in addition, the infinite system model describing the evolution of the conditional pull strategy is numerically validated, and argued to be the proper limiting process as the system size tends to infinity. finally, we compare the mean delay of max-push and conditional-pull in section 6. 2. rate based strategies we consider a continuous-time system of n queues, where each queue has a single server and infinite buffer. each queue operates under poisson job arrivals with rate λ < 1, and exponential service time with mean 1. jobs are processed in a first-come-first-served order. traditional strategies send a maximum of lp probes the instant a server’s last job completes or the instant a job arrives when the server is already busy. in contrast, under rate-based strategies probes are no longer sent at job arrival or completion times but at a fixed rate r as long as the server is idle (pull) or has at least t jobs waiting (push). more formally, probe messages are transmitted by a server according to an interrupted poisson process with rate r. the strategies considered in this paper can be summarized as follows: 1. rate-based push: as soon as the queue length exceeds t , a server starts to generate probe messages according to a poisson process with rate r. whenever the queue length drops below t , this process is interrupted until the queue length exceeds t again. the node that is probed is selected at random and is only allowed to accept a job if it is idle. 2. rate-based pull: whenever a server is idle it generates probe messages according to a poisson process with rate r. this process is interrupted whenever the server is busy. the node that is probed is selected at random and is only allowed to transfer one of its jobs if its queue length exceeds t . 3. max-push: the instant a new job arrives at a queue with length t , probes are sent at an infinite rate. when λ < 1 this corresponds to stating that the job is instantaneously transferred to an empty server. a server with t jobs in its queue, generates probe messages according to a poisson process with rate r. whenever the queue length drops to t − 1, this process is interrupted as long as the queue length remains below t . the node that is probed is selected at random and is only allowed to accept a job if it is idle. 4. conditional-pull: whenever a node is idle, the node will generate probe messages according to a poisson process with rate r. this process is interrupted whenever the server becomes busy. the probed node is selected at random and the probe is always successful if there are at least t jobs waiting to be served, and successful with some probability p (matching m , see (26)) if there are exactly t − 1 jobs waiting to be served. we do not consider hybrid strategies, which combine both push and pull behavior. these were proven to be inferior to a pure push or pull strategy when t = 1 [5, theorem 4]. 3. pull and push strategies infinite system models and closed form solutions for both pull and push strategies were introduced in [5] and [6]. before introducing new constraints and strategies, we briefly summarize the main findings of [5] and [6]. the evolution of both the rate-based pull and push strategy under the infinite system model is described by a set of odes denoted as d dt x(t) = f (x(t)), where x(t) = (x1(t), x2(t), . . .) and xi(t) represents the fraction of the number of nodes with at least i jobs at time t. from [6, theorem 2 and 3], it is known that d dt x(t) = f (x(t)) has a unique fixed point π̄ = (π̄1, π̄2, . . .) with ∑ i≥1 π̄i <∞ that is a global attractor, given by π̄i = λ ( (1 + r)λi−1 − rλt ) 1 + r(1− λt ) 1 ≤ i ≤ t + 1, (1) π̄i = π̄t+1 ( λ 1 + (1− λ)r )i−t−1 i > t + 1. (2) this fixed point is used in conjunction with little’s law in [6, corollary 1] to formulate the mean delay dboth of a job under the push or pull strategy: dboth = 1 1− λ − rλt ( λ (1−λ)(1+r) + t ) 1 + r(1− λt ) . (3) from the relationships r = (1− π̄1)rpull|r and r = rpush|rπ̄t+1, we find r = (1− λ)rpull|r, (4) and r = λt+1 (1− λt ) + 1/rpush|r . (5) it follows that whenever r > λt+1/(1−λt ), the rate rpush|r can be chosen arbitrarily large (i.e., rpush|r =∞). 3.1 limiting the overall migration rate when the overall migration rate is limited, the choice of r must satisfy this constraint. we first indicate how to set r to match m , and rewrite the formula for the mean delay. then we show whether r or m is the strictest constraint for a given load λ. theorem 1. both rate-based pull and push strategies match a predefined migration rate m by letting the probe rate r = rboth|m , with rboth|m : rboth|m = m (λ(1− λ) +m)λt −m . (6) for this setting, both strategies achieve the same mean delay. proof. the relationship (6) readily follows from the formulation of the overall migration rate for both rate-based strategies: mboth = r(1− λ)λt+1 r(1− λt ) + 1 . (7) from a push perspective this equation describes the fraction of nodes with queue length larger than or equal to t + 1 (π̄t+1 = λt+1/(1 + r(1 − λt )) from (1)) sending probes at rate r, succeeding with probability (1 − λ). for a pull strategy the overall migration rate is expressed as the fraction of empty queues (1 − λ) sending probes at rate r and succeeding when probing a queue of length t + 1 or longer (π̄t+1 = λt+1/(1 + r(1− λt )) from (1)). theorem 2. the mean delay of rate-based pull and push strategies can be expressed as dboth = 1 1− λ ( 1− mboth λ ( t + λ (1− λ)(1 + r) )) . (8) 0.4 0.5 0.6 0.7 0.8 0.9 1 0 5 10 15 20 t 1 t 2 t 3 t 1 t 2 t 3 r push|r r pull|r r both|m r=1 m=0.125 1−m/r load (λ) p ro b e r a te ( r) figure 1: the probe rates r imposed by either the probe limit r = 1 for push (dot-dashed) and pull (dashed), or migration limit m = 1/8 (full), for t = 1, 2, 3. note that rpull|r is independent of t . proof. equation (8) follows by rewriting (7) to rλt 1 + r(1− λt ) = mboth λ(1− λ) , and substituting this expression in (3). the previous theorem shows that the improvement in mean delay compared to a standard m/m/1 queue, can be expressed as a migration frequency (m/λ) times a migration gain (t + λ/((1− λ)(1 + r))). the migration frequency denotes how many migrations per job take place on average. the migration gain quantifies the number of places in the queue the migrating job skips. all migrating jobs skip at least t places by construction of the strategy, and skip more places depending on the queue length of the job sender. the average number of places skipped above t equals the average number of customers in an m/m/1 queue with service rate 1 + r(1− λ), which equals λ/((1− λ)(1 + r)). both the overall migration limit m and the overall probe limit r impose a maximum on r. in case r ≤m , all probes are allowed to generate a migration, so r will only be constrained by r. in any practical setting there will be more probes allowed than migrations, and the probe rate will be constrained by r or m depending on λ. an overview of the probe rates matching r or m , for both push and pull strategies with t = 1, 2, 3, is given in figure 1. to determine the range of λ in which each constraint is most strict, we determine the intersection of rboth|m with rpush|r and rpull|r. lemma 1. the probe rates rpush|r and rboth|m intersect at λ = 0 and 1−m/r only, and both rates are positive for λ = 1−m/r if and only if ( 1− m r )t > r2 r−m+r2 . the proof is given in appendix a of [7]. theorem 3. for the rate-based push strategy r should be set as follows in order to respect both the probe rate r and migration rate m : 1. r ≥ λt+1/(1 − λt ) and m ≥ λt+1(1 − λ)/(1 − λt ): r can be arbitrarily large. 2. r ≥ λt+1/(1 − λt ) and m < λt+1(1 − λ)/(1 − λt ): r can be at most rboth|m . 3. r < λt+1/(1 − λt ) and m ≥ λt+1(1 − λ)/(1 − λt ): r can be at most rpush|r. 4. r < λt+1/(1 − λt ) and m < λt+1(1 − λ)/(1 − λt ): let τ = ( 1− m r )t and υ = r2 r−m+r2 . • if τ > υ, r can be at most rboth|m if λ < 1−m/r and at most rpush|r otherwise. • if τ ≤ υ, r can be at most rpush|r. the proof is given in appendix b of [7]. lemma 2. if m < r 1+tr , rboth|m − rpull|r has a unique root λt in (0, 1), otherwise it has no roots in (0, 1). the proof is given in appendix c of [7]. for t = 1, the unique root λt of lemma 2 reduces to λ1 = √ m +m/r. however, there seems to be no closed form expression for general t . theorem 4. for the rate-based pull strategy r should be set as follows in order to respect both the probe rate r and migration rate m : 1. m ≥ λt+1(1− λ)/(1− λt ): r can be at most rpull|r. 2. m < λt+1(1− λ)/(1− λt ): • if the migration limit is sufficiently high (m ≥ r 1+tr ), then r can be at most rpull|r. • if the migration limit is sufficiently low (m < r 1+tr ), r can be at most rpull|r if λ < λt , and at most rboth|m otherwise. the proof is given in appendix d of [7]. 4. max-push the rate-based push is unable to reach an overall request rate higher than λt+1/(1−λt ) for any t . when the overall probe limit r exceeds this value, it is possible to use the remaining request rate by using the max-push variant as introduced in [6]. this strategy lets nodes with a queue length of t send probes at a finite rate rmp|r, and migrates all new arrivals to queues with length t by sending probes at an infinite rate until an empty server is found. as λt+1/(1− λt ) is an increasing function in λ and decreasing in t , the unique solution for λ to λt+1/(1− λt ) = r is increasing in t . therefore, there is a unique t > 1 satisfying λt+1/(1− λt ) ≤ r < λt /(1− λt−1). (9) for this t , the evolution of the max-push strategy can be described by a set of odes d dt x(t) = g(x(t)), where x(t) = (x1(t), x2(t), . . .) and xi(t) represents the fraction of the number of nodes with at least i jobs at time t. theorems 7, 8 from [6] show that the set of odes has a unique fixed point π̇ = (π̇1, . . . , π̇t ) that is a global attractor, and can be expressed as π̇i = λi 1 + ( λ 1−λ + r)(1− λt−i) 1 + ( λ 1−λ + r)(1− λt−1) , (10) for 1 ≤ i ≤ t . the mean delay dmp of a job under the max-push strategy is given by [6, corollary 3]: dmp = 1− λt + ( λ 1−λ + r)(1− tλt−1 + (t − 1)λt ) 1 + r(1− λ)(1− λt−1)− λt . (11) for the max-push strategy the overall probe rate r equals r = π̇t ( λ 1− λ + r ) , (12) as the instantaneous transfer of an arrival to a queue with t jobs requires 1/(1 − λ) probe messages on average. therefore, a predefined overall probe rate r can be matched by setting rmp|r = r λt−1(r+ λ)−r − λ 1− λ , (13) where 0 ≤ rmp|r < ∞ for λt+1/(1 − λt ) ≤ r < λt /(1 − λt−1). 4.1 limiting the overall migration rate as the rate-based push strategy cannot exceed the probe rate λt+1/(1 − λt ), it is unable to exceed an overall migration rate of (1 − λ)λt+1/(1 − λt ). it follows that when m > (1−λ)λt+1/(1−λt ), queues with a length of at least t+1 can probe at an arbitrarily high rate without exceeding the migration limit m , effectively reducing all queues to a length of at most t . queues with length t can then send probes with a finite r to match m . in other words, in order to match m (instead of r as in the previous section), set t such that (1− λ)λt+1 1− λt ≤m < (1− λ)λt 1− λt−1 . (14) and determine the probe rate rmp|m when the queue length equals t by the following theorem: theorem 5. the max-push strategy matches a predefined migration rate m by letting the probe rate r = rmp|m with rmp|m = λ ( m ((1− λ)λ+m)λt − λm − 1 1− λ ) . (15) when matching m this way, π̇i for i ≤ t reduces to π̇i = λi − m(1− λi−1) 1− λ , (16) proof. the relationship (15) follows from the formulation of the overall migration rate. the migrations of new arrivals in queues with length t are given by π̇tλ. the migrations resulting from a successful probe sent by queues with length t are given by π̇t r(1−λ). probes are successful if they locate an empty server, which they do with probability 1 − λ. therefore, the overall migration rate can be expressed as mmp = π̇t ( λ 1− λ + r ) (1− λ) (17) = (1− λ)((1− λ)r + 2λ)λt+1 λ(r(1− λ) + 1)− ((1− λ)r + λ)λt . the reduction of π̇i to (16) follows from substitution of (15) in (10), and shows the improvement over an m/m/1 queue directly. theorem 6. for the max-push strategy r and t should be set as follows in order to respect both the probe rate r and migration rate m : • if λ < 1 −m/r, t must be chosen according to (14) and r can be at most rmp|m . • if λ > 1 −m/r, t must be chosen according to (9) and r can be at most rmp|r. • if λ = 1−m/r, both constraints are equivalent. the proof is given in appendix e of [7]. theorem 7. the mean delay of the max-push strategy can be expressed as dmp = 1 1− λ ( 1− mmp λ ( α+ β mmp )) , (18) with α = π̇tλt and β = π̇t r(1 − λ)(t − 1). when r = rmp|m , the mean delay dmp reduces to dmp|m = 1 1− λ + m ( 1− λt ) (1− λ)2λ − mt + λt+1 (1− λ)λ . (19) proof. the improvement in mean delay compared to a standard m/m/1 queue, can be expressed as a migration frequency (mmp/λ) times a migration gain. the migration frequency denotes how many migrations per job take place on average. the migration gain quantifies the number of places in the queue the migrating job skips. the fraction of migrating jobs arriving at a queue with length t (π̇tλ/mmp) skip t places in the queue. the fraction of migrating jobs from queues with length t , being πt r(1−λ)/mmp, skip t − 1 places in the queue. hence, the migration gain is (α + β)/mmp. the reduction to dmp|m is found by applying little’s law to the expression for π̇ in (16), and shows the improvement over an m/m/1 queue explicitly. 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 1 2 3 4 5 6 r=1 m=0.1 t 1 t 4 load (λ) m e a n d e la y ( d ) figure 2: the mean delay of the pull strategy for t = 1, ..., 4. the probe rate r is constrained by both r and m (full lines). the delay shown in dashed lines is achieved when there is no migration limit, and only the probe limit is in effect. choosing t = 1 is no longer optimal when a maximum migration rate is imposed. 5. conditional pull when only considering a maximum allowed probe rate r, the optimal choice for a pull strategy is to let t = 1 [6, theorem 5]. this is no longer the case when taking a maximum allowed migration rate m into account, as shown in figure 2. intuitively, when the migration limit is small, it is best to pull jobs from longer queues only, resulting in a lower mean delay. to reduce the mean delay of the rate-based pull strategy, we introduce the conditional pull strategy that can match both r and m . empty servers send probes according to an interrupted poisson process with rate r. under the conditional pull strategy, empty nodes always accept jobs from queues with length of at least t + 1 and also accept jobs from a queue with length t with some probability p. this strategy relies on the choice of p to match the migration rate m , and lets the probe rate r be determined by r, i.e. r = rpull|r = r/(1− λ). thus, both r and m are matched, this is in contrast with the previous strategies, where r was always chosen as large as possible without exceeding r and m . first we note that one can easily see that for λt , being the unique root defined in lemma 2, λt < λt+1 (as m/((λ(1− λ) + m)λt − m) increases in t and r 1−λ increases in λ independent of t ). given λ, the conditional pull strategy sets t such that λt−1 ≤ λ < λt , (20) with λ0 = 0. to analyze the response time of a job under the conditional pull strategy we introduce a set of odes d dt xi(t) = h(x(t)), where x(t) = (x1(t), x2(t), . . .) and xi(t) represents the fraction of the number of nodes with at least i jobs at time t. as explained below, the set of odes h(x(t)) describing the time evolution of the queue lengths under the conditional pull strategy is defined as 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0.5 1 1.5 2 2.5 3 3.5 4 4.5 r=1 m=0.1 t 1 t 5 load (λ) m e a n d e la y ( d ) figure 3: showing the mean delay of the pull strategy with t > 1, respecting a migration limit ṁ . the conditional pull variant is shown in dashed lines. dx1(t) dt = −(x1(t)− x2(t)) + (λ+ rxt+1(t) + rp(xt (t)− xt+1(t)))(1− x1(t)) (21) dxi(t) dt = λ(xi−1(t) − xi(t)) − (xi(t) − xi+1(t)), (22) for 1 < i < t , and dxi(t) dt = λ(xi−1(t)− xi(t)) − (1 + rp1[i=t ](1− x1(t)))(xi(t)− xi+1(t)), (23) for i ≥ t , where 1[a] = 1 if a is true and 1[a] = 0 otherwise. the terms λ(xi−1(t) − xi(t)) and xi(t) − xi+1(t), for i ≥ 1, correspond to arrival and service completions, respectively. queues of length 1 are created by job transfers at rate (rxt+1(t) + rp(xt (t)−xt+1(t)))(1−x1(t)) as the fraction of empty nodes (1−x1(t)) probe at rate r, and a probe is successful with probability xt+1(t) + p(xt (t)− xt+1(t)). similarly, migrating jobs reduce the number of queues with exactly i jobs, for i > t , at rate r(1−x1(t))(xi(t)−xi+1(t)) and at rate rp(1− x1(t))(xt (t)− xt+1(t)) for i = t . the next theorem shows that this set of odes has a unique fixed point with ∑ i≥1 π̂i < ∞. in appendix f of [7] we briefly argue why this fixed point can be used to approximate the queue length distribution of a node as the number of nodes becomes large. the argument is similar to the one used in [5]. we also validate the accuracy of this approximation by simulation in section 5.1. theorem 8. the set of odes d dt x(t) = h(x(t)) has a unique fixed point π̂ = (π̂1, π̂2, . . .) with ∑ i≥1 π̂i < ∞. the fixed point can be expressed as: π̂i = λi ( (1− λ)r (∑t−i j=0 λ j + p(r + 1) ( 1− λt−i )) + 1 ) (1− λ)r (∑t−1 j=0 λ j + p(r + 1) (1− λt−1) ) + 1 (24) for 1 ≤ i ≤ t , and for i > t as π̂i = πt ( λ 1 + r(1− λ) )i−t (25) proof. assume π̂ is a fixed point with ∑ i≥1 π̂i < ∞, meaninghi(π̂) = 0 for i ≥ 1, whereh(x) = (h1(x), h2(x), . . .). when ∑ i≥1 π̂i < ∞, we can simplify ∑ i≥1hi(π) = 0 to λ − π̂1 = 0. hence, π̂1 must equal λ. the expressions for π̂i then readily follow from the conditions hi(π̂) = 0, for i ≥ 1. theorem 9. a predefined overall migration rate m can be matched by setting p = pcp|m , with pcp|m = m − π̄t+1r(1− λ) (π̄t − π̄t+1)r(1− λ) (26) = λ ( r ( −λ2 + λ+m ) λt −m(r + 1) ) (1− λ)r(r + 1) (λm − (−λ2 + λ+m)λt ) . when matching m by setting p = pcp|m , π̂i reduces to π̂i = λi − m(1− λi−1) 1− λ , (27) for i ≤ t . proof. the fraction of empty queues (1−λ) send probes at rate r. probes are successful with probability 1 if they locate a queue with length at least t + 1 (π̄t+1). probes are successful with probability p if they locate a queue with length equal to t (π̄t − π̄t+1). in other words: mcp = r(1− λ)(π̄t+1 + p(π̄t − π̄t+1), (28) from which (26) follows by algebraic manipulation. the reduction of π̂i to (27) is found by substituting (26) in (24). theorem 10. the mean delay dcp of a job under the conditional pull strategy equals dcp = 1 1− λ ( 1− mcp λ (α− β) ) , (29) with α = t + λ (1− λ)(1 + r) and β = r(1− λ)pπ̄t mcp . proof. the improvement in mean delay compared to a standard m/m/1 queue, can be expressed as a migration frequency (mcp/λ) times a migration gain (α − β). the fraction of migrating jobs where the job is pulled from a queue with length at least t + 1, (r(1 − λ)π̄t+1/mcp) skip α places in the queue: the same remarks as in theorem 2 apply. the other jobs ((r(1 − λ)p(π̄t − π̄t+1))/mcp) are pulled from a queue with length equal to t , thus skipping exactly t −1 places. in other words, the migration gain can be expressed as: αr(1− λ)π̄t+1 + (t − 1)(r(1− λ)p(π̄t − π̄t+1)) mcp , which can be rewritten as α− β. figure 3 shows the mean delay of the conditional pull strategy. the dots represent λt , i.e., the intersection points of rpull|r and rboth|m . the conditional pull strategy achieves a lower mean delay compared to the rate-based pull strategies with t > 1, as it transfers more jobs. theorem 11. when r = +∞ and m is finite, the maxpush and conditional pull strategies have the same stationary queue length distribution. proof. when there is no probe limit r, the parameter r is allowed to be arbitrarily large for the conditional pull strategy. in this case the maximum queue length will be t as limr→∞ π̂i = 0 for i > t , see (25). we therefore know from theorems 5 and 9 that both the max-push and conditional pull strategy have the same queue length distribution when only matching m , if they use the same t . what remains to be shown is that both strategies make use of the same t . recall that λt was defined as the solution in (0, 1) of rpull|r− rboth|m , that is, r 1− λ = m (λ(1− λ) +m)λt −m . the left hand side tends to infinity as r tends to infinity. hence, rboth|m must tend to infinity, meaning λt is the solution to m = (1 − λ)λt+1/(1 − λt ). the λt ’s are thus exactly the m values where the max-push strategy changes its t value, see (14). hence, both the conditional pull and max-push strategy choose the same t . 5.1 model validation we validate the infinite system model for the conditional pull strategy by comparing the closed form results of theorem 10 with time consuming simulation results for systems with a finite number of nodes n . the infinite and finite system model only differ in the system size. hence, the rate r and probability p in the simulation experiments is independent of n and was determined by using the expression for p from equation (26) and r = r/(1 − λ). each simulated point in the figures represents the average value of 25 simulation runs. each run has a length of 106 time units (where the service time is exponentially distributed with a mean of 1 time unit) and a warm-up period of length 106/3 time units. load (λ) 0.5 0.65 0.7 0.75 0.8 25 1.1e-2 1.7e-2 1.9e-2 2.4e-2 2.9e-2 50 5.6e-3 8.2e-3 9.5e-3 5.7e-3 7.1e-3 system 100 2.8e-3 3.9e-3 4.6e-3 5.7e-3 7.1e-3 size 200 1.3e-3 2.0e-3 2.3e-3 2.7e-3 3.4e-3 (n) 400 7.0e-4 1.0e-3 1.2e-3 1.3e-3 1.7e-3 800 3.5e-4 5.0e-4 5.6e-4 6.6e-4 8.1e-4 1600 1.6e-4 2.5e-4 2.6e-4 3.8e-4 4.3e-4 table 1: relative error of mean delay, given by (29), for the conditional pull strategy with r = 1 and m = 0.1 when compared to simulation results. table 1 compares the mean delay in a finite system with n nodes with the mean delay in the infinite system model under the conditional pull strategy with r = 1 and m = 0.1 for n = 25, 50, . . . , 1600 and λ = 0.5, 0.65, 0.7, 0.75 and 0.8. for each combination of n and λ we also show the relative error. the error clearly decreases as n grows, and is worse for larger λ values. the observed overall migration rate in the simulation is strictly lower than the predefined m , meaning less jobs will be transferred than anticipated. hence, the mean delay in the simulation experiments is pessimistic. this error is in part due to the choice of p, which was determined using (26). this choice relies on the infinite system model whereas we are now studying a finite system. the relative error in the observed overall migration rate is nearly load-insensitive and decreases linearly as the system doubles in size, as shown in table 2. n 25 50 100 200 400 800 1600 rel. err. 4% 2% 1% .5% 0.25% .13% .064% table 2: relative error of the observed overall migration rate for finite system size when compared to the targeted migration rate m . 6. push versus pull strategies we compare the performance of the max-push and the conditional pull strategies with a predefined overall probe limit r and migration limit m (using theorems 7 and 10). the parameter t is determined by the load λ, as each strategy is only defined for a specific t given any λ (see (9), (14) and (20)). for the max-push, the value for t and r is chosen to match the strictest constraint of either r or m depending on the load (see theorem 6). for the conditional pull all idle servers probe with rate r = r/(1− λ), and p is chosen to match m (see theorem 9). the mean delay of the max-push and conditional pull strategy with m = 0.1 and r = 0.4 is shown in figure 4. the max-push strategy is limited by the probe limit when λ > 1−m/r and by the migration limit when √ m < λ < 1 −m/r. the mean delay of the push strategy is one in case λ < √ m , as all newly arriving jobs at a busy server can be migrated instantaneously to an empty server without violating the r and m constraints. for the conditional pull strategy the limiting factor is r when λ < √ m +m/r, and m for λ > √ m +m/r. the intervals where both strategies are constrained by m do not always overlap, i.e. √ m +m/r can be larger than 1 −m/r, as is the case for r = 1 and m = 0.3. when√ m +m/r < 1 −m/r both strategies transfer the same number of jobs when √ m +m/r < λ < 1 −m/r. however, the max-push will outperform the conditional pull as the average migration gain is larger. this is not unexpected as the max-push strategy avoids that queues become larger than t , whereas queues with a length exceeding t exist for the conditional pull as it only sends random probes at a finite rate. 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 2 3 4 5 6 7 1−m/r √ m √ m +m/r push pull r=0.4 m=0.1 load (λ) m e a n d e la y ( d ) figure 4: mean delay of the max-push and conditional pull strategies, with r = 0.4 and m = 0.1. 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 2 3 4 5 6 7 1−m/r √ m √ m +m/r push pull r=1 m=0.1 load (λ) m e a n d e la y ( d ) figure 5: mean delay of the max-push and conditional pull strategies, with r = 1 and m = 0.1. as expected from theorem 11, the difference in performance between max-push and conditional-pull becomes smaller when increasing r, as shown in figure 5. as the empty queues send probes with rate r = r/(1 − λ), they are allowed to send more probes as r increases. this increases the odds that a long queue is probed, thus lowering the mean delay. this can also be observed by looking at the values for t . by increasing r, a larger value for t can be used for the same load. this requires that jobs are pulled from longer queues, increasing the migration gain per transfer. in conclusion, whenever the maximum allowed probe rate r clearly exceeds the maximum allowed migration rate m (which is the case that is mainly of practical interest), the pull strategy is either clearly superior (for large λ) or has a similar performance to the max-push strategy (for medium to low λ). 7. references [1] d. eager, e. lazowska, and j. zahorjan. adaptive load sharing in homogeneous distributed systems. software engineering, ieee transactions on, se-12(5):662 –675, may 1986. [2] d. eager, e. lazowska, and j. zahorjan. a comparison of receiver-initiated and sender-initiated adaptive load sharing. perform. eval., 6(1):53–68, 1986. [3] n. gast and b. gaujal. a mean field model of work stealing in large-scale systems. sigmetrics perform. eval. rev., 38(1):13–24, 2010. [4] y. lu, q. xie, g. kliot, a. geller, j. r. larus, and a. greenberg. join-idle-queue: a novel load balancing algorithm for dynamically scalable web services. perform. eval., 68:1056–1071, 2011. [5] w. minnebo and b. van houdt. a fair comparison of pull and push strategies in large distributed networks. ieee/acm transactions on networking, 2013. [6] w. minnebo and b. van houdt. improved rate-based pull and push strategies in large distributed networks. in proc. of the ieee 21-th international symposium on modeling, analysis and simulation of computer and telecommunication systems, san francisco (usa), 2013. [7] w. minnebo and b. van houdt. tech. report: analysis of rate-based pull and push strategies with limited migration rates in large distributed networks. http://win.ua.ac.be/~vanhoudt/papers/reports/ migrationpaper.pdf, 2015. [8] r. mirchandaney, d. towsley, and j. stankovic. analysis of the effects of delays on load sharing. ieee trans. comput., 38(11):1513–1525, 1989. [9] r. mirchandaney, d. towsley, and j. a. stankovic. adaptive load sharing in heterogeneous distributed systems. j. parallel distrib. comput., 9(4):331–346, 1990. [10] m. mitzenmacher. the power of two choices in randomized load balancing. ieee trans. parallel distrib. syst., 12:1094–1104, october 2001. [11] i. v. spilbeeck and b. v. houdt. performance of rate-based pull and push strategies in heterogeneous networks. performance evaluation, 91:2 – 15, 2015. special issue: performance 2015. [12] a. stolyar. pull-based load distribution in large-scale heterogeneous service systems. queueing systems, 80(4):341–361, 2015. [13] b. van houdt. performance comparison of aggressive push and traditional pull strategies in large distributed systems. in proceedings of qest 2011, aachen (germany), ieee computer society, pages 265–274, sep 2011. [14] n. vvedenskaya, r. dobrushin, and f. karpelevich. queueing system with selection of the shortest of two queues: an asymptotic approach. problemy peredachi informatsii, 32:15–27, 1996. [15] l. ying, r. srikant, and x. kang. the power of slightly more than one sample in randomized load balancing. in proc. of ieee infocom, 2015. http://win.ua.ac.be/~vanhoudt/papers/reports/migrationpaper.pdf http://win.ua.ac.be/~vanhoudt/papers/reports/migrationpaper.pdf introduction rate based strategies pull and push strategies limiting the overall migration rate max-push limiting the overall migration rate conditional pull model validation push versus pull strategies references high availability of charging and billing in vehicular ad hoc network mohamed darqaoui1, slimane bah2, marouane sebgui3,∗ 1ecole mohammadia d’ingénieurs, electrical and communication laboratory, rabat, morocco 2ecole mohammadia d’ingénieurs, electrical and communication laboratory, rabat, morocco 3ecole mohammadia d’ingénieurs, electrical and communication laboratory, rabat, morocco abstract vanet (vehicular ad hoc network) is actually an important field for the development of a variety of services. in vanet charging and billing of services could not be enabled in the same way as in classical mobile and fix networks and manet (mobile ad hoc network) because of the characteristics of such network namely the high speed of nodes, frequent disconnection between nodes, rapidly changing topology and the large size of the network. the purpose of this work is to propose a flexible high level charging and billing scheme to allow a high availability of the charging and billing process in vanet. received on 6 december 2017; accepted on 18 december 2017; published on 12 february 2018 keywords: vanet, charging, billing, prepaid, on-line/off-line charging copyright © 2018 mohamed darqaoui et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.12-2-2018.154102 1. introduction in recent years, the field of vehicular ad hoc network (vanet) has attracted a growing amount of interest. vanet [1] is a term associated with technologies (architecture, data, and protocols) developed and standardized under the umbrella work of intelligent transport systems (its) [2]. standardization of its is done in various governmental and nongovernmental standard development organizations namely ieee, iso, itu. vanet comprise vehicle-to-vehicle and vehicleto-infrastructure communications based on wireless local area network technologies. vehicular networking offers a wide variety of applications [3], including safety, non safety and infotainment applications. the abundance of vanet applications is a benefit for a wide range of parties: governments, vehicle manufacturers, operators and consumers. for the operators promoting their services in vanet a robust charging and billing architecture is needed. although many works have been done in charging and billing in ad hoc environment, most of them does not addressed the high availability of charging and billing process when nodes move ∗corresponding author. email: darqaoui.med@gmail.com from vanet infrastructure to a pure infrastructureless vanet environment. charging and billing process relies on an existing infrastructure which constitutes a severe limitation and raises a highly complex problem for which no satisfying solution exists. to address this problem, we propose a scheme making the charging and billing control available even out of vanet infrastructure. we address this problem from two perspectives: first, when a vehicle under online charging and billing in vanet environment moves to an infrastructure-less environment; second, when a vehicle under online charging in vanet moves to a different autonomous vanet domain or network. . this paper is structured as follows: section 2 provides background information on vehicular networks and charging/billing systems in traditional mobile networks. section 3, proposes requirements for billing and charging in vanets and provides a critical overview of existing solutions. section 4 proposes a hybrid charging and billing mechanism to take into consideration vanet’s characteristics. we conclude our work in section 5. 2. background on vanet and charging/billing 1 eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e1 http://creativecommons.org/licenses/by/3.0/ mailto:<darqaoui.med@gmail.com> darqaoui m., bah s., sebgui m 2.1. vehicular ad hoc network ad hoc networks are communication networks that are formed in a more or less spontaneous way and comprise an arbitrary number of participating nodes. they typically comprise wireless communication terminals forming a wireless stand-alone network. examples of such networks are mobile ad hoc network (manet) [4] and vehicular ad hoc network (vanet). the current trend in ad hoc networks is vehicular ad hoc network. vanet is an emergent technology that receives, recently, the attention of the industry and research groups. it allows different deployment architectures in highways, urban and rural environments [5]. in vanet architecture, the communication can be either among nearby vehicles or/and between vehicles and roadside units leading to three possibilities: vehicle-to-vehicle (v2v) communication, vehicle-to-infrastructure (v2i) communication and hybrid architecture (as shown in figure 1): figure 1. vanet communication architecture vehicular ad hoc networks present some particular characteristics despite being a special case of classical mobile ad hoc networks namely the high speed of nodes, the rapidly changing topology, frequent disconnections between nodes [1] and in several cases the large size of the network. the particularities of vanet make it a very interspersing domain which deserves in the last years several studies addressing different aspects, such as: applications [6, 7], communication [8], security [9, 10], routing protocols [11, 12, 13], access [14] and cloud computing in vanets [15, 16,17]. although researchers have achieved much great progress on vanets study, there are still some challenges that need to be overcome and some issues that need to be further investigated (e.g., security, services.). especially, one aspect that has not been tackled by research namely the charging and billing issue. 2.2. charging and billing charging is the process of collecting, evaluating and accounting a network resource usage [18]. this resource usage is related to an event that can be either a voice communication or an internet session or a value added service. billing is the step that follows the charging operation, it consists of two mains steps: mediation step that collect, validate, filter correlate, aggregate and convert data to create data record called data detailed record (cdr) and rating step which is a process that puts a cost on a call or a service (monetary values). after the rating step bills are generated. there exist two modes of charging: postpaid and prepaid. in postpaid mode a bill is generated in arrears periodically stating what was owed to the service provider by the customer. the subscriber is then expected to settle the bill (payment). in prepaid mode of charging and billing, the customer pays a sum in advance. the paid amount is depreciated as telecoms services are consumed. in mobile networks (gsm/umts/lte) online and offline charging are two mechanisms used to charge subscribers for rendered services [18]. offline charging is a mechanism that consists of a chain of logical functions, this chain end by generating charging information (cdr) related to a resource usage in the network which is then transferred to the billing system to generate the subscriber bill. in this scenario the charging process does not affect, in real time, the service rendered. offline mode is used to charge a postpaid user. in the same fashion, the online charging information passes through a chain of logical functions. however, authorization for the network resource usage must be obtained by the network prior to resource usage to occur. the online mode is used to charge prepaid users. 3. requirements and critical overview of existing solutions 3.1. requirements the charging and billing system in vanet must be different from the charging and billing process in other mobile networks. we identified main charging and billing requirements to be fulfilled by a charging and billing system in order to carry out its basic tasks in vehicular ad hoc network: (a) the vanet charging/billing system should take into consideration the high speed of vehicles in terms of controlling the charging process and insuring its high availability. (b) the vanet charging/billing system should be flexible. in fact, due to frequent disconnections, the charging solution needs to be aware of the underlying environment updates and adapt to the network topology changes. (c) the vanet charging/billing system should allow the roaming of the charging function between different 2 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e1 high availability of charging and billing in vehicular ad hoc network vanet providers. in fact, when a vehicle travels long distance it is not unusual to traverse different vanet infrastructures belonging to different domains. a service should be charged continuously and accurately in this context. 3.2. related work to the best of our knowledge there is no solution dedicated to vanet environments for billing and charging issues. however, some research works have addressed this problem in peer-to-peer and manet networks. authors in [19] propose the mmapps (market-managed peer-to-peer services) charging solution for peer-to-peer networks. the mmapps accounting and charging system addresses, mainly, the issue of accountability in peer-to-peer environments and associated problems. the work [20] proposes a secure charging protocol (scp). scp aims at answering the complex authentication, authorization, accounting and charging (aaac) problem in manet. it provides a view based on a different business model. this later has been adjusted to cope with technological changes. the work also addresses the improvements made to the scp protocol in terms of quality of service (qos) and user interfaces. the work in [21] proposes a solution for charging in manet. the solution enables charging without any access to external networks. for example, when a communication is initiated by a mobile communication device within an ad hoc network, a small initiation fee is stored securely on the device, typically on a smart card. transfer of the charging information may then occur more or less automatically and/or when the device reaches a coverage area of the operator network. when the network operator’s system receives the charging information from a communication device (i.e. when it comes into contact with the infrastructure) the corresponding account is updated and charged with the activities that have occurred since the last update. 3.3. analysis and discussion generally, the works discussed above provide a suitable charging and billing solution for peer-to-peer networks and ad hoc environment but did not meet the requirements highlighted previously. specifically, the peer-to-peer architecture proposed in [18] does not consider mobility and then does not meet the requirement (a) and (b) in term of flexibility and high availability. the scp protocol proposed in the work [19] has only addressed the security issue in charging process assuming an existing solution. as far as the work in [20] is concerned, it does not take into consideration the requirement (b) and (c). in fact, this work focus on updating the operator charging system with data collected during offline charging. the cooperation between the offline and online charging systems is not considered. therefore, when a node roams from an environment with vanet infrastructure to an environment where the infrastructure of vanet is absent (i.e. no rsus and no possible connection with external networks) the charging process is interrupted. similarly, when the vehicle traverses different autonomous vanet systems the charging is interrupted or may not be possible to update the operator charging system. therefore the high availability of charging and billing is not considered at all. 4. proposed solutions for high availability charging in vanet the main goal of this work is to insure the high availability of charging and billing control in vehicular environment. first, we propose a high level mechanism to address the problem of a vehicle leaving the vanet infrastructure while it is under online charging and billing process. then, we propose a high level mechanism for seamless charging between vanet and 3gpp domains. both cases involve a context-aware charging and billing system. both mechanisms rely on a context-aware charging and billing solution. through this solution, the operator will be able to continuously control its resource usage in vanet and out of vanet. indeed, the roadside units will be responsible for detecting if a vehicle is under vanet control or not using some protocol (e.g. heartbeat protocol) or when the signal noise ratio (snr) reaches some predefined thresholds. before presenting our proposed schemes we highlight the vanet business model. 4.1. business model vanet as a new technology is coming with a new concepts especially regarding business part. vanet could be deployed according a business model, in this model we distinguish generally three partners;vanet provider, operator and end user. the vanet provider is the party which deploy the infrastructure of vanet ( roadside units, vanetenabled vehicles...) it can be for example a manufacturer. the operator is the service provider, it is the party marketing services through vanet, example of operator is telecommunication company providing internet access or cloud computing provider offering cloud service. the operator can also take on the role vanet provider. end user: the obu unit installed in the vehicle enabling vanet communications. 3 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e1 darqaoui m., bah s., sebgui m 4.2. online to offline charging and billing roaming in this scenario, vehicles establish a v2v session (e.g. direct voice call service between vehicles). we propose to equip the vehicles with a prepaid system(pps) such as smart card or virtual storage in the operating system running on the vehicle. however, the charging of the call is carried out by the vanet online charging and billing infrastructure (ocs), the rsu collects the charging data (v2i communication) and send them to billing domain bd (figure 2). the data charging are information related to the call such as start time, duration of the call and end time of the call. figure 2. online charging based system since the communication between vehicle a and b is vehicle-to-vehicle communication, the media channel is not controlled by the rsu. therefore, when the two vehicles leave the vanet charging area (i.e. the zone covered by vanet infrastructure namely rsus) to a non vanet charging area (i.e. area where there is no vanet infrastructure and where vanet become a pure peer-to-peer mobile environment) the communication is not interrupted but the charging of the call is lost (figure 3). figure 3. charging flow interruption from the vanet provider’s business perspective, the scenario above present a crucial problem since the wireless resource (bandwidth) is used for free. to avoid this problem, we propose that the vanet provider implements an on-line context-aware charging and billing system (context-aware ocs). this system will collect several parameters in order to decide to switch automatically to the prepaid charging system implemented in the vehicle (e.g. smart card). we propose to use two parameters: the snr (signal to noise ratio) between the rsus and the vehicles, and/or gps positions of rsu’s zone edges. for the snr, when the signal power reaches a predefined threshold the charging ocs system upload the charging profile to the prepaid system storage. as for the rsu edges’ gps positions, the system (eventually the rsu) records the vehicles’ gps positions in each instant and compare them with a preconfigured table containing the gps positions of rsu’ s zone edges. if the vehicle is near of these positions, the system switches the charging control to the prepaid by uploading the charging profile to the vehicle’s prepaid system. the charging profile consist of subscription information namely, vehicle id, owner of vehicle (subscriber), accounts, balances, services (voice, data, sms, video...), subscription time, expired time. the prepaid system is not necessarily a smart card it could be for example a virtual storage in an operating system implemented in the vehicle which stores the charging profile. once the charging profile information is uploaded from the ocs to the vehicle’s storage, the prepaid system will have a real-time control on the call. therefore, a credit, or an appropriate amount of credits, is deducted from the currently available credits (figure 4). consequently the user will be denied to make any vanet communication when it runs out of credits. figure 4. context-aware ocs and prepaid system charging signalling flow for such system is as described in figure 5. 1 : the vehicle is attached to rsu and under vanet charging 2 : the rsu collect charging data and send it to vanet charging and billing system (vcbs) 3 : the vehicle reach vanet edge’s gps positions 4 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e1 high availability of charging and billing in vehicular ad hoc network figure 5. vanet-to-pps switching charging signaling flow stored in rsu’s database and switch to pps mode 4 : the vehicle is under pps charging 5 : the session is ended or interrupted 6 : when the vehicle gains access to network next time the pps system send the charging data to vcbs for further and final treatment. 4.3. vanet-online charging to non-vanet online charging roaming similarly, in this scenario the service charging is carried out by the vanet online charging and billing infrastructure (ocs). but the vehicles a and b move from a vanet infrastructure domain to a non charging vanet domain but covered by external network such as 2g/3g or 4g or an other vanet (figure 6). when vehicle a and vehicle b leave the vanet charging environment to 3gpp domain, the operator loses the charging and billing control. to avoid this, the ocs system and the vehicle should include context-aware functions. for the ocs system, we propose to measure the signal power parameter between the rsu and the vehicle, and collect gps positions of rsu’s edges. for vehicles, we propose to measure the signal power parameter received from both rsu and radio access network (ran) node of external network. thus, when the vehicle reaches the rsu’s edges, it measures figure 6. vanet to 3gpp and compares the signal power of rsu and ran node, when the signal power of the ran node is higher, then the charging control is switched to the 3gpp network(figure 7). the charging switching is preceded by an authentication procedure of the vehicle in the visited 3gpp network. this authentication is, generally, performed by an authentication server of the operator such as authentication, authorization and accounting server (aaa). therefore the high availability of charging and billing is granted. figure 7. vanet-to-3gpp charging roaming the signalling flow will be in this situation : 1 : the vehicle is attached to rsu and under vanet charging 2 : the rsu collect charging data and send it to vanet charging and billing system (vcbs) 3 : the vehicle switch to external network when the signal of the latter is higher than vanet (rsu) signal 4 : the vehicle is attached to external network and charging is performed by its charging and billing 5 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e1 darqaoui m., bah s., sebgui m figure 8. vanet-to-3gpp roaming charging signaling flow system cbs 5 : the charging is performed by the online charging of external network 6 : the session is ended or interrupted 7 : the charging and billing system of external network transfers the charging and billing data to vanet charging and billing system (vcbs) for final update in the situation where vanet and external network belong to the same service provider, a common charging and billing system is used,but generally the home vanet(hvanet) network and visited vanet or 3gpp networks belong to different operators, therefore charging and billing functions are preferably performed by the home network.in such situation visited vanet or 3gpp networks will only act as a relay network to transfer the charging data to home network(home vanet) for final charging and billing. 5. conclusion vehicular ad-hoc network is a challenging environment especially for charging and billing. nowadays many vanet research are addressing several aspects (e.g. access, routing and services). however, no works have been found in charging and billing systems. in this paper we showed that existing solutions mainly for manet and peer-to-peer do not meet our proposed requirements and therefore are not suitable for vanet. hence, we described two high level proposals for insuring the high availability of charging and billing in vehicular ad hoc environment especially when a vehicle moves from a vanet charging environment to a nonvanet charging one. in the next steps of our work we will detail our solution in term of, business model, architecture, functional entities, protocols, procedures and interfaces and in order to best enforce our solution a simulation of the work is also planned. references [1] zeadally, s., hunt, r., chen, ys. et al. telecommun syst (2012) 50: 217. doi:10.1007/s11235-010-9400-5 [2] hannes hartenstein, kenneth laberteaux: intelligent transport systems, vanet vehicular applications and inter-networking technologies,(2010) [3] anna maria vegni, mauro biagi and roberto cusani (2013). smart vehicles, technologies and main applications in vehicular ad hoc networks, vehicular technologies deployment and applications, dr. lorenzo galati giordano (ed.), intech, doi: 10.5772/55492. available from: http://www.intechopen.com/books/vehiculartechnologies-deployment-and-applications/smartvehicles-technologies-and-main-applications-invehicular-ad-hoc-networks [4] al-omari, saleh ali k. and putra sumari.’an overview of mobile ad hoc networks for the existing protocols and applications.’ corr abs/1003.3565 (2010) [5] felipe domingos da cunha, azzedine boukerche, leandro villas, aline carneiro viana, antonioa. f. loureiro. data communication in vanets: a survey, 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[research report] rr-8498, inria saclay; inria. 2014.<hal-00981126v4> [6] h. hartenstein and l. p. laberteaux, "a tutorial survey on vehicular ad hoc networks," in ieee communications magazine, vol. 46, no. 6, pp. 164-171, june 2008. [7] claudia campolo, antonella molinaro, riccardo scopigno:vehicular ad hoc networks standards, solutions, and research,edition 1, 2015 [8] zaydoun yahya rawashdeh and syed masud mahmud (2011). communications in vehicular ad hoc networks, mobile ad-hoc networks: applications, prof. xin wang (ed.), intech, doi: 10.5772/13399. [9] xiaodong lin, rongxing lu:vehicular ad hoc network security and privacy, 1 edition (22 jun. 2015),216 pages [10] mejri, mohamed nidhal, jalel ben-othman and mohamed hamdi. ’survey on vanet security challenges and possible cryptographic solutions.’ vehicular communications 1 (2014): 53-66. [11] yun-wei lin, yuh-shyan chen, and sing-ling lee:routing protocols in vehicular ad hoc networks: a survey and future perspectives,journal of information science and engineering 26(3):913-932. may 2010 [12] kevin c. lee, uichin lee, mario gerla :"survey of routing protocols in vehicular ad hoc networks,", advances in vehicular ad-hoc networks: developments and challenges, igi global, oct, 2009. [13] benamar maria, benamar nabil, singh kamal deep, el ouadghiri driss recent study of routing protocols in vanet: survey and taxonomy. wvnt 2013 : 1st international workshop on vehicular networks and telematics , 02-04 may 2013, marrakech, morocco, 2013 [14] sjoberg, katrin. medium access control for vehicular ad hoc networks. chalmers university of technology, 2013. 6 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e1 high availability of charging and billing in vehicular ad hoc network [15] md whaiduzzaman, mehdi sookhak, abdullah gani, rajkumar buyya, a survey on vehicular cloud computing, journal of network and computer applications, http://dx.doi.org/10.1016/j.jnca.2013.08.004 [16] e. lee, e. k. lee, m. gerla and s. y. oh, "vehicular cloud networking: architecture and design principles," in ieee communications magazine, vol. 52, no. 2, pp. 148-155, february 2014. [17] nkenyereye, l., park, y. & rhee, k.h. j wireless com network (2016) 2016: 196. doi:10.1186/s13638-0160687-0 [18] 3gpp ts 32.240 v9.0.0:3rd generation partnership project; technical specification group services and system aspects; telecommunication management; charging management; charging architecture and principles (release 9) [19] r. kuhne, g. huitema and g. carle, ’charging and billing in modern communications networks âăť a comprehensive survey of the state of the art and future requirements,’ in ieee communications surveys and tutorials, vol. 14, no. 1, pp. 170-192, first quarter 2012. [20] joao girao, bernd lamparter, dirk westhoff, rui l. aguiar, joao paulo barraca, ’implementing charging in mobile ad-hoc networks’, electronica e telecomunicacoes, vol. 4, no. 1, issn 1645-0493, oct 2004 [21] anders nilsson plymoth, bjorn plymoth, amelie plymoth:charging in ad hoc communication networks,sweden,2009 7 eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e1 1 introduction 2 background on vanet and charging/billing 2.1 vehicular ad hoc network 2.2 charging and billing 3 requirements and critical overview of existing solutions 3.1 requirements 3.2 related work 3.3 analysis and discussion 4 proposed solutions for high availability charging in vanet 4.1 business model 4.2 online to offline charging and billing roaming 4.3 vanet-online charging to non-vanet online charging roaming 5 conclusion a case based reasoning coupling multi-criteria decision making with learning and optimization intelligences: application to energy consumption a case based reasoning coupling multi-criteria decision making with learning and optimization intelligences: application to energy consumption naomi dassi tchomté1,∗, sohail asghar2, nadeem javaid2, paul dayang1, duplex elvis houpa danga1, dieudoné lucien bitom oyono3 1mathematics and computer science, faculty of science, university of ngaoundéré, cameroon 2department of computer science, comsats university islamabad, pakistan 3faculty of agronomy and agricultural sciences, university of dschang, cameroon abstract optimization energy is a technique helpful to manage electricity consumption of home devices according to the electric system. cbr is used to predict consumption but lacks to be generic. this paper intends to design a more generic cbr approach by relying on various intelligences. the retrieve process includes four steps. the first step is weight evaluation of attributes based on ahp. the second step exploits an adapted cosine model for distance similarity. the third and fourth steps use k-means and k-nn to identify the most similar cases. the reuse process is defined as a linear programming problem solved by pso. during revise, an algorithm based on the reuse model and svr, derives the revised solution. experiments on a dataset of 1096 samples are made for forecasting energy electricity consumption. cbr revise process is 99.35% accurate, improving the reuse accuracy by 11%. the proposed architecture is a potential in energy management as well as for other prediction problems. received on 07 july 2019; accepted on 25 november 2019; published on 19 december 2019 keywords: ahp, cbr, forecasting, pso, supervised learning, support vector regression copyright © 2019 naomi dassi tchomté et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.26-6-2018.162292 1. introduction case-based reasoning (cbr) is a methodology which makes use of solutions of past problem cases to solve new problems [1] [2]. it includes four steps. the retrieve process aims to retrieve cases that are similar to the new case of the problem. the reuse process aims to reuse a solution that has been suggested by measuring the similarity in the retrieve phase. the revise process aims to adapt the solution to fit the new problem. the retain process is used to retain the new solution when it is confirmed. cbr is a promising artificial intelligence methodology as compared to machine learning techniques for two reasons [3] and [4]. first, ∗corresponding author. email: naomitdassi@gmail.com it is able to adapt new data which is automatically stored into the knowledge base of the model and become part of the solution for predicting the future solution. second, it is able to provide interesting performance independently to the dataset. on the contrary, supervised learning algorithms require large volume of data and need to be re-calculated when there is new data. it is not representative of the general trends of the modelling data. however, cbr lacks specifications on how these processes should be fulfilled. as a consequence, a cbr system can differ from another. cbr has been largely applied in energy consumption prediction to increase consumer awareness of the forecasted energy consumption. it is done to stimulate the shift their appliance consumption there by improving energy usage. different approaches exist as using cbr to adjust the energy consumption of a house according to the actual state of consumption of appliances [5] and [6], predicting energy consumption 1 research article eai endorsed transactions on smart cities eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 http://creativecommons.org/licenses/by/3.0/ http://doc.eai.eu/publications/transactions/latex/ mailto:<naomitdassi@gmail.com> naomi dassi tchomté et al. according to internal and external factors as well as people habits and agendas in the building [6], and selecting optimal algorithms exploited in different processes in resource scheduling [7] and [8]. however, these works lack to be generic because they only solve specific problems. the suggested aim is to make cbr functionalities more generic based on well structured data for energy forecasting problems. this study proposes case based reasoning architecture based on machine learning (cable), a novel cbr approach coupling various intelligences to efficiently forecast a solution based on historical cases. it relies on a modified version of cosine for distance similarity and associates k-nn and k-means for the retrieve phase. cable structures in the reuse, the determination of solution as an optimization problem from which the solution is determined using particle swarm optimization(pso). the retrieve process combines the reuse model and the svm regression model based on a threshold. experiments were made on real data samples about energy loads in buildings to assess the performance of forecasting using cable. this work is expected to be relevant to people willing to predict their energy consumption for making adequate decisions. and therefore to be further exploited as a support to determine appliances which increase consumptions. the rest of the paper is organized as follows. the first section presents related works about predicting energy consumption using cbr. the second section presents different intelligent techniques required to build the proposed approach. the third section details the different components of the resulted architecture. the fourth section describes a case study exploiting cable to predict the electricity energy consumption in market buildings. the last section concludes and specifies future works. 2. related works several works have been proposed to improve energy consumption using case-based reasoning. platon et al. [7] study the accuracy of cbr and artificial neural networks (ann) models in predicting the hourly building electricity use. they investigate artificial neural networks(ann) and cbr methods for to the development of accurate models. this work uses principal component analysis (pca) to optimally reduce the number of variables by identifying the significant variables containing significant information in the dataset. xiao et al. [9] and shen et al. [10] provide a case-based reasoning model to build green buildings based on past knowledge and experience. they use text mining techniques to translate the experience in the format of text to be systematically descriptive. faia et al. [8] propose a case-based reasoning scheme to determine optimal algorithms selected in previous cases to solve a new problem and the problem of optimal resource scheduling (ors). they define requirements and related meta-heuristics to be applied in each process (retrieve, reuse, revise and retain). faia et al. [5] propose an approach aiming to adjust the instant consumption of a house according to the required reduction values in each moment. this approach couples cbr and an intelligent house management to obtain suggested reduction values for house energy management. authors analyze the history of previous cases of energy reduction in buildings, and using them to provide a suggestion on the ideal level of energy reduction that should be applied in the consumption of houses. gonzález-briones et al. [6], [11] aim to prevent temperature jump of the heating, ventilation and air-conditioning (hvac) system by anonymously analyzing parameters influencing energy consumption. while, considering the presence of people in the building as well as forecasted in-door and out-door temperature fluctuations. they propose a multi-agent system to optimize energy usage relying on information related to the inhabitants captured by sensors and a cbr system, in conjunction with the current indoor and outdoor temperature together with the future temperature. based on cbr, the system recommends the best possible energy saving techniques in the building and propose changes in the habits of the inhabitants. minor and max [12] investigate the replacement of traditional proportional-integralderivative loops (pid) controller by a cbr system for the experience-based control of inert systems and demonstrated the feasibility of the approach for the reduction of energy wastage. kadir et al. [13] show that energy consumption of a building can be predicted by focusing on the properties of the data and their pretreatment methods. authors use automatic learning algorithms for the prediction. problem statement the aforementioned works are limited in three points. firstly, several cases with similarity between each others are required to reach good results and existing cases in the case base should cover every possible option or at least similar cases. these facts are difficult to verify, especially in early stages of the management and execution. concerning this issue, this research supposes to have a consistent dataset as input. secondly, the proposed cbr approaches are so far specific and problem-oriented. and the application of these models in other area, or slightly different problems, require significant changes. this research intends to provide functionalities in each cbr process so that they can be parameterized to every problem instance. thirdly, the rules obtained in the revise stage are subjective. this research relies on supervised learning to produce knowledge to adapt the solution to fit to the problem’s new case. 2 eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 a case based reasoning coupling multi-criteria decision making with learning and optimization intelligences: application to energy consumption 3. background this section presents different concepts required for the cbr proposal. 3.1. case-based reasoning the case-based reasoning is the result of the work of roger schank and his students at yale university in 1980s [2]. the purpose of his work was based on dynamic memory and learning for the story set in natural language [14]. the first cbr system called cyrus was developed by janet kololner using schank’s ideas [5]. this system was fundamentally focused on a question-and-answer system concerning the various trips and meetings of former secretary of state cyrus vance [15]. bruce porter and his team later developed the protos system which is a cbr system used in the classification of stains [16]. cbr is a knowledge-based system where the most suitable solution to a decisionmaking problem based on the most similar cases stored in a database [17]. based on its methodology, casebased reasoning means using old cases from the case database to find the solution to a new case, adapting old solutions to new solution requests or using old cases of the case database to compare and or criticize new situations [18]. case-based reasoning is based on artificial intelligence tools used by designers to build knowledge-based systems. it requires little effort in terms of acquiring bias judgements from experts. the choice of cbr will therefore provide the final system with memory and history. figure 1 illustrates the process of cbr including four steps : retrieve, reuse, revise and retain. figure 1. cbr steps [2] retrieve. this step extracts knowledge, relevant cases that solve the given target problem [19]. the retrieve phase is very important for cbr utility as shown in figure 1. it finds similar cases to the new case in the case base and compares them with the new case. this stage has some classical methods like k-nearest neighbours(k-nn) [19], or methods based on artificial intelligence like artificial neural networks [18] as well as genetic algorithms. park et al. [20] demonstrate that statistical tools can also be exploited to recover best similar cases, by recovering the optimal number of neighbours according to their probability of similarity. reuse. as shown in figure 1, the reuse phase is the second stage of cbr. this step is responsible for proposing a solution to the new problem [21]. it is easy when the similar case of the retrieve step is sufficiently similar to the new case because the solution of the new case will be just that of the similar case found. the following approaches can be exploited in this case [22]. majority rule: the solution is the class ci with the larger number of votes(maxcount), i.e., the class that has solved the larger number of cases in the set of retrieved cases (rc). sq = argimaxcount(ci , rc) (1) probabilistic scheme: this procedure assigns probabilities to each possible outcome or class ci . the class with the higher probability is selected. p(sq = ci) = ∑ j∈rcsim(pq, pj )λj∑ j∈rcsim(pq, pj ) (2) where λj = 1 if sj = ci , 0 otherwise. class-based scheme: this procedure determines, for each class ci , the mean distance of the query case with the cases belonging to ci , and takes the class with the minimum average (minmeant). sq = argiminmeancisim(pq, pj ),∀j, (3) the reuse process becomes more difficult when the retrieve cases have significant differences. one must therefore be able to adapt the solutions of the retrieved cases to obtain new solutions. according to kolodner [18], adaptation can be done in two ways: substitution and transformation. garza & maher used evolutionary algorithms in [23] and suganthan used nature-inspired metaheuristics optimization algorithms in [24]. this step aims to map the solution from the previous cases to the target problem [25]. there are two major steps involved in adaptation: figuring out what it is needed to be adapted and applying the adaptation [21]. revise. the revision process begins when the reuse phase is finished (see figure 1). the purpose of this part is to evaluate the proposed solution in the reuse process that is normally done by simulations. it is noted that simulations often neglect important aspects of reality [5] because one can not always formulate all 3 eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 the aspects that can occur in the real world [26].this step simulates the new solution in the real world and revises it if necessary [27]. retain. this is the last phase and it keep the right solution in the case base. it is often good to record the specification of problem and the solution for future use. veloso et al. [28] shows that it is recommended to store the final solution along with its knowledge structure. this knowledge is exploited to build the new solution to have a decision-making process. this step stores the resulting experience as a new case in memory after the solution has been successfully adapted to the target problem [29]. 3.2. analytic hierarchy process analytic hierarchy process (ahp) is a multi-criteria decision making (mcdm) technique developed by saaty [30]. it models an unstructured problem into a hierarchical structure of elements. the components of the hierarchy include the main goal: criteria that affect the overall goal and that can be used for selection of the final solution and sub-criteria that influence the maincriteria and the alternatives to solve the problem [31]. a pairwise comparison matrix is made by expert’s opinions under the saaty’s preference scale as given in table 1. table 1. saaty’s scales scale compare factor of i & j 1 equally important 3 weakly important 5 strongly important 7 very strongly important 9 extremely important 2, 4, 6, 8 intermediate value between adjacent scales this work uses only the three first steps concerning the determination of weights [32]. the first step builds the pairwise comparison matrix. ann =  a11 . . . a1n ... . . . ... an1 . . . ann  (4) where n is the number of attributes from data, aij is the saaty’s comparison value between attributei and attributej . aij = 1 when i = j and aji = 1/aij . the first step costs about n2 + α, α ∈ r. the second step constructs the normalized decision matrix. cij = aij∑n j=1 aij , i, j = 1, ..., n (5) this step requires n2 + β, β ∈ r. the third step determines the criteria weight vector w by averaging the entries on each row of the normalized matrix. this step requires about n2 + σ, σ ∈ r. wi = ∑n j=1 cij n i = 1, 2, ..., n (6) at the end, performing the vector of attributes weights is solvable in polynomial time proportionally to the square of the number of attributes, i.e (n2 + α) + (n2 + β) + (n2 + σ ) = 3n2 + α + β + σ,with α, β, σ ∈ r. 3.3. cosine similarity model cosine is the most popular euclidean distance based metric for text classification [33] and [34]. it is determined as in equation (7) and its value is between 0 and 1. more its value is closest to 1, more the both vectors are similar. cos ine(a, b) = ∑n i=1 ai × bi√∑n i=1a 2 i √∑n i=1b 2 i a and b are two vectors. (7) 3.4. particle swarm optimization pso is developed by kennedy and eberhart in 1995 [35]. according to [36] and [24] it is considered as the most popular nature-inspired metaheuristic optimization algorithm. the pso algorithm is directed by personal experience (p best), overall experience (gbest) as well as the current movement of the particles to decide the next positions in the search space. additionally, experiences are accelerated by two factors c1 and c2, and two random numbers generated between [0, 1] whereas the current movement is multiplied by an inertia factor w varying between [wmin, wmax]. the initial population (swarm) of size n and dimension d is denoted as x = [x1, x2, ..., xn ]t , where ‘t ′ denotes the transpose operator. each individual (particle) xi (i = 1, 2, ..., n ) is given as xi = [xi,1, xi,2, ..., xi,d ]. also, the initial velocity of the population is denoted as v = [v1, v2, ..., vn ]t . thus, the velocity of each particle xi , (i = 1, 2, ..., n ) is given by vi = [vi,1, vi,2, ..., vi,d ]. the index i varies from 1 to n whereas the index j varies from 1 to d. the pseudocode of pso is given in algorithm 1 [37]. complexity this part evaluates the time complexity of pso algorithm. • line 1 contributes for one (01) operation; • line 2 contributes for n operations; • line 3 contributes for one (01) operation; 4 naomi dassi tchomté et al. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 algorithm 1: pseudocode of pso. 1 set parameter wmax, wmin, c1 and c2 of pso ; 2 initialize population of particles having positions x and velocities v ; 3 set iteration k = 1 ; 4 calculate fitness of particles fki = f (xki ), ∀i and find the index of the best particle b ; 5 select p bestki = xki ,∀i and gbestk = xkb ; 6 w = wmax − k ∗ (wmax − wmin)/maxite ; 7 update velocity and position of particles ; 8 v k+1 i,j = w ∗ v ki,j + c1 ∗ rand() ∗ (p bestki,j − x k i,j ) + c2 ∗ rand() ∗ (p bestki,j − x k i,j ) ; ∀j and ∀i ; 9 xk+1 i,j = xki,j + v k+1 i,j ; ∀j and ∀i ; 10 evaluate fitness fk+1 i = f (xk+1 i ), ∀i and find the index of the best particle b1 ; 11 update gbest of population ; 12 if fk+1 i < fki then 13 gbestk+1 = xk+1 j 14 else 15 p bestk+1 j = p bestkj 16 update p best of population ; 17 if fk+1 b1 < fkb then 18 gbestk+1 = p bestk+1 b1 and b = b1 19 else 20 gbestk+1 = gbestk 21 if k < maxite then 22 k = k + 1 and goto step 6 23 else 24 goto step 25 25 print optimum solution as gbestk ; • line 4 contributes for 1 + logn operations with a binary search to look for index of the best particle; • line 5 contributes for two (02) operations; • line 6 7 perform n iterations in outer loop and use bubble sorting algorithm with six (06) operations; • line 8 performsn iterations in outer loop for nine (09) operations; • line 9 performs n iterations in outer loop for one (01) operation; • line 10 performs logn operations to look for the best element (binary search); • line 11 performs one (01) operation; • line 12 to line 15 perform one (01) operation; • line 16 performs one (01) operation; • line 17 to line 20 perform one (01) operation; • line 21 to line 24 perform one (01) operation; • line 25 performs one (01) operation. • n.b: the goto operation indicates k iterations in a outer loop from line 6 to line 22. in summary, t(n) = 1 +n + 1 + (1 + logn ) + 1 + k(6 + n logn +n (9 + 1) + (logn + 1 + 1 + 1 + 1 + 1 + 1)) = n + logn + k(10n + 12 + logn +n logn ) + 4. pso includes two inner loops based on the population n, and one outer loop for iteration k (from line 6 to line 22). the complexity time t(n) is linear in terms of k, which is in fact, the number of iterations of the particle movements. higher, the number of iterations, higher is t(n). the main computational constraint concerns evaluating complexity time related to the objective function (#obj). therefore, t(n) = n + logn + k(10n + 12 + logn +n logn ) + 4 + #obj 3.5. k-nearest neighbors k-nearest neighbours (k-nn) is a supervised learning technique used for classification based on majority of k nearest neighbours [38] and [39]. it relies on euclidean distance based metrics to determine minimum distance from the query instance to the training samples to determine the k-nn. the pseudocode of k-nn is given in algorithm 2 [40] and is illustrated in figure 2. algorithm 2: pseudocode of k-nn 1: the data is loaded. 2: the value k is initialized. 3: for every point in the training data 4: distancevector <calculate the distance between testing data and each row of training data. here, euclidean distance or other metrics such as chebyshev or cosine can be used. 5: vectorsorted <sorting distancevector in ascending order based on distance values; 6: topk <get top k rows from vectorsorted; 7: frequentclass <get the most frequent class of these rows; 8: return frequentclass 3.6. k-means clustering k-means [41] is an unsupervised learning technique used for clustering. the following steps [42] are involved in k-mean clustering and is illustrated in figure 3. 5 a case based reasoning coupling multi-criteria decision making with learning and optimization intelligences: application to energy consumption eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 figure 2. k-nn • k observations are randomly selected (they are called centroids); • each instance in the dataset is affected to a cluster represented by nearest (euclidean distance) centroid; • once the clusters are constituted, the centroid is updated for each cluster to the mean of all cluster members. and the cluster constitution reinitializes with new centroids. this step is repeated until the centroids become themselves mean of clusters. it means that the centroid become unchanged; • the prediction of a test sample is done based on the nearest centroid calculated based on euclidean distance. 3.7. support vector machine support vector machine (svm) [43] is a discriminative classifier defined by a separating hyperplane. the algorithm outputs an optimal hyperplane given labelled training data (supervised learning) to classify new data. in two dimensional space, this hyperplane is a line dividing a plane in two parts, where each class belongs to either side. as shown in figure 4, points in star and in circle can be separated with an infinite number of hyperplanes. the best hyperplane maximizes the margin. the margin is the distance between the hyperplane and a few close points. these close points are the support vectors because they control the hyperplane. the support vector classifier fails if the data is not linearly separable as in figure 5. in this case, the aforesaid problem is solved through transformation of original feature space. it requires a nonlinear separation to a feature space that can be separated by a linear function. these approaches include linear kernel, polynomial kernel and gaussian kernel. 3.8. regression regression refers a model which relates dependent attributes to independent attributes as shown in figure 5. it is used to predict a variable in terms of other variables. simple linear regression models relationships between a dependent variable and an independent variable. multiple linear regression is an approach to model the relationship between a dependent variable and several independent variables. svm regression [44] is used within the scope of this work. the version of svm for regression was proposed in 1996 by vapnik et al. and baptised as support vector regression (svr) [45]. svr is illustrated in figure 6. it differs from svm in some aspects. svr deals with continuous classes by setting a margin of tolerance 6 naomi dassi tchomté et al. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 figure 3. k-means figure 4. svm figure 5. non linear separation (epsilon) in approximation to the svm. the main idea remains the same: minimize and tolerate error, and determine the hyperplane which maximizes the margin. a svr problem is formulated as [46] min1 2 ‖ w ‖ 2, where ‖ w ‖2 is the magnitude of the normal vector to the surface being approximated. subject to, yi − wxi − b ≤ ε and wxi + b − yi ≤ ε where xi is the a training sample with target value yi . 7 a case based reasoning coupling multi-criteria decision making with learning and optimization intelligences: application to energy consumption eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 ε is a free parameter which is used as a thresold: true positives are predicted within a ε range. figure 6. linear svr 4. model development the proposed approach, namely case based reasoning architecture based on machine learning (cable) is structured in three layers as shown in figure 7. the retrieve layer relies on an adapted cosine similarity combined to ahp, k-nn and k-means to determine the most similar cases to the query case. the reuse layer formulates the prediction problem as a linear programming problem on the similar cases and exploits an optimization technique to obtain the solution of the query case. the revise layer improves the detection efficiency based on a certain threshold, by using svr. methodologies for predicting a case solution are presented in the following sections. 4.1. retrieve the aim of retrieve is to provide the most similar cases to a new incoming case. there are some components to describe to achieve this mission. case base. the case base is represented as relational matrix depicted in table 2 where attribute i refers to characteristics of the case and solution i is the solution value obtained for the problem case i. v alueij is the value of the attribute, which could be of type continuous, discrete, ordinal or nominal. the solution can be discrete or continuous. generation of attribute weights. considering the importance of an attribute is relevant to improve performance of cbr systems [47–49]. literature exploits [47] the whole costly process of ahp to determine the weights of attributes. on the contrary, some steps are considered to obtain the normalized vector of weights ( see section 4.1. each attribute refers to criteria. the pairwise comparisons are determined through interviews with domain experts under the saaty’s scale to compare attributes with each others. consistency (lower to 0.1) is checked according to responses [30]. the details on similar case retrieval are described in the following section. determination of similar cases. this step takes as input a query case (cq) and finds similar cases based on distance measures. at this stage, the query case only includes of attributes associated to weights with a solution to be determined. three steps are performed to get similar cases. first, the similarity measure is computed between the query case and every case in the case base. this operation is realized with the adapted cosine, which considers the importance of attributes as proposed in equation (8). cosinemod(a, b) = ∑n i=1wiaibi√∑n i=1wia 2 i √∑n i=1wib 2 i (8) therefore, it takes each case with its pairs (attribute, weight) as determined by ahp. there are therefore as much similarity values as the number of cases. for instance, if the case base has hundred cases with solutions, then there will be hundred similarity measures. each case is possibly similar to the query case. at this point, it is important to define the criteria to select cases considered as similar. we adopt to realize it by experimentally finding a value (α) varying in the range [0.1, 0.9], which provides the higher number of cases closer to cq. the logic exploited here is that more experiences, a person has, more that person can make a decision on a future similar problem. it is justified by the fact that the person has enriched with enough knowledge. in this regards, more there are cases, much precise is the determination of the query case solution. cases with a similarity greater than (α) are consequently taken. determination of the most similar cases. the first activity here is to transfer the similar cases (without their solutions) to k-means to create cluster of cases that are similar to each other. the intention is to put together cases with similar characteristics trend. the algorithm k-nn is then taken into account to match the query case into the closer cluster. this cluster is determined based on calculation of euclidean distance between previous cluster centroids and the query case. the selected cluster includes the most similar cases. for instance, k-means provides the following output: 1, 1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2. the position represents the case index and the value is the cluster identifier to which the case belongs. in this example, case 1, case 2, case 9, case 10 belong to cluster 1. case 3, case 4, case 5 belong to cluster 2. the next step consists to apply k-nn to determine in which cluster the query case fits better: it is a classification problem. in other words, this step 8 naomi dassi tchomté et al. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 figure 7. cable cases attributes solutions attribute1 attribute2 ... ... attributem case1 v alue11 v alue12 ... ... v alue1m solution1 case2 v alue21 v alue22 ... ... v alue2m solution2 ... ... ... ... ... ... ... ... ... ... ... ... ... ... casen v aluen1 v aluen2 ... ... v aluenm solutionn table 2. case base determines the centroid most closer to the query case, based on euclidean distance. in case, several clusters are equally distant, the operation is restarted based on cosine distance. at the end, there are two outputs. • the cluster with the centroid with the smaller euclidean distance is selected; • the cases belonging to that cluster are elected as the most similar cases for the problem. 4.2. reuse this stage aims to take the set of most similar cases to deduce the solution of the query case. for that, as described in section 3.1, there are three main possibilities. first, the attributes are modified; second, the problem structure is modified; and third, solution of the retrieved cases are together merged to the query case while changing some parameters such as attribute weights. the adopted method is the last option because the two first options modify either the original problem structure. this situation is represented as a model of relationships between different cases. that is, to determine a linear function between the solutions and case attributes, based on the actual structure of the case base. this problem can be modelled as a linear programming model as shown in equation 9, where • xij is the attribute i’s value of the case j; • wi is the ith ahp weight; • rj is the solution value of the case j. 9 a case based reasoning coupling multi-criteria decision making with learning and optimization intelligences: application to energy consumption eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 rj = w1xj1 + w2xj2 + w3xj3 + ... + wixji (9) equation (10) is obtained after applying equation (9) to the set of retrieved cases. x11 . . . x1i ... . . . ... xj1 . . . xij  ∗  w1 ... wi  =  r1 ... rj  (10) variables called errors in equation (11) are the gap between the expected solution and the scalar of casei by the vector of weights.  x11 . . . x1i ... . . . ... xj1 . . . xij  ∗  w1 ... wi  −  r1 ... rj  =  e1 ... ej  (11) the objective function in equation (12) has been adopted from [5] with the main goal of minimizing the sum of square root of the error ej . this function reaches a minimum value when the minimum combination of weights is obtained by solving each of the equations resulting from the matrix calculation. minf (e) = 2 √√√maxj∑ i=1 (e2 j ) (12) particle swarm optimization (pso) is used to find the optimal weights in equation 12. the query case’s solution is simply calculated by substituting the attribute’s optimal weights and its attribute values. evaluating the objective function costs about #attribute ∗ #cases for solving the linear system. #attribute is the number of attributes and #cases is the number of cases. 4.3. revise this activity is about improving the solution of the case query so that to minimize errors. it includes different steps. step 1 the case base c is splitted in possible x% training cases (training) and y% testing cases (testing) such that x belongs to 50%, 55%, 60%, 65%, 70%, 80%, 85%, 90%, 95% and y is 100% − x. for each splitting, perform step 2 to step 4 step 2 the svr algorithm is applied to the training cases to obtain the model of regression svrmodel. step 3 for each testing case, (a) compute µtestingcase such that µtestingcase = 1 − mean(solutionretrieve(testingcase)) solutionreuse(testingcase) (13) solutionretrieve(testingcase) provides solutions of the most similar cases for the testing case and solutionreuse(testingcase) gives the solution of the testing case obtained in the reuse. the set of training cases is considered as the case base to obtain solutionretrieve and solutionreuse. (b) determine µmin as the smallest of µtestingcase. step 4 determine the solution of the query case (newcase) such that solutionrevise(newcase) ={ svrmodel(newcase) µnewcase > µmin solution1reuse(newcase) otherwise solution1reuse(newcase) is computed on the original c to obtain the solution in the reuse. svrmodel(newcase) predicts the solution of the query case based on the regression model. 5. tests and validation this research focused on proposing a reliable scheme to estimate solutions of new case problems. various experiments using the collected cases were conducted to test the reliability of cable. all the scripts have been written using matrix laboratory (matlab) version 2018a because this environment basically includes pre-integrated machine learning and optimization packages. the hardware consists to a machine with a processor core i5 of 3.20 ghz and a memory of 8 gigabytes with microsoft windows 8 as the hosted operating system. 5.1. experiment design and process the experiment design has chronological phases as illustrated in figure 8. the first phase is the collection of the dataset, which includes different cases related to energy consumption. the second phase concerns the application of cable on the gathered data. this phase includes application of different layer processes involved in cable. experiments based on ttest are exploited to determine which reuse algorithm provides best prediction results as well as to examine which whether reuse or revise is precise in prediction. the final performance of cable is obtained by computing the prediction accuracy based on root mean square error (rmse) since the target variable is continuous. the last phase aims to measure effects of varying k-nn and pso parameters on the retrieve and reuse results. this phase is validated by studying consistency of the retrieved cases obtained for each parameter value. 10 naomi dassi tchomté et al. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 collecting reliable data application of cable investigations of impact of parameters 1 2 3 validation based on rsme validation based on test statistics validation based on the retrieved cases figure 8. experiment design table 3. description of dataset attributes attribute description da_demand(a1) day-ahead cleared demand rt _demand(a2) real-time demand da_lmp(a3) locational marginal price one day ahead da_ec(a4) energy part of the day ahead price da_cc(a5) congestion part of the day ahead price da_mlc(a6) marginal loss part of the day ahead price rt_lmp(a7) real-time locational marginal price rt_ec(a8) energy component of real-time rt_cc(a9) congestion component of real-time rt_mlc(a10) marginal loss component of real-time dry_bulb(a11) dry-bulb temperature in °f for the weather station dew_point(a12) dewpoint temperature in °f for the weather station reg_service_price(a13) regulation market service clearing price reg_capacity_price (a14) regulation market capacity clearing price system_load(a15) real load corresponding to the energy demands 5.2. collecting of data the dataset is collected from of nyiso [50]. it has 1096 cases gathered day-by-day during two years from the first of january 2015 to the 31 december 2017. it concerns electrical consumption of different appliances in market buildings. this dataset has fourteen (14) attributes (a1 to a14) required for assessing energy load (a15), which is the target variable to forecast. they are described in table 3. table 4 presents the types of attributes and some descriptive statistics such as the minimum, the maximum, the mean and the standard deviation of each attribute. figure 9 depicts the distribution of the target variable. this figure illustrates that system_load follows a normal distribution with a skewness of 0.755. figure 9. distribution of the system_load variable 5.3. application of cable this experiment focused on applying cable methodologies (see section 4) on the collected dataset. the dataset has been splitted into training cases and testing cases such that training possibly belongs to 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95% and testing is 100% − x. different experiments take the training set as case base and the testing set includes the query cases to estimate solutions. the overall aim was to estimate the testing solutions through cable schemes and to evaluate prediction performance. retrieve. table 5 presents an excerpt of the case base and a new case. as presented in section 4, this layer aims to find the most similar cases. attributes are weighting with ahp based on 10 surveyed experts in energy domain, who provided comparisons under saaty’s scale. based on the answers from expert, the following attribute weights have been obtained based on the methodology 4.1. w1 = 0.185, w2 = 0.11, w3 = 0.14, w4 = 0.090, w5 = 0.093, 11 a case based reasoning coupling multi-criteria decision making with learning and optimization intelligences: application to energy consumption eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 table 4. data types and descriptive statistics type min max mean standard deviation da_cc continuous -29 2 -0.221 1.436 da_demand continuous 11419 22928 15718.270 1987.782 da_ec continuous 10 241 44.06204380 28.139 da_lmp continuous 10 242.00 44.032 28.405 da_mlc continuous 0.00 3.000 0.120 0.375 dew_point continuous -17.00 74.00 38.917 19.592 dry_bulb continuous 1.00 90.00 53.683 19.399 reg_capacity_price continuous 0.00 435.00 22.977 34.652 reg_service_price continuous 0.00 10.00 0.498 1.750 rt_cc continuous -15.00 23.00 0.029 1.758 rt_demand continuous 11955 23633 16020.553 2082.461 rt_ec continuous 0.00 334.00 42.283 33.008 rt_lmp continuous 0.00 336.00 42.486 33.536 rt_mlc continuous -1.00 3.00 0.108 0.360 system_load continuous 12167 23970 16264.166 2112.897 table 5. case base representation attributes a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11 a12 a13 a14 solution weights 0.185 0.11 0.14 0.090 0.093 0.057 0.048 0.056 0.049 0.044 0.043 0.036 0.024 0.015 case 1 16679 16391 63 62 0 1 45 45 0 0 30 9 6 0 16688 case 2 16924 16649 57 56 0 1 22 22 0 0 31 15 7 0 16934 case 3 15999 16624 53 52 0 0 58 58 0 1 27 25 12 1 16958 case 4 14404 15765 41 40 0 0 77 76 0 1 41 40 21 1 16058 case 5 18036 18557 83 82 0 1 103 111 0 1 19 30 25 3 18867 case 6 18504 19259 82 82 0 1 130 130 0 1 15 10 28 0 19554 case 7 19409 19883 115 114 0 1 127 126 0 1 10 20 24 0 20159 new case 18602 19901 81 82 0 1 99 114 0 1 18 25 26 2 w6 = 0.057, w7 = 0.048, w8 = 0.056, w9 = 0.049, w10 = 0.044, w11 = 0.043, w12 = 0.036, w13 = 0.024, w14 = 0, 015 the adapted cosine provides the similarity results depicted in table 6. table 6. similarity results cases cosine values case 1 0.63 case 2 0.71 case 3 0.52 case 4 0.48 case 5 0.900 case 6 0.911 case 7 0.902 next, the optimal threshold is selected to provide the best similar cases. for that, the following steps are executed while looping from 0.1 to 0.9 with a pace of 0.1. step 1 k-means is used then to form the clusters provided in table 7. step 2 k-nn classifies the new case in different classes. for every alpha, k-nn selects the class {5,6,7} to assign the new case. case 5, case 6 and case 7 are the best similar cases to be retrieved. an experiment has been realized on different dataset splitting to examine similarity trends. for each splitting, the most similar cases are obtained as previously presented and then the average between their similarity measures is calculated. as presented in table 8, the overall similarity scores ranged from approximately 70% to 91%. these similarities show that cases similar to the given case were extracted with a similarity of approximately 80.5%, which ensures the reliability of the retrieved cases for prediction. furthermore, the subdivision (75%, 25%) seems to provide consistent retrieval. reuse. experiments here were achieved based on the dataset subdivision (75%, 25%) because it provided best similarity values (see table 8), therefore optimal retrieved cases. reuse can be performed by copying solution values from the retrieved cases or by adapting historical cases with a mathematical function. two procedures has been used to identify which one fits the best to the problem, adapting and copying. 12 naomi dassi tchomté et al. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 table 7. k-means clustering alpha cases clusters 0.1 empty empty 0.2 empty empty 0.3 empty empty 0.4 case 1, case 2, case 3, case 4, case 5, case 6, case 7 cluster 1={1,2} cluster 2={3,4} cluster 3={5, 6, 7} 0.5 case 1, case 2, case 3, case 5, case 6, case 7 cluster 1={1,2} cluster 2={3} cluster 3={5, 6, 7} 0.6 case 1, case 2, case 5, case 6, case 7 cluster 1={1,2} cluster 2={5, 6, 7} 0.7 case 2, case 5, case 6, case 7 cluster 1={2} cluster 2={5, 6, 7} 0.8 case 5, case 6, case 7 cluster 1={5, 6, 7} 0.9 case 5, case 6, case 7 cluster 1={5, 6, 7} table 8. experiments about dataset splitting vs. similarity measures subdivisions (training, testing) (50,50) (55,45) (60,40) (65,35) (70,30) (75,25) (80,20) (85,15) (90,10) (95,5) similarity measures 0.79 0.75 0.86 0.84 0.905 0.913 0.77 0.85 0.79 0.70 reusing by adapting the parameters of pso are the following. • inertia weight: 0.9 to 0.4 • acceleration factors (c1 and c2): 2 to 2.05 • population size: 10 to 100 • maximum iteration (maxite): 100 to 500 • initial velocity: 10% of position in this appraoch, testing solutions are obtained when pso converges. figure 10 shows the gap between the solutions obtained after pso convergence (graph in red) and the expected solutions (graph in blue). figure 10. reuse results figure 10 reveals some gaps between the expected solutions and predicted solutions. moreover, cable is able to optimize testing solutions through pso with an accuracy of 0.88. reusing by copying in this scheme, solutions of testing cases are determined by applying the majority rule (mr), the probabilistic method (pm) and the class-based method (cm) as described in section 3.1. table 9 is an excerpt of the first nine case solutions calculated in each technique (according to section 3.1). 13 a case based reasoning coupling multi-criteria decision making with learning and optimization intelligences: application to energy consumption eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 the first remark is that mr, pm and cm have values that are sometimes repeated across cases. mr has its majority value 15153 copied in all cases; pm has either values 15192 or 15409 that are repeated across cases and cm has either values 17480 or 16086 obtained in different cases. this situation is explained by the fact that these models compute solutions independently from the case base structure. it is therefore observed that these estimations can be efficient only in some cases. the next section investigates which reuse model (mr, pm, cm or pso) makes solution estimations more closest to the expected testing solutions (see the column "expectedsolution" in table 10). to achieve this objective, expectedsolution is compared indepedently to mr, then to pm, then to cm and to pso. the statistical technique t-test is used to check if the means in each case are significantly different from each other. t-test the aim here is to examine, for example, whether expectedsolution and pso values, are different on average, then pso could not be chosen as the one getting closer to the expected values. the hypotheses are the following. ho(null hypothesis) the sample means are equal or they do not have any significant difference. for instance, expectedsolution’s mean and pso’s mean do not have any significant difference. h1(alternate hypothesis) the sample means are different or they have significant difference. for instance, expectedsolution and pso means have significant difference. table 10 presents the results from the statistical test. concerning pso, p (t <= t) = 0.64 > 0.05, ho is therefore accepted. it means that pso and expectedsolution samples have statistically the same means. pso is appropriate to approximate expectedsolution. concerning mr, the difference between mr and expectedsolution means is significant because we have evidence to reject the null hypothesis (p (t <= t) = 5.3971e − 50 < 0, 05). mr differs or moves away from expectedsolution. this conclusion is the same for pm and cm. in view of results, only the test between the expectedsolution and pso reveals that they do not differ on average (from a statistical point of view), and that there is only 5% chance to fail in this assertion. in addition, mean values of pso and expectedsolution are too close as well as their correlation equals 0.995, close to 1. pso is therefore the model which is more appropriate to the expected values. revise. the revision of reuse solutions is made as described in section 4.3. first we experimented different dataset subdivisions as presented in table 11. then we investigated the subdivision which offers the high revise accuracy related to dataset. the subdivision (75%, 25%) offers the best accuracy. figure 11 illustrates results of revise (graph in red) compared to expected solutions (graph in blue). we observe that the accuracy has improved from 88.38% in the reuse to 99.35% in the revise. therefore, some mispredicted testing solutions in reuse has been correctly classified in the revise. the svm regression model effectively improves the determination of solutions. figure 11. revise result we performed a statistical test to investigate whether the reuse approach is better than the revise approach. t-test the aim here is see, for example, whether expectedsolution and reuse’s estimated values, are statistically different on average, then reuse could not be chosen as the one getting closer to the expected values. the hypotheses are the following. ho(null hypothesis) the sample means are equal or they do not have any significant difference. for instance, expectedsolution’s mean and revise’s mean do not have any significant difference. h1(alternate hypothesis) the sample means are different or they have significant difference. for instance, expectedsolution and revise means have significant difference. table 12 presents the results from the statistical test. concerning reuse, p (t <= t) = 0.64 > 0.05, ho is therefore accepted. it means that pso and expectedsolution samples have statistically the same means. pso 14 naomi dassi tchomté et al. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 table 9. first nine case solutions expectedsolution pso mr pm classbasedmethod case 1 16688 16798.60 15153 15192 17480 case 2 16934 17032.85 15153 15192 17480 case 3 16958 16833.86 15153 15409 16086 case 4 16058 15809.71 15153 16911 16086 case 5 18867 18835.71 15153 15409 16086 case 6 19554 19572.17 15153 15409 16086 case 7 20159 20278.36 15153 15409 16086 case 8 20143 20127.56 15153 15409 16086 case 9 18454 18510.97 15153 15192 16086 table 10. t-test: expected solutions mean vs. pso mean (resp. mr, pm, cm) , significance level = 0.05. es: expected solutions t-test: paired two samples for means, alpha = 0.05 es pso es mr es pm es cm mean 16714.4 16769.6 16714.4 15153 16714.4 15588.8 16714.4 16503.1 variance 1957287.0 2051434.9 1957287.0 0 1957287.0 401251.5 1957287.0 409003.8 observations 274 274 274 274 274 274 274 274 pearson correlation 0.99 0.006 -0.10 hypothesized mean difference 0 0 0 0 df 546 273 380 382 t-stat -0.45 18.47 12.13 2.27 p(t<=t) one tail 0,32 2.69855e-50 3.72486e-29 0.01 t critical one tail 1.64 1.650454303 1.64 1.64 p(t<=t) two tail 0.64 5.3971e-50 7.44973e-29 0.02 t critical two tail 1.96 1.96 1.96 1.96 table 11. experiments about dataset splitting vs. revise accuracy subdivisions (training, testing) (50,50) (55,45) (60,40) (65,35) (70,30) (75,25) (80,20) (85,15) (90,10) (95,5) regression accuracy 69.24 86.24 75.24 76.23 90.13 99.35 88.20 79.99 95.12 84.6 table 12. t-test: expected solutions mean vs. reuse mean (resp. revise mean) significance level = 0.05. es: expected solutions t-test: paired two samples for means, alpha = 0.05 es reusesolutions es revisesolutions mean 16714.4 16769.64 16714.4 16713.18 variance 1957287.0 2051434.904 1957287.0 1938675.069 observations 274 274 274 274 pearson correlation 0.995 0.999 hypothesized mean difference 0 0 df 546 546 t-stat -0.45 0,01 p(t<=t) one tail 0.32 0,49 t critical one tail 1.64 1,64 p(t<=t) two tail 0.64 0,991 t critical two tail 1,96 1,96 is appropriate to approximate expectedsolution. concerning revise, p (t <= t) = 0.991 > 0.05, so the difference between both samples is not significant. in terms of mean, revise is statistically equals to expectsolution. revise is also appropriate to approximate the expected solutions with 5% chance to be mistaken. however, 15 a case based reasoning coupling multi-criteria decision making with learning and optimization intelligences: application to energy consumption eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 to choose the model that best approximates, we refer to mean and correlation coefficient values. the results illustrate that expectedsolution and revise means are very close (16713 and 16714). additionnally, the correlation coefficient between expectedsolution and revise is closest to 1 (0.9998) compared to expectedsolution and reuse (0.995). the revise model is therefore the model that best approximates the expected values. 5.4. study of k-nn and pso parameters on the determination of solutions this step investigates the incidence of variability of pso and k-nn parameters, on the determination of similar cases. number of neighbors table 13 provides the similar cases for case 1 based on the number of neighbours in k-nn. for each k, the similar cases are ordered based on the distance considering the fourteen attributes. as k is reduced, the k-nn algorithm selects the most similar cases. the most similar cases are performed until the selection is done for k = 1. table 13 reveals that case 57 is the neighbour closest to case 1 for k = 1. figure 12 shows different case values for k = 10 and case 57 is found as the most closest to case 1 in terms of system_load prediction. this experiment demonstrates that while varying k, k-nn remains consistent in the selection of most similar cases. this result means that the approach used to determine similar cases is effective. figure 12. similar cases for case 1 pso executions case 5 is investigated to analyze the relation between the number k of neighbours and the objective function value. table 14 provides results. the estimation of case 5’s solution with pso is independent to the number of executions of pso. it is justified by the fact that the estimated solution remains the same across k and the objective function is constant. a better value of the objective function is attained when k takes the value of 10. 5.5. discussions determination of similar cases. determination of similar cases. existing works determine similar cases in the retrieve process based on euclidean distance models by randomly selecting the number of similar cases. this work proposes a new scheme based not only on euclidean distance but also on k-nn and k-means for two reasons: the first reason is to take into account continuous solutions using k-means to create clusters. the second reason is that the hyper-parameter k is very useful to set the number of similar cases taken here as the number of voted neighbors. however, the problem still exists. there should be a number of cases at the beginning. therefore, a considerable amount of experiences should be gathered for the same problem. otherwise, k-means and k-nn will lose their performance. collecting such information is sometimes very hard. this scenario is a limitation for cable since similar cases required for reuse and revise would possibly not exits due to dataset size. genericity. cable is composed of different components in different stages. in the first stage, cable includes ahp means of computing attribute weights. the latter takes as input a matrix of pair comparisons between attributes by experts. therefore, it is configurable and not fixed to a particular problem. the other functionalities such as the adapted cosine, k-means and k-nn are adaptable to the dataset taken as input. in the second stage, cable uses pso, which computes the set of weights to apply to each attribute in other to find the solution of the new case. pso depends on the dataset since it takes as input the subset of known cases from the dataset. in the third stage, cable includes an algorithm, which depends on the result in reuse and the svm regression. this algorithm is based on two parameters: the number of training cases (x), and the number of testing cases (y ). the former is used to derive the regression model and the latter is used to obtain the threshold which indicates whether the reuse solution is applied or the reuse solution is revised. these overall descriptions demonstrate that cable is configurable according to the dataset provided as input. it is therefore, generic-dependent to the dataset provided for the forecasting problem to solve. more important it deals with continuous solutions since in the retrieve, kmeans is used to make cluster of retrieve cases before transferring it to k-nn. however, it is limited when one cannot provide enough data at start. in this case, an alternate learning algorithm must be determined, whose performance is not dependent to data size. association of intelligences. this research contributes in the way that cable federates various intelligences and computational approaches: an adapted version of cosine similarity, a multi-criteria decision making, (un)supervised algorithms such as k-nn and k-means, an optimization algorithm and the supervised svm regression. the cbr architecture proposed so far is able to accurately forecast the electricity energy 16 naomi dassi tchomté et al. eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 table 13. similar cases selected for case 1 k index of cases 10 57, 1069, 188, 126, 568, 561, 147, 470, 1019 5 57, 1069, 188, 126 3 1, 57, 1069 1 57 table 14. pso executions for case 5 pso executions measures k=1 k=3 k=5 k=10 100 minimum 18867 18758 18758 18624 mean 18867 18823.66 18813.6 18735 std 0 57.83 44.89 89.70 10 minimum 18867 18758 18758 18624 mean 18867 18823.66 18813.6 18735 std 0 57.83 44.89 89.70 consumption in home buildings and can be generic to other type of dataset with non-discrete class. the efficiency of forecasting after the reuse and revision stages is due to the good measure of approach of similarity implemented in the retrieve stage and the optimization in the determination of solutions. nonetheless, this process of association induces a complexity to deal with in case one does not have enough resources for computing. since input data can be huge, approaches should be designed to avoid unuseful and repeated operations. performance. the cable’s revise varies sizes of training and testing sets. the splitting (75%, 25%) has been found accurate in improving the determination of solutions since accuracy has improved by 11% from reuse to revise. although, this process provides interesting results, it lacks to generalize results to the data structure. it is unsure that the performance remains acceptable if one changes the structure of the dataset: for instance, does the performance remain when the first 20% samples are used for training and the 80% remaining samples are used for testing –or when the first 20% samples are used for testing and 80% remaining for training. 6. conclusion and perspectives iot supports the smart city paradigm in collecting information for making decisions. smart city requires to connect appliances and equipments that consume energy. optimization of energy consumption is therefore a concern for reduce monthly expenses. to address this problem, this paper proposed cable, a threelayer novel architecture of cbr with more generic functionalities. cable combines optimization and machine learning algorithms to forecast energy consumption in buildings. the first layer is made of two ways. the first extends the cosine model to consider attribute weighting while evaluating similarity between cases. the second applies k-means then k-nn to find the most similar cases to the new case. the second layer designs the determination of the solution as a linear programming problem solved with pso on the retrieved cases. the third layer improves the solution with the svm regression model. experiments realized with 1096 samples about electricity energy consumption revealed that the proposed scheme is accurate using the adaptation manner with pso in the reuse. in fact, the revise approach is able to improve accuracy by 11% while reaching around 99% of prediction of expected solutions. the proposed architecture is a big potential to predict continuous solutions for the energy problems. the proposed architecture has two advantages. the first is that it optimizes the prediction of solution based on the association of machine learning and optimization processes. the second is its capacity to adapt to energy problems. as future work, we aim to design efficient retain process concerning integration and indexing of solved cases. references [1] d. b. leake and d. b., case-based reasoning : experiences, lessons & future directions. aaai press, 1996. 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[50] nyiso, “nyiso electricity market data.” http://www. nyiso.com/ accessed 01 october 2019, 2019. 19 a case based reasoning coupling multi-criteria decision making with learning and optimization intelligences: application to energy consumption eai endorsed transactions on smart cities 06 2018 02 2020 | volume 4 | issue 9 | e4 http://www.nyiso.com/ http://www.nyiso.com/ 1 introduction 2 related works 3 background 3.1 case-based reasoning retrieve reuse revise retain 3.2 analytic hierarchy process 3.3 cosine similarity model 3.4 particle swarm optimization 3.5 k-nearest neighbors 3.6 k-means clustering 3.7 support vector machine 3.8 regression 4 model development 4.1 retrieve 4.2 reuse 4.3 revise 5 tests and validation 5.1 experiment design and process 5.2 collecting of data 5.3 application of cable reuse revise 5.4 study of k-nn and pso parameters on the determination of solutions 5.5 discussions determination of similar cases genericity association of intelligences performance 6 conclusion and perspectives this is a title 1 an interactive adaptive learning system based on agile learner-centered design a. battou1*, o. baz2 and d. mammass1 1irf-sic laboratory, faculty of science, ibn zohr university, agadir morocco 2irf-sic laboratory, high school of technology, ibn zohr university, agadir morocco abstract adaptive and interactive learning concepts has apprehended the interest of educational actors and partners, especially in higher education. however, the implementation of those concepts has faced many challenges, particularly in interactive adaptive learning systems (ials). the present paper aims to give the foundation of a framework for an ials that gives extensive attention at each stage of the design process to the end-user: learners. the system proposed is based on balanced combination of agile learning design and learner-centred design to improve teaching effectiveness, facilitate learning among learners, encourage long life learning and maximize motivation as well as reducing the dropout rate. keywords: adaptive learning, interactive learning, ials, agile learning design, learner-centred design. received on 18 december 2017, accepted on 12 january 2018, published on 12 february 2018 copyright © 2018 a. battou et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.12-2-2018.154106 1. introduction one of the challenges faced by developers of ials has been how to design and create quality and pertinent ials, able to build courses based on a model of the goals, preferences and knowledge of an individual learner and use this throughout the interaction for adaptation to the needs of that learner. this is due to the fact that ials deal with diverse backgrounds, such as software developers, web application experts, content developers, domain experts, instructional designers, user modeling experts, pedagogues, etc. [1]. moreover, the process of defining and developing elearning material for an ials is often expensive to produce especially in a single context settingmaking the return on investment difficult to quantify [2]. the most of ials currently available provide similar sets of features. the most of them are designed and developed from scratch, without taking advantages of the experience *corresponding author. email:ambattou@gmail.comom from previously developed applications, because the latter’s design is not codified or documented [3]. thus, development teams are wasting time and efforts to reinvent the wheel. various works have been presented in the literature in order to support the design of ials [2][3][4][5][6]. thus, there are several learning design methods presented in the literature, such as addie, ouldi, design thinking, xproblem, etc. however, the most of them don’t involve the learner until late in the project which is in our view an obstacle for the adaptation of the content to the features of the learner and leads to the dropout. in this work, we focus on one of the recent works proposed to design ials, which is called agile learning design. this choice is based on a comparative study of the most used approaches in the literature that was subject of other publications [7][8]. a learner-centered approach -that is increasingly being encouraged in higher educationwill be implemented with agile learning design process to involve the learner in each stage of the design process. eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e5 http://creativecommons.org/licenses/by/3.0/ a. battou, o. baz and d. mammass 2 the present work aims to present a framework for designing an ials based on agile learning design approach and integrating the learner-centred approach. the structure of the rest of this paper is as follows. the second section provides an overview of the concepts learning design, agile learning design and learner-centred approach. the third section discusses the interest of integrating learner-centred approach into agile learning design. the fourth section describes a case study based on agile learning design approach and integrating the learner-centred approach to teach the “c programming language”. the fifth section provides some of the preliminary results of this work. finally, a conclusion and future work are presented in the last section. 2. background and related work in this section, we present first an overview of the concept of learning design. we provide afterwards a summary of agile learning design and learner-centered design. 2.1. learning design historically, learning design has emerged from instructional design, but with a focus on learning activity as the central concern of the design process [9]. it was presented as a methodology for both articulating and representing the design process and providing tools and methods to help designers in their design process [10]. koper [11] defines the learning design as the description of the teaching-learning process that takes place in a unit of learning (eg, a course, a lesson or any other designed learning event). other authors [9] use the term designing for learning which is defined as the process by which all actors involved in the support of learning arrive at a plan or structure or design for a learning situation. learning design representations enable teachers to document, model and share teaching practice at various levels: from the creation of a specific learning activity, through the sequencing and linking of activities and resources, to the broad curriculum and program levels. 2.2. agile learning design the agile learning design is an iterative model of learning design that focuses on collaboration and rapid prototyping. agile learning design can be adjusted to fit the needs of the learning and training community. it is more a philosophy or ethos, rather than being a methodology, that is best described by its manifesto [12]. several agile methods have been presented and developed (scrum1, extreme programming2, feature-driven development3, etc.) the flow of agile learning design may contain several cycle (fig.1) 1 www.scrum.org 2 www.extremeprogramming.org/ figure 1: the flow of agile learning design each cycle consists of problem analysis in the first phase, followed by the development of a single feature of the final product. once this single small part of your course is finished you can start testing and evaluating the efficiency and the return on investment of this part. if the results are satisfying a new iteration begins, until the course or the project are fully finished, otherwise the designer has to take one step back, understand what went wrong, and correct. there is a variety of agile design practices, in the literature, based essentially on agile manifesto. each of these practices is important, and each is needed. here some of these practices [13]:  active learners participation : learners are involved in the development process, helping to identify and solve problems and mistakes and providing rapid feedback to the team;  collaborative development: all team members constantly interact and communicate throughout the development process, promoting a collaborative and productive environment;  architecture/design envisioning: initial software architecture and requirements are designed at the beginning of a project to identify and think through critical issues;  iterative modeling/ design: software functionalities are designed at the beginning of an iteration to identify team's strategy for that iteration;  model/ design storming: software functionalities are designed on a just-in-time basis to reflect on specific aspects of team's solution;  early and continuous evaluation: testing and validation activities are conducted at the beginning of the project and extend throughout the development process; 3 www.featuredrivendevelopment.com/ eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e5 an interactive adaptive learning system based on agile learner-centered design 3 2.3. learner-centred design the learner-centered design involves methods of teaching that move the emphasis of teaching from the instructor and contents to the learner. in the literature, the terms learner-centered, learning-centered teaching or student-centered learning, are commonly used to design this approach. the term learner centered will be used through this work even if some authors use the other terms. several authors [14][15][16] when the focus becomes learner higher rates of student retention is attained and have better prepared graduates than those students who were more traditionally trained. moreover, mattheu [17] claimed that adopting learner centered approach; learners are proactive independent, responsible for both what they learn and how they learn. the course provides a flexible framework, supportive environment and collaborative learning culture, with faculty guiding learners through their learning as mentors, with the focus on developing students' critical thinking, problem-solving and research skills. this enables them to become effective lifelong learners. the section above presents the two concepts agile learning design and the learner-centered approach and gives some of their advantages. the section below will give some response to how can we integrate learner-centered approach into agile learning design process to improve the teaching effectiveness, facilitate learning among students, and maximize motivation as well as reducing the dropout rates? 3. agile learner-centred design as the proliferation of content, online courses and leaning activities is increasingly significant, learners must take an effective role and be agents for change by taking part of their learning. they must no longer keep up with the change neither be receptive agents who expect their teachers to transmit the knowledge. they must be more productive by participating in the construction of their knowledge and competencies and creating new opportunities for themselves. according to prensky[18], many authors underlined that the didactical formula based on lectures where the teacher teaches (teacher telling or talking or lecturing) and students learn is not more adequate: the new paradigm fostered by the use of technologies is “students teaching themselves with teacher’s guidance” [18]. in line with above, stewart[19], states that learner have to participate actively to the learning process, that is they have to discuss, to read, to write, but also to solve problem, to analyze, to evaluate and to synthesize. to be active, students have to do things in addition to think about the think they are doing; moreover, to be cooperative students have to participate in tasks as a group. therefore, the new role of instructors is facilitator of learning and training. they have to attract all learners, guide and emphasis on debate along courses. as far as the learners are concerned, they have to be cooperative contributors not only listeners. as we can see, the learner-centered approach is in line with the practice of agile learning design cited above (§ii. b). indeed, the two approaches have a lot of similarities such as focusing on learners and their needs; encourage communication and collaboration between learners and teachers, use adaptive and iterative processes to achieve goals. however, some authors such blomkvist[20] and fox[21] claimed that even if agile learning design and learnercentered design are compatible, there are some dissimilarities. as an illustration, we evoke the concept of learner involvement and the end-learner. thus, in the learnercentered design, learners involved in the design process are the same learners that will interact with the system in last. for the agile learning design, learners involved in the design process are not necessarily the end users of the system. this may affect the efficiency of the learning as the end learners are not those who were involved in the design process. blomkvist[20] presents three approaches to explain how learner-centered design may be integrating with agile learning design.  integrating learners-centered design practices into agile development methodology.  apply agile learning design practices into learnercentered design framework.  balanced combination of agile learning design and learner-centered design. the study of the three approaches, lead us to choose the third one because it is in line with our goals. indeed, it permits us to combine the most useful practices of the agile learning design and the learner-centered design to achieve the development of an ials in which learners are part of the team of the design and at the same time they are the end learners. 4. a case of study: 4.1. the design of the framework the agile learning design method used to implement the framework is organized in main four phases (design, develop, test and evaluate). we notice that we use the same phases to design all the components of the framework. in the initial plan and design, we establish the initial content of the ials. in this stage, we use as a starting point, an architectural design of the proposed system which is composed by three main components (fig.2). eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e5 4 figure 1: adaptive content generation process in the following, we present these components, their descriptions, their features and interactions between them a) the domain model: the domain model is characterized by its competence in terms of representation of concepts to learn, the resources available to learners and the structuring of various elements of the field. b) the learner model [19]: the learner model allows changing several aspects of the system, in reply to certain characteristics (given or inferred) of the learner. it includes two type of information grouped in two domains domain independent data (did and domain dependent data (ddd) c) the adaptation model: the adaptation model deals with the generation of adaptive content that will be subsequently presented to the learner. this component has four sub components: the navigation model, the presentation model, the content model and the pedagogical rules. each subcomponent contains a set of rules to achieve the adaptation. after specifying the initial requirement and the main components of our system, every component was subject of a series of iterations, analyzing, designing, developing and testing each feature in turn. in the stage of testing we focused on remarks and feedbacks of learners. we collect all information that could be used to improve the succeeding sprint and to contribute to the constant enhancement process. we notice that all data used in all stage of the design process, were collected through survey or during meeting. the next paragraph presents the learner model design as an example of the implementation of our approach. 4.2. the design of learner model the agile learning design method used to implement the learner model is organized in four phases: establish the initial content of the learner model. in this stage, we use as a starting point, the learner model giving in generic ials that allows changing several aspects of the system, in reply to certain characteristics (given or inferred) of the learner [22]. the learner model in ials includes two type of information grouped in two domains: 1. domain independent data (did): are composed of two elements: the psychological model and the generic model of the learner profile, with an explicit representation [23]. these data are more permanent which allows the system to know beforehand which the characteristics that it must adapt to [24]. the did include several aspects such initial learner knowledge, objective and plans, cognitive capacities, learning styles, preferences, academic profile eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e5 a. battou, o. baz and d. mammass 5 (technological studies, knowledge of literature, artistic capacities, etc.), etc. 2. domain dependent data (ddd): information referring to the specific knowledge that the system judges that the learner possesses on the domain. martins [25] say that the components of the ddd correspond to the domain model with three-level functionality: (a) task level, with the objectives / competences of the domain that the learner will have to master. in this case, the objectives or intermediate objectives can be altered according to the evolution of the learning process; (b) logical level, which describes the learner knowledge of the domain and is updated during the student’s learning process; ( c) physical level, that registers and infers the profile of the learner knowledge. those two elements and theirs contents were discussed with prospective learners, and the member of our team to approve the initial architecture of the learner model, presented below. figure 3 : characteristic used in the learner model plan and create the structure. in this stage, we agree the content of the learner model in adequacy with our learning context. we highlight that we can refine this model (add or delete some content) since we can do iterative design. implement the component. in this stage, we start the implementation, we agree the technologies that we will use to implement our learner model and the design of the learner interface. two different types of techniques are used to implement the learner model: knowledge and behavioral based. the knowledge-based adaptation typically results for data collected through questionnaires and learner studies, with the purpose to produce a set of initial heuristics. the behavioral adaptation results from the monetarization of the learner during his activity [25]. for the did, we developed a form from which we will collect all the information about did evaluate. in this step evaluates and approves the work. some learners create their account in the component of that learner model, fill in the form and evaluate the initial version of the learner model. in this stage, we focus on remarks and feedback of learners. we collect all information that ca be and used to improve the succeeding iteration and to contribute to the constant enhancement process. 5. some results and discuss the first version of the framework presented in previous section, has already been implemented and tested to validate the proposed approach with some selected learners. as we work in faculty, we can’t work in the stage of the design with much learner, especially with our first experience. for the first version of the system we highlight that the agile learning design method allows designs to be modified, repurposed and evolved according to the needs of learners emerging during development. in terms of the applicability of the method, the preliminary results indicate that the method is useful, easy to use. furthermore, it focuses on the final client which is in our case the learners and their interactivity with the system another result is the human contact with the learners, they have not been considered without knowledge but rather partners who participate in the improvement of the system. this motivated them to give their best and develop further learning in the discipline. at the end of the project, we conducted a survey that aimed to have the opinion of the learners on the new way to learn. we can highlight from the results of the survey that the most learners accepted the new learning model and expressed their satisfaction with the new learning experience. this lead us to believe that the implementation of those two approaches in the learning will surly diminish the dropout rate. indeed, learners enjoy learning and give their best when they are involved in the learning experience and considered as partners not only listeners. 6. conclusion in this paper we proposed a general view of how to support de design and the implementation of an ials respecting the agile learning design method and integrating the learnercentered approach. first, we expose the interest of integrating the learner-centered approach and using the agile learning design. furthermore, we present the preliminary results showing the success of this approach in designing and implementation of the components of ials. we intend to complete our system and to enhance our proposal based on the results of the experiment and on the feedback from learners. for further validation, firstly, we plan to embed more learners on the experiment of the all components of ials, enhance our proposal based on the results of the experiment and on the feedback from those learners. secondly, we plan to improve the proposal pedagogical model, including more materials to make learning more effective, amusing and attractive. eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e5 an interactive adaptive learning system based on agile learner-centered design a. battou, o. baz and d. mammass 6 references [1] a,battou, o. baz,mammass (2016) toward a framework for designing adaptive educational hypermedia system based on agile learning design approach. volume 520 of the series advances in intelligent systems and computing pp 113-123. 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[18] m. prensky (2008) the role of technology in teaching and the classroom. educational technology nov-dec. [19] c.j. stewart, c.s. decusatis,k. kidder, j.r. massi, and k.m. anne (2009) evaluating agile principles in active and cooperative learning. proceedings of student-faculty research day, csis, pace university, may 8th. [20] s. blomkvist (2005) towards a model for bridging agile development and user-centered design. human-centered software engineering—integrating usability in the software development lifecycle. pp. 219-244. springer netherlands. [21] d. fox, j. sillito, & f. maurer (2008) agile methods and user-centered design: how these two methodologies are being successfully integrated in industry. agile'08. conference pp. 63-72. [22] p. brusilovsky (2001) adaptive hypermedia. user modeling and user adapted interaction, 11 (1/2), 87-110. [23] a. kobsa (2001) generic user modeling systems. user modeling and user-adapted interaction, 11 (1-2), 49-63. [24] j. vassileva,a (1998) task-centred approach for user modeling in a hypermedia office documentation system. in brusilovsky, p., kobsa, a. & vassileva j. (eds.), adaptive hypertext and hypermedia, dordrecht: kluwer academic, 209-247. [25] a. c. martins, l. faria, c. vaz de carvalho, & e. carrapatos (2008) user modeling in adaptive hypermedia educational systems. educational technology & society, 11 (1), 194-207. eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e5 http://www.agilemanifesto.org/ challenges of ehealth and current developments in ehealth applications: an overview 1 challenges of ehealth and current developments in ehealth applications: an overview saikumari v.1,* and arunraj a.2 1professor and head of the department, department of management studies, easwari engineering college, chennai 2assistant professor, department of management studies, easwari engineering college, chennai abstract healthcare sector is moving towards digitalization in every aspect including e-consultations, surveillance of health,and all other services in healthcare industry. ehealth ends in the remodel of conventional methods of imparting specialist healthcare offerings digitally through the use of technology aimed toward both fee-effectiveness and patient satisfaction who are the customers of health offerings. electronic health records has been maintained by developed countries which makes evaluating patient outcome easier. which makes evaluation of patient outcomes much easier. in the health sector, a variety of new icts are implemented to improve the efficiency of all levels of healthcare. ehealth—or digital health—is the use of ict to improve the ability to treat patients, facilitate behaviour change, and improve health. advances in information and communication technology (ict) and the dissemination of network data processing created a new environment of universal access to information and globalization of communications, businesses, and services ehealth applications were analysed to determine the brand new developments in e-health programs. in this paper, the stakeholders are identified who're accountable for contributing to a selected ehealth challenge. by analysing the current scenario of e-health, we identified the challenges faced by ehealth technologies. the factors influencing the challenges were identified and classified. the emerging trends in the field of e-health was studied and the applications and its benefits towards the patients was also analysed. the paper also elaborates on the role of mhealth in ehealth. keywords: ehealth, health informatics, management, ehealth programs, ehealth utility categories, smart city, artificial intelligence, mhealth. received on 29 july 2022, accepted on 05 september 2022, published on 20 september 2022 copyright © 2022 saikumari et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i18.2261 1. introduction e-health refers to the use of facts and verbal exchange technology to enhance or decorate fitness care. e-health is also referred to as health informatics. the development of e-health systems has expanded many folds over the past decade. over the beyond few years, the ehealth area has grown worldwide. furthermore, some emerging technologies have an immense capacity to transform certain areas of health and social care service. it is to be noted that technology plays a vital role in improving *corresponding author. email: dr.kumaris@gmail.com healthcare prices, affected person safety and excellent in medical care. e-health can play a critical function in facing the challenges within the field of health care. the use of fitness facts generation dates lower back to the mid-90s. areas supposed for ehealth • electronic health facts control; • networks and communication infrastructure • suspension of patient records; • data privacy and security • countrywide research and international cooperation. eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e1 https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:dr.kumaris@gmail.com saikumari v. and arunraj a. 2 some of the important benefits of ehealth applications are: • health care programs enhance useful resource usage (high-quality value effectiveness) • promoting better selection-making. • information and data: additional get right of entry to, availability, speed • professional impact: enhance performance (accuracy, records generation) • useful for evaluating crucial affected person identity data and scientific records. there are many ehealth programs evolved however many guarantees of ehealth research and development have not yet been fulfilled. the effective and green improvement of the ehealth gadget faces many challenges. the most crucial problems are a lack of commitment from fitness care authorities and a lack of interplay between exclusive health data systems. over the beyond decade, researchers have raised numerous challenges dealing with ehealth. it is vital to review those demanding situations and divide them into unique categories. the motive of this paper is to differentiate the ehealth demanding situations into broader classes via a complete review of articles posted on this location [1][2][3]. 2. smart cities and e-health the current population growth and urbanization have ignited a desire to create smart cities by integrating technology into the design of city services”. this renewed desire has resulted in the use of information and communication technologies (ict) to increase critical urban support for larger communities like crime sourcing, emergency response and transportation.[4] the general parameters like traffic conditions, pollution level, temperature, humidity, allergens, pollution and power grid status are perceived using the sensors in smart cities. the values of these different parameters provide information and context that helps the system to monitor and understand the state of a citizen at any given time. responding strategically to the sensed data makes heath care smarter. by gaining real-time access to this information, smart city services can respond immediately to urgent health needs and take critical decisions to avoid unhealthy situations by gaining real time access to the sensor data information [5]. electronic health records and personal health records were introduced in the early 2000 and even played a major role by influencing various decisions of the government regarding investments in healthcare fund. historical data like e-health data, data mining helps the doctors to understand the health condition of the entire population and also to understand the recent health trends. it is estimated that nearly 55% of doctors now make use of electronic health record. and personal health record sources different types of sources provide information to the smart cities. sensor data from the mobile sources and ambient sensor data are some of the sources. these include the information sources listed in the previous section such as mobile device sensor data and ambient sensor data. added to this, data like transportation grid status. vehicular networks, locations of emergency service providers, size of the population can be tapped from city wide sites throughout the region [6]. 3. current challenges in ehealth 3.1. detection of sickness at early stage detection of ailment at early level helps no longer most effective to reduce value of clinical treatment however it is also useful in saving precious lives of humans. for example, detection of cancer at early stage might also rescue man’s lifestyles as opposed to detection of disorder at later degree. the technologies related to e-health falter at identifying the sickness at an earlier stage [7]. 3.2. management of patient’s facts in an efficient manner capturing, storing and maintaining information and accessing information in green manner is likewise a massive venture. efficiently keeping ehr (electronic health report) is a large problem .there is need of clear information requirements to get greatest value in implementing ehealth systems and also reducing cost of health care through the usage of ehealth system. reducing cost of health care with assist of ehealth is a huge challenge. health care systems contain a module called health information exchange. this module aims to get 360 degree view of the treatment plans of the patients and the sufferers [7]. 3.3. effective usage of skills of hsr and it ehealth solutions are developed by expert health service researchers. the challenge lies in saving the time of the expert health service researcher and minimising his involvement in improvement of ehealth. so, combining abilities of each hsr and it expert in an effective way to achieve maximum gain is a highly challenging task [7]. 3.4. establish agreement with between hsr and it expert health service researchers are people who are actively involved in the improvement of the ehealth solutions and work in parallel with the it professionals so, there must be mutual admiration and co-operation among both the teams but troubles arise whilst both hsr and it professional are eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e1 challenges of ehealth and current developments in ehealth applications: an overview 3 interacting with each other. therefore, organising a mutual agreement among each health service researcher and it professional crew is a huge task [8]. 3.5. data privacy in sch programs, a large quantity of information is continuously gathered from and about patients. these data can be modified duplicated, accessed with ease via unauthorized parties through malicious assaults like tag cloning, radio frequency jamming, and cloud polling and spoofing. rfid tags which do not include password and also not protected by encryption over the air can be duplicated and cloned. a radio frequency jammer is a tool used for saving the received radio transmissions using a receiver applicable to its characteristic. this type of assault can interrupt the functionalities of existence-monitoring structures, now and again leading to loss of lives. in cloud polling, traffic is redirected, allowing unauthorized command infusions at once right into a device through a man-in-the-middle assault [7][9]. 3.6. exchange of data amongst different healthcare places patient’s facts interoperability among exclusive health care places like hospitals, private clinics is a key trouble. due to loss of interoperability, statistics stay fragmented, remoted and information analysis cannot be achieved. due to this problem, replacing statistics among exceptional structures is not feasible that's problem to perform fundamental goals of healthcare. who also advocated its members to adopt requirements for powerful exchange of statistics among ehealth implementations and fitness care practitioners. solution to this hassle is making records in a well-known form [8]. 3.7. health care infrastructure it is an uphill task to develop and maintain the healthcare infrastructure. healthcare infrastructure may be complicated because of distinct reasons. populated countries take active steps to increase the number of hospitals and also to provide better healthcare facilities. similarly, geographically dispersed regions have a welldeveloped health care infrastructure. such developed infrastructure should assist ehealth however the infrastructure provides insufficient support to ehealth. there are many factors for such problems to occur. factors ranging from lack of electricity to lack of internet connection. these troubles are extra not unusual in rural regions. however, mobile smartphone infrastructure is growing at a growing price provides opportunities to put into effect structures with much less assets). hence mhealth (part of broader telemedicine discipline) can be useful in presence of insufficient infrastructure. there are also other problems consisting of fragmented records and problems for project scalability. ehealth system infrastructure consists of both hardware and software. it is our fortune that now hardware fee is comparatively low than previous year. due to low fee of hardware developing and beneath growing international locations are in function to make initiative of distributing low cost computers. open source motion is helping constrained useful resource international locations in terms of software. postgresql (an open source dbms) and open mrs (helps to design custom designed ehrs) are two correct examples of open source software [10]. 3.8. shortage of ehealth experts professionals are fewer in this interdisciplinary region and there is also shortage of such experts in the e-health sector. this association laboured in growing countries like singapore and argentina to create a worldwide model tailored to cater to the ehealth requirements. another technique to counter this trouble is to use cellular and telemedicine devices to attach educated assets with population. it is especially useful in rural areas. such initiative is taken in india where in cell tools are being used to screen in retinopathy [10]. 4. recent trends in ehealth programs 4.1. artificial intelligence ai and machine learning are used in this area as solutions to gather, examine and exploit facts to be able to automate sure recurring responsibilities in order that docs can focus on different tasks with higher brought value. these technologies will attain maturity within the e-health area by means of 2030.the uses may be very numerous, inclusive of triage and orientation of sufferers, acceleration of drug improvement, diagnostic help through digital assistants, computer-assisted surgery or epidemiological prevention [11]. 4.1.1. applications of artificial intelligence a) support for clinical decision making it is highly essential for the health professionals to take each and every piece of information into consideration during diagnosis of the patients. if there's a mistake in keeping track of even a single relevant fact, the life of a patient could be put at risk. with the help of natural language processing doctors find it convenient to chart down all relevant information from patient reports. large sets of data could be stored and processed using artificial intelligence and it is useful in creating databases of the patients and enhance individual patient clinical support. eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e1 saikumari v. and arunraj a. 4 b) primary care through chatbots people in general have the tendency to visit a nearby hospital or doctor immediately at the slightest medical issue which at times could be self treated or can be a false alarm. through artificial intelligence doctors can concentrate on more critical and deadly cases as artificial intelligence enables smooth flow of primary treatment and also automation of primary care. medical chatbots is based on ai and is incorporated with smart algorithms that provide instant answers to all the health-based queries and concerns of the patients. and also, chatbots guide them on how to deal with any potential problems. the availability of chat box is 24/7 and they can also handle multiple patients at the same time. c) virtual nursing assistants virtual nursing assistants are facilitated by artificial intelligence systems, and they can perform a variety of tasks like striking a conversation with the patients and guiding the patients to the effective care unit. the virtual nursing assistants can answer the queries of the patients’ and also examine them and provide instant solutions. the availability of virtual nurses is 24/7. nowadays using many ai powered applications virtual nursing assistants has enabled more frequent interactions between patients and care takers in between office visits to overcome any unnecessary visit to the hospital. the world’s first virtual nurse assistant care angel, can facilitate wellness checks through ai and also voice [12]. d) machine vision for diagnosis and surgery computer vision usually interprets the images and videos by machines at par or above human-level capabilities which involves recognising object and scene. image-based diagnosis and image-guided surgery are areas where computer vision is making a strong impact. 4.2. remote fitness remote health has experienced a first-rate increase in the course of the covid-19 health disaster. according to a mckinsey record, telehealth use has extended 38x from the pre-covid-19 baseline. in 2022, it's miles fairly possibly that the telemedicine and faraway fitness services advanced during the pandemic to control sufferers in the context of number one care may be extended to many different specialties and care paths, including intellectual health, tracking of chronic diseases or monitoring of sufferers recuperating from surgical treatment or serious infection. 4.3. internet of things the internet of things, allows an expansion of medical gadgets to be connected to the internet. thanks to those connected items, patients can end up increasingly involved of their fitness. they can use or wear these devices to check their body temperature, blood strain or coronary heart price, and transmit them to a medical doctor who can be able to remotely reveal the affected person’s fitness repute. this type of tool can help patients with chronic sicknesses better control their health and contribute to better care. with the information transmitted, healthcare professionals can, as an example, deliver recommendation to the patient or better prepare for an emergency management [12][13]. 4.4. applications for employee wellness as lifestyles amid a plague prolonged, it had a strong negative impact on the mental health. mindfulness applications like, liberate, headspace and calm weren’t only for the niche target market, as mainstream adoption drove download numbers within the wellbeing application market. employers are more and more spotting that wellness applications might be useful for their personnel. company had taken initiatives like corporate wellbeing retreats, place of job yoga, and crew-building events for many years, but the corporation-furnished wellbeing app is a fantastically new idea [14]. 4.5. virtual reality and augmented reality few years ago, virtual reality seemed like a novelty idea exceptional acceptable to video games. now, virtual reality and augmented reality generation offers a huge variety of sensible uses past gaming and leisure. in healthcare, virtual reality facilitates with surgical education and making plans, allowing both doctors and sufferers to get extra comfortable with procedures. there also are multiple reviews about the efficacy of virtual reality for supporting with chronic pain control and mental strength. markets and markets performed a study on the anticipated boom of ar and vr in healthcare, projecting a 30.7% annual boom charge between 2017 and 2025 [15]. 4.6. mobile health (m-health) one among the subsets of e-health is the usage of handheld devices like mobile phones, which is known as mobile health (m-health). the mobile phones prove to be the handiest tool nowadays, as it has become into a personal object that the most of the people use frequently and does not part with. mobile phones can be used for e-health in a different way: notification of the patient about the about their medication timings through messages that are automatically sent, their appointments that has been scheduled or reminding the pregnant women in detail about eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e1 challenges of ehealth and current developments in ehealth applications: an overview 5 different stages of pregnancy and advice on how to deal with unusual conditions [16]. 4.7. deep learning and medical image recognition “deep” relates to the multi-layered nature of machine learning amidst all deep learning techniques, convolutional neural networks has been the most promising in the field of image recognition. many features of an image are identified through image recognition. additionally convolutional neural networks requires a significant amount of training data that is in the form of medical images along with labels for what the image is supposed to be. convolutional neural networks can adjust the applied weights and filters at each hidden layer of training to improve the performance on the given training data [16][17]. 5.swot analysis on ehealth strength • the date can be collected at ease automatically. • personalised medicine could be given to the patients based on the ailment of the patients. • the patients can be monitored closely through the use of artificial intelligence and other ehealth applications. • the data collected is standardised and can be used as benchmark for further data collection. weakness • the infrastructure required for ehealth is highly underdeveloped • there are high chances of data privacy to be compromised • exchange of data could lead to data duplication and also other complications • the data available on active diseases is highly limited opportunity • the workload of the doctors, could be reduced • emergence of ehealth tools for drug development • the emergence of artificial intelligence also plays a vital role in ehealth • internet of things and usage of convoluted neural networks threat • widespread implementation of unvalidated ehealth tools • ehealth could lead to negative impact on the psychology of the patients • overinterpretation of the role of the patients 6. conclusion ehealth is a research area that is on the rise and has gained the interest of research people, industries, and also the governments throughout the world as it has the potential to transform the healthcare field into an ecosystem that is efficient and effective. the power of data obtained from multiple medical equipment, mobile devices, miniature sensors, and other sources can be harnessed by sch. secondary research was carried out for this study and it has been understood that e-health is facing lot of challenges like data privacy, management of patient’s data, lack of trained professionals, usability and accessibility and also lack of a connected and central patient database. it has been understood from the review of literature that artificial intelligence would play a vital role in ehealth with technologies like chatbot and virtual nursing assistants. through swot analysis some of the strengths of ehealth was found to be ease of data collection, and also close monitoring of the patient and personalised medication. it is suggested that more it professionals could be involved in e-health and proper training about e-health be given to them. despite challenges and weakness, it is incurred from the study that ehealth would play a major role in transforming healthcare industry in the future through the use of technology. references [1] m. carolyn clancy, ‘‘getting to ’smart’ health care: comparative effectiveness research is a key component of, but tightly linked with, health care delivery in the information age,’’ health affairs, vol. 25, no. 1, pp. w589– w592, jan. 2006. [2] smart and connected health (sch) program solicitation nsf 18-541, national science foundation, alexandria, va, usa, 2013. [3] k. taylor, ‘‘connected health: how digital technology is transforming health and social care,’’ deloitte, vol. 6, p. 40, apr. 2015. [4] m. chen, j. qu, y. xu, and j. chen, ‘‘smart and connected health: what can we learn from funded projects?’’ data inf. manage, vol. 1, no. 2, pp. 141–152, 2018. [5] 5.r. vaishya, m. javaid, i. h. khan, and a. haleem, ‘‘artificial intelligence (ai) applications for covid-19 pandemic,’’ diabetes metabolic syndrome, clin. res. rev., vol. 14, no. 4, pp. 337–339, jul. 2020. [6] 6. r. k. r. kummitha, ‘‘smart technologies for fighting pandemics: the technoand human-driven approaches in controlling the virus transmission,’’ government inf. quart., vol. 37, no. 3, jul. 2020, art. no. 101481. [7] 7. k. kumar, n. kumar, and r. shah, ‘‘role of iot to avoid spreading of covid-19,’’ int. j. intell. newt., vol. 1, pp. 32–35, ja. 2020. [8] 8. r. shaw, y.-k. kim, and j. hua, ‘‘governance, technology, and citizen behavior in pandemic: lessons from eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e1 saikumari v. and arunraj a. 6 covid-19 in east asia,’’ prog. disaster sci., vol. 6, apr. 2020, art. no. 100090. [9] 9. m. h. chowdhury, m. n. i. shuzan, m. e. h. chowdhury, z. b. mahbub, m. m. uddin, a. khandakar, and m. b. i. reaz, ‘‘estimating blood pressure from the photoplethysmogram signal and demographic features using machine learning techniques,’’ sensors, vol. 20, no. 11, p. 3127, jun. 2020. [10] 10. a. u. haq, j. p. li, j. khan, m. h. memon, s. nazir, s. ahmad, g. a. khan, and a. ali, ‘‘intelligent machine learning approach for effective recognition of diabetes in ehealthcare using clinical data,’’ sensors, vol. 20, no. 9, p. 2649, may 2020. 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[14] 14. g. ciuti, r. caliá, d. camboni, l. neri, f. bianchi, a. arezzo, a. koulaouzidis, s. schostek, d. stoyanov, c. m. oddo, b. magnani, a. menciassi, m. morino, m. o. schurr, and p. dario, ‘‘frontiers of robotic endoscopic capsules: a review,’’ j. micro-bio robot., vol. 11, nos. 1–4, pp. 1–18, jun. 2016 [15] 15. s. mohammed, h. w. park, c. h. park, y. amirat, and b. argall, ‘‘special issue on assistive and rehabilitation robotics,’’ auto. robot., vol. 41, no. 3, pp. 513–517, 2017. [16] 16. protagon.gr. expansion of the national telemedicine network to another 22 aegean islands [internet]. 2020. available from: https://www.protagon.gr/themata/epektasitou-ethnikou-diktyou-tileiatrikis-se-akomi-22-nisia-touaigaiou-44342094422 [17] 17. detection and characterization of e-health research: a bibliometrics (2001–2016) written by zhiyong liu, jianjun su and lei ji submitted: december 24th eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e1 this is a title 1 influence of urban renewal on the assessment of housing market in the context of smart city development i. rącka 1 * and s. palicki 2 1 the president stanisław wojciechowski university school of applied sciences in kalisz, ul. nowy świat 4, 62-800 kalisz, poland 2 poznań university of economics and business, al. niepodległości 10, 61-875 poznań, poland abstract the variability of the urban environment, where the symptoms are observed in terms of spatial, aesthetic, architectural, urban and socio-economic development, seems to be relevant to the functioning of the local real estate market. housing issue is the vital component of sustainable socioeconomic city development. the perception of the property attractiveness is determined by price-setting attributes such as: building standard, area, utilities, zoning and also location and neighbourhood. the attractiveness of the residential property is manifested in its market value. as part of the follow-urban transformation, it seems to be important to reconstruct the impact of the neighbourhood changes on the housing market. the authors attempt to explain the ensuing problem on the example of one of the streets in a polish city – kalisz, which over the years has gained a new streetscape and market image. they endeavour to simulate changes in the market value of selected properties located on the street, in order to map the influence of changes on the value. keywords: housing market, property value, revitalization, neighbourhood. received on 16 october 2015, accepted on 17 may 2016, published on 20 july 2016 copyright © 2016 i. rącka and s. palicki, licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.18-7-2016.151626 *corresponding author. email:i.racka@pwsz.kalisz.pl 1. introduction symptoms of changes in the urban environment can be seen in a number of aspects: spatial, aesthetic, architectural, urban and socio-economic. they seem to be relevant to the functioning of local property markets. perception of property attractiveness by potential buyers depends on evaluation of its vital qualities, the result of which is an objective economic measure – property market value. this value is affected by all relevant market attributes, which in turn affect a particular property. under this study, observations focused on revitalization processes in dobrzecka street in a polish city, kalisz, in 2006-2014. the analysis was accompanied by identification of trends and dynamics of changes in the local property market in kalisz. the choice of the research object was deliberate – within a few years dobrzecka street gained a new aesthetic streetscape and market image. the main purpose of the study was assumed to be an evaluation and interpretation of the impact of urban transformations upon the economic and social assessment of residential properties. thus, a possibility was recognized of conscious programming of a sustainable city development taking into account the influence of revitalization processes upon attractiveness of the local property market. the research procedure employed the principles of a quantity and quality analysis of the property market (including a statistical analysis of phenomenon structure and dynamics), a case study, a comparative analysis, a methodology of property assessment in a comparative approach, a simulation method and a questionnaire. above research article eaeai endorsed transactions on smart cities eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e2 http://creativecommons.org/licenses/by/3.0/ i. rącka and s. palicki 2 all, a market survey was conducted to evaluate the level of value changes and related factors used by various social and trade groups during their assessment. the article sheds new light on contemporary changes in a smart city space. it simultaneously presents two diverse systems for measuring revitalization outcomes: objective analysis of transfer prices and trends on the residential real estate market as well as the perception of changes from the social perspective. this unusual juxtaposition of quantity modeling with the analysis using sociological methods was intentional. the aim was to directly compare factual and socially perceived response of the real estate market to revitalization. such approach allowed for representation of the perception and response of two groups: those actively involved in the transactions made in the real estate market (investors) as well as the passive users of the domain (observers). the picture obtained as a result, merges two ways of perceiving real estate and its surrounding area – as an economic as well as a social space. the presentation of different reactions of diverse groups of stakeholders helps to better understand and in future better design the changes in space during the process of smart city revitalization. 2. impact of changes in the urban environment upon the property value properties are characterized by interdependence, which means that by possessing a certain image, they affect the surrounding, including properties in the close and more distant neighbourhood [1]. the interdependency in the property market also means spatial and functional interrelations. this kind of interaction is explained by concentration of functions in space, influence exerted by development methods, neighbourhood effects, local site development plans and the power of brand [2], [3]. a diagnosis of the sources and essence of the interdependence first led researchers to consider environmental causes of changes in property values. they analyzed impact of air quality and its pollution upon market listings of flat and house prices [4]. already then, the term of externalities began to be used, which determine change in attractiveness of individual premises in the property market [5]. the externalities also include relations caused by neighbourhood of specific assets or limitations. microlocation may mean a potential asset or a negative circumstance affecting the value, depending on the nature and perception of the neighbourhood. also complexes of properties desired due to popularity, usually improve assessment of their surrounding [6]. the most vivid effects can be observed in commercial property markets where interdependence causes more intense investment activity in the neighbourhood (for instance, ikea, “old brewery: in poznan, “manufacture” in lodz) [1], [2]. it is not only connected with investments in the commercial property market, but also in residential and public properties [7], [8]. studies of the neighbourhood nature and quality consider presence of organized urban greenery and recreational areas (municipal parks or areas accompanying residential estate space) [9], [10]. the widely understood public space and its influence on fluctuations of property value or more generally – on neighbourhood assessment – was analyzed referring to several cities in poland [11], [12]. the said studies prove that among various types of urban public space, centres and representative squares to a large extent determine market aspects of the surrounding development. in the context of transformations in the property market, a lot of attention is dedicated to space transformations, including revitalization processes. the notion of city revitalization combines both revitalization and gentrification. variety of forms and conceptions of developing european urban space as part of revitalization projects or gentrification phenomena [13] points to conscious attempts of determining interdependence effects in the property market. what is interesting from the point of view of evaluating phenomena accompanying city revitalization, is in particular reconstruction of the way it affects the residential and commercial property market [14], [15], [16], [17], [18], [19]. the property market plays an important role in attracting both investors and residents. a huge capital consumed by revitalization processes is a barrier to its development. a rapid growth of prices in the property market, especially in the residential one, attracts entities with strong capital which follow a disinvestment strategy (meaning a relatively quick sale at a high price) [20]. the market value is the estimated amount for which an asset or liability should exchange on the valuation date between a willing buyer and a willing seller in an arm’s length transaction, after proper marketing and where the parties had each acted knowledgeably, prudently and without compulsion [21]. the market value is a resultant of attractiveness of perception of important property qualities. these qualities comprise attributes related to a particular property (such as a standard and technical condition, usable area, plot area, premises location within a building) and other non-related attributes (such as general location, detailed location, neighbourhood nature and quality, available technical infrastructure, designation in the local site development plan). these attributes, called price determining attributes, are defined each time for a market segment where the assessed property falls in. weights of individual attributes may be assigned by examining customer preferences in a particular property market or by analyzing transactional prices [22], [23]. relations between city revitalization or functional and quality surrounding transformations and the property market value in poland are not exhaustively described; they are still open to preliminary analysis. the development level of domestic residential segment suggests a necessity to carefully examine the phenomenon of transmitting revitalization effects in the property market. the market value is determined in relation to properties which can be traded. this value is the most probable price that could be obtained on the real estate market, having taken into account the price levels of realized deals, as well as making the following assumptions: the parties are independent from each other, do not act under pressure and eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e2 influence of urban renewal on the assessment of housing market in the context of smart city development 3 are willing to conclude a deal; the parties have sufficient time to negotiate, according to the market conditions. the market value is determined without taking into consideration the property related sale-and-purchase costs, as well as any additional taxes and fees. one of the approaches to valuating the property is the comparison approach, which is based on immediate comparison against verified market information on transactions, having comparable characteristics, similar to those of the object of valuation [11]. following a selection of comparable properties, in a similar area and of similar characteristics, similar method of construction and other comparable attributes, the significant similarities and/or differences are established, making adjustments to determine a market price, based on which the estimate value of the real estate under valuation is determined. the comparison approach in poland has three forms: the method of pairwise comparison; method of average price adjustment; method of statistical market analysis. in this paper we applied average price adjustment method. the method of the average price adjustment makes use of a group of properties, similar in characteristics to the appraised real estate, that have been a subject of market transactions. under this method an average price adjustment is applied in relation to comparable properties, using weighted coefficients depending on the individual characteristics of the real estate. 3. changes in the market value of living premises in kalisz – a case study analysis of the residential property market in kalisz in 2006-2014 the analysis of the residential property market included sale transactions of flats in kalisz from the beginning of january 2006 to the end of december 2014. the authors analyzed 2,941 market transactions of flats. between 2006 and 2010, the number of transactions declined, however, in the period considered as crisis in the property market in poland, it grew. every second flat sold had an area between 30 sq m and 50 sq m (an average size of a property sold in 20062014 in kalisz was 49 sq m). by examining unit transactional prices, a trend formula was created for flats sold in kalisz between 2006-2014. the linear trend function takes the following form: (1) the average price of one square metre increased month by month by pln 0.27 and its theoretical value in the period immediately preceding the analysis, i.e. in december 2005, amounted to pln 2,108.81. the average increase of residential properties in kalisz property market in 20062014 was found to be 0.39% monthly. throughout the entire analysis the average unit price reached 2,526 pln/sq m (fig. 1). figure 1. average price and linear and exponential price trends [pln per sq m] of flats in kalisz from 2006 to 2014. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e2 4 the goodness of fit of the linear trend function is poor. correlation coefficient r2 equals 11.99%. similarly, the exponential function explains only 13.25% of individual price variability during the analyzed period. because of that, a non-linear model was constructed, explaining the individual price variation over time. the best fit proves to be the degree 6 polynomial function, accounting for 30.72% of individual price variability over time. using this trend function for adjusting the prices for appreciation/depreciation, allows to eliminate at least some of the price differences stemming from the passage of time. other research [24] confirms the low values (30-35%) of the correlation coefficient, even when using polynomial trend functions. this is due to the heterogeneity of real estate – there are no two identical pieces of real estate. the examined sample of apartments was very diverse. the flats traded ranged from studios to 4-bedroom units, with the surface area starting from 13.7 to 138 m2, located centrally, in-between and in the outskirts, differing in standard, fit-out, condition and other variables influencing the price. such a high number of real estate attributes with price influence suggests that the passage of time might not be the dominant factor in this case. by examining unit transactional prices a polynomial trend formula was created for flats sold in kalisz between 20062014. the trend function takes the following form (coefficients have been rounded): (2) the theoretical value in the period immediately preceding the analysis, i.e. in the end of december 2005, amounted to pln 1,322.66. the average increase of residential properties in kalisz property market in 2006-2014 was found to be 0.32% monthly. however, this interpretation does not apply to the price variability within the whole analyzed period – as illustrated by the line of the trend function, the years 20062014 recorded both price increases and decreases (fig. 2). figure 2. polynomial price trend [pln per sq m] of flats in kalisz from 2006 to 2014. characteristics of the analyzed area dobrzecka street in kalisz is about 2.6 km long; it starts near the city centre and reaches the administrative areas of the village of dobrzec. the name “dobrzec” goes back to the oldest tradition of this land and bears a large emotional and historical significance. the first mentions of the dobrzec settlement date to 1280. the street has a non-homogenous nature. its beginning consists of multi-family residential buildings which are about one hundred years old, built close to each other. in the post-war years they were confiscated from private owners by the state and at that time they were mostly tenement blocks. they alternate with other buildings: community services (a blood donor station, social aid centre) and manufacturing (former clothes plant). in its middle section the street is built up with warehouses, engineering and service buildings. the end of dobrzecka street crosses the area of the former dobrzec village, partly transformed into detached house estates, and partly still settlement and farming areas. a particular attention was paid to transformations in the initial sections of the street. this area has changed its character in years. tenement houses administrated then and partly now by a municipal company have been regained by previous owners; other ownership transformations have taken place. the first effective action was the change of ownership of a shabby residential building located at 6 dobrzecka street. the building was later demolished and in 2006 replaced with a new one. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e2 i. rącka and s. palicki 5 a similar step aimed at changing the street character, was the replacement of the old residential structure at the junction of dobrzecka and poznańska streets, where one of kalisz housing associations built the first block of flats in 2005 and the second one in 2008. the obsolete petrol station located at the beginning of the street was dismantled in 2007. in the same year the ownership transformation of the property located at 10 dobrzecka street was finalised enabling its general repair. at the same time, some manufacturing areas, which formerly belonged to kalpo textile plant, were – upon announcing the company’s bankruptcy – bought out by a local investor (a quasi-developer) and transformed into residential areas. construction of a block of flats (flats and apartments) began in january 2008 and finished in december 2009. the result was a 37 m tall building of 9 overground and 1 underground storeys and 100 flats. to make room for this building, the manufacturing facility was mostly demolished. the only thing left was a raw structure which was subsequently developed and a few storeys were added. in 2009 the perpetual administrator (pck) of the property located at 2 dobrzecka street renovated the building, made the façade, replaced the woodwork and roof. recently, renovation of the building at 5 dobrzecka street was completed. in 2014 the legal status of the property located at 8 dobrzecka street was regulated. currently, the third building joining the two residential houses owned by a housing association is being built. the legal status of a few of the properties is still unregulated, there have been no inheritance proceedings carried out, they are not entered into the title deeds register (land and mortgage register). the current law does not provide for the option to demolish an unsafe and unsightly old tenement house which is adjacent to an apartment building. market value of the flats in the analyzed area in order to show changes in values of the flats as a result of positive changes in the surrounding, a flat situated in an old tenement house in dobrzecka street in kalisz was valued. the said flat covering 50.0 sq m is situated on the first floor of a short building, consists of two rooms, a kitchen, a bathroom with a toilet and a hall. its market value was determined. transactions connected with non new-build properties were analyzed, which were located close to the flat and were of a similar technical condition and standard. based on our own analysis and surveys of preferences among potential buyers in property agencies, basic attributes were identified which determine the property’s value as well as their percentage weights. the average annual time trend was found to be 4,6% in 2006-2014. due to non-linearity of the applied trend for price variability, the average value of price variability over time is not an indicator of the future price behavior. therefore, the transactional prices were corrected due to elapsing time based on the degree 6 polynomial function – see formula (2). next, transactions were selected which best correspond to the said flat. for the representative sample, parameters shown in table 1 were identified. table 1. the parameters of a representative sample – flats in kalisz in 2006 and 2014 [pln per sq m]. paramet er 2006 2014 transacti on prices adjusted (polynomi al) prices transacti on prices adjusted (polynomi al) prices minimum price 489 797 679 725 average price 1502 2805 2719 2868 median price 1429 2710 2788 2967 maximu m price 4197 6393 6130 6662 standard deviation 504 923 704 732 coefficie nt of variation 34% 33% 26% 26% the most important asset in the calculation was comparison of the market value of the same flat in two situations – the former unimproved surrounding (picture of dobrzecka street in 2006) and upon the image transformation of the surrounding (picture of dobrzecka street in 2014). the property prices which were the reference point in both situations referred to the same moment – 31.12.2014. as a result, it was possible to maintain comparability of all other market conditions. the results of the property assessment were as follows (fig.3):  pln 113,000 before the surrounding changes (2006),  pln 128,000 after the surrounding changes (2014). interestingly, adjusting of the transaction prices after considering the linear trend function for price variability over time, as per formula (1), may lead to false perception regarding changes in the surroundings of the property being valued. assuming that the price variability in 2006-2014 was linear, the value of the property with the surroundings as per 2006 and price adjusted for 2014, would amount to pln 83,000. if the property was valued with the surroundings as per 2014 and price adjusted for 2014, the value would reach pln 123,000. refining the methodology of the research through the introduction of the polynomial trend function improved the quality of the model used and allowed for more precise representation of the local real estate market. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e2 influence of urban renewal on the assessment of housing market in the context of smart city development 6 figure 3. the value of the flat according to its surrounding in 2006 and 2014 (prices as on 31.12.2014). econometric modelling of apartments value according to their surroundings as the issue of surroundings influencing apartments value has not been fully examined, additional study has been carried out, based on the analysis of 2,945 transactions of apartments sold in kalisz during the years 2006-2014 and the changes in their surroundings which took place at that time. the analysis was carried out on the base of econometric modelling with the use of multiple regression equations. in the chosen procedure, the dependent variables were:  the transaction price [pln/sq m] of a flat,  the adjusted price [pln/sq m] of a flat. 11 independent variables were initially chosen:  x1 – building a block of flats (2 poznańska street),  x2 – destroying and building a new building (6 dobrzecka street),  x3 – renovating a building (10 dobrzecka street),  x4 – destroying a gas station (dobrzecka-poznańska corner/beginning of the street),  x5 – building a block of flats (2b poznańska street),  x6 – building a block of flats (16 dobrzecka street),  x7 – renovating a building (2 dobrzecka street),  x8 – building a pavement,  x9 – renovating a building (5 dobrzecka street),  x10 – building a block of flats (2a poznańska street),  x11 – change in the legal state of a property enabling its renovation (6 dobrzecka street). after carrying out the consecutive steps of regressive elimination, it occurred that the parameters of the regression function did not show statistical significance. estimating the equation of relations between the variables could not be written. perception of space transformation in the analyzed area by kalisz residents one of the purposes of the study was to collect information about perception of changes in the urban surrounding by kalisz residents. the questionnaire asked about feelings and knowledge about changes in the city’s image within the last ten years and about the trend, visibility and image transformation of dobrzecka street (from poznańska to al. wojska polskiego streets). a question was also asked about most likely and desired trends in this area. the survey was designed to recognize and compare knowledge of kalisz inhabitants about changes in values of the properties located there. the respondents were kalisz residents belonging to various groups:  property market specialists (property agents and property surveyors),  clerks employed in kalisz city office,  students from the president stanisław wojciechowski university school of applied sciences in kalisz,  inhabitants of dobrzecka street,  passers-by. table 2. number of surveyed residents. no trade group no of respondents share in total 1 specialists 25 6.6% 2 clerks 70 18.4% 3 students 43 11.3% 4 dobrzecka st residents 43 11.3% 5 passers-by 199 52.4% total 380 100.0% survey results the respondents were asked to define the image trend within the last decade for the analyzed section of dobrzecka street. the changes were perceived as common, repeatable and lacking outstanding diversity. furthermore, dobrzecka eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e2 i. rącka and s. palicki 7 street was evaluated subjectively – despite the changes – as ugly. when asked about the degree of changes in the image of dobrzecka street over the last 10 years, the respondents most often gave neutral answers as they thought the street’s image had changed to some extent (45%). few (17%) considered the changes as visible. the survey also examined the knowledge of trends in flat prices in kalisz. kalisz citizens were asked about changes in flat prices in kalisz within the last ten years including dobrzecka street. the biggest number of the respondents thought that the prices of flats in kalisz and in dobrzecka street had been stable, however, almost as large a group said the prices went up. only 4% marked a high increase of the prices in kalisz – 3% for dobrzecka street. as many as 22% of the respondents thought that flat prices had gone down in kalisz. of the 22% who said that flat prices in kalisz went down, 28% said that flat prices had been stable in dobrzecka street, while other 19% thought that in dobrzecka street they had gone up. also every fifth who thought the prices were generally stable in the city, pointed to their rise in dobrzecka street. what is interesting, (compare: fig. 1) wrong answers about the drop of flat prices in kalisz within the last 10 years were most frequently given by property agents and clerks. the surveyors, students and passers-by marked the price increase whereas the inhabitants of dobrzecka street were convinced of their stabilization. the respondents were asked to identify which presently existing element is the strongest sign of space changes in the analyzed section of dobrzecka street. the block of flats dominated the spontaneous answers. supported answers were similar. even though 100 new flats were built in the analyzed vicinity, as many as 16% thought the social structure of the street inhabitants had not changed while 35% thought it had been poor (fig. 4). figure 4. accents of changes within dobrzecka street. next, they were asked about respondent anticipated and desired trends in that area. spontaneous answers about the desired trends boiled down to two main options:  renovation of tenement houses,  development of transportation infrastructure. next, the respondents were offered a few variants of answers regarding the change of dobrzecka image. the respondents considered the majority of the suggested trends as quite or rather unlikely. the highest score was given to further growth of blocks of flats – renovation of tenement houses (p=0.49). on the other hand, construction of tall buildings is regarded as slight less likely (p=0.38). the respondents also pointed to transfer of the current trend to the farther section of the street or adjacent areas as quite probable (p=0.46). the likelihood of growth of commercial and other functions was estimated by the respondents as p=0.38 and p=0.36 respectively. the last question asked to kalisz citizens was about their satisfaction with transformations within dobrzecka street within the last ten years. most people did not clearly state their attitude to the changes (selected the neutral answer), however, the emotionally burdened answers were mostly positive (fig. 5). the lowest satisfaction with the changes was shown by property agents and passer-bys; the students are slightly more satisfied. among the street inhabitants negative scores prevail, which proves their dissatisfaction with the changes. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e2 influence of urban renewal on the assessment of housing market in the context of smart city development 8 figure 5. the level of satisfaction with the changes within dobrzecka street in the last ten years. 4. conclusions the article discusses a new approach to studying contemporary transformation in a smart city space. measuring the quantitative effects of city revitalization (analysis of transaction prices and trends in the residential real estate market) as well as the qualitative effects (perception of changes in social perspective) allows for comparison of factual and socially perceived response of the real estate market. the study shows the trends and dynamics of the changes in the market value of the flat located in kalisz, dobrzecka street. this area was subject to urban transformations which in 2006-2014 improved the surrounding quality and image and consequently increased attractiveness of the local flat market. the flat’s market value was defined according to its surrounding in 2006 and 2014. due to the simulations taking into account various states of attractiveness of the analyzed flat, it was assessed that should the surrounding’s condition remain relatively low and typical of 2006, its market value would now amount to pln 113,000. however, the actual improvement of the neighbourhood’s image and quality made the value go up to pln 128,000. therefore, in the observed period the real appreciation of the said flat increased approximately by 13%. this change, arisen as a consequence of the local revitalization, proves a connection between transformations in the space and flat valuation. it illustrates possibilities of stimulating price increase in a property market in areas subject to revitalization. consciousness among the respondents of the scale of changes in flat prices is low. they diagnosed the difference slightly higher on the scale for dobrzecka street than for the whole city. when asked about desired trends of changes in that area, the respondents indicated a necessity to modify the social structure. significance of changes in urban space and their market consequences reaches more strongly and quickly to profiteers who seek to multiply their assets through successful investments. general social consciousness is limited and blurred. typical space users behave inconsistently – they notice accents, evident signs of transformations, however, at the same time they say the transformations cannot be easily noticed. they also cannot see a link between changes in the surrounding with prices of flats. in this way, a surprising mechanism was caught of separation between social and market consciousness. this indicates a gap in consciousness or economic competence in the society which is unable to translate significance of physical changes in the space to their market consequences. this phenomenon identifies diverse potential of social consumption of benefits offered by smart city transformation. it is an important factor for consideration to ensure a balanced development of urban areas. references [1] kucharska-stasiak, e. (2006) nieruchomość w gospodarce rynkowej (warszawa: pwn). [2] olbińska, k. (2014) the influence of real estate on its surroundings based on the example of the manufaktura complex in lodz. real estate management and valuation 22(4): 5-16. [3] polko, a. (2005) miejski rynek mieszkaniowy i efekty sąsiedztwa (katowice: ae w katowicach). [4] ridker, r.g. and henning, i.a. (1967) the determinants of residential property values with special reference to air pollution. review of economics and statistics, 49(2): 246-257. [5] mason, g. (2007) revealing ‘space’ in spatial externalities: edge-effect externalities and spatial incentives. journal of environmental economics and management 54(1):84-99. [6] simons, r., quercia, r. and meric, i. (1998) the value impact on new residential construction and neighborhood disinvestment on residential sales price. journal of real estate research 15 (1/2):147-161. [7] emery, j. (2006) bullring: a case-study of retail-led urban renewal and its contribution city centre regeneration. journal of retail and leisure property 5(2): 121-133. [8] trojanek r. and trojanek m. (2012) profitability of investing in residential units: the case of the real estate market in poland in the years 1997-2011. actual problems of economics 7: 73-83. [9] gies, e. (2006) the health benefits of parks (san fransisco: the trust for public land). [10] matusiak, m. (2010) przestrzeń publiczna jako czynnik konkurencyjności miast. in gaczek, w. m. [ed.]: prace eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e2 i. rącka and s. palicki 9 z gospodarki przestrzennej, zeszyt 161, (poznań: wydawnictwo uniwersytetu ekonomicznego w poznaniu). [11] palicki, s. (2013) a valuation of public spaces: selected research results. real estate management and valuation 21(1):. 19-24. [12] tanaś j. (2013) differentiation of local housing markets in poznań suburban area. real estate management and valuation, 21(3):88-98. [13] couch, c. (2003) economic and physical influences on urban regeneration in europe. in couch c., fraser, c., percy, s., urban regeneration in europe, (oxford: blackwell publishing). [14] bryx m. [ed.] (2013) rynek nieruchomości. finansowanie rozwoju miast (warszawa: cedewu). [15] kaźmierczak, b., nowak, m., palicki, s. and pazder, d. (2011) oceny rewitalizacji. studium zmian na poznańskiej śródce (poznań: wydawnictwo wydziału nauk społecznych uam). [16] palicki, s. (2012) interakcje przestrzeni publicznej z rynkiem nieruchomości komercyjnych. przykład śródmiejskiego obszaru poznania. in gaczek, w. m. [ed.], prace z gospodarki przestrzennej. zjawiska i procesy współczesnego rozwoju społeczno-gospodarczego(poznań: wydawnictwo uniwersytetu ekonomicznego w poznaniu). [17] palicki, s. and rącka, i. (2015) wartość lokali mieszkalnych wobec zmian wizerunkowych przestrzeni miejskiej. in palicki, s. [ed.], nieruchomość w przestrzeni (kalisz: wydawnictwo uczelniane państwowej wyższej szkoły zawodowej w kaliszu), ch. 4. [18] belniak, s. (2009) rewitalizacja nieruchomości w procesie odnowy miast (kraków: wydawnictwo uniwersytetu ekonomicznego w krakowie). [19] smith, m. m. and henever, c. c. (2011) the impact of housing rehabilitation on local neighborhoods: the case of small community development organizations. american journal of economics and sociology 70(1): 5185. [20] trojanek r. (2013) fluctuations of dwellings' prices in the biggest cities in poland during 1996–2011. actual problems of economics 2(1-2): 224-231. [21] international valuation standards 2013 framework and requirements (2013) international valuation standards council. [22] rącka, i. (2013) sales of residential properties illustrated with the city of kalisz. the journal of international studies 6(2): 132-144. [23] rącka, i. (2015) czynniki atrakcyjności nieruchomości mieszkaniowych na obszarach podmiejskich kalisza. problemy rynku nieruchomości. biuletyn stowarzyszenia rzeczoznawców majątkowych województwa wielkopolskiego 2: 29-37. [24] frukacz, m., popieluch, m. and preweda, e. (2011) korekta cen nieruchomości ze względu na upływ czasu w przypadku dużych baz danych (real estate price adjustment due to time in the case of large databases). infrastruktura i ekologia terenów wiejskich (infrastructure and ecology of rural areas) 4: 213–226. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e2 influence of urban renewal on the assessment of housing market in the context of smart city development this is a title eai endorsed transactions on smart cities research article 1 open data in smart region o. kodym1,*, j. unucka2,3 and d. létavková4 1 college of logistics, palackého 25, přerov, czech republic 2 moravian–silesian region regional authority, 28. října 117, ostrava, czech republic 3 všb – technical university of ostrava, 17. listopadu 15, ostrava, czech republic 4 coordinator odis, na hradbách 16, ostrava, czech republic abstract putting together up to date particular technical and organizing solutions brings us significant spin-off effecting. with support of information and communication technologies we are able to accelerate innovations, new services in region and its municipalities. we can improve life of citizens, improve regional transportation and deliver unprecedented value in many other areas. industry 4.0 is not the goal but the means. topics and issues in field of public transportation are discussed and some examples of open data processing are presented. 1. introduction the moravian-silesian region today is a varied palette of natural and cultural monuments that inspire life with sporting events and social events of national importance. the interconnection of industrial history with current trends in architecture, education and tourism makes the region and the cities of ostrava a powerful magnet for tourists and visitors, as well as for entrepreneurs and investors. the moravian-silesian region is like a scaled model of the czech republic with mountains on the border and the river odra, which pours life into the whole region and beautifully contrasts with the "steel hradčany", who are witnesses to the history of the region. the region has the same ambitions in terms of sustainable development and the trend of improving the quality of the environment and the lives of its inhabitants. it wants to be a model region that will inspire other regions of the czech republic to implement the concept of a smart region. the moravian-silesian region has for a long time been focusing on improving the quality of life of its inhabitants. this effort is reflected in engaging in strategic concepts of sustainable development and concrete projects. *corresponding author. email:oldrich.kodym@vslg.cz the moravian-silesian region has simplified the definition of a smart region: such region employs modern technology to save time and money of people who live there. the reason for this simplification is the fact that the multitude of definitions makes it impossible to find the one that would be generally recognized and that would clearly express what a "smart city", "smart project" or "smart region" is. in most cases, the term "smart" refers to the application of new technologies, ict in particular, to improve the quality of services and the quality of life in cities and regions. the smarter region strategy should also initiate the emergence of a new industry that will develop and produce products for smart solutions with a high added value. the strategy should contribute to making the moravian-silesian region a leader in the use of smart solutions in the czech republic and an exporter of these solutions from the region itself. the smarter region strategy will be a dynamic process. it will evolve continuously and respond to the development of new technologies and the transformation of social processes, lifestyle, and preferences of people. keywords: smart region, industry 4.0, transportation, open data. received on 2 december 2017, accepted on 15 december 2017, published on 19 december 2017 copyright © 2017 kodym et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.19-12-2017.153480 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e5 http://creativecommons.org/licenses/by/3.0/ o. kodym, j. unucka, d. létavková 2 the smarter region strategy of the moravian-silesian region will also draw on the european commission's working definition which is based on a mapping of smart concepts in european cities [1] and the smart city concept methodology [2]: • a smart city is a city seeking to address public issues via ict-based solutions on the basis of a multistakeholder, municipally based partnership. • it is one of the concepts of applying sustainable development principles to the city management that relies on the use of modern technologies to improve the quality of life and make governance more effective. this concept is most widely applied in the energy and transport systems which can be managed more effectively by deploying appropriate information and communication technologies (ict). nevertheless, it can also be applied to other fields, like waste management or e-government. the era we face as a society is not limited to revolutionary changes in the production and consumption of goods and services. it also relates fundamentally to how society and its institutions in this new context will understand and touch on important issues: what role will the individual, human being – as the proponent and subject of this phenomenon, play in this 21st century society? [4] see fig. 1. figure 1. evolution of embedded systems into the internet of things, data and services [6] 2. strategic management the relationship between characteristics and components of smart region is complex topic. it is very similar to smart cities [7]. in practice, components and characteristics are often difficult to distinguish; components, in particular, are not systematically identified. the central thesis of this section is that they cannot easily be separated and that they should therefore be analyzed together. components can be conceptualized as the building blocks of smart city initiatives. they comprise the inputs, technologies and processes of specific initiatives, as well as the norms or standards deployed. it is summarized in fig. 2. the outer ring shows the components, and the inner ring the characteristics. rather than each component mapping onto specific characteristic, a range of technological, human and institutional factors underpins all characteristics. figure 2. the relationship between components and characteristics of smart region/cities [7] (smart characteristics: eco: economy, env: environment, gov: government, peo: people, mob: mobility, liv: living) this allows us to understand the relationships between components and characteristics as both direct and indirect. in some cases, the characteristic fully describes the initiative by displaying what the initiative is about and the priorities of its participants and direct beneficiaries. the strategic management of the smarter region [5] will be linked to six general areas. infrastructure infrastructure = availability of an infrastructure for open data and information provision of a modern digital infrastructure offering secure yet open data and information to the inhabitants whenever they need access to it in quality that helps them make their decisions. inhabitans inhabitans = concentration of smart solutions on the needs of the inhabitants in the first place public services provided primarily for the benefit of the inhabitants. the needs and problems of the inhabitants are at the focal point in the smart city strategies and take precedence eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e5 open data in smart region 3 over organizational, institutional, or sectoral structures. the development of services is simplified in order to increase enduser convenience while reducing provider costs. agendas related to life events, such as an address change, service payment, as well as subsidy or regulatory agendas, aim at maximal simplification of the process for the inhabitants, while saving both time and costs on both sides. this means to minimize the need, for example, to make arrangements for one event at multiple places and communicate with multiple authorities, or to provide irrelevant information and undergo undue procedures to obtain a subsidy. this concept also includes providing internet services wherever possible in the simplest way for no or minimum fees. systems systems = smart infrastructure, the internet of things, 3e, and security smart systems or the internet of things enabling service providers to use the widest possible range of data to manage and provide services on a daily basis (e.g. air quality measurement), or to make decisions on strategic investments (e.g. collecting and analyzing data about the use of mass public transport for community planning of its modifications both on the city and the regional level). it is essential to provide real-time protection of personal and business data and implement security features to prevent cyberattacks on smart technologies and cases of data misuse, in compliance with the eu data protection law, namely the general data protection regulation (gdpr). this regulation shall apply from 25 may 2018, bringing the biggest revolution to date in the protection of personal data across the eu as well as astronomical fines for its violations. the management of public funds must follow the 3e principles, i.e. to ensure the attainment of the specific objectives set and the achievement of the intended results, to provide the best relationship between resources employed and results achieved, and to make resources available in due time, in appropriate quantity and quality and at the best price. [3] innovations innovations = innovative approaches and experimentation the openness of organizations and people to learn new things, learn from each other, experiment with new approaches, use new economic models, such as precommercial public procurement (pcp) to provide for the development of a new solution that meets the demands of the contracting public authorities (regions and cities) but is not available at the given time, or public procurement of innovation (ppi) to purchase innovative solutions that are not yet in the market or its availability is very limited (such solutions may be the results of the pcp model). opennes opennes = transparency of outputs and results transparency in results and performance reporting, such as “city dashboards” (online web applications with real-time information and data on the regional / city events), enabling comparisons and motivating authorities, organizations, neighborhoods, or municipalities to achieve improvements in specific monitored areas (e.g. measuring the cycling rate). leadership leadership = consistent vision, strategic management, partnership transparent and consistent leadership and strategic management in the field of smart solutions to provide benefits for the inhabitants of the region and the commitment to work on delivering necessary changes on a daily basis. this vision must be communicated in a clear and trusted manner and consulted with the inhabitants. an attractive environment must be created to encourage the entrepreneurial spirit of individuals and businesses and to attract new inhabitants to the region offering them as favorable living conditions as possible. it is necessary to initiate and support partnerships through networking of stakeholders which is a proven and effective way for the smarter region concept to mobilize them to carry out specific activities. 3. long-term objectives of the smarter region strategy the main objectives of the smarter region strategy are to save time and money, and to reduce negative environmental impacts through the use of ict technologies, innovative processes, and the support of a long-term systematic search for optimal solutions in partnership with relevant stakeholders in the moravian-silesian region. list of main topics is in table 1. table 1. main long-term topics objectives solutions t im e sa v in g s when commuting to work, schools, etc. when communicating and arranging issues with the authorities when searching for and using necessary information when managing and organizing public administration when marketing products and services to the end customers when visiting a doctor or a hospital m o n ey s av in g s when paying for energy and fuel consumption, heating and cooling when communicating and arranging issues with the authorities when managing and organizing public administration when searching for and using necessary information eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e5 o. kodym, j. unucka, d. létavková 4 objectives solutions when running businesses and non-profit organizations when marketing products and services to the end customers when shopping h ea lt h y e n v ir o n m en t due to reduced harmful emissions in the air due to air purification in heat recovery units due to better resource utilization and a more efficient circular economy due to a higher share of renewable energy use due to lower temperatures in the cities due to a more considerate and healthier lifestyle 4. strategic priorities for the smarter region for 2017–2023 there are total of 5 priorities in smarter region activities (see fig.3). each covers several sub priorities, as there should be at least basic overview or detailed specification. expected long-term benefits and measures for evaluation of achievements are mentioned in following chapters. transport (i) to build an infrastructure and smart systems to support smart mobility. (ii) to increase the use of mass transport and sustainable forms of transport (walking, cycling). (iii) to increase the share of electro mobility and hydrogen vehicles in transport. figure 3. strategic priorities and flagship projects for the smarter region for 2017–2023 [5] ict infrastructure (i) to build a backbone data infrastructure and a technology center capable of handling high capacity future demands for data, audio, graphics, and video. (ii) to cover public buildings and mass transport vehicles with wi-fi. (iii) to cover the region with networks for the internet of things (iot networks). savings (i) to reduce the costs for the supply of energy and maintenance of buildings and infrastructure in the region. eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e5 5 (ii) to increase the share of renewable energy sources in the energy mix. (iii) to increase the efficiency of waste management and reduce energy consumption. healthcare (i) to improve the quality and availability of healthcare services. (ii) to foster responsible attitudes of the inhabitants towards health and improve the quality of social care. reducing bureaucracy (i) to remove bureaucratic obstacles while maintaining high quality of services provided by the regional authority and its associated organizations by means of electronic solutions. (ii) to maintain high quality and level of corporate governance and services of the moravian-silesian region. (iii) to provide information and open data to the region's inhabitants. 5. priority 1 – transport long-term benefits are expected as follows: • faster and more convenient public transport. • limiting the negative impact of individual car as well as public transport on the quality of the environment in cities and villages (especially with the aim of reducing air pollution caused by airborne dust and carbon dioxide, reducing noise caused by transport, and improving parking systems in cities and villages). • streamlining the coordination of regional transport and reducing infrastructure maintenance costs in the region. • flagship projects • smart parking – pilot projects of smart parking facilities and navigation systems for managing and organizing parking in selected cities. • support for building an infrastructure of charging stations for electric cars and electric bicycles – support for projects to extend the network of charging stations for electro mobility (cars, bicycles, urban maintenance vehicles) and stations for hydrogenpowered vehicles. provision of corporate organizations of the moravian-silesian region with electric buses, electric cars, electric bicycles, and hydrogen-powered vehicles. • intelligent traffic management systems – smart navigation and information systems, support for open data and traffic information, introduction of information boards and applications for faster and more convenient regional transport. • monitoring and evaluation of traffic flows (traffic research) – efficient collection and evaluation of data and information on transport demand and mass and individual transport volumes. • wi-fi in public transport – introduction of wi-fi on regional buses and trains to make public transport and sustainable mobility more attractive. 5.1. strategic objective 1.1 – free flow of traffic to build an infrastructure and smart systems to support smart mobility. examples of measures to meet so 1.1: • intelligent traffic management – managing traffic and providing passengers with information on the traffic situation to increase the free flow and safety of the road traffic without the need to build complex infrastructure. adaptive traffic management, providing real-time traffic information, developing parking information and navigation systems, customizing traffic light signalling. support for cooperation and exchange of experience among the cities of the region with implementing intelligent traffic management systems. • mobile traffic applications – developing and offering products and services for mobile devices that show the real-time traffic situation based on location and preferences, allow communication with the internet of things and car applications, and allow entering notes, traffic alerts, or detours to the car on-board management systems. • autonomous and cooperative transport systems – development and preparation for the transition to autonomous forms of individual, freight, mass, and air transport, and for the application of cooperative systems (vehicles communicating with each other and with the infrastructure) with the aim of better traffic management and the elimination of traffic collapses. 5.2. strategic objective 1.2 – sustainable transport to increase the use of mass transport and sustainable forms of transport (walking, cycling). examples of measures to meet so 1.2: • improving the attractiveness of public transport – promoting the use of public transport, improving its image. improving the convenience of travelling by the means of public transport – access for disabled passengers, faster services, safer boarding platforms, wi-fi on buses, vouchers, discounts, competitions, better and easier orientation in public transport options (unified fares, contactless payment), x+1 systems (one passenger pays, the other travels for free), public transport cultural programs, better vehicle design, etc. eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e5 open data in smart region 6 • integrated travel planning systems – travel planning comparing time, costs, and emissions produced for each mode of transport for a given time of travel and route to encourage using modes of transport which are more environmentally friendly than individual car transport. limiting the negative impact of individual car as well as public transport on the quality of the environment in cities and villages (especially with the aim of reducing air pollution caused by airborne dust and carbon dioxide, reducing noise caused by transport, and improving parking systems in cities and villages including shared parking lots). • integrated transport systems – transport services for a particular area that accommodate multiple types of public transport (urban, regional, rail) and multiple carrier lines with unified schedules and ticket cards. these systems integrate various modes of transport and connect them with cycling, walking, and car transport. smart cards are used carrying various types of information, enabling contactless online payments, etc. see fig.4 for implementation of contactless payment bank cards in public transport. figure 4. terminal for contactless payment in public transport [https://www.dpo.cz/soubory/ aktuality/prirucky/platebni-karty-1.pdf] • smart stops – linking the functions of transport to social use, including environmental friendliness and enjoyable waiting at stops. examples of smart stop functions – charging mobile devices, wi-fi connection, generating power from alternative sources and physical exercise equipment, warming in winter, air purification, more comfortable (enjoyable) seats, attractive design and aesthetic appeal for the public space, information for both city inhabitants and visitors, emergency service calling 112. the role of the region can be primarily motivational, for example in the form of grants for municipal projects. • car sharing, ride sharing, bike sharing – creating conditions for sharing services that reduce the amount and use of individual car transport through shared cars or bicycles. an example of such service can be the provision of a fleet of electric cars and bicycles that will be available at a particular location, with the option of online reservation at flat rates or special tariffs. 5.3. strategic objective 1.3 – electro mobility and hydrogen vehicles to increase the share of electro mobility and hydrogen vehicles in transport. examples of measures to meet so 1.3: • support for building an infrastructure of charging stations for electro mobility – support for projects to extend the network of charging stations for electric cars and electric bicycles. connecting the network of charging stations with the internet of things, sharing information on occupancy and additional services with users. extending the network of charging stations for electro mobility (cars, bicycles, and urban maintenance vehicles) and stations for hydrogenpowered vehicles. provision of corporate organizations of the moravian-silesian region with electric cars. promoting the use of electric bicycles as an alternative option to individual car transport. 6. three basic smart criteria for smart projects the following three basic smart criteria will be the simplest fundamental measure of whether the proposed or implemented projects fit into the smarter region strategy and can be therefore considered smart. this assessment is purely indicative and is not intended to replace any complex standardization system developed at the national level of the czech republic. the condition for including a project in the strategy is meeting the smart 1 criterion, taking into account the 3e principles – economy, efficiency, and effectiveness of public investment. involvement of broader partnerships or innovative and experimental elements in the project will be considered as a higher added value, i.e. promoting the search for and implementation of solutions that go beyond standard procurement processes and rigid systems that do not reflect the specific conditions of the region and the needs of end users in the long term. eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e5 o. kodym, j. unucka, d. létavková 7 smart 1 – application of ict and other technologies the project involves a development or application of technology which, in addition to a financial benefit, brings also a socio-economic benefit, such as a positive impact on the quality of the environment while respecting the principles of safety and 3e. smart 2 – partnership principles the project is managed and implemented in a partnership, not by a single organization only, in an open environment of information sharing and access to expertise, without the risk that the applied solution will be unavailable for further use. smart 3 – innovative and experimental elements the project includes innovative or experimental elements testing the application of new technologies or solutions in the market. 7. open data for analysis of transportation nowadays ict enable gaining a variety of types of information. for projects supported and often co-financed from public sources, it is often agreed that the outputs and the related data sources will be open for general usage. in order for the open data to be effectively used for subsequent analyzes, the data sources must meet several basic requirements. metadata each attribute must necessarily have a description assigned. this description differs slightly from the commonly used "metadata" concept in transactional databases. the content of such description resembles the simplified form of analytical part of metadata in data warehouses. in particular, it is the information on how the data originated, what is the sampling period, what are the measuring units, the position of the sensor with sensor data (gps coordinates). the most important part is a description of the exact meaning of the published data. lookup lists if the individual records refer to the lookup lists, the relevant lookup lists must be completely available. unless the meaning of the individual lookups is completely clear from the context, it must also be accompanied by a description. time stamps each record must contain a time stamp, because it allows the users to interconnect the individual datasets and also to create time series. we must take into consideration that the forecasting analytical procedures assume the time series to be complete, and that the sampling period is constant. for example, if we have daily records, we must adhere to the daily intervals and no single day should be missing. integrability of tables for open data, large amounts of data are expected from different areas (public and passenger transport, environment, tourism, waste management, medical care, hydro-meteorological data). analytical processing often utilizes combined data sets, such as combination of environmental and transport values, or tourism combined with the data on weather. it should be taken into account when loading data into the data platform. for example, if the data contents are related to different territorial units which are mutually incompatible, their subsequent integration for analytical purposes is impossible. as an example we may note the eurostat data and the data from the czech statistical office, which have a completely different territorial classification and therefore cannot be combined. unchanging collection methodology historical data must be available for forecasting purposes. if there is a change in the methodology of data collection, it often makes it impossible to analyze the time series as a single unit. we thus lose the possibility to observe changes in trends or irregularities, which may be very significant in content. data granularity deciding on the appropriate data granularity is absolutely crucial. from the basic granularity, a range of applicable analytical techniques is developed. on the one hand, there is a demand for most detailed values with the shortest sampling period, i.e. transaction data. one transaction is understood as a sequence of operations that are no longer divisible from the point of view of content. e.g. one ride of one passenger, cash withdrawal from an atm, one order of a plane ticket. on the other hand, we are limited by the technical and economic resources needed to manage such a large data volume. attention is also drawn to the risks of misuse of transactional data in connection with the public security. sensory data in tunnels, subways, etc. are particularly sensitive in this respect. intuitive, fast and easy to navigate a user-friendly environment will have a direct impact on the utilization of open data. selecting a suitable navigation system will not be easy, as data from different areas, with different granularity, related to different objects or territories, will be counted in the future. in some cases, it is possible to increase the clarity by mapping. predefined outputs and analyzes should the public data really serve the general public, it should contain a set of the most frequently used queries and outputs. it should be reflected that an ordinary citizen will not waste time searching for data, combining them and processing them. these can be simple questions like: find the nearest open emergency, show the trend of air pollution for the next day, find the optimal method of transport between the given points, and find the date of the next large-scale waste collection in the village. nonetheless, eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e5 open data in smart region 8 more sophisticated outputs or the possibility to use integrated analytical tools directly in the open data environment can be available. for example, eea european environment agency manages the european publicly available database on the environment and health of the population. clear navigation in the data sources, including metadata, is only one of the functionalities. in addition, users are provided with integrated data tools from olap analytics (figure 5) to interactive charts. therefore everyone can view data cubes, set up filters, change views, visualize and combine data quickly, comfortably and without any previous skills. simple work instructions are also integrated. there are sets of pre-prepared interactive graphs (figure 7), more complex analytical outputs (figure 6), professional literature, and a description of the indicators used. figure 5. olap gui – total emissions in the eu [8] open data in the smart city context should: • increase citizens' awareness and assist them in their both daily and occasional activities; • provide data base for analytical activities. as far as services for the general public are concerned, passenger transport appears to be a suitable initial application. at present, it is a burning problem for most large cities. participating organizations strive to publish up-to-date information on traffic intensity on critical roads, inform about planned and acute road repairs, congestions and traffic accidents, suggest preferable highway exits and detours, help plan routes, inform about paid parking areas, parking slots and free capacities of car parks, enable citizens to book and pay a parking space online. most applications offer the closest object search according to the current gps position of the user, or by selecting the area of interest in the map. examples of successful portal in the czech republic: • the road and motorways directorate of the czech republic publishes (at http://scitani2016.rsd.cz) interactive maps with focus up to the composition of the traffic flow, the amount of pollutants emitted, the intensity of traffic, etc. (in an annual aggregation). • the rodos project (rozvoj dopravních systémů – development of transport systems) publishes (at https://rodos.vsb.cz) current traffic situation on motorways and expressways in the form of simple graphics. the information is updated every halfminute, supplemented by meteorological data, bypass suggestions, statistical indicators, etc. • tsk prague operates a prague parking portal (at http://www.parkujvklidu.cz) where citizens can find not only interactive maps with parking zones, vending machines and parking, but also virtual parking. figure 6. exposure-response associations between temperature and mortality in two european cities, together with related temperatures distributions. the shaded grey area delineates the 95 % empirical confidence interval. solid grey vertical lines are minimum mortality temperatures and dashed grey vertical lines delineate the 2.5th and 97.5th percentile temperatures. [https://www.eea.europa.eu/data-and-maps/figures/ associations-between-temperature-and-mortality] eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e5 o. kodym, j. unucka, d. létavková 9 individual portals and applications are user-friendly, intuitive, functional and up-to-date. unfortunately, they always focus only on a selected section of the whole issue of public / passenger transport, and wider public often lacks awareness of their existence. a data platform that will have access to the relevant data sources will have a unique opportunity to integrate the individual sections into a common unit. an appropriate addition seems to be increased effort to motivate population for wider use of public transport and alternative modes of transport. a good start is creating an introductory interactive map comprised of several layers – passenger transport and parking, public transport, cycling and pedestrian traffic. figure 7. primary energy consumption and linear trajectories to 2020 targets, 2015 and 2016 [https://www.eea.europa.eu/data-and-maps/daviz/ primary-energy-consumption-and-linear#tab-basedon-data] the cycling+pedestrian layer may provide information on pedestrian and cycling zones, bicycle stands and rentals, on-line booking of bicycles, location of parks and green areas, outputs from online cameras as well as meteorological outputs with forecasts for an upcoming time period. park+ride parking should obviously be included too. the p+r parking should encourage drivers for frequent usage not only with easy navigation and virtual parking slots. the offer should include real time departures of the nearest public transport links, including information on the impact of car traffic on the environment and possibly health.the following figure (figure 8) shows a proposal for information on a selected parking lot. the bar graph is based on the historical occupancy values of the car park, varying depending on the day of the week or possibly taking into account the difference between working day/weekend. drivers can easily recognize that from 1417 o’clock the parking lot is fully occupied, how many parking spaces are available (123 of 450), and how many tons of pollutants the car park has already saved over the week thanks to the people going by tram or walking instead of going by car. values are calculated based on the entrance barriers readers. the calculation formula was proposed by the european environment agency according to term 027 indicator and traccs 2013 database [9]. the formula is based on the average occupancy of 1.2 passengers per car, which may slightly differ; the data can be found for individual sections at (http://scitani2016.rsd.cz). the amounts of pollutants saved are really impressive, as in a single week it can be even several tons of greenhouse gas, if we count with the average saved driving distance of 5 km. figure 8. parking popularity on monday with additional informaton as far as the utilization of the data platform for analytical purposes is concerned, optimizing public transport is a suitable area of expertise. in order to modify the structure of the network of individual public transport lines and the frequency of connections, we need to trace the transport habits of the population. one of the possible methods is to analyse transaction data of public transport. the entry condition is, naturally, the technical capability to record boarding / exit stops of the passengers in vehicles. using analytical procedures, we can identify the utilization rates of individual lines and links, as well as the stops where passengers most often board and disembark the vehicles. with certain reservations we thus gain an overview of where to and from the inhabitants are transported by public transport. it is desirable to motivate passengers to use the contactless chip cards as much as possible. data usability will be multiplied. this will allow analysis of the passenger features (child, student, adult 15+, pensioner) (see fig. 5) and the fare type (type of long-term ticket, individual fare). we will get the background data for optimizing fare and fare rates, we can track how many times a week the individual groups use public transport, which payment method they prefer on which routes. another useful aspect of chip cards is the ability to identify the transfer eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e5 open data in smart region 10 passengers and to get a complete overview of where (from), when, how often, and on which lines they travel. detailed processing of transaction data enables the maximal utilization of the information contents of the data base. see example at figure 9. facts that have so far escaped our attention are often revealed. it is because in the aggregate data values of anomalies and small patterns of behaviour often simply disappear. looking at transaction or sensory data directly, even if there is a significant anomaly, we will probably not pay appropriate attention to it. only when we notice that the anomalies are periodically repeated or show some mutual relation, we try to find out their cause. transaction data have to be processed with all the details available, in different relations and variants. otherwise, the discovery of hidden information is more a matter of coincidence than the analytical activity. we cannot do without powerful technology, high-quality software and relevant analytical knowledge. figure 9. customer profile of public transport provider number of transactions in one week 8. compliance with major policies and strategies the smarter region strategy differs from other development and sectoral policies and strategies with an impact on the moravian-silesian region by the use of ict technologies and innovations along the lines of other smart policies and strategies. compliance with the objectives and general aims of these policies has been ensured during the drafting of this strategy and will be followed in the future as well. the smarter region strategy will not develop its own complex metrics and set of indicators. the strategy will be implemented by means of projects that meet the smart criteria in constant interaction with existing development, sectoral, and thematic strategies and sub-strategies, plans and action plans. the strategic framework of the smarter region strategy is primarily based on the following strategic policies and documents: europe 2020 strategy, partnership agreement for the 2014–2020 programming period digital agenda for europe: the goal of the europe 2020 strategy is to create a digital single market based on fast and ultra-fast internet and interoperability of applications: • by 2013: basic broadband coverage for all; • by 2020: next generation networks (ngn), 30 mbps or more for all; • by 2020: 50 % of households having 100 mbps subscriptions or higher. innovation union • focusing research, development, and innovation policy on the major challenges of the world today, i.e. climate change, energy industry, resource efficiency, healthcare, and demographic changes. • supporting each element of the innovation process, from basic research to product marketing. strategic framework czech republic 2030 (government of the czech republic, 2016) section 412 – (sub)urbanization and spatial mobility: "in their urban development, cities must seek the ways in which technological innovations can be combined, in particular finding the so-called integrated solutions (combining transport, energy, architecture, communication, or green technologies). however, the overall streamlining of urban systems, sought for example by the smart cities concept, must not be at the expense of preserving the identity of the city, created by monuments as well as other buildings, the public space, culture, and everyday life. planning at the local level must therefore also promote social cohesion and create living communities and viable cities. this goal should be aimed at with the smart cities concept prioritizing not only technological changes, but social and organizational innovations which are often of higher importance." smart city concept methodology (the ministry of regional development of the czech republic) the methodology includes, for example, the following definition of smart cities: "a city that holistically manages and follows its longterm development strategy which is based on qualitative and numerical indicators and serves to cultivate the political, social, and spatial environment of the city to enhance the quality of life and its attractiveness, and to reduce negative environmental impacts. by deploying appropriate ict technologies, it enables its citizens to engage in the city development and to materialize their ideas and suggestions through community programs or sharing economy in order to improve their communication with the city and revitalize the public space. the city encourages this process of transition to the culture of conscious behaviour by deploying suitable organizational and technological tools of the 21st century in a wide-spread, eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e5 o. kodym, j. unucka, d. létavková 11 integrated, and open way to ensure the interoperability of different systems and technologies and their synergies. the quality of life in the smart cities concept means the digital, open, and cooperative environment of the city that is healthy, clean, safe, and economically interesting for the citizens." strategic framework of the economic restructuring of the ústí, moravian-silesian, and karlovy vary regions in strategic objective g.2, this strategy sets the goal of "streamlining the management and performance of public administration for businesses and inhabitants, building the necessary ict infrastructure for this purpose and implementing additional investment projects using modern technologies for applications and services.” the required changes focus on the applications of the smart cities concept both in software and hardware. one of the changes should be the introduction of ict services and applications which address the most pressing needs of people and businesses in communicating and arranging issues with public administration authorities and implementing electronic solutions for the city agenda. these include, for example, open data and database sharing, faster communication with people and businesses by electronic tools, using electronic forms, empowering participatory management, and strengthening hardware capabilities for software solutions. development strategy of the moravian-silesian region for 2009–2020 (updated in 2012) the strategy states its mission: "we create our future in our heads and hearts!" "we perceive our region as a living organism, of which we all are active parts. our personal qualities rest in flexible minds and muscles trained by years of work on the transformation of the backbone economic, transport, and technical infrastructure. we search for smart solutions for the future and we will use our inner strength and motivation to implement them." other documents: • regional action plan for the esif 2014–2020 programming period • regional innovation strategy of the moraviansilesian region 2014–2020 (ris3 update to follow the smart specialization strategy – regional annex, may 2016) • joint declaration on the collaboration in drafting the smart city and smart region policies with the priority to improve the overall quality of life and the environment in ostrava and the moravian-silesian region • strategic development plan of the statutory city of ostrava 2017–2023 • the smart city concept "třinec i ty" of the city of třinec 9. conclusion the industrial heritage is an opportunity and a test for the future development of the region. achievements in traditional industries in the past do not automatically mean success in the present or future. rather, it seems that the future prosperity of the region will have to be built on new sectors, which are based on the traditional industries of the region. the automotive industry is to be complemented by new, dynamically developing sectors such as information and communication technologies, renewable energy sources, robotics and others that will provide job opportunities for the next generation as well as the competitiveness of existing businesses and sectors. reducing the product lifecycle, constant pressure on price and innovation are forcing companies to join the industry 4.0 initiative, which is one of the answers to the question of today's business going tomorrow. a similar challenge as businesses is also facing regions. they engage each other in attracting people and maintaining the optimal structure of the population. lack of workers in the industry can partially address companies by introducing digital technologies and robotics. however, the outflow of the region's inhabitants cannot be solved as easily. however, even in this case, the deployment of modern technologies can help. the moravian-silesian region has long been facing the population outflow. young, economically active people stay in college towns and cities after school. at best, in prague or brno, the worse they scatter around the world. the concept of a smart city and region is one of the ways to slow this negative trend and make life more attractive in so-called smarter cities and regions. acknowledgements this is the acknowledgement text. this is the acknowledgement text. this is the acknowledgement text. this is the acknowledgement text. this is the acknowledgement text. this is the acknowledgement text. references [1] d. f. i. p. european parliament: mapping smart cities in eu, brussels: european union, 2014. [2] transport research center, ministry of transport of the czech republic: methodology of the concept of smart cities (metodika konceptu inteligentních měst), ministry of regional development of the czech republic, brno, czech republic: 2015. [3] ministry of finance of the czech republic: public procurement methodology fulfilling 3e principles in public procurement practice (metodika veřejného nakupování – naplňování principů 3e v praxi veřejného zadávání), ministry of finance of the czech republic, prague, czech republic: 2016. [4] ministry of industry and trade of the czech republic: initiative industry 4.0 (iniciativa průmysl 4.0). ministry of industry and trade of the czech republic, prague, czech republic 2016. [on-line] https://www.mpo.cz/assets/ dokumenty/53723/64494/659339/priloha001.pdf eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e5 open data in smart region 12 [5] beepartners: smarter region – strategy of development of smart region 2017–2023 (chytřejší kraj – strategie rozvoje chytrého regionu 2017–2023). moravian–silesian region regional authority, ostrava, czech republic: 2017. [6] germany trade and invest: industrie 4.0 – smart manufacturing for the future. germany trade and invest gesellschaft für aussenwirtscaft und standortmarketing, berlin, germany 2016. [on-line] http://www.gtai.de/gtai/ content/en/invest/_shareddocs/downloads/gtai/broch ures/industries/industrie4.0-smart-manufacturing-for-thefuture-en.pdf [7] directorate-general for internal policies: mapping smart cities in the eu. 2014. isbn 978-92-823-4761-4. [8] the european environment agency: data and maps. denmark [on-line] https://www.eea.europa.eu/data-andmaps [9] european environment agency: carbon dioxide emissions from passenger transport (emise oxidu uhličitého z osobní dopravy). [on-line] https://www.eea.europa.eu/cs/pressr oom/infografika/emise-oxidu-uhliciteho-z-osobni-dopravy/ image/image_view_fullscreen eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e5 o. kodym, j. unucka, d. létavková consociate healthcare system through biometric based internet of medical things (bbiomt) approach 1 consociate healthcare system through biometric based internet of medical things (bbiomt) approach sherin zafar1,*, samia khan1, nida iftekhar1 and siddharta sankar biswas1 1department of cse, sest, jamia hamdard, india abstract internet of medical things (iomt) or healthcare internet of thing (iot) is a collection of medical devices and applications that connect the various healthcare systems based on it through online computer networks. the devices are connected the output wi-fi allowing the m-m (machine to machine) communication through iomt. iomt provides various applications including remote patient monitoring (rpm), wearable fitness bands (wfb), hospital beds that are sensor equipped and many-more. iomt allows communication of medical devices without the intervention of human. the widespread deployment of iomt faces challenges of security, privacy, connectivity as well as compatibility. iomt based systems suffer from various security breaches and hacking attacks. traditional security measures of login/password do not compliment iot based systems. so this research chapter proposes a novel biometric based internet of medical things (bbiomt) technology that is unique and spoof free. the bbiomt approach eliminates shortcomings of traditional password schemes and offer a much superior authentication solution. keywords: iomt, iot, bbiomt received on 30 january 2020, accepted on 21 may 2020, published on 23 june 2020 copyright © 2020 sherin zafar et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.23-6-2020.165499 1. introduction enabling interaction of machine to machine and intervention of real time solutions to radically transform the delivery, affordability and reliability of healthcare in near future is the basic task of internet of medical things (iomt). due to increased engagement of patients in decision making or boosting compliance of healthcare service, leads to increase in technology adoption rate that will reach to about $156 billion by year 2020. figure.1 depicts utilization of iomt devices and services currently and in near future (anya, o., & tawfik, h, 2016) eai endorsed transactions on smart cities research article *corresponding author. email: zafarsherin@gmail.com eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ 2 figure 1. iomt devices and services iomt evolved from internet of things (iot) having a complex architecture where multiple components keep on interacting, enabling in providing solutions for the end user. iot is an interdependent system enabling real time data acquisition connectivity of devices, transfer of data and different analytics for controlling applications of end-user. a connected environment of cyber physical systems integrating data driven human and computer intervention that facilitates decision process is the basic workflow of iot. various technologies encompassed by iot are: • smart grids • intelligent logistics • smart towns • integration of data analytics and sensors all the above technologies are augmented by: • actuators • communication protocol networks the various industry segments where iot is being utilized and will cause transformation in near future are: • manufacturing industry • construction industry • power distribution • healthcare iomt is the healthcare application provided by iot that develops a network comprising of real time sensing of vital data by connected devices. iomt lead to personalized care for patients, hence providing a high standard of living, promoting individual patients regiment treatment that is data driven and also according to the physiological conditions optimizing the healthcare devices (ashton, k., 2009). figure.2 specifies importance of iomt in medial industry. sherin zafar et al. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 consociate healthcare system through biometric based internet of medical things (bbiomt) approach 3 figure 2. iomt the need of hour in medical industry iomt provides an ecosystem of connected health through affordable sensors, cloud networks and mobile big data domains. with increase in utilization of iomt devices and services, leads to increased healthcare frauds which are treated as a white collar crime in present day world. it involves various filings of dishonest claims of healthcare, dos and malware attacks on user sensitive data stored in healthcare database for profit turning or illegitimately accessing healthcare services. the healthcare frauds and attacks lead to intentional deception or misrepresentation of an individual’s entity causing unauthorized benefits to an individual or an organization (baker, l. a., 2014). figure.3 depicts various parameters of attacks and frauds on iomt devices and data. iomt: internet of medical things, whats else? iot cloud software digitized patient information hospitals electronic health records identity theft physician patient letters compromised notification intruder database third party medical data breach cellphone health server unencrypted inappropriate stolen laptop identity eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=2ahukewj8ryusjkheahuvxcskhfrycisqjrx6bagbeau&url=https://www.slideshare.net/softimize/iomt-is-coming&psig=aovvaw2_3o7whq4cnc7njslqog_d&ust=1540539848517019 https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=2ahukewj8ryusjkheahuvxcskhfrycisqjrx6bagbeau&url=https://www.slideshare.net/softimize/iomt-is-coming&psig=aovvaw2_3o7whq4cnc7njslqog_d&ust=1540539848517019 sherin zafar et al. 4 figure 3. parameters of medical breaches http://www.iritech.com/blog/biometric-healthcare/ there are various forms of fraudulent health care schemes that include false statement, deliberate omission or misrepresentation by a healthcare recipient for gaining payable benefits. the attacks and frauds of iomt are criminal in nature varying from state to state and country to country leading to deployment of “biometrics” as a security solution for this sector. biometrics is defined as the measurable physical and behavioural characteristics of an individual for establishment and verification of its identity (j.daugman 2004; blair, l. m., 2016).the biometrics pattern includes: • fingerprint • iris scan • palm prints • gait • facial recognition • voice recognition figure.4 represents various biometric traits that are utilized for verification and authentication. figure 4. biometrics traits utilized for verification and assessment biometrics physiological behavioral face fingerprint hand iris dna keystroke signature voice eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 http://www.iritech.com/blog/biometric-healthcare/ 5 biometrics science recognizes an individual based on his/her physical as well as behavioural traits. the biometric based internet of medical things (bbiomt) authentication systems are much more reliable than the traditional password systems for individual verification and ensuring their identities. 2. internet of things (iot) today in the digital era, analysts evaluate that by year 2020 iot development of remote associated gadgets will surpass the value of forty billion. iot is an arrangement of computing integrated gadgets, mechanical and computerized machines and items, various creatures and individuals. various iot devices, gadgets, machines, individuals, creatures are all furnished with an identifier that exchanges information along the system with no pc (personal computer) and human intervention. figure.5 represents rise in internet usage from year 2012 onwards that leads to development of iot. iot is gaining attention both at workplace and outside for impacting life and work. use of iot leads to reduced loss, costs, wastes and repairs, reviews and supplants items having new or past expiry dates. a basic example of iot is a smart fridge causing alerts about no milk through the internal camera inside. this research study presents internet as an essential part of day-to-day life, future web-vision and security issues and other gigantic difficulties for iot world (brewka, g., 1996). figure 5. rise in internet usage from year 3. iomt relating iot to broad terms it’s a collection of various interconnected devices and applications that are interconnected devices and applications that are linked through online network of computers. its subdivision iomt (internet of medical things) deals with the interconnection of medical devices and equipment that are related to medicare-it and healthcare-it. iomt devices are equipped with a wi-fi or some near field communication (nfc) technology that allows machine-to-machine (m-m) communication. 30.3% of iot devices are utilized in healthcare. iot economic impact is expected to rise from $3 trillion-$6 trillion in 2025, connecting about 31 billion devices and 4 billion people together. iot in healthcare is predicted to raise around $2.5 trillion by year 2025. healthcare stands 3rd most utilized sector for iot where around 60% of healthcare organizations are utilizing the internet of things technology and around 87% organizations are planning to implement the services of iomt in their usage by 2019 making iomt the most utilized technology consociate healthcare system through biometric based internet of medical things (bbiomt) approach eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 sherin zafar et al. 6 in the upcoming years (cercone, f'ieee, n., chan, h. c. y., 2015). 3.1 iomt categories despite various issues exist, but iomt has increased the medical industries workforce productivity and reduced the costs of medicare to large levels. iomt solutions generally fall into the below mentioned categories: 1. clinical efficiency: delivery of medicare devices is improved by utilizing iomt by various hospitals and dedicated clinics. iomt devices are utilized for tracking visits of patients from even the most remote locations. patients and medical equipment location tracking is done by iot sensors. tracking of medical adherence is developed by iot utilized pill bottles. 2. consumer/home monitoring: self-monitoring for consumers and collection of biometric information is done by iot technology. for e.g. smart thermometer that reads the temperature utilizing temperature sensors present in smartphones and other devices, ecg (electrocardiogram) done at home are all applications of iot. iomt devices help in tracking and collection of patient information from home and also provide assistance in the services of telemedicine. 3. fitness wearable: iomt based biometric sensors are utilized in settings of clinics and hospitals. heart patches, armlets monitoring blood pressure are connected to the clinical monitoring devices (cmd) that are located at various distant places. “auto refractor” based smartphones applications utilizing iomt for vision testing are popularly utilized nowadays. 4. brain sensors/neuro-technology: cranial wearable are in progress developed by researchers targeting high-tech consumers. iomt devices are well capable for brainwaves reading, tracking and transmitting patient’s mental health. drug efficiency analysis is being performed through researches on non-evasive neuro-tech (brain wave reading/recording). 5. infant monitoring: iomt enabled wearables for monitoring and tracking infant moments, temperature and pattern of sleep to the parents is another application of iot. it provides assistance for parents as they are aware of their baby’s physical health condition and then respond accordingly. 6. sleep monitors: tracking and monitoring of sleep is utilized for treatment of various neuropsychological disorders; as another application of iomt. these iomt monitoring devices continuously send reports to various clinics at distant locations. iomt applications that are smart-phone enabled are connected to various sleep monitors for further regulating patterns of sleep without clinical intervention. figure.6 depicts various iomt categories and their utilization in modern day world figure 6. iomt utilization in modern world eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=2ahukewi8jzcu-6heahvkko8khvd9b7gqjrx6bagbeau&url=https://medium.com/@sahana_63956/why-the-internet-of-medical-things-iomt-will-start-to-transform-healthcare-in-2018-5fdce4e8335c&psig=aovvaw3mydj-aec1b4swrgbfkv2l&ust=1540569657160820 consociate healthcare system through biometric based internet of medical things (bbiomt) approach 7 3.2 advantages of iomt iomt in today’s world provides a large number of advantages related accompanied with various concerns and future requirements that are listed below: 1. improvement in the outcomes of treatment as patient care monitoring and deliverance is done round the clock. 2. costs of medicare facilities are decreased due to real time as well as remote monitoring of patients which leads to fewer clinical visits. 3. disease management has shown visible improvement as careful real time monitoring is being provided to patients. 4. patient experience is enhanced as they get complete as well as customized treatment and care. 5. drug management is also improved due to iot growth as the iomt devices and applications assist in research of drug, their deliverance as well as adherence (kranz, m., 2016). 3.3 concerns and future requirement of iomt the concerns and future requirements of iomt are briefly discussed below: 1. sensor technologies based innovations are driving iomt platform as these intelligent networks will be the major future of internet world. 2. iomt growth will be assisted by development of high speed cloud based computing platform. 3. large amount of big data is processed through advanced analytics performed through iomt devices. 4. round the clock iomt based patients data should be secured from various attacks. figure.7 shows the various levels through which iomt data travels. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 sherin zafar et al. 8 figure 7. levels of iomt data 3.4 real world applications of iomt traditional and existing medical devices are upgraded to modern iomt devices for real-time sensing of data for monitoring the patients by various enhancements of iomt devices like sensors, signal converters and communication based modems that can perform remote communication: • wearable devices • home-use medical devices • point-of care kits iomt devices are utilized in various situations of emergency like: • disease prevention • fitness promotion • remote intervention table.1 discusses the key applications and utilization of iomt. table 1. discusses the key applications and utilization of iomt. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 consociate healthcare system through biometric based internet of medical things (bbiomt) approach 9 s.no application iomt utilization 1. management of chronic disease devices that are iomt enabled are providing alternative for management of chronic diseases like: • hypertension • cardiac failure • diabetes the iomt enabled devices monitor body parameters like • random blood sugar levels • weight and electrolyte concentrations inside the body vital data that is real time is sourced by the iomt devices which are utilized for future treatment alterations, changes of dose and prediction of progress of diseases. the research studies on epidemiological trends of various diseases for a specific population is furthermore changed and enhanced through iomt enabled data collection (chesbrough, h.2010). 2 living assisted through remote monitoring (tele health) the physician office is utilized as a central registration location of data from various network devices. patient specific data is compiled, processed for healthcare automation and analysis of fresh data is performed against various past records which decide upon the management of patient against future courses. thus tasks of data routing, it’s monitoring and proper field administration is intelligently machine enabled through iomt machines saving costs of implementation of follow-ups and infrastructure utilization. remote monitoring has also led to decrease in the rate of member drop-outs and increase in productivity of healthcare resources. cardiac monitoring is performed through commercialized body guardian remote monitoring system (bgrms) that maintains data security as it separates identification information of patients from its observation (davenport, t. h., & lucker, j. 2015). 3 preventive care wellness and assessment of lifestyle health supervision through diet, various physical activities and life quality is digitized through iomt enabled innovative devices like: • wearable devices • implantable chips • embedded systems • advanced sensors the innovative devices keep track of patient’s vital data changes and events of various health conditions at local level and expert assistance during situations of emergency at various locations of remote access. 4 remote intervention during emergency real time data that is obtained through sensors helps the physicians for drug administration. the timely reports help in high-tech medical assistance which reduces hospitalization costs (dhar, v. 2014). 5 improvement in drug management radio frequency identification (rfid) tags that are iomt enabled help in the management of problems related to drug availability and their related costs of supply. iomt enabled medication solutions like wuxi pharmatech and trugtag have led to the development of iot enabled edible smart pills that monitor patient’s drug doses and pharmacodynamics. these solutions help the drug companies is mitigating risks as well as losses during the administration of supply chains (deloitte, 2017). 6 other applications • paramedical staffs training courses and coaching. • rehabilitation and hospitalization assistance. • health information access to health records without losing medical information. • online analysis of protein and composition accuracy. figure.8 represents the iomt applications utilized in modern world eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 10 figure 8. application of iomt 3.5 cyber attacks in iot 73% of organizations of medicare are utilizing iot for monitoring patients and other research studies hence posing lot of concerns of data security. recently around 89% of healthcare utilizing iot has suffered from various security breaches. iomt interconnection of various devices causes personal information as well as business data to be passed on to the cloud and forth along thousands of devices that leads to various exploitable vulnerabilities. one of the serious concerns is privacy in all the devices, applications and systems that share information. users take precautions to secure data but many-a-times conditions goes beyond their control (geng, h., 2017). attacks of unprecedented sophistication are crafted by hackers that not just only correlate information from various private sources like: • cars • smart phones • home • automation systems • refrigerator etc. following are the various attacks that commonly occur on various iomt devices: 1) denial of service (dos) dos attack lead to inaccessible services due to overburdening limits and other parameters. dos causes malicious attacks in distributed system by causing botnets. distributed denial of service (ddos) is a subversion of dos attack. botnets are the multiple connected services that are online which are involved during a ddos attack to overwhelm a targeting website by sending fake traffic. breaching of security parameter is not done during ddos assaults, rather than website and server services are made unavailable for legitimate sherin zafar et al. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 consociate healthcare system through biometric based internet of medical things (bbiomt) approach 11 users (ma, d. (2007). the main features of ddos attacks include: a) its highly noticeable event that impacts the entire base of user online. b) it’s a popular weapon for various; • hacktivists • cyber-vandals • extortionists • champions of web that want to prove their point to world. c) these attacks last for days, weeks, months and at various times are extremely destructive for various online organizations. d) they causes losses to revenue, erode the trust of customer, businesses are forced to spend fortunes for compensations and cause damage of reputation for long terms e) unlike regular attacks where perpetrator utilizes a single connection of internet for exploiting software vulnerability, flooding of fake requests for target is an attempt for exhausting the resources of server like cpu and ram; the ddos attacks are launched through various connected devices which are distributed all across the internet. f) the ddos are multi-person and device barrages that are quite harder to deflect due to enormous amounts of involved devices. g) ddos attacks are targeting towards networks infrastructure for saturating traffic volumes unlike the single source dos assaults counterparts. h) their execution is also different from normal attacks as dos are launched through homebrewed scripts or the dos tool like: loworbi ion canon; the ddos assaults are launched through botnets which are large clusters of various connected devices like: cellphones, router etc. which are infected and allow attackers remote access. categories of dos attacks include: • attacks at layer 7 i.e. application layer attacks: these are dos or ddos threats that overload a server by sending huge number of requests for processing and resource-intensive handling. the application layer attacks include: a) http floods b) slow attacks e.g., slowloris or rudy c) dns query d) flood assaults the application layer assault size is measured typically in request per second (rps). around 50100 rps is required for crippling most of the websites that are midsized. • attacks at layer 3 and 4 i.e. network layer attacks: the network layer assaults are ddos assaults that clog the “pipelines” which connect the network. the network layer attacks include: a) udp flood b) syn flood c) ntp amplifications d) dns amplifications they prevent the servers’ access, causes severe types of operational damages like: suspension of accounts and huge overage charges. these assaults are like high-traffic events measured in giga-bits /sec(gbps) or packets/sec(pps). the network layer assaults exceed to around 200gbps but 2040gbps tend to completely shut the network infrastructures down. motivations of attacker for ddos: the attacks are mostly launched by various individuals, businesses and nation–status motivations that include: a) hacktivists: the hacktivists dos assaults are utilised as means of achieving criticism for governments, politicians and and current business events. they follow the principle that “if we disagree, your site goes down” i.e. “tango down”. the hacktivists are lesser technically savvy and use premade tools for waging assaults on their targets. “anonymous” group is the popular most hacktivist group which in february 2015 cyber attacked isis in paris office and in june 2014 against the brazilian world cup sponsors (gong, a., 2013). b) cyber-vandalism: “script kiddies” is a referral name for cyber vandals as they rely on premade scripts and tools for causing grief on the fellow citizens of internet. they are bored teenagers that look for rush for adrenaline, or vent anger, frustration against a school or eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 sherin zafar et al. 12 institution or against a person that has wronged them. some cyber vandals are just teenagers seeking attention and respect of their peers. they use ddos for hiring services of booters and stress for little as $19 a pop (he, d., & zeadally, s 2015). c) extortion: they are the cyber-attacks criminal type activities that demand money in exchange for stopping i.e. not carrying out crippled type of ddos attack. the companies that are at the receiving end of the ddos notes that goes offline to succumb after refusing extortionist threats are: a) meetup b) bitly c) vimeo d) basecamp like their counterpart, cybervandalism is enabled by the stresser existence and booter services. • personal rivalry: these attacks are utilized for settling personal scores or disrupt their online competitions. they mostly occur as multiplayer online games, which are launched ddos barrages against each other, against gaming servers to edge gain or for avoiding imminent defeat by causing the “flipping the table” condition. the attacks on the players are dos attacks that are executed on the widely available malicious software attacks on servers that are launched from the booters and stressers (mahoney, b. 2012). • business competition (bc): the bcddos attacks are increasingly utilized as competitive tool of business, designed to drag away a competitor in participating for a significant event like “cyber-monday”. some bc assaults are launched to completely shut-down the online based business for months and years. they cause disruption that well-encourage financial damage of customers and affect business reputation. the business feud bc attacks are quite funded well and executed through professional “hired guns” that have conducted scary reconnaissance and utilize proprietary wots as well as resources for sustaining the heavily aggressive ddos assaults. • cyber-warfare: they are the state sponsored ddos assaults that have the aim to silence the global critics and internal opposition. they work as a means for disrupting critical services of finance, health and infrastructure of the enemy countries. the cyber-warfare attacks are backed by nation, states and are well funded. preventing ddos attacks: the ddos attacks are difficult to prevent as the cyber criminals attack their targets regardless of their defences. the brewing storm of ddos can be spotted by the following: i. monitoring traffic against abnormalities like: traffic spikes that are unexplained, suspected ip address visits and geolocations. they could be “dry-runs” from attackers for testing the defences before the full-fledged attack. recognition of the abnormalities can help preparing the onslaught. ii. keeping eye on social media like twitter, public waste-bin like: pastebin.com against threats, boats and the conversations that hit the incoming attack. iii. consideration of the third party ddos based pen-testing for simulating attack against it infrastructure to prepare against moment of truth. iv. creation of a response plan and a rapid response tea for minimizing the impact of assault. they include customer support based communication teams. v. it’s important to choose a correct mitigation strategy. as rightly said by richard clarke of national security council (nsc) “if you spend more on coffee than on it security you will be hacked. what’s more you deserve to be hacked”. for preparing against ddos incidents leads accessing the risk that includes answers to the following questions:  which level of assets of infrastructure requires protection?  what are the soft spots (ss) or the single failure points?  what’s required for their shut-down? eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 consociate healthcare system through biometric based internet of medical things (bbiomt) approach 13  how and when you are targeted and when it will be too late?  what are the financial impacts against an extended outage? vi. it’s important to prioritize concerns after examination of various ddos based mitigation options within the security budget framework. a commercial website or online saas banking e-commerce protection, a law firm wants protection of its email, ftp servers, back office platforms, business require “on-demand” solution. vii. it’s important to choose the deployment method. the border gateway routing protocol (bgp) is the most common and effective way for deployment of the core infrastructure services across the subnet. it works on-demand on manual activation of the security solution. viii. a dns redirection for re-routing all the http and https traffic is an always-on ddos protection for the web application. they absorb volumetric assaults, minimize latency and accelerate the content delivery. ix. network layer attacks require additional scalability through bgp announcement for ensuring routing the incoming traffic to a set of scrubbing centres. it has the capacity to process hundreds gbps of traffic. scrubbing centres have powerful servers that filter out the malicious packets forwarding only the clean traffic through the tunnel. it provides protection against the direct-to-ip attacks being compatible with all infrastructures and communication protocols like: udp, smtp, ftp, voip etc. figure.9 shows the amplification attack scenario. x. traffic profiling solutions are utilized for application layer attacks mitigation to distinguish between malicious bots and website visitors who are legitimate signature and behaviour based heuristics, ip reputation scoring, cookie challenges are best practices for traffic profiling. the filter out malicious traffic protect against application layer attacks without impacting legitimate visitors. figure.10 specifies the most affecting cyber-attacks on iomt devices and services. mugger stooge exposed resolver exposed resolver exposed resolver eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 sherin zafar et al. 14 figure 9. amplification attack scenario figure 10. latest cyber attacks in iot 3.6 ransomware cyber-attacks are rising at a great rate affecting critical services despite of the efforts by security professionals to prevent them. ransomware attacks are gaining attention as they capitalize on the victims fear factors. phising emails, direct downloads, scare tactics as utilized by attacker in ransomware attacks to prevent or restrict access of critical data files. a highly profitable business model is evolved through ransomware attacks by criminals as they utilize sophisticated encryption methods, advanced options of payment for extorting money and enticing users to realize its real potential. about 100 new ransomware families in year 2015 were identified as revealed by symantic a leading global cyber security organization. ransomware has led to losses of 100’s of millions of dollars as the attack is selfpropagating and has the potential and power for infecting the entire organization. they restrict the user access as they encrypt most sensitive data files and lock down system completely. they focus on direct generation of revenue as the perpetuators use the scare tactics for demanding a huge ransom for service restoration. bitcoins is the most preferred method of payment utilized by ransomware attackers. bitcoin is a digital currency that has non traceability during online transactions of money. crypto-ransomware is the most common type of ransomware attack that aims for encrypting sensitive data files of victim. locker ransomware locks the victim’s computer and devices access is the second most common type of ransomware attack (mell, p., & grance, t., 2011). figure.11 focuses on the percentage of ransomware attacks on different iot based services. according to recent survey ddos and ransomware attacks are becoming some of the most common and dangerous threats of modern day it world eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 https://www.incapsula.com/ddos/attack-glossary/ntp-amplification.html consociate healthcare system through biometric based internet of medical things (bbiomt) approach 15 figure 11. percentage of ransomware attacks on different iot based services target and ransomware attacks implications: the objective of ransomware assaults can be the customers and associations which incorporate home clients, little to huge organizations, open or government offices, and even legislators/famous people. the ransomware assaults target touchy data including business recommendations, individual data, bank points of interest, passwords, client data and so forth which can make disastrous impacts in business or in the life of people. the client won't have the capacity to get to a ransomware hit machine as the assailant takes control of the basic documents and encodes it. the results of ransomware assaults incorporate loss of delicate data either briefly or for all time, interference in the standard task or working of administrations, money related misfortunes and in addition reputational harm for the people in question. in a large portion of the occurrences, the recuperation of information will be to a great degree troublesome and may require the help of information recuperation authorities (raghupathi, w., 2010; ripberger, j. t. 2011). working of ransomware: there are different techniques in which a ransomware can hit a shopper or an association. one of the conspicuous techniques to spread ransomware is through malignant spam messages, which are generally disseminated utilizing botnets. this can occur through social designing strategies or direct download too. the email or the downloaded document contains a vindictive connection and once the injured individual access this, it can encode the information inside the framework or can bolt the framework dependent on the kind of the malware. the server at that point advises the injured individual requesting a ransomware to decode the records or open the framework. the assailants may initiate the dread strategies by acquainting a commencement clock the payoff, which for the most part says once the due date is crossed it will annihilate the encryption key or twofold the payment sum. clearly, paying the payoff isn't an assurance as the shopper or association may in any case free the records even after the installment of payment (ruths, d., & pfeffer, j., 2014; schatsky, d., & trigunait, a. 2011; schellevis, j. 2014). protection against ransomware attacks: 1. consumers, independent companies and undertakings must execute multilayered barrier systems while managing ransomware assaults. organizations must utilize standard information reinforcement and recuperation anticipates all the basic information they store. the reinforcements ought to be tried and the upheld up information must be put away in independent gadgets ideally dis-connected. 2. regular patching updates should be performed against the attacks. the application fixes and working framework patches must be cutting-edge and tried to maintain a strategic distance from any potential vulnerabilities. productive fix administration lessens the odds of assaults through exploitable frail connections. 3. the restricted model of privilege should be followed by the organizations for reducing the installation chances and running of unwanted software applications. 4. the antivirus must be updated and frameworks must be introduced with most recent antivirus series 1, business/profess ional services, 28, 36% series 1, government, 19, 25% series 1, healthcare, 15, 20% series 1, retail, 15, 19% series 1, other, 0, 0%heathcare hit by 77% of all attacks including ransomware business/professional services government healthcare retail other eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 sherin zafar et al. 16 programming and all the downloaded records must be looked over it. 5. application whitelisting must be implemented by the organizations. associations must pursue an application whitelisting process which forestalls the framework and system getting tainted with pernicious or unapproved applications. 6. user awareness will be created against ransomware attacks. clients are the weakest connection in digital security and instructing them through appropriate preparing is vital. security proficient must know about the most recent patterns in this space and need to instruct the clients in regards to spam messages and phishing assaults. 7. email should be protected against ransomware attacks. associations must watch out for their messages. they should square email messages with connections from suspicious sources. 8. endpoint should be protected against the ransomware attacks: associations must secure the endpoints by keeping malignant documents from running. 9. good security practices should be nurtured. associations must keep up great security propensities and safe practices when perusing the web and should defend the information with suitable controls. 10. an integrated approach against ransomware attack should be followed. by following an incorporated way to deal with digital security, associations can to a great extent address the difficulties with tending to the digital dangers including ransomware assaults. most joyful personalities digital hazard insurance stage is such an incorporated stage which enables associations to use on numerous security advances progressed and cutting edge organize, endpoint security, giving further examination and experiences to a coordinated way to deal with danger lifecycle. digital hazard insurance stage is a cloudfacilitated stage and can be utilized in a membership based model. digital hazard insurance stage is chance mindful, character mindful, information mindful and condition mindful stage giving complete perceivability of the security pose (schilling, m., 2012). 4. biostatical techniques for maintaining security goals as past sections examines, why it is essential to keep up security of iomt, utilizations of the iomt in this day and age and diverse kinds of digital assaults in iomt, this section will examine biostatical systems for keeping up security and protection of iomt. biometric is one of the components which can be utilized as biostatical strategies for keeping up security of iomt. biometric is a confirmation system which partners client character check process that includes natural sources of information or examination of some piece of body. it is fundamentally a security procedure that relies upon one kind of a natural person to confirm its character. biometric information is collected and gathered in the database. on the off chance that both the information coordinates then verification is affirmed. fundamentally these all instrument are done to give security and protection to the iomt administrations and gadgets (sherin zafar, m.k soni and m.m.s beg 2015). figure.12 speaks to the sorts of biometric groups as solid and feeble biometrics. biometrics universali ty uniquene ss permanen ce collectabili ty performan ce acceptabili ty circumventi on face h l m h l h l fingerprin t m h h m h m h hand geometry m m m h m m m keystroke dynamics l l l m l m m hand vein m m m m m m h iris h h h m h l h retina h h m l h l h signature l l l h l h l voice m l l m l h l facial thermogr am h h l h m h h dna h h h l h l l h=high , m=medium, l=low figure 12. various sorts of biometric groups as solid and feeble biometrics eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 consociate healthcare system through biometric based internet of medical things (bbiomt) approach 17 there are various sorts of biometric like unique finger impression, confront, dna, iris and so on. some solid biometric are iris, dna, confront, retina. iris is a robotized procedure of biometric distinguishing proof component which utilizes scientific acknowledgment methods on video pictures of either of the iris of people. the different reasons which made iris acknowledgment framework as one of the most grounded biometric instrument are listed below(steinbrook, r., 2008; sweeney, l. 2002): • stable – the interesting example in the human iris is shaped by 10 months of age, and stays unaltered all through one's lifetime • unique – the likelihood of two ascents delivering a similar code is about unimaginable • flexible – iris acknowledgment innovation effectively incorporates into existing security frameworks or works as an independent • reliable – an unmistakable iris design isn't powerless to burglary, misfortune or trade off • non-invasive – in contrast to retinal screening, iris acknowledgment is non-contact and snappy, offering unmatched exactness when contrasted with some other security elective, from separations to the extent 3″ to 10″. subsequent to performing writing overview, the different customary security systems that are use in iot and their assaults and disadvantages are recorded beneath in the table.2. table 2. different customary security systems that are used in iomt and their assaults and disadvantages s no. name of mechanism description of mechanism different attacks or drawbacks 1 advanced encryption standard (aes) aes is a symmetric square figure, which is favored by the us government to encode the delicate information around the world. it is anything but difficult to actualize on different equipment and programming and in addition in an exceptionally limited condition. different highlights of aes are secure, cost effective and it is outfitted for managing 128 pieces square while using key estimated at 128, 192 and 256 bits. it uses a substitution change framework and work on 4*4 systems. aes is powerless against man-inmiddle assaults. 2 high security and lightweight (high) high is used for basic operation like xor operation on fiestel network. key for high is generated while encryption and decryption phase. it has a block size of 64 bits with 128 bit key of 32 rounds. main features of high are it require less power, few lines of code and it improve the speed of rfid. high is vulnerable to saturation attacks. 3 bootstrap security security is the most imperative factor in the success of internet of medical thing. secure transmission of data will always be challenge for this growing area. today, generic bootstrap architecture, technology supports data integrity and authentication in iomt. to share the initial key with the smart phone or home gateway qr code are required. these qr code is packed in a package of thing and employee of company can easily see qr code and key. attacker can perform dictionary attack to get key and plain text. also long and random key can’t be stored in the device.[14] 4 elliptical curve cryptography (ecc) ecc is a kind of public key encryption strategy which depends on elliptic curve hypothesis and which is utilized for making quicker, smaller and effective cryptographic keys. it uses 164 bit keys to a hp researcher nigle smart discovered a flaw in which some curve are extremely vulnerable.[9] eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 sherin zafar et al. 18 provide levels of security rather than 1024bit keys used by other system to achieve it. they give comparable security bring down processing force and battery asset utilization. it is a looping line crossing two axes based on condition made by mathematical gathering. 6 present present is utilized as ultra-light weight algorithm for security. it requires 4 bit input and output s-boxes, works mainly on substitution layer. it works on 64 bit size block and key of 80 or 128 bit. present is vulnerable to. integral attacks. it is powerful technique to recover secret key. 7 rc5 rc5 is firstly proposed by rivest for the rotations that are data independent. it is used mainly in wireless scenario and work well as a light weight algorithm. it possesses fiestel structure and works on 32 bit size which can also vary to 16,32,64. rc5 is vulnerable to differential attacks. 8 rsa rsa was invented by ron rivest, adi shamir and leonard adleman in 1978. it works by selecting two large prime numbers and then generating public and private key pair of by them. in the wake of finding their modulus and picking encryption key aimlessly and after that figuring the decryption key. in general public key is distributed to everybody and private key is made secure. it is vulnerable to various attacks like cycle attacks, searching message space, guessing and and so on. the social insurance framework, during the time spent change to upgrade protected, quality and cost contained consideration, is confronting numerous difficulties. the most major issues that human services framework is encountering are medicinal wholesale fraud, different sorts of misrepresentation in social insurance administrations and social insurance protections. as indicated by financial cost of healthcare fraud report 2014, the current worldwide normal misfortune rate expanded from 5.99% in 2007 to 6.99% in 2011 equivalent to $487 billion. the ongoing report from fbi expressed that "medicinal services extortion costs the nation several billions of dollars a year. it's a rising danger, with national medicinal services uses assessed to surpass $3 trillion out of 2014 and spending proceeding to outpace swelling". (viju raghupathi, w. r., 2013; walker, r., 2015). the best answer for avoid misrepresentation and restorative data fraud in human services is to reinforce the confirmation and limit the dangers of security ruptures with the utilization of biometrics. biometrics has been turning into the best decision for the medicinal services supplier to fathom fake issues. as of late, biometrics has being embraced by different human services associations worldwide to secure wellbeing records, encourage simpler access to medicinal data, and guard social insurance shoppers against cheats. moreover, the ascent of interoperable wellbeing data databases utilizing biometrics can empower administrations to just and consistently administrate the entrance to medicinal personality by approving access to patient's records utilizing biometric character. by connecting such data, the patients can be effortlessly distinguished and associated with their own restorative records accommodating particular medicinal services administrations. consequently, the connecting among biometrics and electronic wellbeing records enables the wellbeing associations to give more precise and effective social insurance administrations. since april 2009, the us requires the doctors and human services experts who utilized electronic wellbeing record should check painstakingly the getting to the patient's record. biometrics enables the doctors to do this effectively. by making the records just open to somebody who is distinguished by unique mark, vein or iris, a record can be kept of personality and time getting to the document, and it very well may be guaranteed that the individual who got to the document is certainly the one has the privilege to see a patient's record. on the off chance that they jumble, the fitting specialists can be told that unapproved individual is endeavoring to get to anchor information (white, s., 2014). human services biometric advertise has imagined a gigantic development in the previous couple of years. as per “medicinal services biometrics advertise” report from eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 consociate healthcare system through biometric based internet of medical things (bbiomt) approach 19 transparent market research distributed on september 2013, the unique finger impression acknowledgment innovation is the most unmistakably utilized biometric innovation and will make up over half percent of biometrics request in human services industry through 2019. additionally, face and iris acknowledgment are likewise anticipated that would have quick development in term of the interest for consistent access control in social insurance administrations. as of now, north america alongside europe catches over 75% of the piece of the overall industry. the worldwide social insurance biometrics showcases cost of $1.2 billion out of 2012 is anticipated to ascend by 25.9% from 2013 to 2019 with the evaluated market estimation of $5.8 billion of every 2019. human services has turned out to be one the most alluring markets that numerous biometrics organizations plan to infiltrate in including 3m cogent, inc., bio-key international inc., digitalpersona inc., nec corporation, m2sys llc (wilkinson, z., 2013;yin, r. k., 2013). there is almost certainly that biometrics has huge potential in human services, in encouraging cost decreases, upgrading data security, expanding the administrations quality, enhancing availability, and much more noteworthy geographic value of conveyance. to push biometric innovation into the standard id advertise, it is essential to support its assessment in reasonable settings and encourage development of modest and easy to use executions. 5. consociate healthcare it system through biometric based internet of medical things (bbiomt) approach this research chapter takes note of that "human services biometrics" used for access control, distinguishing proof, workforce administration or patient record stockpiling. biometrics in medicinal services often takes two structures: giving access control to assets and patient recognizable proof arrangements. the developing interest for biometrics arrangements is essentially determined by the need to battle misrepresentation, alongside the basic to enhance tolerant protection alongside social insurance security. biometrics is additionally being utilized for medicinal observing and versatile social insurance. the biometric enlistment process starts with endorsers visiting a registration office and giving their biographic data and unique mark tests. before part information is for all time added to the part database, automated biometric identification system (abis) contrasts the unique biometric impression tests and all people as of now in the database. any copies identified by the abis are physically arbitrated by a mediation officer who, bolstered by a devoted programming application, examines every potential copy and chooses which of them to acknowledge as authentic. when this procedure is finished, the framework recovers the significant biometric and biographic data from the local database and in a split second customizes and prints a shrewd card for the par (yasseri, t., sumi, r., & kertész, j.,2012). the whole procedure of catching a part's information, de-duplication, card personalization and printing is commonly finished inside 7 minutes. to check the increasing expense of cases and therapeutic case extortion, biometric confirmation is performed at the social insurance supplier’s end. at the point when a card holding part visits a medicinal services supplier, their unique mark information is caught and coordinated against the finger impression format put away on their part card amid enrolment. on the off chance that confirmation is effective, an irreversible case check code (cvc) is produced and entered on the part's case frame. the cvc depends on biographic information, setting data, (for example, medicinal services supplier id, benefit date and enrolment id) and the consequence of the biometric confirmation. since the cvc must be created accurately if the part is available at the time the case is produced, it goes about as a biometric evidence of-nearness, in this way dispensing with phony and copy claims from human services suppliers. an across the country rollout of the biometric participation enlistment and moment issuance of the id card framework began in january 2014. up until this point, more than 4 million supporters have been effectively enlisted utilizing the new framework. the activity to receive biometric innovation in the medicinal services framework is relied upon to prompt a copy free part database, insurance of information uprightness and enhanced effectiveness in administration conveyance. moment issuance of part id cards at the purpose of enrolment has likewise dispensed with postponements in id card creation. these advantages, together with the radical decrease in deceitful cases through biometric validation at the purpose of administration conveyance offer long haul advantages to country’s social insurance. as far as appropriation, the interest of biometric human services for patient distinguishing proof arrangements clearly lies with its natural advantages. biometric id arrangements offer the choice to distinguish appropriate protection status, in this manner expanding extortion assurance. another key advantage is wellbeing. with the utilization biometrics, a confirmed patient acquires the right treatment. figure.13 depicts the biometric based internet of medical things (bbiomt) approach to make the iomt system more secure against various attacks. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 sherin zafar et al. 20 eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 consociate healthcare system through biometric based internet of medical things (bbiomt) approach 21 figure 13. biometric based internet of medical things (bbiomt) approach further, the utilization of biometrics is fast and proficient, disposing of the requirement for entering in information which can prompt temperamental information. these frameworks are likewise advantageous since they work for lethargic patients. the driving goal behind biometric medicinal services is in this way to join high security with accommodation. as associations receive innovative guides that grasp higher security through biometrics, the following obstacle will execute understanding distinguishing proof arrangements and making open systems for patients to get to their medicinal records over a large number of suppliers and stages. with the coming changes to the patients wellbeing framework and as therapeutic record administration capacities change with innovation, tolerant recognizable proof components will without a doubt stick to this same pattern. the abilities and adaptability of biometrics as to tolerant distinguishing proof evacuates numerous dangers of fabrication, misidentification and record security. 6. conclusions and future scope versatile wellbeing, otherwise called iomt, is a term utilized for the act of medication and general wellbeing upheld by cell phones. the term is most generally utilized in reference to utilizing versatile specialized gadgets, for example, cell-phone, tablet pcs and individual advanced partners (pdas), for wellbeing administrations and data. iomt is a subset of ehealth, which is the utilization of data and correspondence innovation. iomt applications incorporate the utilization of cell phones in gathering network and clinical wellbeing information; conveyance of social insurance data to experts, scientists, and patients; ongoing checking of patient imperative signs; and direct arrangement of consideration by means of versatile telemedicine. iomt is an undeniably famous thought in light of its ability to build access to human services and wellbeing related data, especially in difficult to-achieve populaces and in creating nations. iomt applications can enhance the capacity to analyse and track ailments and can give timelier, more significant general wellbeing data. further, iomt applications can give extended access to continuous medicinal instruction and preparing for wellbeing labourers. biometrics research group, inc. expects that biometric innovation will be exceedingly utilized to secure portable wellbeing gadgets, applications and assets. unique mark acknowledgment innovation will be used the most since it is the essential biometric innovation used in cell phones and various iomt devices. for sure, unique mark innovation is in the spotlight because of apple, samsung and other gadget producers, who have expelled the persona around biometrics by acquainting the innovation with the purchaser. unique mark acknowledgment is in this manner turning into a comprehensively acknowledged strategy for positive recognizable proof and anticipated that it will be progressively utilized in iomt applications. since wastefulness and extortion are abrogating authoritative worries for human services frameworks interest expansion in social insurance security conventions that include biometrics is being adopted. selection of "medicinal services biometrics" is done in healing centres, facilities and different offices. as far as work process, these apparatuses will secure medicinal services assets and therapeutic information. concerning patients, biometric frameworks will be utilized for patient distinguishing proof. while little eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 sherin zafar et al. 22 scale executions are utilized it’s expected that huge scale persistent distinguishing proof frameworks will be taken off in rising and creating nations. medicinal biometrics will keep on forming into a development showcase because of the expanding interest for "wearable" buyer gadgets. the expanding utilization of iomt applications will likewise drive the use of biometric validation for security purposes. while iomt-based restorative innovation applications are still in a beginning phase of advancement, the execution of associated gadgets could altogether enhance human services conveyance. maybe the best preferred standpoint would be an upgraded operational proficiency through a developing utilization of arranged gadgets. straightforward information spill out of lower-level physical gadgets to the cloud (and related information examination) could empower continuous reaction from remote areas, maybe sparing lives now like never before previously. information driven basic leadership is probably going to engage guardians to precisely screen a patient's complete wellbeing status, take pre-emptive preventive measures, and also momentarily react to crisis circumstances. the interconnected frameworks are estimate to decrease the weight of expense on patients, increment quiet consistence, and use the upsides of savvy gadgets that can give quick responsive human services. in spite of the fact that computerization in medicinal services checking would increment operational proficiency, it might present genuine dangers amid usage, for example, information robbery, uncertain information exchanges, and unpredictable system associations. these difficulties, joined with administrative obstacles, are anticipated to drive development in iomt-based systems administration and information arrangements. there is still extension to enhance gadget and worldwide information gauges over the business, which would empower information taking care of in a reliable manner. considering the advantages and related difficulties, iomt appears an encouraging answer for enhance medicinal services checking and treatment results. by giving individual information driven treatment regimens and streamlined gadgets according to physiological prerequisites, this innovation speaks to another 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[79] jorge granjal, edmundo monterio and jorge sa silva (2015). security for the internet of things: a survey of existing protocols and open research issues. ieee communications surveys & tutorials. volume: 17, issue: 3, third quarter. retrieved from http://ieeexplore.ieee.org/document/7005393/. eai endorsed transactions on smart cities 02 2020 06 2020 | volume 4 | issue 10 | e5 http://ieeexplore.ieee.org/document/7427903/ http://ieeexplore.ieee.org/document/6778504/ https://tweakers.net/nieuws/95410/belgische-rechter-verbiedt-taxi-app-uber-in-brussel.html https://tweakers.net/nieuws/95410/belgische-rechter-verbiedt-taxi-app-uber-in-brussel.html http://ieeexplore.ieee.org/document/7005393/ comprehensive survey on smart cities architectures and protocols 1 comprehensive survey on smart cities architectures and protocols syed waqar shah1,, tahira magsi1, and ahthasham sajid1,* 1department of computer science, faculty of ict, balochistan university of information technology engineering and management sciences, quetta, baluchistan, pakistan abstract the world has advanced more than two centuries in the last 20 years in every aspect of existence. every day, new inventions are made that improve our quality of life and make our lives easier. one aspect of contemporary innovation is the idea of the smart city. many businesses and governments are embracing the idea of the "smart city" to improve quality of life for citizens while cutting costs. this model is made up of a variety of different technologies. internet of things, cloud and fog computing, uav, and other technologies are among them. on the other hand, in order to achieve these important goals, it is necessary to provide the multiple system components with the necessary synchronisation and mechanism, which calls for well-organized interaction and communication protocols. in this study, we categorise the networking requirements and characteristics of smart. keywords: iot, cloud computing, uav. received on 19 june 2022, accepted on 05 september 2022, published on 07 september 2022 copyright © 2022 syed waqar shah et al., licensed to eai. this is an open access article distributed under the terms of the cc bync-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i18.2065 *corresponding author. email: ahthasham.sajid@buitms.edu.pk 1. introduction the smart cities concept brings revolution to urban planning. in 1994 amsterdam formed a virtual digital city to endorse internet procedures [3]. they are the result of knowledge-intensive and ground-breaking policies, pointing at refining sensible enactment of cities [4]. smart cities are based on an auspicious combination of human capital, and commercial capital [4].the smart cities concept is a superlative typical urban gathering, but in actuality, we note numerous smart appearances in urban systems, such as creative districts, smart urban villages, or sustainable knowledge-based urban spaces [4]. the contextual idea of smart cities is built on the circumstance that cities house, in principle, a variety of inventive talents and can offer novel and justifiable solutions [1]. the accumulation compensations generated in modern urban groups are critical limitations for developing the potential benefits of innovative urban spaces. it has been projected that by almost 2050, two-thirds of the world's inhabitants will be living in urban regions, which will be around 7billion people. hence, equipping the cities with smart technologies and analytics can make it resilient and efficient. a large number of cities like dubai, singapore, amsterdam, new york etc., around the globe start using the smart city concept to facilitate their citizens using city infrastructure. these smart services help to improve the working techniques of different departments e.g. education, transportation, healthcare, and many others. the smart city concept is based on many advanced technologies like i.o.t, wireless sensor networks (wsn), robotics, unmanned ariel vehicles (uav), cyber-physical systems (cps), big data analytics, etc. [5]. a major step toward the practical understanding of the smart city concept comprises the growth of a communication setup capable of gathering data from a large diversity of unlike devices in a typically constant and seamless manner, according to the internet of things (iot) paradigm [2]. the internet of things (iot) period is progressing into a sensor-initiated, actuation-driven, and eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e5 https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:ahthasham.sajid@buitms.edu.pk https://www.sciencedirect.com/topics/computer-science/internet-of-things syed waqar shah, tahira magsi, and ahthasham sajid 2 machine intelligence-based decision-making platform for smart cities [3]. the smart environment is sedate by the attraction of the natural environment, pollution intensities, environmental safety activities, and resource supervision methods. it is assumed that cities can be well-defined as smart if they have the following elements as described in figure 1 below [13]. figure 1. elements of smart city 2. characteristics of smart city as there is no predefined description of a smart city but a handful of researchers have jotted down a few characteristics which sum up the modern city. a digital city comprises all the expected virtues one looks forward to in a modern city. a city must be inclusive of its entire people who are liveable and appreciate the innovation of technology. the city is resilient and resource efficient. as per the economic point of view, it will be dynamic (adaptable to change) and sustainable. but it must care for the environment and be climate-friendly. the natural ecosystem is in complete harmony with such a resilient city [19]. while the tool used to achieve the holy grail is embedding the information and communication technology (ict) in the nerve of the city through huge financial expenditure. the assistance of data-driven information with a participatory approach paves a path for integrating planning. figure 2 [12] demonstrates the characteristics and tools which can help in transform a city into a smart city. figure 2. characteristics and tolls of smart city [12] 3. related work the amount of work issued concerning about network and communication issues of the digital city is meagre. zanella et al [6] cursory define the ways through which iots can be deployed in padova, italy. zanella offered a two-way approach to address the data access, i.e. (i) using unlicensed short-range communication using a multi-hop mesh network (ii) using licensed long-range cellular technology [7]. laccase et al. suggested utilizing raspberry-pi card to control the street lights through the zigbee sensor network and wi-max [8]. while wan et al. proposed event-based communication architecture that allows facilitating communication between machine to machine (m2m), as machine being the essential component of the modern city [9]. quality of service is a vital part of any application to be successful. jin et al in their research paper presented different architecture concepts based on quality of service (qos) [10]. information-driven architecture (idra) is an innovative network architecture that focused on network functions and services such as forwarding, naming, addressing, etc. [11]. these network services are mostly used for configuration purposes for different applications. the participatory sensing network architecture is wellthought-out a special case and a new model of iot. in this model, citizens through their consumer devices gather, examine, and share sensor records. this can be entitled “human-as-a-sensor”. in this mode, wireless infrastructures such as wi-fi, gprs, and 3g are used. some conceivable applications of this architecture are ecological observing, intellectual carrying, and healthcare. qos in such a network can be complicated as humans are the central foundation of data and humans can be slothful, privacy-stricken, and prone to errors. the smart economy is restrained by private enterprise and a city's output, alteration to changes, the suppleness of the labour market, and international collaboration [13]. smart mobility is professed by the convenience of information and communication organization, from side to side the growth of supportable, ground-breaking, and harmless transport [13]. this is the body text with indent. this is the body text with indent. this is the body text with indent. this is the body text with indent. this is the body text with indent. this is the body text with indent. this is the body text with indent. this is the body text with indent. this is the body text with indent. this is the body text with indent. this is the body text with indent. 4. architectures of smart cities there are many proposed models of architecture that are suggested by numerous authors but the two main which are quite adaptable are: 1. centralized operational platform: this model is proposed by mahmoud et al. he has suggested that a digital city must have a pyramid-shaped architecture. smart city smart mobility smart people smart environment smart living smart economy smart governance eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e5 comprehensive survey on smart cities architectures and protocols 3 where every management and operation is monitored through a centralized platform. at the bottom, of the pyramid, there lies a smart infrastructure that includes all the devices that are employed in this project. following that in the middle tier, there lie smart database resources, smart building management, and smart infrastructure; which keep a record of all the data being generated. while at the top of the helm, lies the smart city itself which take care of all the affair of the city. figure 3. centralized operational platform 2. three layer architecture: three-layer architecture was proposed by harrison et al, whose crux is that a city will be divided into three halves for better management. according to this model, the instrumented layer captures and integrates the live world data with the help of the sensors, like water reading meter or water quality measurement, etc. then it’s the onus of the interconnected layer to act as the middleman and integrated the data collected and maps numerous outputs into some useful information. in the end, the intelligent layer processes the desired data into a broader context to identify city-related issues and analyze them to take action upon them. figure 4. three layers architecture 5. networking characteristics of smart cities 5.1 bandwidth bandwidth ranges from low, medium, and high (l, m, h) [15]. for example, if those applications which only control commands required a small bandwidth then those applications which utilized image and video data required medium or high bandwidth. 5.2 delay tolerance delay tolerance varies from application to application in smart city architecture. in some applications where immediate control is essential, a delay means disaster e.g. collision between cars while in some applications, such as uavs required data for future dispensation. 5.3 power consumption power consumption is a vital need for a smart city system. however, it is visible in table 1 [14] that those applications which have a local energy source, easily deal with high power consumption and those applications which have low energy capacities have low power consumption. 5.4 reliability reliability levels vary from one application to another. as shown in table 1 [14] smart water networks have medium dependability necessities and smart grids and intellectual conveyance have a high-reliability ratio. 5.5 security security importance is the same as reliability. for example, some applications due to it critical data required high security and some applications required medium security level i.e. monitoring applications. 6. routing protocols of smart cities smart city is an amalgamation of heterogeneous networks and technologies. so, every component that gets embedded in the digital city base has its own characteristics and requirement. therefore, all relevant protocols are to be followed to take maximum utilization from that component. wireless technology: in the smart city if wireless technology is deployed then its only communication mode will be wi-fi, gprs, or 3g networks. short-range applications are designed where the required energy is limited and are compact in size. they smart city database resource smart infrastructure intelligent layer interconnected layer instrumented layer eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e5 syed waqar shah, tahira magsi, and ahthasham sajid 4 don’t need frequent battery changes. applications that are short-range and installed are in smart buildings; water and grid prefer ieee 802.15.4 zigbee protocol [20]. table 1. networking protocols for smart city applications protocol data range transmis sion range applications satellite 10 mbps (for upload) 7 1 gbps (downloads) satellite can cover 100’s km to entire earth uav, monitoring uav, intelligent transport cellular 4g/ lte 300 mbps to1gbps normally 1 km area diameter pipeline monitoring, smart grid, uavs, smart water cellular 3g 144 kbps (mobile) to 42 mbps (stationary) 1km to several stationery -dowimax 802.16 275mbps up to 56km -do802.11n 15,30,45,60,9 0,120,135, 150 mbps 250m outdoors all 802.11g 6,9,12,18,24, 36,48,54mbp s 140m outdoors all 802.11b 1,2,5.5, 11mbps -doall 802.11a 24,36,48,54 mbps 120m outdoors all bluetooth 802.15.1 1mbps 10 to 100 m smart water, grid and building zigbee 802.15.4 20kbps to 250kbps 10 to 20m smart water, grid and building bluetooth uses ieee 802.15.1 which serves as master/slave time division duplex (tdd) protocol. it ranges from 10 to 100 m. (wimax), cellular 3g, cellular 4g/lgt, and satellite use ieee 802.11a, ieee 802.11b, ieee 802.11b, ieee 802.11 g protocols respectively. these protocols are the most frequently used in all urban city systems. 3g and 4g are used in smart grid applications, water management, pipeline monitoring, and uavs while satellite communication is employed for uavs, pipeline monitoring and intelligent transport. table 1 further describe the details of protocols with features. 7. conclusion with each passing day, all technical platforms—including cloud computing, the internet of things, wireless networks, robotics, etc.—have experienced a growth. the goal is to create a city that is smart and capable of coping with the constantly expanding population as well as their demands through the convergence of all these technologies. to provide the greatest utility with the least amount of overhead costs, every vista is being investigated. the core of smart technology relies entirely on reliable routes for communicating information. the only paradigm for turning a town or metropolis into an intelligent one is a quick and dependable transmission route. people do absolutely contribute to technology when they are connected to it directly through applications. acknowledgements. we would like to thanks our teacher dr. ahthasham sajid to motivate and guide us for the understanding and writing of a survey paper as class assignment during ms (cs) course. references [1] ermacora g, rosa s, bona b (2015) sliding autonomy in cloud robotics services for smart city applications. in: proceedings of the tenth annual acm/ieee international conference on human-robot interaction extended abstracts. acm. pp 155–156 [2] a. cenedese, a. zanella, l. vangelista and m. zorzi, "padova smart city: an urban internet of things experimentation," proceeding of ieee international symposium on a world of wireless, mobile and multimedia networks 2014, 2014, pp. 1-6, doi: 10.1109/wowmom.2014.6918931. 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(2016). smart cities: concepts, architectures, research opportunities. communications of the acm. 59. 46-57. 10.1145/2858789. eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e5 https://doi.org/10.1186/s13174-018-0097-0 https://doi.org/10.1007/978-3-030-04789-4_4 https://doi.org/10.1007/978-3-030-04789-4_4 https://doi.org/10.3390/smartcities3030050 https://doi.org/10.1007/s11277-022-09658-2 addressing the deployment challenges of health monitoring devices for a dementia study t. collins s. i. woolley school of electronic, electrical and systems engineering university of birmingham edgbaston, birmingham, uk. t.collins@bham.ac.uk s.i.woolley@bham.ac.uk s. aldred s. rai school of sport, exercise and rehabilitation sciences university of birmingham edgbaston, birmingham, uk. s.aldred.1@bham.ac.uk sxr294@student.bham.ac.uk abstract this paper presents the findings of a technological adoption assessment of health monitoring devices for a dementia study. the work was motivated by the need to monitor physical activity interventions in a study cohort of dementia patients living with caregiver support in the community. the system requirements were for a discrete and unobtrusive solution with activity level (energy expenditure) and heart rate monitoring. in addition to fulfilling system requirements, successful technology adoption requires careful consideration of practical challenges in deployment. the paper addresses these challenges in particular, aspects relating to the servicing and maintenance of units over the study period and the access and synchronisation of data. test data visualisations and data mining results for sustained, long-term data capture are provided. categories and subject descriptors j.3 [life and medical sciences]: health; j.3 [life and medical sciences]: medical information systems general terms health monitoring, activity monitoring keywords activity monitoring, dementia 1. introduction dementia is a term used to describe several neurodegenerative disorders, of which alzheimer’s disease is the most common, affecting millions worldwide. physical activity and exercise are known to reduce risks for diseases such as alzheimer’s disease, cardiovascular disease and diabetes by decreasing oxidative stress and inflammation in mobihealth 2015 london, uk the periphery [10]. evidence from animal-based research has shown that exercise promotes extensive vascular changes and adaptive mechanisms in the central nervous system (e.g. growth of blood vessels), consequently improving brain blood flow. however, whilst the most effective exercise has arguably been characterised for prevention and treatment of cardiovascular complaints, little is known about the best form of exercise to benefit people with dementia. monitoring the levels of physical activity in people with dementia is not straightforward. dementia sufferers are anxious about change [5] and they can become very agitated by anything new appearing in the home, or on the person [12]. in addition, the loss of short-term memory can make simple solutions, such as the compilation of an activity log, unsuitable. a wearable, self-contained, solution is preferable. a 2012 review of wearable and ambient sensing systems for health and rehabilitation highlighted the potential of objective monitoring for home-based rehabilitation interventions [9]. in addressing dementia, the authors observed that an “important factor in this patient population is that the monitoring system must be totally unobtrusive and, if possible, collect information in a transparent way without patient intervention”. while research effort in remote and “sensor-less” sensing (opportunistic sensing from devices in daily use) [8] offers some potential in terms of future solutions meeting the twin ideal of totally unobtrusive and nothing new, the recent surge in commercially available solutions for wearable activity and health monitoring devices evidences moves in the right direction. in this paper we explore and compare candidate products closest to this ideal and which comply with the study requirements. the practical issues surrounding implementation are reported together with test results for sustained, long-term data capture with visualisation analytics from raw data and data mining. 2. system requirements study requirements in terms of system sensing, data access and invasiveness were determined. the study design was for a 4-week physical activity intervention for a patient cohort with a moderate degree of dementia living with caregiver mobihealth 2015, october 14-16, london, great britain copyright © 2015 icst doi 10.4108/eai.14-10-2015.2261638 table 1: comparison of monitoring systems device activity pulse eda other raw data price manufacturer product monitoring monitoring monitoring sensors access basis peak yes yes yes skin temp. yes £200 polar ft60 yes yes∗ no gps yes £160 mio alpha no yes no yes £150 jawbone up24 yes no no no∗∗ £100 withings pulse ox yes yes no spo2 ∗∗∗ yes £100 nike fuelband yes no no no∗∗ £90 fitbit flex yes no no yes £80 ∗ requires separate chest-strap sensor for pulse rate measurement ∗∗ raw data access is not supported by the manufacturer but ‘hacks’ to achieve it are reported online ∗∗∗ spo2 = peripheral capillary oxygen saturation (pulse oximetry) support in their own homes. up to 30 study participants could require concurrent monitoring over 4 weeks. device monitoring was provisioned to supplement other study data including health, behaviour and quality of life assessments. 2.1 sensors activity monitoring is attempted to some degree by even the most basic of commercial devices and can also be achieved, in part, via embedded smartphone accelerometers. however, to better inform the assessment of energy expenditure, additional measures such as heart rate and electrodermal activity (eda) (an indicator of perspiration) were desirable. in combination with accelerometer data, these metrics allow different types and intensities of physical activity to be characterised. gps location data was also desirable but not essential. 2.2 access to raw data access to raw data may seem an obvious requirement but its support cannot be assumed. a number of systems use proprietary communication protocols to relay sensor data to a smartphone or pc and only provide access to summarised data rather than the full set of recorded sensor data. we planned to analyse and mine the data and therefore required access to the raw sensor data, for example, in csv (commaseparated value) or xml (extensible markup language) form. 2.3 invasiveness systems with separate sensors that attach to different parts of the body can give good results but were deemed too invasive for the dementia study cohort. expert advice recommended that less invasive, single unit, belt-worn devices and wrist-watch formats were preferred. 3. comparison of activity monitoring systems a survey of commercial activity monitoring systems was conducted in december 2014. the candidate devices, summarised in table 1, were: fitbit flex [2]; nike+ fuelband se [7]; jawbone up [4]; withings pulse ox [13]; mio alpha [6]; polar ft60 [11]; and basis peak [1]. all are wrist watch formats with the exception of withings pulse ox which can optionally be belt-worn. the activity monitoring market is evolving very quickly and within six months of the survey, several models had already been superseded. for example, newer devices from fitbit, mio, jawbone and microsoft include pulse monitoring and gps. these devices would be good candidates for future studies. at the time of our survey, however, these models were not available. devices that did not measure pulse rate were eliminated first. the withings’ pulse ox can measure pulse rate but not continually. to measure pulse the wearer removes the device from their wrist and puts their finger over an optical sensor on the back. this requirement was deemed unsuited to the study participants. the mio alpha was eliminated because it did not provide activity monitoring data. the remaining contenders were the polar ft60 and the basis peak. although the polar ft60 provided gps sensing, it was eliminated because of the practicalities of the pulse sensor. unlike the other devices which use optical sensors to detect pulse rate, the ft60 required a separate heart-rate sensor mounted on a chest strap. the basis peak, made available in the uk in january 2015, was the only remaining device that met the study requirements and also provided additional skin temperature data. 4. deployment challenges study adoption required the technology to be deployed with up to thirty participants concurrently for four weeks. to reduce participant invasion and researcher workload, the preferred number of researcher visits to participant homes was limited to one per week. 4.1 battery life limited battery life is a common problem associated with wearable computing devices. the basis peak watch has a battery life of between 3-5 days depending on usage. wireless data synchronisation, for example, is an energy-demanding function. with only one researcher home visit per week, there was a need for additional recharging. it was determined that placing the watch in its charging cradle for ten minutes each day would maintain the charge and could be adopted into caregiver responsibilities. 4.2 data synchronisation data synchronisation presented something of a challenge. the watch is designed to synchronise data with an iphone figure 1: examples of steps-per-minute, eda and pulse rate data collected during two four-hour periods during testing. (ios) or android smartphone via a wireless bluetooth connection using the basis app which communicates via the internet with the database held by basis. there were initial problems with android phone use because the bluetooth interface was not compatible with the latest version of the operating system (v5). however, using an older phone (with android v4.4) and disabling system updates provided a workaround. no similar problems were encountered with ios devices. 4.3 deploying multiple units although slightly convoluted, the process of data acquisition worked satisfactorily with a single watch. in the study, however, thirty watches would be deployed simultaneously. each watch expects to pair with a phone but the current phone app does not support multiple watches or multiple users. in order to synchronise data from more than one watch with a single phone, it is necessary to first create separate user accounts for the different watches. then to synchronise, the phone and watch must be paired and the account details entered into the app. once synchronisation is complete, the account details must be deleted and the watch unpaired in order to repeat the process with another device. this is not a procedure that one would wish to repeat daily. the watch is capable, however, of buffering at least a week’s worth of data although the time taken to upload this via the bluetooth link can be quite lengthy. a simple solution to the multiple unit problem would be to provision a phone for every participant. this increases the equipment costs and is wasteful given that the phone’s capabilities would otherwise not be required. single-board computers running android os were considered for an alternative solution. the most cost-effective options being media-streaming android boxes which, at the time of writing, can be sourced for as little as £20. these devices require an hdmi monitor to set-up initially, but can then be left to operate without a display and will automatically upload data from the watch to the internet at regular intervals. 5. pilot testing and visual analytics as part of the technological pilot testing, researchers wore the basis peak watches for periods of several days and weeks. reliability is a common problem with ambulatory sensing especially with sensors requiring skin contact: pulse rate, eda and skin temperature in this case. however, analysis of the raw sensor data revealed fairly good performance with 90% of sensor losses lasting less than five minutes. for the purposes of study monitoring, it was judged that this missing data could be approximated by interpolation. data recorded during different examples of fairly intense activity are plotted in figure 1 and show the result of this processing. raw data for both eda and pulse rate exhibits several short losses. the filtered data was processed by averaging valid samples within a cosine-squared windowed block of 30 minutes duration. also shown in figure 1 is the ‘expected’ value of each parameter calculated by averaging the readings from each of the 45 days during the testing period. the data in figure 1(i) was gathered during a circuit training exercise class and, as shown, the steps per minute, eda and pulse are significantly higher than average. in this example, physical activity could have been detected from the pedometry data alone. however, figure 1(ii) shows data collected from a spin (indoor cycling) session. in this case, the wrist remains virtually static so the accelerometer senses very low activity. figure 2: example of motion chart visualisation of 45 days of data. it is only the eda and pulse data that show evidence of significant physical exertion. relationships between the multiple sensed parameters were visualised using google’s motion chart [3] dynamic visualisation tool. figure 2 shows a snapshot. each ‘bubble’ represents data from a different day, bubble size varies according to eda and colour according to skin temperature. animating over the course of 24 hours reveals patterns of behaviour that can be difficult to visualise by other means. data mining techniques were used to characterise activities. the example scatter plot in figure 3 shows the results of k -means clustering. here the data has mostly been segregated across the pulse/skin-temperature plane. cluster c6, however, appears to overlap with several other clusters but, in fact, is differentiated by a higher steps-per-minute parameter. 6. conclusions careful device selection decisions, including timely consideration of practical implementation issues, are important to the design of monitoring studies. with devices evolving very quickly there is, necessarily, a new improved option near-market or another just arrived but too late for adoption. waiting for the ideal device could take years and, with crises in dementia care from the scale of demands in our aging societies, there is a need to make the best of currently available technology. careful assessment of deployment challenges has the potential to contribute by substantially reducing obstacles to effective study adoption of new technologies. in addition, pilot testing and data analysis can provide a degree of confidence in terms of system robustness and data processing requirements with visual analytics and data mining providing insights into the substance of sensed recordings. 7. acknowledgments this work was funded, in part, by the european union through a european regional development fund accelerating business knowledge base activity award in collaboration with care companions ltd. figure 3: results from k-means clustering of 45 days of data. (point colours correspond to clusters c1-8; point size corresponds to steps-per-minute.) 8. references [1] basis. basis peak, 2014. http://en-gb.mybasis.com/ [accessed 10-dec-2014]. [2] fitbit. fitbit flex, 2014. https://www.fitbit.com/uk/flex [accessed 10-dec-2014]. [3] google. motion charts, 2014. https://developers.google.com/chart/ [accessed 17-jun-2015]. [4] jawbone. jawbone up, 2014. https://jawbone.com/up [accessed 10-dec-2014]. [5] m. s. mega, j. l. cummings, t. fiorello, and j. gornbein. the spectrum of behavioral changes in alzheimer’s disease. neurology, 46(1):130–135, 1996. [6] mio. mio alpha, 2014. http://www.mioglobal.com/ [accessed 10-dec-2014]. [7] nike. nike+ fuelband se, 2014. http://store.nike.com [accessed 10-dec-2014]. [8] p. paredes, d. sun, and j. canny. sensor-less sensing for affective computing and stress management technology. in pervasive computing technologies for healthcare (pervasivehealth), 2013 7th international conference on, pages 459–463, may 2013. [9] s. patel, h. park, p. bonato, l. chan, m. rodgers, et al. a review of wearable sensors and systems with application in rehabilitation. j neuroeng rehabil, 9(12):1–17, 2012. [10] a. m. w. petersen and b. k. pedersen. the anti-inflammatory effect of exercise. journal of applied physiology, 98(4):1154–1162, 2005. [11] polar. polar ft60, 2014. http://www.polar.com/ [accessed 10-dec-2014]. [12] h. ragneskog, l. a. gerdner, k. josefsson, and m. kihlgren. probable reasons for expressed agitation in persons with dementia. clinical nursing research, 7(2):189–206, 1998. [13] withings. withings pulse ox, 2014. http://www2.withings.com [accessed 10-dec-2014]. microsoft word urb-iot2016m.oliveti.doc 1. introduction with predictions that 66% of the world's population will live in urban areas by 2050, internet of things technology is increasingly drawing the attention of city planners, engineers and architects [1]. sustainability is a common thread in conversations about the internet of things and urban areas, as a truly smart city, complete with data from its citizens' behaviours, could drastically reduce pollution and waste. present urban development policy aims to achieve sustainable mobility patterns, shifting mobility to soft transportation modes such as walking and cycling [2]. in the past few decades travel patterns have become more complex, and policy makers demand more detailed information. as a result, conventional data collection methods seem no longer adequate to satisfy all data needs [3]. recent advancements in positioning technologies, such as gps (global positioning systems), has enabled inexpensive and straightforward acquisition of movement data with handheld positioning devices [4]. this paper aims to provide empirical research on the relation between urban form and travel patterns, taking advantage of new technologies and open data. we intend to contribute both to studies on people travel behaviour, trying to demonstrate that the use of gps tracks is a useful instrument to study people travel habits, and on the other hand to studies on mobility patterns and urban neighbourhood design. the general scope of this research is comparing the performance of different neighbourhoods in terms of mobility patterns, where mobility patterns stands for “where do people actually go?”, “which mode of transportation do they use?”, “what are their main destinations?”. this research focuses on urban neighbourhoods in the netherlands. in particular, 10 different neighbourhoods are considered in three different cities: amersfoort, zeewolde, and veenendaal. 2. related work a lot of different studies have been developed regarding people travel behaviour in the last decades. 3. case study this study focuses on urban neighbourhoods in the netherlands. in particular, 10 different neighbourhoods are considered in three different cities: six in amersfoort, two in zeewolde, and two in veenendaal (see table 1). the reasons behind this choice are the evaluating urban neighbourhoods in terms of mobility performances, using open data and gps tracks to assess actual people travel behaviour eai endorsed transactions smart cities research article most of them are related to psychological and social science and try to combine travel personal diaries with socio-economic and demographic statistics [5, 6]. not so many researches about people travel behaviour use gps tracks data, since most of them tend to use traditional methods, such as paper travel diaries, phone recall surveys. it has been shown that data collected using these methods deviate systematically from actual behaviour [3]. gps devices are mainly used for orientation, navigation and communication, but in some cases they can also be used as “sensors” for tracking and for measuring activities of people. compared to traditional surveys, gps offers clear advantages including the ability to collect all movements, precise times, locations, and routes; the chance to collect multiple days of travel; and a little burden on respondents [7]. gps adds an important temporal dimension to research in urban design, primarily focused on spatial patterns, providing a new layer of knowledge that gives insight in processes and actual movement of people [4]. in the past, efforts were attempted by governments in order to reduce car mobility. for instance, in the '90s the dutch government introduced the vinex policy with the hope to influence peoples’ travel behaviour by creating urban landscapes that invite people to use alternative modes of transportation. however, the results of this policy have not been very successful, as today the new districts developed are still too much oriented towards auto mobility [8]. recently, several researches have been carried out to study travel patterns of the inhabitants of a small number of neighbourhoods in order to investigate to what extent certain spatial features of neighbourhoods provide an explanation for mobility [3, 9]. the present research is built on this literature. matilde oliveti1, stefan van der spek1 1tudelft university abstract managing urban areas has become one of the most important development challenges of the 21st century. building sustainable cities is a major factor nowadays. in this context, the advent of technologies such as gps (global positioning system) and gis (geographical information systems) enables to better address the relationship between urban form and people travel behaviour. spatial and temporal data can be collected at once, giving an insight into the actual movement pattern of people. in this paper we make a contribution to the existing literature in mobility and urban studies by comparing a series of gis-based neighbourhood indicators with the actual people travel behaviour detected by gps survey. information about built environment characteristics is retrieved by openstreetmap and other datasets. 10 different neighbourhoods in the netherlands are compared and in the end the main features that characterize efficient neighbourhoods in terms of sustainable mobility patterns are identified. received on 14 november 2016; accepted on 07 september 2017; published on 20 december 2017 keywords: gps tracking, open data, openstreetmap, people travel behaviour, mobility patterns, neighbourhoods copyright © 2017 matilde oliveti1 and stefan van der spek, licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.20-12-2017.153495 1 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e1 consistency of the data and of the gps survey, and the diversity of the three cities in size, urban form and mobility facilities. table 1 overview of neighbourhoods’ statistics of 2012 [10]. amersfoort is the second largest city of the province of utrecht in central netherlands. the city is growing quickly but has a wellpreserved and protected medieval centre. it is one of the largest railway junctions in the country. zeewolde is a town in the flevoland province in the central netherlands with a population of approximately 20.000. it is a new planned town in the early ‘80s and it has no railway station. the municipality of zeewolde was founded in 1984 and therefore it is one of the youngest in the netherlands. veenendaal is a city in central netherlands, which is part of the province of utrecht. the municipality has a population of approximately 63.000. in 1997 it was elected the greenest city of europe and in 2004 of the netherlands and it has been also the top bikecity of the netherlands in 2000. 4. methodology this research proposes a new methodology for analysing and comparing a series of neighbourhoods taking into account facilities and infrastructure networks, respect to the real movement patterns of inhabitants. with the purpose of describing the characteristics of the built environment in each neighbourhood, 17 gis-based indicators were selected and organized into three groups (proximity, density, and accessibility), based on the classification gil and read [11] made in their work. proximity indicators are mainly related to measures like the distance to the closest railway station, bus stop, supermarket, etc.; density indicators are measures of intensity, such as the land use mix, green area density, buildings density, etc.; while accessibility indicators represent the mean distance to activities and facilities, like the percentage of buildings within a railway station, etc. 4.1 datasets the gps tracks used in this study were derived from a previous gps survey conducted in 2012 [12, 13]. in total, over 800 households were tracked for a week in the three dutch cities. the raw data consisted of about 40 million gps points. over the gps tracks, information about the infrastructure networks and neighbourhood characteristics was retried from openstreetmap (osm) [14], a digital map database of the world built through crowdsourced volunteered geographic information (vgi). osm data is freely available, it has universal coverage and a rich feature set that covers all modes of transportation. osm seemed the most appropriate choice for the netherlands, as it offers high semantic accuracy and it can have a very good level of completeness. finally, additional datasets were used in this study to acquire information about addresses and buildings (bag), land use (bbg) [15], and population (cbs) [16]. 5. data processing and analysis 5.1 gis-based indicators in order to compute the gis-based indicators to assess characteristics of the built environment in each neighbourhood, a preliminary step was performed: the construction of the infrastructure networks. this operation was performed using the database postgresql [17], through which all the data about roads, cycleway, footway, etc. was extracted in osm. in the end three separated networks were created (car, cycle and walk networks), according to the different types of roads considered in osm. later, all proximity, density and accessibility indicators were computed using different tools and plugins in postgresql and qgis. for instance, within proximity indicators, it was measured the shortest path from the centre of each neighbourhood to the closest railway station (see figure 1). figure 1 shortest path between the city centre of amersfoort and the central station with pedestrian network. city neighbourhood construction period avg. number of cars per households amersfoort vathorst 1990s2000s 1,075 nieuwland late 1990s 1,1 kattenbroek early 1990s 1 schothorst 1970s-1980s 0,75 amersfoort city centre 1400-1500 0,6 leusderkwartier 1940s-1950s 0,9 zeewolde horsterveld 1995-2005 2,3 zeewolde zuid late 1980s1990s 1,2 veenendaal dragonder noord 1970s 1,1 dichtersbuurt schepenbuurt 1970s-early 1990s 1,15 permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. to copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. urbiot’16, may 24–25, 2016, tokyo, japan. copyright 2016 acm 1-58113-000-0/00/0010 …$15.00. 2 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e1 matilde oliveti1 and stefan van der spek moreover, density indicators were used to measure land use mix in the different neighbourhoods, analysing the percentage of the diverse classes of land use (e.g. residential, reatil, industrial, etc.) (see figure 2). figure 2 overview of the land use mix in the different neighbourhoods. 5.2 gps tracks analysis after the gis-based indicators implementation, the next step consisted in validating the built environment characteristics of each neighbourhood using gps real data. no effort was spent here in gps data classification and trip segmentation, since it was out of the scope of this study. the gps tracks used in this research were already pre-processed and classified in an interpretation-validation process made in previous studies [3]. a series of cleaning operations needed to be performed before analysing the gps log. the amount of data was reduced, selecting only the gps track points of the residents within the neighbourhoods. the analysis of gps tracks aimed to assess several aspects of actual people travel behaviour. first of all, travel modes were investigated counting gps track points for each modality (car, bicycle, walk, etc.). second, the most visited locations were taken into account, querying the gps data in postgresql in order to obtain the main destinations of households per neighbourhood. by filtering the track points based on the postal code and on the timestamp, only households’ single visits were selected and analysed (see figure 3). figure 3 main destinations in vathorst, based on the number of visiting households. third, all the track points with travel mode classified as ‘foot’ were selected with the purpose to highlight where people actually walk. for each neighbourhood all the gps walking track segments were then represented on a map (see figure 4). figure 4 walking travel mode trajectories in amersfoort city centre and in dichtersbuurt and schepenbuurt. 5.3 statistical analysis a statistical analysis was carried out in order to be able to compare the results coming from the gis-based indicator implementation and from the gps analysis. first, the data was normalized using one of the most common normalization method in data mining: z-scores method. then, the data was clustered and assembled in classes using the natural breaks method, chosen after having considered several clustering options. finally, a correlation test was run in order to see if a relationship existed between neighbourhood built environment characteristics and actual travel behaviour of inhabitants. several correlation methods exist, but in this case spearman correlation was used since there were only 10 cases and most of the variables were not normally distributed. a score between 1 and 5 was assigned to each group of indicator (proximity, density and accessibility) with the aim to assess the overall performances of each neighbourhood. each score represented a different level of performances: low, medium-low, medium, medium-high and high. the spider diagram (see figure 5) shows how each neighbourhood performs according to proximity, density and accessibility. figure 5 neighbourhoods’ performances in terms of proximity, density and accessibility. 3 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e1 evaluating urban neighbourhoods in terms of mobility performances, using open data and gps tracks to assess actual people travel behaviour 6. discussion and results after the analysis presented in the sections above, we came up to several conclusions and interesting results. in general, the best neighbourhoods in terms of sustainable mobility were found to be amersfoort city centre and dichtersbuurt and schepenbuurt. amersfoort city centre ranked the best mainly because of: • high population density. • wide building function types mix. • high density of cycle and pedestrian network. • great accessibility of shops by walking and cycling within 5 minutes travel time. dichtersbuurt and schepenbuurt ranked the best as well, but mainly because of: • proximity to railway station and bus stop. • great accessibility of railway station by driving, cycling and walking within 10 minutes travel time. on the contrary, horsterveld scored the worst, mainly due to: • remoteness of the railway station and of the motorway exit. • low buildings density. • bad accessibility of railway station within 10 minutes travel time. • bad accessibility of shops by walking within 5 minutes travel time. • low number of schools within 5 km. analysing the overall results coming from the gps analysis of the actual performances, it is clear that travel behaviour of households who live in amersfoort city centre and leusderkwartier is more sustainable in terms of mobility. in fact, residents in these two neighbourhoods tend to travel more by foot and by train and tend to use car less respect to residents of other neighbourhoods. in vathorst and in the two neighbourhoods in veenendaal there are still medium-high performances, mainly because of a frequent use of bike as travel mode. the lowest levels of actual mobility performances are recorded in horsterveld and zeewolde zuid, where households are more willing to use the car instead of nonmotorized transportation means. thanks to the analysis of the case study, it is now possible to identify the general features that characterized an efficient neighbourhood in terms of sustainable mobility patterns: • closeness to the city centre, given the presence of various facilities and services, especially related to shopping. • diverse building function types, as they promote walking trips since services are better accessible. • high building density, since people who live in highdensity neighbourhoods tend to walk more, because all the facilities are much closer to each other. • high pedestrian and cycle network density, as a large presence of pedestrian streets and cycle paths can encourage the use of non-motorized transport modes. • great accessibility to railway station, since people are more willing to travel by train if the railway station is close by. • great accessibility of bus stops and good level of service, as it promotes the use of public transport. 7. conclusions in this paper we make a contribution to the existing body of knowledge in mobility studies by comparing a series of gis-based neighbourhood indicators with the actual people travel behaviour detected by gps survey. this study provides empirical research on the relation between urban form and travel patterns, taking advantage of new technologies and open data. thank to the use of gps real data, today it is possible to validate current statistics with actual data, adding a new layer of knowledge to mobility studies. this research brings points of innovation to the existing literature in the field of mobility studies. in fact, thanks to the availability of new tools and thanks to the upgrade of computing power, nowadays many calculations have become much simpler and indicators from some time ago can now be enhanced. the indicators are chosen in such a way that they can be easily understood and interpreted by researchers, planners and policy makers. in doing so, the indicators are more likely to be used in mobility evaluation studies and to have impact on the policy making process. in fact, the methodology presented can be used for investigating sustainable mobility potential of neighbourhoods during planning stages of new neighbourhoods, but also for monitoring performance, propose policy and planning interventions on existing neighbourhoods. thanks to the use of datasets like openstreetmap, which is open and available worldwide, the same procedure can be applied in several cases. the method of validating spatial indicators by gps real data has demonstrated to be successful and to have a lot of potential for the future, especially if considering the wide availability of gps apps in devices like smartphones and tablets. 8. future research the work described in this paper can be improved in the future. here we address some recommendations for future work. first, improving the implementation of the theoretical performance indicators could be a possibility. improving for instance the computation of the shortest path and using additional datasets to add information to the network can lead to a more precise measure of distance. regarding the density indicators, improvements can be made especially for the analysis of land use mix and the building function types. the list of the theoretical performance indicators can always be changed and improved in future research. some indicators may be found to have limited impact on the analysis, and therefore new indicators may be added to the list. furthermore, as indicators may have different influence on the final results, a series of weights may be applied in order to level them. finally, the accuracy of the study related to the main destinations can get better if using additional technologies, such as wi-fi, bluetooth or rfid, which are often used in indoor environments. in fact, as we know, gps reception is not so good indoors, since it really depends on the building material. in a concrete building, almost no gps track point is logged. therefore, a possibility 4 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e1 matilde oliveti1 and stefan van der spek would be to use gps for tracking people outdoors, while using other technologies to track people indoors. in such a way, the accuracy of the actual performances could be enhanced. 9. references [1] united nations, department of economic and social affairs, population division (2015). world urbanization prospects: the 2014 revision, (st/esa/ser.a/366). [2] gil, j. 2010. urban form and the multi-modal mobility network structure. evaluating the sustainable accessibility of urban areas in the city-region. phd review report, tu delft [3] bohte, w., maat, k., and quak, w. (2008). a method for deriving trip destinations and modes for gps-based travel surveys. in j. van schaick, & s. van der spek (eds.) urbanism on track, chap. 10, (pp. 129-145). ios press. [4] van der spek, s., van schaick, j., de bois, p., and de haan, r. (2009). sensing human activity: gps tracking. sensor journal, issn 1424-8220 [5] beirão, g., and cabral, j.s. (2005). modeling service quality for public transport contracts: assessing users perceptions. http://hdl.handle.net/10216/67471, 9th conference on competition and ownership in land transport [6] jensen, m. (1999). passion and heart in transport — a sociological analysis on transport behaviour. pergamon, transport policy 6 (1999) 19–33 [7] wolf, j., bachman, w., oliveira, m.s. et al. (2014). applying gps data to understand travel behaviour. volume i: background, methods, and tests. national cooperative highway research program, report 775, transportation research board, washington, d.c. [8] snellen, d., and hilbers, h. (2007). mobility and congestion impacts of dutch vinex policy. tijdschrift voor economische en sociale geografie 98 (3): 398–406. [9] meurs, h., and haaijer, r. (2001). spatial structure and mobility. transportation research part d 6 429±446, elsevier [10] centraal bureau voor de statistiek (cbs) (2014). kerncijfers wijken en buurten 2004-2012. http://www.cbs.nl/nlnl/menu/themas/dossiers/nederlandregionaal/cijfers/incidenteel/maatwerk/wijkbuurtstatistieken/kwb-recent/default.htm [11] gil, j., and read, s. (2012). measuring sustainable accessibility potential using the mobility infrastructure’s network configuration. paper ref # 8104
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(2010). residential self-selection and travel. the relationship between travel-related attitudes, built environment characteristics and travel behaviour. in sustainable urban areas, delft university press [13] onderzoek verplaatsingsgedrag, research on travel behaviour, may 2105. url: http://www.verplaatsingsgedrag.nl/index5.html [14] openstreetmap. openstreetmap wiki, january 2015. url http://wiki.openstreetmap.org/wiki/main_page [15] bodemgebruik nederland. land use netherland bbg, february 2015 url http://www.compendiumvoordeleefomgeving.nl/indicatoren/ nl0061-bodemgebruikskaart-voor-nederland.html?i=1518centraal bureau voor de statistiek (cbs), (2014). onderzoek verplaatsingen in nederland 2013 (ovin). http://www.cbs.nl/nr/rdonlyres/e29e2fb9-f7cf-4b0eb497-e09c8f1f6aa1/0/2014ovin2013.pdf [16] postgresql. database management systems, january 2015, url http://www.postgresql.org/ [17] qgis. quantumgis, geographical information systems, january 2015, url https://www.qgis.org/en/site/forusers/download.html 5 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e1 evaluating urban neighbourhoods in terms of mobility performances, using open data and gps tracks to assess actual people travel behaviour artificial intelligence in smart cities and healthcare eai endorsed transactions on smart cities research article 1 artificial intelligence in smart cities and healthcare sowmitha r.1,*, shanmuga raju s.2, harshini r.3, arjuna s.4 and ram kumar c.5 1m.sc. biomedical engineering and medical physics technical university of munich, germany 2assistant professor, department of ece, dr. n.g.p. institute of technology, coimbatore, india. 3ug student, department of bme, dr. n.g.p. institute of technology, coimbatore, india. 4ug student, department of bme, dr. n.g.p. institute of technology, coimbatore, india. 5associate professor, department of bme, dr.n.g.p. institute of technology, coimbatore, india. abstract in the era of the internet of things iot and artificial knowledge (ai) continues to define the century.artificial intelligence refers to a wide term that incorporates machine learning, normal language handling, rule based expert systems, actual robots, and robotic automation . the rise of computerized system and clinical gadgets in securely and productively diagnosing, treating, and planning care is an obvious sign that ai is digging in for the long haul and fill in significance. while ai holds a great deal of potential, the ramifications for essential consideration suppliers should be tended to as it might restrict execution. since the epidemic cities in 2019, the healthcare industry has escalated its ai-based advances by 60%. as indicated by the investigation, ai calculations like ann, rnn/lstm, cnn/r-cnn, dnn, and svm/ls-svmbhas a higher impact on the different smart city domains. smart city advances the unification of conventional urban infrastructure and information technology (it) to improve the quality of living and sustainable urban services in the city. to achieve this, smart cities require coordinated effort among the general public as well as private sectors to introduce it stages to gather and examine massive amounts of information. simultaneously, it is vital to design effective artificial intelligence (ai) based tools to deal with medical services emergency circumstances in smart urban communities. this paper reviews about the current technologies like artificial intelligence in the healthcare for smart cities. keywords: artificial intelligence, iot, smart cities, healthcare received on 31 july 2022, accepted on 12 september 2022, published on 21 september 2022 copyright © 2022 sowmitha et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i3.2275 1. introduction healthcare is a fundamental part of city life. a healthcare system includes particular gatherings (e.g., patients, essential consideration doctors, drug specialists, trained professionals, and different specialists) and various stages (counting medical issue checking, illness determination, clinical therapy, and restoration). late years have seen the quick development of populace thickness in urban communities, the consistently maturing populace, and the ascent in constant disease, which presents fabulous difficulties on existing medical care frameworks, like the appeal on clinics, clinical staff, and clinical assets in *corresponding author. email: mysteryprincess27@gmail.com feasible urban communities. the headways in internet of things (iot) and ubiquitous computing have presented to us a smart city, where we trust the controllable and organized city foundations (e.g., transportation devices, structures, public activity offices) can be utilized to help illness transmission identification, treatment checking, and recovery the board. besides, man-made brainpower (ai) enabled medical services has demonstrated to be more productive, more reasonable, and more customized. consequently, accumulating ai advances to medical services with regards to smart cities is profoundly essential. these days, urban communities are becoming shrewd and can be proficiently overseen through various frameworks and offices. its capability to help shrewd medical care frameworks can infiltrate various events (e.g., eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e5 https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:harshinikaranr@gmail.com sowmitha r. et al. 2 savvy homes, local area wellbeing focuses, and brilliant emergency clinics) and situations (e.g., strange conduct observing, illness counteraction and analysis, clinical direction, solution proposal, recovery, and stamping observation). in this research topic, we exceptionally value the commitments exploring any of the diverse angles with respect to shrewd city helped medical services. all the more explicitly, we momentarily give a few opening issues as specific illustrations: as far as infection observing and counteraction, it is promising to use the foundations conveyed at each side of the city (e.g., building entryways, road garbage bin, and lifts) to identify sickness side effects (e.g., hack, fever, and asthma) among specific populaces. considering significant wellbeing direction, strong profound learning calculations and structures, (for example, convolutional brain organizations and diagram brain organizations) can be conveyed in brilliant wellbeing places to examine huge scope wellbeing information, find recognizable transient/spatial/topological examples, and backing exact determination. further, building a savvy medical care system among various gatherings is critical for effective clinical benefits. recently, the population density in cities has increased at a higher pace [1]. to make lifestyles in cities more agreeable and functional, the city ought to be smart and compelling. it is basically accomplished through a clever unique cycle using computational intelligence based advancements. this paper investigates how artificial intelligence (ai) is being used in the smart city thought. innovation has an imperative impact in smart cities, and imaginative mechanical procedures truly help metropolitan networks in turning out to be smarter. smart cities use ict to mechanize cycles and work on the idea of people's lives in metropolitan locales. likewise, it uses facilitated information advances to chip away at metropolitan foundation and enable responsive organization to remember inhabitants for city association. different present-day advances and approaches grant smart assist models with encouraging foster efficiency and exercises in medical administrations, transportation, energy, training, and various areas [1]. 2. artificial intelligence technology has a vital impact in smart cities, and imaginative mechanical methods truly help metropolitan networks in turning out to be smarter. smart cities use ict to computerize cycles and work on the idea of people's lives in metropolitan areas. moreover, it uses facilitated knowledge advances to chip away at metropolitan foundation and enable responsive organization to remember inhabitants for city association. different present day advances and approaches grant smart assist models with encouraging foster efficiency and exercises in medical administrations, transportation, energy, training, and various districts. artificial brain organization and significant learning computerized thinking progressions are quickly growing, basically in light of the fact that ai processes a great deal of data a ton faster and makes assumptions more unequivocally than humanly possible. while the huge volume of data being made reliably would cover a human trained professional, ai applications that utilizations ai can take that data and quickly change it into critical information. as of this synthesis, the fundamental block of using ai is that it is exorbitant to deal with a ton of data that ai programming requires. the ideal trait of artificial intelligence is ability to help and take actions have the clearest opportunity concerning achieving a specific goal. a subset of artificial intelligence is ai (ml), which implies that pc ventures can normally gain from and conform to new data without being helped by individuals. profound learning strategies engage this customized learning through the maintenance of tremendous proportions of unstructured data like text, pictures, or video [2]. intelligence is portrayed by learning and thinking. learning is a basic part in ai and is acknowledged through ai. thinking is another piece of ai, which consolidates data control to make exercises. the ai is expected to oversee two distinct ways emblematic based and information based (ai). human's interaction data through the eyes and that might measure up to the computer vision. in ai it incorporates techniques for getting, handling, examining, and figuring out images [2]. 3. ai in smart healthcare artificial intelligence in health care is an umbrella term to portray the application of machine learning (ml) algorithms and other cognitive technologies in clinical settings is shown in figure 1. in the least difficult sense, ai is when pcs and different machines mirror human perception, and are equipped for picking up, thinking, and simply deciding or making moves. computer based intelligence in medical care, then, is the utilization of machines to dissect and follow up on clinical information, typically determined to foresee a specific result [2]. a huge ai use case in medical care is the utilization of ml and other cognitive disciplines for clinical conclusion purposes. utilizing patient information and other data, ai can assist specialists and clinical suppliers with conveying more precise determinations and treatment plans. additionally, ai can assist with making medical services more prescient and proactive by breaking down huge information to foster better preventive consideration proposals for patients. medical services are quite possibly of the most basic area in the more extensive scene of large information due to its crucial job in a useful, flourishing society. the use of ai in healthcare service information can be a matter of life and death. computer based intelligence can help specialists, medical caretakers, and other medical services laborers in their everyday work. simulated intelligence in medical services can upgrade preventive consideration and personal satisfaction, produce more exact conclusions and therapy plans, and lead to better understanding results in eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e5 artificial intelligence in smart cities and healthcare 3 general. simulated intelligence can likewise foresee and follow the spread of irresistible infections by investigating information from an administration, medical services, and different sources. therefore, ai can play a crucial part in worldwide general wellbeing as a device for combatting epidemics and pandemics [3]. figure 1. artificial intelligence in smart healthcare numerous cities are to attempting to mimic the concept of smart city medical administrations via completing regular advancements and contraptions by merging clinical resources with ai-composed game plans. since smart wellbeing is related with the ict underpinning of the smart city, it very well may be named a subset of e-wellbeing. artificial intelligence composed iot has assisted wellbeing with caring frameworks essentially. dependability, quality, network dormancy, and information move limit are several the issues holding state of the art medical consideration back from transforming into a reality [3]. 4. e-health service architecture the iot smart city logical classification unites a lot of correspondences shows, data associations, standards, and prerequisites for the creation of uses in a city. however, special care ought to be taken to complete e-health care services, not simply considering the way that it is an order focused on prosperity and prescription, yet rather because it oversees issues that can be obstructing to a singular's life [4]. moreover, focuses associated with security and assurance should be surveyed preceding advancing health applications. an inconceivable representation of this sort of organization is m-health applications that have flooded the market due to the smart-telephones and wearables that work with the looking at and assessments of the clients due to the colossal number of sensors that these contraptions integrate. m-health applications rely upon a lot of internet and figuring developments, correspondence and information systems, and sensors and wearables contraptions related in a body region organization (ban), individual region organization (pan), thus on, which are used to get constant data which is transported off the pc people group to be taken apart by trained professionals and expect control over their patients [4]. whether or not we talk about the destiny of iot in this field, these integrate becoming new enabling stages for a developing people, for instance, recognizing the activities of everyday living, checking social co-tasks and industrious disorder management. in this regard, e-prosperity presents another medical consideration network perspective that interconnects ip based correspondence progresses, for instance, close field communications (nfc), 6lowpan, low power bluetooth and emerging 5gnetworks for future internet-based medical consideration organizations. thus, the make of m-iot applications is normal due to the interest for care in homes; where the two patients and their gatekeeper will be benefited, from the individual and monetary viewpoint [5]. accordingly, consistent trades for routine tests clinical can be avoided; convey ability cost in medical administrations can lessen, flow, and redesigns in clinical outcomes can be gotten to the next level. likewise, a sweeping improvement in the underpinning of data associations and clinical contraptions using far off correspondence to grasp data and send through different structures until they show up at the master doctor. eprosperity applications should be arranged so they do not hinder patients' normal schedules passing on them to communicate their thoughts in a protected environment, serenity of mind, food and drink contacts with friends and family, including giving encouragement physical, social and mental inclination [5]. 4.1. sensor data collecting layer data securing is performed through different sensors answerable for estimating physiological signals, for example, body temperature, heart rate, respiratory rate, pulse, muscle action, and others. the sensors are associated with a passage, which is liable for handling the data prior to being conveyed to the doctor; generally, it is a versatile (cell) base situated nearby the patient. sensors incorporated into the ban ought to be light weight, little and shouldn't ruin the singular's development, regardless of whether they utilize battery-powered or replaceable battery they ought to guarantee that the data isn't lost during substitution periods [6]. also, the ongoing sensor plans are flexible on the grounds that they can be put anyplace on the body creating more vigorous medical applications, and closeness and the contact with the skin the sensors permit estimating specific physiological boundaries. in this context, an identification design in view of iot works with the execution of these plans, since they adaptively further develop energy efficiency, permitting the utilization of sensors in light of the patient necessities. because of the energy impediment eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e5 sowmitha r. et al. 4 of these devices, these may require low power correspondence conventions, for example, zigbee or bluetooth that are utilized in low-speed wpans [6]. 4.2. medical resource management layer putting away the cloud offer versatility and openness benefits of interest from the two patients and clinical organizations. also, hosting and handling can lessen costs by giving better demonstrative data. despite the fact that there are issues that should be viewed as in clinical data put away in the cloud like hybrid cloud/cloudlet architecture: cloudlets have been acquainted as an answer with convey low dormancy to observing undertakings through pans. plus, the correspondence between the concentrator (mobile) and the cloudlet is finished through a wi-fi interface, lessening inertness and data move albeit the utilization of lte isn't enthusiastically suggested in light of the fact that it is uncovered the transmission of data to the slack delivered by the mobile network [7]. protection patient's data: the patient data can undoubtedly be compromised, on the grounds that a pan or ban is associated with a centre point, and anybody with a straightforward sniffer could catch the network bundles, uncovering the patient's status and weaknesses. it is prescribed to utilize encryption strategies to guarantee data security. secure data stockpiling in the cloud: per the terms defined by the health insurance portability and accountability act (hipaa), clinical records should be divulgence safeguarded, making fitting moves for forestalling unapproved getting to this data. clinical data handling in the cloud is as yet a test in iot applications [7]. 4.3. smart medical service layer the sensors can in-corporate different physiological examples to the customary office and research office assessments, allowing to work on the patient's medicines. this dataset brings the chance of performing data assessment, and define an ai model for sickness prediction or recognize upgrades during the time spent clinical diagnostics. not enduring, prior to being utilized for a huge extension, a couple of hardships ought to be overcome, these consolidate the support of the regulatory prerequisites for the medical gear, the readiness of clinical staff, etc., which makes that these improvements won't be taken on quickly [8]. usually, breaking down the tremendous proportion of data that the sensors give is an outstandingly perplexing endeavour. nevertheless, with the ascent of big data for the control of huge volumes of data, various estimations and methodologies have been made for the treatment of clinical data. one of the most generally perceived issues presented in this field is that the data have not a semantic connection. thus, the growing experience may not work; one expected reply for this issue is to take advantage of the clinical records that various substances have taken care of in their electronic systems. similarly, view of data in the clinical field is fundamental, in light of the fact that reference charts, pie frames and other can be utilized to address the improvement of a disorder, and subsequently specialists find it more straightforward to show the conditions of a patient. due to the high volume of data accumulated by the iot sensors means a lot to consolidate present day portrayal gadgets for addressing this data. besides, a vital piece of compact finders, concerning the data obtained in a lab, is that data are assembled over a much longitudinal way, inside radiant short lived looking at and simultaneously through different modes [9]. 5. smart applications and role in e health the technology address serious areas of strength for a, we can approach sensors, coordinated circuits, and more instruments which can be used by subject matter experts, scientists, schools and even high school projects, to propel the creation of iot applications. these parts incorporated into an exchanges net-work, allowing have applications or things related with the internet. the going with depicts specific smart city applications that contribute to a great extent to e-wellbeing organizations [10]. 5.1. smart building the aim is to make residencies, homes and business structures more sustainable, put together on energy efficiency to work with respect to the individual fulfilment, e.g., smart structures can screen their essential prosperity, direct lighting and warming considering presence detection, and use wise devices to robotize everyday tasks [11]. 5.2. smart environment the aim is to chip away at the quality of life and security of residents, e.g., avoiding noise in metropolitan networks, early rebuke of episodes or unforeseen events, obstruct guides of people and safe districts in case of disastrous occasions, e.g., shakes, floods, volcanic launches, twisters, and forest fires [12]. 5.3. open data it implies data that is openly available and may be used and inspected by outcasts (legal openness). metropolitan people group can use opensource stages like jkan to convey data and to use the data to make one more application to help people. eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e5 artificial intelligence in smart cities and healthcare 5 5.4. smart citizens this thought is associated with the creation of networks, e.g., smart training uses life-long learning programs, which could focus in on employability, digital thought, or specific people social affairs, e.g., children with mental irregularity, more established or those with physical disabilities. 5.5. smart transport one of the most important aspects to consider within a smart city is mobility. it can work on the security, efficiency, quality of life and time of users within the urban communities, e.g., using complex sensors, an independent vehicle can incorporate a personal assistant, self-driving and self-leaving capacities, control the force of the lights and even work on in the decrease of co2 emissions. indeed, whether the driver experienced any crisis, the vehicle could go without help from anyone else to the closest clinic. at long last, paths committed to bikes can give an option to the utilization of vehicles, decreasing the outflow of gases and working on the health of the users [13]. the objective is to further develop medical services frameworks, making them more powerful and efficient under the watchful eye of patients being this physically or from a distance, e.g., the wearable devices could send data from patients with a sickness (cardiac pathologies, insufficiencies, arrhythmias, etc.) to continuous checking frameworks, permitting specialists to act in the shortest conceivable time when something unanticipated is happening. ambulances could send continuous estimations of a patient to the trauma centre so that while showing up the hospital, the specialist has every one of the outcomes and manage the most effective prescription for his/her fast recuperation, or even saving the patient's life. to be sure, rescue vehicle robots could be incorporated for sending them to remote or painful regions in optimal times, keeping away from jams and land courses [13]. 6. iot and healthcare related to wsns the iot brings an exceptional measure of information that the network foundation necessities to deal with. the answer for these issues is to tweak the customary organization plans to the most recent guidelines of organization insight, which guarantees ideal security. medical clinics, centres and care offices need cost effective network, the security of which consents to information insurance guidelines but at the same time is simple to utilize and to work [14]. 6.1. digital drugs one of the more current improvements in the medical administrations industry is known as "smart pills". smart pills are taken like normal medication yet are furnished with an observing development extension to the genuine solution or some likeness thereof. they use it to propel data to a sensor worn on the body. these sensors screen drug levels in the body considering a patient's obvious or dissected condition. the data from the minimal sensors are then conveyed to a cell phone application, and that suggests that patients can get to data on their vital capacities themselves. experts can do this expecting the patient agrees. this is the manner in which the treating specialists choose if a drug is filling in as expected or possibly causing optional impacts. in november 2017, abilify my cite shipped off the main fda-cleared smart pill that time ventured when the medicine was truly taken. at the point when the pill comes into contact with the patient's gastric destructive, it sets off a sensor that means the hour of contact and first advances this data to the wearable sensor ultimately to the cell phone application. the right estimation and the supported confirmation are huge basics for a viable treatment. such data is altogether vital for clinical specialists, and they at absolutely no point in the future need to rely upon the patient's assertion alone when treatment plans ought to be totally adhered to. if patients fail to do this, the expert can search for a discussion and explain the explanation straight forwardly. one of the areas that causes fairly more trouble are assumed "mechanical" pills. once ingested, they can do certain jobs straightforwardly in the patient's body. right when the prescription is conveyed, the development separates and is handled, a decision that is great for enormous, long, chained drug particles like proteins, peptides and antibodies [14]. 6.2. patient monitoring pattern setting advancements in medical administrations license both continuous and transient consideration to eagerly be seen even more. distant patient checking (rpm) engages medical administrations specialists to screen fundamental signs and assess genuine reactions to past medications without being in a comparative spot as the patient. the gadget used depends upon the prosperity of the different patient. for instance, it very well may be an embedded-on heart device, an airflow monitor, or an arranged blood glucose meter. the gadget being alluded to accumulates the best data. in case the characteristics are not as they should be, the data are simultaneously shipped off a data set for recording and to the treating trained professional. the expert can analyse the data dynamically and answer as required. such gadgets are as often as possible used following a movement. they help with decreasing the number of medical facilities stays and avoid re-confirmations since issues are perceived even more quickly. this licenses experts to answer earlier and keep away from likely ensnarement’s. with the help of the data accumulated consistently, it is besides possible to change and change treatment decisions even more quickly, dependent upon the patient's actual reaction and condition. eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e5 sowmitha r. et al. 6 this grants experts to answer earlier and avoid likely troubles [15]. 7. conclusion the future of health care is exceptionally encouraging, taking into account the rapid development in sensor technology, ai and machine learning. for patients, hospitals and physicians as well medical device manufacturers, there are new open doors as well as even the commitment to utilize the internet of things. clearly challenges and significant changes must be dominated. all through the investigated writing there is a consistency for use of smart advancements in smart cities and particularly in healthcare, and ai and blockchain innovations are key driving factors for enhancement and improvement of overall user experience of smart cities. despite the fact that there are expected drawbacks of artificial intelligence and machine learning advancements with regards to smart cities, they still likewise have a potential to have an impact on the manner in which we know smart healthcare and smart urban communities at this point. references [1] winston ph. artificial intelligence. addison-wesley longman publishing co., inc.; 1992 jan 2. [2] hamet p, tremblay j. artificial intelligence in medicine. metabolism. 2017 apr 1;69: s36-40. [3] holzinger a, langs g, denk h, zatloukal k, müller h. causability and explainability of artificial intelligence in medicine. wiley interdisciplinary reviews: data mining and knowledge discovery. 2019 jul;9(4):e1312. [4] allam z, dhunny za. on big data, artificial intelligence and smart cities. cities. 2019 jun 1; 89:80-91. [5] batty m. artificial intelligence and smart cities. environment and planning b: urban analytics and city science. 2018 jan;45(1):3-6. [6] voda ai, radu ld. artificial intelligence and the future of smart cities. brain. broad research in artificial intelligence and neuroscience. 2018 may 8;9(2):110-27. [7] luckey d, fritz h, legatiuk d, dragos k, smarsly k. artificial intelligence techniques for smart city applications. in international conference on computing in civil and building engineering 2020 aug 18 (pp. 3-15). springer, cham. [8] srivastava s, bisht a, narayan n. safety and security in smart cities using artificial intelligence—a review. in2017 7th international conference on cloud computing, data science & engineering-confluence 2017 jan 12 (pp. 130133). ieee. [9] agarwal pk, gurjar j, agarwal ak, birla r. application of artificial intelligence for development of intelligent transport system in smart cities. journal of traffic and transportation engineering. 2015 jun 24;1(1):20-30. [10] bokhari sa, myeong s. use of artificial intelligence in smart cities for smart decision-making: a social innovation perspective. sustainability. 2022 jan 6;14(2):620. [11] voda ai, radu ld. how can artificial intelligence respond to smart cities challenges? in smart cities: issues and challenges 2019 jan 1 (pp. 199-216). elsevier. [12] kirwan cg, zhiyong f. smart cities and artificial intelligence: convergent systems for planning, design, and operations. elsevier; 2020 may 6. [13] golubchikov o, thornbush m. artificial intelligence and robotics in smart city strategies and planned smart development. smart cities. 2020 oct 3;3(4). [14] ahmed s, hossain m, kaiser ms, noor mb, mahmud m, chakraborty c. artificial intelligence and machine learning for ensuring security in smart cities. in data-driven mining, learning and analytics for secured smart cities 2021 (pp. 2347). springer, cham. [15] veselov g, tselykh a, sharma a, huang r. applications of artificial intelligence in evolution of smart cities and societies. informatica. 2021 jul 15;45(5). eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e5 this is a title 1 computational viability of fog methodologies in iot enabled smart city architectures-a smart grid case study md. muzakkir hussain 1,* , mohammad saad alam 2 , m.m. sufyan beg 1 1 2 department of computer engineering, aligarh muslim university department of electrical engineering, aligarh muslim university abstract the gradual evolution in the information communication technology (ict) support of smart city (sc) architecture leveraged with meshes of internet of things (iot) creates and welcomes research and investment efforts from academia, r&ds and policymakers. the iot utilities are being deployed at every layers of a typical sg backbone namely application layer, energy layer and communication layer. the geo-distributed clusters of iot ―objects‖ produce galactic volume of data that exacerbates the need to make a paradigm shift from centralized data center based processing to a hybrid model that supports both in situ as well as cloud based storage and computational resources. to combat such sc issues, fog computing (fc) emerges as a promising solution, which pushes the computation resources onto the network edge nodes. this work investigates the high performance of fog computing over generic cloud computing in terms of metrics viz. latencies, power consumption etc, through a smart grid (sg) use-case. through an operational cost optimization framework, the work comprehends the suitability of fog methodologies to make a synergistic interplay with the core centered clouds thus empowering a wide breed of real-time and latency free services. finally, an overview of the core orchestration issues, challenges, and future research directions are presented for fc enabled scs. keywords: smart cities (sc), smart grid (sg), internet of things (iot), fog computing, cloud computing, differential evolution (de) received on 09 december 2017, accepted on 21 december 2017, published on 12 february 2018 copyright © 2018 md. muzakkir hussain et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.12-2-2018.154104 1. introduction smart city vision brings emerging heterogeneous communication technologies such as fog computing (fc) together to substantially reduce the latency and energy consumption of internet of everything (ioe) devices running various applications. the key feature that distinguishes the fc paradigm for smart cities is that it spreads communication and computing resources over the wired/wireless access network (e.g., proximate access points and base stations) to provide resource augmentation (e.g., cyber-foraging) for resourceand energy-limited wired/wireless (possibly mobile) things. moreover, smart city applications are developed with the goal of improving the management of urban flows and allowing real-time responses to challenges that can arise in users’ transactional relationships. the notion of smart city (sc) arises from the concept of efficient utilization of city resources for enhancing quality of life of inhabiting citizens, leading to acceleration of urban penetration. for ensuring an enhanced standard of living, utilities should focus on improvement of services and infrastructure in such cities. thanks to the revolution in information and communication technology (ict) and the power of the internet, the contemporary infrastructures and public services are expected to be more interactive, more accessible, and more efficient while stepping towards the realization of smart cities. in lieu of such domains, the emergence of the internet of things (iot) paradigm strongly encourages utilization of the iot’s potential to support the smart city vision around the globe. as a consequence, the smart city has emerged as one of the important application drivers for iot aided services. iot enabled sc architectures promote the concept of interrelated physical objects (things), uniquely identified and distributed over broad physical areas covering entire city geography. recently, the iot technologies have stepped forward towards connecting five pillars viz. ―things‖, data, process, energy and people, forming the internet of everything (ioe) environments. from one perspective, cities can be regarded as an aggregation of interconnected networks that make up the ioe. hence, the ioe pillars play a significant role and work together toward the promise of our smart city vision for the eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e3 ∗corresponding author. email: md.muzakkirhussain@zhcet.ac.in http://creativecommons.org/licenses/by/3.0/ future. the ioe’s creation of data deluge synonymously big data (bd) over a distributed environment has the potential to create processing as well as storage concerns for such datastreams. although, cloud computing posits to address such problems providing virtually unlimited and flexible resource pools but cannot work efficiently for mission critical smart city applications due to its inherent problems. for instance, smart city applications like health monitoring, traffic monitoring, power transmission networks of smart grid systems etc, cannot tolerate the delay and latency incurred when transferring a massive amount of data to the remote cloud computing center and then back to the application. the concept of fog computing (fc) had recently been proposed here, as an architectural set-up that extends cloud services to the edge of the network, closer to the end user, which reduces data processing time and network traffic overhead. the primary definition of fc was introduced by cisco as ―an architecture that uses one or a collaborative multitude of end-user clients or near-user edge devices to carry out a substantial amount of storage (rather than stored primarily in cloud data centers), communication (rather than routed over the internet backbone), and control, configuration, measurement and management (rather than controlled primarily by network gateways such as those in the lte (telecommunication) core)‖. the most fundamental entity in fc, called a fog computing node (fcn), facilitates the execution of iot applications. basically, fc can act as an interface layer between end users end devices and distant cloud data centers, with the aim of satisfying mobility support, locational awareness, geo distribution, and low latency requirements for iot applications. in future scs, the sg will be critical in ensuring reliability, availability, and efficiency in city-wide electricity management. figure 6 demonstrates an example future smart grid system, where fog/cloud computing can play a significant role. a successful smart grid system will be able to help improve transmission efficiency of electricity, react and restore timely after power disturbances, reduce operation and management costs, better integrate renewable energy systems, effectively save electricity for future usage, and so on. it will also be critical in building better electricity networks to help bring down electricity bills and balance the whole electricity system. in addition, the smart power grid system should monitor power generation, power demands and help make storage decisions. in terms of security, a smarter grid will also add resiliency to large-scale electric power systems so as to help governments react promptly to emergencies or natural disasters, e.g., severe storms, earthquakes, large solar flares, and even terrorist attacks, etc. motivated by those considerations, we present fc supported smart grid (sg) use-case to investigate the expediencies of fc paradigms towards fulfilling store and compute requirements of emerging sc services. a multitier fc structure in sg supports the applications running on things to jointly compute, route, and communicate with one another through the ioe environment to decrease latency and improve energy provisioning and the efficiency of services among things of varying computational capabilities. the fog (from core to edge) paradigm will potentially abridge the silos between personalized and bulk level analytics in sg informatics. a robust fog topology allows dynamic augmentation of associated fog nodes, thus significantly improvising the elasticity and scalability profiles of mission critical infrastructures. this work outlines the fog computing paradigm and examines its primacy over the cloud computing counterpart that became ubiquitous in fulfilling the computational and analytics needs of a reliable, robust, resilient and sustainable sg. the argument here is not to cannibalize the existing cloud support for sg, but to comprehend the applicability of fog computing algorithms to interplay with the core centered cloud computing support leveraged with a new breed of realtime and latency free utilities. the objective is to assess the computational viability of fc for sc services (taking smart grid as use-case) in the realm of iot space, through proper orchestration and assignment of compute and storage resources to the endpoints and where the cloud and fog technologies tuned to interplay and assist each other in a synergistic way. the key contributions of the work are outlined as: i. proposed a fog processing architecture customized to mission critical requirements of smart grid. ii. a cost effective resource provisioning optimization model is proposed to guarantee computational qos in emerging smart grid. iii. a modified differential evolution (de) enhanced by fitness sharing is used for solving the proposed optimization model. iv. a comparative analysis of both cloud and fog execution framework is performed to assess and unveil the suitability a fog aware cloud computing platform over generic cloud framework. v. the significant issues, challenges, and future research prospects towards fog orchestration of iot application in smart city domains are highlighted. 2. fog computing in smart grid-a case study there exist relentless economic as well as environmental arguments in the academia, industries, r&ds and legislative bodies for the overhaul of the contemporary power grid comprehended by a full smart grid rollout [1]. the latter integrates green cum renewable energy production utilities, robust power monitoring schemes, adapts and evolves with the consumption behavior and requirements. however, the unique feature that overlays on the heap of a sg amenities is connectivity and real-time analytics [2]. the recent advancements in information and communication infrastructures in general and internet of things (iot) utilities in specific redefine the notion of ―smart‖ in current sg architectures. this work outlines the fog computing paradigm and examines its primacy over the cloud computing counterpart that became ubiquitous in fulfilling the computational and analytics needs of a reliable, robust, resilient and sustainable sg. the notion of smartness has been introduced into the contemporary sg architectures where the local nodes will be leveraged with computational capabilities. they will no longer remains a ―thing‖ rather will be transformed into active 2 md. muzakkir hussain et al. eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e3 computing nodes or ―objects‖. every component of sg network whether it is at the generation, transmission or service level, will act as active nodes in the entire transportation web. they are now called object in the sense that they will be having attributes, gateways, states etc. the whole transportation system can be encapsulated as a network of active nodes having deterministic state transitions. this is achieved through the notion of internet of thing (iot). iot will ensure real-time transport of information to and from the utilities, smart grid system and other components in the power system and charging infrastructure in a way that the current as well as future needs of these entities along with dedicated business engagement can be determined [3]. such technologies are enabled by the recent developments in rfid, smart sensors, communication standards, and internet protocols [4]. the basic principle is to have an environment where smart sensors collaborate directly with the ―objects‖ without human involvement aiming to deliver multitudes of applications and services [5], [6]. it is a consensus belief by industries as well as research giants that down the line, in near future iot will emerge as a technology enabler for smart transport, x2x (where x may be any of but not necessarily same from entities like vehicles, grids, homes, micro-grid etc.) data and energy exchange topologies, optimal renewable integration and intelligent charging infrastructures [7]. however, it is obvious that in the iot architecture the population of connected entities will overshoot the current growth drift and will jeopardize the normal computing configurations [8]. this will in turn cause an exponential escalation in data generation, handling of which is key task to ensure viable implementation any data aware infrastructure. connecting the objects through edge networks and technologies such as wireless sensor networks (wsn), zigbee, bluetooth, rfid, wifi, 3g, and 4g etc. will increase the complexity of underlying communication architectures. efficient and robust data analytics setup that can establish a real-time cum intelligent decision making atmosphere at every edge services becomes the need of hour. an exhaustive review of existing control paradigms reveal the presence centralized coordination strategies such as cloud computing, grid computing etc [8],[9]. however the service demands of iot architecture reflect that there needs computing schemes that can execute locally at the edge itself. the prevalent cloud models are not intended to handle the seven unprecedented v’s (volume, velocity, variety, variability, veracity, visualization and value) in the data generated by iot architectures and coupling the whole universe of ―things‖ or ―objects‖ directly to the cloud is nearly unfeasible [10]. fog computing approaches seem to be the preeminent preference for computations at the extreme edges such as vehicles, roadways, charging station etc [10]–[13]. however installation of fogs (mini data centers) everywhere across the edges of the networks and entities may not be cost productive. the infrastructure demands varying levels of services which in turn have specified qos requirements. transporting tera-peta bytes of data from millions of edge devices to the central cloud in real-time is quite infeasible and even unessential, as a significant percentage of data are passive and don’t contribute to any decision making process. furthermore, there exist several tasks that don’t even entail storage, processing and analytics at cloud scale. such requirements motivate the need of a hybrid control architecture where the mining and analytics activities are intelligently dispersed. the smart grid applications require location aware geodistributed intelligency in services such as metering information updates, power thefts, distribution outages, network intrusions etc, and require prompt and reflex actions to evolve and organize according to the adversaries. however, the current smart grid is under immense pressure owing to its sullen response to the abovementioned computational demands. also, due to its fragility concerns in sg control and coordination sub-systems, repercussions of power outages, resiliency and reliability issues are growing ever more serious. upgrading to a computationally smarter, reliable and resilient grid has escalated from being a desirable vision, to an urgent imperative. here we itemize few but not the least, of some of the mission critical requirements of an ideal sg infrastructure plus the sombre experiences encountered while going for pure cloud computing deployment. 1.1 support for scalable real-time services: the need of real-time analytics and decisions is being emerged as the need for the hour to carry up the timing requirements of mission critical sg utilities [14]. even if some servers’ fiascos occur, the system should heal itself with just graceful degradation in latency services. the current cloud models support for sgs can provide rapid response mechanisms but adversaries still pose threats to responsiveness. 1.2 support for scalable, consistency guaranteed, fault-tolerant services: consistency for cloud-hosted utilities is a broad term associated with acid (atomicity, consistency, isolation and durability) guarantees, support for state machine replication, virtual synchrony, and support for only limited count of node failures [1]. today’s smart grid cloud infrastructures often ―embrace inconsistency‖, thus implementing consistency preserving computational structures constitute a nascent thrust domain for the research & development sector. 1.3 privacy and security: the woeful protection services of current cloud deployments often stimulate the cloud vendors to recapitulate their security management folks to ―not be evil‖. stern efforts are in progress across the power system and transportation communities to come up with sg cloud utilities and platforms leveraged with robust protective contrivances where the stakeholders could entrust the storage of sensitive and critical data even under concurrent share and access architectures [15], [16]. 1.4 highly assured connectivity: added with power outages, the smart grid consumers also experience intermittence in data connectivity. projects for establishing mechanisms dedicated to support secured multipath data routing from user edges to cloud services are on headway [17],[18]. critical components of the future smart grid applications demand better quality of service (qos) and quality of experience (qoe) from the data routing backbone that underlie the cloud-hosted utilities. 3 computational viability of fog methodologies in iot enabled smart city architectures-a smart grid case study eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e3 figure 1: topology of fog computing paradigm in a smart grid 1.5 need for risk management modules: switching from traditional power grid to multi-tenant sg subsystems introduce substantial risks to power sector, an issue that need to get fixed in inception phase. the penetration of autonomous evs into modern road transport manifolds such concerns. the evs are becoming a basin for multidimensional data production, an asset if mishandled, may befool the execution of whole systems. moreover, the data generated due to cloud-iot integrated transportation telematics coupled with advanced metering infrastructures (ami) can prove to be harmful to its stakeholders, specifically for privacy and security [19]. thus, it’s an earnest need for the stakeholders to be assured with stringent protection protocols and be inert from the vulnerabilities. such scenario necessitates incorporating robust risk analysis procedures that will evaluate and quantify the computational and business risks that persist in such critical infrastructures [20]. selection followed by implementation of proper risk analysis paradigms is itself a full-fledged realm to dwell on. risks perceived to be minor in inception phase, later elicits tougher public concerns. though the ―pay-for-usage‖ protocols of cloud computing business models are efficient in satisfying the bulky analytics and computational tasks, the bliss transforms into worries when the applications demand null-latency services and when the data stream chokes the bandwidth restricted communication buses [21]. the emerging wave iot based transportation telematics can prove potentially astonishing in fulfilling the mobility requirements of contemporary smart grid architectures [21], [22]. motivated by the above mentioned mission critical smart grid requirements, the pitfalls associated with current cloud computing infrastructures to meet such needs, and having the assumption that the smart grid community is not in a position to reinvent a remotely owned internet infrastructure or to develop computing platforms and elements from scratch, this work presents a fog computing framework whose principle underlie on offloading the time and resource critical operations from core to edge. the argument here is not to cannibalize the existing cloud support for sg, but to comprehend the applicability of fog computing algorithms to interplay with the core centred cloud computing support leveraged with a new breed of real-time and latency free utilities. 3. fog computing architecture for smart grid this section presents a three schema computing architecture where the significant portions of smart grid control and computations are non-trivially hybridized alongside the cloud computing support. the objective is to overcome the disruption caused by the development of iot utilities where the control, storage, networking and computational needs are actively proliferated across the edges or end-points. the lowermost schema namely physical schema or data generator layer primarily comprises of a wide range of smart iot enabled devices which come within the sg domain. for simplicity, the entities are abstracted into logical clusters of applications, directly or indirectly influenced by the expediency of sg operations. the first cluster (c1) represents vehicular applications where the intelligent vehicles are arranged to form vehicular fogs. the existing transportation telematics support such as cellular telephony, on-board sensors (obs), roadside units (rsu), and smart wearable devices will uncover the computational as well as networking capabilities latent in the underutilized vehicular resources. the notion is to employ the underutilized vehicular resources into 4 md. muzakkir hussain et al. eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e3 communicational and analytics use, where a collaborative multitude of end-user clients or near-user edge devices carry out communication and computation, based on better utilization of individual storage, communication and computational resources of each vehicle [5]. similarly, similar presence of clusters (c2) could also be traced in smart home networks that have a noteworthy contribution in consistent operations of the backend sg support. the intelligent iot equipped home gadgets such as washing machines, ac, freezes, parking lots, cc camera etc, are also potentially active to provide storage, analysis and computational support for satisfying the prompt and local decision making services. the third but not the least, cluster c3 depicts similar structure that can be constituted by utilities involved at the extreme ends of a sg infrastructure viz. micro-nano grid, plcs, (han, man etc) automated circuit breakers and other entities associated to diverse range of sg generation, transmission and distribution services. the smart nodes within such clusters sense and cultivate the heterogeneous physical attributes and transmit it to the upper layers through dedicated edge gateways. however, the whole or a portion of data generated within these physical clusters are accumulated at the interim across access points such as global positioning (gps), gis, road-side units (rsu),remote terminal units (rtu), intelligent electronic devices (ied), phasor data concentrators (pdc), and other field arrays. the next tier constitutes the fog computing layer comprising of intelligent fog devices such as scada, smart meters, routers, switches high-end proxy servers, intelligent agent and commodity hardware etc, having peculiar ability of storage, computation and packet routing. the software defined networking (sdn) assembles the physical clusters to form virtualized inter cluster private networks (icpn) that route the generated data to the fog devices spanned across the fog computing layer the fog devices and its corresponding utilities form geographically distributed virtual computing snapshots or instances that are mapped to lower layer devices in order serve the processing and computing demands of sg. 4. networking and system formulation in a cloud computing model the mega data center (mdc) provides sharable resource pool available for on demand use. since the mdc are far remote from the generation and query sites, data migration and service latency gives rise to infeasibilities for real-time and interactive sg applications and services. however, in a fog architecture, low power fog computing nodes (fcn) are deployed at the dedicated edges of the network to provide platform for sg mobility, real-time response and geo-distributed intelligence. consider a fog architecture customized for sg services which supports both cloud as well as local fog processing, in which data and computation are selectively offloaded to either cloud or fog scale processing guided by an application specific logic. without loss of generality, let us assume the sets d , f , and n represents the set of data centers, fog nodes and number of consumers having cardinality d, f and n respectively. an instance of smart grid (sg) network can be modeled as a connected cellular graph of order (n +f) whose vertices are constituted by data consumer set (n) and fcn set (f). let ( a i r ) be the frequency of workload arrival on fog node i. the fcns are equipped with set of processing elements (e) each having service rate s i r . an fcn j is reachable from query source node k if the former is in the preference list l. for demonstrating the feasibility of a customized fog computing architecture in smart grid sub-systems proposed in section 3, the work utilizes metrics that correlates the performance of fog computing services to that of traditional cloud computing paradigms. the geo-distributed micro datacenters in a typical fog model performs a significant proportion of local computations on the data produced by data generators at the schema 1. however, the devices are leveraged with distributed intelligence, in that depending upon the degree of services criticality and the types of data, the righteous decision of whether to offload the data to the cloud or to the local micro-data centers can be undertaken. for sg applications, the fog computing framework outperforms its pure cloud counterparts in respect to metrics like power consumption, latency and carbon footprint (emission) etc [25]. figure 2: probabilistic decision tree depicting the workload offloading strategy consider a pilot sg analytics service to be delivered from the three tier fog architecture devised in section 3 over a 24 hour time horizon. out of volume  of data generated in the whole day, the pre-processing and decision modules deployed in the first tier offloads 1  into the mega datacenters for cloud level analytics while distributes 2  to the micro datacenters for local and instant scale processing and computations. the uncertainty in the data distributions across multiple schemas is captured by probability tree depicted in figure 2. an ideal fog-cloud framework is leveraged with robust inferencing logic and intelligent filtering devices to undertake instant decisions on where to distribute the produced datasets. the objective of the proposed framework is to minimize the cost encountered due to power consumption, latency and emission issues. in case of fog computing approach, an additional cost term needs to be added due to communication among the iot enabled sensors as well as micro datacenters. 1. cost profile for generic cloud processing: ( ) ( ) ( ) ( ) c c c c f x c v c w c c   (1) where ( ) c f x , ( ) c c v , ( ) c c w and ( ) c c c represent the overall cost function, power consumption cost (incurred due to 5 computational viability of fog methodologies in iot enabled smart city architectures-a smart grid case study eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e3 storage and execution of the data at the mega datacenters), cost due to latency terms and the cost due to carbon footprint at the data centers respectively. 1 3 . { .( ) (1 ).( )} ( ) . (1 ).(1 ).( ) . c c s c s c s c a c e c f c a v v v                    (2) where, c s  , c a  and 3 v represent the power consumed in cloud storage, cloud storage cum processing and amount of data that is migrated to the cloud layer through cloud-fog gateway interface (21-22 in fig 1). e  ((usd/kwh)) is the energy to cost conversion factor. 1 3 . (1 ) .(1 ) . ( ) . 1 1 1 . c c f d c l d e e f f c v v w w w w w                        (3) l  (usd/minutes) is the delay to cost conversion factor.  1 ( ) . . .(1 ) . c c c g c c v v      (4)  and g  represents the gas emissions rate from the data centers and emission to cost conversion factor. 2. cost profile for fog aware cloud processing: ( ) ( ) ( ) ( ) f f f f f x c v c w c c   (5) where ( ) f f , ( ) f c , ( ) f c and ( ) f c represent the overall cost function, power consumption cost (incurred due to storage and execution of the data at the micro datacenters), cost due to latency terms and the cost due to carbon footprint at the local data centers respectively. 2 3 ( ) .(1 ).{ .( ) ( ) . (1 ).(1 ).( ) . c f f a f c f f s v c v                (6) where, f a  and f s  represent the energy consumed in fog processing, fog processing plus cloud storage respectively. 2 3 3 1 (1 ) . .( ) . ( ) . 1 1 (1 ) .(1 ) . . f d e f l c f e f f c v v w w v w                       (7) 2 3 ( ) .(1 ) ( ) . . .(1 ) .(1 ) c f c v v c v              (8) d c w , d e w , e f w and f c w represent the bandwidth of the channel linking generators to mega datacenters (when data demands pure cloud storage or computations), generators to edge routers, edge routers to fog gateways and fog gateways to cloud gateways respectively. 3. optimization model: in order to assess the viability of proposed fog computing framework, in this subsection a cost optimization model is proposed. the objective is to reveal the fact that, if properly designed, a fog computing framework can circumvent intricacies prevalent in contemporary cloud computing paradigms. the following optimization framework captures the scenario where former outperforms the later in terms overall performance. m axim ize  m in ( ) m in ( ) f f x f x (9) subject to: 1 v v v  (10) ( ) ( ) f c c c c (11) ( ) ( ) f c w c w (12) 5. simulations and results for simulating the topology, the 100 most populated cities around the world are considered for representing the number of iot users and the corresponding geographical coordinates are used to determine the relative euclidian distance. the number of application consumers and the potential data traffic is assumed to be proportional to the population of internet users of the city. the user to fog links allows transmission of packets of 34 to 64k bytes following poisson arrival pattern having 8 byte instruction size. the capacity of user to fog links and fog to cloud links is assumed as 1gbps and 10gbps respectively. for assessment of system performance against the network parameters the total population of consumers is captured in a variable in the range [10000, 100000]. the number of data centers is considered to be 8 and the pairwise euclidian distance is stored in 2d variable    e d . for cost analysis, the cost of 1gbps and 10gbps gateway router port is kept usd50 each per year while cost of server is usd 4000 per year. these routers are assumed to consume electricity at 20w and 40w respectively. upload rate is usd 12 per byte while storage cost is kept in the range of usd 0.45-0.55 per hour. the penalty corresponding to co2 emission is kept usd 1000 per tons of co2 emitted. the formulated optimization model is a multistage, discrete, nonlinear, constrained mixed-integer programming problem (minlp). usually classical mathematical programming techniques fail to provide tractable solutions to such problems. evolutionary optimization algorithms specifically meta-heuristic methods such as differential evolution (de) [price] are promising approach to solve an minlp. de is a population-based evolutionary optimization method which had proven to be very simple yet powerful to solve minimization problems with nonlinear and multi-modal objective functions. it differs from conventional evolutionary 6 md. muzakkir hussain et al. eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e3 algorithms in that instead of having a predefined probability distribution function (pdf) for mutation process, it utilizes the differences of randomly sampled pairs of objective vectors for its mutation process [6]. such variations will ensemble the topology of the objective function towards optimization procedure thus providing more efficacious global optimization capability. we employed, a modified version of differential evolution with fitness sharing function of niche radius () in order to reduce the fitness of similar offspring’s. the fitness function is given by ( , ) 1 0 0 f f o th e r w is e              (13) as in de the evolution strategy is focused to obtain minimal optimal value, of the shared fitness is obtained from 1 . ( , ) p s j f j s f f f      (14) where, j f controls the crossover constant commonly determined on a case to case basis. in order to guarantee the fact that the best offspring always appear for next generation, elitism is employed. further details are beyond the objective of this paper. in this section we presented the comparative result analysis of cloud and fog execution in terms of performance metrics namely response times (service delay), electricity consumption and cost of architecture. we depict the overall latency profile of a fog aware cloud architecture with a generic cloud execution scenario. the upload latency, inter-fog communication delay and delay due to fog to cloud dispatch is abstracted in transmission latency while the delay caused due to computations and analytics at vm fog nodes and data center servers is accumulated to processing latency term. the overall service delay is the linear sum of transmission and processing latency. for a parameter  defined to be the ratio of data packets dispatched to cloud core to the number of packets entering into the fog network through consumer to fog gateways. fc f     (15) the fog-cloud comparison delay statistics is shown in fig. 3 for .2 5  (three fourth of requests are served within fog alone). it can be observed that for both the fog as well as cloud platforms the latency is proportional to the population of data generators (traffic) and performance of fog aware execution outperforms the cloud counterparts for every volume of traffic. in fig. 4 the electricity consumption pattern in transmission/dispatch of data bytes, computation (at both fog and cloud servers) is analysed. it can be observed that with the rise in the population of service consumers the overall power consumption show linear growth and is significantly lower than the conventional cloud framework. the fog aware framework betters the aggregated electricity consumption over the cloud computing paradigm by more than 40%. 0 2 4 6 8 10 0 10 20 30 40 50 60 la te nc ie s ( se co nd s) no. of consumers * 10 4 fog transmission latency fog processing latency fog service latency cloud transmission latency cloud processing latency cloud service latency figure 3: comparison of latency metrics between generic cloud vs fog assisted cloud platforms 0 2 4 6 8 10 0 1000 2000 3000 4000 5000 c os t d ue to p ow er c on su m pt io n no of consumers (*10 4 ) fog cost due to data transmission fog cost due to computation fog cost due to data storage fog-net power consumption cost cloud cost due to data transmission cloud cost due to computation cloudcost due to data storage cloud-net power consumption cost figure 4: comparison of various cost parameters 6. fog enabled smart cities-challenges and future directions a typical fog platform is driven by key technology enablers, for its successful deployment. since, the field is relatively immature [23], a large amount of experimentation needs to be done. the fc platform should be able to provide a framework that others can use it to test different approaches, techniques, and algorithms. for instance, there are many ways to autonomously annotate data with semantics within a fog gateway. it is not possible to develop one universal approach or algorithm to annotate data. thus, a fc platform should be provide flexibility to the developers to write exertions, support new ways of annotating data [24]. also, fc should provide built-in supports for varying communication standards and application level protocols [21]. further, providing support for existing data analytics frameworks is also important. due to low computational 7 computational viability of fog methodologies in iot enabled smart city architectures-a smart grid case study eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e3 resources of fc gateways, it is important that these plugins can be easily removed to avoid resource wastage when not required in a given fog gateway. despite we see a large number iot cloud platforms in the market in both academia (e.g., openiot) and industry (e.g., ibm bluemix, microsoft azure iot), a fog computing platform that supports all the those features are yet to be researched and developed [25]. we believe such fog platforms would be greatly beneficial to the research and industrial communities once available as by then people can easily test new fog computing related approaches, techniques and algorithms. distributed intelligence will be very critical in making fog computing platforms successful in building future smart cities. the main reason is that prompt reactions and best possible decisions should be achieved in a timely manner to make future cities smarter, safer and more living-enjoyable. this requires a large amount of research efforts in putting distributed intelligence in place properly across smart things, buildings, fog devices/gateways, and cloud computing infrastructure in a city. this process will involve many important aspects, such as available domain-dependent knowledge/ intelligence, combination of business logic, engineering processes and government policies, cost-efficient and computation-efficient and context-/semantics-aware computing models for real-time decision making, etc [26]. high paced r&d and investments efforts since past decade have led to the maturity of the cloud based techniques having efficient frameworks, deployment platforms, simulation toolkits and business models. however, in context of fog deployments such efforts though on pace, but still near its infancy [21], [26]. there may be plenty of literatures hypothesizing the execution scenario of fog platforms but are still in concept and simulation phase. roll-out of fog services needs to inherit many of the properties of cloud counterparts and the requirement of deploying computational workloads on fog computing nodes (fcn) need to be demystified properly [27]. in addition fog comes with its inherent silos and raises many questions asking for right and consensus answer. some of them may be, where to place a workload, what are the connection policies, protocols and standards, how to model/interpret the interaction of/among fog nodes, how to route the workload etc. since iot enabled smart city services are pervasive in cyber-physical environments and the complex iot services are increasingly composed of sensors, devices, and compute resources within fc infrastructures, orchestrating such applications can simplify maintenance and enhance data security and system reliability [28]. however, efficiently dealing with dynamic variations and transient operational behavior of such sc services is a crucial challenge. this section provides an overview of the core issues, challenges, and future research directions in orchestration for iot services in fc enabled smart cities. in the next sub-section we highlight the key orchestration challenges in fog-enabled orchestration for sc applications. following this, the nascent research avenues envisioned by such issues and challenges are also explored. a. fog orchestration challenges for intelligent transportation applications in iot space 1. scalability since the heterogeneous sensors and smart devices employed in sc are designed from multiple iot manufacturers and vendors, selecting an optimal device becomes increasingly intricate while considering customized hardware configurations and personalized sc requirements. moreover, there may be applications can only operate with specific hardware architectures viz. arm or intel etc, and through wide range of operating systems [29]. additionally, the sc applications with stringent security requirements might require specific hardware and protocols to function. an orchestration framework need not only to cater to such functional requirements, it must scale efficiently in the face of increasingly larger workflows that change dynamically [23], [30]. the orchestrator must assess whether the assembled systems, comprised of cloud resources, sensors, and fog computing nodes (fcn), coupled with geographic distributions and constraints are capable of provisioning complex services correctly and efficiently. in particular, the orchestrator must be able to automatically predict, detect, and resolve issues pertaining to scalability bottlenecks that could arise from increased application scale in a customized sc architecture. 2. privacy and security security is also a critical issue in building future smart cities. this mainly refers to security of fog computing platforms, including potential cyber-attacks to smart things, fog devices/gateways, and trust and authentication, network security, and data security, etc [31]. for example, cyberattacks to smart things, fog devices/gateways can dysfunction smart things, fog devices/gateways and pose risks in failure of providing proper services to the city and making wrong decisions in reaction to emergencies and disasters. failure of ensuring trust and authentication will also put any large-scale fog computing platforms at risk, potentially leading to intentional and accidental misbehaviour, criminal activities and so on. network security is also of great importance since network attacks such as jamming attacks, sniffer attacks and so on can create huge risks in fog computing systems, potentially leading to chaos of the whole fog computing systems. data security will also be critical. sensitive and/or valuable data generated from any fog computing platforms should be kept secure [32]. since in iot aided sc like use-cases such as smart grid, smart parking etc, a specific application is composed of multiple sensors, computer chips and devices, their deployment in varying different geographic locations result in increased attack vector of involved objects. examples of attack vector may be human-caused sabotage of network infrastructure, malicious programs provoking data leakage, or even physical access to devices [33]. holistic security and risk assessment procedures are needed to effectively and dynamically evaluate the security and measure risks, as evaluating the security of dynamic iot based application orchestration become increasingly critical for secure data 8 md. muzakkir hussain et al. eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e3 9 placement and processing. the iot integrated devices for fog support such as switches, routers and base stations etc, if are brought to be used as publicly accessible computing edge nodes, the risk associated by public and private vendors that own these devices as well as those that will employ these devices will need revised articulation. also, the intended objective of such devices, e.g. an internet router for handling network traffic, cannot be compromised just because it is being used as fog node. the fog can be made multi-tenant only when stringent security protocols are enforced. 3. dynamic workflows another significant characteristic and challenge for iot enabled sc applications is their ability to evolve and dynamically change their workflow composition. this problem, in the context of software upgrades through fcns or the frequent join-leave behavior of network objects, will change the internal properties and performance, potentially altering the overall workflow execution pattern. moreover, handheld devices used by sc stakeholders inevitably suffer from software and hardware aging, which will invariably result in changing workflow behavior and its device properties (for example, low-battery devices will degrade the data transmission rate). furthermore, performance of transportation applications will change owing to their transient and/or shortlived behavior within the sc subsystem, including spikes in resource consumption or big data generation. this leads to a strong requirement for automatic and intelligent reconfiguration of the topological structure and assigned resources within the workflow, and importantly, that of fcns. 4. tolerance scaling a fog computing framework in proportion to sc application demands increases the probability of failure. some rare software bugs or hardware faults that don’t manifest at small scale or in testing environments, such as stragglers, can have a debilitating effect on system performance and reliability. at the scale, heterogeneity, and complexity we’re anticipating, different fault combinations will likely occur. to address these system failures, developers should incorporate redundant replications and user-transparent, fault-tolerant deployment and execution techniques in orchestration design. b. future research directions the challenges outlined in the above sub-section unlock several key research directions for successful deployment of fog supported sc architectures. the research prospects defined for fog life cycle management can be executed in three broad phases. in deployment phase, research opportunities include optimal node selection and routing, parallel algorithms to handle scalability issues, etc. in runtime phase, incremental design and analytics, re-engineering, dynamic orchestration etc, are potential research thrusts for supporting dynamic qos monitoring and providing guaranteed qoe [34]. in the evaluation phase, big-data-driven analytics (bd 2 a) and optimization algorithms are prime avenues that need to be explored to improve orchestration quality and accelerate optimization for problem solving. figure 5: functional elements of a typical fog orchestrator 1. opportunities in deployment phase: i) optimal node-selection and routing: determining resources and services in cloud paradigms is a well explored area and easily understood, but exploiting network edges in decentralized fog settings call for discovery mechanisms to associate optimal nodes [5],[34],[35]. resource discovery in fog computing is not as easy as in both tightly and loosely coupled distributed environments, and manual mechanisms are not feasible because of sheer volume of fcns available at fog layer. if the sc utility needs to execute machine learning or big-data tasks, resource allocation strategies also need to cater for datastream of heterogeneous devices from multiple generations as well as online workloads. benchmark algorithms need to be developed for efficient estimation of fcn’s availability and capability [4]. these algorithms must allow for seamless augmentation (and release) of fcns in the computational workflow at varying hierarchical levels without added latencies or compromised qoe. autonomic node recovery mechanisms needs to be devised to ensure consistency and reliability in in fault detection in fcn networked architectures, as existing cloud based solutions don’t fit to them. besides, the most potential research aspect to ponder is workflow partitioning in fog computing environments. though numerous task partitioning techniques, languages and tools have been successfully implemented for cloud data centers, but research regarding work apportioning among fcns is still in concept phase. without specifying the capabilities and geo-distribution of candidate fcns, automated mechanism for realizing computation offloading among those nodes is challenging. maintaining a ranked list of associated host nodes through priority aware resource management policies, making hierarchies or pipelines for sequential offloading of workloads, developing schedulers for dynamically deploying segregated tasks to a multiple nodes, algorithms for parallelization and multitasking of only fcns, fcns and data centers or only data enters etc, are rigorous research hypes in academia as well as r&d community [35]. computational viability of fog methodologies in iot enabled smart city architectures-a smart grid case study eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e3 ii) parallelization approaches to manage scale and complexity: optimization algorithms or graph-based approaches are typically time and resource-consuming when applied on a large scale, and necessitate parallel approaches to accelerate the optimization process. recent work provides possible solutions to leverage an in-memory computing framework to execute tasks in a cloud infrastructure in parallel. however, realizing dynamic graph generation and partitioning at runtime to adapt to the shifting space of possible solutions stemming from the scale and dynamicity of iot components remains an unsolved problem. iii) heuristics and late calibration: to ensure near-real-time intervention during iot application development, one approach is to use correction mechanisms that could be applied even when suboptimal solutions are deployed initially. to ensure near-real-time intervention during iot application development, one approach is to use correction mechanisms that could be applied even when suboptimal solutions are deployed initially. for example, in some cases, if the orchestrator finds a candidate solution that approximately satisfies the reliability and data transmission requirements, it can temporarily suspend the search for further optimal solutions. at runtime, the orchestrator can then continue to improve decision results with new information and a reevaluation of constraints, and use taskand data-migration approaches to realize workflow redeployment. figure 6: the conceptual framework for big data-driven analytics and optimization of smart city based on cloud and fog platforms 2. opportunities in runtime phase i) dynamic orchestration of fog resources: apart from the initial placement, all workflow components dynamically change in response to internal transformations or abnormal system behavior. iot applications are exposed to uncertain environments where execution variations are commonplace. because of the degradation of consumable devices and sensors, capabilities such as security and reliability that initially were guaranteed will vary, resulting in the initial workflow being no longer optimal or even totally invalid. furthermore, the structural topology might change according to the task execution progress (that is, a computation task is finished or evicted) or will be affected by the execution environment’s evolution. abnormalities might occur owing to the variability of combinations of hardware and software crashes, or data skew across different management domains of devices due to abnormal data and request bursting. this will result in unbalanced data communication and subsequent reduction of application 10 md. muzakkir hussain et al. eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e3 11 reliability. therefore, dynamically orchestrating task execution and resource reallocation is essential. ii) incremental computation strategies: the sc applications may often be choreographed through workflow or task graphs to assemble different iot applications. in some domains, the orchestration is supplied with a plethora of candidate devices with different geographical locations and attributes. in some cases, orchestration would typically be considered too computationally intensive, as it’s extremely time-consuming to perform operations including pre-filtering, candidate selection, and combination calculation while considering all specified constraints and objectives. static models and methods become viable when the application workload and parallel tasks are known at design time. in contrast, in the presence of variations and disturbances, orchestration methods typically rely on incremental scheduling at runtime (rather than straightforward complete recalculation by rerunning static methods) to decrease unnecessary computation and minimize schedule makespan. iii) qos-aware control and monitoring protocols: to capture the dynamic evolution and variables (such as dynamic evolution, state transition, and new iot operations), we should predefine the quantitative criteria and measuring approach of dynamic qos thresholds in terms of latency, availability, throughput, and so on. these thresholds usually dictate upper and lower bounds on the metrics as desired at runtime. in normal setting, complex qos information processing methods such as hyper-scale matrix update and calculation would lead to many scalability issues. iv) proactive decision making: localized regions of self-updates become ubiquitous within fog environments. the orchestrator should record staged states and data produced by fog components periodically or in an event-based manner. this information will form a set of time series of graphs and facilitate the analysis and proactive recognition of anomalous events to dynamically determine such hotspots [36].the data and event streams should be efficiently transmitted among fog components, so system outage, appliance failure, or load spikes will rapidly feed back to the central orchestrator for decision making. 3. opportunities in evaluation phase: big-data-driven analytics (bd2a) and optimization a typical sc framework congregates the diverse smart entities into a clique like structure in iot realm and enables a bidirectional flow of energy and data among the stakeholders in order to facilitate the assets optimization. the major data sources for a data driven sc include sc sensing objects such as sg, scada, connected vehicles, on-board sensors (obs), road-side units (rsu), traffic sensors and actuators, gps devices, smart traffic lights and the web data from recommender systems, crowdsourcing, feedback modules. furthermore, the domain of iot in sc applications is extended to numerous geographically distributed devices that produce multidimensional, high-volume dynamic data streams requiring a noble mix of real-time analytics and data aggregation. figure 15.6 depicts the conceptual framework for big data-driven analytics (bd2a) and optimization of an intelligent traffic management use-case based on cloud and fog platforms. the fog orchestration module should employ efficient data-driven optimization and planning algorithms for reliable data management across complex iot aided sc endpoints. while developing sc applications adhered to fog computing and making proper trade of such applications across different layers in the fog environment, the developers should employ robust optimization procedures that stabilizes the schema definitions, mappings, all overlapping, interconnection between layers (if any). in order to reduce data transmission latencies data processing activities and the database services may be pipelined. rather than frequent triggering of move-data actions, use of multiple datalocality principles (e.g. temporal, spatial etc.) and efficient caching techniques can distribute or reschedule the computation tasks of fcns near the sensors thereby improving the delays. the data relevant attributes related to qos parameters such as the data-generation rate or data-compression ratio can be customized to adapt to the desired degree of performance and assigned resources to strike a balance between data quality and specified response-time targets. a major challenge is that decision operators are still computationally time consuming. to tackle this problem, online machine learning can provision several online training (such as classification and clustering) and prediction models to capture the constant evolutionary behavior of each system element, producing time series of trends to intelligently predict the required system resource usage, failure occurrence, and straggler compute tasks, all of which can be learned from historical data and a history-based optimization (hbo) procedure. researchers or developers should investigate these smart techniques, with corresponding heuristics applied in an existing decision-making framework to create a continuous feedback loop. cloud machine learning offers analysts a set of data exploration tools and a variety of choices for using machine learning models and algorithms. 7. conclusions due to the improvements in sensing technology and reduction in costs, sensing capabilities are expected to be integrated into everyday objects around us. there is a natural tendency that smart city applications are being built in a centralized manner. that means all the data collected by sensors are transferred to a cloud node for knowledge discovery. however, this is a very inefficient approach from both computational and communication perspectives. to address such issues, the fc paradigm has been proposed, as it brings sustainability to the smart city computations. in this work, high performance of fog computing over generic cloud computing is evaluated, in terms of metrics viz. latencies, power consumption etc, through a smart grid (sg) use-case. this paper also provides an overview of the core issues, challenges, and future research directions in fogenabled orchestration for iot enabled sc applications. references [1] l. da xu, s. member, w. he, and s. 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(2013) internet of things ( iot ): a vision, architectural elements, and future directions. futur. gener. comput. syst., 29 (7), 1645–1660. 12 md. muzakkir hussain et al. eai endorsed transactions on smart cities 12 2017 02 2018 | volume 2 | issue 7 | e3 flexible access to patient data through e-consent haridimos kondylakis forth-ics n. plastira 100, vassilika vouton, crete, greece kondylak@ics.forth.gr giorgos flouris forth-ics n. plastira 100, vassilika vouton, crete, greece fgeo@ics.forth.gr irini fundulaki forth-ics n. plastira 100, vassilika vouton, crete, greece fundul@ics.forth.gr vassilis papakonstantinou forth-ics n. plastira 100, vassilika vouton, crete, greece papv@ics.forth.gr manolis tsiknakis forth-ics n. plastira 100, vassilika vouton, crete, greece tsiknaki@ics.forth.gr abstract the advances in healthcare and information technology are shifting more and more the ownership of data from medical institutions and doctors to individual citizens. however, since the medical information of an individual is confidential, the only basis for sharing it, is through prior informed consent which will regulate access to his private healthcare data. this paper highlights challenges investigated in three eu research projects and presents a solution utilizing novel access control mechanisms to ensure the selective exposure of the patients’ sensitive information thereby empowering them. our solution can efficiently support the entire lifecycle of consent such as withdrawal, activation, deletion or update. moreover it responds to complex and different scenarios in which the patient can define complicated and dynamic access control policies at different granularity levels. in this paper we propose a personal health record (phr) system, accessible through desktop and mobile devices, that explores the efficient access regulation to information according to the consent forms provided by the patients. 1. introduction a recent report by the ehealth task force entitled “redesigning health in europe for 2020”1 focuses on how to achieve a vision of affordable, less intrusive and more personalized care, ultimately, increasing the quality of life as well as lowering mortality. such a vision depends on the application of ict, the use of data and requires a radical redesign of health to meet these challenges. the starting point for such a redesign, as identified by the report, is enacting individual ownership of personal health data. the adopted theme is “my data, my decisions”. individuals are 1http://goo.gl/wyizho the owners and controllers of their own health data, they can manage their data with their personal devices, and have the right to make decisions on who can access the data and to be informed about how it will be used. this principle is outlined in eu law but is rarely fully implemented in health systems. in parallel, a second main driver for change is currently taking place under the term “liberate the data”. the secondary use of care data for research, quality assurance and patient safety is still rarely supported and the main barriers to this are the lack of interoperability, common standards and terminologies. large amounts of data are currently stored in different silos within health and social care systems. if this data is released in an appropriate manner respecting the patients’ privacy and used effectively it could transform the way that care is provided. this paper focuses on current research activities within three eu research projects ( imanagecancer2, eureca3, p-medicine4) which are currently trying to enable individuals who are the owners and controllers of their own health data, with the right to make decisions over access to their data and to be informed about how it will be used by third parties. more specifically, the scenario that we envisage is that the patients’ data are stored in some repository, upon which several data consumers (such as doctors, nurses, funding organizations, insurance companies etc.) would require access for different purposes. in such a setting, we explore how to enforce appropriate access control to the patients’ data, given the electronic consent forms that are provided by the patients. at the same time a key requirement is to support the release of the data from different silos throughout the healthcare system and to connect them to the vibrant digital environment for health information which is expected to transform the landscape of healthcare. our approach relies on the rdf data model [3] that promotes the interoperability among e-health systems among others and has the following benefits: 2http://imanagecancer.eu/ 3http://eurecaproject.eu/ 4http://p-medicine.eu/ mobihealth 2015, october 14-16, london, great britain copyright © 2015 icst doi 10.4108/eai.14-10-2015.2261673 • it provides an appropriate access control enforcement mechanism, that essentially filters the data shown to a data consumer, depending on who the consumer is, his current role, the purpose of access, and the access rights imposed by the consent form(s) for the patient’s data as specified by the patient herself. • it allows partial release of personal health information at different granularity levels. the patient can avoid the low-level detail but is also capable of defining fine grained access control to his/her information. • instead of defining explicitly the roles that may have (or not) access to the information, access privilege to entire hierarchies of roles can be used. • it manages the entire lifecycle of consent such as consent withdrawal, activation, and deletion. it handles updates on information efficiently and effectively without requiring each time e-consent redefinition. in addition, it can handle emergency situations and provides an auditing mechanism to ensure proper system usage. providing patients with consent management offers a dual benefit: first of all there is the direct empowerment aspect of controlling one’s own data; and second, it facilitates interaction with patients in order to ask for new consent for a different purpose, both increasing efficiency and involving the patient actively. the rest of this paper is structured as follows: in section 2 we give example healthcare scenarios that show the complexity of the problem. section 3 focuses on the access control approach that we propose for implementing the patient consent forms. in section 4 we present other approaches that try to resolve similar problems and finally section 5 concludes the paper and presents directions for future work. 2. scenarios, challenges and requirements in this section, we give some example scenarios that highlight the complexity of providing selective access to patients’ health record and analyze the challenges that must be addressed. section 3 presents in detail our approach for addressing these challenges. let us consider a patient, named alice, who moves to another city, or decides to visit a new general practitioner (gp). the gp would require access to alice’s medical history, which consists of several medical tests and reports by various healthcare professionals. all required information is stored in alice’s phr account and the gp would greatly benefit if he could have direct access to alice’s data. to perform this, alice must give permission to the doctor to access her medical record through a consent form. according to the eu data protection directive [6] the data subject’s consent shall mean any freely given specific and informed indication of his wishes by which a data subject signifies his agreement to personal data relating to him being processed. furthermore, according to the same directive, the patient’s personal data may only be accessed if she has given her consent for a well-defined access purpose (”least privilege”); data subjects may withdraw their consent at any time (”right to be forgotten”). in addition, the phr system should offer a simple web-based interface that allows her to access her personal records from everywhere, using her computer, or her smartphone, requiring no special software or hardware. this web interface should provide basic functionality for alice to easily create and manage e-consent forms. such consent forms would allow her to give or withdraw (”right to be forgotten”) consent for specific part(s) of the dataset to specific data consumers (users/roles) and for a specific purpose. moreover, alice should be able to monitor the access requests by different data consumers (in this case, the gp), allowing her to review who is requesting the access, the purpose of the request, and which data is requested and accessed and when. this will allow her to easily decide whether access should be granted, and fill in the corresponding e-consent form. management functionalities for the consent forms would be useful in this respect; for example, alice may decide to change a consent form or she may want to withdraw or delete saved consent forms and to re-activate withdrawn consents. in addition, an auditing mechanism should record each access to one’s medical information to ensure that only authorized accesses are actually realized. assume now that alice is updating her phr. new entries should be checked against existing consent forms so that alice can review whether these forms address in a satisfying manner the newly added information. note that an update could cause other items to be accessible due to correlations in the data. for example, assume that alice has created a consent form through which she accepts to release to a research trial her tumor type if and only if the stage of her tumor is greater or equal to t3. after a future treatment, if the cancer is in recession (cancer stage different than t3), the information that was previously accessible for the specified role and purpose should not be accessible anymore. on the other hand, irrelevant data and consent forms should not be affected by a change in the data. the phr system should ensure that the identification of relevant and non-relevant consent forms and data, as well as the access control enforcement should be efficient. now, suppose that, alice has a car accident and sustains minor injuries. the emergency response team reaches the accident location and starts treating alice. for the treatment, the paramedic requires alice’s consent to access her medical history to get information about her allergies and any serious conditions that she already may have and could interfere with the provided emergency treatment. however, alice is unconscious, and cannot provide the required consent. to support this case, alice’s phr should provide a basic medical data set which can be accessed only in emergency situations. so, the necessary access control mechanisms should be in place specifying not only the user or role that should have access to the information, but also the purpose and the situation in which they apply. auditing will be a measure to prevent data misuse in this case. besides defining explicitly that specific roles have access or not to information, hierarchies of roles could also be used. for example, alice could decide that all emergency medical responders (emrs) have access to her information. since a paramedic is a specialization of an emr all paramedics have also access to her information. from the aforementioned examples, it becomes obvious that specifying a set of authorization policies which capture all the details required to enforce correctly an individual’s decisions about consent is a very complex task and should also adhere to the existing legislations. although work has been done to address the problem of automatically resolving conflicts [11], it is not possible to completely automate the decision since in the specific case of the healthcare scenarios humans are also involved. to complicate matters further, contextual information needs to be captured to identify the purpose of the access being requested. serious consequences might arise if the security administrator does not record correctly all these details in the policy specification. and although the social workflows of the scenarios described in this section are not yet fully in place and some aspects require further exploration, we expect that the situation will soon change. to this direction, in this paper, we explore the technological mechanisms that should be fully in place when this happens. 3. access control mechanism annotation models are simple and straightforward, but cause efficiency problems when dealing with dynamic information, because any change in the dataset would affect some of the implicit annotations, but there is no way to know which ones (or how). thus, a change in the dataset would require the re-computation of all annotation labels to make sure that the access labels of all triples are correct. the same is true if a change in the access control policy happens (which could be as simple as the introduction/ withdrawal of a consent form in our scenario, or as complex as a legislation change that causes massive changes in the accessibility rights of medical data). in our setting, both the data itself and the related accessibility information are dynamic, especially given the fact that any patient can at any given time submit (or withdraw) a consent form that changes the access rights to her information. thus, we chose an abstract access control model, described in [9], which has better computational properties in the presence of dynamic information. in this subsection we give a brief introduction to this model, without entering into too many technical details, as the focus of this paper is on the application of the model in a patient-managed medical data repository; further details on the technical aspects can be found in [9]. unlike standard annotation models, abstract access control models are based on the idea that the accessibility of each data item (triple) is not pre-computed; instead, each data item is associated with an access label, which is essentially an abstract algebraic expression that encodes how the label should be computed (rather than the result of this computation). thus, in abstract access control models, the access control annotation is an algebraic expression, rather than a simple access label (value). these algebraic expressions are constructed using abstract tokens and abstract operators. abstract tokens are explicitly assigned to the data items by the knowledge curator, and determine the ”chunks” of data that need protection: two data items with the same token are necessarily protected under the same access control scheme. all triples associated with the same abstract token are assumed to be of the same ”nature”, as far as accessibility is concerned. abstract operators are applied in cases where the accessibility of a triple is somehow related to the accessibility of other triples, e.g., in the case of inference described above. essentially, abstract operators ”compose” access tokens into more complex algebraic expressions [9]. to identify the accessibility of a given triple, we first compute its abstract label using the abstract token(s) explicitly assigned by the curator (if any) along with any implicit labels (resulting from inference). the final algebraic expression does not, in itself, tell us whether a triple is accessible or not for a given user/role and purpose; to determine that, we need to associate each token with a specific (concrete) value, and each abstract operator with a specific (concrete) algebraic operator. this is the done via the concrete policy, which is a set of definitions determining how abstract tokens and operators should be interpreted (i.e., translated into concrete ones), and allows the computation of the actual accessibility of the triple under question. to allow different accessibility schemes, a different concrete policy per user/role and purpose is defined. in our example scenario, when alice submits an e-consent form (either an explicit one, or a default one), behind the scenes, a new concrete policy is defined for the specified user/role and purpose. moreover, alice can also specify the granularity of the information she is sharing; for example, she can allow only the tumor type to be accessed but not more specific details about it. this is done by specifying the appropriate condition under which an algebraic expression is evaluated to an accessible or inaccessible value. when a patient wants to refine the granularity of data access this is handled by simply defining correctly the concrete policy and more specifically the condition under which an algebraic expression is evaluated to an accessible or inaccessible value. this happens without involving the patient in the definition of low-level algebraic expressions. these are automatically generated as the patient selects the necessary information level from the hierarchy of the data currently available. if alice later decides to change or withdraw her consent, such an update would normally result in the costly recomputation of access control annotations for all triples in standard access control enforcement approaches. however, our technique avoids that by using abstract access control models which persist; the only thing that changes is the way that the algebraic expression is interpreted (when the accessibility of the corresponding triple is computed which is done at query time). similarly, when alice adds new data or updates her existing data, there is no need to re-compute the access labels of all triples and recheck all applicable consents; algebraic expressions allows us to determine which triples are affected by the change, and how, essentially limiting re-computation to the part of the data that is indeed affected. 4. related work in the literature, there have been proposed several approaches for regulating access to data. there are role-based, team-based, attribute-based, content-based, scenario-based, situation-aware, context-aware, and context sensitive access control methods (see [14] and [4] for an overview). however, only some of these approaches have been implemented for healthcare scenarios [4]-[15], a few of them consider the problem in distributed and dynamic scenarios [7] whereas a small number of approaches propose models adherent to healthcare standards [14], [2], [5], [8]. in all these systems the notion of e-consent is integrated with the policy decision mechanism. other approaches focus on the notion of e-consent. for instance, russello et al. [12] propose to capture the notion of consent through the use of medical workflows and to integrate it with ponder2 authorization policies. however, there is no automatic mechanism for managing the lifecycle of consent, such as consent withdrawal, activation or deletion. in another work, asghar and russello [1] suggest a mechanism for managing the consent lifecycle. they introduce a notion of very expressive consent represented as a consent policy. however, they assume that a data subject defines solely his/her consent policies; unfortunately, such a solution may not be acceptable because data subjects may not be able to understand low-level policy details. the same limitations with complicated preferences can be also found in the encore (http://www.encore-project.info) uk research project. in a follow-up work of asghar and russello, called actors [10], a goal-driven approach is presented to glue together and manage authorization policies that aim at handling user consent in a specific context. the authors simplify the specification of authorization policies when these are treated as a program sequence towards a specific goal. by using such teleo-reactive programs a security administrator can capture more naturally the security requirements. however, we believe that both administrator and usual user preferences should be considered when dealing with patient data. wuyts et al. [13] use the xaxml policy language. however, the attributes defined a priori may not be sufficient to capture consent since the latter might involve multiple different conditions and exceptions. other approaches [1] try to overcome this issue, by considering consent as an authorization policy; however, other problems appear in these cases. for example, these approaches require users to specify low-level details, a normal user may not be aware of at the time of policy creation. second, there is no automatic mechanism for managing the consent life-cycle. given the fact that patient information is distributed across different sources, it is required that she should manage her different consent forms in a unified and consistent manner. our approach succeeds in collecting all patient data in a phr and then managing his/her consents in a unified consistent manner. 5. conclusions this paper presents an approach for e-consent implemented on top of a phr system. our approach promotes interoperability among different e-health systems and allows partial release of personal health information at different levels of granularity. the rules generated continue to work when new knowledge is entered in the system or to knowledge inferred by existing data. the system efficiently supports different and complex scenarios in which the user can define complicated and dynamic access control policies. for future work we plan to optimize the system implementation and to evaluate its usability with real patients. in addition, we expect more complex use-cases to appear, which might dictate changes in the approach. it becomes obvious that informed consent is an important topic and several challenging issues remain to be investigated in the near future. 6. acknowledgments this work was partially supported by the imanagecancer (h2020-643529), the p-medicine (fp7-270089) and the eureca (fp7-288048) eu projects 7. references [1] r. g. asghar, m.r. flexible and dynamic consent capturing. in inetsec, 2011. [2] b. blobel. trustworthiness in distributed electronic healthcare records basis of shared care. computer security applications conference, 17, 2001. [3] d. booth, c. dowling, e. fry, s. huff, and j. mandel. rdf as a universal healthcare exchange language. semtech panel, 2013. [4] a. ferreira, r. cruz-correia, l. antunes, and d. chadwick. access control: how can it improve patients’ healthcare? studies in health techn. and informatics, 127, 2007. [5] p. hung. towards a privacy access control model for e-healthcare services. in pst, 2005. [6] n. iheanyi. legal and ethical issues in integrating and sharing databases for translational medical research within the eu. in bibe, 2012. [7] j. j. hu and a. weaver. a dynamic, context-aware security infrastructure for distributed healthcare applications. in workshop on pervasive privacy security, privacy, and trust, 2004. [8] w. jih, s. cheng, y. hsu, and t. tsai. context-aware access control on pervasive healthcare. in mam, 2005. [9] v. papakonstantinou, m. michou, i. fundulaki, g. flouris, and g. antoniou. access control for rdf graphs using abstract models. in sacmat, 2012. [10] a. m. rizwan. actors: a goal-driven approach for capturing and managing consent in e-health systems. in policy, 2012. [11] g. russello, c. dong, and n. dulay. authorisation and conflict resolution for hierarchical domains. in policy, 2007. [12] g. russello, c. dong, and n. dulay. consent-based workflows for healthcare management. in policy, 2008. [13] k. wuyts, r. scandariato, g. verhenneman, and w. joosen. integrating patient consent in e-health access control. ijsse, 2(2):1–24, 2011. [14] m. h. yarmand, k. sartipi, and d. g. down. behavior-based access control for distributed healthcare systems. journal of computer security, 21(1):1–39, 2013. [15] l. zhang, g. j. ahn, and b. chu. a role-based delegation framework for healthcare information systems. in sacmat, 2002. evaluation of a self-organized traffic light policy michelle borm technical university eindhoven m.a.m.w.borm@student.tue.nl brendan patch the university of queensland, university of amsterdam b.patch@uq.edu.au thomas taimre the university of queensland t.taimre@uq.edu.au ivo adan technical university eindhoven i.j.b.f.adan@tue.nl abstract this paper presents a preliminary assessment of the potential performance gains of a self-organized traffic light policy developed by lämmer and helbing. a large amount of data was obtained for a complex real-world intersection that serves as an ideal test-bed for comparison of traffic control policies. we provide evidence that a change in policy may drastically decrease average queue lengths and waiting times, suggesting the self-organized policy is a promising approach to the control of traffic intersections deserving further investigation and potentially implementation. categories and subject descriptors i.6.3 [simulation and modelling, applications]; i.6.8 [simulation and modelling, types of simulation] discrete event; g.3 [probability and statistics] queueing theory keywords local control, dynamic control, traffic light policy, traffic network 1. introduction recent increases in computational power and new technologies (e.g. sensors) enable sophisticated traffic light control methodologies. classically, traffic light policies use periodic schedules based on the assumption that the average number of cars flowing through a road approximates the actual flow at any particular time. this assumption may result in suboptimal traffic light policies. recent research has focused on relaxing this assumption to develop traffic light policies that depend on real time traffic patterns (see e.g. [1] and the references therein). in this work we use data from a real-world system to investigate the effectiveness of a self-organized traffic light control policy developed by lämmer and helbing [2], which we refer to as “lämmer’s policy”. the policy uses the number of approaching cars from each direction of traffic flow to an intersection and the number of waiting cars to prioritize directions and determine the duration of green time per direction for each cycle. the policy prioritizes minimization of total waiting times over the reduction of the total number of cars in queue in all traffic directions. we provide evidence that introducing lämmer’s policy to a network of intersections (figure 1) in brisbane (australia) may reduce congestion. currently this intersection exhibits congestion at peak times, and is controlled by the sydney coordinated adaptive traffic system (scats) [3]. the exact specification of scats is unknown to the authors; we will instead use a scats-like policy based on observation in our case study, which is a fixed green times policy. 2. case study: toowong we model the traffic intersection depicted in figure 1 as an open queueing network by viewing cars as customers and the set of traffic lights at intersections as servers. this model is studied computationally through the use of discrete event simulation. for each traffic direction cars are served first12 34 56 7 8 9 10 11 1213 14 1516 17 toowong shopping center library and train station royal exchange hotel a b c figure 1: schematic of our case-study traffic network, the toowong shopping center intersection. come-first-served and the intersection can only serve predefined subsets of the approaching roads at any given time. we take the topology of the intersection to be fixed. arrivals are valuetools 2015, december 14-16, berlin, germany copyright © 2016 icst doi 10.4108/eai.14-12-2015.2262666 0 4 8 12 16 20 24 20 60 100 140 180 time [hours] to ta l q ue ue le ng th current policy self−organized policy (a) expected total queue length for the scats-like and self-organized policy. 0 4 8 12 16 20 240 40 80 120 160 time [hours] q ue ue le ng th ro ad i (b) contribution of each road to the total queue length for the scats-like policy. 4 8 12 16 20 240 10 20 30 40 time [hours]0 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 (c) contribution of each road to the total queue length for the self-organized policy. figure 2: comparison of total queue lengths and road contributions to total queue lengths for both policies in simulation. assumed to follow a nonhomogeneous poisson process. the network consists of three intersections, which all are regulated by traffic lights. the roads (or lanes) are labeled from 1 up to 17, however road 17 has no traffic light and will not be shown in the results. the network is divided over three intersections, a, b, and c. 2.1 results all figures are the result of the average of ten runs of one day. figure 2a shows the total queue length of all roads for the two different policies with a constant service rate of 0.45 cars per second. from this, we see the simulated ex0 4 8 12 16 20 240 100 200 300 400 time [hours] a pp ro ac hi ng c ar s pe r 1 5 m in ut es n1 n2 n3 n4 n5 n6 figure 3: estimated average daily arrival of cars at intersection a. 4 8 12 16 20 240 20 60 100 time [hours] g re en ti m e g ro ad i [m in ] 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 figure 4: simulated green time of each road for the selforganized policy. pected total number of cars in queue in the morning is much higher for the scats-like policy than for the self-organized policy. however, the actual difference would probably be smaller, because we assumed that the scats-like policy uses fixed green times, which is less flexible than the real scats. to examine the differences between the two policies the total queue length of each road for each policy will be compared. figures 2b and 2c show the contribution of each road to the total queue length under the two policies; note that the figures have different scales. the figures show that the scats-like policy has a large queue on road 11; this is not observed for lämmer’s policy in which the queue length is more balanced between the different roads. to get a better understanding of the behavior of lämmer’s policy the minutes of green time for each road during 15 minutes is studied; see figure 4. this figure shows the adjustments of lämmer’s policy to the arrival rate of traffic at intersection a over the course of a typical week day in september 2014. as is shown in figure 3, the number of approaching cars to intersection a is increasing around 4 am, which also shows up in the self-organized policy at this time as a new apportioning of the green times in figure 4. 3. outlook from this preliminary study it can be concluded that lämmer’s policy improves traffic flows and is promising for the future of adaptive traffic control in congested road networks. for further research it would be interesting to investigate what effect unpredictable (adaptive) traffic lights have on drivers; it may cause irritation or confusion when one lane is served twice before another lane is served. 4. acknowledgements we thank yoni nazarathy for initiating this dutch–australian collaboration through partial support of australian research council (arc) grants dp130100156 and de130100291. 5. references [1] j. de gier, t. m. garoni, and o. rojas. traffic flow on realistic road networks with adaptive traffic lights. journal of statistical mechanics: theory and experiment, 2011(04):p04008, 2011. [2] s. lämmer and d. helbing. self-control of traffic lights and vehicle flows in urban road networks. journal of statistical mechanics: theory and experiment, 2008(04):p04019, 2008. [3] a. g. sims and k. dobinson. the sydney coordinated adaptive traffic (scat) system philosophy and benefits. vehicular technology, ieee transactions on, 29(2):130–137, 1980. iot-based hybrid wireless network for tourist boat tracking towards smart cities 1 iot-based hybrid wireless network for tourist boat tracking towards smart cities tuyen phong truong*, phong vu truong and viet quoc tran can tho university, can tho city, vietnam abstract moving and transporting by canoe and boat on rivers and canals is a cultural feature of the mekong delta and plays an important role in the economy and society. however, the management and use of equipment to support the monitoring of waterway transport vehicles in this area has yet to receive adequate investment and attention. given the complicated evolution of the covid-19 epidemic, it is critical to strengthen oversight of inland waterway management, as well as freight and passenger transportation. this paper presents the design and implementation of an iot-based support system for managing and monitoring passenger ships and tourism activities in smart cities. this study proposes a hybrid wireless communication network solution that takes advantage of the strengths of lora and zigbee wireless communication technologies, as well as telecommunication networks, to ensure that the system has a wide operating range of several kilometers, low power consumption, and can be deployed in areas where telecommunications are not available. aside from tracking the journey and managing information about vehicles, drivers, and passengers, the system also aids in the collection of environmental parameters along river routes according to the travel route. an experimental evaluation of the system's operation was carried out for the tourist boat route between two famous tourist sites, ninh kieu key and cai rang floating market in can tho city, vietnam. keywords: environment monitoring, hybrid wireless networks, lora, tourist boat, zigbee. received on 20 october 2022, accepted on 16 february 2023, published on 08 march 2022 copyright © 2023 tuyen phong truong et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v7i1.2789 1. introduction most monitoring applications use a standardized network protocol, such as zigbee2 or lora3, to allow for easy management of network nodes. although zigbee allows for quick data transmission, the data transmission distance is only a few hundred meters. mesh zigbee allows for flexible network routing and is easily adaptable to environmental monitoring applications with many sensors densely deployed in a small area, as well as propagation environments with many mobile obstacles. however, because some applications necessitate a long transmission *corresponding author. email: tptuyen@ctu.edu.vn 2 digi international inc. zigbee wireless mesh networking. available from: https://www.digi.com/solutions/by-technology/zigbee-wireless-standard 3 lora alliance. 2019. a technical overview of lora and lorawan. available from: https://loradevelopers.semtech.com/uploads/documents/files/lora_and_lorawan-a_tech_overview-downloadable.pdf distance from the node to the gateway, zigbee wishes to meet and deploy more devices in the middle to serve as relays of data from the sensor node to the gateway. lora meets this requirement, but it is not the best solution for applications requiring short transmission distances and high speeds. by referencing much successful research, this paper proposes the establishment of a hybrid wireless communication network for the application of a tourist boat tracking support system to capitalize on the strengths of these two communication standards [1-7]. many researchers conducted projects for providing information such as train numbers, train drivers, passengers, and so on, as well as monitoring the operating position of the boats [811]. eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e3 https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:tptuyen@ctu.edu.vn t. p. truong, p. v. truong and v. q. tran 2 the mekong delta has a nearly 28,000-kilometer-long interlaced river system [12]. water freight transport volume exceeds 51.5 million tons per year [13]. river tourism activities such as floating markets, tourist boats, and so on are very developed here and attract a large number of tourists each year. according to statistics, the number of visitors to the mekong delta in 2019 is expected to be 47 million. the total revenue is estimated to be 30 trillion vnd, promoting economic restructuring and onthe-spot exporting [14]. furthermore, this country is affected by the spread of coronavirus 2 (sars-cov-2) and there is no downward trend, causing many economic sectors to freezing. the tourism industry has been severely impacted by the tightening of social distancing and lockdowns as a result of the ongoing spread of the covid19 epidemic. considering the above issues, it is urgent to deploy a monitoring and management system for tourism activities in waterways based on iot technology. faced with the complicated situation of the covid-19 epidemic and the increasing number of tourists returning to vietnam when the country reopens to tourists, the system must be able to query the schedule and provide information about passengers at tourist destinations. as a result, the mekong delta's tourism development is aided by the implementation of safe social distancing. recognizing this demand, conduct research, design, and implementation of a tourist boat management support system with a small, compact size, broad coverage, and reasonable price. applications for smart object tracking in smart cities have received a lot of attention in recent years [15-25]. these can be telemedicine tools, tools for managing landbased and maritime transportation, or even tools for managing population mobility [26-32]. research on applying artificial intelligence to tracking objects, vehicles, and human behaviors, with many outstanding achievements, especially during the time of social distancing due to the recent pandemic, is attracting much attention from the science and technology community, as is the financial investment for research and application development by large corporations [33-46]. this is essential to keep socio-economic activities going, to reduce the covid-19 pandemic outbreak, and to lessen the impact of supply chain disruptions. the hardware in this study is designed to establish a hybrid wireless sensor network capable of performing tasks such as locating the position of passenger ships and collecting environmental parameters (temperature, humidity, pressure, etc.) on board during the voyage. data such as passenger information and train location should be stored in a cloud database and used to query the information in the event of an incident if any. in addition, a mobile application running on the android operating system has been developed to aid in the monitoring and management of cruise ship information. the remainder of this article is structured as follows. session 1 provides an overview of related studies on the use of wireless sensor networks in traffic management, tourism, and environmental monitoring. the characteristics, significance, and current state of waterway traffic in vietnam's mekong delta are also summarized. session 2 focuses on the design and implementation of a hybrid wireless sensor network system for tourist boat monitoring applications that employ both lora and zigbee wireless communication technologies. section 3 describes experiments to assess system performance for the river cruise route between ninh kieu key and cai rang floating market in can tho city, vietnam. section 4 wraps up the article by summarizing the achieved results and outlining future development directions. 2. background 2.1. lora technology lora is a low-power wide-area wireless network (lpwan) protocol developed by semtech. with the use of diverse spreading factors, this technology makes use of a spread-spectrum technique derived from the chirp spread spectrum (css), which enables many devices to operate separately from one another without interfering with the signal. unlike wi-fi and bluetooth, which are used in iot applications with high energy consumption, large bandwidth, and short transmission distances, lora is designed to serve applications with wide coverage, low cost, and energy savings [5]. in lora networks, the factors that affect transmission distance and rate are bandwidth (bw), spreading factor (sf), and coding rate (cr), which are all configurable for different applications. bw controls the frequency amplitude of the chirp signal, and different lora chips can be configured with different bandwidth levels. large bandwidth allows for faster signal encoding and transmission time, but at the expense of a shorter transmission distance. sf specifies the number of bits needed to encode a character (symbol), which ranges from 7 to 12. the larger the sf, the longer the data transmission time and the higher the power consumption, but the error rate is lower and the transmission distance is greater. cr is the number of bits that must be added to a lora data frame for the receiving circuit to recover the incorrect number of data bits and thus recover the transmitted frame data in its entirety. the higher the cr, the more likely it is to receive the correct data; however, the lora chip must send more data, increasing transmission time. lora wireless communication technology was created for network systems with a star topology, in which the gateway plays a central role in controlling and managing all nodes. the wireless star topology network demonstrates flexibility in deployment and system expansion while maintaining high reliability through this connection. because of the nature of the point-to-point connection, the system can easily maintain operation and handle errors when data transmission fails. however, that is also the main drawback of this type of network. if the gateway fails or is damaged, all devices on the network will stop working [47]. eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e3 iot-based hybrid wireless network for tourist boat tracking towards smart cities 3 2.2. zigbee technology some network topologies supported by zigbee include star, mesh, and tree networks. a mesh network, on the other hand, is a typical zigbee network; the nodes are interwoven like a honeycomb so that they can connect and exchange data with one another. if there is interference, the mesh network can reroute the data by “switching” through other nodes in the network until it reaches the destination node. a tree network is a type of mesh network with high coverage and scalability. zigbee includes three types of devices to manage network devices: coordinators (coordinator), routers (router), and terminal devices (enddevice). a zigbee network has only one coordinator who configures the entire network, allowing routers and terminals to connect while consuming a lot of energy due to the inability to sleep while operating. the router inherits all of the network functions of a zigbee node; it can participate in network packet transmission and data routing. there can be many routers in a network. the coordinator and the router control the terminal, which can sleep to save energy. the channel, pan id (personal area network id), and address parameters define the zigbee device's internal network configuration. the pan id allows devices with the same value to communicate with one another. to determine where the data needs to go, each zigbee device has a unique address specified by the manufacturer or configured by the user [48]. 2.3. hybrid networks many wireless communication protocols arose in response to the advancement of iot technology. wireless networks are classified into two types: base-station-based communication networks (bs) and ad hoc wireless networks. base station communication, which involves devices exchanging data with one another via a single base station, has a high level of performance and reliability. however, even if there are many nodes, the response time of this network is not fast because it only has one central operating node. meanwhile, hybrid networks are wireless ad hoc networks that combine multiple network protocols to form a unified network [1-7]. figure 1. structure representation of a hybrid network figure 1 depicts a basic hybrid network structure consisting of a star topology using lora technology and a mesh network using zigbee technology. these two technologies have different advantages and disadvantages, but when combined, the system will inherit all of the advantages that these technologies bring while also improving the disadvantages such as energy consumption, transmission distance, data rate, number of nodes in the network, and so on. since then, the system has demonstrated high reliability and adaptability in a wide range of conditions. however, deploying multiple network forms in the same system increases the complexity of data transmission and reception, as well as the possibility of high collision if transmission time is not properly allocated, resulting in traffic congestion. therefore, the use of hybrid networks necessitates a reasonable design and deployment solution, particularly for the management and regulation of data transmission throughout the network. 3 system design figure 2. general diagram of the proposed hybrid network for tourist boat tracking figure 2 depicts an overview diagram of the tourist boat management support system. the system using a wireless sensor network is a hybrid network; in this network, there are two networks: zigbee (black dashed line) and lora (red dashed line). between the two networks, zigbee and lora are linked together through the 01 coordinator (orange circle). the zigbee network consists of one coordinator and two sensor nodes (green circles) connected in the form of a mesh network. the sensor node collects and encapsulates data and sends it to the coordinator upon request via zigbee links. the lora network is connected in the form of a star network, including the 01 gateway, 02 tracking nodes (violet circles), and the 01 coordinators of the zigbee network. the tracking node works similarly to the sensor node; the coordinator will aggregate data from two sensor nodes and send it to the gateway via lora transmission when required. gateway receives data from the above nodes, then aggregates, checks, calculates, packs, and uploads data sets to a cloud database via an internet connection such as 3g, 4g, and so on. for convenience in monitoring and managing data, the topic of developing mobile applications running on the android operating system this application has permissions to access data, either administrative or user rights. user permissions can only monitor and observe data, while eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e3 t. p. truong, p. v. truong and v. q. tran 4 administrative rights have all the permissions with the application, including user rights and some special permissions like database administration and editing. the names gateway, coordinator, sensor node, and location node mentioned above will be used in describing the design and implementation in the following sections. 3.1. hardware design figure 3. block diagram and communication between coordinator and sensor node the cy8ckit-059 prototyping kit serves as the coordinator's central processor as well as a sensor node in the zigbee network (see figure 3) [49]. temperature, humidity, air pressure, and co2 concentration are read from the sensor and then synthesized, calculated, and packaged in a predetermined format while waiting for a request from the coordinator to send the data to the database via zigbee transmission. after a pre-programmed time, the coordinator will perform a network scan to determine the number of active devices and send a request to those devices to receive data, then check, process, pack, and store the collected data while waiting for the data collection request from the gateway. figure 4. block diagram and communication between the gateway and tracking node in figure 4, the lora network's components include a gateway and tracking nodes with a central processing unit built with the pi zero w4 and pi zero5, respectively. the 4 raspberry pi. raspberry pi zero w. available from: https://www.raspberrypi.com/products/raspberry-pi-zero-w/ 5 raspberry pi. raspberry pi zero. available from: https://www.raspberrypi.com/products/raspberry-pi-zero gateway is the sender of the request, and the remaining components are the executor. when the actuator receives the request, it sends the collected data, including the location (for the tracking nodes) and sensor parameters (for the coordinators), to the gateway via lora transmission. the data will be examined, processed, aggregated, and packaged before being uploaded to a cloud database via an internet connection. in addition, on each node, the device is also equipped with a camera that takes pictures and stores them internally on a memory card for querying when each node fails. figure 5. schematic circuit of the sensor node figure 5 shows a block diagram of a sensor node in a zigbee network created with psoc creator 4.2, which includes functional blocks such as i2c, mhz uart, xbee, xbee uart, and uart [49]. the i2c block is set up to communicate with the bme280 sensor6. the clock 1 clock runs at 1.6 mhz, allowing for a maximum data rate of 100 kbps. mhz uart communicates with the mh-z19b sensor using the configured parameters of 9600 bps and 8-bit data. to avoid continuous system execution due to data polling, the mhz uart block uses the mhz isr interrupter to receive and process data. the uart protocol is used by xbee and xbee uart to communicate with the xbee 3 pro module (115200 bps, 8bit). xbee uart, like the mhz uart block, receives data via the xbee rx int interrupt. the design employs a uart block (9600 bps, 8-bit) configured in the data-only mode for testing and debugging during system development and implementation, which connects to the computer via a com port. 6 bosch sensortec. bme280 combined humidity and pressure sensor. available from: https://www.boschsensortec.com/products/environmental-sensors/humidity-sensorsbme280/ eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e3 iot-based hybrid wireless network for tourist boat tracking towards smart cities 5 figure 6. schematic circuit of coordinator in the zigbee network as can be seen in figure 6, lora_spi operates at 1 mhz, serving spi communication with the lora inair4 module. the lora int pin is an external interrupt source input that is connected to the dio0 pin of the inair4 module, which is responsible for receiving data in the lora transceiver's buffer. timer and timer 2 are added to the system to update the network state and send data collection requests in the zigbee network at 60-second and 10-second intervals, respectively (reprogrammable as needed). the interrupt priority order is reset to match the application of the system. in order to send data to the gateway, the coordinator must aggregate data from the sensor nodes in the zigbee network before requesting to send data, so the xbee_rx_int interrupt has the highest priority for the request as well as the request. receive data from the sensor node. the timer_isr and timer_isr_2 interrupt are set with the next priority for state updates and data collection in the zigbee network. finally, the lora_int interrupt has the lowest priority to receive data requests from the gateway. 3.2 data communication in hybrid network the zigbee and lora hybrid network system has two links: one between the sensor node and the coordinator (zigbee) and another between the gateway or location node and the coordinator (lora). 7 trimble. 2009. copernicus ii gps receiver reference manual for modules with firmware version 1.05. figure 7. (a), (b) tracking node packet and coordinator packet structures in lora network, respectively, (c) sensor node packet structure in zigbee network the requesting role in a wireless network using lora wireless communication technology is the gateway, and the responders are the tracking nodes and the zigbee network coordinator. the gateway sends a request packet to collect data that includes the ids of the network's nodes, then waits for a response packet with the corresponding id from the nodes, then checks, aggregates, and stores the received data. the data-receiving process is complete when the gateway receives the response data from the tracking node and coordinator that were asked to send the data. otherwise, after the predefined timeout period, the gateway skips receiving data at the current node and continues collecting data for the next node. when nodes receive a data request packet from the gateway, they read trimble gps7 values (for tracking nodes) or aggregate data from zigbee network sensor nodes (for the coordinator), encapsulate the packet, and send it via corresponding links. if the sending is successful, the nodes will complete their tasks and enter a waiting state for the next request from the gateway. the coordinator plays a requesting role in a zigbee wireless network, and the corresponding devices are the sensor nodes. the process of requesting data is similar to that of the lora network's gateway, except that the value sensor nodes from the sensors are automatically read by the microcontroller after the pre-programmed time so that when the coordinator sends a data aggregation request, sensor nodes can immediately send prepared measured values. figure 7(a) depicts the lora network packet structure, where the payload includes start, id, and data with lengths of 1 byte, 1 byte, and 21 bytes, respectively. the start is (a) (b) (c) eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e3 t. p. truong, p. v. truong and v. q. tran 6 used to identify the start of the packet. each node in the network has a named identifier (id), which is a unique integer within the network, corresponding to the gateway, coordinator, and two tracking nodes, to ensure that the packet is sent to the proper destination. at the tracking node, data is a 21-byte-long composite data frame to send to the gateway. unlike the tracking nodes, the coordinator's data frame is depicted in figure 7(b). because the system employs a hybrid network, the coordinator's packet will include two addresses, id and xid, where id is the lora network coordinator's identifier name and xid is the zigbee network sensor node's identifier. figure 7(c) depicts the packet structure of a sensor node in a zigbee network. start and xid are defined as lora packets. the data frame contains the parameters read from the sensor as described above and has a total length of 29 bytes. the packets sent to the gateway will be aggregated and packaged, then uploaded to the cloud database. 4. experiment the experimental circuit, after making the pcb board and soldering the components, produces results as shown in figures 8 and figure 9, including full electrical functions as described above. the circuit is powered by two batteries connected in parallel and includes a charging circuit with a micro-usb port. to avoid overheating other components in the circuit, the power block is placed separately. figure 10 shows the position and distance between nodes in an experiment to test the operation of the proposed system, with points numbered 1, 2, and 3 corresponding to the coordinator and two sensor nodes, respectively. the sensor node in position 3 will be located so that the coordinator cannot send the request packet, but node 2 can receive the signal from the coordinator and node 3. the coordinator sends data requests to each sensor node after verifying signal transmission between nodes 1, 2, and 3. it should be noted that nodes 1 and 2 communicate directly. however, because node 1 is too far away to establish a direct connection, packets between nodes 1 and 3 will be relayed by node 2. when transmitting data between the gateway and network nodes in the lora network, the antennas must be arranged reasonably to satisfy the lineof-sight condition. therefore, the location of the antenna must be placed in a high position, avoiding obstacles, for the best data transmission. figure 8. the actual circuitry for the sensor node and the coordinator an android application is being developed with the primary functions of displaying the location of tracking nodes on a map in real-time and managing information about cruise ships, train drivers, and passengers (see figure 11). furthermore, the application includes utilities for monitoring environmental parameters and taking pictures on board while in operation. a strict permission mechanism will be used to store and share the collected data. the information that can be accessed is determined by the account's permissions. only administrators have access to a vehicle and passenger information. ordinary users are only permitted to monitor the ship's position and environmental parameters. figure 9. the photo of the sensor node and coordinator circuitry eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e3 iot-based hybrid wireless network for tourist boat tracking towards smart cities 7 figure 10. (a) location of nodes on the map, (b) zigbee network recorded on xctu software figure 11. android smartphone application for tourist boat management 5. conclusion the design and implementation of a hybrid wireless communication network system to support tourist boat management toward smart city development are presented in this paper. the system proposed in this study has a compact hardware design, a low implementation cost, and stable software that enables the nodes in the sensor network to transmit and receive data stably in the obstacle environment, exploiting the advantages of both zigbee and lora technologies. the system also includes an android application with continuously updated data in real-time to help users easily observe the ship's position and related information. aside from the benefits gained, such as flexibility in system deployment even in areas without telecommunications coverage, the system still has some limitations in value update rate due to the lora communication standard's low transmission speed. research to improve the system's features and data transmission rate is ongoing. references [1] gonzalez n, van den bossche a, val t. hybrid wireless protocols for the internet of things. the 5th international conference on performance evaluation and modeling in wired and wireless networks (pemwn); 22-25 november 2016; paris, france. ieee xplore; 2017. p. 1-4 [2] zhou w, tong z, dong zy, wang y. lora-hybrid: a lorawan based multihop solution for regional microgrid. ieee 4th international conference on computer and communication systems (icccs); 23-25 february 2019; singapore. ieee xplore; 2019. p. 650-654 [3] sant’ana jmds, hoeller a, souza rd, montejo-sanchez s, alves h, noronha-neto m de. hybrid coded replication in lora networks. ieee trans ind informatics. 2020;16(8):5577–85. 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[45] sodhro ah, pirbhulal s, luo z, de albuquerque vhc. towards an optimal resource management for iot based green and sustainable smart cities. j clean prod [internet]. 2019;220:1167–79. available from: https://doi.org/10.1016/j.jclepro.2019.01.188 [46] park e, kim wh, kim sb. tracking tourism and hospitality employees’ real-time perceptions and emotions in an online community during the covid-19 pandemic. curr issues tour [internet]. 2022;25(23):3761–5. available from: https://doi.org/10.1080/13683500.2020.1823336 [47] semtech corporation. 2020. sx1276/77/78/79 137 mhz to 1020 mhz low power long range transceiver. rev. 7, 2020. https://semtech.my.salesforce.com/sfc/p/#e0000000jelg/a/ 2r0000001rbr/6efvzuorrpokffvaf_fkpgp5kzjinyiabq cpqh9qsje [48] digi international inc. digi xbee 3 zigbee rf module. https://www.digi.com/products/embedded-systems/digixbee/rf-modules/2-4-ghz-rf-modules/xbee3-zigbee-3 [49] infineon technologies. 2019. psoc 5lp: cy8c58lp family datasheet. https://www.infineon.com/dgdl/infineonpsoc_5lp_cy8c58lp_family_datasheet_programmabl e_system-on-chip_(psoc_)-datasheet-v15_00en.pdf?fileid=8ac78c8c7d0d8da4017d0ec547013ab9 eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e3 proceedings template word detection and alleviation of driving fatigue based on emg and ems/eeg using wearable sensor hong wang*, zuoqiu qi, rongrong fu, fuwang wang, qingwen yu and chong liu school of mechanical engineering and automation, northeastern university, shenyang, china *hongwang@mail.neu.edu.cn abstract we present a new technique to detect and relieve drivers’ fatigue by using electromyography (emg) and electrical muscle stimulation (ems) respectively, while drivers are driving without any interruption. driving fatigue was detected by emg from the biceps femoris of drivers’ legs through a noncontact acquisition system. the peak factors (fc) of the emg were used as the feature of driving fatigue state. when the threshold of fc is met or exceeded, the abductor pollicis muscle and thumb flexor muscle of drivers’ hands can be stimulated by ems without affecting the normal driving. the experiment results show that the brain fatigue of drivers can be effectively alleviated by this ems while driving. keywords emg, electrical muscle stimulation, eeg, driving fatigue, highway 1. introduction with the development of motor industry and transportation, traffic safety is becoming a serious problem. traffic accidents have caused enormous damage to family and society. according to relative report, driver fatigue is the main cause of traffic accidents [1]. therefore, it is very important to detect driving fatigue and then alleviate this fatigue efficiently. a driver’s physiological state can be measured in various ways. the sensor such as the electromyography (emg) is the popular method for evaluating the muscle tension, and is much less expensive and more portable [2]. the electrical muscle stimulation can enhance the muscle and brain activity [3-4]. eeg is also an electrical change recorded from the brain in relation to an event that occurs either in the external world or within the brain itself. eeg could describe the brain fatigue state [5-9]. could the ems alleviate the driving fatigue? here, we have studied how to detect and relieve driver fatigue by using emg and ems/eeg respectively, while drivers are driving without any interruption. the relationship between the emg and ems/eeg was reported. 2. experiments the whole system is composed of two parts, including the noncontact detection of driving fatigue based on emg and the driving fatigue alleviation by ems. in this study there were two types of the experiments. one type of the experiment was the bus driving on the highway (about 252km) from shenyang (41.93◦ north latitude, 123.43◦ east longitude) to dandong (40.04◦ north latitude, 124.35◦ east longitude), china (fig.1). twenty healthy male subjects (age: 24 ± 2.76) participated in the experiments. the experiment time involved 2-2.5 h per subject. for the noncontact detection of driving fatigue, the surface emg recording electrodes (two pieces of conductive knit fabric of silver-plated nylon with the size of 12 cm × 22 cm and a surface resistivity of < 1ω/sq) were placed on the top surface of car seat cushion, while the reference electrode was located on the left ankle bone. the physiological signals were then acquired from the biceps femoris muscle of each leg without direct contact while the subjects were driving without any interruption. in the driving section, every 10min, 30-s length of data were extracted. other two 30-s length of data were also extracted from post-driving part and post-rest sitting part, respectively. fast independent component analysis (fast ica) and digital filter were utilized to process the original signals. the peak factor of emg can be defined as follow: fc=a/x (1) where a is the amplitude of emg and x is the square root of emg. fc was selected as the characteristic feature to detect fatigue of drivers based on the statistical analysis results given by kolmogorov-smirnov z test. (a) (b) (c) fig.1 bus driving on the highway (about 252km) from shenyang (41.93◦ north latitude, 123.43◦ east longitude) to dandong (40.04◦ north latitude, 124.35◦ east longitude), china; (a) the driving rout, mobihealth 2015, october 14-16, london, great britain copyright © 2015 icst doi 10.4108/eai.14-10-2015.2261628 mailto:hongwang@mail.neu.edu.cn (b) the bus driver, (c) schematic diagram of the noncontact acquisition system for emg. the other type of the experiment was the simulation driving on the driving simulation (fig.2). fifty healthy subjects (twenty males and thirty females, age: 22 ± 2.10) were included in the study. they were recruited within the university and free of medication at the time of the recording session, as well as had no history of neurological diseases. for the driving fatigue alleviation by ems, the two conductive knit fabrics were fixed on the steering wheel as stimulation electrodes (fig.2). when the threshold of fc was met or exceeded, the abductor pollicis muscle and thumb flexor muscle in drivers’ hands can be stimulated by ems without affecting the normal driving. bipolar square wave pulses were as the stimulation current. the pulse amplitudes within the range from 1 to 3 ma were chosen according to the comfort of subjects, and the pulse (0.2 ms width) frequency was set as 1 hz. the effect of the driving fatigue alleviation was evaluated by the features of electroencephalogram (eeg) evoked by ems. meanwhile, a mobile phone can also send out a sound alarm about the driving fatigue. in this work, after a one-hour drive, the abductor pollicis muscle and thumb flexor muscle in the experiment group began to be stimulated by ems without affecting the normal driving. the control group chose normal driving during the experiment. θ subband (4~8hz) and β subband (12~32hz) of eeg from the subjects were selected as the evaluation criterion for judging the effect of the driving fatigue alleviation by using ems. in this experiment, every 12 min, 3-min length of eeg data were extracted. 3. results the signals recorded by two channels from biceps femoris muscles of the subject while driving are shown in fig. 3 (a and b). the signals included emg, electrocardiograph (ecg) and noises. fast ica was used to extract emg (fig. 3d) from the raw data. the peak factors (fc) from the emg show upward trend as the driving time increases (p < 0.05, fig. 4). the effects of driving fatigue alleviation using ems are shown in both fig. 5 and fig. 6. in control group, the relative power spectra of θ subband in eeg present general upward trend while increasing the driving time (fig. 5). in ems group, during the ems section, the relative power spectra of θ subband in eeg show a downward trend until the alert driving state at the beginning of the experiment (fig. 5). there is a significant difference of the relative power spectra between ems group and control group during the ems section (p < 0.05, fig. 5). the relative power spectrum ratio of θ/β is shown in fig. 6. fig.2 schematic diagram of the noncontact detection for driving fatigue by emg and driving fatigue alleviation by ems. fig.3 the two-channel raw signals (a, b) from biceps femoris muscles while driving, ecg (c) and emg (d) separated by fast ica from a and b. fig. 4 the peak factor (fc) (mean ± s.d.) from the emg. abscissa axis shows the calculation time of fc (*post-driving section, ** post-rest sitting data). 4. discussion in this work, the noncontact detection of driving fatigue based on emg and the driving fatigue alleviation by using ems are presented. in order to collect physiological signals from subjects while they were driving without any interruption, the system adopted a type of non-contact electrode based on the capacity coupling theory. recording sensors were placed into the surface of car cushion to collect physiological signals from biceps femoris of each driver, which has made the long-term collection easy to realize. the peak factor (fc) of emg from the biceps femoris muscle can be selected as the characteristic feature to detect fatigue of drivers. the results show that the method proposed can give well performance in distinguishing the normal state and fatigue state. the brain fatigue of drivers can be effectively relieved by the electrical stimulation to the abductor pollicis muscle and thumb flexor muscle. the ems could evoke less slow waves (θ) and more fast waves (β). theta wave from brain should be produced when human is the shallow sleep state or half awaken consciousness or unconscious activity. beta wave from brain should be produced when human is consciousness and nervous tension. the inhibition of theta wave from brain could show that the ems can inhibit the unconscious activity of brain. this means that ems could lead to cognitive enhancement and may help remission of the driver fatigue. our experiment results could have guiding significance on the detection and alleviation of driving fatigue. fig.5 relative power spectrum (mean ± s.d.) of θ subband in eeg as the evaluation of effect of ems. abscissa axis shows the recording time of eeg. fig.6 relative power spectrum ratio θ/β (mean ± s.d.) as the evaluation of effect of ems. abscissa axis shows the recording time of eeg. 5. acknowledgments we gratefully acknowledge the financial support of k. c. wong education foundation and the state key laboratory of process industry automation of china (pal-n201304). 6. references [1] gastaldi m, rossi r and gecchele g. 2014. effects of driver task-related fatigue on driving performance. procedia-social and behavioral sciences. 111 (february 2014): 955-964. doi= http://dx.doi.org/10.1016/j.sbspro.2014.01.130. [2] cronin nj, kumpulainen s, joutjaervi t, finni t and piitulainen h. 2015. spatial variability of muscle activity during human walking: the effects of different emg normalization approaches. neuroscience. 300 (august 2015): 19-28. doi= http://dx.doi.org/10.1016/j.neuroscience.2015.05.003. [3] guzman m, rubin a, cox p, landini f and jackson-menaldi c.2014. neuromuscular electrical stimulation of the cricothyroid muscle in patients with suspected superior laryngeal nerve weakness. journal of voice. 28 (march 2014): 216-225. doi= http://dx.doi.org/10.1016/j.jvoice.2013.09.003. [4] kim yhb, lonergan sm, grubbs jk, cruzen sm, fritchen an, della malva a, marino r and huff-lonergan e. 2013. effect of low voltage electrical stimulation on protein and quality changes in bovine muscles during postmortem aging. meat science. 3 (july 2013): 289-296. doi= http://dx.doi.org/10.1016/j.meatsci.2013.02.013. [5] tokudome w and wang g. 2012. similarity dependency of the change in erp component n1 accompanying with the object recognition learning. international journal of psychophysiology. 83 (january 2012): 102-109. doi= http://dx.doi.org/10.1016/10.1016/j.ijpsycho.2011.10.012. [6] qamir h and ing-marie j. 2007. a multi-modal architecture for intelligent decision making in cars. springer-verlag berlin heidelberg. [7] lange k and schnuerch r. 2014. challenging perceptual tasks require more attention: the influence of task difficulty on the n1 effect of temporal orienting. brain and cognition. 84 (february 2014): 153-163. doi= http://dx.doi.org/10.1016/j.bandc.2013.12.001. [8] yeo mvm, li x, shen k and wilder-smith epv. 2009. can svm be used for automatic eeg detection of drowsiness during car driving? safety science. 47 (january 2009): 115124. doi= http://dx.doi.org/10.1016/j.ssci.2008.01.007. [9] herring s and hallbeck ms. 2007. the effects of distance and height on maximal isometric push and pull strength with reference to manual transmission truck drivers. international journal of industrial ergonomics. 37 (august 2007): 685696. doi= http://dx.doi.org/10.1016/j.ergon.2007.05.003. data fusion and visualization towards city disaster management: lisbon case study 1 data fusion and visualization towards city disaster management: lisbon case study luís b. elvas1*, sandra p. gonçalves1, joão c. ferreira1,3 and ana madureira2,3 1instituto universitário de lisboa (iscte-iul), istar, lisboa, portugal luis.elvas@iscte.pt; sandra_goncalves@iscte-iul.pt ; jcafa@iscte-iul.pt 2instituto superior de engenharia do porto – p.porto, isrc, porto, portugal amd@isep.ipp.pt 3inov inesc inovação—instituto de novas tecnologias, 1000-029 lisbon, portugal abstract introduction: due to the high level of unpredictability and the complexity of the information requirements, disaster management operations are information demanding. emergency response planners should organize response operations efficiently and assign rescue teams to particular catastrophe areas with a high possibility of surviving. making decisions becomes more difficult when the information provided is heterogeneous, out of date, and often fragmented. objectives in this research work a data fusion of different information sources and a data visualization process was applied to provide a big picture about the disruptive events in a city. this high-level knowledge is important for emergency management authorities this holistic process for managing, processing, and analysing the seven vs (volume, velocity, variety, variability, veracity, visualization, and value) in order to generate actionable insights for disaster management. methods: a crisp-dm methodology over smart city-data was applied. the fusion approach was introduced to merge different data sources. results: a set of visual tools in dashboards were produced to support the city municipality management process. visualization of big picture based on different data available is the proposed work. conclusion: through this research, it was verified that there are temporal and spatial patterns of occurrences that affected the city of lisbon, with some types of occurrences having a higher incidence in certain periods of the year, such as floods and collapses that occur when there are high levels of precipitation. on the other hand, it was verified that the downtown area of the city is the most affected area. keywords: disaster management, data mining, smart city, crisp-dm. received on 12 march 2022, accepted on 31 may 2022, published on 06 june 2022 copyright © 2022 luís b. elvas et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i18.1374 1. introduction natural and man-made disasters have become more common across the world, with devastating repercussions reflected in the loss of human life and material/facilities destruction [1]. in reality, 3 751 natural catastrophes such as earthquakes, tsunamis, and floods have been observed globally in the previous ten years, causing $1 658 billion in damages and affecting more than 2 billion people [2]. as a *corresponding author. email: luis.elvas@iscte.pt result, disaster management measures must be implemented in order to reduce the risks. catastrophe management is a comprehensive process with the core aims of avoiding, reducing, responding to, and recovering from disaster impacts in the system. disaster response requires a variety of groups, including governmental, public, and private organizations, as well as several tiers of authority, due to the complexity of major situations [3]. the engagement of several entities in disaster management procedures emphasizes the need of cooperation and coordination systems, since these agencies eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e3 mailto:luis.elvas@iscte.pt mailto:sandra_goncalves@iscte-iul.pt mailto:jcafa@iscte-iul.pt mailto:amd@isep.ipp.pt mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ mailto:luis.elvas@iscte.pt luís b. elvas et al. 2 must communicate, coordinate, and work with one another in order to be effective in a catastrophe situation. some issues, such as a lack of situational awareness or the difficulties in deploying technical solutions for disaster response due to their high costs, may make communication amongst stakeholders' problematics [4]. cities must provide better services and infrastructure to their citizens since population density and the frequency of catastrophes have increased in recent years. in this environment, the smart city (sc) concept emerges as the appropriate answer for overcoming the problems posed by globalization and urbanization [5]. cities aiming to achieve sc status employ digital and networked technology to solve a variety of issues, including enhancing service quality, becoming more sustainable, boosting the local economy, improving quality of life, and ensuring the safety and security of their residents [6]. electronic devices and network infrastructures are combined in a sc to gain high-quality services, and when cities acquire the most up-to-date network infrastructure, smart devices, and sensors, a large quantity of data is collected, referred to as big data (bd). this data may contain a considerable quantity of contextual, geographical, or temporal information [7]. in catastrophe scenarios, bd plays a critical role in disaster management procedures because it is feasible to use data mining (dm) and analytical tools to examine trends and forecast disasters, allowing the creation of appropriate disaster management plans based on historical data [6]. in this sense, the use of bd technologies aids agents in decision-making by allowing them to recognize possible risks and, as a result, establish suitable plans to deal with catastrophic circumstances, so increasing the sc's resilience [2]. the goal of this study is to use a data-driven strategy to extract knowledge regarding catastrophes in the context of a sc to improve the city's management. in order to achieve a descriptive and predictive analysis of data given by the lisbon city hall, which includes information on occurrences that have happened in the city. this research will be conducted using multiple data sources, where from the data collected of the firefighter’s incidences between 2011 and 2018, we will merge datasets containing the average age of the buildings in each parish, the number of populations, and temperature, allowing us to perform a complete and deep descriptive analysis finding patterns between these variables, the types of incidents and the area where they occur. the investigation was carried out in two parts in both situations, with the first phase focusing on a general examination of the reported events and the second phase focusing on occurrences that harmed city structures. 2. state of the art due to the large number of works that have been produced, data-driven disaster management is a new sector that has been evolving [8]. in this regard, using the preferred reporting items for systematic reviews and meta-analyses (prisma) approach [9] and the systematic literature review stages described by okoli and schabram [10], a survey and critical appraisal of the literature related to the chosen issue was conducted. as a result, a systematic search was done on the issue in two electronic databases: scopus [11] and google scholar [12], with the primary goal of identifying and selecting research publications relating to data-driven disaster management research. with this in mind, a question was posed in order to narrow down the work done in this area. the question is as follows: (("disaster management" or "incident management") and ("smart city" or "data analysis" or "data mining" or “big data”)). additionally, a ten-year time window was defined (2010-2020), and the research covered areas such as decision science, computer science, environmental science, and engineering. in terms of document typology, only journal articles, articles, and book chapters were considered. the documents were selected through the abstract and in cases where the information contained in the abstract was not sufficiently complete, the document was consulted in its entirety. the work done in this area covers both natural and man-made disasters. 2.1. natural disasters natural catastrophes are distinguished by the significant influence they have on society, disrupting its regular functioning. in the field of data-driven disaster management, work has been done to develop decision support systems that aid decision-makers in making faster and better-informed judgments based on analytical results. with this in mind, jeong and kim [13] undertook a statistical study of electrical mishaps such as fires and system failures that occurred in korea as a result of climate change. a relationship was established between climate change and electrical-equipment-related incidents in this investigation. in 2017, another research [14] found a correlation between bd systems and disaster management. to examine hydroclimate data, big data analytics tools were applied to a dataset from malaysia's national hydraulic research institute. the purpose was to gain knowledge about climate change and use it to prepare for, reduce, respond to, and recover from natural catastrophes. the use of bd technologies enabled the identification of exceptional precipitation and runoff events, as well as the tracking of drought occurrences. briones-estébanez and ebecken [15] used dm approaches to discover and evaluate trends in the incidence of widespread and intense occurrences, such as floods, river overflows, and landslides, in five ecuadorian cities. other works have been produced to undertake a quantitative study of the eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e3 data fusion and visualization towards city disaster management: lisbon case study 3 damage caused by natural disasters, in addition to works made to assess catastrophes from a spatial and temporal perspective. park et al. [16] used a similar technique to evaluate the potential impacts or effectiveness of damage caused by three types of catastrophes in korea, including typhoons, severe rain, and earthquakes, on water delivery systems. the work done in the field of data-driven disaster management is diverse, since different methodologies are used to make data available to decision-makers. in the work by saha, shekhar, and sadhukhan [17], the analytical results were presented in a more iterative manner by constructing a dashboard to forecast and identify floodprone locations in west bengal, india, utilizing geographic map visualization. other research [18]–[21] created catastrophe susceptibility maps using a mix of dm and gis methodologies. the main goal of these studies is to identify and classify places that are prone to natural catastrophes, with the exception that various dm models are employed in different research projects. 2.2 man-made disasters in the case of man-made disasters, smith et al. [22] conducted study on the use of big data technology for disaster management. they analysed a dataset about fires that happened in australia using the statistical program r, as well as its graphical capabilities. balahadia et al. [23] used the k-means clustering technique to establish patterns and build clusters of fire incidents based on data from fires that happened in manila, philippines. in summary, the purpose was to collect fire event characteristics that might be utilized for risk assessment and risk management in the case of such catastrophes, as well as to aid in the creation of preventative measures. asgary et al [24] attempted to evaluate the geographical and temporal patterns of fire-related occurrences in toronto, canada, using spatiotemporal approaches. the link between the economic, physical, and environmental features of distinct communities and the overall number of fires that occurred in those neighbourhoods was analysed to extract insights. a dm technique based on utilizing bayesian network to model building fires in urban settings was suggested by liu et al. [25]. they examined the potential fire risk based on building design characteristics and environmental variables using historical data of fires in a chinese city between 2014 and 2016. lee et al. [26] used the support vector machine model to investigate the link between building attributes, inhabitants, and fire incidences in sydney in another study aimed at analysing fire trends. finally, in a study by wan, xu, he, and wang [27], bd technologies were used to investigate the distribution and influence factors of harmful gases in the chongqing city's urban underground sewage pipe network, as well as the impact of smart city developments on harmful gases in the urban underground sewage pipe network. in the particular case of lisbon, we can see that author on study [28], aim to increase catastrophe resilience in a smart city, offering an integrated resilience system that connects interrelated vital infrastructures, increasing the total resilience capability of the city by allowing it to plan, adapt, absorb, respond, and recover from disasters by utilizing the linkages between its numerous essential infrastructures. regarding incidents management and data analytics over road accidents, authors on studies [29], [30], recurring to the data fusion of several data sources, achieve conclusions that the accidents are due to human factors, occurring mostly on good weather, and where environmental factors may impact their severity, and noticing that most incident occur on the historical part of the city, where the majority of older buildings are present. in summary, the literature review revealed that the majority of the research in this field was conducted in china, and that the research in this field covers both natural and man-made disasters, with a predominance of flood incident analysis in natural disasters and fire-related incident analysis in man-made disasters. 3. methodology this study analysis has its main focus that on performing a spatial-temporal analysis of occurrences collected in lisbon to extract knowledge about the circumstances in which they occur. the dataset from the fire brigade regiment was subjected to the cross-industry standard process for data mining (crisp-dm) [31] technique to extract insights on disasters that impact the city of lisbon with a focus on buildings. the crisp-dm methodology-based analysis approach began with a business knowledge that allowed the project's scope to be contextualized and understood. in this way, a commercial problem was assessed by looking at several features of the city of lisbon from multiple views, such as demographic, climatic, and educational perspectives. following the completion of the business understanding phase, the following phases were data understanding, data preparation, modelling, and assessment. in order to make the data more valuable and extract more information from it, it was necessary to use data mining techniques such as feature engineering, creating new variables from the ones we have, making the information more valuable, and using data integration and data fusion techniques, where we join several data sources, bringing more richness and knowledge to our dataset and study the firefighter's dataset, given by lisbon city hall, is a csv file that provides information on the incidents that the firemen have reported. the description of the event, the date of the occurrence, the location of the occurrence (i.e., latitude, longitude, and address), and the human (number of people) and material resources (number of vehicles) assigned to each occurrence are all covered by information. eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e3 luís b. elvas et al. 4 there are 135 200 entries (rows in the csv file) and 22 characteristics in the dataset, which spans 2011 to 2018 (columns in the csv file). the columns are all of the type "object," and 13 of them have null values. during the data preparation, it was discovered that the years 2011 and 2012 have much less data than the others, thus those years were omitted from the study so that all years have representative data. in addition, during this phase, cleaning procedures such as column format conversion were used, as well as the selection of relevant features/characteristics for analysis, with attributes that did not add value to the scope of the study being deleted. because the null values could not be replaced by the mean or median because they are geographic coordinates, parishes, and descriptions of occurrences, the records with null values were removed. in this study we have created new attributes from existing attributes, such as the type of street, where from the address of the occurrence, we have created a new variable that gives the information if the accident occurs on an avenue, on a street, on a square, etc. we have also done data fusion between data from multiple source such as ine [32] and ipma [33]. this external data brings valuable information about the weather on the period of the incidents, and demographic and architectural aspects of the city of lisbon. for example, we have merge data that gives us the information of the average age of buildings on each parish, as well as the fraction of structures in need of substantial repairs or that are severely deteriorated. meteorological factors such as average air temperature, relative humidity, average wind speed, and precipitation define the city of lisbon. finally, because there were so many different sorts of occurrences in structures, it was important to categorize them. categorization helps with visual analysis. the "occurrence description" column contains information on the sorts of occurrences, and this property has 25 categories of occurrences established by the firefighters' occurrence management system. the following seven categories were created from the 25 different sorts of occurrences: infrastructures – collapse, infrastructures – floods, infrastructures – landslides, fire, accidents (with machinery or elevators), industrial technology – gas leak, and industrial technology – suspicious situations are all examples of industrial technology (check smoke or check smells). the modelling step begins when the data preparation phase is completed. this phase focuses on gathering information that will assist decision-makers in effectively managing the city in the event of a crisis. the first step in the process is to figure out how the data has changed over time. it was feasible to verify that the number of events recorded in the firefighter's occurrence management system decreased from 2013 to 2018, however this decline was not linear since there were fluctuations over the years. in the year 2013, there were 17 176 incidents, 17 607 occurrences in 2014, 16 717 occurrences in 2015, 15 089 occurrences in 2016, 17 582 occurrences in 2017, and 13 368 occurrences in 2018. firefighters are called to a variety of situations involving a variety of actions. the types of occurrences were evaluated for a better understanding of the actions conducted by firemen, and it was confirmed that the distribution is not balanced among the nine categories of occurrences reported in the dataset. there is an overrepresentation of one category, namely services, which accounts for 45.6 % of all occurrences in the dataset. road cleaning, opening and closing doors, hospital transport, water supply, and preventative services during shows, sports, and patrols are all included in this category. infrastructure and communication route incidents, which include collapses, floods, landslides, falling trees and structures, and falling electric wires, account for 14.7 percent of the total number of occurrences in the dataset. accidents, which include train accidents, road accidents, and accidents involving equipment (elevators, escalators), account for 10.1 percent of all occurrences. activities, with 5.9% of the total occurrences, industrial-technological with 5.1 percent, legal conflicts with 0.5 percent, and civil protection incidents with 0.004 percent of the total occurrences are the categories with the least representation in the dataset. the study focuses on the occurrences that occurred in the buildings of the city of lisbon to classify them geographically and chronologically after a broad examination of the types of occurrences. as indicated in figure 1, the types of incidents that most damage the structures in the city of lisbon are collapses (1816 records) and floods (1778 records), followed by suspicious situations (including verification of odours and smoke) (1478 records). failing structures, with a total of 1234 records, accidents with equipment's with 1166 records, fires in buildings with 926 records, and with equipment with 646 records. other types of incidents, have a representation of 631 records. all have a considerable number of incidents but are less expressive when compared to the previously stated categories. figure 1. number of each type of incident when these events are evaluated over time, i.e., their distribution over years (figure 2), it is confirmed that some occurrences, such as collapses, suspicious circumstances (checking smoke or odors), and floods accidents, occur in higher proportion over time. flooding had a greater prevalence in 2013 and 2014, then declined in the following years. focusing the analysis on each occurrence to extract insights about its pattern of occurrence over the course of the year, it is possible to verify that in the case of the infrastructure categories, i.e., collapses and floods. represented in figure 3, we can see that accidents related with equipment occur most during the middle of the eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e3 data fusion and visualization towards city disaster management: lisbon case study 5 summer until the beginning of the winter, they are evenly distributed throughout the region of lisbon, but with greater concentration in the city centre, with regard to the means of intervention, this type of incident requires an average of 6.2 persons and 1 vehicle. figure 2. types of incidents per year figure 3. equipment incidents regarding collapses, on figure 4, we can see that this occurs more frequently in the autumn and winter months, with maximum values (over 150 records) in the months of october and january. the frequency of recordings of this sort of occurrence declines as the spring and summer months approach, peaking at lower levels in the summer peak. this type of incidents is mainly concentrated on downtown lisbon and on the city centre, with an average of 7.2 people and 1,4 vehicles per intervention. figure 4. collapses concerning falling structures, on figure 5 it is noticeable the difference between the winter and the summer months, where they are considerable higher when we compare january and october with the others. this type of accidents, occur mostly on downtown lisbon. figure 5. falling structures on figure 6, we can see the distribution of fires in buildings. this kind of accidents are the ones taking more personnel, with a number of vehicles that quadruples the average of the other accidents, and the triple number of people. the monthly distribution is almost evenly, with a higher number during the cold months, since it his when people turn on the heaters, being among them fireplaces and braziers. figure 6. fires in buildings in terms of floods, figure 7, shows us that the winter months have a greater incidence, with the greatest values in the months of october to january, whereas the summer months have significantly lower values when compared to the winter months. figure 7. floods on figure 8, we can depict that suspicious situations occur more frequently in the winter months, especially in december, and are comparable to the categories outlined above. eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e3 luís b. elvas et al. 6 figure 8. suspicious situations the first analysis revealed that certain types of occurrences have a higher incidence in specific seasons of the year, such as collapses, floods, and suspicious situations (checking for smoke or odors), which have a higher incidence in the winter/spring months. the impact of weather conditions on the incidence of various types of events affecting the city of lisbon has been confirmed. with this in mind, the impact of precipitation on various forms of occurrence data was examined during four separate periods: when it does not rain, when it rains lightly, when it rains moderately, and when it rains heavily. the development of these four categories allows for the classification of precipitation in terms of quality. an interquartile technique was used for this, and using the interquartile ranges, four datasets with the four precipitation amounts previously indicated could be created. it was feasible to deduce from the study of occurrences according to the four precipitation levels that there are two categories of occurrences, namely floods and collapses, that grow as precipitation levels rise. in the case of floods, it is noticeable from figure 9, the increase in incidence based on precipitation levels is remarkable, since the incidence was 9% when there was light precipitation level, 32% when there was moderate precipitation, 46% when there was heavy rain, and 8% when there were abnormal levels of precipitation. heatmaps were created for the six categories of occurrences that most influence buildings in the city of lisbon, shifting the focus to a study of occurrences from a spatial perspective to verify how occurrences are spread throughout the cities of lisbon. from figure 10, it is possible to see, how the precipitation levels impact certain type of occurrences, where we can see that the highest peak is on flood, preceded by falling structures and collapses. the regional distribution of collapses and flooding is depicted in figure 11. according to the heatmaps presented on figure 11, collapses, which are the type of event that most affects the city of lisbon, have a higher concentration of points in the city's central zone, implying that collapses primarily affect parishes in the city's central area, such as arroios, santo antónio, so vicente, misericórdia, campolide, avenidas novas, penha de frança, and areas of the historical center floods, like collapses, have a larger concentration in the city's downtown region, with the exception that this type of event also occurs with a significant frequency in the north western portion of the city, notably the parishes of benfica and so domingos de benfica. figure 9. heatmaps with the 4 types of precipitation and the number of incidents progression because there is a concentration of events in a certain location of lisbon, it was decided to gain a better understanding of the city by examining characteristics such as the condition of conservation of structures and the average age of buildings in different parishes. it is possible to create a relationship between the spatial concentration of occurrences and the condition of the structures through spatial visualization of buildings that are deteriorated or in need of repair, as well as the visualization of parishes where the oldest buildings are situated. figure 10. number of of people and precipitation by each type of incident from the conclusions drawn from the two heatmaps shown in figure 12, it is clear that areas with older buildings and a higher proportion of degraded buildings in need of repair are more vulnerable to events such as collapses, floods, suspicious situations (check smoke or smells), and gas leaks, which occur in greater numbers in these parts of the city. eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e3 data fusion and visualization towards city disaster management: lisbon case study 7 figure 11. regional distribution of collapses and floods on figure 13 it is also possible to acknowledge that the accidents where the proportion of degraded buildings have more impact are on collapses, followed by floods, suspicious situations (check smoke or smells) and falling structures figure 12. figure a shows the spatial representation of the proportion of buildings that are degraded or in need of major repairs and figure b shows the spatial representation of the average age of the buildings per parish figure 13. number of people/vehicles and proportion of degraded buildings by each type of incident on figure 14 we can see almost the same pattern regarding the age of the building, where we can conclude that the oldest buildings are also the ones in need of major repairs. figure 14. number of people/vehicles and proportion of degraded buildings by each type of incident 4. conclusion big data's importance in disaster management has evolved over time. nowadays, scientists face one of the most daunting tasks of organizing massive amounts of data eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e3 luís b. elvas et al. 8 collected after catastrophes. due to the massive volume of data created by disasters, conventional data storage and processing systems are having difficulty meeting the performance, scalability, and availability requirements of big data. we propose a solution for data integration, aggregation, and visualization must be developed effectively while optimizing the decision-making process, as the quality of judgments made by disaster management authorities is dependent on the quality of accessible information nowadays, visual analytics dashboards for decision support systems for disaster management are critical, as the frequency of such calamities continues to increase. it is very beneficial to make decisions in a time-sensitive situation using a broad variety of quick data. as a result, it is vital to minimize the overhead associated with data integration and visualization in order to facilitate decision making. geographical map visualization may be a useful solution in these situations since it enables the extraction, integration, and presentation of disparate data. the purpose of this article is to construct an analytics dashboard for detecting and visualizing risk zones and susceptible locations organized by different accident types in a city. as a result, city management authorities will have more time to prepare and a more detailed strategy for solving disruptive events and relocating resources in a proper manner. massive amounts of geographical and temporal data are created in a disruptive event in a city from a variety of sources. because charts, tables, and static maps have limited exploratory capabilities, it is not feasible to efficiently interpret these large amounts of data. as a result, choices may be postponed. our approach allows to create a geo-space and time visualization dashboards that can allow management authorities get big picture and prioritizes intervention teams using this knowledge preservation by communicating geospatial data, integrating it with other databases, and creating a dynamic environment that enables quicker decision-making. geovisualization enables more interactive maps, such as the ability to explore various levels of the map, zoom in and out, and modify the map's visual look, which is often shown on a computer monitor. additionally, risk indices may aid in allocating for example post-flood rescue and relief operations to high-risk zones in terms of shelter placement, central depot establishment, logistics, and evacuation strategy. map depiction of these essential places using different colour codes may assist in delineating them and ensuring that they get preferential care. from this study, it is possible to conclude the areas that need more attention, since we can see those events, such as collapses and floods occur mostly in buildings that are very degraded and older. it is also possible to see that these buildings are mainly concentrated in the historic area and downtown of the city, which is also the area where most incidents occur. the suggested system requires various enhancements as part of future study. to make the dashboard more dynamic and engaging, real-time fluctuations in risk levels within a municipality may be integrated. additionally, dynamic dashboard visualization may be accomplished using d3.js, javascript, css, and bootstrap. acknowledgements. this work was supported by eea grants blue growth programme (call #5). project pt-innovation-0045 – fish2fork. abbreviations dm – data mining ai – artificial intelligence sc – smart cities bd – big data ine – instituto nacional de estatística ipma – instituto português do mar e da atmosfera gis spatial and geographical information system crisp-dm cross industry standard process for data mining references [1] j. j. wellington and p. ramesh, “role of internet of things in disaster management,” in 2017 international conference on innovations in information, embedded and communication systems (iciiecs), mar. 2017, pp. 1–4. doi: 10.1109/iciiecs.2017.8275928. 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[27] z. wang, j. xu, x. he, and y. wang, “analysis of spatiotemporal influence patterns of toxic gas monitoring concentrations in an urban drainage network based on iot and gis,” pattern recognit. lett., vol. 138, pp. 237– 246, 2020, doi: 10.1016/j.patrec.2020.07.022. [28] l. b. elvas, b. m. mataloto, a. l. martins, and j. c. ferreira, “disaster management in smart cities,” smart cities, vol. 4, no. 2, art. no. 2, jun. 2021, doi: 10.3390/smartcities4020042. [29] j. mesquitela, l. b. elvas, j. c. ferreira, and l. nunes, “data analytics process over road accidents data—a case study of lisbon city,” isprs int. j. geo-inf., vol. 11, no. 2, art. no. 2, feb. 2022, doi: 10.3390/ijgi11020143. [30] l. b. elvas, c. f. marreiros, j. m. dinis, m. c. pereira, a. l. martins, and j. c. ferreira, “data-driven approach for incident management in a smart city,” appl. sci., vol. 10, no. 22, art. no. 22, jan. 2020, doi: 10.3390/app10228281. [31] “[pdf] crisp-dm: towards a standard process modell for data mining | semantic scholar.” https://www.semanticscholar.org/paper/crisp-dm%3atowards-a-standard-process-modell-for-wirthhipp/48b9293cfd4297f855867ca278f7069abc6a9c24 (accessed aug. 27, 2021). [32] “portal do ine.” https://www.ine.pt/xportal/xmain?xpid=ine&xpgid=ine_ inst_legislacao&xlang=pt (accessed may 04, 2021). [33] “ipma serviços.” https://www.ipma.pt/pt/produtoseservicos/index.jsp?page =dados.xml (accessed may 04, 2021). eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e3 this is a title 1 cycling intellectualization in smart cities i.v. makarova, k.a. shubenkova* and a.d. boyko kazan federal university, pr-t syuyumbike, 10a, naberezhnye chelny, russia abstract intellectualization is the basis for managing smart cities. this involves infrastructure development and design of vehicles equipped with intelligent modules, which provide the control ability. along with it, the transition to “green”, safe and sustainable modes of transport, such as bicycle, should be realized. the widespread use of environmentally friendly bicycles is constrained by a number of reasons. the first is the absence of models designed for physically untrained people and the second is that almost half of all deaths on the world’s roads are among pedestrians and cyclists. we propose to solve these problems in two ways: development of an information system for bicycle infrastructure planning and modelling and creating control system of smart bike with adaptive electric drive that turns on when it’s necessary. functional requirements for the proposed control system, its algorithm and the conceptual scheme of interaction between system’s modules are presented in the article. keywords: smart city, intellectualization, control system, smart bike, sensors, controllers, internet of things, transport system copyright © makarova et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.20-12-2017.153498 1. introduction despite the increasing level of urban mobility worldwide, access to places, activities and services has become increasingly difficult. owing to urban sprawl – the horizontal, low-density growth of cities over vast areas – distances between functional destinations such as workplaces, schools, hospitals, administration offices, or shopping amenities have become longer, leading to a growing dependency on private motorized transport and other car-centered mobility. consequently, widespread congestion and traffic gridlock have now become the norm in many cities, impacting urban life through negative externalities such as pollution, noise stress, and accidents. thereby, the government has now realized the need for cities that can cope with the challenges of urban living and also be magnets for investment. this can be developed through environmental sustainable solutions combined with a full use of the possibilities, which are given by the digitalization of the society. this means enabling the technology to gather data, which can be used by the technology itself in order to adapt to the most sustainable *corresponding author. email:ksenia.shubenkova@gmail.com and smart behaviour. enabling the technology to communicate, to share the gathered data with people or other technologies, to borrow relevant data from elsewhere and to make the technology multifunctional – all of this provides solutions not only to one, but to multiple problems [1]. the smart city concept can be defined as a model of the city development, which creates a surplus of resources through the use of information and communication technologies combined with sustainable and environmentally friendly multiple solutions. it emphasizes the need to improve the level of mobility and connectedness through collaboration and open source knowledge on all levels of the society [2]. one of the main ways to create a smart city is smart transportation systems’ implementation, which is in line with the united nations sustainable development goals and the transition to a green economy. as far as transport starts to be one of the main sources to produce air pollution, emissions of greenhouse gases, noise as well as one of the main reasons of the consumption of nonrestorable resources, household inconveniences caused, for example, by the neighborhood with a highway, etc. [3], the number of adherents of transition to a green economy is growing. they eai endorsed transactions smart cities research article received on 12 august 2017; accepted on 12 november 2017; published on 20 december 2017 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e5 http://creativecommons.org/licenses/by/3.0/ i. v. makarova, k. a. shubenkova and a. d. boyko 2 initiate the development of strategies and policy documents on sustainable development of the urban transportation systems. transition to a smart transport involves the development of appropriate infrastructure, which will ensure the rational management of transportation system, as well as the intellectualization of vehicles, which can provide a sustainable urban mobility. 2. ensuring sustainable mobility in smart cities 2.1. main ways to increase sustainability of the city transport system there are three main ways cities can innovate to make transport more sustainable without increasing journey times:  better land use planning.  making existing transport modes more efficient.  moving towards sustainable transport. part of measures to ensure the sustainability of transport can be planning for urban and suburban centres in accordance with development, providing for a mixed fleet of vehicles and reasonable growth. such principles of urban development will help to reduce dependence on private vehicles and to ensure widespread use of public and non-motorized transport for short trips and for regular commuting into the city from the suburbs [4]. the unep report [5] states that in order to achieve economic goals and objectives of sustainable transport development and integrated planning of its development and regulation system load, you need to switch to fuels with lower carbon content and to implement a more extensive electrification of transport. safe public transport systems are increasingly viewed as an important tool for safe increase of mobility of the population, especially in urban areas suffering from growing traffic congestion. in many cities with high income the policy of reducing the use of personal motor transport is particularly emphasized through investment in the development of public transport networks. [6]. according to the global status report on road safety 2015 [3], moving towards more sustainable modes of transport (such as cycling and public transport) has positive effects if associated road safety impacts have been well managed. these include increased physical activity, reduced emissions and noise levels, reduced congestion and more pleasant cities. moreover, measures to promote safe public transport and non-motorized means of transport are also in line with other global moves to fight obesity and reduce noncommunicable diseases (such as heart disease, diabetes) [7]. 2.2. benefits of using bicycles as a travel mode and examples of their implementation international experience shows that countries have a choice when it comes to the development of the pattern of motorization. rather than opting for a pattern of high use of private vehicles (as the one in the united states or australia), cities have the possibility of a more balanced approach (as in europe) or select what was labeled by uitp as the most efficient pattern (tokyo, amsterdam, hong kong, madrid). this pattern has the smallest role for private motorized vehicles in meeting demand for transport and the highest share of public transport, walking and biking [8]. considering the fact, that the world community has set an objective to reduce the levels of greenhouse gases (first of all carbon dioxide) by 50 % by 2050 [4], bicycles get an additional advantage, as they do not produce co2 emissions. furthermore, bicycling makes efficient use of roadway capacity and reduces congestion. the advantages of cycling include cheap infrastructure requirements and improvements in public health. bicycle pathways, lanes and parking require less space than their automobile counterparts. cycling has direct health benefits. it is an aerobic exercise that can minimize the risk of muscle and ligament injury, lower blood pressure and reduce the risk of heart disease) [9]. moreover, in urban areas, cycling can sometimes prove to be faster than other transport modes and also allows cyclists to avoid traffic jams. cycling caters for the mobility needs of considerable numbers of urban dwellers in developing country cities, especially in asia. problem of the environmental pollution is a major issue in china with its notoriously poor air quality in large cities. probably, this was the main reason of china’s bicycle development [10]. in 2014 lanzhou (northwest china) was praised for integration asia's second-largest bus rapid transit system with a bike share system (14,000 docks planned), bike parking, and greenways [11]. bike share system is also implemented in such cities as beijing, zhuzhou, shanghai, wuhan and hangzhou [12], where the popularity of this mode of transport is also provided by the widespread introduction of electric bicycles that help physically untrained people to overcome steep climbs and long distances, that’s why an increasing number of people choose non-motorized transport as a travel mode. in india, household bicycle ownership rates are high in cities such as delhi (38 per cent), ahmedabad (54 per cent) and chandigarh (63 per cent). this is reflected in the relatively higher modal share of cycling in these cities – delhi (12 per cent) and ahmedabad (14 per cent). in some asian countries with relatively higher incomes, however, the modal share of cycling is much lower, such as in singapore (1.6 per cent of work trips), 9 the republic of korea (1.2 per cent) 10 and hong kong sar (0.5 per cent) [7]. in african cities, cycling plays a comparatively limited role, accounting for less than 3 per cent of total trips in capital cities such as bamako (mali), dakar (senegal), harare (zimbabwe), nairobi (kenya) and niamey (niger). to promote bicycling in african city of dar-es-salaam nkurunziza et al. in their study [13] identified the bicycling policies. also, technology can be used not only to make better eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e5 cycling intellectualization in smart cities 3 cars but also better cycle paths, such as the proposed airconditioned bike path in qatar [14]. such cities of latin america as bogotá, medellín, león, buenos aries, rio de janeiro, são paulo, several chilean cities, etc. have included to their local and national strategies of transportation system’s development such projects as introduction of permanent bike paths and bike lanes, safe parking and transit stations [15]. rio de janeiro launched a bike-sharing program, it has now 600 bicycles and 200 km of bike routes. são paulo launched the establishment of bicycle lanes more than 120 km long. after the general street protests that occurred in brazil in june 2013, triggered by the high cost and low quality of public transport, the municipality of são paulo announced a further 310 km of bike routes, which are actually signaled lanes shared with cars [16]. in car dependent countries such as australia, canada and the usa the proportion of non-motorized trips up less than an eighth of daily trips. however, it is shown in [9] that investment in well-designed bicycle facilities (pathways, lanes and roadways) in the largest canadian cities (for example, calgary) has resulted in modest shifts in the commuting patterns to work in favor of cycling. bicycle ownership in western europe, especially in the netherlands, germany and denmark, is very high and if cycling in the us is mostly for recreational and fitness purposes, in europe it is a key means of movement for utilitarian purposes. today, in some european cities – such as amsterdam or copenhagen – two-thirds of all road users are cyclists. in other words, it is perfectly feasible for a majority in a metropolis to ride a bike and not travel by car. not everybody can ride a bike every day, however, which is why the bike should not be seen as a competitor, but rather as complementary to public transport. especially on the way to and from work, there is a lot of potential: in london around 2.5 percent of all commutes to work are by bike, in berlin 13 percent, in munich 15 percent and in copenhagen and amsterdam a whopping 36 and 37 percent respectively. such a high percentage of number of trips to work or education by bicycles in copenhagen is provided by the fact that the priority strategy of politicians is development of bicycles infrastructure as a way to create more friendly city living condition [17]. for example, there are currently several programmes in europe testing the introduction of cargo bikes, including the eu-funded project cyclelogistics. while the main focus of the project has been on urban freight and courier services, it has also included shop-by-bike campaigns. indeed, private cargo bike use is a reality in cities like copenhagen [14, 18]. the so-called “carbon footprint” of copenhagen is one of the smallest in the world (it is less than two tonnes per capita). but there is even more ambitious goal to become neutral on emissions has been set in its development strategy. to do this there have been set very strict targets in order to follow energy efficiency standards, “green” construction and “green” energy. the city government approved the project of equipping bicycles with special sensors that report on the level of pollution and traffic congestion in real time [19]. in portugal as inductor of desired modal shifts (changing behavior from using cars to other modes such as cycling) local administration of the city lagoa conducted an experiment. each employee of the city council travelling from home to work (and vice versa) and able to shift their usual mode of transport (car) to other options (walking, cycling with public bicycles, electric bicycles, car sharing) could be offered “money vouchers” (equivalent carbon credits to their reduced co2 emissions). these vouchers were redeemable in several public facilities and cultural events [20]. there is an effective bike sharing system in london, barcelona and paris. to use such a system you need to register and receive a personalized card. in barcelona, you can rent a bike and leave it at any convenient point of the city, because there are bicycle parkings all over the major streets. an extensive network of bicycle paths and cycling facilities and services are also contributes to the development of this system. essential infrastructure in a city with the size and traffic volume of moscow includes a strategy for secure parking lots and allowing for alternative ownership structures through a bike share system. moscow decided to introduce various parking facilities appropriate for short-term and longterm parking and to introduce a bike sharing system similar to schemes in london, barcelona and paris [21]. thus, in the last decade non-motorized transport has become a symbol of sustainable urban transport all over the world. 2.3. factors that prevent bicycle transport usage and the ways to increase its attractiveness cycling is a low-polluting and a low-cost transportation alternative and can be an important mean for getting to destinations that are not serviced by transit [22]. however, a considerable proportion of commuters choose to use other means of transport. even in the netherlands, which has a bicycle-friendly infrastructure and where cycling has a positive image, many people choose not to cycle in situations when cycling would be a highly appropriate transport mode. the impediments to bicycling include factors like long trip distances of commuters, harsh weather conditions, greater physical effort, the difficulty of carrying loads while cycling, infrastructure unavailability, a lack of health and environment consciousness among people, extreme traffic conditions that lead to the risk of an accident [23] and, outside urban areas, travelling more slowly than motorized transport. factors such as physical effort and speed also limit the distance that a cyclist can travel [24]. one of the most popular counter-argument about cycling are adverse climatic and natural conditions. however, it is a matter of attitude and priority for cycle paths when clearing snow. this is confirmed by the example of oulu, where a substantial proportion of people commute by bicycle, even when the temperature is below zero in deepest winter. this is ensured by 845 km of routes (4.3m per inhabitant), 98 % of which are maintained throughout winter because main route maintenance priorised over driveways. routes parallel to driveways are separated with a green lane, which also serves as snow build-up space. there are underpasses in most busy eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e5 i. v. makarova, k. a. shubenkova and a. d. boyko 4 crossings and you can reach every place by bike using cycling routes [25]. introducing bicycle lanes is not enough to make a city attuned to cyclists’ needs. thus, despite the investments in london’s cycling infrastructure of about 4 billion dollars over the last 10 years, the proportion of commuting by bicycle has increased from 1.2% to 2.5%. a similar situation is observed in the united states, where more than 15 billion dollars over the last 10 years were invested in development of cycling infrastructure and where commuting by bicycle has increased only from 0.3% to 0.6% during this period. in new york, despite the 300 miles built safe bicycle lanes (which are separated from vehicles and pedestrians) over the last 10 years, commuting by bicycle has increased from 0.6% to 1.1%. a radical change in modal split in favor to bicycle transport is often hampered by considerable distances from centers to the points of passengers’ attraction in metropolitan areas. the diagram below confirms this conclusion (fig. 1). the research of the ways to increase the sustainability of urban transportation system was based on the assumption that population will prefer the cycling as a mode of transport in a case if there is a considerable advantage of its using. figure 1. relation between the number of cycling commutes and the city size one of the most objective methods to study the transport preferences of the population is a questionnaire survey that allows predicting the most likely options of the transportation system development. survey was held in naberezhnye chelny – one of the most young russian cities. linear structure open type with the “classic” functional zoning was laid in the basis of planning organization of the city with a parallel location of industrial and residential areas, suburban recreation zones. in connection with these peculiarities of urban planning, in the case when the destination point is situated on the longitudinal avenue that is parallel to the point of departure) and there is the lack of the lateral routes of public transport in the city, the “last mile” problem exists in naberezhnye chelny [26]. the questionnaire to find out what transport modes are the most popular among population has been developed. 953 respondents, constituting the various target groups, took part in the current survey (table 1) [27]. results of the research show that one of the deterrent constraints of cycling development are psychological factors. they, in turn, may be due to various reasons: from the incertitude of ability to overcome the route due to the individual physical characteristics, to the lack of information about the route characteristics. therefore, the number of people who choose bicycle as a mode of transport can be increased by the expansion of nonmotorized model line-up and the integration of its infrastructure to the city road network system. what is more, cycling facilities and services should be developed. these steps, on the one hand, will help to enhance the attractiveness of bicycles for different groups of population and, on the other hand, will make roads safer and more secure particularly for non-motorized road users who are the most vulnerable. in simplified form, ways to increase the attractiveness of non-motorized transport are shown on the fig. 2. table 1. the results of the sampling survey of population indicator s tu d e n ts w o rk e rs r e ti re e o th e r c a te g o ry t o t a l number of respondents 624 299 16 14 953 number of trips to work or education by public transport 313 109 422 number of trips to work or education by bicycles 50 7 57 number of trips to work or education by cars 163 133 296 number of trips to work or education by foot 98 50 148 number of bikes in the personal property 313 86 2 6 407 the number of drivers who are ready to transfer to bicycles, if there are: bikeways 127 56 0 0 183 bicycles parkings 129 46 0 0 175 bike hire system 75 28 0 0 103 the possibility to take the bike in buses or trams 76 21 0 0 97 e-bikes 78 22 0 0 100 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e5 5 figure 2. measures to implement for moving towards non-motorized modes of transport thus, as the experience shows, one of the deterrent constraints of cycling development are psychological factors. they, in turn, may be due to various reasons: from the incertitude of ability to overcome the route due to the individual physical characteristics, to the lack of information about the route characteristics. the case of copenhagen proved that the attractiveness of cycling may be increased by the expansion of bicycles model line-up for different population groups and different use cases. in copenhagen you can rent not only conventional bikes, but also such models as [28]: (i) the velomobile. it protects against wind, rain and drizzle and it is best suited for long distances over 20 km and runs well on wide bicycle lanes outside the city and that several users would cycle more in the rain if they had a similar cycle. (ii) the cargobike. it is good to transport children and to carry things and products and it is best suited for short distances below 10 km. (iii) the recumbent. it is comfortable and good to ride on, especially in headwind and it lends itself well to long distances over 20 km. (iv) the electric-assist long john. it is good to carry cargo and children and it motivates to cycle more and drive less. it is fast, practical, fun and effortless to get around within the city. (v) the electric bicycle. it is fun and different to drive on. the electric slide is a good help, especially uphill and against wind. bicycle infrastructure planning should include the creation of bike parkings, bike sheds and bikeways as well as it should be taken into account the terrain and the structure of population, who want to use the bike to get around the city. despite a fast growing literature on the bike lanes design [29], the problem of terrain identification and topographic conditions modelling is still actual. the most common method of bicycle wayfinding is the shortest path method. as far as bicycle routing is not always possible to avoid hilly terrain, bike-lifts and electric drives creation can solve the problem of overcoming steep climbs. in contrast to the electric scooter or motorcycle, e-bike may be driven by pedals. at this time electric drive is off and accumulator is charging. e-bikes are generally different from ordinary bicycle because of three additional components presence such as an electric motor, a storage battery and a battery controller. despite of electric drive presence electric bike is used approximately the same as an ordinary bicycle and in most countries does not require the driving license or license plate presence. electric bicycle is suitable as a vehicle for a wide range of people with the different level of abilities, as it is easy to dose physical training. there is a number of disadvantages of electric bicycle that, makes it difficult to use. they are: significant weight (from 20 to 50 kg or more) and the corresponding inertia; lack of power reserve on the drive (rarely more than 25-50 km); long battery charging (usually at least 2-6 hours); short service life of lead-acid and lithium-ion storage batteries; the high cost of the final product and its use compared with an ordinary bicycle cost and use (from 2 to 10 times). one of the ways to ensure sustainable mobility in smart cities is the combination the possibilities of bicycles and electric transport. when using the electric transport, movement parameters are set by the motor and the cyclist determines the trajectory, e.g. performs control. bicycle movement is provided by the cyclist who sets the driving speed and the movement direction. this means that cyclist manages the process of cycling. but at the same time cycling parameters depend on environmental conditions (including the terrain characteristics), natural conditions, time of day and the physical condition of cyclist. in short, cycling parameters depend on everything that affects the possibility of bicycle movement. if we consider the “bicycle” system, its functioning is provided by the interaction of such subsystems as “external environment” – “infrastructure” – “bicycle” – “cyclist”. to ensure the traffic safety it is necessary to eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e5 cycling intellectualization in smart cities i. v. makarova, k. a. shubenkova and a. d. boyko 6 establish a control system that implements the interaction of subsystems for rational functioning of the system. the most common variant of the bicycle’s electric drive is the one that is based on commutatorless dc motor. the engine is build in the wheel instead of the hub. any of the wheels can be the motor-wheel, as well as the both on them at the same time. motor-wheel is often sold in assembled form. the power of the motor is determined for the fully loaded electric bicycles, with a maximum speed and without traction of the cyclist. the pattern of the forces acting on the bike when it moves is used for this purpose. thus, to ensure the maximum speed of movement up to 50 km/h, for a person weighing 70 kg the motor wheel of 1000w would be enough. to simplify installation, the wheel designed for the bicycle’s front fork weighing 6,5kg has been selected. this wheel can withstand loads of up to 135kg. an example of such bicycle with the dc motor can be the copenhagen wheel, that is a rear bicycle that has an in-built electric motor, battery, and in-built computer. 3. cycling intellectualization: our proposed solution 3.1. smart bike control system idea of the smart bike control realization electric bicycles are controlled by cycling computer (controller), which is supposed to: supply amperage from the battery to the electric motor in accordance with the user’s settings; show residual battery charge on the indicator; determine the rotation / stop of pedals; limit the maximum speed of the bicycle movement in order to save energy; keep constant speed (cruise control); charge the battery while braking. at the same time there is a variety of velosimulators that are belong to the group of cardiovascular machines which are equipped to control the physical condition of a user. at the same time the main indicator to diagnose critical state is a pulse rate. as far as the parameters of the bicycle motion are influenced by both condition of the cyclist and the parameters of the environment, the rational management should be based on monitoring, analysis and on taking into account all these factors. today there are two types of systems that are used to analyse bicycle’s characteristics and motion parameters. they are:  cycling computers – electronic devices to measure the speed and daily run of bicycle as well as such additional parameters as average speed, travel time, full speed, transmission (for multi-speed bikes), running time, temperature, atmosphere pressure, cadence (pedal rotation frequency), etc.  smart phones applications – applications that duplicate functionality of cycling computer, except the ability to monitor the transmission and cadence, use built-in phone sensors such as gps, accelerometer, barometer. figure 3. the elements that are included in the developed module to implement the smart bike control idea it is necessary to design a system that combines cycling computer, motorized wheel (it is the type of a driving wheel, complicated mechanism, that combines the wheel itself, electric motor, power gear and braking system) and velosimulator that control the physical condition of a user. sensors readings are transmitted into the controller for the further analysis. in critical cases (when the physical cyclist’s condition is bad) the system sends the request to turn on the electric drive and after receiving the confirmation from user electric drive control is transferred to the controller. thus, if to equip the bicycle with the universal module, which includes a pulse sensor, a controller and other components that are shown in fig. 3, and to manage it in accordance with the selected program installed on smartphone it will help to increase the attractiveness of cycling among untrained population. functional requirements for the proposed control system existed sensors and controllers can be used to implement the concept of smart bike. to determine the condition of the cyclist and monitoring travel times are required:  means of identification of a cyclist – to set his physical characteristics in the rest condition;  pulse sensor – to determine heart rate;  timer – to determine the travel time, setting training modes. to measure the parameters of the bicycle will be required:  gyroscope/accelerometer – to determine the position of the bicycle in the area;  speedometer – to determine the travel speed;  sensor of used chain sprockets;  gps sensor – for positioning, location and route setting. module which determines the weather conditions on the route and transmits it to a smart phone is required to determine the parameters of the environment. while designing bicycle control system it should be taken into account that the control system is completely autonomous, and the interference from the cyclist is impossible so it may be unsafe for the rider. that’s why the principle of feedback between control system and a person should be implemented with the help of notifications. in this eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e5 7 way, the possibility of accidents in electric drive of bicycle false alarm cases will be excluded. smart bike control system algorithm bicycle movement is provided by the cyclist who sets the driving speed and the movement direction. this means that cyclist manages the process of cycling. but at the same time cycling parameters depend on environmental conditions (including the terrain characteristics), natural conditions, time of day and the physical condition of cyclist. in short, cycling parameters depend on everything that affects the possibility of bicycle movement. if we consider the “bicycle” system, its functioning is provided by the interaction of such subsystems as “external environment” – “infrastructure” – “bicycle” – “cyclist”. to ensure the traffic safety it is necessary to establish a control system that implements the interaction of subsystems for rational functioning of the system. while designing bicycle control system the list of monitored events and the system’s responses was made (table 2). there is a smart bike control system’s data analysis algorithm in fig. 4. table 2. list of the bicycle control system’s events № event response 1 cyclist’s pulse > otp display of overcoming the training threshold, offer to turn on the electric drive 2 road gradient > 15° (uphill) display of the warning of an uphill, offer to turn on the electric drive 3 cyclist’s pulse > otp + 50 display of excessive overcoming the training threshold, offer to stop for the rest or to continue motion completely on electric drive 4 road gradient < – 15° (downhill) display of the warning of a downhill, electric drive's switching-off, accumulator charging 5 non-stop travelling during more than 1 hour display of the need to have a rest, offer to stop for the rest or to turn on the electric drive 6 non-stop travelling during more than 2 hours display of excessive overcoming the training threshold, offer to stop for the rest or to continue motion completely on electric drive 7 travel speed < 15km/h during 15 seconds display of the offer to turn on the electric drive figure 4. data analysis algorithm eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e5 cycling intellectualization in smart cities 8 table 3 shows one of the system’s operation scripts. if cyclist’s pulse value is higher than otp and the movement speed is less than average speed that is usual for this person, the screen displays an offer to turn on the electric drive. when the pulse value and the speed become normal, the electric drive switches off. to determine the cyclist’s optimal heart rate the formula (1) may be used: otp = (220 – a – prc) ∙ k + prc , (1) where otp – optimal training pulse; prc – pulse in the rest condition; a – cyclist’s age; k – coefficient which varies depending on the cyclist's preparation level: k = 0.6 for the freshman, k = 0.65 for a man of medium-level training, k = 0.7 for well-trained person. thus, the developed system analyses sensors’ readings and if the cyclist, bicycle and the environment parameters’ values are not normal, it warns the cyclist about the critical case, as well as offers problems’ solutions. implementation of the system and test results conceptual scheme of interaction between modules of the developed system is shown in fig. 5. primary data collection is realized using mpu6050 digital sensors and pulse sensor (plug-and-play heart-rate sensor for arduino). these sensors being located on the steering wheel, on the frame and wheels, as well as on cyclist, are connected to the arduino board via the i2c protocol. the motor-wheel mxus xf39-30h is controlled by arduino board. connection to the smartphone is realized via the bluetooth wireless connection. sensors’ readings are transmitted to the smartphone and then they come into the microsoft sql server database for storage and processing. the application for smartphones, which was developed with the help of android studio in java, allows to manage the sensor system according to the above-described algorithm and taking into account the state of the external environment as well as the cyclist itself. the prototype of the developed system was tested in laboratory conditions. the results of tests confirmed that even physically weak category of people can use a bike equipped with the developed system as a mode of transport. moreover, the widespread introduction of bicycles with such system allows to improve the road safety by avoiding accidents, which are related to fatigue or to a sharp deterioration of cyclists’ physical appearance. an example of the control realization scheme is shown in fig. 6. table 3. an example of the script «turn on the electric drive» step event action user’s condition data collecting (pulse, weight, height, location tracking, etc.) 1 the value of the pulse exceeded otp, movement speed is less than 15 km/h comparison of these indicators with the “reference” values for a particular cyclist. display of overcoming the training threshold. offer to turn on the electric drive. 2 heart rate decrease electric drive's switching-off, resetting the display of overcoming the training threshold figure 5. conceptual model of interaction between system’s modules eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e5 i. v. makarova, k. a. shubenkova and a. d. boyko 9 figure 6. control realization scheme the uniqueness of our smart bike because of the wheel is build in the bicycle’s front fork, it is still possible to use this system for multi-speed bicycles. high power offers to go up the hill keeping the same movement speed as well as to use such a system if the cyclist is carrying heavy cargo. since the system monitors user’s physical condition, the battery consumption is considerably reduced. the help by turning on the motor operates only in the case of cyclist fatigue. this allows increasing the maximum distance that untrained person can cycle with this system. the principal difference between our smart bike and copenhagen wheel (tab. 4) [30]:  a bicycle equipped with a copenhagen wheel in effect becomes a pedelec, i.e. a bicycle in which the electric motor assists the rider when necessary but only when they are actively pedalling.  in our smart bike engine helps the driver only in critical conditions. 3.2. software solution for the choice of the optimal route we offer a software solution for the choice of the optimal route. route rating should be made from the standpoint of safety, convenience and comfort of passage. to compare the routes the multi-criteria evaluation that considers particular qualities of cyclist and his preferences is used. the user can set the start and finish points, evaluation criteria and preferences. for the calculation it is also necessary to know such cyclist’s parameters as age of cyclist, height, weight and level of physical abilities. possible routes are evaluated on the base of this information. to do this a matrix of the given route options is constructed and then the overall routes’ performance indicators are calculated. the value of the route safety indicator is calculated with provision for correction factors that depend on the physical condition and characteristics of the cyclist. the user receives information about the best possible option. the total length of the route serves to bring the settings (fig. 7). to implement the proposed idea an application for smartphones integrated with gis system was developed (fig. 8). to verify a route the user enters or indicates on the map his location and the destination point. table 4. comparison of the copenhagen wheel and our smart bike p o w e r (w ) s p e e d , m a x ( k m / h ) d is ta n s , m a x (k m ) b a tt e ry c a p a c it y (v ) w h e e l d ia m e te r (i n .) w e ig h t, k g copenhagen wheel 350 32 50 48 26 6 our smart bike 1000 50 48 26 6,5 the command “find a path” displays a list of routes, sorted by the travel time. after that user can proceed to the route’s safety checking. after checking and calculating the overall safety performance indicators, the user can perform the route preview. when scaling up or selecting the particular area on the route map, routes are highlighted in different colours: the dangerous areas are marked in red and yellow. these are such areas as non-signalized pedestrian crossings, lack of bike lanes, etc. safe areas are marked in green. thus, the colour of the route depends on the total points of safety, from the green (that is the safest) to red (that is the most dangerous). the application provides the ability to assess the route by the user. he can leave a feedback and indicate problems on the route by attaching photos or text description. such feedbacks will help to respond quickly to problems. city authorities and road services, getting information on the state of the infrastructure, may take appropriate action to solve the identified problems. the application has been tested on the site of the road network of naberezhnye chelny city. for the correct work of the application it is necessary to administrate database with actual information (such as the state and characteristics of the road network, infrastructure parameters, etc.) that should be updated when changes occur. using the mobile application to find the safest route will not only plan the trip, but also will reduce the possibility of accidents. besides, such an application would be useful for the bicycle infrastructure development as it will help to assess how the appearance of new attraction points influence to the cyclists’ travel demand and which of the routes are need to be improved. moreover, data analysis on the accidents with cyclists will help to identify problem areas and inform cyclists about the need of increased attention to unsafe areas when they are planning trips. implementation of the intelligent active cyclist assistance systems, the design of correct and safe bicycle paths, their timely maintenance and repair will help to reduce accidents with cyclists. however, even when implementing intelligent system for the choice of the optimal route it is not always possible to avoid hilly terrain. bike-lifts and electric drives creation can solve the problem of overcoming steep climbs. in contrast to the electric scooter or motorcycle, e-bike may be driven by pedals. at this time, electric drive is off and accumulator is charging. eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e5 cycling intellectualization in smart cities 10 figure 7. algorithm for the choice of the optimal route according to safety criteria a) b) c) figure 8. a) selecting the destination point; b) route options; c) route previewing smart bikes with adaptive electric drive that is turns on when it is necessary, can help even physically untrained people to overcome steep climbs and long distances without overload. accumulator charges from the household electric system. bicycles provide comparable speeds in urban environments and at the same time energy and economic costs of the one person relocation by bicycle are much more lower than by any other mode of transport, including public transport. 4. conclusions despite the obvious advantages of using bicycles for short distances there are still a lot of obstacles to the widespread use of the bicycles as an alternative travel mode. some of these problems can be solved by two ways: choosing the most secure cycle route’s option in developing bicycle infrastructure and creating smart bike with adaptive electric drive that is turns on when it is necessary. this cannot be realized without cycling intellectualization. we propose the concept of an information system for bicycle infrastructure planning and modeling and the concept of the smart bike control system developed to help the cyclist in situations when the values of his physical condition as well as parameters of environment are critical. to control the cyclist’s condition in real time is proposed to use a set of sensors, information transmitting means and the data processing program. successful development of smart city need complex solutions. implementation of the intelligent active cyclist assistance system, the software solution for the bicycle infrastructure planning, the smart bike control system, development of bicycles infrastructure and its integration into the public transport system will contribute to use of bicycle and public transport, as well as will help to increase the road safety, especially for the cyclists. this will create for citizens a comfortable urban environment, as well as obtain a synergistic effect that will contribute to the sustainable development of smart city. moreover, the experience of developed countries shows that this clean and efficient kind of transportation also contributes to the economy's development. besides, the health and longevity also benefits from cycling. as it is seen in denmark, the cycling benefits are seven times greater than the cost of accidents, in money value the total health impact is worth 230 million euro. references [1] green capacity, http://greencapacity.ru/ru/ information/smart-cities [2] smart cities preliminary report 2014, http://www.iso.org/iso/smart_cities_report-jtc1.pdf eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e5 i. v. makarova, k. a. shubenkova and a. d. boyko 11 [3] global status report on road safety 2015, http://www.who.int/violence_injury_prevention/road_sa fety_status/2015/gsrrs2015_summary_en_final.pdf [4] share the road: investment in walking and cycling road infrastructure, http://www.unep.org/transport/ sharetheroad/pdf/str_globalreport2010.pdf [5] global “green” new deal. policy brief, http://www.unep.org/pdf/ggnd_final_report.pdf [6] makarova, i., shubenkova, 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(2014) the case of moscow. in roethig, m., efimenko, d. [ed.], changing urban traffic and the role of bicycles: russian and int. experiences. (moscow: friedrich-ebert-stiftung), 72-79. [22] handy, s. and xing, y. (2011) factors correlated with bicycle commuting: a study in six small us cities. international journal of sustainable transportation 5: 91-110. [23] verma, m., rahul, t., reddy, p. et al. (2016) the factors influencing bicycling in the bangalore city. transportation research, part a, 89: 29-40. [24] heinen, e., wee, b. and maat, k. (2010) commuting by bicycle: an overview of the literature. transport reviews 30: 59-96. [25] tahkola, p. (2014) the case of oulu. in roethig, m., efimenko, d. [ed.], changing urban traffic and the role of bicycles: russian and int. experiences. (moscow: friedrich-ebert-stiftung), 29-43. [26] makarova, i., shubenkova, k. and gabsalikhova, l. 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(2017) development of sustainable transport in smart cities. in proceedings of 3rd ieee int. forum on research and technologies for society and industry, rtsi 2017, modena, italy, september 2017, http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber= 8065922 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 6 | e5 cycling intellectualization in smart cities http://city-smart.ru/info/125.html untitled a distributed platform for big data analysis in smart cities: combining intelligent transportation systems and socioeconomic data for montevideo, uruguay sergio nesmachnow*, sebastián baña*, and renzo massobrio* universidad de la república, herrera y reissig 565, montevideo, uruguay abstract this article proposes a platform for distributed big data analysis in the context of smart cities. extracting useful mobility information from large volumes of data is crucial to improve decision-making processes in smart cities. this article introduces a framework for mobility analysis in smart cities combining intelligent transportation systems and socioeconomic data for the city of montevideo, uruguay. the efficiency of the proposed system is analyzed over a distributed computing infrastructure, demonstrating that the system scales properly for processing large volumes of data for both off-line and on-line scenarios. applications of the proposed platform and case studies using real data are presented, as examples of the valuable information that can be offered to both citizens and authorities. the proposed model for big data processing can also be extended to allow using other distributed (e.g. grid, cloud, fog, edge) computing infrastructures. received on 9 may 2017; accepted on 18 october 2017; published on 19 december 2017 keywords: smart cities, big data, distributed computing, intelligent transportation systems copyright © 2017 sergio nesmachnow, sebastián baña, and renzo massobrio, licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/ licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/xx.x.x.xx 1. introduction the paradigm of smart cities proposes taking advantage of information and communication technologies to improve the quality and efficiency of urban services [1]. modern cities are increasingly becoming sensed and instrumented. the embedding of smart devices into traditional city’s physical systems together with the emergence of citizen sensors, such as mobile phones or "internet of things" (iot) enabled domestic appliances, are generating vast volumes of data that present unprecedented opportunities as well as challenges. extracting insights from these datasets is crucial to improve decision-making processes in cities and to achieve quality improvements and increase efficiency. a particular sub-domain of a smart city are intelligent transportation systems (its). its integrate synergistic technologies, computational intelligence, and engineering concepts to develop and improve transportation. its are aimed at providing innovative ∗corresponding authors. email: {sergion,sbana,renzom}@fing.edu.uy services for transport and traffic management, with the main goals of improving transportation safety and mobility, and also enhancing productivity [2]. its allow gathering large volumes of data by taking advantage of different sensors and devices present in current vehicles and infrastructure (e.g., passenger counters, gps devices, video cameras, ticket vending machines). the development of smart tools that use data gathered by its infrastructure and vehicles has risen in the past years. these tools rely on efficient and accurate data processing (even in realtime), which poses an interesting challenge from the technological perspective. furthermore, these data can be combined with more traditional data sources, such as sociodemographic data that are regularly and systematically collected by government agencies. this combined approach enables characterizing areas of study and helps answering questions such us how equitably the services delivered are and whether certain communities are disproportionally affected by poor service quality. 1 eai endorsed transactions smart cities research article eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e http://creativecommons.org/licenses/by/3.0/ http://creativecommons.org/licenses/by/3.0/ mailto:<\protect \t1\textbraceleft sergion,sbana,renzom\protect \t1\textbraceright @fing.edu.uy> sergio nesmachnow, sebastián baña, and renzo massobrio in this context, applying distributed parallel computing and machine learning techniques arise as a promising methodology for processing large volumes of data to be used in services and applications targeting both citizens and authorities alike. this article proposes a framework for capturing and processing large volumes of data in the context of the resolution of urban problems. the problems involve processing large volumes of data to offer real-time information to both citizens and transport authorities. the proposed framework applies distributed computing and big data processing methods to provide an easy-to-use and efficient solution. furthermore, two specific applications of the proposed framework are presented: i) an analysis of public transportation in the city of montevideo, uruguay that uses historical geo-spatial data from vehicles combined with socioeconomic datasets to withdraw conclusions regarding both quality and equability of the services provided [3] and ii) the estimation of od matrices and mobility patterns for the same public transportation system [4]. an experimental analysis is also reported, studying the computational efficiency of the proposed framework over both applications. the main results demonstrate the efficiency and scalability of the proposed solution, making it a promising approach to be applied in modern smart cities. the article is organized as follows. section 2 describes the generic framework proposed for distributed big data analysis for its in the context of the smart city paradigm and introduces the two practical applications studied. a review of related works on distributed big data analysis for smart city applications is presented in section 3. section 4 describes the proposed model for the distributed processing and the specific details of the implementations for the two cases of study. the computational efficiency analysis is reported in section 5. two examples of studies that generate useful statistics for the population are described in section 6. finally, section 7 presents the conclusions and main lines of future work. 2. big data processing for intelligent transportation systems in smart cities this section describes two problems related to processing big data from transportation systems applying distributed computing and computational intelligence. 2.1. analysis of the quality and equability of the public transportation system the first case of study proposes combining multiple datasets and performing both off-line and on-line analysis of gps data and ticket sales information from buses. given a big set of data collected fromgps devices and ticket sales machines in buses, the problem consists in computing a number of important statistical values to assess the quality of the public transportation system. the information collected by gps devices includes the time and the coordinates for each bus, reported with a frequency of 10–30 seconds, which allow determining the location of each bus within its route. on the other hand, information from ticket sales include the information of every ticket sold on each bus, including: gps coordinates, time, and date the ticket was sold. additionally, if the ticket was paid for using a smartcard, a unique identifier for the smartcard is included, which allow identifying trips done by the same passenger. the main goal of the data processing is to compute relevant metrics to assess the efficiency of the public transport system in montevideo, for example: i) study the impact of traffic conditions and external events on the efficiency of the transportation system ii) analyze the real time that each bus takes to reach some important locations in the city (known as control points or remarkable locations), and iii) compute statistical information about the arriving times and delays for each remarkable location (maximum, minimum, mean, mean absolute deviation, and standard deviation). the information to report must be classified and properly organized in order to determine accurate values according to different days of the week and hours in the day, which imply different passenger demands and different traffic mobility patterns. the benefits of the proposed system for processing gps data are twofold: i) from the point of view of the users, the system provides useful information from both historical data (monthly, yearly) and the current status of the public transportation in the city, to aid with mobility decisions (e.g., choose a certain bus, move to a different bus stop, consider using a different line); this information can be obtained via intelligent ubiquitous software applications and websites; ii) from the point of view of the city administration, the statistical information gathered is useful for planning long-term modifications in the bus routes and frequencies, and also to address specific bottleneck situations in the public transportation system. a diagram of the proposed system for processing gps data in its is presented in figure 1. the system is based on buses that upload data reporting their current location (collected by the on-board gps unit) and ticket sales to a server in the cloud and a historical database which includes transport and socioeconomic data from the past. the server applies big data and streaming analysis techniques to the collected data. the results are then exposed to be consumed by mobile applications for end-users and also to be used in monitoring applications for the city government authorities. 2 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e a distributed platform for big data analysis in smart cities: combining its and socioeconomic data for montevideo, uruguay figure 1. architecture of the proposed big data analysis for its the proposed system is useful for performing both on-line and off-line data processing. on the one hand, on-line processing applying streaming analysis techniques fulfill requirements in areas such as early warning and detection, and adaptive routing. the offline analysis on the other hand, is focused on the study of trends that allow identifying mobility patterns and creating predictive models that can be later used in conjunction with sensors that stream data in real-time. on-line its metrics and statistics. in order to handle real-time data the system relies on a streaming processing engine that enables high throughput ingestion from multiple concurrent data sources. the proposed system presents a set of expressive abstractions, such as join, map, and reduce, to apply transformations to the data before persisting the results into the storage subsystem. off-line its metrics and statistics. for computing offline mobility metrics, the proposed system demands processing a large volume of data in short execution time, thus leading to a classic big data problem. the system applies a parallel/distributed model to perform the data processing, where the original data is split and distributed across different nodes to be processed independently. finally, all the partial results from each node are combined to return the final solution. these data are used to derive metrics of the quality of the service that are later merged with socioeconomic indicators that are used to characterize the geographic area served by each particular bus line. the number of bus lines, bus stops, and individual trips completed every day constitute a relatively large volume of data. thus, even some of the more traditional geo-spatial analysis problems, such as deriving the isochrones for a fixed walking distance from the stops on a bus line–to determine the bus coverage area– becomes a candidate problem for parallel processing. the social dimension of the analysis is crucial to evaluate whether the services are being fairly delivered, benefiting all the communities irrespectively from their location or demographic characteristics. the concept of “equitable city” is one of the promises of urban informatics and it is a central premise of our research. 2.2. estimation of mobility patterns: demand and od matrices the second case of study proposes applying distributed computing techniques for estimating mobility patterns and od matrices in its systems. origin-destination (od) matrices are often not directly observable, because sensors or gps gadgets in buses typically measure traffic characteristics, which are the result of not just origin-destination trips, but also of route choices and traffic operations for certain types of vehicles. thus, od matrices have to be estimated from any available relevant data. this is a relevant problem for implementing the smart city paradigm. determining themobility patterns to build demand and od matrices is crucial for analyzing the transportation system and the resulting outcomes are key for city administrators to take decisions that improve the quality of the system. the main challenge faced when generating demand and od matrices using data from gps and tickets sales is that in almost every system passengers validate their smart cards when they board but not when they alight a bus. therefore, while the origin of each trip is known with certainty, it is necessary to estimate the destination. furthermore, in many urban systems some passengers do not use smart cards to pay for their ticket and pay cash instead. therefore, there are sale records which do not provide information that can be used to track several trips made by the same passenger. specific big data processing algorithms must be designed and implemented for each case. data from gps, sensors, and traffic gadgets are gathered in many formats and with different granularity. this case of study focuses on a study of the its for the city of montevideo, uruguay. thus, the types of input data considered in this article for origin-destination estimation and prediction are the gps and ticket sales data from buses in montevideo. the city government in montevideo introduced in 2010 an urban mobility plan to redesign and modernize urban transport in the city [5]. under this plan, the metropolitan transport system (sistema de transporte metropolitano, stm) was created, with the 3 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e sergio nesmachnow, sebastián baña, and renzo massobrio goal of integrating the different components of the public transportation system together. one of the first improvements in stm was to include gps devices on buses and allow passengers to pay for tickets using a smart card (stm card). additionally, the complex system of fares was simplified to allow only two different type of tickets: i) "one hour" tickets, allowing up to 1 transfer within an hour of boarding the first bus; ii) "two hours" tickets, allowing unlimited transfers within 2 hours from the moment the ticket is purchased. however, it is not compulsory to use the stm card to buy bus tickets, as passengersmay paywith cash directly to the driver. in this case, the ticket is only valid for that trip and no transfers are allowed. using historical information gathered in the context of the stm transport system of montevideo, the goal is to accurately estimate demand and od matrices from gps bus location and ticket sales data (considering tickets payed with and without smartcards). the computed results are of significant value to the authorities at the city government in montevideo, since there is a serious lack of mobility information. traditional methods (e.g., passenger surveys, visual inspections) have proven to be expensive and offer outdated information while novel methods based on information already gathered by the its have not been explored by the city authorities yet. 3. related works this section reviews the related works on the two main topics addressed in this article: applying big data and distributed computing approaches for processing data from its and related systems in the context of smart cities, and processing data to estimate demand and od matrices. 3.1. distributed computing for processing traffic data several articles have proposed applying distributed computing approaches to process large volumes of traffic data with diverse goals. a brief review of related works is presented next. the advantages of using big data analysis for social transportation have been studied in a thorough manner in the general review of the field by zheng et al. [6]. the authors analyzed using several sources of information, including vehicle mobility (e.g., gps coordinates, speed data), pedestrian mobility (e.g., gps andwifi signals frommobile devices), incident reports, social networking (e.g., textual posts, address), and web logs (e.g., user identification, comments). in the review, the advantages and limitations of using each source of data are discussed. several other novel ideas to improve public transportation and implement the its paradigm are also reviewed, including applying crowdsourcing techniques for collecting and analyzing real-time or near real-time traffic information, and using databased agents for driver assistance and analyzing human behavior. a conclusion on how to integrate all the previous concepts in a data-driven social transportation system that improves traffic safety and efficiency is also presented. several other computational intelligence techniques have been recently applied to process its data in order to help the decision-making processes in smart cities. oh et al. [7] proposed a sequential search strategy for traffic state prediction combining a vehicle detection system and the k nearest neighbors (knn) nonparametric method for classification. an experimental evaluation was performed considering data from the performance measurement system from state route 78 highway in california, united states. the results demonstrated that the proposed system outperformed a traditional knn approach, computing significantly more accurate results while maintaining good efficiency and stability properties. shi and abdel-aty [8] applied the random forest data mining technique and bayesian inference to process large volumes of data from a microwave vehicle detection system, with the main goal of identifying the contributing factors to crashes in realtime. rear-end crashes were studied because they have a straightforward relation with congestion. the experimental evaluation of the proposed computational intelligence approachwas performed considering traffic data from state routes 408, 417, and 528 in central florida, united states. a reliability model was also included in the analysis. the main results allowed the authors to conclude that peak hour, higher volume and lower speed at upstream locations, and high congestion index at downstream detection point significantly increased the probability of crashes. ahn et al. [9] applied support vector regression (svr) and a bayesian classifier for building a real-time traffic flow prediction system. data preparation and noise filtering are applied to raw data, and a traffic flow model is proposed using a bayesian framework. regression techniques are used to model the timespace dependencies and relationships between roads. the performance of the proposed method is studied on traffic data from gyeongbu, the seoul-busan corridor in south korea. the experimental results showed that the approach using svr-based estimation outperformed a traditional linear regression methods in terms of accuracy. chen et al. [10] proposed a model that aims to efficiently predict traffic speed on a given location using historical data from various sources including its data, weather conditions, and special events taking place in the city. to obtain accurate results the prediction model needs to be re-trained frequently in order to incorporate the most up-to-date data. the prediction model 4 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e a distributed platform for big data analysis in smart cities: combining its and socioeconomic data for montevideo, uruguay combines the knn algorithm with a gaussian process regression. additionally, the results are computed using a map-reduce model, implemented under the hadoop framework. the experimental evaluation was performed over a real scenario using data from the research data exchange, a platform for its data sharing. the data used corresponds to the interstate 5 higway in san diego, california, united states. the processed information included speed, flow, and occupancy data measured using loop-detectors on the road, as well as visibility data taken from weather stations nearby. experimental results showed that the proposed method was able to accurately predict traffic speed with an average forecasting error smaller that 2 miles per hour. additionally, a 69% improvement on the execution time was achieved by using the hadoop framework in a cluster infrastructure when compared with a sequential algorithm running in a single machine. xia et al. [11] studied the real-time short-term traffic flow forecasting problem. to solve the problem, the authors proposed using the k nearest neighbor algorithm in a distributed environment, following the map-reduce model implemented over the hadoop framework. the proposed solution considered the spatial-temporal correlation in traffic flow, i.e., current traffic at a certain road segment depends on past traffic (time dimension) and on traffic situation at nearby road segments (spatial dimension). these two factors can be controlled using weights in the proposed algorithm. the experimental analysis was performed using data of trajectories of more than 12000 gps-equipped taxis in the city of beijing, china, during a period of 15 days in november 2012. the first 14 days of data are used as the training set and the last day is used for evaluating the computed results. the proposed algorithm allows reducing the mean absolute percentage error by 8.5% to 11.5% on average over three existing techniques based on the knn algorithm. additionally, a computational efficiency of 0.84 is reported for the best case. 3.2. estimation of demand and od matrices the estimation of demand and od matrices is a wellknown problem in the field of public transportation. this problem has had a renewed interest with the increasing availability of large volumes of data from modern its systems. many articles in the related literature have proposed applying statistical analysis for estimating od matrices and computing several other relevant statistics for its. some approaches applying parallel and distributed computing techniques have also been proposed recently. a review of the main related works is presented next. an analysis of the literature about using smart cards in its was presented by pelletier et al. [12]. the review covered all the details about hardware and software needed for deploying smart card payment solutions in urban transportation systems. in addition, privacy and legal issues that arise when dealing with smart card data were also reviewed. the authors identified the main uses for smart card data, including: longterm planning, service adjustments, and performance indicators of the transportation systems. finally, the review described several examples of smart card data utilization around the world. trépanier et al. [13] proposed a model for estimating the destination for passengers boarding buses with smart cards, following a database programming approach. two hypotheses are considered, which are also commonly used in many related works: i) the origin of a new trip is the destination of the previous one; ii) at the end of the day users return to the origin of their first trip of the day. based on the previous two assumptions, the authors proposed a method to follow the chain of trips of each user in the system. those trips for which chaining is not possible (e.g., only one trip in the day exists for a particular user) are compared with all other trips of the month for the same user, in order to find similar trips with known destination. the experimental evaluation was conducted using real information from the transit authority in gatineau, quebec. two datasets were used, with 378,260 trips from july 2003 and 771,239 trips from october 2003. results showed that a destination estimation was possible for 66% of the trips. it is worth noting that most trips for which its destination could not be estimated with the proposed approach take place during off-peak hours, where more atypical and non-regular trips are performed. considering only peak hours, the percentage of trips with their destination estimated improves to 80%. however, the real estimation accuracy could not be assessed due to lack of a second source of data (e.g., automatic passenger count) for comparison. wang et al. [14] proposed using a trip-chaining method to infer bus passenger origin-destination from smart card transactions and automatic vehicle location (avl) data from london, united kingdom. in the studied scenario, authors needed to estimate both origin and destination of trips. origins are accurately estimated by searching for the timestamp of each smart card transaction in the avl records to determine the bus stop of each trip. to estimate destinations, the authors used a similar methodology to that presented by trépanier et al. [13], chaining trips when possible to infer destinations. results were compared against passenger survey data from transport for london, performed every five to seven years for each bus route and including the number of people boarding and alighting at each bus stop. the analysis show that 5 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e sergio nesmachnow, sebastián baña, and renzo massobrio origins can be estimated for more than 90% of the trips while origin and destinations can be estimated for 57% of all trips. when compared to the survey data, the difference on the estimated destinations were below 4% on the worst case. finally, two practical applications of the results are presented. the first one consists of studying the daily load/flow variation in order to identify locations along each bus route where passenger load is high, as well as underutilized route segments. the second application consists of a transfer time analysis, evaluating the average time that users need to wait for transferring between buses, based on the alighting stop and the avl data. later, munizaga et al. [15] presented a similar approach to the one applied by wang et al. [14] for estimating od matrices in the multimodal transportation system of santiago, chile. the scenario considered in the article by munizaga et al. is more general, because passengers can use their smart cards to pay for tickets at metros, buses, and bus stations. the proposed approach is evaluated using smart card datasets corresponding to two different weeks, with over 35 million transactions each. the origin of the trip is accurately determined for nearly every transaction while the destination and time of alighting was estimated for over 80% of the transactions. after extrapolating and post-processing, an estimated od matrix is presented to visualize the computed results at any given timespace disaggregation. several proposals have applied distributed computing approaches to process large volumes of traffic data, but fewworks have dealt with the estimation of demand or od matrices. early works on this topic applied distributing computing to gather traffic data. sun [16] proposed a client-server model developed in corba for collecting traffic counts in real time, to be used for dynamic origin/destination demand estimation. the proposed solution included a corba client to extract data from the traffic network, and a corba server for storing data in a centralized repository. all the information is processed to be later used in dynamic traffic assignment strategies for the traffic network studied, for the estimation of dynamic od matrices applying a bi-level optimization framework. toole et al. [17] propose combining data from many sources (call records from mobile phones, census, and surveys) to infer od matrices. the authors combine several existing algorithms to generate od matrices, assign trips to specific routes, and to compute quality metrics on road usage. furthermore, a web application is introduced to give simple visualizations of the computed information. the authors mention that computations are performed in parallel, but no parallel model is described and no performance metrics are reported. also using mobile phone data, mellegård [18] proposed a hadoop implementation to generate od matrices while keeping users’ privacy. however, the experimental analysis is done on synthetic data due to the difficulties on getting real data from mobile operators. furthermore, no performancemetrics are reported, so the advantages of the hadoop implementation are unclear. huang et al. [19] proposed a methodology for offline/online calibration of dynamic traffic assignment systems via distributed gradient calculations. an adaptive network decomposition framework is introduced for parallel computation of traffic network metrics and for parallel simulation, in order to accelerate the computations. parallel origin-destination demand estimation is proposed as a line for future work, in order to deal with large-scale traffic networks with huge number of origin-destination pairs and sensors. 3.3. summary of related works the analysis of related works allows identifying several proposals for using big data analysis and computational intelligence methods to design improved its. computational intelligence and learning methods, such as regression, knn and bayesian inference are often used to identify traffic patterns and provide useful information for planning. however, there are few works focusing on improving the public transportation systems, especially considering the point of view of the users. furthermore, few works focus in the social justice, integrating into the analysis elements that provide insights into the fairness with which the service is delivered. in this context, the research reported in this article contributes with specific proposals to monitor and improve the public bus transportation, considering the point of view of both users and administrators, and providing objective metrics on the way communities receive these services in montevideo, uruguay. regarding demand and od matrices estimation, previous works have addressed the problem of estimating the destination by chaining trips where the destination is assumed to be near the origin of the following trip. this article expands that idea by also considering transfers between bus lines, which are specifically recorded in the smart card dataset used for the evaluation. additionally, a novel parallel/distributed computing approach is presented to allow solving a more complex and computingintensive data processing problem. to the best of our knowledge, this approach has not been previously proposed in the related literature. 4. the proposed solutions this section describes the proposed solutions for the two cases of study presented in this article. 6 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e a distributed platform for big data analysis in smart cities: combining its and socioeconomic data for montevideo, uruguay 4.1. processing gps data from buses in the public transport system historical gps data processing applying map-reduce over hadoop. the first case of study is described next. design and architecture. the problem is decomposed in two sub-problems: i) pre-processing to properly prepare the data to be used as input for the processing in the next phase, and ii) statistics computation of the public transportation system, using a parallel/distributed approach. a master-slave parallel model is used to define and organize the control hierarchy and processing. figure 2 presents a conceptual diagram of the proposed solution. in the pre-processing phase, the master process filters the data, in order to select only that information that is useful to compute the statistics. the data processing phase applies a data-parallel domain decomposition strategy for parallelization. the available data resulting from the previous phase is split in chunks to be handled by several processing elements. the master process is in charge of controlling and monitoring the system, performing the data partition, and sending the chunks to slaves for processing. each slave process receives a subset of the data from the master. the group of slaves processes collaborate in the data processing, generating the expected statistical results. each slave performs the same task; therefore, a single program multiple data (spmd) parallel model is applied. strategy for data processing: algorithmic description. the input data correspond to the gps coordinates sent by each bus in operation, during each trip. every line in the input file represents a new position recorded by a certain bus during a given route and for a particular instant of time. the first column of the input file corresponds to the line number field, which is a unique identifier for each bus line. in turn, to distinguish different trips of the same bus line, the file has a self-generated numeric field, trip number, which identifies a particular trip of a bus line. pre-processing stage. the main goal of pre-processing is data preparation. this stage filters input data that do not contain useful information for the statistics to compute, and classifies/orders useful records. three phases are identified in the data preparation: 1. filtering: this phase filters the data according to the statistics to compute. two relevant cases are considered: i) discarding non-useful data, as the raw data files include information that is not useful for computing the statistics (e.g., when computing the accuracy of buses to reach remarkable locations, the gps information not related to remarkable locations is not needed); and ii) filtering ranges, as the system receives a time range as input and computes the statistic for that given period of time. 2. time range characterization: this phase identifies the time range of the timestamp of each record containing useful information. since traffic patterns vary significantly throughout the day, the time range must be taken into account when computing and analyzing the generated statistics. to compute and analyze statistics generated due to variations of this factor determines very different values to be processed. we consider three time ranges in the study: • morning, between 04:00 and 12:00, • afternoon, between 12:01 and 20:00, and • night, between 20:01 and 4:00. figure 2. conceptual diagram of the proposed application 7 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e sergio nesmachnow, sebastián baña, and renzo massobrio 3. sorting: this phase sorts the records according to the bus line identification (line number) and the timestamp of the record. these fields define a processing key, which is needed to compute the time differences between the departing time for each bus and the time taken to reach each of the remarkable locations. after applying the pre-processing stage, the master process has the filtered data to be used as input data for the processing to be performed by each slave process. the data consist in a set of records containing the following fields: line number, trip number, timestamp, timerange, and bus stop. statistics generation stage. the statistics generation stage is organized in four phases: 1. data partitioning and distribution: the master process divides the dataset of useful gps records and distributes the resulting subsets among the slave processes. each of the resulting data subsets includes a group of records associated with the same line number, sorted according to the criteria applied in the pre-processing stage. statistics associated with the same line number are processed in the same slave. 2. computing temporal distances. in this phase, each slave processes the subset assigned by the master process, splitting each record into different fields, to create new data. for each bus line number, the distances between different points on the bus route are calculated iterating through a date-ordered list containing the distance values. the start of each trip is defined by the first new occurrence of a trip number found in the subset containing the gps data handled by each slave process. each slave uses that initial time to track each remarkable location or bus stop, by computing the time between the timestamp and the initial time (i.e., the relative time). the computed relative times are then filtered by timerange and by remarkable location. the generated results are stored in memory, grouped by the fields mentioned above, to be available for the next phase. 3. statistics generation. in the third phase, data are reduced into results and finally statistics are computed. for each occurrence, an iteration over the calculated distances is performed to compute several metrics, including: • the maximum differences between times (max time difference); • the minimum differences between times (min time difference); • the average time (time average); and • the standard deviation of time values (time standard deviation). these metrics are computed considering the relative time (accumulated time of the trip from the starting location) to reach each bus stop or remarkable location for each bus line, and filtering by the different time ranges considered. the output values are grouped and ordered by line number, remarkable location, and timerange. 4. return results to the master process. the slaves return the partial results to the master, who groups and prompts the final results to the user. implementation details. the proposed parallel/distributed system for traffic data processing is implemented using a map-reduce approach in hadoop. the application fits in the map-reduce model because no communications are required between slave processes and the only communications between master and slaves are performed for the initial phase of data distribution and the final phase to report the results. the map-reduce engine in hadoop is applied using one master node and several slave nodes. the master node uses the jobtracker process to send jobs to different tasktracker processes associated to the slave nodes. when the slaves finish processing, each tasktracker sends the results back to the jobtracker in the master node. the details for each stage are presented next. pre-processing stage. the pre-processing stage involves the traditional phases usually applied when using the hadoop framework: splitting, mapping, and shuffling and sorting. all these tasks are performed by the hadoop master process: • splitting. the splitting phase assigns records to the master process. two instances of the fileinputformat and recordreader classes in hadoop were implemented to filter useful data and generate the input data to be used by the mapper process. after that, all selected records are converted to appropriate datatypes to be used in the statistics generation stage (e.g., numerical data are converted to long or int, dates are converted to timestamp, etc.). • mapping. in the mapping phase, each mapper receives a subset of data (data block) to process. the number of mappers on execution is defined by x/b, where x is the size of the data to process and b the size of the data blocks. data filtering is applied by each mapper, using recordreader<keybuscompound,businfo> objects. keybuscompound and businfo are used as <key,value> pairs for records sent to mappers. keybuscompound is a compound key including the fields needed to identify a bus trip (line number, trip number, and timestamp). businfo includes values for remarkable locations, timerange, trip number, and timestamp, needed to apply a secondary sorting (see sorting). 8 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e a distributed platform for big data analysis in smart cities: combining its and socioeconomic data for montevideo, uruguay the hadoop framework creates a number of filtering instances according to the number of input splits on the input file. each instance p operates on a data subset {l}p , where {l} is the set of input lines received in the splitting phase. several methods were implemented to define the filtering logic to return the next register to be processed by mappers. for each record on the input, an integrity check is performed to discard records without the expected format and those not included in the range to process. a two-field record <keybuscompound, businfo> is added to the resulting set for each record not discarded. the output is a list containing {t}p records, with the format <(line_number, trip_number, timestamp), info>. • shuffling and sorting. sorting, shuffling, and partitioning are applied after the map stage on a typical map-reduce application. the common practice is sorting keys, but we decided to apply a secondary sorting [20] to deliver ordered values to each reducer to compute temporary distances in the proposed system. the secondary sorting is needed to sort both keys and values (i.e., the wellknown value-to-key conversion procedure). statistics generation stage. this stage is performed by hadoop reduce processes, which correspond to slave processes in the conceptual algorithmic description. each process has three phases: • data partitioning and distribution. this phase corresponds to the data sent from map to reduce processes. by default, the hadoop framework distributes keys to different reducers applying a hashmap partitioning. this distribution mechanism does not guarantee an appropriate load balancing, because reducers do not receive equallysize subsets to process. furthermore, the results produced by reducers will not be ordered, as it is desirable for the reports to be delivered to the users of the proposed application. for these reasons, we implemented a specific partitioning method using a treemap [21] hash, so the reducer sends those records associated to a specific bus line number. the treemap structure is dynamically generated in the main program, taking into account the number of reducers and a csv file containing ordered unique keys (line number). • reduce. according to the procedure in the previous phase, each reducer receives records with the format: <(line_numberi ), [infoi1, . . . , infoin ]>, related to a given bus line number, and all values associated to keys are ordered. a reduce function is executed on each key (line_number) on set {t}: the initial times are determined for each bus trip and the relative times between remarkable locations in the trip are computed. data is temporarily stored in a treemap structure, using keystatistics (line_numberi , control_pointi , timerangei ) as key and longwritable representing the time differences, as values. • statistics generation. a second function on the reducer receives each <keystatistic, longwritable> pair and computes the statistic values from the previous partial results. in the cases of study reported in this article, we compute the maximum, minimum, arithmetic mean, mean absolute deviation, and standard deviation of times for each bus line number, control point, and timerange. the reducers output is <(line_numberi , timerangei , control_pointi ), (min_timei , max_timei , meani , mean_deviationi , standard_deviationi )>. these pairs are represented as text, key, and value, to prompt results to user. fault tolerance. the proposed implementation applies the automatic fault tolerance mechanism included in hadoop. additionally, some features are activated to improve fault tolerance for the its application developed: i) the feature that allows discarding corrupt input lines is enabled, to be used in those cases where a line cannot be read (the impact of discarding corrupt lines is not significant, because the system is oriented to compute statistics and estimated values); and ii) the native replication mechanism in hdfs was activated, to keep data replicated in different processing nodes. characterizing the bus service zones using socioeconomic indicators. the main details on the procedures for defining and characterizing the bus service zones are presented next. data and methods. this part of the solution relies on a combination of geo-spatial analysis and traditional statistics. the bus service areas are based on isochrones which define equal travel times for a walking distance of ten minutes from each of the stops of a particular bus line. the bus lines and bus stops geometries to derive the isochrones were obtained from the open data available on the geographic information system (gis) site of montevideo city government [22]. these shapefiles were fetched using python scripts and manipulated using python packages including geopandas [23], fiona [24], and shapely [25]. the socioeconomic indicators were obtained from the national institute of statistics (instituto nacional de estadísticas, ine) in uruguay. for the purpose of this study, we used the continuous household survey (encuesta contínua de hogares, ech) [26]. this is a cross sectional survey, conducted uninterruptedly since 1968, that delivers the official indicators for 9 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e sergio nesmachnow, sebastián baña, and renzo massobrio employment and income (for both household and individuals). ine also makes available shapefiles for the areas of analysis (the census sections and census segments) [27]. merging all these datasets and shapefiles we developed a combined geo-spatial and socioeconomic view of each area. figure 3 illustrates this approach presenting all the census sections and segments with an overlapped bus service area. figure 3. choropleth map of the serviced area for bus line 185 in montevideo. the divisions are census segments and the color represents household income (in uruguayan pesos per inhabitant) the bus line shapefiles are used exclusively to represent the bus trajectory on the maps. all the bus lines geometries are contained on a single shapefile that the gis publishes. from these files, the two relevant attributes for our analysis were: the bus stops shapefiles, which are used both on the visual representations and as input to derive the isochrones for the bus service zones. the stops are also contained on a single shapefile with similar attributes. in this case, the geometry contains the latitude and longitude for the point object that represents the stop. figure 4 displays the bus lines and the corresponding isochrones of their service areas for the city of montevideo. figure 4. map of montevideo with isochrones representing the bus coverage areas (light blue shapes). the map displays large areas of the city outside of the service coverage. the ech datasets and shapefiles are accessible from the ine websites [26, 27]. we created local copies of these datasets and used the geopandas package to perform the mapping and statistical manipulations. basic data wrangling was performed to merge the datasets in order to produce a consolidated geopandas geo dataframe containing both the relevant geometries and the indicators selected for the analysis (geometry, median household income, and number of inhabitants per household). we used the most granular census unit: the census segment. data extraction, manipulation, and generation of the datasets was scripted using python. we intend to update the computed results yearly, as new data from the ich is published. 4.2. mobility patterns and demand/od matrices estimation design and architecture. initial experiments confirmed that processing only a small portion of the ticket sales dataset requires a large computation time: studying only one month of ticket sales data demands over 18 days when using a sequential algorithm in a regular desktop computer (intel core i5 x2 processor with 6 gb ram and linux ubuntu 14.04 operating system). therefore, applying a parallel/distributed approach is fully justified to reduce the execution times. our proposal is based on executing the algorithms for demand and od matrices estimation in parallel, making use of several computing units. the main idea of the proposed parallel algorithm is to apply a data-parallel approach. the datasets of ticket sales and gps records are divided in chunks, following the bag-of-tasks paradigm [28]. in this case of study, the bag-of-tasks corresponds to a set of user trips records. since each set of trip records is independent, as they hold information of different citizens, the bag-of-tasks can be assigned to different slaves for processing. using a master-slave model for organizing the processes is an appropriate choice for implementing the estimation algorithm, since the slave processes do not need to share information with each other. a set of slave nodes are created and organized in a slave pool, to be used on demand. this decision reduces the overhead of thread creation and destruction, as every thread is used many times while there are records left to be processed. initially, the master process collects all the data to be processed and applies a pre-processing stage to filter inconsistent records. after that, the master builds the bags-of-tasks and sends the corresponding bags to each slave in the slave pool, which will perform the assigned computation task. afterwards, each slave node executes the destination estimation procedure. finally, the master receives the partial results, persists them, and join them together to create the final demand and od matrices. 10 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e a distributed platform for big data analysis in smart cities: combining its and socioeconomic data for montevideo, uruguay strategy for data processing: algorithmic description. the main details of the proposed algorithm are presented next. data description. the bus companies that operate in montevideo are required to send bus location and ticket sales data to the city authorities. the bus network in montevideo is quite complex, including 1383 bus lines and 4718 bus stops. the case study described in this section considers the dataset of ticket sales and bus locations for january 2015, comprising about 200 gb of data. bus location data contains information about the position of each bus, sampled every 10 to 30 seconds. each location record holds the following information: • lineid, the unique bus line identifier; • tripid, the unique trip identifier for each single trip for a given lineid; • latitude and longitude; • vehicle speed; • timestamp of the location; and • stopid, the identifier for the nearest bus stop to the current bus location. ticket sales data contain information about sales made with and without stm cards. each sale record has the following fields: • tripid, the unique trip identifier for each single trip for a given lineid; • latitude and longitude, • stopid, as in location data; • number of passengers, since it is possible to buy tickets for multiple passengers at once; and • timestamp of the sale. additionally, tickets payed with stm cards have the following fields: unique stm card identifier (cardid) that is hashed for privacy purposes, number of transactions for that stm card (transactionid), and the last payed transaction (payedid). these data allow identifying when a passenger transfers between buses: transactionid increments while payedid remains unchanged. the number of transfers is equal to transactionid−payedid. methodology. the proposed methodology for estimating demand and odmatrices takes into account the two kinds of transfer trips existent in montevideo (detailed in section 2.2). the proposed model is based on reconstructing the trip sequence for passengers that use a smart card, following a similar approach to that applied in the related literature [13–15]. we assume that each smart card corresponds to a single passenger, so we use the terms card and user in an indistinct manner. the proposed approach is based on processing each trip, retrieving the bus stop where the trip started, and identifying/estimating the stop where the passenger alighted the bus from the information available. therefore, two models for estimation are proposed: one for direct trips and one for trips including transfers: • transfer trips. in a transfer trip, passengers pay for their ticket when boarding the first bus by using a smart card identified by its cardid. later, they can take one or more buses within the time limits permitted by the ticket. for each ticket sold, transactionid and payedid) are recorded. these values allows detecting whether a smart card record corresponds to a new trip (payedid is equal to transactionid) or to a transfer between buses (transactionid is higher than payedid). we assume that passengers avoid excessive walking in transfers; we consider that a passenger finishes its first leg at the nearest bus stop to the bus stop where he boards the second leg, and so on. the boarding bus stop for the second leg is recorded in the system, thus we estimate the alighting point from the first bus by looking for the closest bus stop corresponding to that line. • direct trips. direct trips are those that have no bus transfers. we also consider the last leg of a trip with one or more transfers as a direct trip. in both cases, the difficulty lies in accurately estimating a destination point for these trips. to estimate the destination points we consider two assumptions, which are commonly used in the related literature: i) passengers start a new trip at a bus stop which is close to the destination of their previous trip; ii) at the end of the day, passengers return to the bus stop where they boarded the first trip on the same day. in order to estimate destinations it is necessary to chain the trips made by each passenger on a single day. a preliminary study performed on the sales dataset showed that the best option is to consider each day starting at 04:00, since the lowest number of tickets are sold at that time. this allows considering passengers with different travel patterns, such as those who commute to work during the day and those who work at night. the model for chaining direct trips of a specific passenger works as follows. we iterate through all the trips done in a 24 hour period (from 04:00 to 04:00 on the following day). for each new trip, we try to estimate the alighting point by looking for a bus stop located in a predefined range from the boarding bus stop of the previous trip. when no bus stop is found on that radius, the procedure is repeated using a larger radius (twice the original one) to search for bus stops. if no bus stop is found using the larger radius, the origin of the trip is recorded, in order to report the number of unassigned destinations. 11 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e sergio nesmachnow, sebastián baña, and renzo massobrio estimation algorithm. we propose a specificmethodology for reconstructing the trip sequence for passengers, by estimating the destination points from the information available. three phases are identified in the proposed algorithm, which are relevant for building the estimated demand and od matrices: 1. pre-processing. the pre-processing phase prepares the data, filtering those records with incoherent information and classifying records by month per passenger. the algorithm receives as input an unstructured dataset containing raw gps positions and ticket sales data. initially, the algorithm discards those sales records that have invalid gps coordinates; which are not processed for demand and od matrices estimation. a sale record has an invalid location when its coordinates are not within the route of the bus corresponding to the sale, with a tolerance of 50 meters. finally, trip records with consistent location information are separated into different files, according to their cardid and then ordered according to their date field. this allows processing the trips of each passenger independently. 2. core processing. in this phase the sales data are processed in order to generate demand and od matrices. data are iteratively processed: for each passenger, trips are analyzed considering 24 hour periods starting and finishing at 04.00. first, the origin of the trip is recorded. the trip destination is estimated depending on whether it is a transfer or a direct trip. once the origin and the destination are computed, the corresponding values are updated in the demand and od matrices. the process is repeated until all trip records are processed. in our study, we consider a distance of 500m for the search radius used when estimating destination of direct trips, as previously described. 3. output. after all records are computed the demand and od matrices are returned. two variants of the proposed algorithm were implemented, one for each of the two different estimation procedures presented in section 2.2. both variants follow the same general parallel approach previously described. the main implementation details are presented next. implementation details. the proposed algorithms were implemented using python 2.7.5. the crossplatform open-source geographic information system qgis [29] was used to manage geographic information corresponding to bus location and bus stops data. the dispy [30] software package was used for creating and distributing parallel tasks among several computing nodes. dispy is a python framework that allows executing parallel processes, supporting many different distributed computing infrastructures. the main features of the framework include tasks distribution, load balancing, and fault recovery. the dispy framework provides an api for defining clusters and schedule jobs to execute on those clusters. creating a cluster in dispy consists of packaging computation fragments (code and data) and specifying parameters that control how to execute the computations (e.g., which nodes can execute each computation). a number of parameters are needed to set a dispy cluster, including the program to execute in each node must, the list of nodes available to execute the jobs, and a list of dependencies needed for computation must be specified (in the proposed application there is only one dependency: the availability of the qgis software). once a cluster is created, jobs can be scheduled to execute at a certain node. dispy executes the job on an available processor in the defined cluster. after a job finishes, the information about the origin-destination pairs computed is used to build the od matrix. each slave keeps track of the index of the last file or line processed. therefore, in case of a system failure it is possible to resume the execution from the last processed record, without the need of starting the process from the beginning. in our approach, the master creates a set of bagof-tasks where each task corresponds to all the trip records of a single passenger. then, each bag-of-tasks is distributed using dispy across the different slaves to execute the estimation algorithms. it is important to choose the amount of passengers’ trip records to assign to each slave in order to optimize the execution time, avoiding costly communications between the slaves and the master. this parameter is configured in the experimental analysis presented in section 5. finally, the master node distributes tasks to slaves on demand, and obtains the results computed by each slave to gather them to return the final solution. 5. computational efficiency evaluation this section describes the experimental evaluation of the proposed system for generating statistics of public transportation based on its data. the setup for the experimental evaluation is described, including the computational platform used and the problem instances generated from the historical data. after that, the computational efficiency results are reported. finally, sample studies are presented from the data processed for a specific bus line. 12 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e a distributed platform for big data analysis in smart cities: combining its and socioeconomic data for montevideo, uruguay 5.1. platform, instances, and metrics the main setup for the experimental analysis is described next. computational platform. the experimental evaluation was performed over the cloud infrastructure in cluster fing, the high performance computing facility at universidad de la república, uruguay [31]. the analysis was performed using amd opteron 6172 magny cours (24 cores) processors at 2.26 ghz, 24 gb ram, and centos linux 5.2 operating system. problem instances and data. the problem instances considered in each case of study are described next. gps and ticket sales data. several datasets are used to define different scenarios conceived to test the behavior of the system under diverse situations, including different input file sizes, different time intervals, and using different number of map and reduce processes. we work with datasets containing 10 gb, 20 gb, 30 gb, and 60 gb, and also different time intervals (3 days, and 1, 2, 3, and 6 months), with real gps data from buses in montevideo, provided by the local administration intendencia de montevideo. the input data file to use in each test of the experimental evaluation was stored in hdfs. to better exploit the parallel processing, more mappers thanhdfs blocksmust be used when splitting the file. considering an input file of size x mb and hdfs blocks of size y mb, the algorithm needs using at least x/y mappers. hadoop uses the input file size and the number of mappers created to determinate the number of splits on the input file. demand and origin-destination matrix estimation. for the experimental analysis of demand and od matrices estimation, the dataset corresponding to the its in montevideo for january 2015 was processed, including ticket sales and bus location information. this dataset holds the mobility information for over half a million smart cards (corresponding to more than 13 million individual trips). the total size of the dataset is 120gb. computational efficiency metrics. several metrics have been proposed in the related literature to evaluate the performance of parallel and distributed algorithms [32]. in the experimental analysis reported in this article we focus on two traditional metrics for performance evaluation: the speedup and the efficiency. the speedup evaluates how much faster a parallel algorithm is compared to its sequential version. it is defined as the ratio of the execution times of the sequential algorithm (t1) and the parallel version executed on n computing elements (tn ) (equation 1). the ideal case for a parallel/distributed algorithm is to achieve linear speedup (sn = n ). however, the common situation for parallel algorithms is to achieve sublinear speedup (sn < n ), due to the times required to communicate and synchronize the parallel/distributed processes. the efficiency is the normalized value of the speedup, regarding the number of computing elements used for execution (equation 2). the linear speedup corresponds to en = 1, and in usual situations en < 1. sn = t1 tn (1) en = sn n (2) 5.2. experimental results the results of the computational efficiency analysis for the two cases of study is presented next. gps data processing. we evaluated the computational efficiency of the proposed distributed solution and also the correctness to produce useful information for users and administrators. table 1 reports the computational efficiency results for the proposed application when varying the size of the input data (#i), days (#d), number of mapper (#m) and reducer (#r) processes. mean values computed over five independent executions are reported for each metric. all times are reported in seconds. table 1. results of the experimental analysis: computational efficiency of the proposed map-reduce implementation for processing gps data #i #d #m #r t1(s) tn (s) sn en 10 3 14 8 1333.9 253.1 5.27 0.22 10 3 22 22 1333.9 143.0 9.33 0.39 10 30 14 8 2108.6 178.0 11.84 0.49 10 30 22 22 2108.6 187.3 11.26 0.47 20 3 14 8 2449.0 351.1 6.98 0.29 20 3 22 22 2449.0 189.8 12.90 0.54 20 30 14 8 3324.5 275.6 12.06 0.50 20 30 22 22 3324.5 238.8 13.92 0.58 20 60 14 8 4762.0 300.8 15.83 0.66 20 60 22 22 4762.0 264.7 17.99 0.75 30 3 14 8 3588.5 546.9 6.56 0.27 30 3 22 22 3588.5 179.6 19.99 0.83 30 30 14 8 5052.9 359.6 14.05 0.59 30 30 22 22 5052.9 281.1 17.98 0.75 30 60 14 8 5927.9 383.4 15.46 0.64 30 60 22 22 5927.9 311.4 19.04 0.79 30 90 14 8 7536.9 416.6 18.09 0.75 30 90 22 22 7536.9 349.2 21.58 0.90 60 3 14 8 7249.6 944.0 7.68 0.32 60 3 22 22 7249.6 362.1 20.02 0.83 60 60 14 8 10037.1 672.6 14.92 0.62 60 60 22 22 10037.1 531.4 18.89 0.79 60 90 14 8 11941.6 709.6 16.83 0.70 60 90 22 22 11941.6 648.9 18.40 0.77 60 180 14 8 19060.8 913.7 20.86 0.87 60 180 22 22 19060.8 860.3 22.16 0.92 13 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e sergio nesmachnow, sebastián baña, and renzo massobrio the results in table 1 indicate that the distributed algorithm allows significantly improving the efficiency of the sequential version, especially when processing large volumes of data. the best speedup value was obtained when processing the 60gb input file: 22.16, corresponding to a computational efficiency of 0.92. the distributed implementation allows reducing the execution time from about 6 hours to 14 minutes when processing the 60gb input data file. this efficiency result is crucial to provide a fast response to specific situations and to analyze differentmetrics and scenarios for both users and administrators. figure 5 graphically summarizes the computational efficiency results when using input data files with different size. and figure 6 when processing records from different numbers of days. 10gb 20gb 30gb 60gb 0 0.2 0.4 0.6 0.8 1 0.49 0.66 0.75 0.87 0.47 0.75 0.9 0.92 size of the input data file co m p u ta ti o n al effi ci en cy #m=14, #r=8 #m=22, #r=22 figure 5. computational efficiency for different input data files 3 60 90 180 0 0.2 0.4 0.6 0.8 1 0.32 0.62 0.7 0.87 0.83 0.79 0.77 0.92 days co m p u ta ti o n al effi ci en cy #m=14, #r=8 #m=22, #r=22 figure 6. computational efficiency results for different days using 22 mappers and 22 reducers allows obtaining the best efficiency, improving in up to 15% the execution time (9% in average) over the one demanded when using 14 mappers and 8 reducers. working on small problem instances causes data to be partitioned in small pieces, generating low loaded processes and not improving notably over the execution time of the sequential algorithm. the efficiency analysis also determines that the map and reduce phases have similar execution times and reach themax cpu usage (above 97% at everymoment). these results show that the load balance efforts in the proposed algorithm prevents a majority of idle or lowloaded mappers and reducers. demand and origin-destination matrix estimation. the proposed master-slave parallel model requires defining the size of the bag-of-tasks assigned to each slave to compute. a proper bag size must be used in order to have an appropriate load balance and avoid excessive communication between the master and the slaves. experiments were performed varying the size of the bag-of-tasks as well as the number of cores used. the experimental results are reported on table 2. the number of cores (#cores) and the size of the bag-of-tasks (#bag-of-tasks) used in each experiment are indicated. then, for each combination of these values, the best (i.e., minimum), average, and standard deviation of execution time and speedup values are reported for both direct and transfer trips. execution times are reported in minutes and the results correspond to 5 independent executions of the algorithm using each configuration of #cores and #bag-of-tasks. the experimental results obtained suggest that the parallel approach is an appropriate strategy for significantly improving the efficiency of the data processing for demand and o-d matrices estimation. promising speedup values were obtained, up to 16.41 for the direct trips processing and using a bag-oftasks of 5000 trips and executing in 24 nodes. these results confirm that the proposed master/slave parallel model allows improving the execution time of the computational tasks by taking advantage of multiple computing nodes. furthermore, the computational efficiency results indicate that the size of the bag-of-tasks (i.e., the amount of passengers’ trip data given to each slave to process at once) has a significant impact on the overall execution time of the algorithm. execution times were reduced when using the smallest size for the bag-oftasks (5000). further experiments should be performed to assess if using a smaller size for the bag-of-tasks is still more efficient, and to determine the trade-off value before the communications between the slaves and the master become more expensive and have a negative impact on the execution time. 14 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e a distributed platform for big data analysis in smart cities: combining its and socioeconomic data for montevideo, uruguay #cores #bag-of-tasks direct trips transfer trips avg. time±std. dev. best speedup avg. time±std. dev. best speedup 1 1 25920.0 25920.0 30240.2 30240.2 16 5000 2092.1±3.4 2089.6 12.40 2648.9±3.2 2645.5 11.43 16 10000 2372.4±1.8 2371.1 10.92 3068.8±3.5 3063.2 9.87 24 5000 1582.7±2.4 1579.4 16.41 2371.1±2.5 2368.1 12.76 24 10000 1858.2±2.1 1855.9 13.96 2617.9±3.3 2614.3 11.56 table 2. execution time results and performance analysis. using 24 cores and tasks with the trip data corresponding to 5000 passengers, the proposed strategy allows improving in up to 54.4% the efficiency when compared to using 12 cores and a bag-of-tasks size of 5000, and up to 57.9% against a sequential algorithm running on a single computing node. this efficiency allows processing the full information of gps and trip data for one year (more than 130 gb) in 33 days, a significant improvement over the 468 days demanded by a sequential algorithm. 6. two sample studies this section presents two sample studies performed using the proposed distributed system for its in montevideo: average speed/troublesome locations detection and performance of the public transportation across socioeconomic stratas. 6.1. average speed and troublesome locations the calculation of the average speed of buses and the analysis of troublesome locations is a relevant study for the public transport in montevideo. figure 7 presents the study of the average speed of the seven bus lines (100, 102, 103, 105, 106, d11, d8, d10 and ca1) traveling through 18 de julio avenue (the main avenue in montevideo) in four relevant time ranges (including peak hours). the speed analysis is a valuable input for decision making in order to improve quality of service and travel experience for users. figure 8 presents a report extracted from the analysis of delays of buses to identify troublesome locations in the city. results correspond to bus line 195 at night. delay values are computed according to six months of historical gps records, comparing the times to reach each bus stop against the scheduled times, as reported in the website of stm, montevideo [5]. these results can be obtained in real time using the distributed algorithm, allowing a fast response to specific problems. in addition, the information can be reported to users via mobile ubiquitous applications. 6.2. fairness of the public transportation service delivery the preliminary work in this area allow characterizing each of the bus routes using the median household income for the census segments covered by all the bus lines. using these indicators the bus line coverage area is defined as unit of analysis, deriving its socioeconomic characteristics from the census segments that are included on it. figure 9 shows an example of two different instances of the unit of analysis: the bus service areas for bus figure 7. average speed of buses in 18 de julio avenue. 15 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e sergio nesmachnow, sebastián baña, and renzo massobrio figure 8. average delay for bus line 195 in the night, using six months of historical data lines 121 and 195. the map shows that the service area for bus line 195 covers a significantly larger number of census segments, and its median household income is visibly lower than the average income of the service area for bus line 121. this example illustrates the type of contrasts that exists between different bus service areas across the city, which is worth further studying. the proposed methodology to assess the service fairness involves deriving quality metrics– such as the standard deviations of the total routes duration and the deviation from the original schedules– and measuring the correlation coefficient with the socioeconomic indicators that we use to characterize the service zones, such as the household median income. once this phase of the study is completed, we aim at delivering a novel data product that will provide researchers and policy makers with a new perspective on the matter of the fairness of public services delivery. in particular, we will be contributing to answer the question of whether or not certain neighborhoods or areas in the city are dis-proportionally affected by poor public transportation services. 7. conclusions and future work this article described our experiences on designing and building a platform for big data analysis for smart cities. this platform combines distributed computational intelligence and geo-spatial analysis to process historical gps data to compute quality-ofservice metrics for the public transportation system in montevideo, uruguay. furthermore, we presented two case studies that rely on the platform capabilities to answer relevant research questions related to two different urban problem domains: operational efficiency and equability. an intelligent system for data processing was conceived, applying the map-reduce paradigm implemented over the hadoop framework. specific features were included to deal with the processed data: the figure 9. maps of service areas for buses 121 and 195: the red areas correspond to census segments that display the highest household income (in uruguayan pesos per inhabitant) 16 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e a distributed platform for big data analysis in smart cities: combining its and socioeconomic data for montevideo, uruguay proposed implementation allows filtering and selecting useful information to compute a set of relevant statistics to assess the quality of the public transportation system. an application-oriented load balancing schema was also implemented. additionally, a method for accurately estimating trips’ destination based on smart card data is proposed, based on ideas presented in the related literature. this estimation allows computing demand and od matrices, which are crucial for transport planning and are difficult to obtain using traditional methods. the experimental analysis focused on evaluating the computational efficiency and the correctness of the implemented system, working over several scenarios built by using real gps and ticket sales data collected in 2015 in montevideo. the datasets comprise over 200 gb of data corresponding to over 1300 line services operating in the city. the main results indicated that the proposed solution scales properly when processing large volumes of input data, achieving a speedup of 22.16 when using 24 computing resources, when processing the largest input files. regarding demand and od matrices estimation, the experimental results suggest that the proposed platform is appropriate to increase efficiency, achieving speed up values of up to 16.41 when using 24 computing resources. as examples, we computed two types of metrics that provide insights relevant to both citizens and decision makers. one is a collection of average speeds for different segments of bus lines in montevideo using the available historical data. these averages allow to identify troublesome locations in the public bus network, based on the delay and deviation of the times to reach each bus stop. the second type of metrics are related to the bus routes service quality in relation to the socioeconomic characteristics of their service areas. both studies aim at providing authorities and policy makers with a better understand of the transportation system infrastructure. some of these insights can also be incorporated in mobile applications that might help improving the travel experience of the general population. the research reported in this article is based on processing the bus gps and ticket sales data gathered in 2015. however, the proposed distributed architecture would scale up efficiently when processing larger volumes of data, as shown in the experimental analysis. the city government collects the bus gps and ticket sales data periodically, so it is possible to incorporate additional data in order to get even more accurate statistics. furthermore, the uruguayan government handles several other its and non-its data sources (including gps data for taxis, mobile phone data, ticket sale data, special events in the city) which could be easily incorporated to the proposed model to get a holistic understanding of mobility in the city. the main lines for future work are oriented to further extend the proposed system, including the calculation of several other important indicators and statistics to assess the quality of the public transportation. relevant issues to include are the construction of odmatrices for public transport, the evaluation of bus frequencies (and dynamic adjustment), etc. the proposed approach can also be extended to provide efficient solutions to other smart city problems (e.g., pedestrian and vehicle fleets mobility, energy consumption, and others). using other distributed computation frameworks (such as apache storm) is also a promising idea to better exploit the realtime features of the proposed system. references [1] deakin, m. andwaer, h. (2012) from intelligent to smart cities (taylor & francis). [2] sussman, j. (2005) perspectives on intelligent transportation systems (its) (springer science + business media). [3] massobrio, r., pías, a., vázquez, n. and nesmachnow, s. (2016) map-reduce for processing gps data from public transport in montevideo, uruguay. in 2nd argentinian symposium on big data: 41–54. [4] fabbiani, e., vidal, p., massobrio, r. and nesmachnow, s. (2016) distributed big data for demand estimation in its. in high performance computing latin america, communications in computer and information science, springer 697: 146–160. [5] intendencia de montevideo (2010), plan de movilidad urbana: hacia un sistema de movilidad accesible, democrático y eficiente. [6] zheng, x., chen, w., wang, p., shen, d., chen, s., wang, x., zhang, q. et al. (2016) big data for social transportation. ieee transactions on intelligent transportation systems 17(3): 620–630. [7] oh, s., byon, y. and yeo, h. 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[28] cirne, w., brasileiro, f., sauvé, j., andrade, n., paranhos, d. and santos-neto, e. (2003) grid computing for bag of tasks applications. in proceedings of the 3rd ifip conference on e-commerce, e-business and egovernment. [29] qgis development team (2009) qgis geographic information system, open source geospatial foundation. url http://qgis.osgeo.org. accessed: april 2017. [30] pemmasani, g., dispy: distributed and parallel computing with/for python, http://dispy.sourceforge.net/. accessed july 2016. [31] nesmachnow, s. (2010) computación científica de alto desempeño en la facultad de ingeniería, universidad de la república. revista de la asociación de ingenieros del uruguay 61: 12–15. [32] foster, i. (1995) designing and building parallel programs: concepts and tools for parallel software engineering (boston, ma, usa: addison-wesley longman publishing co., inc.). 18 eai endorsed transactions on smart cities 12 2016 12 2017 | volume 2 | issue 5 | e http://sig.montevideo.gub.uy/ http://sig.montevideo.gub.uy/ http://geopandas.org http://geopandas.org https://github.com/toblerity/fiona https://github.com/toblerity/fiona https://github.com/toblerity/shapely https://github.com/toblerity/shapely http://www.ine.gub.uy/web/guest/encuesta-continua-de-hogares1 http://www.ine.gub.uy/web/guest/encuesta-continua-de-hogares1 http://www.ine.gub.uy/web/guest/338/ http://qgis.osgeo.org http://dispy.sourceforge.net/ 1 introduction 2 big data processing for intelligent transportation systems in smart cities 2.1 analysis of the quality and equability of the public transportation system 2.2 estimation of mobility patterns: demand and od matrices 3 related works 3.1 distributed computing for processing traffic data 3.2 estimation of demand and od matrices 3.3 summary of related works 4 the proposed solutions 4.1 processing gps data from buses in the public transport system historical gps data processing applying map-reduce over hadoop characterizing the bus service zones using socioeconomic indicators 4.2 mobility patterns and demand/od matrices estimation 5 computational efficiency evaluation 5.1 platform, instances, and metrics 5.2 experimental results gps data processing demand and origin-destination matrix estimation 6 two sample studies 6.1 average speed and troublesome locations 6.2 fairness of the public transportation service delivery 7 conclusions and future work future feasibility of using wearable interfaces to provide social support natalie wilde*, hamed haddadi*†, akram alomainy* *queen mary university of london, uk †qatar computing research institute, qatar n.wilde@qmul.ac.uk abstract social support has a positive influence on a person’s overall wellbeing. the recent creation of mobile and online social networks have changed the methods used to obtain such support. previous wearable devices have focussed on increasing an individuals perceived level of social support by either encouraging new social relationships or strengthening those already existing. with the release of the apple watch, wearable interfaces are becoming popular but there is little research into the current attitudes of using these interfaces as a social support medium. in this paper we present the results of our survey to establish the attitudes of current smartwatch owners. results show owning a smartwatch has no effect on the levels of social support a person feels they have. the most commonly used method of support was through smartphone, which was true for people regardless of whether they own a smartwatch. a large number of smartwatch owners stated using their device was their last preference in seeking emotional (61%) and informational (57%) support from others. results from the survey indicate that more research is needed to establish exactly what factors make technological devices well suited to accommodate social support and how these can be applied to wearable interfaces in the future. categories and subject descriptors h.5.m [information interfaces and presentation]: miscellaneous; j.3 [computer applications]: life and medical sciences—consumer health general terms social support, wearable technology, social relationships keywords smart watch, wearable interfaces, social networks mobihealth ’15 london, great britain 1. introduction social support can be described as any type of communication, both verbal and non verbal, that reduces an individuals uncertainty. it helps an individual feel as if they have increased control of either themselves or the situation that is causing them distress [1]. long term social support is usually provided by the individual’s informal network, which includes their family and friends. but support can also be provided from more formal networks such as their doctor or a councillor. social support offers many benefits to an individuals overall wellbeing, regardless of stress levels [3]. this is because social support meets basic human needs for a sense of belonging and reassurance of one’s self worth. having adequate social support available ensures that stressful events are handled and coped with in a way that minimises the negative effects on one’s health. this is called the buffering effect and helps to keep both short and long term health consequences low [11]. there are two distinct measurements of social support. actual support is the amount of support that is given to the individual, either in what others have said or done for them. but another measurement which is proven to be of greater importance is that of perceived social support; the amount of support that the individual feels is available to them. in previous studies, it has been found that perceived social support is what actually contributes to good health and wellbeing within an individual [17]. this shows the perception of support to be subjective, what works for one person may not be perceived so beneficial by the next. an individual obtains social support by accessing and utilising their social networks. previous research has stated that offline social networks can have a positive effect on a person’s wellbeing [8]. recent advances in technology have changed the whole structure of social networks and how they are accessed. the development of internet based support groups and online social networks (osn) have recently gained in popularity [9]. these online virtual communities come together to share common interests, experiences and to offer support to each other. osn offer benefits for an individual as they can seek support at any time and from any geographical location. there are also mobile social networks (msn) that allow groups of people to be accessed and engaged with from one’s mobile device [4]. previous studies have found msn to be beneficial in offering social support mobihealth 2015, october 14-16, london, great britain copyright © 2015 icst doi 10.4108/eai.14-10-2015.2261584 in both verbal and non verbal communication [6, 13]. as wearables become more widely available to the consumer, this may give rise to a new type of wearable social network. there is little work within this area and how wearable technology is perceived to affect levels of social support in the user. with the recent release of the apple watch, this paper aims to highlight the current attitudes of smart watch owners with using a wearable interface for seeking social support. opinions are collected in the form of an online survey. the survey focusses on two main types of social support; emotional and informational. emotional support includes needing reassurance, affection and someone to show concern about specific issues. informational support includes advice, guidance, suggestions and useful information about an issue. the rest of the paper is organised as follows. the current methods used by wearable technologies to aid social support are discussed. the methodology behind the survey and analysis are outlined. then the results of the survey are presented and discussed to offer directions for future work. 2. background currently there are two methods used by wearables to strengthen the users perceived level of social support. the first is to help the user create new social relationships and links within their social network. the more people they have in their network, the more likely they are to have someone they can turn to in times of needing support. the memetag device is worn around the users neck and allows users to share their ideas and opinions with each other [4]. the tag consists of a lcd screen with red and green buttons for accepting and deleting memes. users wearing the same tag can like each others memes when they meet. these small devices are all connected to community mirrors. these are large public displays that show real time visualisations of the community dynamics. from looking at the community mirror, an individual may be able to pick out people they feel they want to form relationships with. studies held at a conference found the device to be effective at supporting the users in the formative stages of social network building. more recently in [10], kan et al. developed a t-shirt that also aims to make it easier to form new social relationships. the t-shirt has letters on the front printed with thermochromic ink, which is coloured ink that turns transparent at 89◦f. when two users wearing the t-shirt high five, certain words are highlighted. these words reveal common interests between the wearers and aim to serve as a social catalyst. in [7], chambers et al. focussed on easing the problem of social isolation. they developed a wearable application that used play as a method to increase an individuals levels of social support. it did this by awarding badges and points every time the user carried out social gestures on others, such as shaking hands. the second method used to increase perceive social support is to enhance the social relationships that an individual already has. one way to achieve this is by facilitating social support between people over great distances. technologies developed have allowed people in two different geographical locations to support each others running sessions [12]. devices have also started to use touch to strengthen relationships between users. previous studies have shown touch to play an important role in interpersonal communications and therefore the maintenance of social support networks [16]. devices created such as the smartstones touch1 allow communication through touch and gestures to be sent in the form of vibrations. sociometric badges are wearable devices that automatically track the wearers face to face interactions and conversational times [14]. they achieve this through analysing social signals obtained from vocal features, relative location and the wearers body motion. this data can then be presented back to the wearer for reflection and to provide support on their social behaviour. examples of sociometric badge uses include conferences [4, 5] and analysing childrens social behaviour in kindergarden [15]. 3. survey methods the study conducted aimed to highlight smartwatch owners thoughts towards using wearable interfaces to obtain social support. participants to the survey were recruited through the osn platforms reddit and facebook. on reddit, online communities based around smartwatches such as the pebble, moto 360 and apple watch were selected as potential participants. the survey itself was created and shared through the google forms platform for ease of distribution across the internet via online forums. the survey questionnaire contained 17 questions split into three parts; a, b and c. before the survey each participant was presented with an information page and consent form to sign. part a of the questionnaire asked the participant about the technological devices that they own and their current social support habits. the final question of part a asked the participant if they ever ask for help and advice from others. if the participant responded to this with a ‘yes’ they were required to fill out both parts b and c. if they answered ‘no’ only part c was required. before part b, the participants were given a definition of social support to aid them in answering the survey. part b of the survey asked more in depth questions regarding the participants preferences in ways of receiving social support. respondents where given a list of mediums to rate in order of preference for receiving different types of social support. this list included face to face, desktop computer, laptop, tablet, smartphone and smartwatch. the types of social support questioned were emotional and informational types of social support. before answering the questions, a definition and example of each type of social support was explained to the participant. it also asked how easy they find obtaining social support through their smartwatch devices. finally, part c of the survey contained a set of demographics questions. 4. results a total of 266 respondents completed the survey. of these, 177 (66.5%) already owned a smartwatch device. when studying the demographics of smartwatch owners there were a couple of observations. a high majority of smartwatch owners were male (87.5%), which was found to be statistically significant (p < .001). the age group of smartwatch 1http://www.smartstones.co/ figure 1: method of communication currently used for social support owners was also found to be significant (p < .001), rejecting a null hypothesis that age and gender of smartwatch owners is equally distributed. of smartwatch owners, 96 (54.2%) were aged 18 25 and there were a further 59 (33.3%) within the 26 35 category. 258 (97%) of the respondents state that they use technology to communicate with friends and family at least every day. for the next section, only the data from respondents who owned smartwatches was analysed. 126 (77.3%) respondents agreed with the statement ‘social support is very important to my overall happiness and wellbeing’. this was found to reject a null hypothesis that social support has no effect on happiness levels (p < .001). when asked if they agreed with the statement ‘i am fully socially supported’, 105 respondents (70.5%) answered ‘yes’. when comparing data between groups, there was no significant difference between owning a smartwatch and not. this means that the owning of a smartwatch has no effect on perceived levels of social support. 109 (61.6%) respondents stated that they do seek support and advice from others so were able to continue to complete part b of the survey. when asked what method of communication they use to talk to family and friends, 48 respondents (44%) stated their smartphone, making it the most common method as shown in figure 1. significantly, no one stated their smartwatch as a preferred communication device (p<0.01). at this stage, data from smartwatch owners and non smartwatch owners were compared. when comparing commonly used devices for obtaining social support, the smartwatch option was omitted from the significance test to eliminate bias. no difference was found between the two groups most commonly used method for receiving social support. when the smartwatch owners were asked to rank technological devices in order of preference for receiving emotional and informational support, figure 2 shows the results. for emotional support the smartwatch was not anyone’s first or second preference. a majority of respondents (61%) stated it as their last preference in seeking emotional support from others. preferences were similar for informational support also, with 59 (57%) of respondents placing figure 2: preference of using smartwatch for support over other mediums figure 3: ease of use of smartwatch in obtaining social support smartwatches in last place. these rankings of preference for both emotional and informational support were found to be statistically significant (p < .001). when asked how easy they found obtaining social support through their smartwatch, there were mixed responses as shown in figure 3. roughly equal numbers of respondents found smartwatches both difficult and easy to use for social support. 31 (28.4%) respondents had never used their smartwatch for obtaining social support. there was no difference with regards to gender or age as perceived ease of use of a smartwatch was fairly evenly distributed. 5. discussion and future work when referring to the technology adoption lifecycle [2], smartwatches appear to be in the early adopters stage. when looking into the demographics of people who make up these early adopters, the majority are male and aged between 18 25. this could indicate the current average user profile, indicating that wearable smartwatches are not appealing to the female consumer at the current moment. this could be because of aesthetics or function. a large amount of respondents use technology to communicate with family and friends and obtain social support currently. a majority of smartwatch owners agreed that social support is important for their happiness which suggests that they would prefer social support on a regular basis. 70.5% of owners felt that they were fully socially supported but this is no different to the proportion when looking at people that do not own smartwatches. this could suggest that wearable technology is not enhancing social support levels at the current time. this could be down to the fact that the technology is still relatively new, there are not many current applications that deal with social support specifically. it may also be down to the fact that the user is getting support, but the wrong kind for what they require at the time. for example they may be getting informational support when they desire emotional. also applications that allow support are still in the early stages development wise and they are improving their designs on a daily basis. another possibility could be that the watch interface and form itself is just not effective in raising the levels of social support a person feels that they have. the fact that 61.6% say that they actively seek social support would suggest the need for more research into wearable interfaces that can accommodate these needs. the fact that nobody chose their smartwatch as their most commonly used device for social support could be down to it been a relatively new technology. but observing that there is no difference in usage regardless of whether they own a smartwatch suggests that it does not offer the needed ease and functionality that other devices such as the smartphone do. future work could focus on the exact reasons why people prefer certain mediums and use this to build a stronger application for the smartwatch. for example, do people prefer texting or talking? smartwatch owners also do not prefer to use their smartwatch for seeking emotional or informational support from others. this further backs up that the current interfaces used are not suitable. future work could focus on why it is not working for them and generate systems that encourage the use of wearable interfaces for social support. there was no difference between type of support and preference, which suggests future work should look into how the two types of support differ from each other and the best way support can be given through wearable devices. there are a large number of smartwatch users that are not using their device at all for seeking social support. this is a statement that needs questioning further. is it because of their personal attitudes towards the device or because the device does not work for social support at the current time? users are finding the interface both difficult and easy to use, suggesting that there is no current system designed for seeking social support through these devices. research into designing an interface that makes it easy for everyone could be beneficial for future developers. overall preference is towards smartphones when it comes to seeking social support, possibly due to portability. over the years devices have got smaller and more ubiquitous; fitting around peoples lifestyles and social networks. it would appear that the smartwatch is not building on the smartphones previous success [13, 6]. much more research into the future interface design of these devices is needed to encourage the use of wearable devices for social support. 6. acknowledgments the authors would like to thank all the people that participated in the survey questionnaire. this work is supported with funding from engineering and physical sciences research council (epsrc) and the arts and humanities research council (ahrc). 7. references [1] t. l. albrecht and m. b. adelman. communicating social support. sage publications, inc, 1987. [2] g. m. beal, j. m. bohlen, et al. the diffusion process. agricultural experiment station, iowa state college, 1957. [3] l. f. berkman and t. glass. social integration, social networks, social support, and health. social epidemiology, 1:137–173, 2000. [4] r. borovoy, f. martin, s. vemuri, m. resnick, b. silverman, and c. hancock. meme tags and community mirrors: moving from conferences to collaboration. in proceedings of the 1998 acm conference on computer supported cooperative work, pages 159–168. acm, 1998. [5] r. borovoy, m. mcdonald, f. martin, and m. resnick. things that blink: computationally augmented name tags. ibm systems journal, 35(3.4):488–495, 1996. [6] l. m. brown and j. williamson. shake2talk: multimodal messaging for interpersonal communication. in haptic and audio interaction design, pages 44–55. springer, 2007. [7] t. chambers. promoting social interactions through a wearable computing application. [8] m. greenblatt, r. m. becerra, and e. serafetinides. social networks and mental health: an overview. the american journal of psychiatry, 1982. [9] c. a. heaney and b. a. israel. social networks and social support. health behavior and health education: theory, research, and practice, 4:189–210, 2008. [10] v. kan, k. fujii, j. amores, c. l. zhu jin, p. maes, and h. ishii. social textiles: social affordances and icebreaking interactions through wearable social messaging. in proceedings of the ninth international conference on tangible, embedded, and embodied interaction, pages 619–624. acm, 2015. [11] m. mattson and j. g. hall. health as communication nexus: a service-learning approach. 2011. [12] f. mueller, s. o’brien, and a. thorogood. jogging over a distance: supporting a jogging together experience although being apart. in chi’07 extended abstracts on human factors in computing systems, pages 1989–1994. acm, 2007. [13] a. u. mutsuddi and k. connelly. text messages for encouraging physical activity are they effective after the novelty effect wears off? in pervasive computing technologies for healthcare (pervasivehealth), 2012 6th international conference on, pages 33–40. ieee, 2012. [14] d. o. olguın and a. s. pentland. sociometric badges: state of the art and future applications. 2007. [15] s. park, i. locher, a. savvides, m. b. srivastava, a. chen, r. muntz, and s. yuen. design of a wearable sensor badge for smart kindergarten. in wearable computers, 2002.(iswc 2002). proceedings. sixth international symposium on, pages 231–238. ieee, 2002. [16] r. wang, f. quek, j. k. teh, a. d. cheok, and s. r. lai. design and evaluation of a wearable remote social touch device. in international conference on multimodal interfaces and the workshop on machine learning for multimodal interaction, page 45. acm, 2010. [17] e. wethington and r. c. kessler. perceived support, received support, and adjustment to stressful life events. journal of health and social behavior, pages 78–89, 1986. this is a title 1 the challenge for the development of smart city concept in bratislava based on examples of smart cities of vienna and amsterdam andrej adamuscin1,*, julius golej1 and miroslav panik1 1 institute of management, slovak university of technology in bratislava, vazovova 5, 812 43 bratislava abstract a smart city in general is a very wide socio-economic-urban-technical phenomenon that inherently represents an increase certain quality of the urban environment and organism. it is not only a technical and technological level of development of infrastructure of a city, but constitutes mainly intellectual maturity and awareness of all stakeholders of the urban organism. topic of smart cities is gaining exponentially in importance, as the socio-economic and demographic changes creating new trends, needs, requirements and challenges for existing urban areas, inner urban processes and their management. there are already a number of applied strategies, which proves the efficiency and sustainability of the solutions. in this contribution authors are trying to outline the problematic areas of bratislava to achieve smart city concept, whereby they take inspiration from the neighbouring city of vienna and amsterdam, which in turn are considered as some of the top smart cities in europe. keywords: smart city, framework strategy, renewal, bratislava, vienna, amsterdam, received on 17 december 2015, accepted on 07 july 2016, published on 20 july 2016 copyright © 2016 a. adamuscin et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.18-7-2016.151629 *corresponding author. email: andrej.adamuscin@stuba.sk 1. introduction with the development and change in society, particularly with changes in the manufacturing sectors of the economy is changing not only the economic structure, but also the environment of the city. cities in the past responded to the industrialization of the construction of industrial buildings and entire structures, thus changed functional, respectively the spatial arrangement (mostly) rural zone of sites. today needs to reflect the opposite trenddeindustrialisation, thus changing the use of functional areas and industry objects to other functions. it may be a manufacturing, services, logistics, research / development, or even housing and recreation. for the past 20 years also bratislava has undergone many dynamic changes. disordered and uncontrollable new construction of buildings and renovation of existing housing stock without comprehensive strategy or insufficient implementation support system, both static and dynamic transport should be the main reasons such as these developing processes should be started to meet the highest requirements of contemporary modern european cities. bratislava as a sister city of vienna, from which it is located approximately 64 km could thus in its direction just to take an example from vienna which is considered among the top european and world smart cities for several years. to achieve this state could be helpful, inter alia, also a project eu-gugle and also prepared several concepts such as “methodology for complex renewal of housing estates with a focus on housing reconstruction” or research article eaeai endorsed transactions on smart cities eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e5 http://creativecommons.org/licenses/by/3.0/ a. adamuscin, j.golej and m. panik 2 still uncompleted implementation of transport policy of the city of bratislava. 2. definitions of smart cities the concept of “smart city” has become more and more popular in scientific literature and international policies. to understand this concept it is important to recognize why cities are considered key elements for the future. cities play a prime role in social and economic aspects worldwide, and have a huge impact on the environment. [1, 2] table 1 reports some of the definitions of “smart city” proposed in the literature, providing an idea of the many meanings that has a smart city. many definitions of smart cities exist. a range of conceptual variants is often obtained by replacing “smart” with alternative adjectives, for example, “intelligent” or “digital”. the label “smart city” is a fuzzy concept and is used in ways that are not always consistent. [3,4] table 1. some selected definitions of “smart city”. definition source a smart city is a city well performing in a forward-looking way in six “smart” characteristics, built on the ”smart” combination of endowments and activities of self-decisive, independent and aware citizens. www.smartcities.eu [4] a city well performing in a forward-looking way in economy, people, governance, mobility, environment, and living, built on the smart combination of endowments and activities of self-decisive, independent and aware citizens giffinger et al. (2007)[5] “[…] two main streams of research ideas: 1) smart cities should do everything related to governance and economy using new thinking paradigms and 2) smart cities are all about networks of sensors, smart devices, real time data and ict integration in every aspect of human life.” p. 57 gabriel cretu 2012) [6] smart cities “are the result of knowledge-intensive and creative strategies aiming at enhancing the socio-economic, ecological, logistic and competitive performance of cities. such smart cities are based on a promising mix of human capital (e.g. skilled labor force), infrastructural capital (e.g. high-tech communication facilities), social capital (e.g. kourtit and nijkamp (2012) [7] intense and open network linkages) and entrepreneurial capital (e.g. creative and risktaking business activities).” p. 93 for better understanding of what all is in the concept “smart” necessary to redefine, a model (figure 1) can be used. the model is based on a definition of giffinger, who defined “smart degree” of 70 medium-sized european cities focusing not only on digital data and information, but on 6 dimensions: smart mobility, smart environment, smart governance, smart economy, smart people, smart living. [5, 8] figure 1. six components of smart city [8] figure 2. the relationship between components and characteristics of smart cities [8] eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e5 the challenge for the development of smart city concept in bratislava based on examples of smart cities of vienna and amsterdam 3 according to de santis, fasano, mignolli and villa (2014b) especially six dimensions of smart city categorize the conception between neoclassical theory of regional and city development. actual study of the european parliament mapping smart cities in the eu (2014) supplements the scheme of six smart city characteristics by three components – technological, human, institutional (figure 2). [8] 2.1. vienna smart city the “smartness” of a city describes its ability to bring together all its resources, to effectively and seamlessly achieve the goals and fulfil the purposes it has set itself. in other words, it describes how well all the different city systems, and the people, organizations, finances, facilities and infrastructures involved in each of them, are: individually working efficiently; and acting in an integrated way and coherent way, to enable potential synergies to be exploited and the city to function holistically, and to facilitate innovation and growth. [9] recent years vienna has become a leading smart and sustainable european city. the austrian capital differs from most other metropolises through its good performance in so many areas: housing, public transport and other infrastructure services (e.g. waste separation, spring water mains), education and universities as well as vast urban green spaces. [10] vienna is the city with the world’s best quality of living, according to the mercer 2014 quality of living rankings, in which european cities dominate. [11] for the city of vienna has been prepared a framework urban development strategy with a view into the 2050. the present smart city vienna framework strategy is directed at all target groups of the city: vienna’s citizens, enterprises, non-profit institutions and, last but not least, the public sector itself. [10] smart city vienna comprises first and foremost the aim of resource preservation. development and modification processes in the sectors of energy, mobility, and infrastructure and building management are to dramatically reduce co2 emissions by 2050. [10] in fact vienna recently created a public private entity, tina vienna which is tasked with co-developing smart city strategies and solutions for the city. nowadays there are prepared more than 100 smart cities projects being developed throughout the city. [12] for example one of the mentioned projects is citizen solar power plant. with a goal of obtaining 50% of their energy from renewables by 2030, the city partnered with the local energy provider, vienna energy, they developed a crowd-funding model whereby individual citizens can buy half or whole panels and receive a guaranteed return of 3.1% annually. [13] vienna is also testing out a range of electric mobility solutions from expanding their charging network from 103 to 440 stations by 2015 to testing ev car sharing and electric bike rentals. vienna bike sharing program is fully accessible to visitors, not just residents. [14] another important innovation has been in rezoning dense neighbourhoods allowing for zero-parking residential buildings. residents in these communities commit to not owning a personal vehicle. finally, vienna is renovating a 40 hectare former slaughterhouse district and turning it into a much smarter use: an innovation district focused on media science and technology. by 2016, the city expects 15,000 people to working on start-ups in the neu marx quarter district. [13] furthermore, vienna took the extra step of incorporating the strategy into law to minimize the risk of future mayors throwing the plan out to start over. [14] smart city vienna framework strategy the key goal for 2050 of smart city vienna is to offer optimum quality of living, combined with highest possible resource preservation, for all citizens. this can be achieved through comprehensive innovations (shown on fig. 3). figure 3. the smart city vienna principle [10] p. 17 the present framework strategy describes the key goals and principal approaches chosen to attain them. it represents guidelines for the numerous important specialised strategies of the city that define concrete multiyear plans for such areas as urban planning, climate protection, the future of energy supply or vienna as an innovation hub. [10] the smart city vienna framework strategy is more comprehensive (but not exhaustive), pursues a long-term horizon (2050) and does not offer detailed packages of measures. however, concrete sub-projects with a shorter timeframe will definitely be formulated and implemented. [10] eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e5 a. adamuscin, j.golej and m. panik 4 2.2. amsterdam smart city the city of amsterdam is ranked third in the european rankings by cohen. amsterdam set out its goals for sustainability in the structural vision 2040 and the energy strategy 2040 follows [15]: • 40% reduction in co2 emissions in 2025, compared with 1990 levels, • 75% reduction in co2 emissions by 2040, • climate-neutral municipal organisation in 2015. to help achieve these targets, the amsterdam innovation motor (aim), now amsterdam economic board, the city of amsterdam, net operator liander and telecom provider kpn started the amsterdam smart city platform in 2009 [15]. the amsterdam smart city (asc) platform is a partnership between businesses, authorities, research institutions and the people of amsterdam that initiates, stimulates and advances smart city projects in amsterdam. the main objective of the asc platform is to help to achieve the targets set out in the energy strategy 2040 and to reduce carbon emissions in amsterdam. asc believes in a habitable city where it is pleasant to both live and work. in 2015 this platform has have into a partnership with over 100 partners, which are involved in more than 90 innovative projects. these smart city projects deal with a variety of topics and cover all characteristics of a smart city including energy transition, smart living, smart society, smart areas, smart economy, smart mobility solutions and open connectivity. the amsterdam smart city platform is aware of the many different ideas that can be applied to the city and the challenges that the city faces. by challenging parties to submit and execute innovative solutions to urban issues, asc connects and accelerates this progress. asc also addresses the possibilities to strengthen previous activities. this advances the development of new markets and profits for innovative solutions. where possible, these solutions are replicated elsewhere in the city (shown on figure. 4). [15] figure 4. the amsterdam smart city platform [15] inspirational projects from amsterdam to bratislava smart parking mobypark parking in big cities is becoming more and more difficult. many drivers spend on average 20 minutes per time while looking for a parking spot. this increases co2 emissions and most important of all; people waste their time. mobypark, a sharing parking platform, will make parking easier and more efficient. private parking lots, public parking garages, hotels, and hospitals: they make their unoccupied parking spots available for drivers through this app. mobypark offers all the available places on a platform where it's possible to see real time availability and book these parking spots ahead. as a result, drivers spend less time searching for a single spot and reduce co2 emissions. in her turn, ensures that you can easily rent a parking place for several days of a private individual, hotel or another institution. the service of mobypark consists of a website and an app (android and ios). it offers parking opportunities in more than twelve cities in the netherlands (2014) and makes it possible in more than five countries to share your parking space and to rent your parking places for a short or long term. its aims to, among others in collaboration with amsterdam smart city, enlarge the amount of parking places and partner up with different with public and private organizations. [16] smart living – city-zen in the city-zen project several innovative solutions are demonstrated in the field of smart grid, heat networks and sustainable housing in nieuw-west in amsterdam. the residents and users have a central position in all the solutions. the changes give the users more choice in the ways they use energy. the project is developing a positive energy district by implementing a variety of measures such as sustainable transport, smart parking systems and car sharing. the city-zen projects provide a major boost to the energy ambitions. in amsterdam, the following projects are being implemented: intelligent net, sustainable heat network, drinking water used for cooling of business area, energy saving by residents, testing living lab, serious gaming and roadmap to city zero energy. [17] 3. methodology for smart cities according global advisory committee for smart cities benchmarking was developed 62 indicators across the smart cities wheel (shown on figure 5). eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e5 the challenge for the development of smart city concept in bratislava based on examples of smart cities of vienna and amsterdam 5 figure 5. smart cities wheel [14] each of the six components of the smart cities wheel are assigned a set of indicators reflect an attempt to create a proxy for measuring each of the sub-components of the wheel. each component contains 3 subcomponents. therefore there are 18 total subcomponents in the model, and with 62 indicators, that leaves an average of almost 3.5 indicators per subcomponent (shown on appendix a. smart cities benchmarking indicators). the data were transformed by using a mathematical formula called a zscore, which permits the comparison of data in different units (e.g. %, tons of ghg emissions, etc.). each of the 6 components is then assigned a maximum of 15 points and the results are transformed in a way that the highest performing city in each category is assigned 15 points. thus, if one city were to lead in each of the six components, the city would obtain a maximum score of 90 points. of the 62, 16 of them are also directly mapped to the new sustainable cities iso standard (iso 37120). [14] 3.1. mercer’s quality of living mercer’s quality of living reports provide valuable information and hardship premium recommendations for over 460 cities throughout the world, the ranking covers 223 of these cities. [11] living conditions are analyzed according to 39 factors, grouped in 10 categories [11]:  political and social environment (political stability, crime, law enforcement, etc.)  economic environment (currency exchange regulations, banking services)  socio-cultural environment (media availability and censorship, limitations on personal freedom)  medical and health considerations (medical supplies and services, infectious diseases, sewage, waste disposal, air pollution, etc.)  schools and education (standards and availability of international schools)  public services and transportation (electricity, water, public transportation, traffic congestion, etc.)  recreation (restaurants, theatres, cinemas, sports and leisure, etc.)  consumer goods (availability of food/daily consumption items, cars, etc.)  housing (rental housing, household appliances, furniture, maintenance services)  natural environment (climate, record of natural disasters) the scores attributed to each factor, which are weighted to reflect their importance to expatriates, allow for objective city-to-city comparisons. the result is a quality of living index that compares relative differences between any two locations evaluated. for the indices to be used effectively, mercer has created a grid that allows users to link the resulting index to a quality of living allowance amount by recommending a percentage value in relation to the index. [11] 4. bratislava until the fall of former political regime in 1989 was in slovakia, including bratislava for several years realized mass production of affordable housing. this construction was marked by the poor quality of buildings, especially as regards their energy performance. this poor technical condition mainly of prefabricated apartment buildings in many cases persists to these days, also thanks to still unrealized coherent concept of housing estates renewal. renovation of buildings in bratislava is provided on individual and un-conceptual basis. renewal is performed only on separate apartment blocks, without connectivity to their immediate surroundings (shown on fig. 6). despite to this state for ministry of transport, construction and regional development has been developed a comprehensive study of housing estate renewal in the recent past: “methodology for complex renewal of housing estates with a focus on housing reconstruction”. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e5 a. adamuscin, j.golej and m. panik 6 figure 6. prefabricated apartments building in bratislava [18] within this study was developed analysis of the current state of housing estates renewal in slovakia architectural, urban, administrative aspects and existing planning tools of complex housing estates renewal. there were analysed european documents in the field of urban development (leipzig charter, toledo declaration, the territorial agenda 2020, the europe 2020 strategy) as well as the research was performed on the selected model of foreign examples. finally was realized the draft of methodology process of preparing strategic documents for housing estates renewal with emphasis on housing reconstruction at urban level, with an emphasis on an integrated approach and feasibility plans. [19] it should be added that putting this methodology into practice is heavily dependent on a momentary political will. now, the slovak capital has a chance to move forward within a project aimed at demonstrating the feasibility of nearly-zero energy building renovation models. bratislava is the only eastern european city to participate in the eugugle project, which stands for european cities serving as a green urban gate towards leadership in sustainable energy. the aim of the project is to create a concept of energy performance and securing the energy efficiency of buildings when using them, as well as the reduction of energy intensity within the city’s district in which the building is located. in other words, the project will take into consideration not only the reduction of energy consumption in the buildings, but will simultaneously deal with other aspects of a sustainable environment, like the interconnection of the building with public space, green areas and sustainable forms of mobility. the latter includes mass public transport, bicycles and moving on foot. bratislava was chosen in a strong competition of 45 european cities and the city is cooperating with vienna in this project, while the austrian capital is serving as a district leader. over the five years of the project (20132018) bratislava with other european cities will join efforts to combine the latest research results in smart renovation of groups of buildings at the district level and use this knowledge to renovate the living space. the main task of this project is to bring to bratislava new, sustainable technologies that will reduce emissions caused especially by heating apartment blocks. within this project, bratislava can receive up to €2 million to renovate 40,000 square meters of total floor area, i.e. up to €50 per square meter to cover the costs of the renovation. out of the total floor area, 20,000 square meters should account for buildings owned by the bratislava municipality, while the remaining 20,000 square meters should account for privately owned housing represented by owners’ associations or apartment block administrators. the european commission will refund the renovation costs only after the works are completed and have achieved the target parameters. [20] “the apartment buildings, selected for the project eugugle demonstration are located in two districts: the wider city centre and the western part of bratislava city (shown on figure 7). a wide range of different building types from different construction systems and construction materials were selected for the eu-gugle project demonstration and are representing the typical city´s building composition. almost all of the selected buildings are characterized by high energy demands and present diverse typical technical difficulties. the buildings, in current stage, have very poor thermal protection of the envelope and require high amount of energy for space heating and domestic hot water preparation. most of the buildings are connected to a district heating network. the selection of pilot private apartment buildings is aimed to identify the wide spectrum of issues and problems that could prospectively occur in the renovation process of housing stock in the city. between 60’s and early 90’s, due to city expansion and lack of housing units, many prefabricated concrete apartment blocks were built. the exemplary renovation of the municipal social housing is expected (the municipal lodging-house for disadvantaged families and the house for elderly people)”. [21]  total floor area to be renovated: ≈ 40,000m²  type of buildings: both private apartment buildings and buildings own by community used for housing.  primary energy savings target: up to 60-75%. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e5 the challenge for the development of smart city concept in bratislava based on examples of smart cities of vienna and amsterdam 7 figure 7. eu-gugle districts in bratislava – demonstrations in red [21] the energy saving measures outlined below will result in 60 to 75 % reduction of energy use in buildings compared to present state. the proposed measures will be replicated in other apartment buildings, located in different city districts, which are constructed in the same or have very similar construction systems. the actions are focussed on following technical and non-technical measures [21]: technical measures [21]:  improvement of the energy performance of buildings through renovation and retrofitting measures (thermal protection of peripheral constructions, roofs, replacement of existing windows with triple-glazed windows,)  implementation of renewable energy sources in district heating systems (eventually disconnection of buildings)  retrofitting of building technical system components and thermal insulation of distribution system pipes; reduction of energy use through technical measures  renewal of elevators, increasing of energy and transport efficiency (duplex elevator group control system)  replacing of fossil energy sources by several innovative technologies (application of heat recovery from the sewage, and air, heat pumps integrated in a low energy heat network, pv, cogeneration systems) non-technical measures [21]:  introduction of metering and regulation control systems • motivation of tenants (metering), communication measures and advisory activities to reduce energy consumption through user’s behavior  energy efficiency rental fee and other agreements with tenants also very important is the issue of transport infrastructure. physical lifetime of transport infrastructure depends primarily on the building materials and old design of transport capacities. the materials that were used for its construction currently do not meet the quality requirements due to the infrastructure was not subject to more fundamental recovery process during its lifetime. moreover, the infrastructure lifetime is significantly influenced by the intensity of its use. its implementation largely falls within the period of implementation of residential buildings and public facilities in housing estates, when at least in a position of static transport capacitively was sufficient for the then demands. the issue of parking in slovakia is a long-term problem, whether in existing buildings or with new development projects where parking costs are only kind of forced expenditure on which developers often want to save money. bratislava is one of the european metropolises, which seeks for the solution for several decades (shown on figure 8). problem that bratislava was not ready for, is a major building boom which caused a further increase in both passenger and freight transport in the city center. this means that the constantly increasing level of motorization brings to slovakia and especially in densely populated urban areas around the capital bratislava even higher space requirements. that becomes the most valuable quantities especially in the inner-city environment. this fact makes new demands on the urbanization of our cities, the professionalism of solutions to traffic problems and high standards to ensure a quality environment. one of the most serious current problems closely related to urban space in bratislava is the traffic situation, especially the issue of static traffic. [22] figure 8. parking in bratislava [23] another important issue in the field of comprehensive transport solutions in bratislava is the fact that there is insufficient traffic data database and the city does not have sufficient details of current conditions of its urban road network. city of bratislava is lacking the scheduled surveys and their results, which would be able to determine the disproportion of the current state and predict its development. [24] the list of projects that have an ambition to contribute to the solution of traffic problem in bratislava is quite long. solving problems with static traffic in bratislava could be implemented using comprehensive regulation through traffic signs. in practice this means charging for parking at a time of increased congestion and the designation of paid parking zones with the road signs. paid parking zones could improve the environment and conditions for non-motorized road users, as well as improving the quality of transport services. one of the solutions to the problems with static traffic could be building a semi recessed and recessed parking, garage houses, increase recessed parking with one or two floors. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e5 a. adamuscin, j.golej and m. panik 8 addressing of static traffic in different districts of the city lies in cooperation with the magistrate of the capital. cooperation includes the selection of appropriate areas that would capacitive mean an increase in parking areas for individual districts. solution of this complex issue could be also implemented through ppp projects. another solution is a free parking not only on the borders of the city, but also outside, for example in malacky, pezinok or senec. the condition is to create high quality service suburban bus line, which will operate at appropriate intervals. another solution of problem of static transport in bratislava could be seen in the construction of smart parking spaces by installing smart parking sensors placed directly on the parking places. drivers would be allowed to easily find a free parking place and would contribute significantly to the reduction of emissions in the city. [22] another important issue is the participatory budget of the city and the city districts. bratislava as the first slovak city began experimenting with the introduction of participatory budgeting since 2011. citizens were given the opportunity to decide directly on the reallocation of public finances and on the form of public space and services. participatory budgeting process takes place throughout the year and is open to all citizens. in the first phase are collected suggestions and ideas from people on the use of public finances. they are then sorted and processed into projects. since the idea is always more than a means to implement them, citizens must also decide which of their ideas are supported and which are not. [25] it took place at participatory budgeting at the city level for a number of deficiencies and irregularities in recent years. they arise in the event of a communication strategy that would attract as many residents into the process; or administrative support, which would work systematically on the involvement of citizens and work on the drafts; and especially mismatch about the rules for the conduct of participatory budgeting process. municipality of bratislava launches e-governance project in 2015. it is a project of electronic council, which contributes to saving the environment and optimizes the work of the city office. the official website of the city will be available invitations and materials for meetings, profiles of deputies and information about their individual vote, or resolution of the city council. the new application will serve all as citizens, as well as local authorities and the deputies. [26] 4. smart living: the concept of lowcarbon housing solutions for the selected urban zone in bratislava defining of the solved area the area of interest falls within the city district of petrzalka in the capital bratislava. extent the solved area covers an area about the size of 1,096,348 m2 (109.6 hectares). in terms of space-functional compositions holds a dominant function of housing in apartment buildings. residential buildings are mostly built in a u shape with exterior surfaces (with centre public playgrounds and the dominant urban vegetation). housing construction in the area is designed in the form of 8-storey and 12-storey panel blocks of flats. the vast range of amenities consists of commercial and service facilities, facilities for sports and administrative buildings. figure 9. defining of the solved area [27] solved area represents a residential zone, which is an aesthetic appearance and functionality relatively the same as the surrounding urban environment within the territory of city district of petrzalka (fig. 9). on this residential zone are linked monofunctional zones of sport, recreation and employment opportunities. solved area and all the territory of petrzalka in addition to interconnection of individual zones requires also a certain humanization of the urban environment and creation of living street space, which at many locations are missing. baseline emission inventory of co2 production within the model area within the framework of the solved area are situated panel apartment blocks built in 1983-1987. construction and technical solution of residential buildings is different, whether the type, size, number of stories or the number of flats (see figure 10). therefore, the energy consumption also varies in each apartment buildings. as the age of the buildings reaches almost 30 years, a major potential for reduction of energy consumption currently lies in the reconstruction of housing stock in this area. in the solved area is situated 37 residential buildings covered by housing association. within the framework, the solved area was carried out renewal of the 25 apartment buildings. for another 14 apartment buildings, the renovation project has not taken place and no requests has not been submitted for realization any renewal. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e5 the challenge for the development of smart city concept in bratislava based on examples of smart cities of vienna and amsterdam 9 type a type b type c figure 10. views and cuts of individual types of apartment buildings in the solved area [28] another factor influencing the leakage of co2 emissions into the atmosphere is the age of apartment buildings, which in this case is determined by approximating the value of the object from a technical point of view. this means to what extent is influenced the overall energy consumption through technical condition and constructional features of a residential building. from housing association were given information about the energy consumption of buildings in 2012-2014. according to the methodology of redistribution of energy consumption in households (58% for heating, 22% for heating the water, 10% for lighting and 10% of electrical appliances) was calculated individual production of co2 emissions from housing (see appendix b). strengths 42 weaknesses 49 green areas 10 panel technology 10 public spaces 10 technical condition of apartment buildings 8 thermal insulation for over 50% of apartment buildings 7 the total energy consumption of apartment buildings 8 monitoring of energy consumption 8 energy consumption for public lighting 9 the quality of life of residents 7 emissions arising from the concentration of vehicles 7 the aesthetic appearance of the environment 7 opportunities 37 threats 15 green infrastructure 9 increase in co2 production 8 complex reconstruction of apartment buildings 10 climate change 7 (energy certification) smart public lighting 8 environmental pollution 8 table 1. swot analysis: identification of positive and negative elements in the context of reduction / production of co2 [27] figure 11. weighted swot analysis [27] for the classification of swot analysis prevails weaknesses (49) above strengths (42), while above threats (23) dominates opportunities (27). based on the assessment, can be determined the strategy of alliance for a given area. taking into account the weaknesses that area has, also has the potential for development in the context of decreasing production of co2 by improving green infrastructure, comprehensive reconstruction of residential buildings and applying smart technology for public lighting. under the final strategy of alliance we can understand cooperation of housing association with different legal entities and public authorities to improve living conditions and even all environment. the conception of housing estate development the philosophy of the conception of area development is based on the analysis of the current state of the territory and lies in the deepening issues in the field of energy consumption with the aim of intensifying functional relations, and reducing co2 gas emissions. the output for design of adequate measures for the model area is a concept developed in connection with invariant solution of the final concepts (fig.). interconnection of individual elements of concepts will contribute to a radical reduction in co2 emissions through various technical and environmental instruments applicable to the model area. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e5 a. adamuscin, j.golej and m. panik 10 figure 12. final concepts of the model area development [27] the concept on the left, naming interest area as "lowenergy housing estate". housing estate with arranged vegetation and interconnected with green gardens in combination with water features could to a certain degree ensure a reduction of emissions and also affect an environmental behaviour of residents of the solved area. each housing inner block should have a uniform structure and continuity to the surrounding green living by using various technical and technological instruments. "lowenergy housing development" would become an economically-profitable and energy-efficient housing estate with a direct impact on the surrounding environment with the possibility of applications to locations outside of this area. the principle of the final concept is the creation of urbanistically compact unit with a lower energy consumption. it also includes the transition of this area to economic efficient and environmental friendly mode of public lighting. this would ensure a significant reduction in energy consumption and thus there would be a housing estate based on power save mode from the energy and economic point of view. the concept on the right side, naming interest area as the "green housing estate." the philosophy of this concept is to reduce co2 emissions through green elements. besides the possibility of revitalization of public green spaces, which has the ability to absorb co2 emissions it is also an appropriate solution for implementation of green roofs on residential buildings. together with smart public lighting this model area could become greener and a more ecological environment for its residents. summary based on the calculation of the energy consumption of residential buildings in the solved area and the subsequent production of co2 emissions, we concluded that one of the most effective tools for reducing emissions is the complex renewal of residential buildings. by using building renewal could be decreased co2 emissions by up to a quarter. by using other technological and technical interventions such as green roofs, smart street lighting, public green revitalization, etc. the reduction of co2 in the area could reach more than 50%. 5. conclusion in order to bratislava achieve the smart city concept it needs to develop and implement mainly a comprehensive concepts a policies in the field of residential and nonresidential buildings, transport infrastructure, technical infrastructure, public spaces but also in the field of sustainable economy and governance. of course, main condition to achieve this effective sustainable development is the implementation of the latest materials, technologies and innovative concepts in each of these areas, whether in the field of urban development, ict and construction and architecture, etc. in this would help to bratislava a generous funding from the european funds, the potential of which the city does not know sufficiently take full advantage. this could help the generous funding from the european funds, the potential of which the city does not know to sufficiently take full advantage. precisely in these areas bratislava could take inspiration from the sister city of vienna and amsterdam, which actual projects and its approaches to them could be considered as an exemplary direction of sustainable development of a modern european city. references [1] mori, k., christodoulou, a. (2012) review of sustainability indices and indicators: towards a newcity sustainability index (csi), environmental impact assessment review, vol. 32, no. 1,pp. 94-106. [2] albino, v., et al. 2015. smart cities: definitions, dimensions, and performance. available on: http://www.academia.edu/8958101/smart_cities_definitio ns_dimensions_performance_and_initiatives [3] o’grady, m., o’hare, g. (2012) how smart is your city?, science, vol. 335, no. 3, pp. 1581-82. [4] available on: (2015): www.smart-cities.eu [5] giffender, r., fertner, c., kramar, h., kalasek, r., pichler-milanović, n., meijers, e. (2007) smart cities: ranking of european medium-sized cities. vienna: centre of regional science – vienna ut. [6] gabriel cretu, l. (2012) smart cities design using eventdriven paradigm and semantic web. informatica economica, vol. 16, no. 4, pp. 57-67. [7] kourtit, k. & nijkamp, p. (2012) smart cities in the innovation age. innovation: the european journal of social sciences, vol. 25, no. 2, pp. 93-95. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e5 the challenge for the development of smart city concept in bratislava based on examples of smart cities of vienna and amsterdam 11 [8] rucinska s., knetova j. (2014). development planning optimalization of the košice city in the context of the smart city and city region conceptions. 5th central european conference in regional science – cers, 2014. available on: http://www3.ekf.tuke.sk/cers/files/zbornik2014/pdf/rucin ska,%20knezova.pdf] [9] iso/iec jtc 1, information technology. smart cities, preliminary report 2014. iso 2015, published in switzerland. available on: http://www.iso.org/iso/smart_cities_report-jtc1.pdf [10] smart city wien, framework strategy (2014). city of vienna. vienna city administration, 2014. isbn 978-3902576-91-0 [11] 2014 quality of living worldwide city rankings – mercer survey. united states, new york, 2014. available on: http://www.mercer.com/newsroom/2014quality-of-living-survey.html#city-rankings [12] cohen, b. (2014) the 10 smartest cities in europe. fast company & inc, 2015 mansueto ventures llc. available on: http://www.fastcoexist.com/3024721/the-10-smartestcities-in-europe [13] cohen, b. (2014). the smartest cities in the world. fast company & inc, 2015 mansueto ventures llc. available on: http://www.fastcoexist.com/3038765/fast-cities/thesmartest-cities-in-the-world [14] cohen, b. (2014) the smartest cities in the world 2015: methodology. fast company & inc, 2015 mansueto ventures llc. available on: http://www.fastcoexist.com/3038818/the-smartest-citiesin-the-world-2015-methodology [15] smart parking amsterdam smart city (2015). available on: http://amsterdamsmartcity.com/about-asc [16] city-zen. amsterdam smart city (2015) available on: http://amsterdamsmartcity.com/projects/detail/id/64/slug/s mart-parking [17] city-zen. amsterdam smart city (2015) available on: http://amsterdamsmartcity.com/projects/detail/id/78/slug/ci ty-zen [18] photo (2015). available on: http://www.konzervativnyvyber.sk/v-bratislave-sa-dennepreda-12-novych-bytov-kupuju-sa-z-papiera/6093/ [19] finka, m., golej, j., jamečný, ľ., ladzianska, z., ondrejička, v., baloga, m., schweigert, m., tóth, (2012). metodika komplexnej obnovy sídlisk s dôrazom na obnovu bytových domov: 1. 2. 3.etapa. bratislava: stu v bratislave. ústav manažmentu, 2012. 248 p. [20] liptáková, j. (2014). making bratislava a smart city. the slovak spectator. available on: http://spectator.sme.sk/c/20049863/making-bratislava-asmart-city.html [21] eu-gugle (2015). available on: http://eu-gugle.eu/pilotcities/bratislava/ [22] špirková, d., golej, j., panik, m. (2014). the issue of urban static traffic on selected examples in bratislava in the context of economic sustainability. international conference on traffic and transport engineering ictte 2014. 27th – 28th november 2014. belgrade, serbia. isbn 978-86-9161531-4 [23] photo (2015). available on: http://bratislava.sme.sk/c/8011526/parkovanie-v-petrzalkestarosta-bajan-podliezol-zakon.html [24] methodology of traffic capacitive impact assessment of investment projects (2014). the annex to decision of the mayor of the capital city of the slovak republic, bratislava. 16 p. [25] vittek, p. (2014). aby aj o peniazoch rozhodovali ľudia. p e r e x , a. s. available on: http://nazory.pravda.sk/osa/clanok/322462-aby-aj-openiazoch-rozhodovali-ludia/ [26] samospráva spúšťa digitálne zastupiteľstvo (2015). hlavné mesto sr bratislava. available on: http://www.bratislava.sk/samosprava-spusta-digitalnezastupitelstvo/d-11048590/p1=11049947 [27] hrabošová, a. 2016. možnosti znižovania produkcie co2 v bývaní v sr v kontexte súčasnej európskej politiky. stu v bratislave. [28] ministerstvo doprav, výstavby a regionálneho rozvoja slovenskej republiky, mdvrr sr, 2008. available on: http://www.telecom.gov.sk/index/open_file.php?file=vysta vba/vedadokumenty/realvyskulohy/zasahnosnkonst003 391a.pdf eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e5 a. adamuscin, j.golej and m. panik 12 appendix a. smart cities benchmarking indicators [14] eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e5 the challenge for the development of smart city concept in bratislava based on examples of smart cities of vienna and amsterdam 13 appendix b. the total average energy consumption and co2 production of renewed and non-renewed residential buildings type of apartment building number of buildings number of households the total average consumption of renewed buildings [kwh] (2012-2014) the total average consumption of nonrenewed buildings [kwh] (2012-2014) the resulting value of co2 of renewed buildings (20122014) [t] the resulting value of co2 of non-renewed buildings (20122014) [t] average percentage of co2 production of renewed buildings on non-renewed a 9 768 496782,74 512181,08 100,002 103,102 15,90% b 4 192 254500 288715,56 51,231 58,118 c 25 1440 262656,93 391430,5 52,873 78,795 source: authors eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e5 emulating vehicular ad hoc networks for evaluation and testing of automotive embedded systems manuel schiller, alois knoll robotics and embedded systems department of informatics technische universität münchen {manuel.schiller,knoll}@in.tum.de abstract the evaluation and testing of cooperative applications based on vehicular ad hoc networks (vanets) in real testbeds is difficult due to the need for repeatable scenarios and largescale experiments. therefore a novel virtualization-based framework is presented to evaluate automotive software in the context of emulated vanets. the approach enables the precise and large-scale evaluation of real-world implementations through the synchronized execution of network and vehicle simulators as well as the applications encapsulated in virtual electronic control units. this paper provides a detailed description of the framework’s structure and its components as well as an validation of the proposed synchronization algorithm. the performance comparison with pure network simulation indicates that despite additional overhead large-scale experiments can be conducted without loss of accuracy. keywords vanet, embedded system simulation, testing, evaluation, network emulation categories and subject descriptors i.6.5 [simulation and modeling]: model development; i.6.7 [simulation and modeling]: simulation support systems; c.2.1 [computer-communication networks]: network architecture and design—wireless communication 1. introduction vehicular ad hoc networks (vanets) have attracted a lot of research attention over recent years due to the potential improvements in traffic safety and efficiency as well as driver comfort. a high variety of applications, commonly referred to as advanced driver assistance systems (adas), such as cooperative driving and subsequently automated driving, are enabled through wireless ad hoc communication between the vehicles on the road. simulation is currently the key methodology to gain an understanding of the various effects that influence the performance and behavior of the entire system composing a vanet. the majority of publications focuses on exploring the lower-level effects such as wireless signal propagation at the physical layer, medium access control and ad hoc routing protocols. the actual applications which are intended to run on top of these layers are usually either left out completely or are only modeled on a very abstract level. however, these applications, which often exhibit safety-critical features, need to be evaluated and tested extensively before deployment in series production. while it is theoretically possible to develop simulation models of the actual implementations and execute them in the established simulators, this approach quickly gets infeasible for complex real world applications. at the other end of the spectrum of available methods real world test drives using physical testbeds of prototype vehicles offer the highest degree of realism. due to the large amount of resources needed for real world test drives, this method is not feasible to perform large-scale and extensive testing of vehicular networks. additionally, achieving repeatable test conditions is next to impossible. in the automotive industry the use of simulation is well established in the development process of traditional driver assistance and active safety systems. however, the current emphasis is primarily on the simulation of individual vehicles at a very high level of detail [6]. when investigating and evaluating the performance of adas based on vehicular communication, this isolated view of a single vehicle in the simulation is not sufficient anymore. potentially every vehicle equipped with wireless communication technology is coupled in a feedback loop with the other road users participating in the vehicular network. therefore the number of relevant intelligent entities which need to be taken into account is drastically increased. to help bridging this gap we present in this paper a new virtualization-based approach for emulating vehicular ad hoc networks as the enabling methodology for evaluating and testing network-centric automotive embedded systems based on this wireless communication technology. our approach ensures that the actual implementations rather than models are employed in the test procedure taking into account the overall system context. by eliminating the need to create such simplified abstractions, testing can be performed earlier and without potential mismatches between the application and its model. simutools 2015, august 24-26, athens, greece copyright © 2015 icst doi 10.4108/eai.24-8-2015.2261004 complex drivers ecu hardware microcontroller abstraction layer services layer application layer autosar operating system (os) runtime environment (rte) ecu abstraction layer application software component application software component application software component application software component figure 1: overview of the autosar layered architecture the remainder of this paper is organized as follows: the testing and evaluation of real-world implementations of adas imposes a certain set of additional requirements, which are discussed in section 2 before giving an overview of the related work. the general concept and architecture of our emulation approach are described in section 3. in section 4 we evaluate the performance and scalability of our approach by means of an exemplary scenario and discuss its benefits and limitations. section 5 concludes the paper and gives an outlook of future work. 2. background and related work before we proceed to the discussion of related work, it is essential to illustrate our scope and area of application as well as the resulting requirements. in order to evaluate and validate real implementations of adas in a simulated, virtual environment, a holistic view of the vehicular ad hoc network comprising the three domains vehicle, network and application is necessary. in contrast to existing approaches we aim to not only cover the network characteristics but also the behavior of the vehicles and the network-aware applications in high fidelity. a high fidelity representation of an application means that the actual code as well as the context in which it is executing must be integrated into the overall simulation. unlike traditional pc-based software, driving assistance systems are typically executed on embedded hardware platforms and must comply with hard real time requirements. a specific software architecture called autosar was developed by the automotive industry for this specific purpose, which defines a generalized architecture for electronic control units (ecus). as shown in figure 1 this model features a separation into multiple layers. autosar also contains the definition of an embedded real time operating system as well as the possibility to define custom interfaces and runtime behavior in a formal description. the different components of an ecu, e.g. application software components (swc), can be developed separately from each other and are combined to the desired overall functionality later on. a key benefit of autosar is the standardization of hardware abstraction layers, which enables hardware-independent development and portability of the majority of an ecu’s software. we will exploit this hardware abstraction in our emulation framework to provide a realistic execution environment for the evaluation of network-based applications. in order to state the fundamentals of this investigation we give a brief overview of existing approaches for vanet simulation and network emulation in the following sections. 2.1 vanet simulation the usual strategy to simulate vanets found in literature is to bidirectionally couple a network simulator and a microscopic traffic simulation. following this approach the interactions between road traffic and network protocols are represented and the mutual impact can be explored [15, 12]. a number of vanet research simulation frameworks which employ this coupling strategy have been developed. they allow researchers to focus on their specific area of interest, i.e. low-level networking such as medium access or high-level concepts of applications such as lowering co2emissions or reducing traffic jams. in veins [15] the application behavior is directly incorporated into the network simulator as a high-level and simplistic model. while vsimrti [13] and itetris [11] provide specific interfaces for integrating vanet applications into the simulation context, adapting real-world implementations of automotive embedded software to these interfaces requires code modifications. since large-scale simulations are usually conducted to perform a statistical analysis of the simulation results, efficient but rather simplistic microscopic traffic simulators are used to generate realistic mobility models. when testing and evaluating real adas implementations a more detailed representation of a vehicle’s state including its sensors and actuators in the simulation is absolutely vital. 2.2 network emulation network simulation and real world testbeds are the usual methodologies for evaluating network protocols and applications. due to the simplifications performed in simulators regarding application models as well as the costs and insufficient repeatability in testbeds, it is desirable to combine the strengths of both methodologies in a network emulator. the original definition of network emulation by fall [5] covers the real time coupling of a discrete event network simulator and hardware executing real implementations of software prototypes. in a wider sense, network emulation can be defined as a hybrid experiment technique that combines both real and simulated network components with real referring to either hardware or software components [1, p. 14]. when the network simulation can not be executed fast enough due to complex models and high node counts, simulation overload causes the network simulator to lag behind the real time execution of the software prototypes and thus invalidates the results of the network emulation [19]. since computational resources can usually not be increased infinitely to speed up the network simulation, several attempts have been made to slow down the execution of the real world implementations to match the execution speed of the network simulation. a common approach is to exploit virtualization to decouple the time perception of the software prototype from the wall clock time [19, 16]. the run-time behavior of such a virtualized system is under full control, so it can be synchronized with the network simulation in virtual time. network emulation based on virtualized pc operating systems such as linux is widely established for evaluating pc-based software, however this methodology is yet novel in the research area of automotive embedded systems and inter-vehicular networks. 3. emulating vehicular ad hoc networks we now present the design and implementation of our emulation framework. after describing the overall concept we explain in detail the four components of which the framework is composed. 3.1 conceptual overview our framework is designed to provide a generic emulation platform for evaluating real implementations of adas which are based on vehicular network communication. the main goal is the support of executing unmodified applications in a high-fidelity and accurate representation of the vanet. the underlying concept is based on the feedback coupling of detailed subsystems for each of the relevant domains constituting a vanet, i.e. the physical domain of each vehicle, the logical domain embodied by the applications running on the ecus as well as the communication network connecting the vehicles through the wireless channel. figure 2 shows the three relevant domains as well as the data flows between those subsystem representations in a conceptual overview of the emulation framework. for reasons of clarity, the data flow from vehicle simulator to network simulator is not depicted but the node positions in the network simulator are kept consistent with the vehicle simulator. swc swc rte os bsw swc swc rte os bsw swc swc rte os bsw vehicle simulator network simulator network packet exchange proxy node simulated wireless channel simulated nodevehicle data exchange ecu virtualization figure 2: conceptual overview of the emulation framework in order to allow evaluation and testing of unmodified applications, the emulation framework needs to provide an execution environment which is as close as possible to the real system on which the applications will be deployed in series production. this could be achieved by representing the logic domain by real hardware ecus executing the software prototypes. however, this approach is infeasible for the following reasons: the development process in the automotive industry is characterized by concurrent engineering in order to shorten the time to market. in the given context this especially covers the parallel design and development of both ecu hardand software, which results in only relatively late availability of the hardware and would thus delay testing of the software prototypes. additionally, conducting large-scale scenarios would require a large number of ecus as well as a high logistic effort for setting up and performing the actual experiments. last but not least, the aforementioned simulator overload resulting from complex models and high node counts in the network simulator can invalidate the evaluation results. for these reasons we choose to integrate virtualized ecus (vecus) as the representation of the logical domain into the overall emulation framework. this approach solves the dependency on hardware availability and the scalability issues and allows us to decouple the emulation from the real time constraint by synchronizing the time progression of the software prototypes with the execution speed of the other simulators. 3.2 network simulation the network simulation is used to model the wireless communication network connecting the vehicles and the applications running on their ecus. as shown in figure 2 each virtual ecu is represented by a proxy node in the network simulation domain. the proxy node acts as a communication endpoint to initiate the simulated transmission of network packets as well as to receive network packets transmitted by other network nodes. additionally, fully simulated nodes can be included, which may for example represent intelligent infrastructure such as traffic lights. we apply the vertical emulation concept which is defined in [7] and also referred to as a split stack in [14]. the network stack is separated into two parts where the upper layers (including the application layer) belong to the vecus, while the lower layers are realized by the network simulator. to offer the highest degree of generality and flexibility, the emulation boundary, i.e. the layer at which the network stack is split up, is drawn at the medium access control (mac) layer. this allows to evaluate arbitrary routing and transport layers as well as the application functionality, which are typically implemented in software and executed in the vecu. network packets generated by these layers are captured at the virtual network interface controller (vnic), which is described in the next section. the packets are then injected into the corresponding proxy node, traverse the simulated mac and physical (phy) layer and are then potentially received in reverse order at other nodes after the simulated transmission has been performed by the network simulator. the proxy nodes therefore handle all lower layer functionality that is usually performed by hardware. this hybrid emulation approach is shown in figure 3. in order to enable communication between fully simulated nodes and vecus above the mac layer, the fully simulated nodes need to have compliant implementations of the relevant vanet protocols (e.g. routing protocols such as geonetworking) and, if necessary and applicable, also application models which can act as traffic sources, e.g. transmitting periodic beacons. simulated wifi channel discrete event network simulator ecu virtualization simulated 802.11 phy simulated 802.11 mac proxy node vnic swc swc rte os bsw figure 3: hybrid vehicular ad hoc network emulation the event-driven network simulator ns-3 is chosen to perform the actual network simulation of the wireless communication domain. ns-3 features an open-source modular architecture that can be extended quite easily. a rich number of simulation models is already available in ns-3, of which we employ the wifi models and specifically the 802.11p mac layer model [2]. network packets in ns-3 are represented as binary packets in network byte order that match their real-world counterparts, so it is possible to directly exchange packets between simulation nodes and external systems without the need for any packet translation through the proxy nodes and a custom data-exchange interface. to allow synchronization of the network simulator with the other domain representations we implemented a custom event scheduler which can be controlled from the outside. in contrast to the default implementation this scheduler executes only those events whose associated simulation time is below a given boundary in virtual time. when this boundary time is reached or a network packet is received by a proxy node, event execution is suspended and the time of the next event in the network simulator’s queue is reported to the outside. the synchronization algorithm is described in detail in section 3.5. 3.3 ecu virtualization as described in section 3.1 our emulation platform is based on the virtualization of ecus. while there are various approaches available for virtualizing such embedded systems, the method of choice is justified by two main reasons. the final hardware design of an ecu is usually determined rather late in the development cycle. therefore important details such as processor architecture, core count etc., which are vital for a detailed modeling of the underlying hardware, are missing until the hardware is specified. additionally, detailed instruction set or even cycle-accurate simulations require a high computational effort, which conflicts with our goal to conduct large-scale evaluations. we have thus chosen the rather hardware abstract approach etas virtual ecu1 which allows us to put the emphasis not on one single, highly-detailed modeled ecu but on the overall system of connected vehicles. this tool enables us to create virtual ecus based on a formal autosar architectural model and the hardware independent c code. this approach can be described as host-compiled paravirtualiza1http://www.etas.com/en/products/isolar eve.php tion [3] where the hardware-abstraction layers of autosar are exploited by porting those abstraction layers as well as an autosar compliant operating system to a standard pc operating system such as linux. this allows the execution of a vecu on a traditional desktop pc on top of the host operating system rather than interacting directly with the actual hardware. a vecu is compiled into a selfcontained executable that can be instantiated as often as necessary, which enables performing large-scale evaluations. each vecu is run as a separate process which has its own virtual hardware (e.g. interrupt controller) modeled on an abstract functional level. in the following we describe the execution concept of a vecu. the execution is stimulated by an internal clock or through virtual interrupts. the internal clock can either progress with respect to the wall clock when running in real-time mode or clock ticks can be injected from the outside, which allows full control over the execution of the vecu. due to the fact that the virtual ecu is executed only on a rather abstract hardware model and since the compiler for the host pc is different from that of the target platform, the execution durations of individual tasks are not representative. we thus interpret the execution of vecu tasks as discrete events which means that a task is executed by an infinitely fast processor in terms of simulated time, as time does not progress during the execution of a task. this assumption leads to the fact that preemption of tasks by higher priority tasks or interrupts does not occur, however considering these scheduling effects only makes sense if a more detailed model of the target platform is available. 0 p ri o ri ty isr task5ms task10ms time (ms) 5 15 2010 execution time preemption interrupt discrete event activation 1 2 3 4 7 5 6 8 figure 4: timing behavior comparison of virtualized ecu figure 4 shows the timing behavior during normal execution and when assuming task activations as discrete events by means of an exemplary ecu, which has two cyclic tasks and one interrupt service routine (isr). during normal execution, tasks can be preempted by tasks of higher priority, which is not accounted for when activating the task execution as discrete events. task activations and interrupt handling are modeled by the discrete-event execution in the correct order but conclusions about the timing behavior of the target hardware platform cannot be drawn. the duration in terms of virtual time between two clock ticks is arbitrary, so the time resolution is configurable for the desired accuracy. by default this time span is set to 1 ms. the discrete event interpretation allows to achieve deterministic and repeatable evaluation of the software implementation under test because influences stemming from the host operating system do not have an impact on the timing behavior of the virtual system. a vecu can communicate with the outside world through virtual hardware devices. since there is yet no standardized integration of vanet hardware in the autosar architecture we have integrated the virtual wireless network interface (vnic) using a complex device driver as shown in figure 5. the vnic redirects the network packets originating from the vecu to the corresponding proxy node in the network simulator. it also offers the interface to inject network packets into the vecu which have arrived at the proxy node. when a packet is injected into the virtual network device, an interrupt in the vecu is raised and in the corresponding isr the packet can be handled by a custom network stack implementation and the autosar software components. vanet complex device driver application layer autosar os runtime environment software component vnic driver vnic figure 5: integration of the virtual network device into the vecu architecture 3.4 traffic and vehicle simulator as stated in section 2.1 the microscopic vehicle models which are usually employed for conducting vanet simulations are not detailed enough for our purpose. the vehicle dynamics as well as actors and sensors need to be modeled in sufficient detail and accuracy in order to supply all necessary state variables to the real implementation of the adas under evaluation. we therefore employ the nanoscopic traffic and vehicle simulator vires virtual test drive (vtd) for the high-fidelity simulation of the physical domain of the vehicles. vtd has been developed for the automotive industry as a virtual test environment used for the development of adas [18]. its focus lies on interactive high-realism simulation of driver behavior, vehicle dynamics and sensors. vtd is highly modular, so any standard component may be exchanged by a custom and potentially more detailed implementation. its standard driver model is based on the intelligent driver model [17], however an external driver model may be applied if necessary. the same concept applies for the vehicle dynamics simulation, where the standard single-track model can be substituted by a complex vehicle dynamic model adapted for specific vehicles. each simulated vehicle can be equipped with arbitrary simulated sensors, for example radar sensors or synthetic video cameras. vtd offers proprietary interfaces to control the simulation execution in a time driven manner as well as to extract the simulation state after the computation of a simulation step. 3.5 simulation synchronizer & scheduler the three described domain representations are either timedriven (vehicle simulator), event-driven (network simulator) or both (vecus). in order to achieve a deterministic cosimulation comprised of all three domains, the subsystems must be synchronized. the simulation synchronizer & scheduler (sss) ensures that the execution of the subsystems is synchronous so that no time drifts can occur as well as causality errors, i.e. executing events from the past, are avoided. since none of the system representations allows to perform rollbacks, an optimistic synchronization algorithm cannot be used; we therefore choose a conservative synchronization algorithm. sss maintains a global event list to determine which system representation is to be scheduled next. after the execution of a system representation is completed, this system is rescheduled when it is due the next time. the determination of this next time depends on the respective system. the vehicle simulator is scheduled once every time step tveh which is configurable for the vehicle simulator. the execution of the vecus can be scheduled every tick ttick which corresponds to the time resolution of the vecus as described in section 3.3. in order to reduce synchronization overhead, the task activation behavior of the vecus, which is contained in the autosar architectural model, can be exploited. if a vecu’s minimum task activation period is tvecu,min, this value can serve as the rescheduling period without sacrificing accuracy. the custom scheduler implementation of the network simulator reports its next event time as described in section 3.2 which serves as the next event time in the global event list of sss for the network simulator. in order to avoid causality errors, the network simulator is only allowed to progress in virtual time until the next vecu will be executed again. this boundary is also derived from the global event list. we illustrate the synchronization algorithm by the sequence diagram in figure 6, which shows the exemplary scenario of two vecus which send ping requests and replies over a simulated wireless channel. for reasons of simplicity the vehicle simulator is left out. the transmission durations in this example are purely fictional and listed for demonstrative purposes only. the vecus in this example exhibit a task activation period of tvecu,min = ttick = 1.0 ms. initially the two vecus execute one tick of virtual time in parallel. vecu2 sends a ping request at time t = 1.0 ms contained in network packet p to vecu1. packet p is captured at the vnic of vecu2 and is then sent to sss which forwards it to the network simulator. this causes the enqueuing of an ns-3 event which injects the packet into the network simulation at t = 1.0 ms through the proxy node associated with vecu1. ns-3 is now allowed to execute events until t = 2.0 ms, which leads to the transmission of p on the simulated wireless channel. at time t = 1.2 ms packet p is received at the proxy node, which corresponds to vecu1. this suspends the execution of events inside the network simulator and packet p is delivered through the sss to vnic of vecu1, which triggers an interrupt. the corresponding isr handles the packet in the network stack and sends a ping reply in a response packet r which travels the exact opposite way back to vecu2. figure 6: synchronization of virtual ecus and network simulation in our implementation, the system representations do not communicate directly with each other but through the sss. the underlying federation concept is derived from the high level architecture (hla), a generic framework for distributed simulations [9]. each system representation is connected to the sss by means of a specific ambassador software component which is responsible for message exchange in both directions as shown in figure 7. these messages involve both the synchronization and the exchange of simulation state data as depicted in figure 2. the ambassadors translate the messages from sss to the respective subsystem and vice versa. this allows to replace any given subsystem by either another software implementation or even by real hardware by modifying just the corresponding ambassador. the flexibility of the architecture also makes it possible to add additional simulators to the overall simulation and to distribute the system representations on multiple machines. figure 7: implementational overview of the emulation framework 4. evaluation and discussion in the following we evaluate the proposed framework by means of a synthetic scenario to examine the timing accuracy and performance with regard to scalability. we then discuss the universal applicability of our approach as well as its limitations. 4.1 evaluation scenario and setup the evaluation is performed by comparing the framework’s results and performance with pure network simulation. in order to achieve a good comparability we chose to use the previously described ping scenario with static node positions. in this scenario there are n = 2k nodes where each node i ∈ [1, k] pings another node j ∈ [k + 1, n] over a simulated 802.11p wifi channel with an interval v between requests. we integrated the open source ip stack lwip [4] (version 1.4.1) in the autosar vecu, which is straightforward due to it being implemented in c. all experiments were carried out on a single machine equipped with an 3.6 ghz intel xeon cpu, 16 gb ram on a 64 bit linux 3.16 kernel using ns-3 version 3.22 and etas isolar-eve version 2.2. 4.2 accuracy and scalability to validate the correct synchronization behavior of our global event scheduler we performed the above described scenario once in ns-3 alone without the sss and any vecus being attached, so all nodes were fully simulated. the same scenario was then run in our emulation framework with each node now configured as a proxy attached to a vecu instance. the transmissions were simulated on a 802.11p wireless channel at 5.9 ghz. the node count was set to n = 20 and the ping interval to v = 10 ms. figure 8 shows an excerpt of the captured round trip times resulting from both the simulation and the emulation experiment between a corresponding pair of nodes. the round trip times vary due to the interference of competing transmissions between the other node pairs on the shared wireless medium. the resulting round trip times are identical for both experiments, which demonstrates that the scheduling of vecus and network simulation in our emulation framework is performed correctly and deterministically. simulation time [ms] 3000 3100 3200 3300 3400 3500 3600 3700 3800 3900 4000 ro u n d t ri p t im e [ m s ] 0 0.5 1 1.5 2 2.5 pure simulation emulation with vecus figure 8: round trip times in simulation and emulation before comparing performance of simulation and emulation we ran the scenario with network simulation disabled. this setup allows to examine the influence of the synchronization tightness by either scheduling the vecus every ttick = 1 ms or every tvecu,min = 10 ms. figure 9 shows the impact of the different synchronization periods. while 40 vecus can be run synchronously in real time in our framework when using the 10 ms period, the synchronization overhead of the 1 ms period is clearly visible and the real-time boundary is crossed when executing more than 24 vecus. in order to quantify the computational overhead in comparnumber of vecus 5 10 15 20 25 30 35 40 d u ra ti o n [ s ] 0 5 10 15 20 real-time boundary sync 1 ms sync 10 ms figure 9: performance comparison of vecu synchronization periods ison with the network simulation, which is introduced by our framework, we conducted a series of experiments with increasing node counts for both the simulation alone and the emulation and measured the real-time duration for each configuration. each configuration was run 10 times for a duration of 10 s of simulated time and the number of node pairs k was increased from 1 to 24. figure 10 shows the durations for the simulation in ns-3 alone as well as for the emulation with the two different synchronization periods of the vecus when running the ping scenario with an interval of v = 100 ms between ping requests. this results in a message frequency of 10 hz, which is typical for cooperative awareness in vanet applications [8, p. 275]. the pure simulation obviously performs fastest since no additional synchronization is necessary. the synchronization overhead, which the emulation results exhibit, stems from the fact that the vecus and the network simulation are executed sequentially when sending and receiving network packets to guarantee a correct and deterministic co-simulation. number of node pairs k 5 10 15 20 d u ra ti o n [ s ] 0 10 20 30 40 50 pure simulation emulation sync 1 ms emulation sync 10 ms figure 10: performance comparison between simulation and emulation the computational effort which is necessary to perform the network emulation depends on multiple factors. the synchronization period of the vecus only shows a rather slight impact on the overall duration, whereas the number of nodes represented by vecus as well as the amount of messages transmitted and received by vecus affect the performance the most. another factor, which is not examined here, is the actual workload of each vecu. if the adas under evaluation performs complex calculations, this will lead to an additional increase of computational requirements. 4.3 discussion the above shown evaluations state that our framework allows to accurately evaluate and test real-world implementations of vanet applications. the overhead introduced by executing vecus for each node as well as synchronizing the three subsystem representations leads to longer simulation durations. however since the simulation is decoupled from the real-time constraint, the accuracy of the results is not affected even when conducting large-scale experiments. in the following we will discuss the universal applicability of the approach as well as its limitations. the chosen virtualization method generally allows to integrate unmodified source code of the adas implementations. however, due to the paravirtualization it is necessary to compile the code to run on the x86 host architecture. typically, software components developed for the autosar architecture are written in ansi c. due to the autosar hardware abstraction layers, they are independent from the underlying hardware which allows to re-compile the code for the x86 architecture without code modification. however, if the standardized interfaces of the autosar architecture are bypassed somehow, the source code may need to be modified. additionally, if source code is not available, e.g. due to ip protection, closed source components can be integrated as precompiled x86 libraries. while we focus on ad hoc communication based on ieee 802.11p, our concept is agnostic to the underlying network topology and transmission medium. this allows to evaluate the network-based adas on other radio technologies such as ad hoc lte only by changing the configuration of the network simulator to apply other simulation models for the phy and mac layer. in our examples we only consider one ecu per vehicle, however the approach is flexible enough to allow the integration of multiple ecus per vehicle and, given that suitable models exist, even the simulation of intra-car networks such as can. since the chosen virtualization approach assumes no detailed knowledge of the target hardware, hardware characteristics which might influence the timing behavior are not taken into consideration. delays which are caused by the target hardware are neglected, which is a limitation of our current implementation. we regard the modeling of hardwareintroduced delays as future work which can be approached by instrumenting and tracing execution on real hardware platforms once they are available in the development process [10]. 5. conclusion in this paper we proposed a novel approach for emulating vehicular ad hoc networks for evaluation and testing of network-aware automotive embedded systems. the presented methodology employs virtualization to allow the integration of real-world automotive software into the overall simulation consisting of the three coupled subsystem representations of the physical, application logic and wireless networking domain. this enables the detailed analysis of network protocol and application implementations in the context of a realistic runtime execution provided by an autosar compliant embedded operating system. a global simulation scheduler synchronizes the execution of all domain representations to achieve a deterministic and correct experiment execution. the evaluation shows that the emulation generates accurate results by synchronously executing the software components encapsulated in virtual ecu instances and the other simulators. the approach allows to perform detailed and large-scale evaluations early in the product development cycle without being dependent on the availability of real hardware. as our next steps we plan to integrate an industry implementation of a car2car communication stack into our proposed virtual prototype solution as well as tackle the area of 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[19] e. weingärtner, f. schmidt, h. vom lehn, t. heer, and k. wehrle. slicetime: a platform for scalable and accurate network emulation. in proceedings of the 8th usenix symposium on networked systems design and implementation (nsdi ’11), boston, usa, march 2011. medical data analytics and wearable devices 1 medical data analytics and wearable devices iswarya manoharan1,*, jeslin libisha j2, sowmiya e c3, harishma s4, john amose5 1pg scholar, masters in industrial bioengineering, university of naples federico ii, italy 2assistant professor, department of biomedical engineering, dr. n.g.p institute of technology, coimbatore, india 3assistant professor, department of biomedical engineering, karpaga vinayaga college of engineering and technology, chennai, india 4assistant professor, department of biomedical engineering, kalaingar karunanidhi institute of technology, coimbatore 5assistant professor (sr.g), department of biomedical engineering, kpr institute of engineering and technology, coimbatore, india abstract clinical decision-making may be directly impacted by wearable application. some people think that wearable technologies, such as patient rehabilitation outside of hospitals, could boost patient care quality while lowering costs. the big data produced by wearable technology presents researchers with both a challenge and an opportunity to expand the use of artificial intelligence (ai) techniques on these data. by establishing new healthcare service systems, it is possible to organise diverse information and communications technologies into service linkages. this includes emerging smart systems, cloud computing, social networks, and enhanced sensing and data analysis techniques. the characteristics and features of big data, the significance of big data analytics in the healthcare industry, and a discussion of the effectiveness of several machine learning algorithms employed in big data analytics served as our conclusion. keywords: wearable technology, decision making, rehabilitation, artificial technology, data analytics. received on 30 july 2022, accepted on 05 september 2022, published on 11 october 2022 copyright © 2022 iswarya et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i4.2264 *corresponding author. email: iswaryamanoharan1997@gmail.com 1. introduction with the introduction of new instruments for biomedical research and healthcare digitalization, data in current biomedical practise and research have been rising substantially. recent advances in wearable and big data technology have made it possible to collect and transform biomedical data in real time. by reducing the risk of damage, boosting doctor-patient communication, and exposing previously unseen scanning and sensory aspects, this has the potential to greatly improve healthcare services [1]. analyzing raw datasets for trends, conclusions, and improvement opportunities is the process of data analytics. healthcare analytics employs both recent and old data to produce macro and micro insights to help business and patient decision-making. improved patient care, quicker and more accurate diagnoses, preventive measures, more individualized treatment, and better decision-making are all made possible by the application of health data analytics. it can reduce expenses; streamline internal processes, and other things at the corporate level. health information is any information pertaining to a patient's or population's health. the many health information systems (his) and other technical tools utilised by government organisations, insurance companies, and healthcare practitioners are where this data is obtained. to obtain, store, communicate, and analyse health data, a number of technologies and systems are employed. every second, more and more health care data are available for analysis due to digital data collecting. there is a substantial amount of data being collected in real time due to the growth of electronic record keeping, applications, and other electronic ways of data collecting and storage. because of the complexity of these data sets, conventional eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e2 https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:iswaryamanoharan1997@gmail.com iswarya manoharan et al. 2 processing tools and storage techniques cannot be utilized. dealing with "big data" necessitates the use of cloud storage. cloud storage is designed to be secure, which is essential when working with private patient data. additionally, it is incredibly economical and has contributed to bringing down the rising cost of healthcare. wearable biosensors, often known as "wearables," have been used as part of a larger, interdisciplinary health care initiative to leverage mhealth to improve data collection, diagnosis, treatment monitoring, and health insights [5, 6]. among the key elements of smart cities is smart healthcare. the area of intelligent healthcare was created in order to better manage the healthcare industry, make better use of its resources, cut costs, and maintains or even raises quality levels. consumable and nonconsumable resources can be broadly categorised in the healthcare industry. consumable resources are those that degrade and run out over time, such as all tools and medical equipment. on the other side, non-consumable resources are those that do not deplete over time. human resources like doctors, nurses, registered nurses, and all other human capital involved in the healthcare process are included in the non-consumable resources. data is growing quickly by several orders of magnitude because of the promise of a smart city. as a result, the iot services are built around these enormous volumes of data, often known as "big data." a bluetooth-enabled in-home patient monitoring system is suggested by cheng and zhuang in [28], making it simpler to identify alzheimer's disease in its early stages. a medical professional can tell whether a target patient is getting alzheimer's disease based on the way they move. they have created a study that demonstrates the viability and practicability of the suggested in-home patient monitoring system. 2. why data analysis in medicine? anyone and everyone can see the effect covid-19 has had on the healthcare sector. the influence covid-19 has had on health care data analytics, however, is something that most people fail to see. according to health it analytics, "big data tools are now used more frequently in healthcare decision-making". big data analytics and predictive models are being used by politicians, academics, and healthcare practitioners to assist manage resources, forecast demand, enhance patient care and results, and implement preventive measures. the fight against covid-19 has benefited greatly from big data and health data analytics. the rate of data entry is almost constant. a greater understanding of how to react and treat patients has been made possible by the analysis of such health data. in recent years, the process of gathering data in healthcare settings has been streamlined. in addition to assisting in bettering daily operations and patient care, the data may now be used more effectively in predictive modeling. we can utilize both datasets to track trends and make forecasts rather than just focusing on historical or present data. we can now take preventative action and monitor the results. in medicine and healthcare, big data analytics can be used to examine huge datasets from hundreds of patients, and data mining techniques can be applied to build predictive models and discover correlations and clusters between datasets [2, 3]. a wide range of reasonably priced technologies has made it possible to continually or frequently monitor physiological parameters and follow changes in a patient's health state or across patient populations. numerous consumer wearables collect information on physiological characteristics like heart rate (hr), skin temperature, and peripheral capillary oxygen saturation in addition to location, physical activity, and other ambient environmental elements [7]. 3. data management in the healthcare an extensible big data architecture was created with the ability to handle a variety of situations, including the early diagnosis of diseases and the identification of emergencies [13]. her for electronic health records. it is made up of a variety of medical data that describes the patient's health state, including the patient's characteristics, prescriptions, diagnoses, lab results, doctor's notes, radiological records, clinical data, and payment notes. it also contains a complete patient medical history that has been digitally stored. for the aim of healthcare analytics, the ehr is a rich source of data. ehr also enables data exchange within the community of healthcare professionals [14]. the healthcare cloud is in charge of storing and retrieving this data. security manager and the health data store are two overlapping components of the healthcare cloud [15]. large-scale health data is typically challenging to manage and store using conventional tools and approaches. as a result, we require a system that can manage the volume and variety of such data. the proposed method accomplishes this by utilising a health data management system that has been deployed using a distinctive cloud database management system architecture [16]. edgecare is a safe and effective data management system for mobile healthcare systems. local authorities are set up to schedule edge servers for processing healthcare data and enabling data trading. a collaborative, multilevel structure is created for the practical implementation of edgecare. following that, a system-wide investigation into safe data exchange and streaming was conducted. in order to try and come up with the optimum incentive system for a consumers and information gathered in the ethical decentralised data trade, the stackelberg game-based optimization technique was also used. in order to show that edgecare provides effective solutions to safeguard healthcare data and facilitate effective data exchange, numerical results accompanied by security analysis are presented. in various circumstances, edge servers can carry out local network administration operations. eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e2 medical data analytics and wearable devices 3 for instance, they are employed to boost decentralised electric car charging and discharging management and to achieve distributed reputation management in vehicular networks [17], [18]. in order to create personal health records, wearable sensors and medical iot devices have lately started to collect personal life-long data (phr) [19]. real-time healthcare analytics enabled by patients, physicians, pharmaceutical researchers, and payers will all receive artificial intelligence (ai) in return. blockchain technology is an additional practical option for managing individual ehrs. for providing their health information to doctors and their research partners, patients can receive tokens as payment through the use of so-called "smart contracts." for instance, health wizz is testing a mobile ehr aggregator app with blockchain and fhir support, which tokenizes data using blockchains, allowing individuals to safely collect, organise, exchange, give, and/or sell their individual health information. in order to improve fostering interaction between healthcare organisations and caregivers and laying the groundwork for improved care, the goal is to give people the same simple control over personal health information as much control over your online financial accounts [20]. with the help of this platform, patients regain control over their personal information. in order to achieve security, accountability, and integrity, the main objective of this study is to retain patient's personal data on the blockchain. patients will have complete control over the blocks that will house their data. the lack of pseudonymity in current healthcare systems is addressed by our platform. "medibchain" will revive people' interest in healthcare while preserving the responsibility, authenticity, anonymization, privacy, and confidentiality that ehr systems are losing. in a smart city, big data applications can assist various industries by enhancing consumer experiences and providing services that make firms run more efficiently (e.g., higher profits or increased market shares). healthcare can be enhanced by enhancing patient care, diagnosis and treatment techniques, medical record management, and preventative care services. big data may assist transportation networks in becoming more environmentally friendly, adjusting to changing demand, and streamlining schedules and routes. 4. data analytics techniques 1. cluster analysis the term "cluster" refers to the activity of grouping a set of data components so that they are more comparable (in a certain sense) to one another than to those in other groupings. clustering is frequently used to discover hidden patterns in the data because there is no goal variable involved. the method is also applied to offer more context to a trend or statistic. 2. cohort analysis this kind of data analysis technique employs historical data to study and contrast the behaviour of a chosen subset of users, which can then be compared to that of other users who have similar traits. with the use of this methodology, it's possible to obtain a thorough understanding of a larger target market or a wealth of insight into customer wants. cohort analysis may be particularly helpful for marketing analysis because it can let you know how your efforts are affecting particular client demographics. consider sending an email campaign inviting users to register on your website as an example. you construct two copies of the campaign for this purpose, each with unique designs, ctas, and ad copy. later, you may follow the effectiveness of the campaign over a longer period of time using cohort analysis to learn which kinds of content are encouraging your customers to sign up, make repeat purchases, or take other actions. 3. regression analysis regression makes use of historical data to analyse how changing or remaining constant values of one or more independent variables affect the value of a dependent variable (linear regression or multiple regression). you may predict potential outcomes and make better judgments in the future by understanding the relationship between each variable and how they evolved in the past. 4. neural networks the neural network serves as the foundation for machine learning's clever algorithms. it is a type of analytics that makes an effort, with little assistance, to comprehend how the human brain would produce insights and forecast values. neural networks change and improve over time because they gain knowledge from each and every data exchange. 5. factor analysis the factor analysis, often known as "dimension reduction," is a method of data analysis that is used to express variation among seen, correlated variables in terms of a possibly smaller number of unobserved variables termed factors. here, the goal is to find independent latent variables, which is a great way to streamline particular parts. a customer review of a product is a useful example for comprehending this data analysis technique. the initial evaluation is based on a variety of factors, including colour, shape, wearability, modern trends, materials, comfort, location of purchase, and frequency of use. based on what you wish to track, the list could go on forever. 6. data mining a technique for analysing data that serves as a catch-all for engineering metrics and insights to provide value, focus, and context. data mining uses exploratory statistical analysis to find relationships, relations, patterns, and trends in order to produce advanced knowledge. adopting a data mining attitude is crucial to success when thinking about how to analyse data; as such, it is a topic worth exploring in more detail. 7. text analysis large collections of textual data are organised in a way that makes them manageable for text analysis, commonly known as text mining in the industry. you will be able to extract the data that is actually pertinent to your organisation and use it to create eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e2 iswarya manoharan et al. 4 actionable insights that will advance you if you carefully follow this purification process. 8. time series analysis a group of data points gathered over a predetermined time period is analysed using the time series method. the time series analysis is not the only technique used by analysts to gather data over time, even though it allows for more frequent monitoring of the data points than just intermittent monitoring. instead, it enables researchers to comprehend if variables changed over the course of the investigation, how the many variables are dependent, and how the study arrived at its conclusion. 9. decision trees making wise and strategic decisions can be supported by using the decision tree analysis. researchers and business users may quickly assess all the relevant aspects and determine the best course of action by visualising probable outcomes, effects, and costs in a tree-like model. decision trees can be used to examine quantitative data and improve decision-making by allowing you to identify chances for improvement, save costs, and increase operational effectiveness and production. 10. conjoint analysis the conjoint analysis is the last but certainly not least. this strategy is one of the most efficient ways to identify consumer preferences and is frequently used in surveys to discover how people value various characteristics of a good or service. conjoint analysis can be used to identify your customers' preferences, regardless of whether they are more concerned with pricing, features, or sustainability when making purchases. in this way, businesses can specify pricing plans, packaging choices, subscription plans, and more. 5. data analysis in iot iot sensor systems are constrained by their network bandwidth and processing speed. smart apps, on the other hand, a significant amount of information and processor speed are needed for dl-based research. to overcome these limitations, modern smart applications use deep learning (dl) research at the gateway or cloud [10]. applications demand input from users or other smart devices capable of bidirectional communication. the processing time needed by a computational intelligence (ci) algorithm that processes input is also greater than is available on constrained hardware [8]. the aged at home are susceptible to falling due to a variety of issues, including heart attacks, physical impairments, low blood pressure, etc. as a result, the rate of elderly falls also rises with age. in the modern world, elderly people utilize smart phones to call or text someone in an emergency. it is preferable to have an automatic fall detection system that can detect falls with accuracy and transmit an emergency message. in order to detect falls accurately, the system is built with accelerometer and gyroscope sensors. k-nearest neighbors (k-nn) and decision trees, two well-known machine learning algorithms, are used to categorize old people's daily behaviors into sleeping, sitting, walking, and falling [9]. a smart house is one that provides a variety of automated services based on internet of things (iot) gadgets equipped with sensors, cameras, and lighting. these devices can be remotely handled via remote controllers like those available on smartphones and smart speakers. in a smart home, iot devices collect and analyse data on motion, temperature, lighting control, and other variables. they also store more intricate and varied user data. although different smart home devices employ different methods for storing data, this information might be useful in forensic investigations, but it might be challenging to recover valuable information. as a result, it is crucial to gather data from different smart home devices as well as to recognise and examine data that might be used in digital forensics [11]. fog computing is a specialised software enhancement that isolates a few key operations and sends them to the consumer's edge. because of the unique circumstances surrounding the bulk of iot installations, many of these concerns brought by cloud computing are further addressed [12]. the sensor hub framework, which combines a number of technologies, is designed as a tool chain to support the creation of iot-related projects. sensor data is gathered, sent, processed, analysed, and supported for use in a variety of ways. the server side development, including data administration and processing, reporting, push notification, and data monetization, are available via a web browser because the framework is designed to be accessed through the platform as a service (paas) model. the solution's core strength and distinctiveness are found here. integrated development environments (ides) frequently only cover a small piece of the total data management process that the sensor hub handles, and they still need to be installed and maintained. 6. wearable devices the smart healthcare system (shs) uses wearables and implantable medical devices to continually monitor a patient's various vital signs and automatically identify and treat life-threatening medical disorders [24]. however, these expanding shs capabilities raise a number of security issues, and attackers can take advantage of the shs in a number of ways, including by interfering with its regular operation, injecting false data to alter vital signs, and tampering with a medical device to alter the course of a medical emergency [27]. the wireless body area network (wban), made up of wearable electronics, has as its primary objective the collection of physiological data from the human body. variable standards for various system components cause a significant problem at this stage in the communication process between a wireless sensor network (wsn) and wearable technology. one eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e2 medical data analytics and wearable devices 5 the one hand, zigbee or ieee 802.15.4 technology is used by sensor nodes to communicate. on the other hand, wearable technology typically utilises the bluetooth interface. this stage has been crucial because it is establishing a truly complete connection of diverse iotrelated specificities is essential. the development of a smart, comprehensive medical monitoring system with semi devices that can assess oxygen saturation and acceleration (spo2), and ekg was described by wanyoung et al. in [29]. figure 1 shows the data acquisition and transmission from the people to the physician and server storage. figure 1. data transmission a wearable device with minimum electrocardiogram, a motion sensor, and a blood oxygen saturation sensors board was integrated for user health monitoring. the technology sends physiological data to a base station connected to a computer to make it possible for access to the data across third party apps [30]. smart interactive watch together physical and learning data from school students. physical data includes heart rate, exercise intensity (number of steps taken while walking), frequency of activity, and learning data includes the number of times students raise their hands and respond to questions as well as the corresponding response time in personal or group competitions. it is also accountable for reporting such data to the cloud-based system and teacher-side application for additional analysis. the study is designed to determine the effect of the pupils' participatory outcomes from the proposed methodology on their academic performances. the interactive results are based on the data that the suggested system has gathered from the students' touch responses, team contests, incredibly quick answers, etc. 7. smart healthcare by establishing new healthcare service systems, it is possible to organise diverse information and communications technologies into service linkages. this includes emerging smart systems, cloud computing, social networks, and enhanced sensing and data analysis techniques. by incorporating individuals, procedures, cultures, norms, standards, metrics, and predictions, such systems may generate added features. electronic health records (big data), new mobile solutions, and cloudenabled smart healthcare systems all hold out unprecedented promise for providing efficient, smart, and affordable health care (such as innovative biosensors, wearable tech, and intelligent software agents) [21]. numerous stakeholders must be accommodated by healthcare services. in addition to assisting physicians, caregivers, and patients, services must also assist clinics, pharmacy, specialized suppliers, research universities, insurance, and service users. along with advocacy groups, research facilities, government agencies, state and local governments, and device makers, pharmaceutical, biotech, and it businesses are also present. consequently, collaboration between interdisciplinary teams is necessary for the greatest healthcare services. compared to the conventional software product development cycle, the product development cycle in healthcare is substantially longer, more regulated, and more expensive. to keep prices down, adhere to laws, and maintain timeliness, healthcare product companies must be cautious about their innovation strategy and product offers. information systems are positioned to produce, capture, store, process, and send timely information to all value partners for better healthcare coordination in addition to the inherent function of it in clinical and diagnostics equipment. the two primary areas of intelligent healthcare research are those that relate to patients and those that relate to processes. the research that focuses on wearable technology for patient data collection to be reported to medical institutions is included in the patient related category, although it is not restricted to it. the improvement of policies to guarantee many elements of the healthcare industry is a focus of process-related research. among these are a variety of process definition and management-related factors, such as resource scheduling, quality of service, and resource usage [22]. integration of all smart systems, including smart healthcare, is crucial for the delivery of a smart city. the use of cloud and edge computing is essential for the effective implementation of smart healthcare services. the suggested smart healthcare system's workflow and resource pools are established on the cloud, where the process is carried out and resources are allocated. each resource has a unique edge node that reports when a task eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e2 iswarya manoharan et al. 6 has been finished. the cloud scheduling algorithm will then redistribute the resource [25]. the suggested approach distinguishes between three emotional states: satisfied, dissatisfied, and indifferent. they used the one versus the rest strategy in the svm. there were several experiments performed. they tested the system utilising the speech signal alone, the picture signal alone, and the combined signals in several sets of experiments. during system training, the optimization and kernel parameters of the svm were fixed. they looked into the rbf and polynomial kernels of two svms. 8. conclusion big data analytics are widely used in the healthcare industry. data formats and big data aspects are described. big data includes a number of properties that require analysis using improved algorithms, something that regular algorithms cannot do. these types of more effective algorithms are discussed. the characteristics and features of big data, the significance of big data analytics in the healthcare industry, and a discussion of the effectiveness of several machine learning algorithms employed in big data analytics served as our conclusion. references [1] chan, m., estève, d., fourniols, j. y., escriba, c., & campo, e. 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(2017, december). medibchain: a blockchain based privacy preserving platform for healthcare data. in international conference on security, privacy and anonymity in computation, communication and storage (pp. 534-543). springer, cham. eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e2 medical data analytics and wearable devices 7 [21] demirkan, h. (2013). a smart healthcare systems framework. it professional, 15(5), 38-45. [22] yin, h., akmandor, a. o., mosenia, a., & jha, n. k. (2018). smart healthcare. foundations and trends® in electronic design automation, 12(4), 401-466. [23] oueida, s., kotb, y., aloqaily, m., jararweh, y., & baker, t. (2018). an edge computing based smart healthcare framework for resource management. sensors, 18(12), 4307. [24] newaz, a. i., sikder, a. k., rahman, m. a., & uluagac, a. s. (2019, october). health guard: a machine learning-based security framework for smart healthcare systems. in 2019 sixth international conference on social networks analysis, management and security (snams) (pp. 389-396). ieee. [25] alamri, a. (2018). monitoring system for patients using multimedia for smart healthcare. ieee access, 6, 23271-23276. [26] haghi, m., thurow, k., & stoll, r. (2017). wearable devices in medical internet of things: scientific research and commercially available devices. healthcare informatics research, 23(1), 415. [27] son, d., lee, j., qiao, s., ghaffari, r., kim, j., lee, j. e., ... & kim, d. h. (2014). multifunctional wearable devices for diagnosis and therapy of movement disorders. nature nanotechnology, 9(5), 397-404. [28] castillejo, p., martinez, j. f., rodriguez-molina, j., & cuerva, a. (2013). integration of wearable devices in a wireless sensor network for an e-health application. ieee wireless communications, 20(4), 38-49. [29] cheng, h. t., & zhuang, w. (2010). bluetoothenabled in-home patient monitoring system: early detection of alzheimer's disease. ieee wireless communications, 17(1), 74-79. [30] chung, w. y., lee, y. d., & jung, s. j. (2008, august). a wireless sensor network compatible wearable u-healthcare monitoring system using integrated ecg, accelerometer and spo2. in 2008 30th annual international conference of the ieee engineering in medicine and biology society (pp. 1529-1532). ieee. [31] ravi, d., wong, c., lo, b., & yang, g. z. (2016). a deep learning approach to on-node sensor data analytics for mobile or wearable devices. ieee journal of biomedical and health informatics, 21(1), 56-64. eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e2 microsoft word paper_technologycameraready_v05fin.doc analytic hierarchy process for assessing e-health technologies for elderly indoor mobility analysis elena simona lohan dpt. of electr. & comm. eng., tut, finland elenasimona.lohan@ tut.fi oana cramariuc dep. of physics, tut, finland centrul it pentru stiinta si tehnologie, bucharest, romania oana.cramariuc@ tut.fi łukasz malicki knowledge society association ul. grażyny 13/15 lok. 221, 02-548 warszawa, poland lukasz.malicki@ ssw.org.pl neja samar brenčič mks electr. syst./ izriis neja.samarbrencic@ izriis.si bogdan cramariuc centrul it pentru stiinta si tehnologie, romania bogdan.cramariuc@ citst.ro abstract accidental falls and reduced mobility are major risk factors in later life. changes in a person’s mobility patterns can be related with personal well-being and with the frequency of memory lapses and can be used as risk detectors of incipient neurodegenerative diseases. thus, developing technologies for fall detection and indoor localization and novel methods for mobility pattern analysis is of utmost importance in e-health. choosing the right technology is not only a matter of cost and performance, but also a matter of user acceptability and the perceived ease-of-use by the end user. in this paper, we employ an analytic hierarchy process (ahp) to assess the best fit-to-purpose technology for fall detection and user mobility estimation. our multi-criteria decision making process is based on the survey results collected from 153 elderly volunteers from 5 eu countries and on 10 emerging ehealth technologies for fall detection and indoor mobility pattern estimation. our analysis points out towards a bluetooth low energy wearable solution as the most suitable solution. categories and subject descriptors h.4 [information interfaces and presentation]: miscellaneous. general terms design, human factors. keywords analytic hierarchy process (ahp), elderly e-health care, fall detection, indoor mobility, user surveys. 1. introduction falls are one of the principal sources of injuries and hospitalization for elderly [5]. also, mobility is a good indicator of health status and changes in movement patterns may signal an increased risk of the onset of a neurodegenerative disease (nd) [13]. for example, moving back and forth in a repetitive way between the same places inside the house may be associated with mild memory losses, remaining in a sitting position for long periods of time may signal mild depression. there is accumulating support in the literature that one of the key factors in increasing the efficacy of an e-health tele-monitoring system is to incorporate in the e-health system the right technology for detecting abrupt falls and estimating the indoor location and mobility [3][11]. there are several emerging technologies to support the fall detection and mobility pattern analysis, as it will be discussed in detail in section iii. each of these technologies has their advantages and drawbacks, and there are very few studies yet which analyze these technologies from the elderly users’ point of view based on survey data. it is the goal of our paper to provide a new framework, based on user survey results, expert opinions and ahp for helping the e-health tele-monitoring system designer to choose the most suitable technology for fall detection and indoor positioning, as bases for mobility pattern analysis. 2. analyzed population 2.1 survey methodology a survey on elderly preferences toward various technologies was conducted in five european countries: france (fr), switzerland (ch), romania (ro), poland (pl) and slovenia (sl). it was based on structured interviews conducted by human operators using a questionnaire, specifically developed, in the local language. most of the questions used during the survey were categorical, with fixed answers, selected from a number of example-situations. few questions, such as when the respondents were asked to justify their preference toward a certain technology, were open type requiring a narrative response. the participants were selected based on the following two criteria: 1) above retirement age or with permanent disability; 2) living alone or households of maximum two inhabitants. 2.2 statistics on survey participants table 1. respondents characteristics based on surveys country ro ch fr pl sl total number of respondents 61 6 10 44 32 153 av. number of flat rooms 3.2 6.7 3.8 3.1 5.2 4.4 average age [years] 73. 1 74. 3 81. 7 74. 0 70. 3 74.7 most recurrent age 65 72 86 65 66 65 % of living alone 27. 9 50 60 27. 3 25 38.0 % female respondents 60. 50 60 45. 75 58.2 mobihealth 2015, october 14-16, london, great britain copyright © 2015 icst doi 10.4108/eai.14-10-2015.2261667 6 4 % of respondents with chronic condition(s) 78. 7 66. 7 80 59. 1 53. 1 67.5 the main characteristics of the analyzed population are given in table 1: the number of respondents per country, the average number of rooms in the respondent primary dwelling, the average and most recurrent respondent age (all being above 60 years old), and the percentages of people living alone, of female respondents and of respondents with at least one chronic health condition. 3. used technologies mobile health assistive technologies for remote monitoring of fall detection and mobility pattern analysis fall into two main categories: i) the wearable technologies, which requires that the users carries a tag, a sensor or a transmitter with her/him (e.g., embedded in clothes, as a bracelet or as a portable device such as the mobile phone), and ii) the device-free technologies, where certain wireless transceivers, tags and sensors are installed in the user home, but the user is not required to carry on any device. 3.1 wearable technologies wearable technologies are the most widespread ones in the ehealth community. the user comfort is not the highest with these technologies, but they are typically more precise than the devicefree solutions. rfid tags: radio frequency identification (rfid) tags are becoming an attractive option for e-health applications, due to their low-cost, tracking and positioning capabilities [12]. passive rfid tags can be embroidered in human clothes and they ‘communicate’ through backscattered power measurements with an in-room reader. rfid ranges are typically small (few m), allowing thus for proximity positioning. recent rfid-based fall detectors have been studied in [5]. ble tags: bluetooth low energy is a bluetooth version meant for low power applications. ble-based solutions have been slightly investigated in the context of fall detection and indoor positioning [8]. wearable ble tags are already available. wifi tags: wifi technology is one of the most popular wireless technologies nowadays and is already heavily present around us: in houses, hospitals, universities, commuting halls, etc. most portable wireless devices have nowadays a incorporated wifi chipset and clothing embedded wifi transceivers are becoming a reality. wifi-based fall detectors were reported in [17] and wifi-based positioning solutions are widespread [11]. accelerometer-based wearable devices: they measure the human body acceleration along certain axes. 3d digital accelerometers are widely used in e-health monitoring [5]. positioning estimation via an accelerometer typically requires few additional sensors, such as gyroscopes (measuring the direction change) and barometers (measuring the height change). uwb tags: ultra wide band (uwb) technology is based on sending short time pulses over a very wide bandwidth, and achieving thus centimeter-level accuracy in positioning accuracy [11]. uwb is still a rather expensive technology and wearable solutions are still rather scarce [18]. 3.2 device-free technologies the device-free or contact-less technologies do not require that users carry any device and thus they cannot be forgotten to be worn. typically, such technologies offer a lower accuracy than their wearable counterpart, since most of them (with the exception of vision systems) are based on the human body influences on the signal strength fluctuations between the in-house tags and inhouse receivers, when the person crosses the wave path. some of them (e.g. vision systems) are quite privacy invasive, and thus have a low user acceptability, as our surveys showed [8]. rfid in-house systems: the same principles as for the rfid tags apply, but this time the tags are scattered all through the house, not carried on by the person. the human body changes the signal propagation characteristics and the readers can thus detect the human presence and movements [12]. ble in-house systems: the technology is the same as with the case of the ble tags apply, with the main difference that the tags are on fixed places inside the house (not carried on). the fall detection and positioning principles [19] are similar with the one from the rfid in-house system. wifi in-house systems: similarly with rfid and ble in-house systems, the wifi in-house systems are contact-less systems, where the access point and the wifi tags or transmitters are installed externally to the human wearable fabrics or pockets. the fall detection and positioning principles [12] are similar with the one from the rfid and ble in-house system. uwb in-house systems: uwb in-house systems differ from uwb tags in the fact that they do not employ any wearable devices [4]. the fall detection and user position are based on the time of arrival of multipath reflections due to human body presence. device-free uwb solutions are still scarce in the literature. vision/camera-based systems: the vision systems are those systems requiring at least one surveillance camera in users’ homes. the surveillance cameras capture continuously the images of the users and analyze their movement patterns and behavioral changes based on vision navigation and pattern matching techniques [6]. other technologies: tactile or smart floors can also offer a device-free solution for user status monitoring indoors. the estimation accuracy depends on the density of the pressure sensing nodes, and the information can be sent to the central server through the wifi network [2]. tactile floors are however too expensive and disruptive technologies for the use in elderly homes, and thus they are not included in our analysis. acoustic and ultrasound solutions have also been investigated in the context of elderly automatic monitoring of activities and indoor positioning [2][12]. 4. analytic hierarchy process analytic hierarchy process (ahp) belongs to the category of multi criteria decision making (mcdm) processes, which derive ratio scales from paired comparisons between criteria and factor [1][2]. ahp can help the decision makers to choose between various options by taking into account both quantitative and qualitative factors. the priority weights can be gathered based on user surveys and expert opinions, as done here. 4.1 problem decomposition a block diagram of the ahp decision tree is shown in figure 1: a decision regarding the suitability of a certain technology can be reached by taking into account several criteria and by dividing the problem into an hierarchical process: the first-level hierarchy shows the criteria according to which a decision is reached, and the second-level hierarchy shows the options (or technologies) to be analyzed. each level has a certain priority factor or weight associated to it, here denoted by iw (first level) and ijv (second level), 1, 2,....; 1, 2,...i j= = according to previous [8] and the current user surveys [3][22], the most important factors to evaluate the quality of a e-health technological solution for fall detection and indoor positioning/mobility analysis are: 1. the system cost: this includes the component costs, and the installation and maintenance costs. 2. the technology acceptability by the end user refers to the subjective appreciation of users whether a certain technology would be acceptable or not to be installed in their homes (e.g., camera based solutions tends to be less acceptable than non-visual sensor-based solutions due to privacy concerns). 3. the ease of use of the technology: this refers to how much input, effort and technological knowledge is required from the user’s side in order to use a certain technology. 4. the accuracy of the solution provided by the technology: here, it refers to positioning accuracy, which is also directly related to the accuracy of deriving viable mobility patterns. 5. the false alarm rates: in here, it refers to the rate of detecting and reporting false falls to the caregivers. 4.2 ahp equations once the main decision criteria are chosen (figure 1), pair-wise comparison matrices at each hierarchy level can be built. figure 1. problem decomposition via ahp. a pair-wise comparison matrix { } , 1, h h ij i j n a a = = for hierarchy level h (here, h=1,2) is built as given in eq. (1), where the ija weights tells us how many times a column criterion (criterion i) is more important than a row criterion (criterion j). the lower diagonal elements of ha are obviously the inverses of the upper diagonal elements of ha . 12 13 1 1 2 3 1 .... .................................... 1 1 1 .... 1 h h h h n h n n n a a a a a a a ⎡ ⎤ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥= ⎢ ⎥ ⎢ ⎥ ⎢ ⎥⎣ ⎦ (1) the normalized version of ha is the matrix hm with elements: { } , 1, 1 with ij h ij ij ni j n ij i a m m m a = = = = ∑ (2) the so-called priority vector 1 n hv r ×∈ is obtained via: ( ) , 1, 2, t h h h sum av h n = = (3) where t ha stands for the transpose of matrix ha .the elements of the priority vector are the weights at each hierarchical level: for the first hierarchical level: { }1 1,i i n v w = = and { }2 1,i ij j n v v = = , i=1,n for the second hierarchical level of figure 1. a decision about the best technology according to the multicriteria of levels 1 and 2 in of figure 1 is taken by computing the final priority levels it of each technology and sorting the technology according to its priority level: 1 2 1 , 1, n i i ij j t w v i n = = =∑ (4) 4.3 ahp pair-wise comparison matrices based on our survey results with the survey data in table 1, on literature searches and on expert opinions based on discussion between authors, the following level 1 pair-wise comparison matrix has been obtained (table 2). for example, this tells us that the cost is 4 times more important than the accuracy from the user’s point of view and the ease of use is twice more important than the false alarm rate. table 2. level-1 pairwise comparison matrix cost acceptability ease of use accuracy false alarm cost 1 1/2 2 4 4 acceptability 2 1 4 10 5 ease of use 1/2 1/4 1 2 2 accuracy 1/4 1/10 1/2 1 1/2 false alarms 1/4 1/5 1/2 2 1 the consistency ratio of table 2 matrix is 2%, which is much below the 10% consistency, showing thus a very good consistency of the data. the five level 2 pairwise comparison matrices are shown in our supplementary material of [8] due to lack of space. in order to build those, we used an average dwelling size of 4.4 rooms (as based on surveys, table 1) and we assumed that the wearable solutions need one tag/user and the device-free solutions need 4 tags/room. these assumptions are based on literature studies and authors’ knowledge on the technological needs in indoor positioning. the in-house rfid and uwb systems also require one reader per room (due to line of sight requirements), while in-house ble and wifi solutions work with one receiver per house. the vision-based system was also assumed to require one surveillance camera per room. the level 2 priority weights according to each criterion and to each technology are summarized in table 3 which also shows which technology is the best among others with respect to a certain criterion. the letters stand for: a) wearable ble tag + in-house receiver (rx) ; b) wearable rfid tag + in-house readers; c) wearable wifi tag + in-house receiver; d) wearable uwb tag + in-house rx; e) wearable accelerometer tag + in house rx; f) inhouse ble system (user is device free); g) in-house rfid system; h) in-house wifi system; i) in-house uwb system; j) vision-based system/ video cameras. higher priority means better technology. it also shows which are the drawbacks and advantages of a certain technology with respect to a certain criterion. for example, technology a (wearable ble tag) is the most cost effective technology, while technology j (vision-based system) is the easiest to be used among the 10 considered ones. table 3. level-2 priority weights ijv [%] techn a b c d e f g h i j cost 28.2 4.6 23.5 1.9 22.3 4.3 2.9 5.9 1.4 4.8 accep 13.0 13.0 13.0 13.0 13.0 9.8 6.2 9.8 6.2 3.1 ease of use 6.2 8.3 2.0 4.2 2.1 14.6 14.6 14.6 12.5 20.8 accur 1.5 1.5 0.75 30.1 0.6 1.5 3.0 0.8 30.1 30.1 false alarm s 1.0 1.5 1.0 29.4 5.9 0.7 1.0 0.7 29.4 29.4 5. suitability ranking the 2-level ahp analysis based on the pairwise comparison tables and eq. (4) gives the suitability ranking. the technologies are ranked from the most suitable (rank 1) to the least suitable, by taking into account the user preferences and the 5 optimization criteria of table 2. the gaining technology is a solution based on wearable ble tags and an in-house ble receiver, followed closely by wearable accelerometer and wearable wifi solutions, while the least suitable technology is an in-house (contact-less) rfid system, no doubt due to high cost, low accuracy and low comfort when installed in the house. the suitability according to ahp, given as percentages, is as follows: rank 1: wearable ble tag + in-house rx (14.41%); rank 2: wearable accelerometer tag + in house rx (12.71%); rank 3: wearable wifi tag + in-house rx (12.64%); rank 4: wearable uwb tag + in-house receiver (11.27%); rank 5: vision system (9.40%); rank 6: in-house uwb (8.93%); wearable rfid tag + in-house readers (8.70%); rank 7: in-house wifi system (8.22%); rank 8: in-house ble system (7.84%); rank 9: in-house rfid system (5.84%). 6. conclusions choosing the right technology to support e-health solutions via fall detection and user mobility patterns analysis is a challenging problem. the aim of our paper has been to identify which of the existing technologies for indoor positioning, fall detection and mobility pattern analysis can satisfy most of the requirements of elderly with respect to acceptability, ease of use and cost, by taking into account also the performance indicators (i.e., accuracy and false rates). an ahp analysis was used based on user survey data collected in 5 eu countries. the result of our analysis show that the most suitable technology among the 10 most promising ones in the field of fall detection and indoor mobility is a technology based on a wearable ble tag and additional fixed inhouse receiver. our analysis also shows that wearable technologies are preferable to the device-free technologies, mostly because their better performance and lower associated costs. another observation is that none of these technologies has a significantly higher priority than the others (the highest priority level is 14.4%, only slightly higher than the 10% likelihood, which is the likelihood of randomly selecting one of these 10 technologies), which points out towards the fact that stand-alone solutions may be unable to address all optimality criteria and more advanced hybrid architectures are needed to be created. 7. acknowledgments this work was supported by the following projects: academy of finland (projects 250266 and 283076), eu aal nitics, mobile@old, pn-ii-pt-pcca-2013-4-2241 no 315/2014. 8. references [1] aflaki, s. meratnia, n., baratchi, m., havinga, p. 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[22] zielinska, i., malicki, l., samar brencic, n., consoli, a., ayadi, j., gilardi, l., cramariuc, o., stanciu, d., didi, t., smidtas, s. d2.1. the results of the multi-national survey. nitics project public deliverables, http://nitics.eclexys.com/node/6. recent trends and challenges in smart cities eai endorsed transactions on smart cities research article 1 recent trends and challenges in smart cities pooja g1, sundar r2, harshini r3,*, arjuna s4 and ram kumar c5 1masters in biomedical engineering, politecnico di milano milan, italy 2assistant professor, department of bme, dr.n.g.p. institute of technology, coimbatore 3ug student, department of bme, dr. n.g.p. institute of technology, coimbatore, india. 4ug student, department of bme, dr. n.g.p. institute of technology, coimbatore, india. 5associate professor, department of bme, dr.n.g.p. institute of technology, coimbatore. abstract smart systems are wanting for smart communities to adapt to restricted spaces and assets across the world. thus, smart urban communities arose mostly because of exceptionally inventive ict ventures and markets, and furthermore, they have begun to utilize novel arrangements exploiting the internet of things (iot), huge information and distributed computing innovations to lay out a significant association between every part and layer of a city. smarter solutions need to be executed to make digital services for economic and social advancement seamlessly reach the occupants in an easy and secure way and encourage them to continue using the amenities. a holistic development rather than just technological advancement is essential for the betterment of smart lifestyle of the present and future population. this paper attempts to analyze advancements, and the challenges involved in implementing them in various sectors should be executed to make computerized administrations for monetary and social headway flawlessly arrive at the tenants in a simple and secure manner and urge them to keep utilizing the conveniences. keywords: smart city, recent trends, challenges. received on 31 july 2022, accepted on 12 september 2022, published on 21 september 2022 copyright © 2022 pooja g. et al, licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i3.2273 1. introduction innovative headways and the blend of various advances, gadgets, and organizations have brought about the idea of shrewd urban communities. these urban communities use various electronic contraptions, advancements, and sensors to gather information and offer raised types of assistance and encounters to individuals. urbanization is expanding at a quick scale internationally with over 1.3 million individuals moving to the urban areas each and every day. it is assessed that more than 65% of the worldwide populace will live in the urban communities by 2040. associated and brilliant urban communities are turning into a stage for development for such a worldwide populace [1]. many governments across the world are taking up various drives towards brilliant medical care and computerized wellbeing. the public authority of india has incorporated the drives, for example, free diagnostics *corresponding author. email: mysteryprincess27@gmail.com service initiative (fdsi), portable clinical units, and so on to help its savvy urban communities mission. the interests in smart medical care appear to be paying off. the whole world was affected by the outbreak of the covid-19 pandemic in 2020. millions of people have died, and millions have been contaminated by the dangerous infection. numerous nations are hit continuously and third wave rushes of the infection. smart and digital technologies have been helpful in pandemic control and management [1]. artificial intelligence and big data technologies have been very helpful in drug revelation and antibody dispersion. far off wellbeing observing through iot-based medical care applications has empowered the patients and specialists to connect without visiting the emergency clinic/clinical focus. such measures have helped with guaranteeing the security of the patients and the clinical experts. similar mechanisms are important for successfully implementing the idea of smart cities [2]. eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e4 https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:mysteryprincess27@gmail.com pooja g. et al. 2 2. smart cities a smart city is a technologically modern urban area that utilizes various kinds of electronic strategies and sensors to gather explicit information. data acquired from that information is utilized to oversee resources, assets and administrations proficiently; consequently, that information is utilized to further develop tasks across the city. this incorporates information gathered from residents, gadgets, structures and resources that is handled and analysed to monitor and manage smart cities and smart enterprises deal with the integration of artificial intelligence, web technologies, smart mobile platforms, telecommunications, e-commerce, e-business, and other technologies. fields of utilizations are related to services for users and citizens, like transportation, structures, ehealth, utilities, etc. which is shown in figure 1. smart cities use information and communication technologies (icts) to scale services include utilities and transportation to a developing population. progressing population development and urbanization are starting a renewed desire to integrate technology into the design of city services, in this way creating the essence of "smart cities" [3]. smart cities rely intensely on sensors to perceive parameters, for example, temperature, dampness, allergens, contamination, traffic conditions, and power matrix status. the values of these parameters provide a context that helps a system to understand the state of a citizen at some random time. figure 1. components of smart city 3. recent trends there are three layers to a smart city: an innovation base which incorporates cell phones and sensors associated by fast correspondence organizations, applications making an interpretation of crude information into bits of knowledge and utilization by urban communities and general society. the rising notoriety of 5g, overall entrance of cell phones and expanding reception of iot are completely expected to speed up smart city advancements and carry them into the standard. with this, there are new ways that innovation can change urban communities [4]. figure 2 describes the impact of innovations that happened in the latest trends. figure 2. impact of 10 smart city trends and innovations in 2022 3.1. smart health the pandemic has made obviously the local area an enormous part in establishing better wellbeing conditions for residents. smart developments can lessen burden on medical services natural systems by supporting finding and therapy, yet furthermore preventive dealing with oneself. this moves the concentration from individual-focused medical care to a local area model. directed by information examination, medical care can be custom fitted for people and their families. smart health can be grouped as a subset of e-health given s-health is comparable to the ict framework of the recognized a smart city. regardless, there is a differentiation between s-health and m-health. for instance, in s-health there is plausibility that the recognized key correspondence may not be portable or not. in reality, for a large portion of cases it could incorporate spread out fixed sensors the patient gets information or information from an interactive pole of information for checking the level of residue, dust, notwithstanding pollution for which individual has sensitivity. the information further aides patients in forestalling the regions that can end up being unsafe for their health conditions. the shaft of information helps in giving the patient with information about the best course or heading that they can take to arrive at an objective eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e4 recent trends and challenges in smart cities 3 and about the nearest pharmacies from where he can purchase antihistamine pills [4]. 3.2. smart infrastructure infrastructure frames the groundwork of each and every city, and development can upgrade existing connection focuses in more ways than one — from green structures to waste management systems to traffic guideline. singapore's green mark affirmation conspire, for instance, is presently pointed toward making 80% of the city's structures green. gartner predicts multiple billion associated iot gadgets in business shrewd structures by 2028, fuelled by broadcast communications frameworks, with 5g and high efficiency wi-fi alongside smart utilities like power, waste and water. moving advancements incorporate platform assessment frameworks, iot sensors for wastewater and obstruct checking, halting sensor applications, lighting sensors and fire identification frameworks. this could provoke more conservative, close sew metropolitan communities in the future [5]. 3.3. smart citizens finally, smart cities enhance the voices of their tenants. applications permit residents to momentarily report nearby issues, while local area network platforms permit people to pool together and share assets metropolitan communities are progressing as cooperative environments, with more investment and straightforwardness. open information and emerging developments are preparing for metropolitan communities to be more human-focused and multidirectional for government, associations and residents the same [6]. 3.4. smart energy besides investing in clean energy, metropolitan areas can utilize development to screen real time energy use and upgrade energy use. this includes the usage of supportable and moral materials, climate friendly and assets productive plans, renewables fuelled frameworks and advanced developments to change in accordance with use. the energy change adds to making a round economy, according to deloitte insights, through the decentralization of energy creation with inexhaustible sources. this is preparing for metropolitan communities to be independent in their energy usage [6]. 3.5. smart safety biometrics, facial recognition, smart cameras and video surveillance all have been building up some forward momentum with expanded use by policing. these advancements assist urban areas with recognizing examples and patterns in crime data, diminish reaction times and investigate crime prediction. yet, despite the fact that these innovations present alluring choices, residents' security, opportunity and common freedoms survive from foremost significance. urban communities should be mindful so as to explore going with moral and administrative issues of utilizing such innovations, and try not to oppress explicit areas or segment gatherings [7]. 3.6. smart mobility smart mobility use innovation to empower individuals and different types of transport to work in more proficient, strong, and maintainable ways. progresses in metropolitan portability rotate around further developed foundation, versatility as-a-administration, micro mobility, operations arrangements, and zero-emission transportation. intelligent traffic management, high level driving, and independent vehicles are making metropolitan mobility ecoaccommodating. novel vehicle choices, for example, hyperloop, robot axis, and water taxis likewise track down applications in brilliant city versatility [8]. 3.7. e-governance the e-governance pattern drives smart city actors to disclose administrations and choices more open, supportable, cooperative, and straightforward. to accomplish this, new businesses use blockchain and iotbased arrangements, to remember all partners for the dynamic interaction. computerized administrations, like web based casting a ballot, advanced visas, and hearty information security instruments, support resident cooperation and lead to the development of e-a majority rule government. further, web based retraining programs, nearby e-profession focuses, and digitalization of business capabilities like permitting and burden filling add to monetary development and a pioneering business climate [8]. 3.8. green urban planning because of environmental change and climatic conditions urban planning is confronting a huge challenge to make urban communities smart, economical, and strong. driven by decarbonization objectives, a green urban plan consolidates reasonable area approaches and 15-minute city models where most everyday necessities are reachable by walking or cycling. besides, smart farms for plant development and vertical miniature forests increases biodiversity. as ocean levels rise globally, new and sustainable alternatives like drifting urban areas, islands, ranches, schools, and riverbanks catch the world's consideration [9]. eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e4 pooja g. et al. 4 3.9. advanced waste management as urban populations and buyer culture consistently develop, waste production increases as well. advanced waste management systems use iot sensors to precisely monitor waste removal, advise inhabitants about their utilization, and energize them with monetary rewards. simultaneously, e-waste reusing permit individuals to trade electronics for money. smart containers sort uncategorized waste and manage amount of waste. artificial intelligence recycling robots exactly recognize the sort of materials during waste separation, which increases overall productivity and large efficiency by keeping away from human association. together, arising waste management solutions decrease the ecological effects of economic activities [10]. 4. challenges in smart city healthcare smart city utilizes ict to provide smart medical services and that can in turn more efficiently channel city assets to help occupants speedily as required. while scientists and city originators have made significant first strides towards coordinating smart ict and medical services, which can scale further by turning out to be all the more completely associated 4.1. cyber security and privacy surely the advances in unavoidable registering and ai open up opportunities for smarter medical care using smart city development. simultaneously, these advances depend on information being both gathered and shared. security issues frequently deflect information sharing. truly, security and protection are the issues that are most often featured in conversations about boundaries to integrating advancement into medical services. concerns about protection and security are not unsubstantiated. smart homes offer enormous advantages for wellbeing observing and intercession, yet reports are oftentimes delivered about ways for into hack into these homes. this new variety of criminals might get insights regarding occupant residing pattern which enables efficient break out into a house, jeopardizing both the inhabitant's possessions and their wellbeing. different types of security hazard might rise in any event, when there is no vindictive aim. for instance, wellbeing checking gadgets that don't adhere to endorsed programming guidelines can imperil lives by not giving basic data at the required time. sharing mobile application data can likewise be hazardous, on the grounds that the gathered data may distinguish the client as well as track their ongoing area and foresee future areas [10]. while information is believed to be encoded before transmission and limit, the force of the information lies in sharing the information to break down patterns over whole populaces. while the primary line of protection that is utilized by scientists preceding sharing information is to displace names with randomized identifiers (derecognizing the information), this isn't adequate. in the space of security protecting information mining, information examination strategies ensure specific degrees of protection while endeavouring to support the utility of the information. this is alluded to as the protection utility trade off. three kinds of privacy-ensuring information mining strategies are being explored that might offer affirmation for smart city inhabitants. to start with, information can be "camouflaged" as it is gathered by annoying the information. second, in situations where the first gathered information will be delivered to outsiders, an objective of protection saving information mining is to guarantee the anonymity of the information [86]. this alludes to the confirmation that the recognizable properties for some random clients are undistinguishable from basically k-1 different clients. k-anonymity can be accomplished through strategies that incorporate eliminating delicate traits, expanding variety of touchy characteristics, or adding manufactured information to jumble the genuine qualities, subsequently permitting delicate information to "conceal in the group". on account of versatile information, an option in contrast to relegating a solitary consistent identifier for every client is to occasionally change identifiers. this change makes following clients over the long run and space difficult. an ideal opportunity to change the identifier is the point at which a client enters a space with k-1 different clients so old and new ids won't be quickly connected. third, the result of information mining computations can be adjusted to try not to leak of delicate information. for instance, the reasonability of a gathering computation can be downsized enough with the objective that it meets execution restricts yet restricts the gamble of being utilized to recognize people. whichever blend of methods is utilized, it is important that all gatherings including city creators, strategy producers, and tech suppliers settle on security ensures and depict to city tenants the potentially delicate information sharing that could happen with smart city advancements [11]. 4.2. accessibility and usability healthcare is a keyword that appears in many smart city efforts. nonetheless, cost is at this point a hindrance for inescapable reception of developments that can be utilized at an individual and nearby local area level. in the long haul, integrating technology into huge medical care can lessen costs for the city and its citizens. temporarily, regardless, the expense of the genuine development could keep networks from embracing the advancement [12]. metropolitan communities can take on a comparative strategy as insurance agency to not simply balanced the momentary expense of wellbeing development yet likewise address one more check of health care technology, which eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e4 recent trends and challenges in smart cities 5 is cutting out a potential open door to learn and embrace the advancement. lately, some insurance agencies have offered limits to clients who consent to introduce telematics in their vehicles that screen driving. the expected guide for deciding to introduce the gadgets, as well as cutting down expense rates, is that the information can further develop street security considering the way that the protection application can illuminate drivers when they are driving too carelessly. comparative rousing forces may be presented in the future by health care coverage associations to introduce ict in homes. the development will maintain quality medical care in a monetarily smart way to citizens when and where they need it [13]. 4.3. connection with other smart city services smart cities utilize information and communications technologies in multiple ways. the objective of smart city platforms is to work with fitting and-play smart items that can be conveyed anyplace with a capacity to mix in to their environmental elements. the items ought to help wellbeing checking as well as design observing, climate observing, security, and insightful transportation. the smart urban communities will likewise possibly use streetlights as the spine for citywide remote organizations. meshing sensors into existing city highlights addresses an illustration of the steadily expanding availability of information that can assist scientists with understanding the association between city plan and wellbeing. by observing air quality also as conduct, we can see the effect of our standards of conduct as well as plan decisions on air quality. also, we can screen the effect of air quality on wellbeing and we can plan mediations, for example, changing city plan or giving continuous data to inhabitants to remain inside during seasons of unfortunate air quality [13]. 4.4. multidisciplinary research and interaction explored areas in this field are generally being studied all around the world by different practitioners as well as researchers. in any case, it is especially uncommon for the analysts to direct review or work in same establishment or associations; consequently, this makes it very difficult for them to share their data for commonly prompting a coordinated arrangement. since ideas in this field are exceptionally new, there is a rising necessity for joint effort, collaboration and communication among different entertainers including specialists, professionals, states, doctors, and so on for characterizing a typical common ground all along, and thus, forestalling excess upgrades as well as over-spending [14]. 4.5. educating & engaging the community for a smart city to truly exist and prosper, it needs "shrewd" residents who are participated in and successfully dynamic in new advances. with any new sweeping tech project, a piece of the execution cycle ought to redetection paradigm for smart cities. ember showing the local area for its benefits. this ought to be conceivable through a movement of in-person civil focus style get-togethers and email crusades with elector enlistment, as well as an electronic preparation stage that keeps awake with the most recent. exactly when a local area wants to have an effect in the overall options impact everyday presence, and is being passed on to in a sensible and shrewd manner, it's more ready to use the development and urge others to include it as well. this is indispensable to a smart city's success [14]. 4.6. being socially inclusive smart travel programs that give riders ceaseless updates are really smart for a clamouring city. regardless, imagine a scenario where a piece of the number of occupants in that city can't bear to take mass travel or uber. the thing may be said about a developing older populace that doesn't utilize cell phones or applications? how should sagacious development reach and advantage these gatherings? it's pivotal that smart city orchestrating includes the prospect, everything being equal, notwithstanding the rich and mechanically progressed. development should continually be attempting to unite people, instead of separation them further considering pay or preparing levels. contemplating these networks, related to different issues tended to in this article, will advance the general outcome of an answer past the space of educated clients [15]. 5. conclusion it can be viewed as a prime contribution to the development of empirical research to get a superior comprehension of the ongoing peculiarities of smart cities. to this end, six principal spaces and the related sub-domains of smart city sending have been classified i.e., natural resources and energy, transport and mobility, infrastructures, government, as well as economy and individuals. a dataset of logical factors has been gathered and relapse examinations have been directed to comprehend the connection between different geological, metropolitan, demographical, human resources, ecological and innovation related factors. the consequences of this study have uncovered that there is no worldwide definition of smart cities, and that the latest things and development examples of any singular smart cities rely generally upon the neighbourhood setting factors. city strategy producers are in this manner asked to attempt to comprehend these variables to shape fitting techniques for their smart cities. this study is specifically founded on a system that could likewise be applied to make a superior determination of eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e4 pooja g. et al. 6 speculation open doors in times of restricted financial assets and to focus on smart cities drives in the different spaces and sub-spaces of expected execution, taking into account their capacity to boost the benefits related with the specific cutthroat trait of a smart city. the smart cities idea has acquired a great consideration lately and it will probably keep on doing as such from here on out. urban communities are distributing smart plans, related gatherings are moving and that's just the beginning and more books are being composed regarding the matter. smart innovations can give answers for urban communities by assisting them with setting aside cash, decrease fossil fuel by products and oversee traffic streams. yet, the intricacy of the plan is hindering its progress. it includes an enormous number of stakeholders (nearby specialists, residents, innovation organizations and scholastics) each having their own vision of what a smart city ought to be; the majority of the discussion gets impeded on attempting to comprehend what 'smart' signifies instead of focusing on how it can assist urban communities with meeting their objectives. additionally, since the market for brilliant advances is moderately new, it needs new plans of action and approaches to working which are yet to be created and carried out. references [1] yin c, xiong z, chen h, wang j, cooper d, david b. a literature survey on smart cities. science china information sciences. 2015 oct;58(10):1-8. [2] al nuaimi e, al neyadi h, mohamed n, al-jaroodi j. applications of big data to smart cities. journal of internet services and applications. 2015 aug;6(1):1-5. [3] harrison c, donnelly ia. a theory of smart cities. inproceedings of the 55th annual meeting of the isss2011, hull, uk 2011 sep 23. [4] chourabi h, nam t, walker s, gil-garcia jr, mellouli s, nahon k, pardo ta, scholl hj. understanding smart cities: an integrative framework. in2012 45th hawaii international conference on system sciences 2012 jan 4 (pp. 2289-2297). ieee. [5] pacheco rocha n, dias a, santinha g, rodrigues m, queirós a, rodrigues c. smart cities and healthcare: a systematic review. technologies. 2019 aug 16;7(3):58. [6] ghazal tm, hasan mk, alshurideh mt, alzoubi hm, ahmad m, akbar ss, al kurdi b, akour ia. iot for smart cities: machine learning approaches in smart healthcare— a review. future internet. 2021 aug 23;13(8):218. [7] hossain ms, muhammad g, alamri a. smart healthcare monitoring: a voice pathology multimedia systems. 2019 oct;25(5):565-75. [8] pramanik mi, lau ry, demirkan h, azad ma. smart health: big data enabled health paradigm within smart cities. expert systems with applications. 2017 nov 30;87:370-83. [9] poongodi m, sharma a, hamdi m, maode m, chilamkurti n. smart healthcare in smart cities: wireless patient monitoring system using iot. the journal of supercomputing. 2021 nov;77(11):12230-55. [10] tripathi g, abdul ahad m, paiva s. sms: a secure healthcare model for smart cities. electronics. 2020 jul 13;9(7):1135. [11] umair m, cheema ma, cheema o, li h, lu h. impact of covid-19 on iot adoption in healthcare, smart homes, smart buildings, smart cities, transportation and industrial iot. sensors. 2021 jun 1;21(11):3838. [12] alghamdi a, hammad m, ugail h, abdel-raheem a, muhammad k, khalifa hs, el-latif a, ahmed a. detection of myocardial infarction based on novel deep transfer learning methods for urban healthcare in smart cities. multimedia tools and applications. 2020 mar 23:122. [13] sanghavi j. review of smart healthcare systems and applications for smart cities. iniccce 2019 2020 (pp. 325331). springer, singapore. [14] baba sm, banday mt. application development for wearable internet of things using hexiwear. in2020 7th international conference on signal processing and integrated networks (spin) 2020 feb 27 (pp. 542-548). ieee. [15] murthy bs, peddoju sk. iot-based patient health monitoring: a comprehensive survey. ict analysis and applications. 2021:349-56. eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e4 this is a title a mobile crowd-sensing platform for noise monitoring in smart cities m. zappatore1,*, a. longo1, m.a. bochicchio1, d. zappatore1, a.a. morrone1 and g. de mitri1 1dept. of innovation engineering, univ. of salento, via monteroni sn, 73100 lecce, italy abstract modern cities are moving towards novel approaches for urban sustainability for improving citizenship’s life quality, thus aiming at the smart city model. environmental and mobility issues represent two key areas where policy makers address their interventions and, amongst them, noise pollution is one of the most significant causes of public concern. however, noise monitoring campaigns are expensive and require skilled personnel. a viable alternative is represented by mobile crowd sensing (mcs) paradigm, which exploits mobile devices as sensing platforms. in this paper, we propose a mcsbased platform that exploits noise measurements collected by citizens and offers a suggestion system to city managers about noise abatement measures (in terms of both estimated noise reduction and average installation costs). several field tests demonstrated the feasibility of this approach as a suitable way to support city managers and to widen the possibilities of collaborative urban noise monitoring. keywords: mobile crowd sensing, urban noise monitoring, urban traffic noise abatement measures, data warehouse. received on 30 november 2015, accepted on 29 april 2016, published on 20 july 2016 copyright © 2016 m. zappatore et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.18-7-2016.151627 1. introduction the continuous improvement in wireless communications, boosted by a series of key technological enablers [1], is nowadays not comparable to any other communication technology. this has originated a shift towards new reference models for networks, devices and standards. as for the mobile devices, we can observe how smartphones, tablets and wearable devices are quickly replacing pdas, laptops and notebooks as the new boundary, since they combine high computational power, embedded sensors (e.g., accelerometers, gyroscopes, light, magnetometers, etc.), smart and intuitive user interfaces. as for the network infrastructures, the broadband capabilities of novel 4g wireless communication standards (i.e., lte† and lte-a‡ [2]) promise up to 1gb/s transfer speed and high-quality coverage. moreover, many other contexts are benefitting *corresponding author. marcosalvatore.zappatore@unisalento.it † lte: long term evolution (wireless communication standard) ‡ lte-a (also known as lte+): lte advanced (wireless communication standard) from wireless communications: smart homes with interconnected household appliances, automated industry processes and remote applications represent indeed other concrete situations where mobile devices can prove their effectiveness. the penetration rate of mobiles into daily life activities, and the corresponding users’ familiarization level with such devices, are nowadays so significant that mobiles can be leveraged as an effective way to improve life quality conditions as well as an effective technological driver for offering a wide range of services within smart cities. one of the most appealing trends in exploiting mobiles pervasively is represented by their usage as sensor data sources, as described by a new sensing paradigm named mobile crowd sensing (mcs) [3]. according to mcs principles, mobiles, along with their built-in sensors and additional pluggable sensors, represent very powerful sensing nodes that overcome typical 1 research article eaeai endorsed transactions on smart cities eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e3 m. zappatore et al. limitations of wireless sensor networks (wsns). on the one hand, from a communication network point of view, they can provide wider coverage areas, greater number of deployable nodes (without requiring any reconfiguration procedure when new nodes have to be added) and more reliable connectivity (thanks to the wireless communication networks serving the mobile). on the other hand, if we consider the sensing capabilities offered by mobile devices, they can offer sufficient levels of accuracy thanks to their embedded sensors or external, pluggable – and more accurate – sensors. therefore, if mobiles are used as sensor data sources in a reasonable way, and even if such devices obviously do not replace professional metering equipment but simply complement their capabilities, they can be used to fulfil a series of relevant tasks. amongst these tasks we can enlist: 1) being dynamically scattered across huge areas with heterogeneous and complex sensing purposes; 2) acquiring contextual awareness opportunistically from the surrounding environment; 3) allowing users to improve their knowledge about specific scientific phenomena and research challenges; 4) allowing easy integration with other ict platforms in smart cities [4]. consequently, multiple roles can be envisioned for mobile devices [5] according to the mcs paradigm. firstly, mcs allows defining innovative services capable of managing contextual information and suitable to interact with user’s social and physical situations. secondly, mobile devices represent a promising solution to engage their owners in collaborative, large-scale monitoring experiences. this may effectively promote wide participatory contributions from citizens, yearning of life quality improvement, as well as positive behavioural changes in citizenship about environmental sustainability. additionally, this makes possible to harvest large and heterogeneous amounts of information from citizens, describing their continuously evolving urban environments. such data can be forwarded to city managers, thus allowing them to have better awareness of the potential issues affecting their municipalities, without relevant additional costs. finally, mobile devices can enlarge the scope of traditional monitoring campaigns significantly, so that the expensive deployment and maintenance of professional metering equipment can be spared for ad-hoc interventions only in those city areas where the noise levels highlighted by mcsmediated campaigns are higher. the features enlisted so far fit perfectly with the requirements of modern smart cities, where contextual information availability, collaborative monitoring and relevant data streams about urban environments are fundamental aspects to be achieved. by starting from such premises, in this research activity, we opted for the urban noise-monitoring scenario, which is gaining relevance in modern cities as assessed by several reports from the european commission. europeans, indeed, are becoming more and more concerned about how noise can affect their quality of life and, consequently, policy makers should consider noise-related aspects when dealing with urban and traffic monitoring and planning. we propose a platform with the following features: 1) direct involvement of users in sensing activities; 2) suggestion of noise abatement interventions to local administrators; 3) gathering of users’ opinions in order to obtain psychoacoustic measurements (i.e., how sound is perceived by humans in terms of loudness, sharpness and direction [6]). in addition to the benefits achievable by the adoption of mcs briefly outlined so far, these three features contribute to improve the overall quality of currently available mcs solutions in the noise-monitoring domain, which are typically tailored to single user’s needs and do not provide any kind of valuable suggestions to city managers. our platform has been designed, developed and tested (in the city of brindisi, southern italy) as a distributed system that gathers sensor data and users’ comments from mobiles and sends them to a context broker application that forwards them to a nosql data storage instance for persistent storage. subsequently, a complete extract-transform-load (etl) pipeline elaborates and manages collected measurements in a data warehouse (dwh) system: this step allows us to aggregate raw data depending on different aspects (e.g., sensing location and device type, measurement time, etc.) as well as to identify outliers. the outlier detection is a crucial elaboration phase in mcs solutions: the outliers represent measurements exhibiting significant biases in comparison with the average, so that they have to be identified and evaluated in order to determine (or, at least, infer from an algorithmic point of view) whether they are caused by wrong measurement procedures or malfunctioning sensing devices. only freeware and open-source it solutions have been used to promote knowledge sharing and reuse. according to the aspects pointed out throughout this section, our proposal behaves as: 1) a sensing platform; 2) a system suggesting noise reduction and abatement policies to urban authorities; 3) a preliminary, low-cost, large-scale and sufficiently accurate monitoring tool. this will allow small and medium municipalities to perform noise monitoring without the need of expensive professional metering equipment. therefore, the platform has a noise-prevention and pre-screening usage: it allows locating areas with potential noise pollution risks where more accurate measurement campaigns requiring professional metering equipment can be addressed. the pre-screening capability of our application represents another relevant advantage for smart city context due to financial and spending reviews, which normally limit the start of professional noise monitoring campaigns. another important aspect to be mentioned pertains to the importance of the developed mobile application for acoustic data collection. even if current mobile marketplaces offer a considerable variety of noise sensing applications (as it will be thoroughly described in sections 3 and 3.3), the majority of them is devoted to personal use only, thus not allowing the smartphone owner to contribute in large and collaborative monitoring activities. only a couple of very recent research initiatives (see again section 3.3) propose a mcs-based approach to noise sensing but they do not offer any decisionsupport tool for city managers and policy makers in order to suggest them possible noise abatement interventions in their 2 eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e3 a mobile crowd-sensing platform for noise monitoring in smart cities municipalities and to estimate the impact of such measurements on current noise pollution levels. before describing our research activity in the rest of the paper, it is worth to point out that throughout this document, when we will use the term “noise”, we will refer only to the “acoustic noise”, since many other noises of different physical nature can be considered (e.g., electromagnetic noise, electrostatic noise, signal processing noise, etc.). the paper is organized as in the following: section 2 describes the actual scenario in terms of noise pollution concerns, health-related effects of noise exposures, typical urban noise sources and noise monitoring regulations. mobile crowd sensing paradigm, along with examples of its applications in urban contexts and in noise monitoring, is presented in section 3. the proposed platform design choices are detailed in section 4, in terms of both data modelling and logical architecture. section 5 presents the developed platform prototype (both the mobile application for data gathering and the web application for data visualization). several discussion aspects are coped with in section 6. section 7 draws conclusions and sketches out further developments. 2. urban noise 2.1. urban noise pollution concerns historically, noise pollution has not been considered similar to other urban pollutants (e.g., chemical or radiological) and still a low number of cities and administrations implements noise-control policies against potential health risks despite several technical reports by the european commission ascertained citizens’ concerns about noise pollution issues. according to the 2013 urban mobility report [7], indeed, the majority of europeans believes that noise (72%) represents the fifth most significant problem within cities after air pollution (81%), road congestion (76%), travelling costs (74%) and accidents (73%). the noise pollution concern reaches even higher values in italy (83%), bulgaria (85%), greece (87%) and malta (92%). if examined from a sociodemographic point of view, the problem is less considered by students (66%) and much more by managers (76%). the situation in italy is well-described by a series of statistical analyses. the annual report by istat§ [8] about the overall quality of the urban environment demonstrates the scarcity of noise assessment interventions nationwide: only 0.98% of the cities carried out noise monitoring campaigns in 2013, mainly required directly by citizens (91%). in 63.2% of the cases, at least one regulatory threshold was trespassed. these values are confirmed by the 10th national report on urban areas, by ispra** [9], which assesses that 52% of the noise emission controls performed in administrative centres exceeded thresholds, mainly due to high vehicular traffic volumes. § istat: italian national institute of statistics large monitoring campaigns would allow italian cities to apply the acoustic classification plan (pca, in italian) for their geographical area, as requested by national laws [10]. this law established that each city should be partitioned into six different area classes (depending on the main socioeconomic activities performed therein) where specific noise thresholds for day and night time-windows hold. however, in 2013, only 53% of the italian administrative centers fulfilled such a requirement. 2.2. health-related effects of noise exposure the necessity of proper noise monitoring activities is enforced also by the outcomes of several epidemiological research works that thoroughly analyse possible correlations between health effects and noise [11]. the outcomes of a primary exposure to a constant environmental noise source can be classified into acute effects, chronic effects and longterm risks [12] but it is important to point out that the exposure levels vary depending on multiple causes and on individual basis (i.e., some subjects are more noise-sensitive than others). amongst the acute effects, we can enlist: decrease sleep quality and quantity, sleep fragmentation [13]; stress and distraction [14]; temporary change in hearing or noise-induced hearing loss (nihl) [15]. moreover, especially in urban scenarios, noise can cause the so-called noise annoyance [16], which stands for a series of socio-behavioural changes and overall discontent in citizens residing in noisy areas that may determine additional effects (e.g., increased drug consumption, increased number of accidents). chronic effects entail hypertension, reduced learning and productivity, disruption of endocrine system and diabetes [17]. the long-term risks range from increased risk of injury to possible ischemic heart disease (ihd), increased risk of heart attack and permanent nihl [18]. from a more general perspective, long-term risks mainly depend on the time duration of the exposure. evidences from several research studies ( [19], [20]) demonstrate that people exposed to higher-volume sound sources or people exposed chronically due to specific life and working conditions (e.g., residents along busy roadways or residents located along a descending/ascending flight path to/from an airport) have the higher risks. noise emissions also affect more heavily specific categories of subjects or people exhibiting additional health risks: for instance, children living in noisy contexts [21] or attending schools located in dense urban areas show poor performances, stress, decreased learning rates, misbehaviour, concentration deficits, hyperactivity and scarce reading comprehension [22]. the chronically ill and the elderly are two other population categories especially vulnerable to noise-related diseases. however, although the specific correlation between health effects and noise is even more documented than other environmental pollutants, the results in addressing noise ** ispra: italian superior institute for the environmental preservation and research 3 eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e3 m. zappatore et al. emissions and planning noise reduction interventions in urban contexts are still disappointing. local authorities do not yet implement stable noise monitoring policies due to several factors, such as high equipment costs, scarcity of skilled personnel and lack of environmental awareness. typical monitoring stations are fixed installations that are located close to take-off and landing airport strips or in the proximity of traffic hotspots. their costs are so relevant (i.e., buying costs: up to 25k€, rental costs: up to 3k€/month) that small and medium municipalities cannot afford similar expenses, thus depriving their citizenship of noise mapping campaigns. consequently, this scenario determines an overall relevant request of novel monitoring solutions to be deployed also in small cities, since even small municipalities have the right to become smart or even smarter. 2.3. noise sources in urban contexts citizens in urban contexts are exposed to multiple sound sources (and the corresponding generated noise), exhibiting different characteristics in frequency and time. a widelyadopted categorization partitions noises into impulsive, transient and continuous ones. the impulsive noise is due to short-duration pulses having random amplitude and random duration (typically less than one second). typical impulsive sources are hammering noises and gunfire. transient noise consists of noise pulses having longer duration or relatively short pulses followed by decaying low frequency oscillations. vehicle pass-by and aircraft flyover are the most common transient sources. continuous noise, instead, exhibit stable conditions over a relatively long time period. as for what concerns the noise sources, the most relevant one within urban contexts is represented by vehicular traffic. it is generated by multiple components: engine and transmission, rolling tires over the asphalt, aerodynamic, braking systems and vehicle-mounted devices, such as horns, sirens and whistles. traffic noise levels depend on many vehicle-related factors, such as typology, speed and age [23]. since it is strictly related to traffic noise, we can also consider the noise induced by roadwork and construction sites. these noise sources, which can be very annoying for the population due to their potential long duration over time, range from interventions by utility companies (e.g., gas, electricity, water, cable services) to constructions (e.g., realization of new buildings, renovation or demolition of existing buildings, etc.). leisure time activities such as concerts and festivals represent another significant source of noise, especially when rock and pop music are played. recent studies highlighted how years of exposure to loud music played at discotheques and during concerts may induce irreversible noise-induced hearing loss in both ears of at least 10db at 3 khz. recent tests activities performed during music festivals highlighted how the individual sound exposure per evening varied between 90 and 115 db(a), with an average exposure of 100 db(a) and prolonged peaks of 110 db(a) [24]. the noise generated by airplanes and airport installations is another major source of disturbance, especially when airports are in close proximity to cities. their contributions are: take-off and landing phases (generated by: aerodynamic, engine and propulsion systems) as well as airport activities (e.g., maintenance and emergency vehicles, baggage and passenger transportation systems, etc.) [25]. 2.4. current noise monitoring regulations in italy and europe one of the widely adopted scale to quantify noise exposure is the a-weighting: it measures the sound pressure level (spl) in units of db(a) [26] and allows measuring the dependence of perceived loudness w.r.t. frequency. since sounds are typically fluctuating (i.e., they vary in time and have different durations) and since spl is an instantaneous measurement instead, the equivalent sound level leq(t) is preferred [26] as the reference exposure descriptor in noise regulations and guidelines. it measures, in db(a), the steady sound level conveying the same sound energy of the actual time-varying noise source in a given place during a given time window t (where t typically ranges from 30s to 24h). in a more simplified explanation, leq(t) averages the spl values measured during t, thus smoothing spikes and outliers. italian noise regulations [27] classify urban areas into six acoustic classes depending on their main usage and building typologies. as reported in table 1, different threshold leq(t) values are provided for each of those classes. in addition [10], [28], these thresholds are also expressed w.r.t.: time of the day (diurnal: 6a.m. – 10p.m.; nocturnal: 10p.m. – 6 a.m.); sensor position w.r.t. the noise source (insertion values: if near the source; emission values: if far from the source); road type (w.r.t. vehicle capacity and speed) and age (novel or already existing roads). the italian laws adopt a precautionary approach, so that the law thresholds that cannot be trespassed (i.e., limit values) are always below the noise emission values representing a lower risk or a potential risk for human health (i.e., quality values and attention values, respectively). as a reference, it could be useful to consider that in urban contexts typical noise values at 15m from the observer are: heavy truck (90db(a)); congested city road (80db(a)); light car traffic (60db(a)). as for the normative situation in the continent, the european commission promulgate in 2002 the environmental noise directive (end) 2002/49/ec [29] about the assessment and management of environmental noise trying to define a common approach across all member states for avoiding, preventing or at least reducing harmful effects of the exposure to environmental noise. the directive aims at harmonizing noise indicators and assessment methods by producing strategic noise maps (snms), enabling comparison of noise levels and affected areas across member states; heightening public awareness about noise as a significant environmental pollutant; adopting strategic action plans (saps) to prevent and reduce noise where/when needed. the end has been acknowledged in italy by the dlgs 194/05 [30] law, but after many years, some issues and misalignment remain between them. this is mainly due to a 4 eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e3 a mobile crowd-sensing platform for noise monitoring in smart cities significant difference between the european directive and the italian law, from a normative point of view. on the one hand, the italian law determines and provides the thresholds to be abided by, the noise monitoring and controlling procedures, the noise abatement and reclamation techniques. on the other hand, the european directive aims at reducing the population noise exposure independently from the compliance with law thresholds and limits established by individual member states. therefore, the european directive does not impose any strict control or obligation on noise exposure but it strongly relies on the individual member states and their capabilities of informing the population about noise exposure levels and their potential health-related effects as well as of involving citizens during the definition of saps for noise exposure containment. the brief normative overview sketched so far highlights how significant can be the impact of smart-city-like solutions providing people the possibility of becoming better aware about noise-related issues within their cities. the mcs-based platform proposed in this research work exactly aims at this direction. table 1. leq(t) threshold values in db(a), according to [10], [27]. the columns corresponding to law limits are grayed out. acoustic class limit quality attention day night day night day night c1. protected 45 35 47 37 50 40 c2. residential 50 40 52 42 55 45 c3. mixed 55 45 57 47 60 50 c4. intense human activities 60 50 62 52 65 55 c5. mainly industrial 65 55 67 57 70 60 c6. exclusively industrial 65 55 70 70 70 70 3. mobile crowd-sensing (mcs) 3.1. mobile device pervasiveness the most recent analyses for the mobile market confirm what have been outlined in the introduction. according to the ict data and statistics division of the itu (international telecommunication union) [31], by the end of 2015 mobile cellular subscriptions will reach a worldwide penetration rate of 97% (127% in western europe [32], 139% on average in eu countries and 158% in italy [33]). in q1 2015, mobile broadband subscriptions reached 535mn in western europe only. by the end of the same year, the mobile broadband technology (3g and 4g wireless communication standards †† umts: universal mobile telecommunications service (wireless communication standard) such as umts†† and lte-a respectively) will represent the most dynamic market segment. they will achieve a penetration rate of 48% in eu countries (52% in italy) and an overall network coverage of nearly 69% of the world population, which reaches the 89% if we consider the urban population only. the prospected trend for year 2020 is even more evident. as envisioned in [32] by ericsson company, the number of worldwide mobile subscriptions will reach 9.2bn (6.1bn for smartphones) w.r.t. the actual 7.1bn (2.6bn for smartphones). the increase for western europe will amounts 140mn, although the 80% of new mobile broadband subscriptions will come from asia pacific, the middle east and africa. as for the mobile traffic growth forecasts, the worldwide monthly data traffic per smartphone amounts 1.05tb/month for q1 2015 and it is expected to reach 4.9tb/month in 2020, with a compound annual growth rate (cagr) of 30% [32]. from a socio-demographic point of view, it is estimated that 90% of world population over 6 years of age will have a mobile phone by the end of 2020 [32]. in italy, the statistical analysis performed in 2013 by nielsen [34] ascertained that 59% of users in the age 16-24 uses smartphones. this percentage increases up to 72% for individuals ageing 25-34 and 70% for subjects in the age 35-44. the success of mobile broadband solutions is due to many reasons, such as high data rates, reliable coverage, high quality of service, extreme portability, data plans and monthly bills less expensive than fixed-broadband plans. moreover, the statistical analyses briefly sketched so far, demonstrate that the highest smartphone penetration rates come from youngsters in urban scenarios, since they are early adopters of new technological solutions and they are typically inclined to use their smartphones to perform many heterogeneous activities (e.g., social networking, audio/video streaming, mobile banking and shopping, location-based services). therefore, our application will benefit significantly from its diffusion across youngsters as primary data collectors. 3.2. mcs paradigm and its applications in urban contexts mcs became known more than one decade ago, when burke et al. [35] proposed the notion of participatory sensing (ps) for the first time, and then it rapidly found application in urban scenarios. such paradigm is realized once individuals are provided with personal electronic devices capable of collecting and analysing data in order to share local knowledge on a broader scale, so that each single user may become a data source point without the need of deploying ad hoc sensor nodes around him [35]. the first applications were aimed only at user’s selfmonitoring in the healthcare sector (e.g., tracking of: nutrition, drug assumption, physical activity) but they rapidly broadened their scope to very heterogeneous contexts. the 5 eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e3 m. zappatore et al. original definition of ps has been then absorbed under the new term of mobile crowd sensing (mcs) [3] that currently describes a paradigm about collecting data directly from mobiles, which is much more advantageous than traditional wsns and whose definition emphasizes the role of mobiles in leveraging their sensing and computational capabilities. mcs actually exhibits multiple features. depending on whether 3g/4g standards (e.g., edge‡‡, umts, lte) or short-range standards (e.g., wi-fi, bluetooth) are used, two different transmission paradigms are possible, named infrastructure-based transmission and opportunistic transmission respectively. similarly, user involvement is now much more considered than before, since mcs applications can be differentiated depending on whether people are allowed to choose when monitoring a specific event (participatory sensing) or simply delegate their mobiles to automatically send data without requiring their participation (opportunistic sensing). nevertheless, the most important step towards a new way of gathering sensor data from users is represented by the significant shift from the initial self-monitoring applications to the so-called community monitoring, where larger and larger number of participants are involved in sensing campaigns. these aspects are particularly evident in urban monitoring scenarios, where four main application areas can be considered. the first area refers to mobility-related issues, such as traffic monitoring and parking availabilities [3] or road safety control [36]. the second category gathers all those applications devoted to the environmental monitoring, such as control of air pollutants ( [37], [38], [39]) and water pollutants [40], [41]. in the third sector, we can enlist the emergency management applications, such as flood alerting systems [42] or earthquake immediate sensing [43], [44]. the last group of applications comprises large-scale events monitoring and planning [45], such as music festivals or exhibitions, in order to follow specific groups of people or to profile their activities or interests. 3.3. mcs-based applications for noise and sound monitoring despite a general interest about mcs-based initiatives for urban monitoring, the currently available solutions dealing with acoustics and noise are mainly focused on research and development and only a couple of them have been deployed so far on a large-scale, in order to achieve significant positive societal impacts within citizenship. the majority of mcs applications for noise monitoring, indeed, are for personal use only: they reproduce main sound level meter (slm) functionalities and allow users to check how loud their surrounding environment is; however, they do not provide noise measurement aggregation on a geographical/temporal basis. ‡‡ edge: enhanced data gsm environment (wireless communication standard) this is the case of apps for controlling sound levels, such as advanced decibel meter [46], sound meter pro [47] or decibel meter pro [48]. very few research works address noise mapping, such as the “ear-phone” project [49] where nokia phones were used to predict sound levels in a given environment, “noisespy” [50], which exploited mobiles carried by bicycle couriers to collect data in cambridge, or the “2loud?” project [51] that uses iphones to assess nocturnal noise within buildings near highways in australia. one of the main limitations in such activities is that users are only involved as data collectors but no specific platform functionalities are tailored to administrators for improving citizenship’s life quality. therefore, if specific software solutions for noise mapping within urban contexts are needed, city managers still have to consider professional systems and platforms, such as the software application suite developed by softnoise [52], which provides a complete toolset of products for environmental noise calculations (“predictorlima”) and mapping (“mapatwork”) as well as for occupational noise mapping (“noiseatwork”). soundplan acoustics [53] represents a similar solution: it is a noise modelling software for technicians and professionals, which offers advanced noise-mapping functionalities and animations for 3d sceneries. the obvious drawback of such products is represented by their high cost and the necessity of skilled personnel capable of managing them properly. consequently, city administrations typically cannot afford their adoption on a large scale. 4. the proposed platform 4.1. overview the proposed system addresses multiple categories of users: on the one hand, municipality managers will be provided with a web application suggesting how to reduce noise levels and where regulatory thresholds are exceeded. on the other hand, mobile users will be allowed not only to collect measurements but also to learn about noise metering and acoustic principles directly on their devices. in order to make this possible, national and international noise norms and regulations have been embedded. this mcs approach also allows us to overcome typical drawbacks of traditional noise monitoring techniques, which are more accurate but much more expensive. by embedding users’ comments into our data collection app, we also can integrate the approach of noise socio-acoustic surveys [54] to analyse the noise-induced annoyance. 4.2. data modelling approach data coming from smartphone-embedded sensors need to be managed properly: after the collection phase, measurements 6 eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e3 a mobile crowd-sensing platform for noise monitoring in smart cities must be cleansed, transformed and stored in order to make them available for final users. these processing steps can be tackled very effectively by revolving to a data warehouse (dwh) approach [55], according to which data are processed in an extract-transform-load (etl) pipeline. the suitability of such an approach is given by the inherent nature of sensor data, which are amenable to be managed in a multidimensional model. a typical approach to this scenario is represented by the dimensional fact model (dfm) [55], which is a conceptual model characterized by a high graphical expressivity, whose clarity allow representing concepts in a straightforward way, thus easing the comprehension of the multidimensional analyses that can be performed on data. the core element in a dfm is the fact: it represents any concept relevant to decision-making processes and which evolves in time. in order to describe it qualitatively, the socalled fact attributes are needed. similarly, the qualitatively description for a fact is given by the measures, which represent numerical properties or relevant calculations. being a multidimensional entity, a fact can be analysed along different coordinates, called dimensions, which enlist several dimensional attributes per each, organized into directed trees departing from the fact. dimensional attributes qualify the finite domain of their dimension along with its different degrees of granularity (e.g., the temporal dimension can vary from seconds to days, weeks, months; a product is described by its name, series, brand, etc.). figure 1 allows us to introduce the dfm notation as well as our modelling choices. we selected the noise measurement as the fact: it is depicted as a rounded box in fig.1. fact measures are inside the rounded box: they refer to both spl and maximum/minimum/average leq(t). we have considered the following dimensions: time (both timestamp and date/month/year); geographical position (latitude, longitude, town, province, region, country); sensor type (external or embedded); device type (model and brand); measurement type; outlier condition. the dimension representing user’s annotations refers to the acoustic source and it is optional. more in details, we firstly manage the acoustic source uniqueness: the user will be asked to evaluate whether there is a predominant acoustic source around her/him or not. then, a series of other user’s annotations are considered, which are all referred to the predominant acoustic source in case of multiple sources present in the same environment. these additional annotations are: source type (i.e., natural or artificial), location type (i.e., indoor or outdoor), annoyance (i.e., annoying or not annoying), nuisance (i.e., how much the acoustic source is deemed noisy by the user) and distance from the observer (i.e., very close, close, quite distant). §§android 4.2 apis (level ≥ 17): http://developer.android.com/about/versions/android-4.2.html *** orion: http://catalogue.fiware.org/enablers/publishsubscribecontext-broker-orion-context-broker in fig.1, the dimensional attributes for each dimension are represented as circles connected by lines to the fact, whilst the dimension is the root circle. figure 1. dimensional fact model (dfm) for the fact: “noise measurement” 4.3. platform logical architecture: design choices and significant components our platform consists of a mobile sensing app and of a cloudbased system tasked to data management. some platform components have been developed by using fiware [52], a middleware supported by the future internet public-privatepartnership (fi-ppp) project of the european union. fiware is becoming an important technological driver for the development of cost-effective and reusable it solutions for the so-called “future internet”, a broad definition encompassing multiple and cross-disciplinary areas such as smart cities, logistics, internet of things, environmental sustainability and transportations. the developed mobile app works on android mobile devices (android 4.2 apis§§). the app mimics a professional slm user interface and collects peak, average and current values of spl and leq(t) on customizable temporal windows, as required by eu and italian noise regulations. measurements are stored locally (short-term history) and sent to the cloud-hosted system for data aggregation and filtering. the data brokering functionality is achieved by using orion***, a generic enabler (ge) from fiware that provides publishing and subscribing operations on collected data. data from orion are persisted into a cloud-based instance of mongodb, the no-sql document-based dbms, thanks to the fiware cygnus††† connector. figure 2 depicts the proposed three-layer logical architecture. the first layer consists of non-persistent sensor data storage on mobiles (implemented via sqlite), of persistent storage on the cloud (via mongodb) and of ††† cygnus: https://github.com/telefonicaid/fiware-cygnus#section1 7 eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e3 m. zappatore et al. relational dbs (via mysql) for law regulations, device technical specifications and administrative divisions. the second layer has context-brokering capabilities for managing multiple sensors as well as data filtering (thanks to pentaho ce‡‡‡, a freeware etl application), integration and reporting functionalities. the third layer offers a web app for accessing data reporting and integration results. mobiles and a limited number of fixed monitoring stations represent data sources. we also developed a web app for data visualization purposes, according to requirements elicited from users (i.e, city managers and citizens). figure 2. platform logical architecture 5. the developed prototype 5.1. mobile application the user interface (ui) of the mobile app mimics a professional slm, thus offering also to unskilled users a way for learning how to manage such kind of equipment as well as to understand which physical quantities (and corresponding units of measurement) are involved in noise monitoring campaigns. figure 3 depicts the app page for the participatory measurements. both leq(t) and spl values are reported and plotted on a xy graph (users can switch between the time analysis and the frequency analysis mode by switching on the corresponding radio-button placed below the graph area), as well as the selected observation time period t. once the measurement ends, users can choose amongst: 1) starting a new measurement by discarding the current one (round orange button in the bottom right corner); 2) sending the measurement without any comments (right green button at the page bottom); 3) commenting and then sending the measurement (left green button at the page bottom). ‡‡‡ pentaho: http://community.pentaho.com/projects/data-integration/ figure 4 represents the app page for comments and assessments, where users can describe the noise source, thanks to radio-buttons, in terms of: location (indoor or outdoor), nature (artificial or natural), annoyance, estimated distance from the observer, uniqueness, typology (by selecting amongst a set of predefined values such as truck engine, car traffic, construction site, crowd, machinery, etc.). it is also possible to quantify the perceived nuisance level, by activating a slider (whose psychometric 10-value scale adheres to specifications proposed in [54]), and to add freetext comments. the round orange button in the bottom right corner allows users to take pictures of the area where noise measurements come from. users’ comments are particularly relevant in order to better characterize measurements taken according to the mcs paradigm: by providing personal comments and evaluations, the users contribute to enrich raw sensor data with contextual information, thus allowing more data management opportunities. for instance, measurements taken inside buildings can be separated from outdoor ones, thanks to the characterization of the measurement scenario provided by the users. similarly, measurements taken by different people at the same location, within the same time range can be compared w.r.t. the perceived nuisance level, thus analysing people differences in perceiving the same sound sources. in the same way, by providing photos of the surrounding sound sources, the users can contribute in creating a live, photographic map of the noisy spots within a city. figure 3. mobile ui: main screen for measurement 8 eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e3 a mobile crowd-sensing platform for noise monitoring in smart cities figure 4. mobile ui: page for user’s comments 5.2. web application we also developed a web application for city managers: it allows users to access a multi-layered, geo-referenced map where data coming from the platform are visualized properly. more in details, the first layer is devoted to visualize measurements coming from a given area as points in a choropleth map (i.e., a map where the colour ramp used to represent the measurement location points is directly proportional to the measured leq(t) values). another layer (fig.5) provides users with the interpolation of measurements achieved in the same area as an intensity heatmap (i.e., a map where adjacent measurements are interpolated according to a given algorithm in order to compute leq(t) values also for those points where no measurements were actually performed). intensity maps are extremely useful for understanding how noise levels are perceived throughout the urban environment without requiring to scatter all across the city mobile sensors. a third layer depicts public transport routes (see again fig.5), in order to cross-correlate visually potential issues about noise pollution with transportation issues. a fourth layer allows the user to superimpose vehicular traffic data with noise mapping, in order to compare noise issues with traffic jams and busy transportation routes. the rendering of all the layers described so far has been achieved by forwarding measurement data, after the etl process, towards a cartodb [56] instance, an open-source, cloud-hosted, geospatial database for map storage and visualization. figure 5. web app: intensity map of interpolated leq with suggested noise abatement measures (in the right vertical frame). the interpolation refers to measurements collected within a 1-hour time window. public transportation routes are visualized as well, thanks to an additional layer 9 eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e3 m. zappatore et al. in addition, the intensity map offers the possibility to dynamically explore how noise level abatement interventions may impact on actual interpolated leq(t) measurements: by selecting from proper dropdown lists a given noise abatement measure, users can see how interpolated values could be reduced accordingly on that area. at this moment, we considered measures addressing traffic noise emissions (since they represent the most relevant cause of urban noise pollution). the system suggests, for each different abatement measures, the corresponding estimated impact on leq(t) and estimated average costs. more specifically, city administrators are provided with several traffic noise abatement interventions (fig. 6). as a first choice, the system proposes interventions on traffic speed/volumes and road pavement techniques. low-noise asphalts (e.g., thin-layer, double-layer, porous) are low-cost and significantly effective options for reducing traffic noise [57]. moreover, they can be applied directly in specific noise hotspots without requiring any relevant environmental or architectonic modification. a second typology of intervention is related to speed limit enforcements, especially in the range 40-70km/h: traffic flow restriction measures are particularly useful, not only in terms of noise reduction but also for air quality and road safety [58]. typically, such solutions have even lower costs for municipalities than low-noise asphalts but they may have collateral social costs due to travel time losses. figure 6. urban traffic noise abatement measures (excerpt from the table provided to city managers): expected impact on leq(t) and estimated costs (for measures aimed at reducing speed or vehicles flow the indirect installation costs per traffic sign are reported). in order to provide noise perception reference values, we remind the reader that a ±2db(a) variation is barely noticeable by humans, a ±3db(a) variation is perceptible, a ±6db(a) is clearly perceived, a ±10db(a) is perceived as the doubling/halving of the loudness of a given sound. 10 eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e3 a mobile crowd-sensing platform for noise monitoring in smart cities other possible suggested interventions are represented by vertical (e.g., speed bumps/humps, rumble areas) and horizontal (e.g., roundabouts, traffic circles) traffic calming measures [23]: however, administrators must evaluate their application by examining each specific case since speed reduction artefacts may generate additional noise (e.g., once a vehicle reaches a road hump). in addition, the suggestion system also proposes noise exposure-reduction measures, such as the noise barriers. barriers are the most effective noise-reducing solution [59] but their installation cost is quite relevant (nearly 300 €/m2 instead of 20 €/m2 on average for low-noise asphalts) and their environmental and visual impact is significant, thus requiring proper preliminary analysis before deciding for their installation in a given location. further combinations of noise abatement interventions and more configuration parameters are also possible for such noise abatement measures: they are actually under investigation in order to be implemented in the next prototype of our platform. more specifically, we are implementing the possibility to apply different noise abatement policies to different roads and city areas, in order to offer estimations about selective and differentiated interventions. similarly, we are enlarging the range of available options, by considering also the evaluation criteria typically used for noise barrier selection. users will be allowed to select amongst barriers [60], [61] differing for: typology (i.e., absorptive vs reflective), material (e.g., wood, plastic, steel, concrete, etc.), height and length, shape and barrier-tops (e.g., conventional, t-profile, yprofile, arrow-profile, curved, etc.). all these design aspects will be briefly described in terms of both installation costs and noise reduction effectiveness. 6. discussion 6.1. measurement accuracy the platform has been preliminary tested at our university campus. subsequently, 20 students from our faculty performed several on-site tests in the central area of the city of lecce (95k inhabitants, southern italy). they collected measurements in multiple 1-hour time windows by moving across high-traffic hotspots (e.g., roundabouts, 4-lane roads, typically congested streets, etc.). three different types of android-based smartphone have been used as metering devices. some of the collected measurements have been also used to produce the noise maps described in section 5.2 (fig.5). the need for testing different smartphones is related to the measurement accuracy issue, which assumes a considerable relevance in mcs contexts, since mobiles embed sensors exhibiting lower accuracies than professional metering equipment. the same issue also refers to their embedded microphones, which are normal directional microphones, instead of the omnidirectional, shielded ones which are available in professional slms. therefore, we coped with this by evaluating the accuracy of the smartphone-embedded microphones instrumentally: we selected a 30-second steady, mid-level and broadband noise source and then we repeatedly compared measurements provided by different models of smartphones to data obtained with a professional, portable, class-1 slm (i.e., deltaohm hd9019). after several comparison sessions, we achieved an acceptable average accuracy: data from mobiles were affected on average by a ±5db bias, which confirms the most recent research works [62] and thus demonstrating their amenability to be leveraged as preliminary monitoring stations. in addition, we also implemented, as a step of the etl process, a univariate algorithm for the outlier detection in order to remove measurements having an excessive sound level amplitude in a given temporal window. we opted for a slightly modified version of the tukey’s method [63], which is simple and quite effective with datasets following both a normal distribution and a not highly skewed lognormal distribution (which is the case of environmental sensors working in normal conditions, without relevant malfunctioning issues or particularly high concentrations of out-of-threshold noise sources). moreover, accuracy issues can be further reduced by implementing calibration procedures for smartphone builtin microphones. these methodologies allow to assess in a more rigorous way the reliability of a given device as an accurate sensor source: they allow us to quantify the discrepancy between a professional measurement and a mcs-based one, so that the latter one can be provided with an additive correction factor. multiple calibration approaches are available in scientific literature for acoustic monitoring equipment. the first and more reliable one requires the comparison between the measurement achieved with a given mobile device and the one achieved by a professional slm (obviously, both referring to the same sound sample). the major drawback of such an approach is that with large numbers of users it is impossible to perform extensive calibration campaigns (also if we consider that periodical calibration are required). other calibration solutions are therefore needed. the second version of the developed prototype will offer: 1) self-calibration performed by each user against a known sound sample; 2) an extensive database of already calibrated smartphones, so that large portions of users can benefit from the already available correction factors. 6.2. privacy issues the web app visualizes collected measures on a georeferenced map: the providing users, scattered on a large area, gather and send measurement by using their mobile devices. this casts the need of proper privacy protection approaches, since one of the most relevant concerns of 11 eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e3 m. zappatore et al. smartphone users, nowadays, is the fear of being tracked or identified as a direct consequence of the usage policies and actions they perform on their devices. in order to minimize such risk and to make aware users of the adopted privacy-preservation strategies, we propose the following interventions. firstly, any information or metadata capable of identifying the device owner is discarded and users are notified about this when they start the app for the first time. mobile devices are only indexed thanks to their imei (international mobile equipment identity) code, which do not allow going back to respective owners (therefore, mobiles are traceable but their owners are unknown to both platform managers and other application end users). secondly, users are required to login to our platform if they want to enrich participatory noise measurements with comments and photos: this solution allows us to achieve a better reliability in psychoacoustic measurements (since registered users are willing to contribute responsibly). 6.3. user engagement and effective channels for data gathering mcs activities usually require specific solutions for engaging people in data gathering campaigns, so that they should not lose interest after their first experiences in mcs. moreover, the involved participants should be informed about how to perform measurements correctly, in order to avoid data quality worsening. thirdly, mcs apps must exhibit effective channels for data gathering, so that their usage mode seamlessly help users in gathering data in the right way. all these aspects have to be considered when designing and implementing mcs solutions, as they represent the key elements for widening the lifespan of a given mcs activity. for such reasons, we are implementing a series of additional functions on our initial platform prototype. amongst them, the most relevant one pertains to the released mobile app. we are planning the release of a second version of the mobile app, not anymore as a standalone app but as a plugin for third-party mobile apps (which we can call “hosting apps”). this different type of distribution will allow us to widen the number of potential users, who will experience the capabilities offered by our platform as an add-on for hosting apps they typically already use. in addition, we will not select the hosting apps simply by considering their level of diffusion amongst mobile users but by paying much more attention to the usage modalities these apps actually offers. indeed, we will select hosting apps that require people to use their smartphone in a way that is also suitable for performing measurements in an effective and reliable way. amongst the requirements needed for identifying hosting apps, we can enlist the following ones: 1) do not use smartphone built-in microphone for other audio registering purposes; 2) do not use other external sensors plugged into the audio jack connector; 3) do not require the usage of specific covers that may obstruct the microphone and hinder the measurement quality; 4) require an intensive usage from smartphone owners, in order to be in idle for shorter timeperiods. 7. conclusions the enormous diffusion of mobile devices is disclosing new opportunities in everyday life for people: the computational power offered by such devices, along with their rich built-in sensor equipment and the capability of being connected anywhere and anytime can be exploited in a plethora of novel and useful ways. one of the core areas where mobile devices can be effectively leveraged is represented by smart cities: urban environments aiming at becoming more environmentally sustainable and more itoriented than ever before in order to improve their citizenship’s life quality. several solutions have been proposed in scientific literature so far about smart cities, dealing with potentially any kind of sector: transportation, logistics, pollution monitoring, public services, wireless communications and so on. however, policy makers and city managers are constantly involved in searching novel ways to cope with typical urban issues, such as environmental quality monitoring and urban mobility. these two aspects, indeed, have a strong mutual relationships, since vehicular traffic is considered one of the prominent causes for urban air and noise pollution. therefore, proper sensing approaches are needed, in order to collect relevant data. the majority of municipalities, unfortunately, cannot afford expensive and long professional metering campaigns, even in western countries, due to several reasons, ranging from equipment considerable installation and maintenance costs to lack of skilled personnel for managing sensors and interpreting their data. consequently, in this paper we decided to leverage the diffusion of a novel sensing paradigm known as mobile crowd sensing (mcs), according to which mobile devices can be used as sufficiently accurate sensing platform, for engaging citizens into large urban noise monitoring campaigns at potentially no cost. we selected the noise monitoring as our first area of application in order to exploit the sound-registering capability offered by mobile built-in microphones. we developed a platform allowing citizens to gather noise measurements (both opportunistically and participatory). collected measurements are then aggregated, filtered and interpolated in order to provide city managers with an overview of the actual noise pollution levels in their cities. specific noise abatement measures are suggested to city managers (in terms of both estimated noise reduction and average installation costs) thanks to a dedicated web app. the proposed solution promises to be very effective in a smart city scenario, where citizens directly contribute to enhancing their quality of life and city managers are constantly informed about noise levels across the entire urban framework without the need of expensive monitoring 12 eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e3 a mobile crowd-sensing platform for noise monitoring in smart cities networks. several tests assessing the accuracy achievable by smartphone built-in microphones in sound monitoring have been performed with satisfactory results. a series of privacy-preserving techniques have been also presented in the paper. the system has been preliminary tested in city of southern italy hosting a large variety of noise sources within its framework (i.e., airport, commercial and touristic harbour, railway station, highway). other additional improvements are actually under development: model scalability, introduction of multiple noise abatement measures, additional setup parameters (e.g., different noise barrier materials and shapes). acknowledgements. this research activity has been developed and financed by the eu-funded project sp4um (grant agreement n. 632853, subgrant agreement n. 021), within the “frontiercities” fiware accelerator, and by the edoc@work3.0 project. references [1] a. goldsmith, wireless communications, cambridge university press, 2005. 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[63] d. hoaglin, b. iglewicz and j. tukey, "performance of some resistant rules for outlier labeling," journal of american statistical association, vol. 82, pp. 1147-1149, 1986. 14 eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e3 c-abac: an abac based model for collaboration in multi-tenant environment mohamed amine madani1,*, mohammed erradi1, yahya benkaouz2 1networking and distributed systems research group, itm team, ensias, mohammed v university in rabat, morocco 2conception and systems laboratory, fsr, mohammed v university in rabat, morocco abstract collaborative systems allow a group of users to collaborate through distributed platforms in order to perform a common task. collaborators usually use cloud-based solutions to outsource their data and to benefit from the cloud capabilities. ensuring access control in a cloud-based collaborative session is an important problem that should be addressed, especially in a multi-tenant configuration. in this paper, we present c-abac, a collaboration attributes based access control model that ensures access control in multi-tenant cloud environments. c-abac supports the workflow concept, preserves the tenants autonomy in defining their local policies and preserves the confidentiality of the object attributes. the implementation of c-abac in the swiftstack environment demonstrates the feasibility of the suggested model. received on 15 december 2017; accepted on 18 april 2018; published on 26 june 2018 keywords: abac model; tasks; collaborative session; access control. copyright © 2018 mohamed amine madani et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.26-6-2018.154831 1. introduction nowadays, multiple organizations collaborate by performing common tasks in order to reach a common goal. such collaborations optimize the usage of the distributed resources of the collaborators, hence, the productivity and the benefit improvements. in this context, collaborative applications bring new solutions and technologies to enable a group of users to communicate, cooperate and collaborate through distributed platforms to perform common tasks. most organizations rely on cloud-based solutions to outsource their it infrastructure such as compute, network and data storage in a cloud service provider (csp). this provides remote access to software and hardware services via internet. in order to ensure the confidentiality and the privacy of these services, the cloud service provider segregates the data and customers services into multiple tenants. each tenant hplease ensure that you use the most up to date class file, available from eai at http://doc.eai.eu/publications/transactions/ latex/ ∗corresponding author. email: amine.madani@um5s.net.ma is assigned to an organization or to a person that uses a given cloud service. during collaborations, the cloud tenants need to access and use the information shared by other collaborating tenants. this information often contains sensitive data. it is meant to be shared only during specific collaborative sessions [5]. this arises the access control issue [4]: the tenants need strong access control model supporting cross tenants access and collaboration. moreover, users may intervene dynamically without a prior knowledge of which user will request an access to a given object. in this direction, designing a fine-grained access control model is mandatory [5]. note that a collaboration might be seen as a set of tasks and workflows. each task is performed by a given tenant and a tenant may achieve one or more tasks. a task might be active (i.e. a part of a workflow) or passive (i.e. does not belong to a workflow). on the other hand, access control models for collaborations in multi-tenant environments might be classified into two categories: centralized and decentralized (peer to peer) access control models. in centralized approaches, the access enforcement and decisions are taken in a 1 eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e3 http://creativecommons.org/licenses/by/3.0/ http://doc.eai.eu/publications/transactions/latex/ http://doc.eai.eu/publications/transactions/latex/ mailto:<publications@eai.eu> m. madani, m. erradi, y. benkaouz specific central point. these models enable granting and revoking permissions while a task is running. in decentralized approaches, each tenant is responsible of its own access control policy. in this respect, tenants are loosely coupled. such approaches could support the following requirements: • autonomy and independence: each tenant maintains control over its resources. each tenant defines its local access control policy and respects the global access control policy. • confidentiality: each tenant is be able to maintain the confidentiality and the privacy of its local policy and its own data. in this paper, and based on the fine-grained access control model "abac: attribute based access control", we propose "c-abac: collaboration abac". c-abac is especially designed for collaborations in multitenants environments. c-abac model overcomes the limitations of the classical access control models that are based on rbac model. it supports an access crosstenant in which a tenant could use shared ressources on the cloud while preserving access control policies. the c-abac model is a centralized model that allows the collaborating tenants to specify a global policy (authorizations) in a specific central point. c-abac supports the task and the workflow concepts. it is scalable and preserves the autonomy of each tenant in defining their policies. in addition, it preserves the confidentiality of the object, resource and environment attributes that are used in the access decision process. this paper is organized as follows: section 2 presents the background of this work, in which, the concepts of cloud-based collaborative applications and the abac model are explained. the related work are presented in section 3. section 4 describes the suggested cabac model. section 5 presents the implemented architecture, the enforcement model and discusses the evaluation results. finally, we conclude in section 6. 2. background this section aims to present the necessary background of this work. it mainly focus on the presentation of the concept of cloud based collaborative application. then, it presents the attribute based access control model. cloud based collaborative applications. collaborative applications are among the services that can be provided by the cloud computing. they enable collaboration among users from the same or different tenants of a given cloud provider [2, 3]. during collaborations, the participants need to access and use resources held by other collaborating users. these resources often contain sensitive data. they are meant to be shared only during specific collaborative session [5]. the collaborative session is an abstract entity, comprising a set of users, called members of the session. these members play either the same role or different roles. they might have concurrent access to shared objects in the collaborative session depending on the access control policy. case study: a collaborative application for telemedicine in this study, we consider the telemedicine scenario shown in figure 1. in this real use case, the school hospital (sh), the emergency medical services (ems), and the home hospital (hh) are three collaborating issuers sharing a common private cloud service. the cloud service provides storage services for the home hospital issuer, and for the three sh’s departments: neurology, radiology and cardiology, as segregated tenants. this private cloud provides a service of collaborative sessions for the emergency medical services (ems). this service allows a group of users, from different tenants, to collaborate in order to observe and treat a patient admitted in the home hospital (hh) emergency. in this scenario, we have a collaborative session cs1 of a telemedicine type. the members of this session are: • user1: neurologist in the tenant neuro of the issuer sh; • user2: cardiologist in the tenant cardio of the issuer sh; • user3: radiologist in the tenant radio of the issuer sh; • user4: doctor_ems (emergency doctor) in the tenant emr of the issuer ems; • user5: doctor_hh in the tenant storage of the tenant hh. abacmodel. abac is an adaptive and a flexible fine-grained access control model. the core components of abac model [9] are: • u , o and e represent finite sets of existing users, objects and environments respectively. • a = {create, read, update, delete} is a finite set of actions. • uat t , oat t and eat t represent finite sets of user, object and environment attribute functions respectively. • for each att ∈ {uat t ∪oat t ∪ eat t }, range(att) represents the attribute’s range, which is a finite set of atomic values. 2 eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e3 c-abac: an abac based model for collaboration in multi-tenant environment figure 1. a collaborative session in cloud environment • attt ype : uat t ∪oat t ∪ eat t → {set, atomic}, specifies attributes as set or atomic values. • each attribute function maps elements in u to an atomic value or a set – ∀ua ⊆ uat t . ua : u → range(ua) if attt ype(ua) = atomic – ∀ua ⊆ uat t . ua : u → 2range(ua) if attt ype(ua) = set • each attribute function maps elements in o to an atomic value or a set – ∀oa ⊆ oat t .oa : o→ range(oa) if attt ype(oa) = atomic – ∀oa ⊆ oat t .oa : o→ 2range(oa) if attt ype(oa) = set • each attribute function maps elements in e to an atomic value or a set – ∀ea ⊆ eat t .ea : e → range(ea) if attt ype(ea) = atomic – ∀ea ⊆ eat t .ea : e → 2range(ea) if attt ype(ea) = set • an authorization that decides on whether a user u can access an object o in a particular environment e for the action a, is a boolean function of u, o, and e attributes: rule: authorizationa(u, o, e)→ f (at tr(u), at t r(o) , at t r(e)). 3. related work several works have been in the literature to ensure access control in multiple environments. in the task based access control [4] (tbac), the permissions are granted according to the progress of several tasks. the trbac [18] model is constructed by adding the "task" concept to the rbac model. in trbac, the user has a relationship with permission through role and task. on the other hand, in the team access control model (tmac) [6], the permissions are granted to each user through its role and the current activities of the team. these models enable fine-grained access control but they do not incorporate contextual parameters into security considerations and do not support collaboration in multi-tenants environments. moreover, the notion of "team" used in tmac model is static. therefore, this model does not support dynamic collaboration. other access control approaches have been suggested to secure resources in cloud environments [2, 3, 19– 21]. calero [2] suggests a multi-tenancy authorization system. this work is based on hierarchical role-base access control with a coarse-grained trust relation and path-based object hierarchies . calero et al [2] assumes that each issuer may use several cloud services and could collaborate with other issuers. tang [20] proposes a multi-tenancy authorization system (mtas) model. this model is based on the rbac model and the trust relations established between the cloud issuers in order to support collaboration between these issuers. the issuer that establishes the trust is called the truster and the one being trusted is called the trustee. the trustee 3 eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e3 m. madani, m. erradi, y. benkaouz can authorize one of the trusters roles to access to a trustee resource. the multi-tenant role-based access control (mtrbac) proposed by tang et al in [3] is a model that provides fine-grained access control in collaborative cloud environments by using trust relations among tenants. in this work, trust relations among issuers were not considered (i.e. they distinguish between issuers and tenants). in mt-rbac model, the truster exposes some trusters roles to the trustee. this trustee assigns their users to the trusters roles. thus, the users can access to the trusters resources by activating the trusters roles. in collaborative task role-based access control ctrbac model [21], authors propose an approach to ensure access control to the shared resources in a collaborative session in multi-tenants environments. the suggested ctrbac model is an extended version of rbac in which new entities were added in order to support together the cross tenants access and the task concept. nonetheless, in this model, a given tenant may use some roles owned by other tenants which will compromise the confidentiality requirement. furthermore, this model is based on rbac model which is not flexible enough to support a complex policy rules. these models are based on a decentralized approach. it supports the following requirements: (1) autonomy and independence: each local administrator maintains control over his system. each organization defines its local access control policy, and respects the global access control policy. (2) cross tenant access: tenant uses some resources shared by other tenants. however, these models do not support task and scalability requirements, especially if we assume that the collaboration is a workflow composed of a set of tasks. moreover, these approaches are based on role based access control (rbac) model. nevertheless, various limitations of rbac have been recognized such as: flexibility and scalability. in this direction, attribute based access control model (abac) is of a great interest. abac model [9, 10] overcomes the limitations of the classical access control models (i.e, acl, mac and rbac). this model is adaptive and flexible. abac is more suitable to describe complex, fine-grained access control semantics, which is especially needed for collaborative environments. there have been few works that used abac in multitenant environment. the multi-tenant attribute-based access control model (mt-abac)[11] presents model to enable collaboration between tenants in the cloud. this model is based on a decentralized approach and supports cross-tenant attribute assignment. however, this model does not support the task concept. in mt-abac model, authors defined a trust relationship established between the truster tenant and the trustee tenant in order to support cross tenants access. in this relationship, the trustee is authorized to assign values for trustee’s user attributes to truster’s users. however, before assigning the users to the attributes, the trustee should know some informations about truster’s users such as their jobs in the organization which will compromise the confidentiality requirement. moreover, the trustee has the full control to assign the truster’s users to the trustee’s authorizations which will compromise the autonomy requirement. therefore, in this paper, we propose c-abac, a novel abac based model following a centralized approach. c-abac allows the collaborating tenants to specify the global policy in a specific central point. c-abac supports the concepts of task and workflow. it ensures the tenants autonomy and preserves the attributes confidentiality of the tenants objects. 4. c-abac: the collaboration abac model in this section, we present the suggested collaboration attributes based access control model: c-abac. in this section, we first define the notion of collaborative tenant. then, we describe the business process for the collaboration. after that, we present the c-abac model definition. finally, we show a use how c-abac might be used in the previously described telemedicine use case. 4.1. a collaborative tenant the collaborative tenant is the tenant responsible for ensuring the collaboration between multi tenants. it provides the collaboration as a service for the collaborating tenants. this collaborative tenant allows a group of users from different tenants to collaborate through distributed platforms in order to perform a common process. note that each set of tenants that want to collaborate with each other should first create this collaborative tenant. then, they should define in this collaborative tenant the collaboration process which is a workflow composed of a set of tasks, each task will be performed by a given tenant and a tenant may achieve one or more tasks. for instance as shown in figure 2, the tenants sh , ems and hh are three collaborating tenants using the collaborative tenant that provides the collaboration as a service. figure 2. collaboration as a service (caas) 4 eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e3 c-abac: an abac based model for collaboration in multi-tenant environment figure 3. a collaboration workflow 4.2. a business process in our approach, each collaboration is specified as a business process that is defined as a set of tasks that are connected to achieve a common goal. for example, figure 3 shows the diagnosis process related to the our use case. in this collaboration, each task will be performed by a given tenant using some resources shared by others tenants. as shown in the tasks assignment (figure 4), the tenant sh is responsible to achieve the task t 7. moreover, in order to perform this task, the tenant sh needs to access to the resources mr, scan and video that are owned by the tenant hh . in this section, we present our core c-abac model which is designed to be suitable for ensuring access control in collaborative multi-tenants environments. abac model has been defined in various ways in the literature, usually for some specific goals. in our approach, we add the tasks (t ) entity in addition to the users and objects of core abac0. the task is a fundamental unit of business work or business activity. tasks are assigned to tenants according to their roles in the collaboration. the task is defined using the triple (task name, tenant that is responsible to achieve the task, set of resources (owned by others) tenants used for achieving the task). for example as shown in figure 4, the tenant sh achieves the task t 7 by using some resources owned by the tenant hh . in order to specify abac authorization while supporting collaboration and tasks requirements related to multi-tenants environments, we should use the notation illustrated in figure 5. c-abac model introduces the task entity to the user and object entities of the abac model. in this model, each task is defined by a set of task attributes like: the task name, the workflow of the task, previous tasks and the collaborative session of the task. moreover, in each task, the responsible of this task may have many authorizations. for example in the task t 7 : t ake_a_decision, a user from the tenant sh needs have four authorizations: (1) read the patient medical record mr1; (2) read the patient scan image scan1; (3) read the patient video file; (4) write the final decision. in c-abac model, each authorization related to a given task is defined as shown in figure 2 by: (1) set of task attributes related to this task; (2) set of user attributes that represent the user who is responsible to achieve this task; (3) set of object attributes related to the resource used in this task; (4) an action which is a specific operation on object. for each task, the user that is responsible of the task should have many permissions to accomplish this task. so each task is assigned to many permissions (abac authorization). a c-abac authorizations are defined using task, user, and object attributes that are independent of one another. moreover, each task attributes have the same value for all c-abac authorizations related to this task. likewise, each user attributes have the same value for all authorizations related to one task the fact that we consider that the user who is responsible to achieve one task is authorized to perform all actions related to this task. a c-abac model is composed of the three basic components: users (u ), objects (o), and tasks (t ). in this model, each user has an attribute uowner which is a many-to-one function from users u to tenants t e. moreover, the model requires each object to have an attribute oowner which is a many-toone function from objects o to tenants t e. further, each user attribute, each object attribute and each task attribute is also uniquely owned by a single tenant, depicted respectively by the many atomicvalued functions uaowner, oaowner and taowner. the crucial concept is that each tenant is responsible for assigning values to attributes that it owns. with isolated tenants, a user can have assigned values only for those attributes owned by the user’s owning tenant. actions are allowed operations in the system. these operations typically include create, read, update and delete. we use the terms actions and operations interchangeably. an action is applied to an object by a user. in our approach, a global c-abac authorizations for a given task of the collaboration includes global attributes which will be defined at the collaborative tenant level. such attributes are the task attributes, user and object attributes related to the collaboration (for instance, membercs(u): member of the collaborative session; sharedcs(o): shared in the collaborative session). on the other hand, in this authorization, the administrateur of the collaborative tenant uses the attributes related to the user who is responsible 5 eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e3 m. madani, m. erradi, y. benkaouz figure 4. tasks assignment figure 5. c-abac authorizations for executing this task. these user attributes will be defined by the task executor (the tenant assigned for executing this task) in a confidential, autonomous and independent way from other collaborating tenants and the collaborative tenant. for this purpose, we propose a new attribute function assignuser() which will be defined at the level of the local tenant. this attribute function is responsible on executing the task and will be used by the collaborative tenant at the level of the global autorization. moreover, in this authorization the administrator uses the attributes related to the object shared within the task. similarly, these object attributes will be defined by the object owner in a confidential and independent way from the other collaborating tenants. for this purpose, we propose a new attribute function usedobject() which will be defined by the object owner and will be used by the collaborative tenant to define the global autorization. 4.3. assignuser function assigneduser(ta:ta;te:t e)(u : u )→ {t rue;false}, a boolean attribute function, mapping user to true or false, which means that the user attributes that represent the user who is responsible to achieve this task t will be defined by the tenant te in a confidential way. this compound attribute is used by the tenant responsible of the task to define the user attributes of the user who will perform this task in the local policy with a confidential and an autonomy way. for instance, the compound attribute assigneduser(t 7;sh)(u) will be defined by the tenant sh to specify the user attributes of the user responsible of the task t 7. the indices used in this function are: • (ta : ta): the current task (the active task) of the workflow collaboration. • (te : t e): the tenant that will perform the this task ta (the task executor). • the couple (ta : ta, te : t e), means that the tenant te is responsible to accomplish the task ta. 4.4. usedobject function usedobject(objt ype;a:a;te:t e)(o : o)→ {t rue;false}, a boolean attribute function, mapping object to boolean true or f alse, which means that the object attributes related to the object of the type objtype will be defined by the tenant te in a confidential way. this compound attribute is used by the tenant provider of the resource to define the object attributes of this resource and the allowed action in the local policy with a confidential and an autonomy way. for instance, the compound attribute usedobject(mr;read;hh)(u) will be defined by the tenant hh to specify the object attributes of the object (of the type mr) used in the collaboration. the indices used in this function are: • objt ype: set of objects that satisfy a common property are classified into an object type. • (a : a): the action related to the authorization. • (te : t e): the tenant that will share the object o in the collaboration. 6 eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e3 c-abac: an abac based model for collaboration in multi-tenant environment figure 6. example: tasks definitions 4.5. a collaboration attributes based access control: c-abac model core c-abac is defined by the basic component sets, functions and authorization policy language given below: • u , o, t and t e represent finite sets of existing users, objects, tasks and tenants respectively. • a represents a finite set of actions available on objects. typically a = {create; read;update; delete}. • cte represents finete set of collaborative tenants (cte ⊆ t e). • ua, oa and ta represent finite sets of user, object and task attribute functions respectively. • for each att ∈ ua ∪oa ∪ ta, range(att) represents the attribute’s range, which is a finite set of atomic values. • attt ype : ua ∪oa ∪ ta→ {set; atomic}, specifies attributes as set or atomic values. • collabors : (cte : cte)→ t e, specifies the tenants that will use this collaborative tenant cte. • each attribute function maps elements in u to an atomic value or a set – ∀ua ∈ ua. ua : u → range(ua) if attt ype(ua) = atomic – ∀ua ∈ ua. ua : u → 2range(ua) if attt ype(ua) = set • each attribute function maps elements in o to an atomic value or a set – ∀oa ∈ oa. oa : o→ range(oa) if attt ype(oa) = atomic – ∀oa ∈ oa. oa : o→ 2range(oa) if attt ype(oa) = set • each attribute function maps elements in t to an atomic value or a set – ∀ta ∈ ta. ta : t → range(ta) if attt ype(ta) = atomic – ∀ta ∈ ta. ta : t → 2range(ta) if attt ype(ta) = set • uowner : (u : u )→ t e, required attribute function mapping user u to owner tenant te. • oowner : (o : o)→ t e, required attribute function mapping object o to owner tenant te. • towner : (t : t )→ t e, required attribute function mapping task t to owner tenant te. • uaowner : (uatt : ua)→ t e, meta attribute function, mapping user attribute ua to attribute owner tenant te. • oaowner : (oa : oa)→ t e, meta attribute function, mapping object attribute oa to attribute owner tenant te. • taowner : (ta : ta)→ t e, meta attribute function, mapping task attribute ta to attribute owner tenant te. 7 eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e3 m. madani, m. erradi, y. benkaouz • ua(u : u ) is defined only if (uaowner(ua) = uowner(u)) ∪ (uowner(u) ∈ collaborators(uaowner(ua))). • oa(o : o) is defined only if (oaowner(oa) = oowner(o)) ∪ (oowner(u) ∈ collaborators(oaowner(oa))). • ta(t : t ) is defined only if (taowner(ta) = towner(o)). • assigneduser(ta:ta;te:t e)(u : u )→ {t rue;false}, a boolean attribute function, mapping user u to true or f alse, which means that the user attributes that represent the user who is responsible to achieve this task ta will be defined by the tenant te in a confidential way. • usedobject(objt ype;a:a;te:t e)(o : o)→ {t rue;false}, a boolean attribute function, mapping object o to true or f alse, which means that the object attributes related to the object of the type objt ype will be defined by the tenant te in a confidential way. • an authorization that decides on whether a user u can access an object o in a particular task t for the action a, is a boolean function of u, o, and t attributes: rule: authorizationa(u; o; t)→ f (ua(u);oa(o); ta(t)), with the additional required condition that (uowner(u) = oowner(o) = towner(t)) ∪ (uowner(u) ∈ collaborators(towner(t)) ∩oowner(o) ∈ collaborators(towner(t))). 4.6. example: c-abac authorizations let us consider a telemedicine scenario where the school hospital (sh), the emergency medical services (ems), and the home hospital (hh) are three collaborating organizations. in this example, we apply the c-abac model on the telemedicine use case a telemedicine previously depicted by specifying authorizations for the tasks interpret_scan and take_a_decision as shown in figure 7. first, for each task we define a set of task attributes, set of user attributes that represent the user who is supposed to achieve this task and set of access permissions related to this task. a permission is an action on object. an object is defined by a set of object attributes. for instance (write,mr), (read, scan) and (read, video) are three permissions related to the task take_a_decision. access control authorizations in c-abac model are defined by the following the formalism shown in the figure 7: the authorization authorizationwrite(ti;u; o) that is shown in the figure 7 matches to ’the rule the radiologist interprets the scan images’ as specified at the first line in figure 6. this authorization is defined in the collaborative tenant ct 1 and is composed of a set of task attributes, user attributes and objects attributes. this authorization is valid for the action write if only if : (1) the instance ti is instantiated of the task interpret_scan; (2) the task instance ti belongs to the workflow tenemo; (3) the previous task instances of the ti are accomplished; (4) there is a collaborative session in which the task runs; (5) the user u is member of the collaborative session cs; (6) the object o is shared in the session cs; (7) the tenant sh authorizes his user u to perform the task t 5; (8) the tenant hh shares the object o of the type objectt ype with others collaborating tenants for the action write. the attributes assigneduser and usedobject are defined and evaluated in the tenant sh and hh respectively. this attribue assigneduser(t 5;sh)(u) = t rue if only if: (1) the user u plays the role radiologist; (2) u is at least level 1 of the neurology expertise; (3) u is at least level 2 of the radiology expertise; (4) u is at least level 0 of the cardiology expertise. the attribute usedobject(scan ;write;hh)(o) = t rue if only if: (1) the object o of the type scan; the sensitivity class of object o is less than or equal to class2. 5. implementation 5.1. system architecture openstack is a robust open-source iaas software for building public, private, community or hybrid clouds. opensteck is adopted by many cloud providers such as rackspace, ibm and redhat. openstack contains the following components: nova, swift, glance, cinder, keystone, and horizon. each component acts as a service which communicates with other services via message queues. keystone provides authentication and authorization for all openstack services. in our work, we focus on the swift object storage. swift is a multitenant, highly scalable and durable software defined storage system designed to store files, videos, virtual machine snapshots and other unstructured data [7]. it allows building, operating, monitoring, and managing distributed object storage systems that can scale up to millions of users. the account server is responsible for listings of containers, while container server is responsible for listings of objects. a container is a mechanism that stores data objects. an account might have many containers, whereas a container name is unique. a user represents the entity that can perform actions on the object in the account. each user has its own account and is associated to a single tenant. swift uses the access control lists (acl) to manage the access permissions. in fact, the acl model defines static access rules. it is not suitable for collaborative environment. in this paper, we implemented the c-abac model on the swift storage 8 eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e3 c-abac: an abac based model for collaboration in multi-tenant environment figure 7. example: c-abac authorizations component. this component acts as a service that communicates with other components (nova volume, nova compute, nova network, glance and keystone) via message queues. these components are loosely coupled. keystone is the identity service used by openstack for authentication and authorization. it provides a token signed by each user’s private key. let us consider the telemedicine scenario where the school hospital (sh), the emergency medical services (ems), and the home hospital (hh) are three collaborating organizations. these organizations share a common private cloud openstack. we consider that these organizations use the swift component for the storage service. in this use case, each organization is assigned to a swift account. (e.g. the accounts acc_sh , acc_ems and acc_hh represent the organizations sh , ems and hh respectively). this cloud provides a service of collaborative sessions for these organisations. this service allows a group of users, from different tenants, to collaborate in order to observe and treat a patient admitted in the home hospital (hh) emergency. in this example, we have a collaborative session cs1 of a telemedicine type. during a collaborative session, users may intervene dynamically without a prior knowledge of which user will access which object. in order to support c-abac model in the openstack swift environment and overcome the limitations of swift acl, we propose to extend the swift component by implementing a new c-abac module (figure 8). the c-abac module is composed of five components: figure 8. the system architecture user attributes, object attributes, task attributes, authorizations and the policy decision component. in the following, we describe each of these components: 9 eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e3 m. madani, m. erradi, y. benkaouz • user attributes: the security administrator defines the user attributes as a function that takes user as input and returns a value from the attribute’s range. (user1 : attr1 : val1) means that for the user user1 the value of the attribute attr1 is val1. for example, a user attribute function such as role ∈ uat t maps user1 ∈ u to a value neurologist. furthermore, the cloud administrator defines the attribute function uowner to specify the user owner. for instance (user1 : uowner : acc_sh) means that the user user1 is owned by the account acc_sh . finally, the administrator defines the attribute function joincs to specify which users could join the collaborative sessions. the value of this attribute is either true or f alse. (user1 : joincs : true) means that the user user1 could participate in the collaboration. • object attributes: the tenant administrator assigns the object attributes as a function that takes object as input and returns a value from the attribute’s range. (obj1 : attr1 : val1) means that for the object obj1 the value of the attribute attr1 is val1. furthermore, the cloud administrator defines the attribute function oowner to specify the object owner. for instance (mr1 : uowner : acc_hh) means that the object mr1 is owned by the account acc_hh . finally, the administrator defines the attribute function sharedcs to specify which objects could be shared in the collaborative session. for example, (p er_inf o1 : sharedcs : f alse) means that the object p er_inf o1 (personal information) could not be shared in the collaborative session. • task attributes : the administrator assigns the task attributes as a function that takes task instance as input and returns a value from the attribute’s range. (ti1 : attr1 : val1) means that for the task instance ti1 the value of the attribute attr1 is val1. furthermore, the cloud administrator defines the attribute function towner to specify the task owner. for instance (ti1 : towner : acc_ems) means that the task instance ti is performed by the account acc_ems. • compound attributes: the administrator of the local tenant defines the new attributes assigneduser and usedobject with a confidential and an autonomy way. these compound attributes are specified here as follows: usedobject|scan |write|hh : −o : objectt ype : scan ∧ o : sensitivity : class0|class1|class2, which means that this attribute is true if only if: (1) the object o of the type scan; the sensitivity class of object o is less than or equal to class2. • authorizations: the administrator specifies the authorizations policy. in our scenario, we consider that each tenant defines its policy rules. note that at this level, we suppose that the security policy rules are valid and conflict-free. the policy rules are specified here as follows: write − ti : task : interpret_scan ∧ ti : workf low : tenemo ∧ ti : previoustask : true ∧ ti : csession : cs1 ∧ u : membercs : cs1 ∧ o : sharedcs : cs1 ∧ u : assigneduser |t 5|sh : t rue ∧ o : usedobject|scan |write|hh : t rue, which means that for the action write’, this authorization is valid if only if : (1) the instance ti is instancied of the task interpret_scan; (2) the task instance ti belongs to the workflow tenemo; (3) the previous task instances of the ti are accomplished; (4) there is a collaborative session in which the task runs; (5) the user u is member of the collaborative session cs; (6) the object o is shared in the session cs; (7) the tenant sh authorizes his user u to perform the task t 5; (8) the tenant hh shares the object o of the type scan with others collaborative tenants for the action write. • policy decision: this component is responsible for evaluating the access request to the resources in the collaborative session based on the collected attributes values and authorizations. when a user sends a request to access a resource stored in the cloud swift, the policy decision component evaluates this request according to the policy rules in order to decide whether the user is authorized to access this resource or not. 5.2. enforcement model a general authorization process for swift component with c-abac module is illustrated in figure 9. when the user user1 attempts to access the resource mr1 stored in the swift. first, (1) the user requests keystone to get his/her token. (2) keystone generates a token and sends it to the user. (3) the user sends a request to abac module by using his/her token to access the resource mr1. the policy decision component receives this request to evaluate it. (4) during the evaluation process, the policy decision component requests the components: user attributes, object attributes and task attributes (5) to receive user1’s attributes, mr1’s attributes and the attributes related to the collaborative session wherein this user is member. (6) the policy decision component requests the authorizations component and (7) receives all the policy rules stored in this component. these attributes and 10 eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e3 c-abac: an abac based model for collaboration in multi-tenant environment figure 9. the enforcement model policy rules will be used by the policy decision to evaluate access request in order to decide whether the user is authorized to access this resource or not. (8) the policy decision will execute an acl command to assign the authorization decision (permit or deny) to the user in the swift environment. (9) the policy decision component executes a swift api command in the swift component using user1’s token in order to send the user1’s access request to swift. (10) user1 access to the resource mr1 if the authorization decision is permitted. 5.3. evaluation in this paper, we implement the abac and c-abac on the swift storage component of openstack. our experiments were run on a virtual machine with the following characteristics (memory 1024mb, 2 cores cpu, hard disk 30gb). we consider the download time of a swift object using abac model and cabac model. we observe that the performance of enforcing our approach depends on many factors, such as numbers of rules, number of attributes and number of concurrent collaborative sessions. in our analysis, we have used a synthetic dataset that contains up to 2000 rules, 2500 attributes and 25 concurrent collaborative sessions. figure 10(a) shows that the average time to authorize the access to a swift object with abac model increases with 13.4% and 22.7% for policies of 400 and 2500 rules respectively using the c-abac model. the waiting time for getting a policy decision becomes larger when there are too many authorizations to be collected. we acknowledge that our implementation works well for a large number of authorizations. furthermore, we compute the running time for access/deny decisions to a swift object using abac and c-abac model for 400 rules and for 500 to 2500 attributes. figure 10(b) shows that the average time for download of a swift resource with abac model increases with 7.6% and 19.6% for 500 and 2500 user attributes assignments using c-abac module. we acknowledge that our implementation works well for a large number of authorizations. finally, we compute the running time for access/deny decisions to a swift object using abac and c-abac model for 400 rules, 500 attributes and number of concurrent collaborative sessions with 10 to 50 active ones. figure 10(c) shows that the average time for access/deny decisions to swift resources using abac model increases with 20.1% and 34.7% for 10 and 50 concurrent collaborative sessions respectively using the abac module. we observe that our implementation works well for a medium number of active concurrent collaborative sessions. the overhead reaches 34.7% in an unusual situations where there are 50 concurrent parallel collaborative sessions. 6. conclusion in this paper, we present a novel abac based access control model called (c-abac). c-abac enables to ensure access control in collaboration between tenants in the cloud. c-abac allows the collaborating tenants to specify a global policy in a specific central point. it supports multiple concepts such as: task and workflow. the suggested model ensures the autonomy of tenant and preserves the confidentiality of each tenant object. finally, an architecture that integrates c-abac in the storage level of the cloud platform openstack has been described. the implementation results have shown that the suggested approach has a very limited overhead. 11 eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e3 m. madani, m. erradi, y. benkaouz figure 10. running time overhead for access/deny decisions references [1] p. mell and t. grance. the nist definition of cloud computing. nist special publication 800145 (draft). retrieved september 10, 2011, from http://csrc.nist.gov/publications/drafts/800-145/draftsp-800-145-cloud-definition.pdf. 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[21] m. a. madani, m. erradi, y. benkaouz. a collaborative task role based access control model. journal of information assurance and security, vol. 11, no. 6, pp. 348-358, 2016. 13 eai endorsed transactions on smart cities 02 2018 06 2018 | volume 2 | issue 8 | e3 1 introduction 2 background 3 related work 4 c-abac: the collaboration abac model 4.1 a collaborative tenant 4.2 a business process 4.3 assignuser function 4.4 usedobject function 4.5 a collaboration attributes based access control: c-abac model 4.6 example: c-abac authorizations 5 implementation 5.1 system architecture 5.2 enforcement model 5.3 evaluation 6 conclusion propaganda fragment detection and auto-fact-check in bi-lingual corpus 1 propaganda detection and challenges managing smart cities information on social media pir noman ahmad1 and khalid khan2,* 1school of computer science and technology, harbin institute of technology, harbin, china 2computer science and software engineering, university of stirling, uk abstract misinformation, false news, and various forms of propaganda have increased as a consequence of the rapid spread of information on social media. the covid-19 spread deeply transformed citizens' day-to-day lives due to the overview of new methods of effort and access to facilities based on smart technologies. social media propagandistic data and high-quality information on smart cities are the most challenging elements of this study. as a result of a natural language processing perspective, we have developed a system that automatically extracts information from bi-lingual sources. this information is either in urdu or english (ur or eng), and we apply machine translation to obtain the target language. we explore different neural architectures and extract linguistic layout and relevant features in the bi-lingual corpus. moreover, we fine-tune roberta and ensemble bilsm, crf and birnn model. our solution uses fine-tuned roberta, a pretrained language model, to perform word-level classification. this paper provides insight into the model's learning abilities by analyzing its attention heads and the model's evaluation results. keywords: machine translation, span, linguistic, neural architectures, bilsm. received on 10 december 2022, accepted on 25 january 2023, published on 30 march 2023 copyright © 2023 pir noman ahmad et al., licensed to eai. this is an open access article distributed under the terms of the cc bync-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v7i2.2925 1. introduction as information dissemination has become more widespread without quality control, users can spread misinformation and target individuals with propaganda campaigns via social media to advance their ideological agendas. there are two main forms of disinformation, which are propaganda and fake news, which differ in that propaganda may be constructed based on accurate information, whereas fake news may be built on top of false information or on top of intentional distortions. propaganda refers to actions or opinions of individuals or groups that are intentionally planned to inspire the actions or opinions of other individuals or groups toward specific goals [1,2]. various solution utilizes bert [3], a transformer-based [4] model relying on multiheaded attention, it purpose of the fragment-level propaganda (flp) classification. social *corresponding author. email: khk00014@students.stir.ac.uk media, mainstream media, and the online internet have become increasingly popular sources of information because of their sheer volume, which makes manual analysis impossible. translating text is an essential task to be able to into natural language sentences to accomplish this goal. an initial method of neural machine translation based on handcrafted translation rules [5]. data-driven approaches have gained more attention as large-scale parallel corpora have become available. the covid-19 crisis redefined administrative policies, citizens’ day-to-day lives, and communications among administrations and users by presenting new methods of working and providing public services. the most recent contributions in literature highlight the need to explore how humane smart cities can help manage critical issues in the administration of smart cities through entrepreneurship, governance, and citizens' inclusion [6], [7]. we are entering a new phase in automating our critical infrastructure when it eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities | volume 7 | issue 2 | https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ pir noman ahmad and khalid khan 2 comes to smart cities. internet-of-things devices now allow city operators to monitor granular levels of key municipal infrastructures and adjust resources accordingly because of their low cost. we detect bi-lingual propaganda fragments in a given text sample and perform two types of methods one is to use a direct dataset for identification. eng/ur or eng-ur using neural machine translation. additionally, we perform deep automatics machine learning techniques to retrieve information and fact-check on detected datasets [8], [9]. we cluster each using a k-mean cluster based on the rating score of each dataset. this paper presents a computational framework for detecting and extracting knowledge conflicts in text sources and identifying misinformation/propagandist fragments. based on deep mining algorithms, our solution translates structured information, and identify propaganda fragment and misinformation, which makes the following contributions: • we proposed a two-step transformers model that detects propaganda fragments in a bi-lingual text sample. • our model predicts and gathers the text sample through information extraction architecture, which assists the dataset in the training process. • the translation strategies applied by the subtitler in the english translation of the text, especially within the domain of the specific topics, that is, of the parts in the propaganda fragments with different denotative and connotative meanings. our paper is organized as section 1 represents the introduction. section 2 overview the brief on related work. the collection of data and the proposed method is explained in section 3. this section also explains propaganda fragment detection, which uses the nmt technique to detect the information retrieved data. section 4 explains the results and implementation of our experiments. section 5 concludes our paper and gives us future research directions. 2. related work when studying the inferences of social media on smart cities, it is vital to know the phases approximately new cities have previously approved in their placement. in a framework where mobile expertise modernizes governments and local authorities, stakeholders have gradually presented an attention in numerous kpis (key performance indicators) at a city level, using social media to simplify connections with citizens. a rahimi et al. answer numerous claims could assist in thoughtful the overall public expressive preference, a complex factor persuading decision-makers at several administration planes. social media stages are shown actual in identifying the granular particulars of local communities, playing a pivotal role in encouraging responsibility and transparency within a culture. a important volume of indication pointed out that us government representatives utilized social media platforms for responsibility in governing, which also aided participants and politicians in a more creative and precise study of a sequence of events that had earlier appeared dissimilar. health care has gone over numerous phases called healthcare 1.0, 2.0, 3.0, and 4.0. individually, khairol et al. [10] proposed these phases is a logical chain of one whole progress, ensuing in answering open challenges and earlier problems. the individual phase has its benefits, shortcomings, distinguishing features, approaches to providing health care, and technical and procedural novelties, where the research is required for considering the classification as a whole, classifying trends, and evolving future directions. several components have been artificially separated from the information extraction problem, including entity type classification, entity mention boundary identification, and event detection and categorization. there is rarely any feedback from the downstream classifiers when upstream errors are compounded and propagated to it, such as mislabeling an entity type [11]. bidirectional lstms and a bidirectional rnn (bi-rnn) are used in the new model for joint extraction of entities and relations. based on a bit-wise parsing operation between two entities, the bi-rnn structure predicts their relationship [12]. we studied the likelihood of the distribution of attention heads, the importance of the attention heads, and the impact of masking out layers [13]. the direct learning of this conditional distribution has been proposed in a variety of papers [14]. the neural machine translation (nmt) approach involves encoding sentence x source and decoding sentence y to target. the variable sentence source length encodes the target sentence using rnn fix-variable vector length [5], [15]. it is essential to convert unstructured text into a structured representation prior to developing automated knowledge analysis and fusion algorithms [16]. thus, to increase the accuracy of crossdocument entities, text fusion must solve cross-document entity co-reference problems simultaneously [17]. a recent study by rashkin et al. (2017) examined trust, satire, hoax, and propaganda (tshp) formats of text news for the detection of deception [18]. it is also considered as a task to fill a table with different entity extractions for multi-way classifications [19]. the active research areas cover textual record analysis involving linguistic and stylistic properties [16,17,18], in contrast to [23], a bidirectional rnn to label each pair of words. online fraud detection has extensively used authorship attribution and stylistic cues, including sockpuppet detection in wikipedia [24], the detection of deceptive online profiles, and the detection of fraudulent online behavior on social media [25]. these methods combine statistical classifiers with rule-based feature specifications, making high-level decisions based on the outcome of these methods. instead, our objective is to extract knowledge information in english language. for about twenty years, the concept of a “smart city” has received increasing attention in urban planning and governance [26], [27]. in light of current worldwide events, applying new knowledge in smart cities needs a combined structure to identify and stop a community health emergency. numerous numerical solutions have been established during the epidemic to implement an approach to comprehend the eai endorsed transactions on smart cities | volume 7 | issue 2 | propaganda fragment detection and auto-fact-check in bi-lingual corpus 3 spread of virus, which controls human anxiety, and joint comfort, and gather complex space-time procedures in a smart city associated to covid-19 protection methods. in several smart cities, the government set up contact-tracing apps, robots, and digital thermal gantries as well as civil society involvement in managing the spread of the virus to contain the pandemic crisis after the early first wave of the pandemic [28]. this combination proved essential to contain the pandemic crisis. technology enables people to maintain social distance while continuing their lives as a result of a pandemic, thus mitigating negative effects. digital skills and the willingness to adopt new technologies are not always present among citizens, governments, and organizations. it will be important to conduct further research to understand how citizens and individuals have adjusted to the technological changes imposed by the pandemic [29]. by strengthening citizens' involvement in policymaking, creating added value in the urban context, and enhancing crisis response capabilities, multiple technological points and their real-time data collection and sharing capabilities can significantly enhance well-being and quality of life. we are doing work on translation knowledge information extraction and bi-lingual propaganda detection is strongly related to treating conflict patterns [30], [31]. a global conflict pattern is constructed in a data corpus (text/smart cities mining) using local conflict rules as a basis for bilingual multi-source knowledge conflict detection, ass hsown in table 1. table 1. the previous proposed model and limitation smart cities method limitation risk management misinformation and fake news [32] smart city risks in the context of the covid-19 pandemic. survey on computing security over smart city [33] it focuses only on who accesses the data developed and conceptualized for the safety and privacy smart cities architectures [34] it does not provide non-repudiation that improves the quality of life propaganda detection system [35] support for numerous languages and a pull mode less instances sample that can facilitate the detection of propaganda character-level detection [36] computational text segregation in mixed-code pre-trained bert language model (lm) [31] identify specific propaganda span prosoul [32] generic analysis of various aspects of the propaganda detection system massive amounts of misinformation, hoaxy [33] track spreading and fact-checking in online information propaganda as neuro-linguistic [36] symbolic data corpora emerging forthcoming human-centered smart cities [41] safety, strength, interpretability, and principled 2.1. processive model given the best-performing systems from the last challenge, we chose the transformer-based model as our solution, focusing primarily on roberta [42]. roberta improves the language masking method of bert by eliminating the ns (next-sentence) pre-training target and training with abundant mini-batches and lr (learning rates) [43]. in recent years, many improved models based on bert have emerged, including distilbert [44], xlnet [45], albert [46] etc. roberta has been trained for longer than bert on massive data provided by researchers from facebook and washington university. we developed a roberta-based architecture with language masking and byte-level byte pair encoding (bpe) as a tokenizer to classify propaganda techniques [47]. our model used the roberta transformer for text classification. we used a pre-trained model on a given dataset and fine-tuned it with a fully-connected (fc) layer. rf (random forest classifier), providing precise baselines on classification and regression tasks. cnb (complement naive bayes classifier), using the similar value behind mnb while modifying its expectations and execution it appropriate for imbalanced data. mnb (multinomial naive bayes classifier), calculating the likelihoods of fitting to a class as a purpose of the rate of dissimilar words. 3. method a lot of research attention has been devoted to transformerbased networks in the recent past, such as bert [3] transformerxl and roberta [42]. the key mechanism for eai endorsed transactions on smart cities | volume 7 | issue 2 | 4 tracking mutual influence in these models is the use of a multi-head self-attention mechanism. the primary aim of the study is to signify text data based on their text contents and then assess words trend to comprehend citizens' sentiment and perception of the calculated smart cities in the pre-covid and post-covid times. 3.1. dataset the dataset provides nlp4if [48], and the training, the development, and the test contain 16,000 and 3,400 sentences, respectively. we also collect data through the information and knowledge extraction process and apply machine translation (google translation) to the extraction information data (ied), as shown in table 2. table 2. the statistics of train/test corpus used in our experiments dataset docume nt senten ce span nmt tshp train 430 7,184 7,184 eng-ur test 107 1,796 1,796 nlp4if train 16,000 32,800 eng-ur test 3,400 6,180 prosoul train 7400 11600 ur test 1100 2300 protext train 800 11,327 11,327 ur test 200 2,260 2,260 ied train 256 6,528 6,528 eng test 64 2832 2832 3.2. smart city tweets collection the twitter advanced search allows web scrapers to collect tweets that respond to query parameters. this application meets both adoption and privacy concerns. for pre-covid (before the covid period) and post-covid (after the covid period), we searched for tweets responding to the keyword "smart city" between january to december 2019 [49]. only the most relevant tweets from 32,334 tweets by 22,202 users are kept after a filter based on indicators related to identified constructs (e.g., virus, infrastructure, transportation, etc.). post-covid, there are 15,130 tweets compared to 17,204 tweets during the pre-covid period. as shown in table 3, cities are distributed as follows. table 2. an overview of the distribution of tweets among cities. city tweets london 18.086 milan 3.896 dublin 1.769 berlin 4.384 madrid 4.199 total 32.334 3.2. neural machine translation encoderdecoder the neural machine translation (nmt) approach is emerging newly to machine translation [14], [15]. with neural machine translation, a single, large neural network is built and trained, which reads and outputs a sentence correctly. in contrast to phrase-based translation, which contains many smaller subcomponents tuned separately. most nmt models are based on encoder–decoders in a multi-lingual task in which an encoder and a decoder for each language. nmt involves encoding specific languages (source) onto each sentence, then comparing the outputs to the source. we now propose a model in which each conditional likelihood is defined according to eq. 1. 𝑃(𝑦𝑖 𝑦1, 𝑦2, . . .⁄ 𝑦𝑖−1, x) = g(𝑦𝑖−1, 𝑠𝑖 , 𝐶𝑖) (1) where 𝑠𝑖 is hidden state (h) for time 𝑇𝑖, computed in rnn by 𝑠𝑖 = f( 𝑠𝑖−1; 𝑦𝑖−1; 𝐶𝑖) (2) the likelihood on each target word 𝑦𝑖 having a distinct context 𝐶𝑖 vector, unlike the current encoder-decoder as in eq. 2. the depends of input sentence of context 𝐶𝑖 vector on a hidden ( ℎ𝑖 = ℎ1, ℎ2, ….,ℎ𝑇) sequence annotations on an encoder. the collection of annotation sequence ℎ𝑖 focus on the input of i-th word which contains information of sourrounding part of input. the 𝐶𝑖 is, computed in eq. 3. which sum weighted of these annotations represented. 𝐶𝑖 = ∑ 𝛼𝑖𝑘 𝑇𝑥 𝑘=1 ℎ𝑘 (3) the weight 𝛼𝑖𝑘 of individual annotation hidden sequence ℎ𝑘 is calculated by 𝛼𝑖𝑘 = 𝑒𝑥𝑝 (𝑒𝑖𝑘) ∑ 𝑒𝑥𝑝 (𝑒𝑖𝑘) 𝑇𝑥 𝑘=1 (4) where alignment model show the position of input/output k and i match. 𝑒𝑖𝑘 = a( 𝑠𝑖−1, ℎ𝑘) (5) the birnn-based hidden ℎ𝑖 state score 𝑠𝑖−1 input sentence just before emitting 𝑦𝑖 , and the j-th annotation ℎ𝑘 eq. 5. a feedforward neural network is used to parametrize the alignment model a while other components of the proposed system are used as well. by calculating an expected annotation from a weighted sum of all annotations, we can understand the approach of taking an expected alignment. the likelihood of 𝛼𝑖𝑘 the target word 𝑦𝑖 aligning with a source word, or converting from a source word, is 𝑥𝑘. then, pir noman ahmad and khalid khan eai endorsed transactions on smart cities | volume 7 | issue 2 | propaganda fragment detection and auto-fact-check in bi-lingual corpus 5 context 𝐶𝑖 vector of the i-th word is expected 𝛼𝑖𝑘 likelihoods over all the annotations. the likelihood 𝛼𝑖𝑘, or its related 𝑒𝑖𝑘, reflects the significance of the annotation ℎ𝑘 with aforementioned hidden state 𝑠𝑖−1 in determining the following state 𝑠𝑖 and making 𝑦𝑖 . this method does not consider alignment as a latent variable like traditional machine translation, as shown in figure. 1. figure. 1 neural machine translation source-target pipeline the input sequence x in eq. 1 described rnn starting symbol 𝑥𝑖 to t the last one 𝑥𝑇𝑘 . the proposed method summarizes the annotation of each word, which lead us to use multi-layer bidirectional rnn and lstm (birnn|bilstm) [50], which has been used successfully in text classification, sentiment analysis, and speech recognition [51]. a birnn and bilstm consists of forward and backward layers. the forward and backward layers rnn/lstm 𝑓 reads the sequence input/output as forward and reverse order. the rnn/lstm read (𝑥𝑖 − 𝑥𝑇𝑘 .) and calculates hidden states ( ℎ𝑖 ⃗⃗⃗⃗⃗ = ℎ1 ; ℎ2 , … , 𝑥𝑇𝑘 ) of the 𝑓 forward layer. while the backward rnn/lstm read ( 𝑥𝑖 − 𝑥𝑇𝑘 .) and calculates hidden states ( ℎ𝑖 ⃖⃗ ⃗⃗⃗ = ℎ1 ; ℎ2 , … , 𝑥𝑇𝑘 ) of the 𝑓 backward layer. the forward 𝑓 and backward hidden state [ℎ𝑖 ⃗⃗⃗⃗⃗ ℎ𝑖 ⃖⃗ ⃗⃗⃗], i.e., ℎ𝑘 = [ℎ𝑖 𝑡⃗⃗ ⃗⃗ , ℎ𝑖 𝑡⃖⃗ ⃗⃗ ] concatenating an annotation for each word 𝑥𝑗 . to summaries preceding and the following words contains the annotation ℎ𝑗 using forward backward rnn/lstm approach. 3.3. propaganda fragment given a text sample, detect all fragments/spans of propaganda present in the given sample text. it is also necessary to identify, for each span, the propaganda technique that was employed. the sentence-level propaganda (slp) and fragment-level propaganda (flp) approach is followed by two components: the information extraction feature and information classification and ensemble component. information extraction features indicate the combination of linguistic investigation, layout, and topical features of rnn and logistic regression. while our rnn/bilstm model, we concentrate the pruning feature in the last hidden layer before classification using roberta. our final model fine-tuned roberta and achieved the sota results with an ensemble of bi-rnn, crf and bilstm. in the final component, we gather the likelihoods propaganda label for each sentence and thus, obtain m number of prediction classifiers for each word token, as shown in figure. 2. figure 2. the proposed fragment level propaganda classification ensemble model flowchart eai endorsed transactions on smart cities | volume 7 | issue 2 | 6 in multi-models, we designed fragment-level propaganda (flp) as sequence taggers [19]. bilstm-crf with word embeddings (𝐸𝑤 ) and character embeddings 𝐸𝑐, tokenlevel features (𝐸𝑇 ) i,e, pos, ner, etc. flp and slp performs jointly with lstm-crf+fine-tune that roberta 𝐸𝑠𝑒𝑛𝑡 , and 𝐸𝑊 (sentence and word embedding) respectively. we fine-tune roberta and ensemble multi-task bilstm-crf, in each sequence tagger considering propagandista span/fragments. when the span overlaps exactly, our model performs at fragment level majority voting for span/fragment, while non-overlap span/fragment our model considers all and truncates it. but when span/fragment overlap with the identical label our model selects the larger span, as shown in figure. 3. figure. 3. prop/nprop and bioe tags samples with the given instance 4. method the model trained nvidia rtx 3090 ti graphic cards. a python-torch-transformers package is used to implement our implementation. a mixed precision model was used to train all the models in the aim of accelerating training time. 4.1. evaluation metrics the f1-score can be classified as a primary metric in the context of our study, whereas p and r can be classified as a secondary metrics, as shown in eq. 6. f1 = ( p ∗ r p + r ) ∗ 2 (6) p = precision = tp/(tp + fp) r = recall = tp/(tp + fn) where tp is true positive, fp, fn is a false positive and false negative, respectively, while p = precision = tp tp+fp , r = recall = tp tp+fn are statistics for the binary classification. evaluation metrics for classification were used the following metrics evaluating the rule-based classification results. as roberta-based is case-insensitive, we chose a version that uses lowercase letters throughout the text, whereas biobert only uses case-insensitive letters. according to table 3, all models were based on the same hyperparameter values. using tensorflow, the roberta layer's hyper parameters were the same as those used in the roberta layer. table 3 list of all hyperparameter values used in experiments. parameter values learning rates 3 x 10−5 epochs 15 bach-size 16-64 sequence length 80-150 embedding size 8-16 token size 4-50 4.2. implementation process the results obtained on bi-lingual corpus, which identify propaganda fragment, with fine-tuned roberta, and ensemble our model with bi-rnn, crf and bilstm model. our model with twelve layers and 64 batches, 180 sequences, 0.1 weight decay, and 15 epochs were trained on all models, on protext ur, as shown in table 4. table 4. fragment identification on bi-lingual corpus results protext ur. model f1 p rl baseline 0.4134 0.4029 0.4188 roberta-rnn 0.4657 0.4780 0.4622 roberta-crf 0.5969 0.5803 0.5811 roberta-bilstm 0.6615 0.6628 0.6529 roberta-bilstm-crf 0.7031 0.7002 0.6984 our tc 0.8871 0.8840 0.8798 our model use the roberta baseline show low results with f1-score 0.4134, precision 0.402, and recall 0.418. roberta-rnn tokenized with crf with f1-score of 0.4657, precision 0.478, and recall 0.462. roberta-crf tokenized with crf with f1-score of 0.5969, precision 0.5803, and recall 0.5811. roberta-bilstm tokenized with crf with f1-score of 0.661, precision 0.662, and recall 0.652. roberta-bilstm-crf tokenized with crf with f1-score of 0.703, precision 0.7002, and recall pir noman ahmad and khalid khan eai endorsed transactions on smart cities | volume 7 | issue 2 | propaganda fragment detection and auto-fact-check in bi-lingual corpus 7 0.698. our tokenized with crf with f1-score of 0.887, precision 0.884, and recall 0.879. the corpus on fragment identification on protext eng (english), as shown in table 5. our model use the roberta baseline show low results with f1-score 0.452, precision 0.461, and recall 0.451. roberta-rnn tokenized with crf with f1-score of 0.312, precision 0.328, and recall 0.320. roberta-crf tokenized with crf with f1-score of 0.490, precision 0.485, and recall 0.489. roberta-bilstm tokenized with crf with f1-score of 0.545, precision 0.539, and recall 0.541. roberta-bilstm-crf tokenized with crf with f1-score of 0.516, precision 0.509, and recall 0.519. our tokenized with crf with f1-score of 0.628, precision 0.624, and recall 0.628. the corpus on fragment identification on protext eng (english), as shown in table 6. table 5. fragment identification on bi-lingual corpus results on protext eng. model f1 p r baseline 0.4527 0.4613 0.4518 roberta-rnn 0.3120 0.3283 0.3204 roberta-crf 0.4909 0.4856 0.4891 roberta-bilstm 0.5425 0.5399 0.5419 roberta-bilstm-crf 0.5164 0.5098 0.5197 our tc 0.6285 0.6243 0.6280 table 6. fragment identification on bi-lingual corpus results on protext nmt. model f1 p r baseline 0.6582 0.6677 0.6648 roberta-rnn 0.5378 0.5289 0.5274 roberta-crf 0.6909 0.6896 0.6886 roberta-bilstm 0.7815 0.7628 0.7649 roberta-bilstm-crf 0.8137 0.8095 0.8177 our tc 0.9071 0.8940 0.8898 compared to the protext with ur, and eng, the nmt achieved f1-score of 0.658, precision of 0.667, and recall of 0.664 on the baseline. roberta-rnn tokenized with crf with f1-score of 0.537, precision 0.528, and recall 0.527. roberta-crf tokenized with crf with an f1score of 0.690, precision 0.689, and recall 0.688. roberta-bilstm tokenized with crf with f1-score of 0.781, precision 0.762, and recall 0.764. robertabilstm-crf tokenized with crf with f1-score of 0.813, precision 0.809, and recall 0.817. our tokenized with crf with an f1-score of 0.907, a precision of 0.894, and recall of 0.889. the protext ur uses google translation to achieve the target language from protext eng. in the above performance comparison, the protext nmt corpus shows a higher f1-score of 0.9071 among all other corpora. finally, the evaluation performance accuracy is compared with 100 examples for each dataset, as shown in figure 4. figure. 4. prop model evaluation performance comparison with the given instance (100) of various datasets in covid-19, the widespread propaganda sentiment analysis that appeared from civilians' tweets from various cities (milan, madrid, london, and dublin) is propagandist. the analysis reveals that in madrid, the propaganda is created from the awareness of the failure to use identity and technology, the requirement to raise information and study how digital tools would be employed. furthermore, p-values are re-counted to estimate the coefficients' degree of awareness (importance). the dissimilar significance values are p < 0.26, as shown in figure 5. eai endorsed transactions on smart cities | volume 7 | issue 2 | 8 figure 5. covid-19, the widespread propaganda sentiment analysis in cities-based 4. conclusion and future direction the rapid spread of information on social media has resulted in an increase in misinformation, false news, and propaganda, which is most challenging aspects of this study, securing high-quality bi-lingual propaganda data from news sources. our system analyzes bi-lingual sources and extracts information automatically based on a natural language processing perspective. using neural machine translation or google translation, to get urdu or english bilingual corpus instances is explore neural architectures, as well as extract linguistic features. furthermore, we use fine-tuned roberta, a pretrained language model, to perform word-level classification as well as experiments with different ensemble schemes such as majority votes and relax votes. moreover, the misinformation and propaganda on social media are detected in the framework, and it can be 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[51] a. graves, n. jaitly, and a. mohamed, “hybrid speech recognition with deep bidirectional lstm,” in 2013 ieee workshop on automatic speech recognition and understanding, 2013, pp. 273–278. eai endorsed transactions on smart cities | volume 7 | issue 2 | intelligent dashboards to monitor the occurrences in smart cities – a portuguese case study eai endorsed transactions on smart cities research article 1 intelligent dashboards to monitor the occurrences in smart cities – a portuguese case study r. silva, m. silva, g. caldas, f. portela* and h. santos algoritmi center, university of minho, azurem campus, guimarães, braga, portugal abstract this article concerns the needed response by the professional fire brigade regiment (fbr) in the city of lisbon. to solve and answer the question "how to improve fbr intervention requests when an emergency is detected?" the project aims to create a functional prototype containing interactive dashboards allowing the analysis of indicators that improve decision capacity. as results attest, 58% of false alarms are cancelled even after the emergency and rescue means have been activated to the location. about 97% of the suspended requests are not cancelled before the means are sent. the number of records of occurrences tends to increase over the 8 years of study. sunday is the weekday with the highest number of associated records, with 23.33%, specifically at 9 am and 8 pm. autumn is the season with more occurrences, with 26.51%. more than 50% of the occurrences are in the administrative services closing time and more than 50% of the registrations send only one vehicle to the place. these indicators aim to understand if these variables are probabilistically associated with requests for interventions to be able to anticipate these scenarios and help in decision-making whenever necessary. keywords: smart cities, business intelligent, intervention requests, data science, big data.. received on 25 october 2022, accepted on 17 december 2022, published on 27 december 2022 copyright © 2022 r. silva et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i4.2796 1. introduction the united nations (un) analysed the growth for the next 30 years. the world population is expected to grow by 2 billion people, from 7.7 billion to 9.7 billion [1]. it is possible to perceive a high population growth with a transition to an increasingly urbanised population which paves the way for different challenges in different areas, especially in the sustainable development of a smart city [2]. one of these challenges is developed in this article, which is, the assurance of response to emergency requests by the emergency and rescue services. based on this scenario, technology emerges as a predominant factor to assist the management of cities today. today’s smart cities have certain patterns in common, such as: *corresponding author. email: cfp@dsi.uminho.pt  according to weiss et al. [3] smart cities are cities that focus on a particular model, with a modern vision of urban development and that recognize the growing importance of information and communication technologies in directing economic competitiveness, environmental sustainability, and quality of life in general;  with the increasing development of technologies associated with cities, a high amount of data to be generated daily was observed. as previously understood, there are certain challenges that a smart city must overcome and the amount of data to be created by the technological infrastructures inserted in cities is one of them;  the search for solutions through technology stands out and there are more and more solutions to fight these challenges to ensure the sustainable growth of cities; eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e4 mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ mailto:cfp@dsi.uminho.pt r. silva, et al. 2  however, beyond the huge amount of data to be generated, it is important to understand that these have different formats, making the analysis process much more complex and intensive for those who use these data. furthermore, all cities have their mode of operation, i.e., no city is similar and therefore the needs tend to be specific and objective when making decisions; the portuguese capital city, lisbon, is the case study of this article. it has about 500,000 inhabitants, which explains why requests for help during an emergency tend to be rather critical. the lisbon professional fire brigade regiment (fbr) is the focus entity of this article. it is responsible for the safety of people and goods in the city through rescue actions, prevention, and civil protection support. the article’s objective is to help solve a challenge suggested by lxdatalab, a management and urban intelligence centre of lisbon. this challenge focus on:  historical homologous periods of the occurrences of the fbr and other entities, characteristics, state and causes of the occurrences and degree of risk, among others;  three main focuses: a temporal analysis, an understanding of the occurrences’ characteristics and finally the mode of intervention and the current state of the occurrences;  a big data problem, in the sense of transforming this high amount of data into a highly effective and efficient process for the fbr when decision-making is necessary, specifically in an emergency intervention request;  solve the problem and answer the question "how to improve fbr intervention requests when an emergency is detected?";  developing a functional prototype containing interactive dashboards allowing the analysis of citystate indicators and the identification of variables that may be associated with intervention requests to anticipate these scenarios; the data were analysed in the “talend data quality” tool to understand the data provided, and their quality and get some conclusions. after that, the data provided in 3 spreadsheets (.xls) was properly organised in a data warehouse to reach a result. the data warehouse structure consisted of a table of facts and eleven dimensions, which were placed in a sql database using the workbench management tool. the transformations that some attributes had to undergo were performed through mysql commands. the result was illustrated with dashboards using the data visualization tool, tableau. the article is structured into seven chapters. the first chapter addresses the objective of the case study and its relevance. the second chapter refers to the background, explaining the basic concepts present in the practical development of the article and the kind of work already done regarding the subject. three previous works were studied. the third chapter presents the materials and methods used for the execution of the article as well as the data model and tools used. the fourth chapter shows the results of the case study. the fifth chapter presents the discussions, an analysis of the main results obtained, as well as measures to act on these events. in the sixth chapter, one can read the conclusions of the development of the prototype and in the seventh chapter the bibliographical references used for the development of the article. 2. background today, there is a variety of new challenges in our cities, created by technological advances and urban development. these challenges lead to the smart city concept. for anthopoulos [4] a smart city is defined as an innovative city that uses information and communication technologies and other means to improve the quality of life, the efficiency of operations and urban services. however, managing a smart city is not an easy process. making a good decision at a critical moment can lead to a more efficient operation, a more profitable city, or perhaps more satisfied citizens. this is how the concept of business intelligence (bi) emerges. at the moment, bi is understood as a set of data that has been collected from the past and the present to make better decisions about the future. this data is selected through certain criteria to draw conclusions. business intelligence makes the whole process of decisionmaking more intelligent, clearer, and as likely to be the future [5]. equally important, the concept of data science emerges, and this concept came from the accelerated growth in government and trade data creation [6]. according to cady [7] the concept is explained through complex algorithms and analysis that organise the data, being possible to obtain forecasts, to help in decisionmaking with greater accuracy, speed and efficiency, concrete hypotheses are obtained, being also possible the anticipation of future scenarios. however, managing and analysing data always offer great benefits to organisations as it is understood. however, as a result, they also imply other challenges. in this way, the concept of big data has expanded to explain a situation in which the logistics of storage, processing or data analysis have surpassed the traditional operational skills of organizations [8]. 2.1. smart-cities (and type of occurrences) the “smart-city” concept has become extremely popular and consists of the use of a plethora of it innovations to make cities smarter for the citizens. this concept first appeared in the 1990s and the main focus was on the impact of new information and communication technologies on modern infrastructures within cities. eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e4 https://www.talend.com/products/data-quality/ https://dev.mysql.com/doc/workbench/en/wb-intro.html https://www.tableau.com/ intelligent dashboards to monitor the occurrences in smart cities – a portuguese case study 3 a dense environment, like that of cities and capitals, requires its subsystems to work as one system with intelligence being infused into each subsystem. according to [9,10], they indicated that the smart city has six possible characteristics: smart economy, smart people, smart governance, smart mobility, smart environment, and smart living. with smart-city it is easier to acknowledge the occurrences happening, and the prevention of them, so the response to requests for intervention in an incident by the emergency and rescue services would be more effective. anepc (portuguese national emergency and civil protection authority) identified 143 types of occurrences, for example, fires, road accidents, harsh weather, and hazards [11]. several works with positive impacts have been done combining data science and iot and using actual occurrences, disasters or socio-economic data to create smart and sustainable cities. [12–14]. 2.2. related works the purpose of this subchapter is to analyse works related to the inherent paper. a portuguese decision support system the first work analysed refers to a dissertation under the theme “cidades inteligentes: um novo paradigma urbano estudo de caso da cidade do porto". the objective of this work was to understand and demonstrate what is the situation in the city of porto, as a future potential intelligent city [15]. this dissertation studied several projects, one in particular to create a centre that would support decisionmaking in the city. the creation of this centre includes elements from the areas of mobility, police, firefighters, civil protection and environment, among others. however, it is an experimental pilot work, unique in portugal. this centre has tried to respond to the city's problems, for example, when someone needs to break a door down it takes an average of 2h30 to do it. given the objectives presented in this work, it provides knowledge and explains the characteristics of the city of porto, intending to create a project to support the decisionmaking for the different problems of the city later on. however, it is only experimental, whilst the present article elaborates a functional prototype of interactive dashboards with real data from the city of lisbon, which found patterns and variations to help decision-making. a project that investigates mobility in cities the second work analysed concerns a dissertation named: "centro de operações integrado: câmara municipal do barreiro cidades inteligentes análise de um estudo de caso". the goal of this dissertation was to analyse and prepare an integrated solution between existing domains at barreiro municipality, creating all the essential conditions, both in terms of infrastructure, communications and the response provided by the municipality to the needs and expectations of its citizens [16]. this dissertation focused on the challenge of mobility in cities. however, this challenge was not only solved by the increase of existing public transport fleets, but also with their modernisation and use of technologies enabling their control and management. even though the goal has been achieved, there was no real implementation of the project as the data sources were not provided, as well as some essential application resources. the work elaborated in the article has an added value, as the lisbon municipality provided the actual data for the project, and in addition to traffic data, climate data and historical data of fbr occurrences were also provided. app: building intelligence system the third work analysed no longer concerns portugal, but boston. firefighters when responding to an emergency call of an occurrence like a fire in a building, have a very short time to evaluate the situation and plan a response. although governments collect a wide variety of information about each building in cities, most fire departments do not have access to this data, leading to unnecessary risk exposure and the inability to make informed firefighting decisions [17]. thus, building intelligence system emerged as a web application that integrates seven sources of city data to provide an optimised view of individual buildings in boston. this technological solution, although well implemented, only responds to requests for help in the type of occurrences such as fires. the other objective of this article is to find variables that might be associated with any type of emergency request. 3. materials and methods for the development of the project, it was necessary to use different tools for different purposes as well as different methodologies. firstly, case study was used with the objective of understanding in detail the case under study to help formulate the problem that the article intends to answer [18]. then, in a second moment, lab experiments was used, which consisted in performing a set of tests and configurations on the chosen variables to analyse the data under study, which in the practical part was developed and tested [19]. with these experiments, one was able to comprehend and identify the trends of the variables under study to understand how they evolve and respond to the paradigm of this article. the first phase did not fully use the case study methodology because only a case was created, but it was essential to understand the topic. the data science team did not have any expertise in managing occurrences at the beginning, and this phase was crucial to understanding the issues and getting sensitive to this area. this phase involved studying the environment and selecting the case from the several datasets received before proceeding with the lab experiment work. the experimental work was eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e4 r. silva, et al. 4 developed to answer the main questions (kpis formulated), so an extract transforming and loading (etl) process was conducted. then, a set of intelligent dashboards was prepared using the selected data. the research process followed the lab experiments steps combined with a case study: 1. examine the need for the experiment (case study); 2. define the objective for the experiment (case study); 3. define measures; 4. identify the important variables; 5. perform experiments; 6. analyse results; 7. act on results; 8. create reports. figure 1 explains and illustrates what kind of technologies and tools were used as well as their designation. as illustrated in figure 1, the initial focus for the project development was to have data sources to feed the analytical system intended to be built. these data sources were provided by lxdatalab in spreadsheet (.xls) format. these data divide into 3 spreadsheets, and each has 65,000 occurrences, which makes a total of 195,000 occurrences. once this stage was concluded, an analysis of the data provided in the "talend data quality" tool was undergone to understand what data were provided, their quality and conclusions about the attributes that feed the data sources. after understanding the characteristics of the data, that is, analysing the type of data delivered and what format they were in, it was intended to store them in a structured database. therefore, it was necessary to build a central structure in which the data were optimised and integrated. the data chosen to respond to the case under study and after being properly organised were placed in a sql database using a workbench management tool. the transformations that some attributes had to undergo were performed through mysql commands. in the last stage of the process, after the database was operational and properly loaded, the tableau tool was used for the analysis of the data obtained. in this stage, interactive dashboards were created to find patterns and facts that help decision-making when needed by the emergency and rescue services. in table 1 it is possible to visualise which tasks were performed in each tool. table 1. tool used for the development of the tasks inherent to this paper tool tasks talend etl (extract transform load) mysql data base tableau data visualization equally important was to understand how the data were organized and to do this kimball's approach was used. a data warehouse was built, through data collection, subject-oriented, integrated, non-volatile and time-varying to support management decisions [20]. for this, an entity and relationship diagram (erd) was developed. figure 2. entity and relationship diagram (erd) figure 2 shows the erd with the respective table designations, the relationship between them and the respective attributes such as metrics, primary keys, and foreign keys. the model is conceived in a star model containing a fact table, and eleven-dimension tables. the fact table, called “occurrences_management” is made up of sixteen foreign keys and four facts that result from the connection to the dimension tables and four facts. 4. experimental case study after receiving the datasets, the team identified the occurrences data as the most relevant to use in this work. then the team needed to study the lisbon reality and understand the type of occurrences, their needs, and figure 1. structure of the procedure to be performed eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e4 intelligent dashboards to monitor the occurrences in smart cities – a portuguese case study 5 features, among other details. after finishing the understanding phase, indicators were defined to answer the main questions. then was time to work with the data and do the etl process. during the preparation process (etp) a data quality analysis was performed, and a set of classes was created to help classify the data. finally, the data were analysed, the kpis were implemented, and the dashboards were produced. this chapter explains the main results of the last stage of the project, a business intelligence analysis, after using the kimball methodology and following lab experiment steps. 4.1. data preparation the analysis through a graphic visualisation makes the analysis much more intuitive and immediate. this way dashboards were elaborated with the help of the statistical data visualisation tool tableau. for the development of the project, the data were provided by the lxdatalab entity. real data from the city of lisbon were sent, thus, it is important to notice that these data are written in portuguese. however, before presenting the analysis, it is also important to understand which data were selected. the data used refer essentially to occurrences such as:  history in homologous periods of the occurrences of the fbr and other entities;  distribution of occurrences among the different civil parishes of the municipality of lisbon;  number of elements and vehicles sent to the location of the occurrence;  type of occurrences and most registered categories;  closing status of the occurrences;  entities which trigger more occurrences;  management of false alarms and suspension of intervention requests;  degree of risk of the occurrences. having understood what kind of data was chosen, an analysis is then carried out with the assemblage of these variables to find patterns and facts that help the decisionmaking, when necessary, by the emergency and rescue services. 4.2. data analysis the carried-out analysis aimed to answer some important questions as well as enter standards to help and facilitate decision-making. the analysis carried out is divided into three major focuses:  time analysis of occurrences;  analysis of the characteristics of the occurrences;  analysis of the mode of intervention and status of occurrences. time analysis of occurrences before analysing patterns in the city of lisbon, it is important to understand in a temporal way how occurrences are being conducted and how they tend to evolve. this temporal analysis refers to the homologous period from 2011 to 2018 and intends to answer five main questions: 1. how do occurrences tend to evolve? 2. which season of the year tends to have more occurrences? and how are these occurrences? 3. which categories of occurrences exist more regularly in the different seasons of the year? 4. on which day of the week and month are there more occurrences? 5. depending on the day of the week, what is the time of most occurrences? the answers obtained to these five questions and after the analysis of the dashboards resulted in the following:  over the years the number of recorded occurrences tends to evolve;  the season with the highest percentage of records, 26.51%, is autumn;  in autumn, the type of occurrence with 69.93% that stands out is infrastructures and roads;  the category of occurrence that stands out in summer is related to buildings. in winter it is water supply, road cleaning and flooding. in spring, occurrences that need support to the population and in autumn the occurrences related to transportation and equipment;  sunday is the day of the week with the highest tendency to register occurrences, with 14.81%;  on monday, the hour with more associated records is 10 pm, with 21.67%;  on tuesday, the hour with more associated registers is 1 pm, with 25.42%;  on wednesday, the hour with more associated registers is 4 pm, with 23.33%;  on thursday, the hour with more associated registers is 4 pm, with 20%;  on friday, the hour with more associated registers is 6 pm, with 30%;  on saturday, the hour with more associated registers is 10 am, with 21.67%;  on sunday, the hour with more associated registers is 9h and 8 pm, with 23.33%. after completing the temporal analysis, an analysis of the characteristics of the occurrences was also elaborated to understand in detail what was happening. analysis of the characteristics of the occurrences once the temporal analysis is concluded and understood as the occurrences happen and tend to evolve in time, the main characteristics of the occurrences under study are eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e4 r. silva, et al. 6 addressed. after looking at the characteristics of the occurrences, the aim is to answer eight questions: 1. how are the occurrences geographically arranged in the civil parishes of the municipality of lisbon? 2. which civil parish in the municipality of lisbon has the highest number of registered occurrences? 3. what happens in more detail in the 5 civil parishes of the municipality of lisbon with the highest number of registered occurrences? 4. how does the degree of risk differ in the civil parishes of the municipality of lisbon? 5. depending on the type of occurrence, which entities mainly trigger the emergency call? 6. which type of occurrence is registered more often? does the month have any influence? 7. depending on the type of occurrence, how many elements of the emergency and rescue services on average are sent to the location? 8. depending on the type of occurrence, how many vehicles are sent to the location? figure 3 shows that the highest number of occurrences recorded is in the civil parish of benfica with 7,351%. to understand this fact, separate research was carried out on the number of inhabitants in these civil parishes of the municipality of lisbon and one can see that, in ascending order, there are more inhabitants in the civil parishes of lumiar, benfica and olivais. it is, therefore, possible to conclude that although the civil parish of benfica is one with the highest number of inhabitants, it does not interconnect to the highest number of occurrences. in short, it is possible to conclude from this analysis that:  100% of the occurrences recorded in the civil parish of lumiar are at the level of services, particularly in the collection and rescue of animals;  the civil parish of parque das nações shows 50% of occurrences with chemicals and 50% of eventual river dumpings:  the civil parishes of misericórdia, beato, marvila and ajuda (100%) have in their history occurrences of moderate risk only;  the civil parish of são vicente (6.90%) is the one with the highest percentage of records of high-degree occurrences;  43.48% of the fire occurrences are triggered by security forces;  50% of the pre-hospital occurrences are triggered by medical emergency;  the types of occurrences more often recorded are "activities", "services" and "fires”;  the number of vehicles sent to an occurrence, regardless of its type, is one vehicle only;  an average of 6 elements are sent to the place of occurrences such as legal conflicts, civil protection, infrastructure and roads or technological and industrial incidents;  when the type of occurrence is fire, 4 vehicles (4.35%) are sent to the location. once all the main characteristics inherent to the occurrences under study have been concluded and assimilated, it is also important to analyse the mode of intervention and their state. thus, the following analysis tends to highlight some evidence of the state of the occurrences to help decision-making and, additionally, assist in the execution of the whole procedure when an occurrence happens. analysis of the mode of intervention and the state of the occurrences it was intended in an intuitive way to address the existence of false alarms of occurrences, the suspension of means of intervention related to the number of vehicles/elements sent and the final status of the occurrences. this way, it is possible to answer six questions: 1. when there is a false alarm, even after activating the emergency and rescue services, in what state is the occurrence? 2. is there a suspension of the request for support before activating the emergency and rescue services? 3. being a false alarm or suspension of occurrence, how many vehicles of the emergency and rescue services are sent to the location? 4. does the state of the occurrence influence its degree of risk? 5. does the entity that triggers the occurrence influence the state of the occurrence? 6. does the entity that triggers the occurrence influence its degree of risk? below are the answers to the above questions, intending to find standards for effective improvement in the management of occurrences. in short:  58.82% of the false alarms are cancelled even after the emergency and rescue means of intervention for the location have been activated; figure 3. geographical analysis of the civil parshes of the municipality of lisbon eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e4 intelligent dashboards to monitor the occurrences in smart cities – a portuguese case study 7  97.10% of the requests for suspension are not cancelled before the means are sent to the location;  be it a false alarm or a distressed call suspension, an average of 1 vehicle is sent;  the higher the degree of risk associated with the occurrence, the state of the occurrence is “administrative closure”; the state associated with a zero risk occurrence is “operational closure”;  regardless of the entity that triggers the occurrence, the state of the occurrence is mostly “administrative closure” and its degree of risk is moderate;  the management of occurrences and intervention requests (gopi) and the volunteer fire department (cbv) entities have 100% of records with a moderate degree of risk;  the lisbon municipal council (cml) entity has 100% of records with a high degree of risk;  the municipal civil protection service (smpc) entity has 77.78% of records with zero risk degree. 5. discussion once the development stage is over, an analysis of the main results obtained is made, as well as the measures adopted. table 2 is a summary of the relevant results achieved and the respective measure table 2. analysis of the main results with the respective measure of action event measures autumn is the season that registers more occurrences, with 26.51% there is a similarity between all seasons. the category of occurrence that stands out in the different seasons of the year:  summer is related to buildings;  winter relates to water supply, road cleaning and flooding;  spring occurrences relate with support to the population;  autumn occurrences relate to transportation and equipment. special attention to the occurrences most often recorded in a different season of the year is needed as well as an increase in the number of elements sent to the location. sunday, with 23.33%, is the weekday with the highest number of associated records, specifically at 9 am and 8 pm. special attention to this day and time to prevent the registration of occurrences needed. the civil parish of benfica registers more occurrences (7,351%). the intervention of emergency and rescue services must be increased in the civil parish of benfica. the civil parish of lumiar registers 100% of occurrences at the level of services, particularly in the collection of animals. the population of lumiar must be informed that the recorded occurrences happen with animals. 50% of the occurrences in the civil parish of parque das nações happen with chemicals and the other 50% are river dumpings. the population of the civil parish of parque das nações should be alerted to this type of occurrence. the civil parish of são vicente (6.90%) has the highest percentage of records of occurrences with a high degree. special attention to the civil parish of são vicente should be paid and notice that most of them are high-risk occurrences. the number of vehicles sent to an event, regardless of their type is one vehicle. at least one vehicle should be always available for an occurrence. 58.82% of the false alarms are cancelled even after the emergency and rescue means of intervention for the site have been activated. the emergency and rescue services should activate their means only when it is confirmed that it is not a false alarm. 97.10% of the suspension requests are not cancelled before the means are sent to the location. the emergency and rescue services must be able to cancel the means before being sent to the location. 100% of records of the gopi and cbv entities are of moderate risk; 100% of records of the cml entity are of high risk; the smpc entity has 77.78% of records with zero risk. when the emergency and rescue services know which entity triggers the occurrence, they should be able to perceive the type of risk of the occurrence. to sum up, in each event, the main measure is about the attention needed to prevent the events. in other situations, the measures involve maintaining emergency and rescue services vehicles always available and aware. eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e4 r. silva, et al. 8 6. conclusion there was an essential question to answer: "how can we improve the requests for the intervention of the professional fire brigade regiment (fbr) when an emergency is detected in a smart city? to answer this challenge was developed a prototype with interactive dashboards and it was successfully achieved. these dashboards are the result of actual data provided by the municipality of lisbon. this prototype aimed to assist decision-making and understand data patterns to identify variables that may be probabilistically associated with intervention requests. as a result, 24 dashboards were obtained to meet the expectational goals. in short, this analysis highlights:  the understanding of the level of false alarms and suspension of media before and after they are sent to a location, and the need to improve because there are more than 50% of false alarms and requests for suspension which is a rather high percentage;  the highest number of occurrences is recorded on sundays, with 23.33%;  in terms of geographical distribution, it was understood that the civil parishes of benfica, lumiar, alvalade and são domingos de benfica are the most critical;  the registered occurrences tend to increase over the 8 years of study and the state after the conclusion of the occurrence is mostly "administrative closure";  regardless of the entity that triggers the occurrence, the state of the occurrence is mostly "administrative closure" and its degree of risk is moderate;  the number of vehicles sent was also analysed depending on the type of occurrence, and on average only one is sent. in future work, it is necessary to increase the variety of data present in the data warehouse which would consequently increase the analysis of business intelligence in the practical part of the article. in addition to this analysis of business intelligence, it would also be necessary to use the olap tool to make the analysis more enriching and intuitive so that at the time of an occurrence decisionmaking might be more direct and clearer. 7. references [1] the united nations. world population prospects 2022. https://doi.org/978-92-1-148373-4. [2] bibri s. big data science and analytics for smart sustainable urbanism. springer cham; 2019. [3] weiss m, bernardes r, consoni f. cidades inteligentes como nova prática para o gerenciamento dos serviços e infraestruturas urbanos: a experiência da cidade de porto alegre. urbe revista brasileira de gestão urbana 2015;7. https://doi.org/10.1590/2175-3369.007.003.ao01. [4] anthopoulos lg. understanding smart cities: a tool for smart government or an industrial trick? vol. 22. springer cham; 2017. [5] scheps s. business intelligence for dummies. john wiley & sons, inc.; 2008. [6] steele b, chandler j, reddy s. algorithms for data science. cham: springer international publishing; 2016. https://doi.org/10.1007/978-3319-45797-0. [7] cady f. the data science handbook. john wiley & sons, inc; 2017. [8] hurwitz j, nugent a, halper f, kaufman m. big data for dummies. 2013. [9] giffinger r, fertner c, kramar h, kalasek r, milanović n, meijers e. smart cities ranking of european mediumsized cities. 2007. [10] perera c, zaslavsky a, christen p, georgakopoulos d. context aware computing for the internet of things: a survey. ieee communications surveys & tutorials 2014;16:414–54. https://doi.org/10.1109/surv.2013.042313.0019 7. [11] anepc. plano nacional de emergência de proteção civil. n.d. [12] ahsaan s, mourya a. prognostic modelling for smart cities using smart agents and iot: a proposed solution for sustainable development. eai endorsed transactions on smart cities 2018:169916. https://doi.org/10.4108/eai.1352021.169916. [13] luís b. elvas, sandra p. gonçalves, joão c. ferreira, ana madureira. data fusion and visualization towards city disaster management: lisbon case study. eai endorsed transactions on smart cities 2022;6:e3. https://doi.org/10.4108/eetsc.v6i18.1374. [14] nesmachnow s, baña s, massobrio r. a distributed platform for big data analysis in smart cities: combining intelligent transportation systems and socioeconomic data for montevideo, uruguay. eai endorsed transactions on smart cities 2017;2:153478. https://doi.org/10.4108/eai.1912-2017.153478. [15] fernandes m. cidades inteligentes: um novo paradigma urbano estudo de caso da cidade do porto. católica porto business school, 2016. [16] durand a. cidades inteligentes análise de um estudo de caso, 82. instituto politécnico de setúbal, 2013. [17] hillenbrand k. boston equips firefighters with hazard data 2016. [18] patton e, appelbaum s. the case for case studies in management research. management research news 2003;26:60–71. https://doi.org/10.1108/01409170310783484. [19] webster m, sell j. laboratory experiments in the social sciences. 1st ed. academic press; 2007. [20] kimball r, ross m. the data warehouse toolkit: the definitive guide to dimensional modeling, third edition. 3rd ed. john wiley & sons, inc.; 2002. eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e4 editorial: welcome to the first issue of volume 7 of the eai endorsed transactions on smart cities eai endorsed transactions on smart cities research article 1 editorial: welcome to the first issue of volume 7 of the eai endorsed transactions on smart cities mohammad derawi1 1 professor, department of electronic systems, faculty of information technology and electrical engineering, ntnu gjøvik, norway received on 01 march 2023, accepted on 15 march 2023, published on 30 march 2023 copyright © 2023 mohammad derawi, licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v7i1.3389 it is indeed a matter of great honour for me to write the preface in the first issue of 2023 for eai endorsed transactions on smart cities. launched in 2016, the journal is now into its 7th volume which adds a sense of pride and confidence. promoting smart cities is advantageous in terms of national benefits as it creates competitiveness, enables the business sector, improves living standards, directs proper utilization of resources, and the like. smart cities aim to make optimal and sustainable use of all resources while maintaining an appropriate balance between social, environmental, and economic costs. the smart city concept represents an irrepressible platform for it-enabled service innovation. it offers a view of the city where service providers use information technologies to engage with citizens to create more effective urban organizations and systems that can improve the quality of life. the emerging internet of things (iot) model is foundational to the development of smart cities. the integrated cloud-oriented architecture of networks, software, sensors, human interfaces, and data analytics are essential for value creation. iot smart-connected products and the services they provide will become crucial for the future development of smart cities. the smart cities are aligned with un sustainable development goals. smart cities are expected to ensure harmlessness to the environment and be beneficial in whatever aspect possible. there is a broad scope of improvement in the development techniques that are currently in use. these limitations ought to be directed to potential future ideas. multiple cities around the world have been converted to smart cities. there are varied examples of smart cities, and a lot can be learned from their experience and achievements. i am extremely delighted to note that this journal emphasizes on smart cities and smart city projects, success stories and lessons learned from cities around the world. the contents in this issue have been organized in a reader friendly manner and the articles are worthy of further references and citations. this issue has attracted contributions from several regions of the world, and i would like to thank the authors for submitting their works. i extend my appreciation to the reviewers and the editorial team for their focused review comments and editing. i congratulate the team of eai endorsed transactions on smart cities and wish good luck for the future issues. eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e1 https://creativecommons.org/licenses/by-nc-sa/4.0/ this is a title this paper proposes an optimised design of an autonomous delivery robot while adopting the latest technologies from the different branching fields of robotics, artificial intelligence, and tele-communication. as a prospective representation of a user-centric robot design, the proposal is design with the major focus on maximizing users’ satisfaction throughout every human–robot interaction (hri) touchpoints. by the use of sensor fusion techniques along with the deployment of an image detection-based technique accompanying the point-cloud-detection-based path-planning methodology, the robot delivery would be optimised with effective path-planning and obstacle avoidance capability. with the extension of 5g connectivity, it is proposed that the real-time status update and video stream would enable greater efficiency in terms of remote monitoring and centralised robot administration. eai endorsed transactions on smart cities research article applied design and methodology of delivery robots based on human–robot interaction in smart cities wing ting law1*, kam wah fan 2, ki sing li 3, and tiande mo4 1,2,3,4 hong kong productivity council, hong kong abstract keywords: smart cities, smart mobility, robotics, robot, human-robot interaction; hri; human-centric computing; interaction design; user centric design; robot design; robot methodology. received on 30 august 2022, accepted on 02 april 2023, published on 26 june 2023 copyright © 2023 law et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/ eetsc.2649 1. introduction adapting to the shift of the modern world with increasing traffic of goods and a severe labour shortage, it is foreseeable that the trend of robot delivery would be much popular in order to serve as a versatile alternative for human labour in cities [1][2][3][4]. by having robots take part in labour-intensive tasks, the automation in various industries allows the precious labour resources to re allocated on the important value-added tasks. in recent years, on-demand delivery robots in buildings have been a welcomed substitution over human delivery in most business. this paper, therefore, aims to demonstrate a user-centric idea on human-robot interaction [5] (hereafter called hri) using various design and methodologies that adopt the latest technology among the fields of robotics, artificial intelligence, and tele communication in real-life applications. throughout the adoption of the different types of technology, it is realised that various hri considerations could be taken into account in order to enhance the overall user experience by revamping human-robot touchpoints. with careful considerations on the planned usage and optimised user experience, hardware design, and software design, the research team proposes the development of an advanced delivery robot that grants the advantages of “user-friendly” system flow, well-compartmentalised hardware architecture, advanced sensor-fusion that enables the deployment of an image-detection-based trajectories prediction technique accompanying the point-cloud *corresponding author. email: cadencelaw@hkpc.org 1 eai endorsed transactions on smart cities volume 7 | issue 2 1 eai endorsed transactions on smart cities volume 7 | issue 2 https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:cadencelaw@hkpc.org w. t. law et al. figure 1. a general user journey map for using a delivery robot detection-based path-planning methodology, as well as a 5g compatible low-latency server-robot connectivity for real-time monitoring and streaming. 2. general hri considerations in delivery robots according to the research from patric r. spence, negative feelings would be easily expressed if the robot is perceived as useless, such that the users would then be encouraged to isolate themselves from the use of the robot [6]. as a matter of fact, it is perfectly common for users to avoid solutions that are perceived to be less efficient or effective when the users believe they could outperform those solutions themselves. this observation gives the insight to the research team that it is crucial to enlighten users with the perception that the robot has to be cognitively effective and efficient in terms of the quality of the robot performance both tangibly and intangibly. this very insight originates the research team’s initial understanding to hri. the rawest concepts of general hri originated from the novel robot of isaac asimov in 1941, which stated that a robot shall not injure a man being, or through inaction, allow a human being to come to harm. it is one of the later interceptions in 1994 that if a robot-based economy develops without equitable adjustments, the backlash could be considerable [7]. therefore, it is the interpretation of the research team that, it is important to create a robot paradigm that balance between the economic or technological advantages provided by the robots and the overall drawbacks led by the deployment of the robots. it is in the consensus of later hri considerations that the goal of hri is to allow comfortable and acceptable interactions [5][8]. it is common that users might have uncertain feelings when considering the interaction with robots in contrary to the face-to-face communication among actual human beings. as such, this paper focuses on enabling user-centric hri by optimised designs and methodologies. in the proposed use-case, there would be numerous touchpoints between humans and robots during the user journey of the delivery robot. 3. planned usage and optimised user experience for general documents/ samples delivery tasks, it is commonly believed that the system performance in terms of stability and reliability are the major focuses from an engineering standpoint. however, in the perspectives of hri, the importance of having an intuitive and fool-proof system design that could optimise user experience outweighs every quantitative study on system performance. in short, the common users would always appreciate a simple robot that could be interacted and controlled easily and intuitively, over a flawless but complicated robot with rigid and exhaustive control measures. as suggested by valeria villani, the effective physical and cognitive interaction on robotic solution not only promotes efficiency, but also grant safety and intuitive ways to program and interact with robots [9]. it is therefore the sense of intuitiveness in user experience that drives the research team to develop a “user-friendly” user journey as the key foundation toward an optimised user journey, as shown in figure 1 which lays out all touchpoints between the users and the robot. from the perspective of general users, the journey of the delivery task always starts from the need for having something delivered, which is a very typical scenario in in building use-cases. then, as an automated delivery service, the item sender would call the robot for delivery service, which should be at its best availability to response to the sender’s call. once the sender drops off the item to the robot, the robot would then begin its delivery in a secure, careful and promising fashion. eventually, the robot should arrive at the destination, so that the item receiver could collect the delivered item in its perfect condition. simple as the below logic flow might sound, the research team believes that the best user experience that could ever be provided, must be a well-planned and comfortable experience, i.e. “user-friendly”. it is therefore obvious that there would be numerous touchpoints between the robot and the users, such as the user interface, the storage cabinet, 2 eai endorsed transactions on smart cities volume 7 | issue 2 applied design and methodology of delivery robots based on human–robot interaction in smart cities figure 2. system architecture of the proposed delivery robot the visual appearance and attraction, as well as the audible alerts for notifications. in the expected use-case of the delivery robot, it is assumed that the robot would have to be able to freely travel within the different floors of the building with reasonable passage space and crowdedness of obstacles. in terms of free travel, the access towards elevators and door would also have to be interactable with the robot, such that the robot would be able to communicate and interact with the elevators and doors in order to get access towards the designated areas inside the building. 4. hardware design with the aim to design a robust delivery robot as a potential alternative for human labour that facilitates and encourages smooth and comfortable user experience regarding user perception, interaction and engagement, the development of a versatile robot would be necessary, such that the robot would have to have an industrial design that emphasises on the robot’s physical appearance and functionality, let alone well-designed compartmentalisation. in general, there are proposed to be six different units in the delivery robot, including power unit, internet unit, sensor unit, i/o unit, storage unit and the driving unit as illustrated in figure 2. the power unit that lives up all parts, like the heart of a human, contains the rechargeable lithium-ion battery for providing dense and efficient energy, and the battery management system (bms) for protecting the battery from operating outside its safe operating status, monitoring and reporting the usage and current information. to ensure safety, the emergency stop (e-stop) is also included as a part of the power unit to sever all power immediately if needed. the sensor suite, as depicted as the eyes of the robot, helps gathering all environment data that enables the robot to have the correct moving directives when performing its task. the inertial measurement unit (imu) measures and reports the orientation of the robot by using a combination of accelerometers and gyroscopes. the ultrasonic sensors and 2d lidar are used to support collision avoidance by detecting nearby objects. similarly, the 3d lidar is used to detect objects in a greater range to achieve accurate localization and navigation. moreover, the camera captures image and videos for further visual analytics. the driving unit, as depicted as the feet of the robot, includes the wheels, motor drivers and bumper, which allow the robot to perform physical movements. to enhance its mobility, the robot is configured to be front wheel-drive with omni wheels so that omni-directional manoeuvring through crowds could be achieved. the i/o unit, as depicted as the mouthful and facial expression of the robot, serves as a communication pathway with other road-users, enabling multiple touchpoints. the on-board touchscreen with intuitive and relatable ui, two-way communication system and the led visual indicator visualise the current status of the robot with the road users with messages like, “i am idle” or “i am in a task”. the storage unit is a value-added unit, acting like the weight-bearing hands of a human, allowing users to deliver goods in a secure way by adopting the use of nfc readers and cards, and an electric lock. the internet unit, as the metaphorical representation of the human mind, provides access to the internet and further expands the touchpoints of the robot. last but not least, the centre processing unit, as depicted as the brain of the robot, links up all the above units to 3 eai endorsed transactions on smart cities volume 7 | issue 2 w. t. law et al. centralise the control over all the computational processes and coordinates all components to perform tasks. in terms of visual and audio design, to increase touchpoints and communicate with users throughout the delivery task, the robot would provide signals through visual and audible indicators, including lcd display, led lighting, and audible alerts and prompts through speaker. it is believed that the with the help of the visual outputs in the forms of graphics and texts that are shown on the lcd display as well as eye-catching led lighting for status indication, along with comprehensive voice prompts and attractive audible alerts, users and passers-by could have a more intuitive understanding to the robot and its status to avoid accidents, and increase the sense of user-friendliness. details of visual led and audible indictors are as described in table 1. table 1 robotics language visual and audible indicators 5. software design as an autonomous delivery robot with the primary duty of in-building delivery, successful navigation among in building structures is the most vital part for the performance of the delivery robot, in terms of navigation robutness and simultaneous localization and mapping (slam) [10][11]. therefore, it is crucial to organise all the related processes in a comprehensive manner. figure 3 above illustrates the entire navigation process from sensor information inputs to hardware actuations, such that the robot could fully utilise the technology advancement in sensor fusion, slam, and 5g. 5.1 sensor fusion – obstacle detection and path planning as mentioned, this delivery robot would be equipped with various kinds of sensors, including inertial measurement unit (imu) for acceleration measurements, motor drivers for odometry measurements, 2d and 3d lidar for real time simultaneous localization and mapping (slam), camera for object recognition, and ultrasonic sensors for collision detection. whenever a navigation task is initiated, the inputs from all the sensors would be firstly combined in the sensor fusion process to enhance the pose estimation accuracy of the robot. after that, the more complete and accurate data would be used to localise the actual location of the robot in the environment through the localization process, through the use of different localization algorithms [12][13]. at the same time, the data from the camera would also be adopted in the object recognition process to identify the category of the filmed objects from the visual feed, so that the later obstacle avoidance process could make reasonable reflections for optimal path planning. likewise, the data from the ultrasonic sensors would be used for the real-time collision detection process, such that imminent collisions figure 3. simultaneous localization and mapping (slam) figure 4. software operation main flow from perception to actuation 4 eai endorsed transactions on smart cities volume 7 | issue 2 applied design and methodology of delivery robots based on human–robot interaction in smart cities figure 5. sensor fusion – object recognition in distance would be detected and address corresponding response, as illustrated in figure 4 and figure 5 figure 3 and figure 4 are the expected visual representation of the navigation and localisation methodology. it should be the core value of this sensor-fused integration to be able to understand the environment in terms of the existence of surrounding obstacles. as depicted in figure 4, if the point cloud data from lidar is obtained as the sole input, accurate size and distance information would be complete for only items that exists in the most effective region of the lidar range. on the other hand, with the use of sensor fusion techniques, as depicted in figure 4, from the image feed from the front camera, the use of the detection models allows the robot to clearly identify every visibly detected obstacle in terms of size and distance. this enhancement in obstacle detection facilitates further decision-making on the path-planning logics. for instance, for static obstacles like chairs and desk, the delivery robot should plan for alternative paths as these types of objects would always stay in their existing position; while if non-static obstacles like pedestrians are detected, the delivery robot could try to eliminate the chance of collision by playing voice prompt to alert those pedestrians or just wait a while in a safe position until the obstacle is clear from the path. it is believed that such soft handling would make the delivery robot more like a human and enable dynamic and case-based decision. 5.2 motion planning flow of an in-building delivery task as the core component of an in-building delivery robot, the functionalities of navigation and localization have been given special focuses in terms of collision avoidance, path planning, and cross-floor travel handling. in the traditional approach for collision avoidance, the algorithm simply stops the robot until the obstacle is out of the detection range. alternatively, it is a more advanced method is to perform path-planning based on the result of model-based trajectory predictions on the movement of moving obstacles like walking pedestrian. while the traditional approaches are less desirable in densely populated environments such as streets and parks given the constant crowdedness, the latter approach performs much effectively on those situations with reasonable traffics. as depicted in figure 6 and figure 7, the trajectory prediction model uses the gathered information from the sensor fusion process, such as current distance, and current linear and angular velocity to serve the purpose of object tracking. with the aid of sensor fusion technology, the research team has adopted the image-detection-based trajectories prediction technique along with the point-cloud-detection based path-planning methodology enabled by the use 3d and 2d lidar, such that the object trajectories information on each of the individually tracked obstacle would be imported to the prediction algorithm to perform movement prediction with a fair confidence level, which would then be combined with the point-cloud-based navigation algorithms to plan for an optimal and obstacle free path. to be specific on the main motion planning flow of the delivery robot, each delivery task the robot handles involve three major iterative steps, namely the “handshakes”, the “walk”, and the “ride”, as illustrated in figure 8. every delivery task starts with the first simple “handshake”, where the users would entrust items to the robot’s cabinet figure 6. illustration on object tracking figure 5. illustration on trajectory prediction 5 eai endorsed transactions on smart cities volume 7 | issue 2 w.t. law et al. figure 6. proposed motion planning flow using the nfc card reader and initiate the delivery task by pressing one single button on the robot, which would then acknowledge the delivery task by audible alerts. this action-and-reaction-based “handshake” aims to work as the initial basic contact that would establish a sense of trustworthiness towards the users. when the delivery task is initiated, the “walk” is begun, where a smooth melody would be played to indicate the robot’s presence, and a vivid led lighting and display would be used to notify near pedestrians, just like taking a good walk together in music and glares. in details, the “walk” is actually a check-point-based path where the robot proceeds to the next check-point after reaching one. the process of path-planning, as mentioned beforehand, consists of two major parts, including the image-based obstacle detection and the point-cloud-based navigation, such that the obstacle detection model would provide trajectory prediction upon moving obstacle while the navigation stack would provide distancing information about static obstacles. to facilitate effective path-planning, the robot takes into concern information from both ends and output the optimal obstacle-free path for the robot to travel. then, the “ride” begins when the robot has to travel in floors with elevator, such that the robot would communicate with the elevator server wirelessly to acquire the current status of each elevator, so that the robot could call for elevators that are currently idle and allow the elevators to prioritise the needs of human passengers. once, the elevator has been called and with the elevator door opened, another detection model would be used to search for passengers and pedestrians, just to ensure the robot would be able to enter the elevator safely. right before entering the elevator, the robot would even notify pedestrians by clear audible alerts. once the destination floor is reached, the “walk” resumes and continues until the robot arrives at the final checkpoint for the delivery. the whole delivery task would then be completed by one last “handshake” where the users would retrieve the entrusted items from the locked cabinet using the nfc card reader and the robot would acknowledge its completion in delivery with another audible alert. from an engineering perspective, this might have been one simple flow design for a basic delivery task. as a matter of fact, the major emphasis in this flow design, as well as the industrial design of the robot, has been the intractability with pedestrians, such that numerous touch points were provided throughout the “handshakes”, the “walk”, and the “ride” in terms of audio, visual and interface interactions as mentioned in previous sections. 5.3 backend server connection and 5g extensibility throughout the design of the delivery robot, various security, safety and administrative considerations were also involved, such that a backend server was developed for the purpose of centralised robot control, especially for those requiring low tolerance in latency for high-speed data transmission [14]. it is the experience of the research team that enlightens the importance of remote monitoring and control of robots. the backend server acts a remote data logger that stores and reflects the current status of the robot, i.e. battery consumption, locational information, task status, task history, and any alert produced. besides data-logging, for security and safety reasons, the backend server also acts as a remote control-panel that allows authorised personnel to control the robot in terms of check-point assignment, task initiation and termination, and real-time video feed from the robot’s front camera. it is fully understood that the more important and powerful the backend server is, the higher the risk associated with the server-robot communication is intercepted, eavesdropped or even altered. therefore, the communication architecture between the server and robot 6 eai endorsed transactions on smart cities volume 7 | issue 2 applied design and methodology of delivery robots based on human–robot interaction in smart cities is reinforced in both software and hardware levels. in terms of software, the content for every outgoing communication would be encrypted with aes format, such that every status information and each frame from the video feed would be masked. however, with the increased processing time for the status update and video stream, it would be much difficult to establish a real-time connection. thus, the 5g technology has been adopted to enhance the speed as well as the security level for the of the data transmission. the use of 5g technology gives three major benefits to the communication architecture, including high data transmission speed, large maximum carrier bandwidth, and mass connectivity. in terms of the expected use-case, the high data transmission speed allows the robot to upload the loads of status messages and streams of video feed to the server with a very low latency, so that real-time monitoring of the robot could be achieved. to be specific, the 5g architecture uses ultra-reliable and low latency communications (urllc) to allow the travelling network to be optimised for processing incredibly large amounts of data with minimal delay so as to support end-to-end latencies as low as 5ms [15]. this is achieved by implementing a new approach to handle radio frame slots. instead of fixed radio slots of 1ms in 4g, 5g uses a multi numerology approach to allow flexible definition of radio slots, so that radio slots with shorter timespan would be allows, in returns of a lower latency. in addition, the large maximum carrier bandwidth benefited from the 5g technology makes the streaming of 4k resolution video possible in real-time. with the use of enhanced mobile broadband (embb), a greater data bandwidth complemented by moderate latency improvements on both 5g nr and 4g lte could be provided, such that the actual latency between image capturing and video presentation on the server for high resolution videos, like 4k or omnidirectional vr video, could be less than 0.3 seconds even after the implementation of the required data compression, and data encryption and decryption as mentioned. last but not least, the advantage of mass connectivity provided by the adoption of massive machinetype communication (mmtc) allows extremely high connection density of online devices, and thus enables the deployment of robot fleets and the potential migration of sensors or processes through cloud computing in the future, where the large number of robots and independent sensors would no longer be the limitation for real-time data transmission and processing, even in conditions of limited communication resource [16]. it has been one of the biggest challenges for traditional indoor-deploying robots to face internet instability due to the complex indoor environment. therefore, to encounter this challenge, numerous 5g-enabling antennas and transceivers have been deployed throughout the building, such that the robot would have guaranteed full internet connection while traveling among the designated deployment areas of the delivery tasks. as a matter of fact, the adoption of the 3.5ghz (sub-6) spectrum has enabled a cost-efficient deployment of the large number of transceivers such that the 3.5ghz spectrum allows a satisfying transmission rate from 193 to 430 mbit/s down, while having a reasonable sensing range of in the building complex, when compared to the two other expensive and range-limiting spectrums of 26-28ghz and 4.9ghz [17]. 6. conclusion it is obvious that the business model of modern companies is experiencing a huge change towards automation in recent years. it is inevitable for business to accompany this shift in paradigm by adjusting their business strategy and even business model to introduce a higher level of business automation. as a result, citizens would have a greater and more frequent exposure towards the different types of robots in workspace. it is therefore a crucial issue to design new robot morphologies, appearances, behaviour paradigms, interaction techniques to encourage a smooth and reassuring interaction between human and robots, let alone the design of systems, algorithms, interface technologies, and computational methods that supports such human-robot interaction. as a prospective representation, the research team proposes the development of a user-centric design of a delivery robot that could optimise user experience. by adopting the latest technologies from the different branching fields of robotics, artificial intelligence, and tele communication, the proposed delivery robot is intended to maximise users’ satisfaction throughout every hri touchpoints. as a delivery robot, the proposed hardware design follows the foundational design concept of a last-mile autonomous delivery robot, such that this robust robot would be able to provide a welcoming visual and audio appearance, as well as a reliable architectural framework with the six core units of power unit, internet unit, sensor unit, i/o unit, storage unit and the driving unit, to metaphorically serve as the heart, mind, eyes, mouth, hands, and feet of a human. as the major attraction, the proposed robot adopts the latest techniques in artificial intelligence to perform real-time slam with both image-detection-based trajectories prediction technique and the point-cloud-detection-based pathplanning methodology for effective navigation and obstacle avoidance. as the major duty of the delivery robot, a cross-floor travelling flow has also been proposed to enable and facilitate effective path-planning, communication between the robot and elevator/doors. it is another design attraction that the internet unit is proposed to be deployed with 5g compatibility in the 3.5ghz (sub 6) spectrum, so that the server-robot connection would be 7 eai endorsed transactions on smart cities volume 7 | issue 2 w. t. law et al. of higher speed and security, enabling stable status monitoring and video streaming. it is believed that the proposed robot design would be able to serve as a viable proposal for a new generation autonomous delivery robot, with the major software design focus on sensor fusion, advanced motion planning, 5g based high-speed backend server communication and streaming. it is the research team’s next action to build the actual prototype that employs the proposed design and methodologies. it is hoped that with such design specification, the user-friendly delivery flow and comfortable user experience provided would be able to encourage a closer and sophisticated human-robot interaction. 7. further development while serving with a vital proposal, the research team believes that, as a further enhancement or a design re deployment with customised use-cases, more reinforcement and alternative design could have been made with the latest technological advancement. the first enhancement proposal would be the adoption and integration of natural language processing (nlp) technology, like chatgpt [18], which could be applied to allow natural and human-esque interaction so that verbal human-to-human interaction could be extended to a human-to-robot level. the touchpoints between the delivery robot would have been evolved to a whole different level, by expanding communication capabilities with contextual understanding and abstract command processing, and dynamic command adaption, such that causal verbal command could be actually used to control the flow of the delivery task, e.g. specifying the destination with abstract verbal description, pausing the robot movement by saying a simple “stop”, and re-defining checkpoints or directions by tipping the robot “turn left” or “turn right”, or even “take this package to the café near the entrance”. another interesting enhancement would be the implementation of multi robot-to-robot communication, for instance the concept of collaborative multi-robotic tasks in the complex development [19], and hence the development of multi agent systems [20]. it is like the sociological paradigm of social collaboration, where multiple people, groups, or departments could interact with each other to achieve common goals, a fleet of robots could apply the same paradigm to accomplish a much intensive task. for example, in terms of items delivery, when the items to be delivered is way too many or too big for one single robot, it might be possible for the fleet of robots to collaboratively deliver parts of the big group of items or move in synchronous movement to deliver the single big item. if a reliable and self-sustaining robot-to-robot communication framework could be developed for general robot collaborations, it is believed that the level of automation could be vastly improved, which could thus further enhance the economic and technological advancement for the realm of hri. references [1] bilge mutlu and jodi forlizzi. 2008. robots in organizations: the role of workflow, social, and envi ronmental factors in human-robot interaction. in pro ceedings of the 3rd acm/ieee international conference on human robot interaction (hri '08), march 12 – 15, 2008, amsterdam, the netherlands. acm inc., new york, ny, 287–294. https://doi.org/10.1145/1349822.1349860 [2] madoka inoue, kensuke koda, kelvin cheng, toshimasa yamanaka, and soh masuko. 2022. improving pedestrian safety around autonomous delivery robots in real environment with augmented reality. in proceedings of the 28th acm symposium on virtual reality software and technology (vrst '22), november 29 – december 1, 2022, tsukuba, japan. acm inc., new york, ny, 1–2. https://doi.org/10.1145/3562939.3565644 [3] shuxiang yao. 2022. research on automatic delivery robot control based on multi-sensor fusion. in proceedings of the 2022 international workshop on control sciences and auto-mation (wcsa '22), april 8 – 10, 2022, xiamen, china. acm inc., new york, ny, 19– 24.https://doi.org/10.1145/3543303.3543307 [4] yan zhang, yunhuai liu, genjian li, yi ding, ning chen, hao zhang, tian he, and desheng zhang. 2019. route prediction for instant delivery. proc. acm interact. mob. wearable ubiqui-tous technol. 3, 3, article 124 (sep. 2019), 25 pages. doi: https://doi.org/10.1145/3351282 [5] thomas b. sheridan. 2016. human–robot interaction: status and challenges. human factors 58, 4 (april 2016), 525–532. doi: https://doi.org/10.1177/001872081664436 4 [6] patric r. spence, david westerman, chad edwards, and autumn edwards. 2014. welcoming our robot overlords: initial expectations about interaction with a robot. communication research reports 31, 3 (july 2014), 272–280. doi: https://doi.org/10.1080/08824096.2014.92 4337 [7] r. clarke. 1994. asimov's laws of robotics: impli cations for information technology. 2. computer 27, 1 (jan. 1994), 57–66. doi: hhtps://doi.org/10.1109/2.248881 [8] kerstin dautenhahn. 2007. socially intelligent robots: dimensions of human–robot interaction. philosophical transactions of the royal society b: biological sciences 362, 1480 (feb. 2007), 679–704. doi: https://doi.org/10.1098 /rstb.2006.2004 8 eai endorsed transactions on smart cities volume 7 | issue 2 applied design and methodology of delivery robots based on human–robot interaction in smart cities [9] valeria villani, fabio pini, francesco leali, and cristian secchi. 2018. survey on human-robot collabo ration in industrial settings: safety, intuitive interfaces and applications. mechat-ronics 55 (nov. 2018), 248–266. doi: https://doi.org/10.1016/j.mechatronics.2018.02.009 [10] eitan marder-eppstein, eric berger, tully foote, brian gerkey, and kurt konolige. 2010. the office marathon: robust navigation in an indoor office environment. in 2010 ieee international conference on robotics and automation, may 5 – 10, 2010, anchorage, ak. ieee, new york, ny, 300–307. https://doi.org/10. 1109/robot.2010.5509725 [11] josep aulinas, yvan petillot, joaquim salvi, and xavier lladó. 2008. the slam problem: a survey. artificial intelligence research and development 184 (2008), 363–371. doi: https://doi.org/10.3233/978-1-5860 3-925-7-363 [12] isro wasisto, novera istiqomah, i kadek nuary trisnawan, and agung nugroho jati. 2019. implemen tation of mobile sensor navigation system based on adaptive monte carlo localization. in 2019 international conference on computer, control, infor-matics and its applications (ic3ina), october 23 – 24, 2019, tangerang, indonesia, ieee, new york, ny, 187-192. https://doi. org/10.1109/ic3ina48034.2019.8949581 [13] kenji koide, jun miura, and emanuele menegatti. 2019. a portable three-dimensional lidar-based system for long-term and wide-area people behavior measurement. international journal of advanced robotic systems 16, 2 (april 2019), 1729881419841532. doi:https://doi.org/10. 1177/1729881419841532 [14] wing-ting law, ki-sing li, kam-wah fan, wang-hon ko, tiande mo, and chi-kin poon. 2022. two-way human-robot interaction in 5g tele-operation. in pro ceedings of the 2022 acm/ieee international conference on human-robot inter-action (hri '22), march 7 – 10, 2022, sapporo, hokkaido, japan. ieee press, new york, ny, 1198–1199. https://doi.org/10.1109/hri53351.2022. 9889509 [15] rashid ali, yousaf bin zikria, ali kashif bashir, sahil garg, and hyung seok kim. 2021. urllc for 5g and beyond: requirements, enabling incumbent tech nologies and network intelligence. ieee access 9 (april 2021), 67064–67095. doi: https://doi.org/10.1109/acc ess.2021.3073806 [16] viacheslav kovtun and krzysztof grochla. 2022. investigation of the competitive nature of embb and mmtc 5g services in conditions of limited communi cation resource. scientific reports 12, 1 (sep. 2022), 16050. doi: https://doi.org/10.1038/s41598-022-20135-5 [17] yi zeng, haofan yi, zijie xia, shaoshi wang, bo ai, dan fei, weidan li, and ke guan. 2020. measurement and simulation for vehicle-to-infrastructure communications at 3.5 ghz for 5g. wireless communications and mobile computing 2020, article 851600 (dec. 2020), 13 pages. doi: https://doi.org/10.1155/2020/8851600 [18] sai vemprala, rogerio bonatti, arthur bucker, and ashish kapoor. 2023. chatgpt for robotics: design principles and model abilities. microsoft. retrieved from https://www.microsoft.com/en-us/research/uploads/prod/ 2023/02/chatgpt robotics.pdf [19] kattepur, a. and khemkha, s. 2021. aspects of mechanism design for industry 4.0 multi-robot task auctioning. eai endorsed transactions on smart cities. 6, 17 (aug. 2021), e2. doi:https://doi.org/10.4108/eai.12-82021.170670. [20] bodi, m. , szopek, m. , zahadat, p. and schmickl, t. 2016. evolving mixed societies: a one-dimensional modelling approach. eai endorsed transactions on smart cities. 1, 3 (may 2016), e5. doi: https://doi.org/10.4108/eai.3-12-2015.2262514. 9 eai endorsed transactions on smart cities volume 7 | issue 2 http://www.microsoft.com/en-us/research/uploads/prod/ wing ting law1*, kam wah fan 2, ki sing li 3, and tiande mo4 abstract 1. introduction 2. general hri considerations in delivery robots 3. planned usage and optimised user experience 4. hardware design 5. software design 5.1 sensor fusion – obstacle detection and path planning 5.2 motion planning flow of an in-building delivery task 5.3 backend server connection and 5g extensibility 6. conclusion 7. further development references artificial intelligence is changing health and ehealth care 1 artificial intelligence is changing health and ehealth care akshaya avr1, vigneshwaran s2, and ram kumar c3,* 1associate professor, department of mba, dr. ngp institute of technology, coimbatore, india. 2assistant professor (sr.gr), department of bme, sri ramakrishna engineering college, coimbatore, india. 3associate professor, department of bme, dr. ngp institute of technology, coimbatore, india. abstract artificial intelligence (ai) will be used more and more in the healthcare industry as a result of the complexity and growth of data in the sector. payers, care providers, and life sciences organisations currently use a variety of ai technologies. the main application categories include recommendations for diagnosis and treatment, patient engagement and adherence, and administrative tasks. although there are many situations in which ai can execute healthcare duties just as well as or better than humans, implementation issues will keep the jobs of healthcare professionals from becoming extensively automated for a substantial amount of time. the use of ai in healthcare and ethical concerns are also highlighted. keywords: artificial intelligence, clinical decision support, electronic health record systems. received on 31 july 2022, accepted on 19 september 2022, published on 21 september 2022 copyright © 2022 akshaya avr et al., licensed to eai. this is an open access article distributed under the terms of the cc by-ncsa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i3.2274 1. introduction role of ai in the 1950s, artificial intelligence (ai) was primitively visualized and gestated to authorize a computer or machine to make it think and learn like humans. ai is extensively utilized by organizations like facebook (for example recognizing who is in a photo), and google (for example availing search ideas or giving the quickest route to drive). in spite of the fact that, inside the medical care area, ai has just continued little strides toward a tremendous and multifaceted open door [1]. 1.1 usage of ai in healthcare there are numerous capacities where ai is coming into view as a game-changer in healthcare sectors. below are some samples in use today which include: *corresponding author. email: profcramkumar@gmail.com in radiology to automate picture examination and diagnosis ai arrangements are being created. this will assist with finishing the field of interest on a sweep to a radiologist, to portable proficiency and decrement human blunder [1]. opportunities are likewise available for completely automated answers for all the while read and decipher an output without human oversight that could assist with entitling prompt translation in dismissed geologies. most recent showings of upgraded growth recognition on mris and cts are extending the development towards new opportunities for the counteraction of cancer. for the occasion, a partnership in the usa has previously presented on fda leeway to examine and decipher cardiac mri pictures for an ai-fuelled stage [2]. in drug discovery to detect new potential therapies from enormous databases of information or data on currently existing medicines that could be recreated to spot severe threats ai solutions are being developed. an example could be taken for the ebola eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e3 https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:profcramkumar@gmail.com akshaya avr, vigneshwaran s and ram kumar c 2 virus. it improves the efficiency, performance, and success rate of drug development, in response to deadly disease threats by energizing the method to introduce new drugs throughout the market [3]. risk identification in patient ai arrangements can supply constant help to clinicians to help with distinguishing the gamble of patients overwhelmingly of patient information from history. a new center integrates re-entrance gambles, and highlighting patients who have a raised chance of getting back to the emergency clinic in no less than 30 days of release from the medical clinic [4]. many organizations and healthcare areas are creating arrangements relying upon the information in the patient's electronic health record (ehr), by hoisting pushback from payers on wrapping hospitalization costs connected with re-confirmation as of now. the possibility to foresee the gamble of sickness connected with cardiovascular relies simply upon a still picture of a patient's retina was shown in ongoing work. in primitive care/triage numerous associations are performing direct-to-patient answers for emergency and they give exhortation through voice or visit based communications. it gives quick, adaptable admittance to major inquiries and clinical issues [5]. it could likewise aid in keeping away from superfluous excursions to the gp, diminishing the rising requirement for crude healthcare suppliers for a succession of conditions, and giving basic direction which wouldn't be available to the number of inhabitants in individuals living in remote dismissed regions. however, the idea is exact and clear, these arrangements actually request significant free approval to show patient wellbeing and viability [6]. 1.2 challenges of ai in healthcare to make ai successful, it requires a tremendous measure of information of the patients to train and streamline the performance of calculations. in healthcare, getting to these data sets has wide issues: patient privacy and the ethics of data ownership is getting to clinical records of the patients exceptionally safeguarded. lately the information dividing among medical clinics and ai organizations has made numerous issues and raised a few moral inquiries: • who owns and controls the patient data and what is need to develop ai solution? • whether hospitals be allowed to continue to provide vast quantities of their patient data even it is accessed by the 3rd party ai companies? • how can patient’s privacy can be protected according to the patient’s rights? • what are the consequences should there be a security breach? • what will be the impact of new regulations, like the general data protection regulation (gdpr) in europe. this explains the sometimes the patient data may be deleted, this creates trustless among patients and the required organisation should pay multimillion dollar penalty. quality and usability of data is very important consideration, in industries all the data are reliable and accurately measured. but, in healthcare the data may be subjective and inaccurate with issues including: • clinician’s notes in electronic medical records are difficult to understand and may not written or typed in order. • data inaccuracy: the data of a patient may be wrongly entered. for example, the patient may be a smoker but, the data entered inaccurately that patient is nonsmoker. • data sources are isolated across many services providers, so the patient’s full profile may not be accessible, so that it creates consequence on monitoring the health of the patient. developing regulations for cloud based technology and constantly evolving obvious challenges. • what are the ways to protect the patients? • how will you provide adequate oversight of a solution that is learning and evolving on medical devices? • ai solution involve direct patients’ interaction with oversight of the clinician, it makes the question, whether the technology is the “practitioner of medicine”, rather than device. • in this case, will it need to operate on license and would a national board will agree to grant this licence? • this will lead to the question that who is liable should anything go wrong? • if diagnosis or treatment is controlled by this technology, does ai companies give assurance for patient’s health? • will insurance companies ever underwrite an ai tool? user adoption is another barrier to utilisation. • the human touch of interacting with a doctor can be lost with these types of tools. it raises the question that, whether the patients trust the software than humans? this makes a trust issues on doctors. • meanwhile are clinicians willing to embrace these new solutions? • in an industry that still widely uses the fax machine, it may be unrealistic to expect rapid adoption rates beyond proof of concept studies. 2. ai in healthcare healthcare is consistently taking on the computerized reasoning (ai) advances that are unavoidable in current business and daily life. computerized reasoning in eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e3 artificial intelligence is changing health and ehealth care 3 healthcare can possibly help suppliers in numerous areas of patient consideration and functional methodology, empowering them to expand on current arrangements and take care of issues all the more rapidly. most of ai and healthcare advances are exceptionally pertinent to the healthcare business, yet clinics and other healthcare associations might utilize altogether different methodologies. despite the fact that a few articles on the utilization of man-made reasoning in healthcare claim that it can perform similarly as well as or better than humans at certain methodology, such as diagnosing illness, it will be a lot of time before ai in healthcare replaces humans for a large number of clinical undertakings [7]. yet, it's as yet a secret to many. what is man-made brainpower in medication, and what are its benefits? what will future utilizations of ai in healthcare seem to be? how could it be presently utilized? will it in the long run supplant individuals in basic activities and healthcare administrations? we should inspect a couple of the different utilizations of man-made consciousness and the benefits that the healthcare area stands to gain from its application. 2.1 types of ai of relevance to healthcare a gathering of innovations all in all alluded to as man-made consciousness. albeit most of these innovations are quickly pertinent to the healthcare business, there is a huge reach in the specific methodology and occupations they help. the definition and portrayal of some particular ai advancements that are critical to healthcare follow [8]. 2.1.1 machine learning one of the most common sorts of man-made reasoning in the clinical field is ai. there are various varieties of this wide procedure, which is at the groundwork of different ways to deal with ai and healthcare innovation. accuracy medication is the most broadly utilized utilization of customary ai in the field of man-made brainpower in healthcare. it is a major step in the right direction for the vast majority healthcare associations to have the option to gauge which treatment approaches would be best with patients in light of their qualities and the treatment system. ai and accuracy medication applications, which make up most of ai in healthcare, require information for training with known results. we call this directed learning [9]. profound learning-based man-made brainpower in healthcare likewise utilizes discourse acknowledgment by means of regular language handling (nlp). profound learning models frequently incorporate not many highlights that have importance to human eyewitnesses, making it challenging to assess the model's result. 2.1.2 natural language processing since the 1950s, ai specialists have pursued grasping human language. nlp includes applications for discourse acknowledgment, text examination, interpretation, and other language-related goals. semantic nlp and factual nlp are the two main strategies. the exactness of acknowledgment has as of late superior thanks to a limited extent to measurable nlp, which depends on ai (especially profound learning brain organizations). it needs a sizable "corpus" or collection of language to be gained from. the age, cognizance, and arrangement of clinical documentation and distributed research contain most of nlp's purposes in the healthcare area. nlp frameworks are equipped for leading conversational ai, investigating unstructured clinical notes on patients, making reports (for instance, on radiological tests), and deciphering patient exchanges [10]. 2.1.3 rule-based expert systems during the 1980s and succeeding many years, master frameworks based on data sets of "in the event that" rules overwhelmed the field of computerized reasoning. throughout recent many years, they have been widely utilized in the healthcare business for "clinical choice help" purposes, and they are still regularly utilized today. today, a ton of providers of electronic health records (ehrs) furnish a bunch of rules with their framework. a bunch of rules in a certain information domain should be worked by human specialists and information engineers for master frameworks. they are easy to comprehend and work well to a certain degree. be that as it may, they regularly fail when there are a ton of rules (normally north of a couple thousand) and when the guidelines begin to struggle with each other. furthermore, it tends to be testing and tedious to refresh the principles assuming that the information domain does. more methodologies in light of information and ai calculations are progressively supplanting them in the healthcare business [11]. 2.1.4 physical robots actual robots are now notable, with in excess of 200,000 modern robot establishments happening every year around the world. they perform present undertakings including lifting, moving, welding, or gathering things in areas like manufacturing plants and distribution centers, as well as shipping supplies in clinical offices. all the more as of late, robots have become simpler to instruct by having them do an ideal undertaking, and they have expanded their ability to work helpfully with individuals. also, as more ai capacities are incorporated into their "brains," they are turning out to be more keen (actually their working frameworks). apparently sensible that over the long haul, actual robots would remember the very progressions for knowledge that we have seen in different parts of computerized reasoning [12]. careful robots give specialists "superpowers," upgrading their vision, ability to make exact, insignificantly intrusive cuts, close injuries, and other surgeries. they were first supported in the usa in 2000. notwithstanding, huge decisions are as yet made by human specialists. gynaecologic medical procedure, prostate medical procedure, and head and neck a medical eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e3 akshaya avr, vigneshwaran s and ram kumar c 4 procedure are among the normal surgeries performed with mechanical medical procedure [13]. 2.1.5 robotic process automation this innovation executes coordinated computerized organization errands — those including data frameworks — as though they were being completed by a human client who was adhering to a bunch of directions or rules. they are more affordable, less complex to program, and more straightforward than different sorts of ai. mechanical cycle robotization (rpa) principally utilizes server-based programming as opposed to genuine robots. to act as a semi-wise client of the data frameworks, it relies upon a mix of work process, business rules, and 'show layer' combination. they are utilized in the healthcare business for routine obligations like charging, earlier approval, and patient record refreshes. they can be utilized to remove information from, say, faxed photographs and feed it into value-based frameworks when paired with different advances like picture acknowledgment [14]. in spite of the fact that we have just talked about these advancements separately, they are continuously being joined and coordinated. for instance, robots are gaining ai-based "brains," and rpa and picture acknowledgment are being consolidated. maybe these advances will turn out to be so entwined later on that composite arrangements will turn out to be more conceivable or down to earth. 3. diagnosis and treatment applications for the beyond 50 years, illness diagnosis and treatment have been at the focal point of ai in healthcare. indeed, even while early rule-based frameworks been able to really analyze and treat infection, clinical practice didn't completely embrace them. they weren't recognizably more precise at diagnosing than humans, and the communication with doctor work processes and health record frameworks wasn't perfect. in any case, whether rules-based or algorithmic, it can habitually be trying to coordinate clinical cycles and ehr frameworks with the utilization of man-made reasoning in healthcare for analytic and treatment plans. when contrasted with idea precision, combination concerns have been a greater barrier to the mainstream sending of ai in healthcare. figure 1 shows the cutting edge time of healthcare industry in ai [15]. clinical programming providers offer an enormous number of free ai and healthcare capacities for diagnosis and treatment that are centered around a solitary discipline of medication. while still in the beginning phases, a few ehr programming suppliers are beginning to incorporate fundamental ai-fuelled healthcare examination capacities into their item contributions. healthcare suppliers who utilize independent ehr frameworks will either have to set out on huge mix projects themselves or utilize outsider sellers who have ai capacities and can associate with their ehr to profit from the utilization of ai in healthcare completely [16]. 3.1 administrative applications computerized reasoning has a few regulatory purposes in the healthcare business. in contrast with patient consideration, the utilization of computerized reasoning in emergency clinics doesn't change the game very so a lot. be that as it may, involving man-made reasoning in medical clinic organization can bring about huge expense reserve funds. claims handling, clinical documentation, income cycle the board, and clinical records organization are only a couple of the uses of ai in healthcare. ai is one more utilization of computerized reasoning in healthcare that is pertinent to the organization of claims and instalments. matching information from a few databases can be utilized. a great many claims are presented consistently, and guarantors and suppliers should affirm that they are exact. time, cash, and assets are undeniably saved when code issues and bogus claims are found and revised [17]. 4. ai and robotics are revolutionizing healthcare ai is ending up being more fit at completely finishing human-like positions even more quickly, capably, and sensibly. both mechanical innovation and ai have huge likely in the field of healthcare. like in our daily lives, our healthcare eco-structure is ending up being progressively more subject to ai and mechanical innovation. figure 1 shows the eight models that show the current status of this shift have been highlighted. figure 1. modern era of healthcare industry in ai one of ai's most prominent potential benefits is to keep individuals healthy so they don't require specialists as regularly, if by any means. individuals are now profiting eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e3 artificial intelligence is changing health and ehealth care 5 from purchaser health utilizations of computerized reasoning (ai) and the web of clinical things (iomt). applications and applications for innovation support proactive maintenance of a healthy way of life and urge people to take on healthier ways of behaving. it gives clients command over their health and prosperity. also, ai further develops healthcare laborers' ability to understand the ordinary examples and prerequisites of the patients they care for, empowering them to offer unrivalled criticism, course, and backing for maintaining health [18]. ai is as of now being utilized to all the more definitively and early analyze illnesses like cancer. the american cancer society claims that an enormous level of mammograms gives deluding results, letting one know in two healthy ladies they have cancer. mammogram audits and interpretations utilizing ai are currently multiple times quicker and 99 percent exact, which takes out the need for inconsequential biopsies. ai is likewise being utilized related to the development of shopper wearables and other clinical gadgets to screen beginning phase coronary illness, permitting specialists and different parental figures to all the more actually screen and distinguish possibly lethal episodes at prior, more treatable stages. healthcare organizations are involving ibm's watson for health to send mental innovation to open gigantic volumes of health information and empower diagnostics. watson can survey and store dramatically more clinical information than any human, including each clinical distribution, side effect, and contextual investigation of a treatment's viability around the world. to address squeezing healthcare issues, google's deepmind health teams up with specialists, researchers, and patients. the method joins frameworks neuroscience and ai to make brain networks that intently look like the human brain and contain strong broadly useful learning calculations [19]. prescient examination can uphold clinical independent direction and activities and assist with focusing on authoritative exercises. further developing treatment includes the arrangement of huge health information with reasonable and opportune decisions. one more region where ai is beginning to flourish in healthcare is the utilization of example acknowledgment to recognize individuals in danger of getting a condition or seeing it deteriorate inferable from way of life, ecological, genomic, or different factors. ai can help clinicians in adopting a more thorough strategy to sickness the executives, better direction care plans, and assist patients with bettering oversee and conform to their drawn out therapy programs, as well as assisting suppliers with recognizing persistently sick people who might be in danger of an unfriendly episode. for over 30 years, clinical robots have been being used. they range from fundamental research facility robots to very complex careful robots that can figure out close by a human specialist or convey strategies all alone. they are utilized in medical clinics and labs for redundant positions, restoration, exercise based recuperation, and backing for individuals with long haul issues notwithstanding a medical procedure. as we close to the furthest limit of our lives, sicknesses like dementia, cardiovascular breakdown, and osteoporosis are making us die in an alternate and more slow way than earlier ages. moreover, it is a phase of life where forlornness is a typical issue [20]. robots can possibly totally change end-of-life care by empowering patients to maintain their autonomy for longer and diminishing the requirement for inpatient care and nursing offices. ai is making it workable for robots to go much further and communicate socially with humans to continue to mature personalities sharp through "discussions" and other social associations. it requires a long investment and cash to get from the examination lab to the patient. a medication should go from an exploration lab to a patient for a normal of 12 years, as per the california biomedical exploration affiliation. of the 5,000 drugs that start preclinical testing, just five arrive at human testing, and only one of these five is at any point approved for use in humans. moreover, from the exploration lab to the patient, fostering another treatment will run an organization a normal of us $359 million. one of the later utilizations of ai in healthcare is drug disclosure. it could be feasible to decisively diminish an opportunity to showcase for new drugs as well as their costs by applying the latest advancements in ai to automate the medication disclosure and medication reusing processes. ai makes it workable for trainees to encounter sensible reenactments in a manner that is preposterous with straightforward pc driven calculations. a trainee's solution to an inquiry, decision, or suggestion can be trying in a way that an individual can't due to the improvement of regular discourse and an ai pc's capacity to draw momentarily from a huge data set of situations. also, the training system can consider the trainee's earlier reactions, permitting it to ceaselessly adjust the assignments to accommodate their learning prerequisites. moreover, training should be possible anyplace because of the force of ai coordinated in cell phones, making it conceivable to do brief get up to speed meetings following testing cases in a facility or while voyaging [21]. 5. ethical implications finally, there are such a large number of moral ramifications around the utilization of ai in healthcare. before, healthcare responsibility was made totally by humans, and the usage of savvy machines for helping with those claims’ issues of liability, clarity, approval, and confinement. perhaps the mass basic issue to recognize in the present advancements is straightforwardness. the vast majority of the ai calculations explicitly profound learning calculations used for picture investigation are essentially unrealistic to decipher. a patient will liable to be need to know why he/she has prompted a diagnosis of cancer with a piece of picture data. albeit, the doctors who are for the most part acquainted with their activity, might not be able to explain profound learning calculations [22]. eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e3 akshaya avr, vigneshwaran s and ram kumar c 6 ai frameworks will make blunders without a doubt in patient diagnosis and treatment and setting up responsibility for them may be hard. numerous episodes were experienced in which patients as opposed to getting from a sympathetic clinician get clinical data from ai frameworks. ai frameworks in healthcare are likewise connected with algorithmic predisposition, they might be not foreseeing illness in view of an easy going component, and anticipating it relying upon orientation or race gives more prominent occupation. many changes including moral, clinical, word related, and mechanical changes are anticipated to be experienced with ai in healthcare. it is vital for set up systems to screen major questions, act capably and set up administration components to put down a boundary to negative ramifications in healthcare organizations, as well as legislative and administrative bodies. that would be viewed as the most vivacious and consecutive innovation to influence human social orders, subsequently it will require smoothed out consideration and insightful standards and strategy for additional years [23]. 6. future of ai in healthcare finally, there are such a large number of moral ramifications around the utilization of ai in healthcare. before, healthcare responsibility was made totally by humans, and the usage of savvy machines for helping with those claims’ issues of liability, clarity, approval, and confinement. perhaps the mass basic issue to recognize in the present advancements is straightforwardness. the vast majority of the ai calculations explicitly profound learning calculations used for picture investigation are essentially unrealistic to decipher. a patient will liable to be need to know why he/she has prompted a diagnosis of cancer with a piece of picture data. albeit, the doctors who are for the most part acquainted with their activity, might not be able to explain profound learning calculations [24]. ai frameworks will make blunders without a doubt in patient diagnosis and treatment and setting up responsibility for them may be hard. numerous episodes were experienced in which patients as opposed to getting from a sympathetic clinician get clinical data from ai frameworks. ai frameworks in healthcare are likewise connected with algorithmic predisposition, they might be not foreseeing illness in view of an easygoing component, and anticipating it relying upon orientation or race gives more prominent occupation. many changes including moral, clinical, word related, and mechanical changes are anticipated to be experienced with ai in healthcare. it is vital for set up systems to screen major questions, act capably and set up administration components to put down a boundary to negative ramifications in healthcare organizations, as well as legislative and administrative bodies. that would be viewed as the most vivacious and consecutive innovation to influence human social orders, subsequently it will require smoothed out consideration and insightful standards and strategy for additional years [25]. 7. conclusion there are a lot of issues to defeat which are driven by proven and factual variables which incorporate a maturing populace of individuals and raised paces of ongoing illness and the necessity for cutting edge creative arrangements in healthcare is clear and exact. ai fueled arrangements took little drives towards naming central points of contention, yet it needs to arrive at a huge gross activity on the worldwide healthcare area, regardless of the significant media perception adjoining it. it could assume a main part in how healthcare frameworks representing things to come work, enlarging clinical assets and guaranteeing ideal patient results in the event that few key difficulties can be tended to before very long. references [1] hechler e, oberhofer m, schaeck t. deploying ai in the enterprise. it approaches for design, devops, governance, change management, blockchain, and quantum computing, apress, berkeley, ca. 2020. [2] lee si, celik s, logsdon ba, lundberg sm, martins tj, oehler vg, estey eh, miller cp, chien s, dai j, saxena a. a machine learning approach to integrate big data for precision medicine in acute myeloid leukemia. nature communications. 2018 jan 3;9(1):1-3. [3] sordo m. introduction to neural networks in healthcare. open clinical: knowledge management for medical care. 2002 oct. [4] fakoor r, ladhak f, nazi a, huber m. using deep learning to enhance cancer diagnosis and classification. inproceedings of the international conference on machine learning 2013 jun (vol. 28, pp. 3937-3949). acm, new york, usa. [5] vial a, stirling d, field m, ros m, ritz c, carolan m, holloway l, miller aa. the role of deep learning and radiomic feature extraction in cancer-specific predictive modelling: a review. transl cancer res. 2018 jun 1;7(3):803-16. [6] davenport th, glaser j. just-in-time delivery comes to knowledge management. harvard business review. 2002 jul 1;80(7):107-1. [7] hussain a, malik a, halim mu, ali am. the use of robotics in surgery: a review. international journal of clinical practice. 2014 nov;68(11):1376-82. [8] davenport t, kalakota r. the potential for artificial intelligence in healthcare. future healthcare journal. 2019 jun;6(2):94. [9] grosan c, abraham a. rule-based expert systems. in intelligent systems 2011 (pp. 149-185). springer, berlin, heidelberg. [10] ross c, swetlitz i. ibm pitched its watson supercomputer as a revolution in cancer care. it’s nowhere close. stat. 2017 sep 5. [11] davenport th. the ai advantage: how to put the artificial intelligence revolution to work. mit press; 2018 oct 16. eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e3 artificial intelligence is changing health and ehealth care 7 [12] coulter a, collins a. making shared decision-making a reality. london: king's fund. 2011. [13] thrall jh, li x, li q, cruz c, do s, dreyer k, brink j. artificial intelligence and machine learning in radiology: opportunities, challenges, pitfalls, and criteria for success. journal of the american college of radiology. 2018 mar 1;15(3):504-8. [14] schmidt-erfurth u, bogunovic h, sadeghipour a, schlegl t, langs g, gerendas bs, osborne a, waldstein sm. machine learning to analyze the prognostic value of current imaging biomarkers in neovascular age-related macular degeneration. ophthalmology retina. 2018 jan 1;2(1):2430. [15] aronson sj, rehm hl. building the foundation for genomics in precision medicine. nature. 2015 oct;526(7573):336-42. [16] rysavy m. evidence-based medicine: a science of uncertainty and an art of probability. ama journal of ethics. 2013 jan 1;15(1):4-8. [17] rajkomar a, oren e, chen k, dai am, hajaj n, hardt m, liu pj, liu x, marcus j, sun m, sundberg p. scalable and accurate deep learning with electronic health records. npj digital medicine. 2018 may 8;1(1):1-0. [18] shimabukuro dw, barton cw, feldman md, mataraso sj, das r. effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial. bmj open respiratory research. 2017 nov 1;4(1):e000234. [19] nait aicha a, englebienne g, van schooten ks, pijnappels m, kröse b. deep learning to predict falls in older adults based on daily-life trunk accelerometry. sensors. 2018 may 22;18(5):1654. [20] low ll, lee kh, hock ong me, wang s, tan sy, thumboo j, liu n. predicting 30-day readmissions: performance of the lace index compared with a regression model among general medicine patients in singapore. biomed research international. 2015 oct;2015. [21] davenport th, hongsermeier t, mc cord ka. using ai to improve electronic health records. harvard business review. 2018 dec 13;12:1-6. [22] volpp kg, mohta ns. patient engagement survey: improved engagement leads to better outcomes, but better tools are needed. nejm catalyst. 2016 may 12;2(3). [23] berg s. nudge theory explored to boost medication adherence. chicago: american medical association. 2018. [24] commins j. nurses say distractions cut bedside time by 25%. health leaders. 2010 mar. [25] utermohlen k. four robotic process automation (rpa) applications in the healthcare industry. medium. 2018. [26] huang cy, yang mc, huang cy, chen yj, wu ml, chen kw. a chatbot-supported smart wireless interactive healthcare system for weight control and health promotion. in2018 ieee international conference on industrial engineering and engineering management (ieem) 2018 dec 16 (pp. 1791-1795). ieee. [27] deloitte llp (firm). from brawn to brains: the impact of technology on jobs in the uk, 2015. [28] manyika j, chui m, miremadi m, bughin j, george k, willmott p, dewhurst m. a future that works: ai, automation, employment, and productivity. mckinsey global institute research, tech. rep. 2017 jun;60:1-35. [29] davenport th, kirby j. only humans need apply: winners and losers in the age of smart machines. new york: harper business; 2016 may 24. [30] davenport th, dreyer k. ai will change radiology, but it won’t replace radiologists. harvard business review. 2018 mar 27;27. [31] char ds, shah nh, magnus d. implementing machine learning in health care—addressing ethical challenges. the new england journal of medicine. 2018 mar 15;378(11):981. eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e3 myketiak_mobihealth_final.pages new/s design: informing future design processes by understanding media reporting of medical errors with medical devices [invited paper] chrystie myketiak university of brighton
 college of arts and humanities
 falmer campus brighton, uk bn1 9ph c.myketiak@brighton.ac.uk shauna concannon queen mary university of london
 school of electronic engineering and computer science
 london, uk e1 4ns s.concannon@qmul.ac.uk paul curzon queen mary university of london
 school of electronic engineering and computer science
 london, uk e1 4ns p.curzon@qmul.ac.uk abstract in this paper we present a case study of media reporting about medical technology issues. we discuss two incidents involving human error with medical devices that resulted in infant deaths, and their relevance for the medical device design and mobile health communities. our analysis into the language and discourses of news reporting shows that the news narratives of these incidents emphasise human aspects of the error and neglect device issues. better design is not conceptualised as an option in these narratives, even when systemic issues are discussed in relation to errors with devices. however, there is a possibility for better design solutions if practitioners are aware of the discursive construction of errors, including how critical incidents are framed and developed in news discourse. categories and subject descriptors j.3 life and medical sciences (e.g., health) j.5 arts and humanities (e.g., linguistics) general terms design, human factors. keywords critical discourse analysis; human error; medical devices; news reporting; patient safety; sociolinguistics. 1. introduction the media helps drive technology cultures, yet its influence is underexplored within the medical device and mobile health communities. this study presents an analysis of news articles about incidents involving medical error and patient deaths. we examine the news reporting of two infant deaths in hospitals in different countries from the same temporal period using critical discourse analysis (cda). both deaths were linked to employee errors in administering medication using medical devices. print and online news articles were gathered on these cases. we found differences in how the errors were discursively constructed. the first case involved an ‘out by 10’ mathematical error, which was often explained in the news articles as ‘user error’ with an interruption being the only systemic issue mentioned. the second case involved incorrect medication and the focus in that coverage was on workspace, personnel and medication placement changes that would be implemented in order to reduce similar errors in the future. 
 an important issue for the medical device design and mobile health communities is how, despite the differences in how these narratives frame the error in the news, there was no focus on the devices, their design, or use. both cases lacked discussion of how poor design/usability could have contributed to the errors or of how improved design could prevent similar errors. although there is a great deal of research on the issues and implementation of wireless sensors for health monitoring (e.g., [14, 27]), there has been little discussion of operator errors post-implementation. our analysis suggests that when incidents with devices occur, the discussion in the media and the framing of investigations lacks emphasis on socio-technical systems and human-computer interaction (hci) issues, including the use, design, and potential for improvement of device design. we assert that this propagates a discourse of technological determinism whereby individuals, organisations, designers, manufacturers, and the media may contribute to a narrative that users (individually or systematically) are responsible for errors and that thinks only of individual or ergonomic refinements rather than how use is impacted by good (and poor) design. this means there is little encouragement from these sources for error reduction improvements in designs and opportunities for designs to be iteratively improved are lost. mobihealth 2015, october 14-16, london, great britain copyright © 2015 icst doi 10.4108/eai.14-10-2015.2261762 2. literature review the field of health communication is broad, with a long history of examining the dynamics of clinical conversations (e.g., [25]). more recently, there have been studies examining mediated interaction, such as emergency hotline calls (e.g., [10, 20]) and health-oriented online communities (e.g., [9, 19]). a complement to this research has been a focus on media representations of specific health topics (e.g., [4, 17, 18]). however, there has been little research on the intersection of media, health, and design. we tie this body of work to that which focuses on design solutions in healthcare technology. in particular, patient safety is a serious technology concern (e.g., [11, 13, 23]). issues surrounding technology and patient safety cover a wide terrain, including bridging strengths from many disciplines (e.g., computer science, engineering, mathematics, sociology, psychology, linguistics, etc.) to improve devices, clinical practices, and incident reporting. the language of reporting cultures provides understanding of individual incidents. it also matters to healthcare technologists because it examines: • the sociocultural environment of medical errors (e.g., real-life use as well as in the larger society where incidents are reported and stories are discussed) • the linguistic and discursive construction of errors (e.g., whose story is told, where/how are users positioned) • how the future of medical device design including mobile healthcare can be impacted by ‘human error’ incidents 3. methodology 3.1. methods this study uses cda, a qualitative methodology often used in sociolinguistics. we adopt corpus techniques as described by [1] to enable this. in addition to cda, we provide supplementary quantitative data, as others using corpora approaches to discourse analysis in the area of health and illness have done [17, 18]. we concentrate on how these incidents are linguistically framed (cf. [21]); examining specific aspects of news discourse, including headlines [2, 7] and noun phrases [6]. the cases examined here were selected because they were critical incidents involving patient safety (infant deaths) and interactive medical devices (infusion pumps) in 2009 with sufficient english language news coverage for analysis. these two incidents are also comparative in that they took place in urban hospitals in western countries (canada and the united kingdom) with publicly-funded health care. • the first case (n=80 articles) involved a four-month old male infant in the uk who died two days after two nurses infused him with 10 times the prescribed amount of sodium chloride. • the second case (n=14 articles) involved a six-week old male infant in canada who died two weeks after pharmacists mixed humulin r (insulin) rather than heparin in his iv food (he was one of four premature babies who received the incorrect medication). news articles were gathered through a combination of lexisnexis, which indexes news articles, and online searches in two countries (canada and uk) in 2012 and 2013 to maximise the sample size; duplicates, such as wire articles running in multiple newspapers, are counted once. the cases are referred to as cases 1 and 2. we made a conscious choice not to use the names of the infants or staff who were involved in the incidents. while these names are part of the public record, we position this research as both sensitive and vulnerable [15] and wish to minimise further harm to those involved and their families. in addition to the infant deaths, nurses were blamed in one of the incidents; we do not want to contribute to a culture of ‘naming, blaming, and shaming’ [12] that some in the medical profession critique [24]. we maintain that this ethical decision does not impede our work. 3.2. data there was an inquest following the infant’s death in case 1, which involved a mathematical error whereby the patient received 10 times more medication than prescribed. number entry research has shown that ‘out by 10’ are a standard class of errors that even skilled users may make [22]. this case received significantly more coverage than case 2. the staff members involved in case 1 were named in the coverage and the nurses were framed as culpable prior to the verdict. news reporting about case 1 covered three distinct temporal periods (2009, 2010, 2012). in contrast with case 1, no individuals were publicly blamed in case 2, in which one of four infants who were infused with the incorrect medication on a neonatal ward died. the error originated in the hospital pharmacy when the incorrect drug was mixed into the patients’ iv food. while the hospital acknowledged the error, a spokesperson said it was a ‘mistake’ and focused on contributing factors as well as procedural and spatial changes that would be implemented in the future. 4. results and discussion we focus our results and discussion on one central theme relating to the data of each incident and how its narrative is constructed. following this we discuss the trend across the two incidents and their narrative arcs to neglect device-related components of the errors. 4.1. reading news headlines headlines draw readers’ attention to news stories, and are critical to news discourse [2, 6, 7]. in examining the headlines associated with the cases where nurses were blamed for infant deaths (case 1), the language used reduces the nurses to the incident and frames them in negative terms. more interesting is the variation in the headlines and how the language of headlines position nurses as incompetent through the deployment of lexical items. table 1. case 1 headline terminology analysis terms in headlines 2009 (n=8) 2010 (n=24) 2012 (n=48) nurse/s or name 0 13 46 adjective applied to nurse 0 5 0 incident applied as adjective to nurse 0 1 9 although two nurses were involved in the error, most headlines (n=52) used the term ‘nurse’ or referred to one nurse by name, with an additional seven headlines using the plural ‘nurses’ (total 59/80 headlines). further analysis also shows a temporal element: none of the articles from 2009 mention the nurse/s involved; instead all articles (n=8) from that period focus on the patient. in 2010, the emphasis is evenly mixed with 24 articles, 13 of which have headlines referencing the nurses. however, in 2012, when the inquest into the death takes place, the headlines skew towards emphasising one nurse (45/48 headlines; an additional headline uses ‘nurses’). thus, there is a notable change over the news cycle of the story: while the subject of headlines immediately after the incident is the patient, in the two subsequent news cycles it is the nurse/s. in the second reporting period (2010) there is also a discursive element of blame that occurs in some of the headlines that refer to the nurse/s. the use of adjectives works to frame the nurses as meriting blame. the five headlines that use adjectives to modify the nurse/s are all negative (lazy (n=2), distracted, bungling, and sickest). the adjectival use terms such as ‘bungling’ or ‘lazy’ when preceding the term ‘nurse’ frame her as culpable for the error and challenge notions of her competency and work ethic. the use of the term ‘sickest’ in a headline frames the nurse in an exclusive category: first it is an absolute and second it implies that the error was purposeful rather than a mistake. additionally, the focus on ‘lazy’, whilst not as dramatic, is a negative linguistic framing tool: it eliminates other possibilities that may have led to the error. mathematical errors can occur for many reasons, individual and systemic, yet this immolates those options. other headlines reduce the nurse to the incident itself (e.g., ‘saline baby death nurse’, ‘fatal blunder nurse’ and ‘salt-death nurse’). although there was one of these found in 2010, as table 1 indicates, the bulk of these (n=9) were in the final reporting period (2012). in these examples, the death comes before the nurse, limiting her to it. the reduction of identity to the incident frames the nurse one-dimensionally as a ‘salt-death nurse’. by using the incident to modify the noun, the nurse is reduced to the incident and, through the lack of person-first language, becomes defined by it. 4.2. system-wide responsibility in the news in case 2 system-wide responsibility was narrativised in the telling of the incident, and received far less news coverage than case 1. in more than half (n=8) of the articles there was discussion of multiple spatial, ergonomic, and non-technical human factors that the hospital resolved to address in the future. various other factors may also have contributed to case 2 receiving less media attention: press culture and regulation differences within canada affect what details can be reported and when [26]; and the decision not to publicly name any of the staff involved, resulted in a news story that did not have a ‘villain’ to anchor the narrative against a ‘helpless victim’, a pattern that can be found in news stories and other narrative forms, including folktales [5]. however, by immediately acknowledging systemwide factors and releasing a plan of how to avoid future errors of this kind, the hospital thereby engaged in ‘image repair discourse’ [3]. the hospital’s public relations approach included addressing systemic factors that were not tied to individual behaviours (e.g., interruptions) but to space, staffing targets, and labeling practices. action points included increasing the size of the hospital pharmacy and the number of pharmacists on staff; implementing safety checks, (e.g., having a second member of staff doublecheck medication); relabeling humulin r to its generic name “insulin” in order to avoid potential confusion with similarly named drugs, such as heparin; and storing insulin in a separate part of the pharmacy, away from other drugs, including heparin. of these action points the last two are specific to the incident – changing how the drug is referred to and where it is stored – and will only prevent a like error from occurring in the future (i.e., an error involving insulin). so although these action points appear to broach system-wide issues that may have contributed to the error they do little in preventing other drug or medical device errors with similar causes. however, by addressing these concerns, the organization took control of the narrative, altering the story itself rather than the way it was framed and moved the focus away from individuals. what is critical is that regardless of the potential efficacy of these actionables with respect to patient safety, they are part of a narrative of ‘taking responsibility’ and allow the hospital to re-position the narrative. the hospital’s own telling (through their spokesperson) of the incident and their proposed actions take the focus from the error and patient death and move it onto their response to the error. 4.3. ‘it’s all about people’ donald norman succinctly described good hci as ‘all about people’ [16]. while people are critical in design processes, our analysis illustrates that devices and design are absent in this coverage. the errors in both cases were described as medication based: a ‘medication error’ and ‘medication mix-up’, respectively. in the total sample (n=94) there was no discussion of the devices used, how the devices may have contributed to the errors, or how better design could have prevented errors. in sum, devices were rendered invisible: organisations and the media did not discuss the possibility that design and devices could be improved. the narratives expressed in the public domain were about people, who were constructed as victims and/or villains. this emphasis is different from what norman and others have called for; the argument for design to be people-centred requires taking situated contexts and actual practices into account and embedding that knowledge into design from the earliest stages. a significant portion of the articles (n=39) mentioned factors that contributed to the error (e.g., interruptions, physical space, labeling, double checking) that good design can broach; of those, 28 of the articles pertained to case 1 (n=80) and focused on interruptions and the remaining 11 were from the case 2 sample (n=14), which covered a wider range of systemic factors. a small number of those articles also discussed changes in guidance that resulted from the errors (n=3 for case 1, n=8 for case 2), but again the focus was on what staff members could do differently or how the workspace could be re-organised. these media case studies illustrate a lack of discourse regarding better design or the possibilities of design: in public and work life technology and design are conceptualised as fixed rather than iterative. 5. limitations as this study consists of a cda of two historic case studies and relies on the information in our corpus, we do not have detailed information about the specific device models used; however, through cda, rich insights are garnered and issues surrounding error interpretation are highlighted that could be of particular relevance for the development of healthcare technology including mobile and remote healthcare application design. this paper offers a theoretical viewpoint that can enhance the understanding of error interpretation in health technologies and inform design protocols that encourage post-implementation, in situ evaluation and monitoring. 6. conclusions while users are critical in usability and design processes, our research into news narratives illustrates that usability and design need to take a more prominent role in public discourse when errors occur. our analysis shows that the reporting on usability related errors is already focused on people and their spaces and that this is problematic for hci researchers and usability designers. even when learning rather than blame is promoted, which has been encouraged by some (e.g., [24]) the discussion in these news narratives focuses on reframing user errors and workplace changes, including traditional ergonomics (e.g., moving supplies, making spaces larger), as is seen in case 2. in both of our news media case studies, technology is seen as outside the realm of what can be transformed, and is discussed only in relation to ‘training’. therefore, the socio-technical system whereby these devices are used, and real-life errors actually occur may be neglected. this suggests a schism with how devices are presented and perceived: there is a focus on human factors in design processes and usability, yet when errors with medical devices occur the device is often rendered invisible. this occurs within the organisations where the devices are used as well as how those errors are communicated to the general public; this can be seen in how the organisations and the news frame the error. it is not simply that a wider understanding of human factor design issues is needed in the general population or within organisations. rather, we propose that design itself may benefit from a more informed and reflexive outlook if hci practitioners and medical device designers have both awareness and a better understanding of the culture of errors, including news reporting of critical incidents. if there were wider public discussion when medical incidents occurred that included the possibility of design changes preventing future errors, then this could promote innovation in design, rather than supporting the status quo. 7. acknowledgments the authors gratefully acknowledge funding from the engineering and physical sciences research council (uk), grant number (ep/ g059063/1). 8. references 1. baker, p. using corpora in discourse analysis. continuum, london, 2006. 2. bednarek, m. and caple, h. news discourse. continuum, london, 2012. 3. benoit, w.l. image repair discourse and crisis communication. public relat rev 23, 2 (1997), 177-186. 4. berry, t.r., wharf-higgins, j., and naylor, p.j. sars wars: an examination of the quantity and construction of health information in the news media. health comm 21, 1 (2007), 35-44. 5. conboy, m. the language of the news. routledge, london, 2007. 6. cotter c. news talk. cambridge university press, cambridge, uk, 2010. 7. dor, d. on newspaper headlines as relevance optimizers. j pragmatics 35, 5 (2003), 695-721. 8. eysenbach, g., powell, j., englesakis, m., rizo, c., & stern, a. health related virtual communities and electronic support groups: systematic review of the effects of online peer to peer interactions. bmj, 328, 7449, (2004), 1166. 9. hamilton, h.e. reported speech and survivor identity in on-line bone marrow transplantation narratives. j socioling 2, 1 (1998), 53-67. 10. imbens-bailey, a., and mccabe, a. the discourse of distress: a narrative analysis of emergency calls to 911. lang commun 20, 3 (2000), 275-296. 11. kushniruk, a.w., triola m.m., borycki e.m., stein b., kannry j.l. technology induced error and usability: the relationship between usability problems and prescription errors when using a handheld application. intl j med inf 74, 7-8 (2005), 519-526. 12. lester, h. and tritter, j.q. medical error: a discussion of the medical construction of error and suggestions for reforms for medical education to decrease error. med ed 35, 9 (2001), 855-861. 13. lin, l., vincente k.j., doyle d.j. patient safety, potential adverse drug events, and medical device design: a human factors engineering approach. j biomed info 34, 4 (2001), 274-284. 14. milenković, a., otto, c., & jovanov, e. 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(2010). wireless sensor network based e-health system: implementation and experimental results. ieee t consum electr, 56(4), 2288-2295. ai for healthy meal preparation in smart cities 1 ai for healthy meal preparation in smart cities bhuvana namasivayam1,* 1software developer, verizon connect, atlanta, usa. abstract introduction: ‘food is medicine’. eating healthy fresh cooked foods is increasingly becoming a challenge, especially among working professionals, elderly people, people in care homes and those getting medical care, as they find it difficult to cook everyday meals and to make sure they take in all necessary nutrients regularly. objectives: with the intervention of robotics and ai, food preparation and delivery can be made efficient in a way it supports overall health and wellbeing. methods: the proposed idea is a smart city ai scheme with robots engaged in food preparation tasks such as chopping, grating etc, robotic kitchens assembled to prepare foods as per the dietary needs of various groups of people and delivery bots and drones to effectively deliver meals, fruits and necessary supplements on a daily basis and also pick up leftovers for effective waste management. this can also be extended to smart hospitals for providing nutritious meals to patients to aid in faster recovery and also avoid the carelessness and haste in food preparation when human workers are involved. keywords: robot, food preparation, drone, artificial intelligence, everyday meals received on 31 july 2022, accepted on 26 september 2022, published on 27 september 2022 copyright © 2022 bhuvana, licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i4.2267 1. background eating healthy is slowly becoming a priority for a lot of people these days and people are willing to spend more money to buy or make healthy wholesome food. at the same time, it is also a challenge to make sure to take in healthy meals on a regular basis, especially among working professionals, elderly people and people getting medical care, because of the time and effort it demands. a good number of people are dependent on house help and restaurants for their everyday meals, but it is still hard to ensure they get wholesome meals with all required nutrients on a regular basis. human prepared meal plans catered to meet nutrient requirements which are becoming increasingly prevalent are quite expensive. also, the availability of such healthy meals should not be a luxury that only the privileged can enjoy and relish. hence creating a system that can provide healthy nutrient rich *corresponding author. email: bhuvana.n21@gmail.com inexpensive meals to everyone alike, becomes important in order to create a healthier and more energetic society [10]. in this day and age, making use of technology and ai to form a system that can provide healthy everyday meals is scalable and efficient and can cater to a large number of people. 2. smart city ecosystem a smart city is an ecosystem of smart capabilities that work with one another to make the city a desired place to live and work. artificial intelligence (ai) plays an important role in the future development of smart cities. a smart city ai framework is an intelligent network of connected objects and machines transmitting data using wireless technology amongst themselves in some cases and to the cloud [17]. by providing the necessary infrastructure, communication platform and enabling access to relevant eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e1 https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:bhuvana.n21@gmail.com bhuvana namasivayam 2 data to integrate any new technological system, smart cities provide a suitable ecosystem to such an initiative. smart cities, in general, also have a health service system that uses technology such as wearable devices, iot, and mobile internet to dynamically access medical information of people, connect people and institutions related to healthcare together and also actively manages medical ecosystem needs in an intelligent manner [4]. iot, mobile internet, cloud computing, big data, 5g, microelectronics, artificial intelligence and biotechnology form the main components of smart healthcare. technology applications and apps also encourage healthier behaviour in people and assist them with the proactive management of a healthy lifestyle. it puts consumers in control of health and well-being [23]. one of ai's biggest potential benefits is to help people stay healthy so they don't need to visit a doctor, or at least not as often. the use of ai and the internet of medical things (iomt) in consumer health applications is already helping people in different ways [3]. 3. robots for food preparation with ai and robotics becoming more accessible, robots are increasingly becoming a commonplace for the food and beverage industry. the early uses of robots in the food industry were primarily for packaging and palletizing operations [7]. now, they are used for various food processing operations from the farm to fork, such as salad making, mixing, chopping, dairy and cheese processing operations like stirring curds, slicing cheese, meat processing operations such as cutting, sorting and packaging and many more [21]. a number of tech firms are now developing robots that can cook and plate up entire meals, both for commercial and domestic kitchens. they can turn on the oven and hob, pick up and put down saucepans and spatulas, stir, whisk and flip [15]. a robotic kitchen has various robots performing different food preparation tasks for different ingredients and an assembler to bring everything together, combine as needed and to arrange entire meals. for example, a steamer component cooks grains and pasta, and a separate element dispenses sauces and garnishes. the different components can be in different temperature-controlled lanes [5], [25]. the robotic kitchen also includes food safe bins where staff in-charge can place ingredients to be cooked. as an alternative, the ingredients are deposited at intervals automatically into bowls that travel through the kitchen on a conveyor belt. an ai vision system, that’s integrated with the robot, identifies the food and the robot picks it up, and cooks it as per the instructions fed to it. the robot then places food in a hot holding area [11]. the chef’s movements can be recorded while making a recipe in a similar kitchen setup as the robot and then transferred onto the robotic arms. those movements would then be streamlined by the robotics team, and formulate a consistent program that would produce the same dish every time [1]. it can also utilise data from the robotic assembly line and other inputs to optimise workflows, recipe development, and food scheduling. a lot of start-up companies are also developing robots that can perform complex food preparation tasks such as flipping burgers, making fried food etc [9]. robotic kitchens are becoming increasingly popular worldwide. an initiative by a start-up in chennai, india in building a fully automated kitchen that can cook more than 800 recipes for provided orders, with no manual effort [24]. a restaurant in boston, called spyce has a dynamic menu where guests can select a dietary or allergy preference on the app while placing an order, and the app instantly reshuffles an item’s ingredients to fit those parameters [8],[12]. 3.1 advantages of robotic kitchens advantages of using robots as compared to manual labour are, they save time, consistency in adding ingredients and preparation, are more hygienic, cost effective and helps reduce food waste. they help people save time and focus on meaningful activities. robots have become capable of producing 350 bowls per hour and completing an order in two to five minutes. there are robots developed that can prepare 50 pizzas an hour, using 35 different toppings and cheeses [18]. performing the various tasks needed to get a dish ready can be tedious and hard to get it right every time for a human chef. for example, griddling patties for burgers, toasting buns and spreading sauces to get a burger ready can be hard or close to impossible to get it right every time maintaining consistency and quality, but the robot chef can do it precisely, quickly and effortlessly. quality food gets delivered quickly and as per guests’ specifications. using robots also helps reduce food waste, avoids cross-contamination, decreases oil spillage, manage resources better and can bring in sustainability [13]. 3.2 robotic kitchen components the main components in a robotic kitchen are robotic arms, which perform the action of picking and placing items and different types of sensors that are integrated in high-precise and lightweight frame structure. often, there is an endeffector attached to the arms that is customised for a specific food preparation task. end-effectors include a wide variety of shaped grippers, suction cups, and other food manipulation devices specific to the size, shape, and rigidity of the food products they are handling. in addition, there is also a computer vision system to determine orientation of the food to be manipulated, attached to the robot. some robot chefs are integrated with natural language processing features and can respond to voice menu orders. eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e1 ai for healthy meal preparation in smart cities 3 robotics also requires special food-safe materials. stainless steel is used commonly since it can withstand caustic cleaning chemicals. in addition, food-safe lubricants can be used on moving parts. cabinets, kitchen appliances and equipment optimised for human and robot use, are integrated and connected to the fully automated kitchens. they can also include a recipe recording system and a connected gui screen with access to a library of recipes. 4. delivery robots and drones four-wheeled, cooler-sized robots that deliver food and beverages, drones that fly to your backyard to deliver food and groceries are increasingly becoming the next future of robotics [16]. robots are already deployed for delivering on college campuses, and in various controlled environments. the robots use satellite imagery to navigate from place to place. they are mostly connected to a centralised computing system which determines the best path for the robot to take for efficiency and safety and also optimises the routes and delivery for the different bots connected to the system at any given point. each robot also has its own set of cameras, sensors and radar to ensure that it can avoid obstacles such as cars, animals and pedestrians [14]. 5. proposed smart city ai scheme for improving overall wellbeing a smart city set up offers various advantages for efficient and autonomous meal preparation and delivery with robotic systems and drones. with iot and high speed 5g network, the overall speed and performance of the system is improved [19]. food delivery bots connected with smart city iot infrastructure and communicating with iot traffic controls and sensors offer efficient and safe navigation and routing through pedestrian walkways in smart cities. exchange of information between meal preparation robotic systems and delivery systems along with the data of dietary requirements of people in the community can be properly utilised to improve the effectiveness of the scheme [2], [22]. a similar robotic kitchen set up in individual households would cost a fortune, whereas a smart city ecosystem with its connected infrastructure, shared resources and services and access to collective data and information encourages community initiatives that can be effectively implemented to improve the quality of life of its inhabitants. the proposed idea is a smart city ai scheme that includes fully automated robotic kitchens with robots and robotic arms engaged in food preparation tasks such as chopping, grating etc, mixing and assembling foods for various pre-programmed recipes and also pack entire meals for people individually based on their dietary needs. figure 1. ai powered meal preparation system the scheme or ai ecosystem proposed also integrates the food preparation units with delivery bots and drones to effectively deliver meals, fruits and necessary supplements on a daily basis to individual homes and care homes in the smart city and also pick up leftovers for effective waste management [6]. this can also be extended to smart hospitals within the smart cities for providing nutritious meals to patients to aid in faster recovery. the system can also be integrated securely with health records of the patients to provide daily supplements and required medications. with the use of robots for meal preparation, the speed and consistency of the number of dishes or food units prepared is considerably increased as compared to human chefs and that provides the way to accommodate individual nutrient needs in every day’s meal preparation schedule. a centralised and decentralised cloud infrastructure and processing system becomes the backbone of the fully automated meal preparation scheme, providing connectivity and communication between the different components of the ecosystem, powering the robotic and ai components and algorithms to function seamlessly, handling and analysing data and information gathered from the smart city’s iot to formulate workflows, optimise routes and make intelligent decisions and also by integrating necessary security and fail safe mechanisms [20]. an ai powered mobile application can be integrated with the scheme for people to include their dietary requirements and receive daily notifications on meal preparation and delivery. eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e1 bhuvana namasivayam 4 6. benefits of the proposed scheme • everyday delivery of fresh meals and nutritious snacks for older people and people getting medical care. • save money and human resources. • variety of menu, catered to dietary needs and nutrition requirements. • more hygienic • fewer mistakes as compared to human workers and reduce food waste. • faster meal preparation and hence • can be extended to use ai to analyse various body types and conditions if any, based on health data collected and to assist people to eat nutritious meals based on that. • cost effective as it can be built to cater to entire communities and also serve different classes of people, equally. 7. conclusion the impact technology and ai can have in improving the collective health of the community is significant and with the belief that nutritious food has the ability to heal and prevent illness, the intent of the proposed idea is to create a healthier and more sustainable societies and cities. references [1] agarwal r, jachowski d, shengxi d. robo-chef: automatic recipe generation. tech. np. 2009 nov. [2] amin su, hossain ms. edge intelligence and internet of things in healthcare: a survey. ieee access. 2020 dec 15;9:45-59. [3] astromskė k, peičius e, astromskis p. ethical and legal challenges of informed consent applying artificial intelligence in medical diagnostic consultations. ai & society. 2021 jun;36(2):509-20. [4] brown j, cug j, kolencik j. internet of things-based smart healthcare systems: real-time patient-generated medical data from networked wearable devices. american journal of medical research. 2020 apr 1;7(1):21-7. [5] cha e, forlizzi j, srinivasa ss. robots in the home: qualitative and quantitative insights into kitchen organization. in proceedings of the tenth annual acm/ieee international conference on human-robot interaction 2015 mar 2 (pp. 319-326). [6] diran d, van veenstra af, timan t, tesa p, kirova m. artificial intelligence in smart cities and urban mobility. policy department for economic, scientific and quality of life policies. 2021. [7] duong ln, al-fadhli m, jagtap s, bader f, martindale w, swainson m, paoli a. a review of robotics and autonomous systems in the food industry: from the supply chains perspective. trends in food science & technology. 2020 dec 1;106:355-64. [8] fürstenau d, auschra c, klein s, gersch m. a process perspective on platform design and management: evidence from a digital platform in health care. electronic markets. 2019 dec;29(4):581-96. [9] hoffmann t, prause g. on the regulatory framework for last-mile delivery robots. machines. 2018 aug 1;6(3):33. [10] klein ja, watson jl, editors. the handbook of food and anthropology. bloomsbury publishing; 2016 aug 25. [11] liu b, zhang m, sun y, wang yc. current intelligent segmentation and cooking technology in the central kitchen food processing. journal of food process engineering. 2019 oct;42(6):e13149. [12] madon s, schoemaker e. digital identity as a platform for improving refugee management. information systems journal. 2021 nov;31(6):929-53. [13] moreno-camacho ca, montoya-torres jr, jaegler a, gondran n. sustainability metrics for real case applications of the supply chain network design problem: a systematic literature review. journal of cleaner production. 2019 sep 10;231:600-18. [14] mukherjee s, baral mm, venkataiah c, pal sk, nagariya r. service robots are an option for contactless services due to the covid-19 pandemic in the hotels. decision. 2021 dec;48(4):445-60. [15] naeem abass m, zohry ae, gamal saad soliman s. the possibility of using robot as one of the artificial intelligence techniques in the food and beverage department in five-star hotels: managers' perspective. 2022 jun 1;11(2):857-907. [16] romanjuk m. delivery robots serving last mile b2c: an evaluation of tallinn residents' incentives behind the usage of delivery robots in 2020 on the basis of starship technologies example. [17] rozenes s, cohen y. artificial intelligence synergetic opportunities in services: conversational systems perspective. applied sciences. 2022 jan;12(16):8363. [18] rusu rb, gerkey b, beetz m. robots in the kitchen: exploiting ubiquitous sensing and actuation. robotics and autonomous systems. 2008 oct 31;56(10):844-56. [19] sallabi f, shuaib k. internet of things network management system architecture for smart healthcare. in 2016 sixth international conference on digital information and communication technology and its applications (dictap) 2016 jul 21 (pp. 165-170). ieee. [20] shuaib m, alam s, alam ms, nasir ms. self-sovereign identity for healthcare using blockchain. materials today: proceedings. 2021 mar 27. [21] singh a, chavan a, kariwall v, sharma c. a systematic review of automated cooking machines and food service robots. in 2021 international conference on communication information and computing technology (iccict) 2021 jun 25 (pp. 1-6). ieee. [22] suppa a, kvist j, li x, dhandapani v, almulla h, tian ay, kissane s, zhou j, perotti a, mangelson h, langford k. roundup causes embryonic development failure and alters metabolic pathways and gut micro-iot a functionality in non-target species. microbiome. 2020 dec;8(1):1-5. [23] tian s, yang w, le grange jm, wang p, huang w, ye z. smart healthcare: making medical care more intelligent. global health journal. 2019 sep 1;3(3):62-5. [24] vijai c, wisetsri w. rise of artificial intelligence in healthcare startups in india. advances in management. 2021 mar 1;14(1):48-52. [25] wallin pj. robotics in the food industry: an update. trends in food science & technology. 1997 jun 1;8(6):193-8. eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e1 securing data using audio steganography for the internet of things eai endorsed transactions on smart cities research article 1 securing data using audio steganography for the internet of things anju gera1,* and vaibhav vyas2 1banasthali university, glbitm, greater noida, india. 2banasthali university, jaipur, india. abstract the internet of things (iot) is prevalent in today's world and is part of our everyday life. while the residential district gains in several respects, numerous problems are developed, such as data confidentiality and privacy. the community is worried, in reality, about what information might leak through iot. therefore, the need for a protected environment is necessary if data transmission from devices across the network is to be protected. as a consequence, this paper proposes a secure scheme for using audio steganography to secure data from laptop, which is distributed as an iot device to other devices, or on lan or wan networks, as an alternative protection strategy along with a home server. the outcome of the developed system shows that the amount of distortion exposed by the signal to noise ratio (snr) is low. keywords: iot, iot protection, disclosure of details, audio steganography. received on 04 july 2022, accepted on 14 november 2022, published on 04 january 2023 copyright © 2023 anju gera et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i4.1775 *corresponding author. email: anju.gera@gmail.com 1. introduction the internet of things (iot) is one of the most emerging innovations to transform the modern world. iot has traditional computing machines but of household devices and several other sensors for data collection. also, hackers could be targets primarily on iot devices with a weak protection level and computing capacities, such as ip cameras, smart tvs and other home appliances with little secrecy. for example, attackers are more likely to intercept continuous data transmission among iot devices because it involves extensive network delivery, typically involving the internet. the intruder can enter or manipulate such iot devices by using the knowledge that he has been obtained for further use by accessing authentication information or by intercepting the link [3, 4]. to solve the confidentiality problem in the iot network, we propose a security scheme involving web access. the use of audio steganography in the lan is based on transmitting confidential audio information between the desktop and home server. in contrast, data distribution between home servers and other computers would be encrypted from a lan (internet). therefore, the paper provides the following efficiency metrics as a steganographic scheme for iot implementation using a robust and lightweight algorithm: computational time, compression ratio, and signal-to-noise ratio, which can accommodate mass deployment [7]. the remainder of the document is arranged accordingly. iot steganography is shown in sec. ii. sec. iii surveys the latest literature on iot steganography. the scheme suggested is defined in sec. iv. sec. v describes modelling tests and outcomes of associated success evaluations. sec. vi ends the paper with future works.2. 2. problems in iot security safety in iot networks entails challenges. these challenges, summarised below, must first be solved before implementing these networks. eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e5 https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:anju.gera@gmail.com anju gera and vaibhav vyas 2 • iot networks need to protect a wide range of products, including laptops, cameras etc. the suggested protection strategies should handle the whole range of heterogeneous systems without compromising their functionality. • devices capacity: because of the heterogeneity of iot architecture connected devices, multiple nodes are available, which include iot networks with limited storage capacity and communication capacities. • data transmission rate: protection schemes should also be able to have high payloads for secured data transfer. 3. related works three essential techniques give security and privacy: cryptography and steganography. encryption turns natural text into an unknown person in an unreadable form. watermarking hides data in a digital medium and sends covers, including ownership and copyright, where the hidden message can be visible or invisible. the unique features, problems and peculiarities of running iot security systems are addressed in an essential work by f. djebbar [1]. the distributed implementation infrastructure, interoperability and heterogeneity of devices and the high traffic amount of iot components are some of these peculiarities. the authors of [2] note that these unique features of iot play an essential role in raising the risk of security attacks in iot compared with other systems with clearly defined security policy and resources in a managed environment. the study [5,6] aims to create an iot security architecture consisting of two algorithms, the aes and the steganography of photography. lightweight encryption is a sophisticated approach for limited conditions, such as rfid tags, cameras, contactless smart cars and medical equipment. in programme deployment, smaller code and ram size implementations which do not always take advantage of the security-performance trade-offs are favoured. if the wsn is built into iot devices to gather adjacent tools and boost the iot device output on the network, self-jamming can be used as a protection mechanism to protect data from disclosure. indeed, selfjamming is a tactic that avoids passive attacks by intentionally jamming the messages obtained by eavesdropper [9,10] and corrupting them. it can be achieved by noise when transmitting data. el gamal encryption is the encryption process used in their analysis. the encrypted message is integrated into the homogenous mp3 audio file frames. the encrypted message is improved with the spread spectrum approach and xor modulation to improve randomness before embedding the register's message. 4. proposed scheme in the real scenario, the mic using desktop allows this opportunity to authenticate customer speech to open doors. in that case, the desktop will receive and transmit users' voices to authentication servers or other computers (ex. cloud storage) outside the lan network for storage, the secrecy of the transmitted data is compromised by every eavesdropping attack, particularly on the lan network. e.g., the voice intercepted is shown as sensitive information in figure 1, and the authentication server [1] would authenticate any intruder who succeeds in getting it through an eavesdropping attack. figure 1. real scheme figure 2 illustrates the proposed scheme for securing a transmitted voice using an iot device. in this case, audio steganography is used to secure sensitive information, such as user voice, which is sent from an ip desktop (iot device) on the lan network. in addition, a home server can be used as a centralised device on the lan network to receive a voice that is already shielded using audio steganography to encrypt it to the computers that are stored on the internet (cloud storage). figure 2. proposed approach eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e5 securing data using audio steganography for the internet of things 3 as a result, the steganography technique can be used as an alternative authentication method for transmitting data in a protected manner. we are implementing audio steganography to protected audio, which is expected to be transferred from an ip desktop to a home server. in order to make the scheme simple, we consider that bob, who owns a home, is entering the desktop with mic to load audio. after the mic has successfully loaded bob's audio, it stores it as audio and loads another audio called the cover audio. instead of transmitting the audio directly to the home server, the audio is covered (embedded) in the chosen audio (cover audio) with a steganography technique to generate another audio (stego audio) that includes the original audio. later, the stego audio can be sent to the home server to recover the original audio from the stego audio using the same steganography method, albeit in a reverse manner. in the other hand, eve, the eavesdropper, has successfully attacked bob 's network to intercept data transfer between the laptop and the home server for any classified information. he realised that a laptop with a microphone would serve as an audio authenticator for bob's front door home. as a result, the user loaded all audios, including stego audio, but does not doubt the audio as it seems to be identical to other audios loaded. steganography is a way of rendering sensitive information and communications undetectable and stopping hackers from identifying them [10]. in the following, the spread spectrum technique was used to conceal encrypted text in the optical audio signal. cast spectrum is a process by which the energy produced in particular by the wavelength is purposefully cast to the frequency domain , resulting in a signal with a broader wavelength. spread spectrum systems encode data as a binary series that sounds like noise but can be understood by a receiver with the right key. there are two types of spectrum spread techniques: the direct sequence spread spectrum (dsss) and the frequency hopping spread spectrum (fhss). in the direct sequence spread range, the data to be transmitted is split into small sections and each piece is assigned to a frequency channel throughout the range. frequency hopping spread spectrum is used in this research work. in frequency-hopping spread spectrum, the frequency spectrum of the audio file is modified such that it jumps easily between frequencies. the explanation for this is that it would be easier to decompose the digital audio signal into an analogue signal using the one dimensional discrete cosine transform (dct). the dct is one of the strong compact transformations. the bulk of the signal energy is transmitted to the first transition coefficients, the lower energy or information is transmitted to other (i.e. high-frequency) coefficients. for x = 0,1,……..n-1, where , where represents the initial sequence of the audio, n denotes the last frames in the audio file, and x denotes the number of frames in the audio file, and u denotes the height of the frame. the spread spectrum combined the compressed text file with the low frequencies of the audio signal using eq.1: ssprect = fdct (low) eq.(1) the embedded signal is applied to the other highfrequency frames using eq.2: fframe(t) = ssprect + fdct (high) eq.(2) the analogue signal generated is then transformed to a digital signal using the inverse discrete cosine transform (idct) as shown below: cdct(u) = eq.(3) where the latest audio signal (stego file) is cdct(u) .the research work was analysed using the following efficiency metrics: computational time, bit per character, compression ratio and signal-to noise ratio. 5. result and discussion the system was implemented using matlab (r2017a version) programming language on windows 8.1 operating system platform. the research work was evaluated using the following performance metrics: computational time, compression ratio and signal to noise ratio. 5.1 signal to noise ratio (snr) signal to noise ratio is a parameter used to know the amount by which the signal is corrupted by the noise. it is defined as the ratio of the signal power to the noise power. alternatively, it represents the ratio of desired signal (say a music file) to the background noise level. it is measured in decibel (db). snr can be calculated by eq. 4 [12] below. snr (db) = eq.(4) 5.2 computational time this is the time taken for the system to execute its function. from table 1, the value of the signal to noise eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e5 anju gera and vaibhav vyas 4 ratio is more than 50db as the size of the text file to be inserted varies from 40 kb to 200 kb, and this means that there will be no distortion of the audio. but from 240 kb to 400 kb, the values of the signal to noise ratio have started to decrease; rendering the values less than 50db and this means that there would be distortion as the value falls from 50db. table 1. snr value after embedding audio size 5. conclusion and recommendation a scheme based on image steganography is proposed in this article, as the ip desktop with microphone and memory capability is used as an iot device to address privacy issues during transmission between smart devices and home servers. in this study, an audio steganography method for mp3 that uses dct and spectrum spread techniques has been developed. implementation and subjective experimentation have shown that the built audio steganography technology supports digital audio mp3 format. the device built has the ability to insert a hidden message of a size of up to 400 kb. additionally, the system has the ability to insert a text size of 250 kb of respect to the digital audio duration or size without any distortion and has the ability to maintain the same size after embedding text into it. these findings suggest that the proposed scheme will satisfy the specifications and difficulties of iot steganography by being able to handle a large number of devices and a large amount of iot traffic. further studies should be carried out to incorporate lightweight cryptography in combination with steganography (dual steganography) techniques to provide more protection for transmitted data using iot devices across the network. references [1] f. djebbar, “lightweight noise resilient steganography scheme for internet of things,” 2017. [2] u. khadam, m. m. iqbal, m. alruily, m. a. al ghamdi, m. ramzan, and s. h. almotiri, “text data security and privacy in the internet of things : threats , challenges , and future directions,” vol. 2020, 2020. [3] h. a.abdullah, a. a. abdulameer, and i. f. hussein, “audio steganography and security by using cryptography,” i-manager’s j. inf. technol., vol. 4, no. 4, pp. 17–24, 2015, doi: 10.26634/jit.4.4.3644. [4] f. djebbar, b. ayad, h. hamam, and k. abed-meraim, “a view on latest audio steganography techniques,” 2011 int. conf. innov. inf. technol. iit 2011, pp. 409–414, 2011, doi: 10.1109/innovations.2011.5893859. [5] a. jurcut, t. niculcea, p. ranaweera, n. an, and l. khac, “security considerations for internet of things : a survey,” sn comput. sci., vol. 1, no. 4, pp. 1–19, 2020, doi: 10.1007/s42979-020-00201-3. [6] c. t. jian, c. c. wen, n. h. binti ab rahman, and i. r. b. a. hamid, “audio steganography with embedded text,” iop conf. ser. mater. sci. eng., vol. 226, no. 1, 2017, doi: 10.1088/1757-899x/226/1/012084. [7] mohsen bazyar, rubita sudhirman, “a new method to increase the capacity of audio steganography based on the lsb algorithm”, journal teknologi science and engineering, 74:6 (2015), 49-53. [8] k.sakthisudhan,p.prabu and dr.c.m.marimuthu,”dual steganograpghy approach for secure data communication”, elsevier international conference on modelling, optimization and computing,2012. [9] mengyu qiao, andrew h. sung, qingzhong liu, “mp3 audio steganalysis”, information sciences, vol. 231, pp. 123-134, may 2013. [10] rostam, h. e., motameni, h., & enayatifar, r. (2022). privacy-preserving in the internet of things based on steganography and chaotic functions. optik, 258, 168864. [11] gera, a., & vyas, v. (2022). hiding capacity and audio steganography model based on lsb in temporal domain. recent patents on engineering, 16(2), 65-74. [12] gera, a., & vyas, v. (2022). message security enhanced by bit cycling encryption and bi-lsb technique. eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e5 this is a title 1 issues of hazardous materials transport and possibilities of safety measures in the concept of smart cities vladimír adamec 1 , barbora schüllerová 1, * vojtěch adam 3 marek semela 1 1vladimir adamec, brno university of technology, institute of forensic engineering, purkyňova 464/118, 612 00 brno, czech republic 2 vojtěch adam, mendel university in brno, department of chemistry and biochemistry, zemědělská 1, 613 00 brno, czech republic abstract the transportation of goods and supplies is an essential part of maintaining a functioning urban infrastructure. it also involves the transport of dangerous goods. this type of transportation may especially in the urban areas signify a high risk that may significantly damage the critical infrastructure of the city if there is an accident and leakage of dangerous chemical substances. the aim is, therefore, to minimize the risk and its consequences. the effective instruments are through the identification, analysis and assessment of these risks, searching for critical areas in cities and ensuring the application of prevention and safety measures. application of risk analysis methods helps to identify the expected and probable risks that can significantly influence the safety of the critical infrastructure. on the other hand, risk analysis methods which can also identify unknown risks with low probability of occurrence are currently being developed. the paper introduces a methodology of assessment of transport risk in cities focusing on reducing the impact of hazard in cities. the risk analysis methods and approaches are subsequently proposed as the initial stage of implementing the selected safety measures. this paper aims to introduce the issue of risks associated with transportation of hazardous substances in cities and to propose measures that are in accordance with the concept of smart cities, in order to contribute to the creation of a functional communication network, traffic flow in cities and increasing the security of critical infrastructure. keywords: road accident, hazardous substances, risk, human health, environment, impact, smart measure. received on 17 december 2015, accepted on 5 may 2016, published on 20 july 2016 copyright © 2016 v. adamec et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eai.18-7-2016.151628 * corresponding author. email:barbora.schullerovar@usi.vutbr.cz 1. introduction one of the aims of ensuring a functional critical infrastructure is its safety. however, it can be endangered by a range of risk factors (disruption to the traffic, to electricity supply etc.). one of the key components of infrastructure is traffic, whose disruption may have an impact on the functioning of the entire society. therefore, it is necessary to be aware of the threats and risks, their assessment, the proposal and implementation of the preventive measures leading to the minimization of these negative phenomena. on the other hand, these measures also help to enhance the ability to respond to undesirable events in time, before the research article eaeai endorsed transactions on smart cities eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e4 http://creativecommons.org/licenses/by/3.0/ v. adamec, b. schüllerová, v. adam, m.semela 2 occurrence of serious damage. the paper introduces the issue of risks arising from traffic focusing on the transportation of hazardous objects in cities, the possibilities of their identification, and analyses including the proposal of measures in accordance with the concept of smart cities. currently, the issue of smart cities is the area that requires the attention of many developed countries and in particular their cities. with respect to the mission of smart cities the emphasis is on creating an environment that uses different flows and interactions in cities (finance, energy, materials, services, etc.). these processes are becoming smart by the strategic use of information and communication infrastructures and services in the process of the transparent land use planning and management, responsive to the social and economic needs [1]. implementing the concept of smart cities should thus be based on strategic planning. one of the current areas is intelligent, ecological, safe and integrated transport. there are currently many projects that are focused on, for example, reducing transport emissions that are in particular associated with the transit traffic in cities [3]. the most serious problem of transport is the contamination of air by the emissions, mainly due to their significant risk to human health, in particular in large cities with a high density of automobile traffic [5]. in recent years, the share of transport in air pollution has been significantly increasing, which leads to the increase in health risks associated with the exposure of humans to these pollutants [6, 7]. one of the completely new groups of substances flowing in this way into the environment is the platinum group of metals (platinum, palladium, rhodium and ruthenium less commonly iridium), which are part of automotive catalysts [8]. in addition to these negative phenomena, there may also be potential risks posed by the transportation of hazardous substances, which is not an isolated case in cities. this risk is only solved marginally within the smart cities. considering the possible risk it deserves more attention, especially in relation to the protection of critical infrastructure, population and the ability to respond faster and more effectively to the resulting undesirable event. 2. transport of hazardous substances hazardous chemical substances and mixtures are substances which exhibit one or more dangerous properties in terms of possible damage to people’s health or lives, to the environment etc. road transport of dangerous things, which also includes transport of hcs, is dealt with in the european agreement concerning the international carriage of dangerous goods by road (adr) [17]. transportation of hazardous substances comprises about 4 8% of the total goods transportation in eu countries. more than 50% of the contents transported are flammable liquids, mostly in the form of propellant fuel. the second most frequently transported substances are condensed gases under pressure. in some of the european countries the amount of the volume transported in 2013 increased by nearly 100% (estonia, luxemburg, great britain) [9]. the risk of the occurrence of a serious road accident is real in spite of the application of safety and preventive measures, which should aim to minimize this risk. one of the reasons is the increasing variety of the transported hazardous substances [10, 11]. hazardous chemicals are not only important for their negative properties but also their other properties, which are used for various activities within the functions of cities, which makes their supply so essential. relevant examples are fuels, gaseous and liquid substances used for disinfection or cooling. currently, the only available summary is the statistics of accidents with leakage of hazardous substances in each country and their regions. these statistics, however, do not contain separate data about accidents of the adr vehicle or vehicles carrying sub-limit volumes in cities. the absence of monitoring the activity of these vehicles in cities becomes a risk which may have a significant influence and impact on urban critical infrastructure and its functionality if it occurs. the importance of the need to reduce the risk of this type of transportation is demonstrated by the experience of the past years (see tab. 1), where there have been accidents of vehicles carrying dangerous substances in cities or urban track, which caused serious damage. in this context it should be noted that these failures have had more serious consequences in urban areas than in rural areas. the evacuation of people can significantly impair the function of the affected cities and disrupt the infrastructure. the accidents may occur particularly in the mobile phase or during loading tasks. in both cases, the level of risk increases with regard to the venue and nature of the event (a dangerous substance was initiated an explosion, fire, toxicity) [10]. table 1 overview of significant hazardous chemical substances accidents [11, 12, 13, 14, 15] event scenario damages 11. 7. 1978, l os alfaques, spain the explosion of a truck with propylene near the camp los alfaques in the village of san carlos de la rápita 216 dead, 200 injuries 10. 11. 1979, mississauga, canada the train explosion and leakage of chlorine in populated areas evacuation of 200 000 inhabitants 4. 8. 1981, montanas, mexico the chlorine leak after truck accident 28 dead, 1000 intoxicated, 5000 evacuated 2. 5. 2011, pilsen, czech republic the fire and explosion pressure cylinders after the accident of 2086 kg of acetylene gas, 50 kg of co2, 240 kg of r-404a, 132 kg of r-407c, 144 kg of r-437a 66 kg r 417a 66 kg of r-422d 72 kg r 134a no injuries. serious property damage. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e4 issues of hazardous materials transport and possibilities of safety measures in the concept of smart cities 3 event scenario damages 7. 5. 2013, mexico city a city of pachua, mexico the explosion of a tank with methane 22 dead, 36 injured, property damage: 30 houses, 20 vehicles 6. 7. 2013, lac-mégantic, canada the explosion of a freight train with crude oil 42 dead, property damage hazardous chemicals have become part of our lives to the extent that it is impossible to imagine a modern society where they are not used. increasing their number as well as the amount of the chemicals transported and used combined with stricter safety requirements leads to the study of the risks arising from the use of these substances, and to the emergence of a series of measures to increase security. this is then reflected for example in legislation or the requirements for emergency preparedness. most of the legislative instruments are focused on static sources, which are for example the production and storage of fuel. the emergency plans for the stationary installations are prepared as part of an integrated emergency system, they are under regular review and the situation is constantly monitored. but there is an absence of such measures in connection with the transportation of dangerous goods. 3. risk of dangerous goods transport in cities risk identification, analysis and assessment are significant stages in the attempt to eliminate it. in general, risk is defined as the probability of an undesirable event occurrence together with often negative consequences [47]. in more detail, risk is described using three main components, which is the probability of an undesirable event occurrence, the vulnerability of the environment in relation to the impact of the undesirable event and finally also the hazard impact itself, whose extent is variable [29]. urban housing estates not only differ in terms of architecture but also in terms of population density, buildings using hazardous chemical substances etc. that is why the level of risk is also variable in this respect and it stresses the significance of risk analysis application, on which preventive, repressive and corrective measures are based. 3.1 critical areas in cities especially vulnerable are the urban areas where there are high numbers of people, whether permanently (city centres, businesses, transfer station hubs, hospitals, schools, etc.) or temporarily (e.g. traffic congestion on the centre circuits and in the city centres). critical places of transport networks can be based on criteria such as: the importance of the road section and the possibility to replace it, the demand for returning the section back into operation, the importance of the section linking a significant portion of urban agglomerations or strategic places, traffic intensity, capacity segment, other risks which threaten the segment [16]. the following are the most frequent causes of road accidents of vehicles transporting goods in the adr mode according to [1,2]:  not keeping safe distance,  not giving way and breaking the traffic rules,  an obstacle on the road,  not respecting safety barriers,  an accident caused by another vehicle,  not adapting the driving style to the situation (traffic density, meteorological conditions etc.). the above mentioned causes of adr road accidents are also the most frequent causes of accidents of common personal vehicles and lorries. this increases the risk of accident occurrence which may involve a vehicle transporting hcs. currently, the movement of dangerous goods by road is coordinated in czech republic only through safety signs (b18, b19) according to the european agreement concerning the international carriage of dangerous goods by road (adr) [17]. each country implements the adr agreement into its national legislation. an example is the regulation on the national and international transport of dangerous goods by road, railroad and inland waters (ggvseb) in germany [43]. this regulation especially concerns motorway transport. outside built-up areas, roads with more lanes and the shortest routes must be used. in a built-up area, a bypass should always be used. in germany and austria, there are also legal measures ensuring the restriction of hazardous chemical substances transport through road tunnels [44]. in the czech republic the movement of these vehicles is limited by prohibition traffic signs especially before some road tunnels where the risk is especially high if an accident occurs. critical points are particularly important transportation constructions, such as bridges, tunnels, intersections. by early identification of these critical points the level of risk can be reduced by using prevention and safety measures. such measures could be, for example, cctv monitoring sites, prohibiting signs for vehicles carrying dangerous substances or providing short arrival times of rescue. one of the effective tools is the application of risk analysis methods and support software tools that can identify, analyse and evaluate the risk, including the modelling of dangerous scenarios development of the situation [10]. 3.2 approaches to assessing the risks of dangerous goods transportation the identification and assessment of the risks of damage requires a comprehensive system approach, both in terms of acute and chronic risk. while the acute risk effects show immediately, especially at the accident location, identification of the chronic risk effects is a complex and time-consuming process [10]. these risks can manifest eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e4 v. adamec, b. schüllerová, v. adam, m.semela 4 themselves, for example in the form of chronic disease on the affected population in the form of respiratory diseases, for example, or the deterioration of environmental quality [5]. first it is necessary to define the area to be evaluated as well as the problem situation and the phase during which the leak occurred:  mobile phase (transportation by road, compulsory safety breaks, checks by state authorities),  loading tasks (loading, unloading, cleaning the shipping containers etc.). in road accidents involving vehicles transporting hcs, there is not only a risk of leakage of a large amount of the transported substance but also a risk of fuel leakage. the volume of fuel in fuel tanks ranges from 200 to 1.200 litres depending on the size and the current condition of the vehicle. although this is an under limit amount of hcs, which is not included in transport according to the adr international agreement, it may also have a significant impact [2]. besides the hazardous substances, the extent of an accident is also significantly influenced by external and internal factors [38] whose character varies with each transport phase (climatic conditions, technical condition of the vehicle, the vulnerability of the environment, health and mental condition of the driver etc.) as shown in figure 1. the example shows the basic factors which can cause an accident either separately or together. with regard to the individual scenario of each road accident or an accident involving leakage of hazardous chemical substances, the probability data are not given for each factor. it is necessary to mention the fact that, with regard to the causes of road accidents mentioned above, it is the human factor which has a significant impact and it is not only the driver of the vehicle transporting hazardous chemical substances but also other road users. it must also be noted that the selection of logic gates may vary regarding the specific hazard scenario. the fault tree (fta) shown below in fig. 1 is therefore illustrative and demonstrates one of the possible scenarios. it is, therefore, necessary to define all the aspects of the transport of dangerous chemicals that may be significant risks for the examined process. a significant part is also the definition of the critical infrastructure vulnerability, which plays a very important role in risk analysis and damage prediction. vulnerability is an important element in the issue of critical infrastructure and its protection, which is also related to transport of hcs. vulnerability expresses the extent to which a system is able to resist adverse effects and, on the contrary, when the ongoing processes and their full functionality are disrupted. according to [29, 30, 31], it is important to distinguish between risk and vulnerability, which is related to loss potential in connection with an accident, destroying, damaging or disrupting a system and its processes. on the contrary, risk is expressed by the degree of probability of an undesirable event occurrence and by the consequences which may be expected within this event. the risk of an accident occurrence involving leakage of hcs significantly lowers the limit to which the whole system (town or village) is able to resist adverse effects. the reason is a high number of residents found in one place at the same time, also the absence of identifying and monitoring the activity of dangerous mobile units in cities, numerous built-up areas, one way streets, heavy traffic without the possibility of providing proper detours when a dangerous event occurs etc. this is also related to the common problem of the time interval of rescue units, which operate in difficult conditions especially in traffic congestions in the morning and afternoon hours. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e4 issues of hazardous materials transport and possibilities of safety measures in the concept of smart cities 5 leakage of hazardous substances during the transport accident technical defect oror roadways natural phenomena human factor failure of the valves breach of tank surface vehicle faults or oror road defect and or natural disasters weather ignoring the safety instructions inattentio n and tiredness impaired health condition material defect mechanical damage material fatigue corosionleakage technical damage (defect) or road obstructi on driver and other factors inattention and tiredness of the other drivers participant of accident wrong road signs traffic situation changes addictive substances figure 1 fta diagram of hazardous materials release during road transport [10] 3.3 application of risk analysis methods to identify risks in urban areas in risk analysis, decisions are made based on the probability estimation (p) of an undesirable event occurrence and its consequences (c) [18, 47]. deciding about the risk means estimating the probability of its occurrence and the probability of the hazard scenario happening [19]. risk analysis of transportation of hazardous substances by road, not only in cities, is a very complex problem as for the selection of a suitable methodology. the aim of the analysis is to obtain relevant information describing the identified risks and their importance for the given area. therefore, it is important to use a combination of methods based on a qualitative, semi-quantitative and quantitative approach. in the first phase of a qualitative approach the process assessed is defined including its components which are related and influence each other. applying this approach can even detect so-called hidden processes, which may occur in connection with the transport of dangerous substances [9]. the application of methods which are based on a semiquantitative approach using a numerical scale helps to determine the level of risk. it becomes an intermediate stage of risk assessment and their categorization and the assessment of events related to each other [19]. the quantitative approach allows modelling of the consequences of hazardous substance leakage in specified areas using precise numerical data. in the case of hazardous substance transportation, the scenarios may include fluid leak followed by evaporation, gas leak with immediate dispersion into the atmosphere, flammable liquids with immediate or subsequent initiation. in general, quantitative approaches numerically evaluate the frequency of undesirable manifestation of the risk sources and their consequences. since the risk analysis methods cannot be used individually for all the transportation phases, the particularly suitable methods are those that are based on a multi-criteria approach using map data and information on where the incident occurred or may occur. some analytical instruments may have a software form and can be connected to an electronic database of chemicals [18, 19]. risk identification should never be underestimated and the occurrence of phenomena which lie beyond the boundary of common expectations (so called black swans) should also be considered. these events are often considered highly improbable as such events have not eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e4 6 occurred before, for example in connection with a particular subject and it is therefore not possible to deduce that this situation will occur. it is the current situation, in which the activity of dangerous substances in a city is not monitored, which means a hidden threat with very serious consequences. these threats do not include only accidents of vehicles transporting hcs. it is also necessary to realize the risk of a possible abuse by terrorist or other radical groups. in transport of hcs, it might be about a deliberate disregard of risk considering the low frequency of these accidents. it could also be a kind of a black swan, the so called unknown known, when the risk significance and its possible fatal impact are realized especially by a group intending to abuse these adr vehicles. although it is not easy to predict precisely the occurrence and extent of the impact of events (e.g. black swan), it is important to ensure that sufficient functional background work is undertaken, which is based on the creation of a communication network and on the preparedness to respond immediately with primary and secondary measures with regard to the safety of the human society. it should also include an adequate analysis and assessment of undesirable events with the objective approach, which includes external experiences and the assessment [20, 21]. within risk analysis and identification, a solution area has been proposed in accordance with the above mentioned procedure. in this case, it is the cities or particularly the urban roads which can be used by vehicles transporting hcs. regarding the high number of various municipality features, the general character of a city with vulnerable elements of critical infrastructure such as bridges, tunnels, roads and the related places like public transport hubs, built-up areas etc. has been considered. 4. proposal for the introduction of smart risk minimization measures currently, there are camera systems monitoring the traffic in most towns. some of them are able to identify a vehicle based on its licence plate. it is especially carriers who use other smart systems – locators – which are linked to an electronic logbook. these locators are equipped with a device based on the global position system (gps) and they can provide information about the current location of a vehicle including a real time display in a map with the update interval of approx. 30 seconds. daily ride overviews allowing for displaying routs in 3d maps are recorded in logbooks. however, these locators are mainly used by private companies and organizations and therefore it is not possible to obtain this data easily and use it for processing statistical data and for marking dangerous routes. with regard to the possible use of safety measures in cities, it is necessary to introduce smart systems that identify the moving city traffic unit, warn drivers of adr vehicles about the route for transportation, communicate with the emergency services and warn other drivers and residents in time in the event of an accident. monitoring of vehicles transporting hazardous chemical substances has been implemented for example in germany, where it is a voluntary measure though especially for private carriers. what is widely used here is for example the rfid system from 2011 [39] or the tracking and tracing application for private transportation companies, whose data are not publicly available. in 2011, the savenav project was also launched, which works with smart warning signs called orangebox. these signs automatically detect a road accident of a vehicle carrying dangerous material and they automatically report the location and some other important information to an emergency center [40, 4]. other projects focusing on monitoring the movement of dangerous material include the bluebox project with the display in map data. the situation in austria is very similar to that in other eu countries. even here there is no legal obligation to monitor the movement of vehicles carrying dangerous material. what is working here, however, is the monitoring of vehicles in the adr mode in tunnels, which uses telematic systems. in the alpine regions, it is also germany and italy who cooperate in the monitoring [44]. the czech republic is also considering the monitoring of vehicles in the adr mode. however, the carriers are afraid of losing sensitive data [45]. some projects concerning the monitoring and identification of vehicles carrying dangerous material were created for the purposes of emergency services which can prevent some other serious consequences of accidents by an early intervention. one of these in europe is the mitra project [46]. in the czech republic there are also companies in the chemical industry cooperating with the integrated rescue system and the carriers using the trins system [47]. the above mentioned examples of project results focus on an overall monitoring of vehicles in the adr mode following their routes, which also means outside cities, and using the gps signals. unfortunately, these measures are not legally obligatory and that is why we cannot rely on the carriers to use them also due to their mistrust in the safety of sensitive data mentioned. however, for the purposes of increasing the safety of critical infrastructure in cities, it is also possible to use the existing systems which have been implemented to monitor regular traffic. one of the measures proposed is the identification and monitoring of the adr vehicles that are arriving in the city or moving around the city. what can be used is the existing cctv system, which is already widely used in most cities. given that these types of vehicles in cities are moving mostly in order to supply, the carrier or the recipient could report the planned entry of vehicles into the city and their predicted route. the integrated rescue system should be able to monitor vehicle movement and communicate with it in order to prevent undesirable events (e.g. the information about the closures, traffic congestion). another option is automatic vehicle identification by the adr marking, which is already used for license plates of vehicles [22]. the necessary need for eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e4 v. adamec, b. schüllerová, v. adam, m.semela 7 the monitoring of the movement of vehicles transporting hazardous substances has been proved by research projects carried out in europe and worldwide [23, 24, 25]. applying these measures may be important not only in the area of prevention. in cases where there is a leakage of dangerous substances, it is necessary to avoid movement in the socalled danger zone in which the substance is spread. in this case, it is necessary to transfer early information to drivers through dynamic information panels informing about the incident in the danger zone and allow other drivers to choose alternative routes. these measures are already often used for example in road tunnels, where the drivers must be informed immediately about the situation if a dangerous event occurs and a safe evacuation of persons present in the tunnel must be ensured. [27]. the timely information through visual communication mediated by these panels can prevent the traffic collapse and enables the rescue services to get to the crash site and to the injured persons. dynamic information panels would be appropriate to supplement a warning light signalling for the cases of an undesirable situation. as study [26] shows, implementing these signs is important for increasing safety not only in the case of an accident but also for prevention and in informing the driver about a possible risk. when these measures are implemented, it is possible to monitor the average activity of hcs in cities, their intensity and possibly also the kind of substance. based on this data it is possible to produce statistics and their evaluation allowing for identification of areas in cities where there is the highest incidence of these mobile sources of risk. as a consequence, safety measures can be adjusted in accordance with the requirements. 4.1 swot analysis of the proposed measures considering the complexity of some operations needed for the possible implementation of these measures into the smart cities system, a swot analysis was carried out (see table 2, 3). the aim of the swat analysis was to identify the individual aspects of the measure from the point of view of internal and external aspects, which may have a significant influence on the decision concerning their integration. within the method, classification and evaluation were divided into 4 basic groups where the mutual interactions of strong factors (s) and weak factors (w) with opportunities (o) and threats (t) were compared. the qualitative information obtained helped to define and evaluate the level of their mutual clash. defining the individual factors in the groups was preceded by an analysis of the current state, which was briefly introduced in the chapters above. it was necessary to define the areas which these measures would apply to. the first part dealt with the legislative and legal form so that the monitoring could be implemented in cities as the measures are currently not enforced on the national, regional or local level. in this case, it is important to formulate a proposal for the measure implementation so that it is in accordance with the current legislation on all levels. therefore, it is not only about cooperation between the state, the regional offices and the municipalities but also cooperation with carriers. these legislative measures should consider the ability to ensure prevention and safety from the point of view of mobile sources, which is currently not dealt with properly except for the adr regulation. it is a complicated step, which may, nevertheless, significantly contribute to the protection of critical infrastructure from the perspective of legal tools. another discussed area is the assessment of technical equipment using the technical elements that have already been implemented or the need for new equipment. the assessment has been based on the obtained data on the technical possibilities of passing on dynamic information and early warning of drivers. the financial demands have also been considered in the case of implementing a completely new system in towns. the ability of the proposed measures to increase effective communication in the case of an accident has been assessed. the measures have also been assessed from the perspective of the integrated rescue system. the first measure assessed by the swat analysis is shown in table 2, which focuses on monitoring vehicles transporting hcs and thus also its ability to identify and analyse a potential source of danger. table 3 specifies the key factors for the provision of dynamic information panels and signs in cities aiming to make communication easier not only with the drivers. table 2 swot analysis of the adr vehicles monitoring in cities strenghts weaknesses  automatic adr vehicles identification  awareness of adr vehicles movement  ability to respond rapidly to adverse situation  use of existing camera systems (cctv) location and communication with the drivers of the adr vehicles  exact location of potentially dangerous goods  obsolete camera systems (cctv)  small cctv coverage  cctv coverage without automatic identification of the adr signs  the new system price  absence of the equipment for communication with the driver of the adr vehicle  absence of solutions in the current legislation opportunities threats  increase of safety and security  improvement of the drivers (adr vehicles) and the integrated rescue system communication  providing better traffic flow  improvement of prevention measures  the annual statistical  adr vehicles without signs  deliberately poorly labelled adr vehicles  illegible signs for vehicles  unreported transport in the city  poor communication by the carrier and recipient  disagreement with the eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e4 issues of hazardous materials transport and possibilities of safety measures in the concept of smart cities 8 reports for the evaluation of the critical points  introductions of these measures into legislation czech and european union legislation then, five or six key points of the internal and external factors were selected based on the swot analysis. monitoring adr vehicles in cities is one of the measures for which the existing cctv systems, implemented mainly in big cities, can be used. the strong point in this case is the possibility of automatic identification, which warns about the activity of moving mobile sources of risk in towns. what is also an advantage is the possibility of communication with the driver of an adr vehicle and allowing him to change the rout if there is an obstacle such as an accident etc. the main advantage could be the possibility of a quick response to the occurrence of an undesirable event. what could become the weak point in this case is an obsolete camera system which is not capable of automatic identification. another weak point of these measures could be a considerable financial burden on towns when implementing these new camera systems. on the other hand, it is an important safety measure allowing for a significant reduction in losses in accidents or other unfavourable events. what is a threat are vehicles that are not marked because of transport of a very small amount or an intentional substitution of the marking, which happens mainly due to the conditions of transport requirements. if there is an accident involving unmarked or badly marked hcs, the risk considerably increases. an especially important opportunity in this case is to improve communication among carriers in adr and rescue services in order to increase safety and security, and to prevent accidents with spills of hazardous substances and ensuring traffic flow. table 3 swot analysis of the dynamic information panels in cities strenghts weaknesses  rapid transfer of the information  ability of the rescue services and drivers to respond rapidly to the undesirable situation  communication with drivers and persons around  using and supplementation of the current dynamic information panels  ensuring the traffic continuity in the case of an accident and information about alternative routes  the new system price  the choice of a uniform style of information for drivers and other persons  obsolete system that does not allow connections to gsm emergency services  selection of specific locations for the placement  depending upon a source of energy opportunities threats  increase of safety and security and accident  accident in location without information prevention  improvement of the drivers (adr vehicles) and the rescue services communication  ensuring a better traffic flow not only in the case of an accident  utilization of the information panels not only after the accident cases  the renewable energy use (alternative or additional source of energy for information panels) panels  unreadable information  failure of energy resources  broken communication system  delay of the information transmission another analysed measure is the use of the dynamic information panels, which are now commonly used for highways or city circuits. that is why this system has also been chosen as a suitable device for communication with drivers. a strong point of this measure is the possibility of a rapid transfer of information on an undesirable situation. this is especially true if the dynamic traffic panels are placed where the vulnerable elements are and they can therefore become an effective information and communication device. these measures can also serve as suitable measures for ensuring the traffic fluency if there is a major accident involving a leakage of hcs and for preventing the movement of persons in a dangerous zone. the weak point is the difficulty in selecting suitable locations for the placement of these information panels. that is why it is important to identify the high-risk areas first and to assess the necessary amount and layout along roads. to ensure fast communication with drivers, a suitable marking of an alternative route is necessary as well as its comprehensible presentation, the choice of language etc. that is why an inappropriate choice of information and its formulation may become a weak point. although these types of panels are equipped with light signs with a relatively long lifetime period, it is necessary to appoint a person who will be responsible and to set the dates of regular checks on the functionality of the dynamic panels to prevent non-functionality of the information or its part. the threat is therefore in this context particularly an accident in an area without the information panels and movement of people in the danger zone. like the previous measure, this one also provides an increase in safety and prevention ensuring the traffic flow and a reduction or complete averting of the undesirable impact in the case of an accident. the possibility of ensuring substitute or additional power sources to prevent any malfunction of the system due to power failure is also important. currently, the variable information panels and traffic signs are equipped with led diodes as they do not require a lot of power supply. this measure could become effective in this case, especially if there is a loss of energy resources. the variable information panels could support eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e4 v. adamec, b. schüllerová, v. adam, m.semela 9 the weakening of the power supply or possibly become an alternative energy source for a certain period of time discussion the risk related to hazardous chemical substances depends on the type and the dangerous properties of these substances such as toxicity, explosiveness, flammability etc. there are also other factors that have a significant influence such as the amount of the leaked substance, the presence of initiation sources, the character of the surroundings where the leakage occurred, the number of persons present in the vicinity of the accident etc. [10]. while the toxicity of the leaking hazardous substances has a significant impact on the residents and on the environment, both acute and chronic, it is especially the explosive and flammable substances that are significant for the overall functionality of the critical infrastructure in cities [13]. these may have, after their initiation, destructive effects not only on a human being but also on property and public urban facilities [12]. therefore, there is an important question of whether vehicles in the adr mode can pass through cities without limitation and whether there is a need for special safety measures for some vehicles with regard to the level of risk and the environment vulnerability. currently, there are more options of monitoring vehicles including the projects mentioned above [39 – 42, 46], which deal with the monitoring of vehicles using the gps signal. however, these are often devices intended for private carriers and in some cases the information is not provided to the emergency services, which may influence the development and seriousness of an accident. what can be used are the monitoring systems that are a common part of the technical equipment in cities and towns such as the cctv. this is a vehicle monitoring system based on identification of signs such as the licence plate or the adr vehicles marking (the un code and the kemler code) [32, 33] and it works on the principle of converting digital images into electronic text [34, 35]. the reasons of an insufficient identification of a vehicle marking are bad lighting conditions, illegible marking due to staining or because there is another object or vehicle covering it [36 38]. identification by the licence plate is suitable for vehicles transporting a sub-limit amount of hazardous substances. considering the number of vehicles in the adr mode and the number of haulage and similar companies, it seems more suitable to identify vehicles by their special marking, which some software is already able to identify [34, 35]. as there are camera systems widely used in cities and towns, the costs are not expected to be as high as for a completely new monitoring system. what remains a problem is the absence of a legal obligation to monitor vehicles transporting hazardous material not only in cities but in all of the eu territory and other places in the world [41, 42]. making this a legal obligation is a matter of a long-term process and it is necessary to notify the state and governing bodies not only in individual countries of the threats posed by insufficient monitoring of hazardous material. the need for legal securing of the other measure (dynamic information panels) is not such a significant problem. applying these measures is a common safety and preventive element in road traffic. its adjustment to accidents involving adr vehicles does not require complicated modification to be functional and implementable. the important thing here is their placement in pre-selected critical locations in cities, where the level of risk is particularly high and an accident may have serious negative consequences. that is why it is important to apply a detailed risk analysis including assessment and determination of the seriousness of various hazard scenarios and the risks arising from them as the paper explains. applying risk analysis and using the proposed measures based on its results should lead to a reduction in hazard thus eliminating the risk. they are especially preventive measures offering alternative uses of the existing safety features to ensure a correct functionality of the infrastructure required by the smart cities standards. conclusion the possibilities of implementing the smart cities concept are very wide and it is a long process. the paper points out the issue of the hazardous substances transport in cities which is currently not dealt with enough. it is an essential part of maintaining their functional infrastructure. despite the low probability of a traffic accident and leakage of hazardous substances the significance of their impact is very high. to ensure prevention and improvement of safety the important part of communication is not only with carriers in adr, but also with other drivers and people who are moving at the place of an accident. therefore, a good knowledge of the transport infrastructure in cities including critical locations is necessary. this paper, therefore, introduces the basic methodology approach to risk identification and analysis. it proposes measures that can be incorporated into the already functional systems in cities and can be used not only for the purpose of transporting hazardous substances in cities which have been assessed by the elementary swot analysis. in the analysis 5 6 key factors were selected that can positively or negatively affect the whole process. the important opportunity is not only to improve the communication network between drivers and emergency services but also the possibilities of using so-called green energy, which can be used in both of the proposed measures. the aim of this paper was mainly to highlight the current situation and the need to ensure the activities in this area. detailed procedures for removing the weaknesses and threats will be the subject of further solutions and research. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e4 issues of hazardous materials transport and possibilities of safety measures in the concept of smart cities 10 references [1] european commission (2015). digital agenda for europe, smart cities, avaliable o the internet: https://ec.europa.eu/digital-agenda/en/smart-cities [2] matějka, p.; jizba, t.; tvrdý, k. 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(2009) risk analysis and management. basic concept and principles. r&rata, 2 1(12), pp. eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e4 issues of hazardous materials transport and possibilities of safety measures in the concept of smart cities performance evaluation of arima and fb-prophet forecasting methods in the context of endemic diseases: a case study of gedaref state in sudan 1 performance evaluation of arima and fb-prophet forecasting methods in the context of endemic diseases: a case study of gedaref state in sudan hussein ali hussein1, mukhtar m. e. mahmoud2,* and haroun a. eisa3 1department of information technology, university of gedaref, gedaref, sudan 2faculty of computer science and information technology, university of kassala, kassala, sudan 3department of computer science, alsharg ahlia college, kassala, sudan abstract today, artificial intelligence is a key tool for turning a city into a smart city, and advances in information and communication technology (ict) have led to the development of smart cities with many different parts. smart health is one of these components and is used to improve healthcare by providing services such as disease forecasting, early diagnosis, and others. there are various machine learning algorithms available now that can help with s-health services, but which is better for disease forecasting? gedaref state, for example, has some of sudan's heaviest rains, and malaria and pneumonia are widespread throughout the year. predicting future trends for these diseases has been a major focus for researchers in order for gedaref's administration and the state's ministry of health to design effective ways to prevent and control the development of these diseases, as well as to prepare an adequate stock of medicine. as a result, it is necessary to establish a trustworthy and accurate forecasting model to aid gedaref's government in developing economic and medical strategies for dealing with these diseases, as well as taking action on medical resource allocation. this study uses a time series dataset collected from the state's ministry of health to estimate malaria and pneumonia as common diseases in gedaref state, sudan, five months later. to comprehend the overall number of cases of diseases, two forecasting methodologies, namely the arima and prophet models, are applied to the disease's dataset. the performance of the arima and fb-prophet forecasting systems in predicting malaria and pneumonia diseases in gedaref state is compared in this study. the data was collected from the state's ministry of health between january 2017 and december 2021. the results reveal that the arima technique outperforms the fb-prophet forecasting method in both malaria (rmse: 182.8, mae: 141.6, mape: 0.0057, and mase: 0.0537) and pneumonia (rmse: 1400.3, mae: 1001.4, mape: 0.0513, and mase: 0.9136). keywords: smart city, artificial intelligence, pneumonia and malaria diseases, endemic diseases, gedaref state. received on 07 february 2023, accepted on 08 march 2023, published on 30 march 2023 copyright © 2023 hussein a. et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v7i2.3023 *corresponding author. email: 1. introduction in recent years, smart cities have dominated discussions about shifting economic growth, local geographic development, and accessibility. despite enormous amounts of global investment in smart cities, such as $608 billion usd, many people are still unclear about what smart cities are. a smart city is defined as a metropolitan area that uses electronic and technological infrastructure, such as information and communication technology (ict), to collect real-time data and insights, supply key services, and address local issues. smart cities are also used to improve municipal operations such as public transportation, power and water supply, and sanitation. eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities | volume 7 | issue 2 | https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ hussein ali hussein, mukhtar m. e. mahmoud and haroun a. eisa 2 using this information, the city administration may make educated decisions about establishing effective solutions to the city's present problems [1]. the use of machine learning and other cognitive sciences to help doctors make decisions is an important way ai is used in medicine.ai could help specialists and clinical professionals share more accurate findings and treatment plans by using information about the patient and other data. furthermore, by breaking down massive volumes of data to produce better preventative care suggestions for patients, ai can help make medical services more predictive and proactive. medical services are likely the most essential area in the bigger picture of huge information because of their critical role in a flourishing society. ai implementation knowledge can mean the difference between life and death in the healthcare profession. in their regular work, specialists, medical caregivers, and other medical service employees can profit from computer-based intelligence. simulated intelligence in medical services can increase preventive care and personal happiness, lead to more precise judgments and treatment techniques, and result in improved overall outcomes. by evaluating data from administration, medical services, and other sources, simulated intelligence can also anticipate and track the development of dangerous diseases. as a result, as a tool for preventing illnesses and pandemics, ai has the potential to play a vital role in global well-being [2]. gedaref state is located in eastern sudan, bordering ethiopia; kassala and khartoum states in the north; aljazira state in the west; and sennar state in the south. the international border crossings in gedaref state are the hamdayet border crossing in the north and the gallabat border crossing in the south. gedaref is home to many tribes, including arabs, beja, nubians, and others. the state is known for its large-scale rainfed agriculture activities and vast agricultural acreage. sorghum and sesame are the two main agricultural products. rainfed agriculture and the production of arabic gum are the state's main sources of revenue [3]. malaria and pneumonia are the most common diseases in gedaref state, with the most cases between 2017 and 2021, according to data from the state's ministry of health. the who says that malaria is a dangerous disease that is found in most tropical countries. prevention and therapy are both options. however, simple malaria can progress to a severe type of sickness that is commonly fatal without treatment if a prompt diagnosis and appropriate treatment are not delivered. female anopheles mosquito bites, which are not contagious and cannot spread the disease from person to person. plasmodium falciparum and plasmodium vivax are the two parasite species that cause malaria and do the most harm to people. there are around 400 anopheles mosquito species, and about 40 of these, known as vector species, are capable of conveying disease. several factors, such as the kind of local mosquitoes, influence the likelihood of infection, with certain areas being more vulnerable than others. the risk is greatest in tropical settings during the rainy season, although it may vary seasonally [4]. pneumonia, according to the world health organization, is an acute respiratory disorder that mostly affects the lungs. when a healthy person breathes, tiny air sacs called alveoli fill up and form the lungs. when a person gets pneumonia, the alveoli get blocked with pus and fluid, making breathing difficult and oxygen intake limited. pneumonia is the leading infectious cause of death in children worldwide. pneumonia killed 740 children under the age of five in 2019, accounting for 14% of all deaths in children under the age of five but 22% of all deaths in children aged one to five. pneumonia affects children and families all throughout the world, with the highest fatality rates in southern asia and subsaharan africa. pneumonia in children can be avoided, and it can be managed with low-cost, low-tech treatment and care [5]. using past and present data, time-series forecasting is a way to predict future values over time or at a single point in time. we may make well-informed decisions about the ministry of health's strategy and future trends by looking at data from the past [6]. the autoregressive integrated moving average (arima) method is a one-dimensional technique. the ar component, often known as p, is calculated by correlating current values in a data series with past values in the same series. the ma component, q, is obtained by associating current values of a random error term with prior values. current and historical data mean and variance values are thought to be steady, or unaffected, over time. a component (symbolized by d) is included if necessary to compensate for a lack of stationarity via differencing. in a non-seasonal arima (p, d, q) model, the number or order of ar terms is denoted by p, the number or order of differences by d, and the number or order of ma terms by q. the parameters p, d, and q are all numbers that are bigger than or equal to 0 [7]. fb-prophet is a time series data forecasting method based on an additive model that takes into account yearly, monthly and daily seasonality as well as holiday factors. it works best with time series that have strong seasonal influences and data from multiple seasons. prophet is robust to missing data and trend changes, and it deals effectively with outliers [8]. this study presents estimates of malaria and pneumonia as common diseases in gedaref state, sudan, five months later, using a time series method and a dataset collected from the state's ministry of health. to comprehend the overall number of cases of diseases, two forecasting methodologies, namely the arima and prophet models, are applied to the disease's dataset. the performance of the arima and fb-prophet forecasting systems in predicting malaria and pneumonia diseases in gedaref state is compared in this study. the data was collected from the state's ministry of health between january 2017 and december 2021. although there are several predicting studies in the literature, we could not find much that compares arima and prophet time series eai endorsed transactions on smart cities | volume 7 | issue 2 | performance evaluation of arima and fb-prophet forecasting methods in the context of endemic diseases: a case study of gedaref state in sudan 3 models at the same time to compare and analyze the malaria and pneumonia datasets. to the best of our knowledge, the dataset investigated in all of the studies listed below was limited to certain commodities or places. unlike prior studies that focused on a specific condition, this one looked at a number of them. furthermore, the most popular forecasting approaches have been used for completeness. the rest of the paper is structured as follows: section 2 presents the related work. section 3 describes the dataset and methodology used. section 4 shows the results of the methods employed and investigates the outcomes of various methods. section 5 discusses the findings. section 6 concludes the paper. 2. related work this section provides a summary of the most relevant papers on the application of arima and fb-prophet in epidemiology. ersoz et al. [9] compare the accuracy of arima, prophet, and holtwinters exponential smoothing forecasting algorithms for covid-19 disease epidemiology in europe. the dataset was obtained from the world health organization (who) and comprises covid-19 case data from european countries classified by the who between 2020 and 2022. the results show that the holt-winters exponential smoothing approach (rmse: 0.2080, mae: 0.1747) outperforms the arima and prophet forecasting methods; the study's main weakness is the limited amount of available data. ziyuan ye et al. [10] made a hybrid model to predict how dirty the air will be in shenzhen, china. for blending time and space relationships, it is based on arima (the auto-regressive integrated moving average model) and prophet. after training their models with data from 11 sites that measure air quality, the researchers gave their models weights. experiment results demonstrated that this hybrid technique can improve air pollutant prediction in shenzhen. in certain ways, arima is more accurate than prophet, but it takes 10 times as long as b. the majority of arima's computation time is spent seeking for the best sequence of (p, d, q) and (p, d, q, s). kumar et al. [11] suggested that data from supermarkets be used to make an fb prophet tool that can predict how much food will be sold. in the proposed study, many forecasting models, such as the additive model, the autoregressive integrated moving average (arima) model, and the fb prophet model, were looked at. according to the proposed research effort, fb prophet is a better prediction model in terms of low error, better prediction, and better fitting. the statistical approaches given by sirisha et al. [12] for this successful inquiry, the autoregressive integrated moving average (arima) and seasonal arima models (sarima), as well as the deep learning technique of long short-term memory (lstm) neural network modeling in time series forecasting, were applied. it was converted into a stationary dataset for arima but not sarima or lstm. based on test data, fitted models were constructed and utilized to forecast profit. forecasts for the next five years have been completed with 93.84% (arima), 94.378% (sarima), and 97.01% accuracy (lstm). in terms of developing the optimal model, the results show that lstm beats both statistical models. ning et al. [13] present a machine learning-based time series forecasting system that uses existing data as time series and extracts prominent attributes from historical data to predict future time sequence values. three methods were explored and evaluated to overcome the restrictions of traditional production forecasting: autoregressive integrated moving averages (arima), the long-short-term memory (lstm) network, and prophet. this study begins with reflective oil supply data from a well in an unconventional reservoir in the denverjulesburg (dj) basin, and the application of arima, lstm, and prophet techniques to 65 wells in the dj basin demonstrates that arima and lstm perform better than prophet—most likely because not all oil production data includes seasonal changes and arima is strong in forecasting the oil production of wells across the dj basin. 3. material and method this section talks about the malaria and pneumonia datasets that were used in this paper and how they were evaluated. while figure 1 depicts the workflow of our methodology, the three subsections that follow, namely i) dataset, ii) arima technique, and iii) fb-prophet technique, provide details on each phase. figure 1. flowchart of our methodology the methodology of the work is divided into 5 steps as follows: step 1: disease dataset: this step concerns collecting the disease dataset from the ministry of health. diseases dataset data pre-processing fb-prophet method arima method forecasting forecasting performance evaluation eai endorsed transactions on smart cities | volume 7 | issue 2 | hussein ali hussein, mukhtar m. e. mahmoud and haroun a. eisa 4 step 2: data pre-processing: this step contains three stages to guarantee the accuracy and completeness of the data: i) data cleaning; ii) feature selection; and iii) feature extraction and transformation. step 3: time series forecasting methods (arima and fb-prophet): in this step, we prepare the system for predicting diseases five months later. step 4: forecasting: this step concerns conducting the forecasting methods and gives the results for each one. step 5: performance evaluation: in this step, we use the error metrics (rmse, mae, mape, and mase) to evaluate the performance of forecasting methods and choose the best one. 3.1. dataset the diseases dataset in gedaref state was collected by the ministry of health's statistics department and the state's information center. the dataset contains data on the total number of disease cases from january 1, 2017 to december 31, 2021. the dataset contains 25062 records from all diseases in the state during this time period, as well as 20 characteristics. the features of the dataset are ("quarter", "diseases", "diseases code", "male -1", "female -1"," male 1-4 years", "female 1-4 years", "male 5-14 years", "female 5-14 years", "male 15-44 years", "female 15-44 years", "male 45-64 years", "female 4564 years", "male 65+ years", "female 65+ years", "sum of males", "sum of females", "total cases", "localities", "years"). data cleaning was undertaken to ensure the accuracy, completeness, and accuracy of the data, which was obtained in arabic and then transformed to english. feature selection: the purpose of this stage was to pick the suitable features (date and total cases) for use in the forecasting procedure. feature extraction and transformation: in this step, the feature that was chosen before is taken out and changed into a form that helps with prediction. the disease dataset was then made by just adding "date" as a time series. it has 60 rows, and the common "diseases" in the state are malaria and pneumonia. in the disease dataset, each row showed the total number of disease cases for each month from 2017 to 2021. tables 1 and 2 show the features of the dataset, and figure 2 shows the dashboard of full diseases, which shows the most common diseases in the state. figures 3 and 4 show the overall number of malaria and pneumonia cases over the five-year period. the data was divided into two sets: one for training the models and one for testing the approaches' performance. table 1. demonstrate the whole dataset before data pre-processing no features data type 1 quarter categorical 2 diseases categorical 3 diseases code categorical 4 male -1 numeric 5 female -1 numeric 6 male 1-4 years numeric 7 female 1-4 years numeric 8 male 5-14 years numeric 9 female 5-14 years numeric 10 male 15-44 years numeric 11 female 15-44 years numeric 12 male 45 -64 years numeric 13 female 45-64 years numeric 14 male + 65 years numeric 15 female + 65 years numeric 16 sum of males numeric 17 sum of females numeric 18 total cases numeric 19 localities categorical 20 years datetime table 2. demonstrate the dataset after data preprocessing. figure 2. demonstrate the dashboard of whole diseases. features data type min value max value mean std. dev date datetime malaria numeric 6786 32383 16839 6082 pneumon ia numeric 9565 27177 18659 4014 eai endorsed transactions on smart cities | volume 7 | issue 2 | performance evaluation of arima and fb-prophet forecasting methods in the context of endemic diseases: a case study of gedaref state in sudan 5 figure 3. illustrates the malaria disease over five years in months. figure 4. illustrates the pneumonia disease over five years in months. 3.2 auto regressive integrated moving average (arima) method the auto regressive integrated moving average (arima) generates forecasts by providing a specific temporal arrangement depending on its limitations and prediction mistakes [14]. the order of the autoregressive expression p, the degree of differencing d, and the order of the moving average expression q define a non-seasonal arima model. the integer p is the number of y occurrences that will be used as indicators. also, q is the number of prediction errors that are not interesting and should be added to the arima model. the modifications required to solve the problem d = 0 if the temporal difference is constant at that instant. the following is the generic difference series equation: ŷt = μ + ϕ1 yt-1 +…+ ϕpyt-p θ1et-1 -…θqet-q (1) where ϕi are the coefficients, yt-p, and et-q are the model's lagging predictors. choosing suitable p and q values necessitates optimization and testing. graphs of the autocorrelation function (acf) and partial autocorrelation function (pacf) must be analyzed to calculate the values. the following prerequisites must be met in order to achieve this goal: a few univariate time series forecasting algorithms that rely purely on subjective eye assessment and follow these guidelines may be beneficial. however, when large sums must be projected, these criteria become ineffective. one option is to use software tools to select arima's parameters automatically. another approach is to search the solution space for different parameters and propose the ones with the lowest error [15]. 3.3 fb-prophet method: facebook developed the fb-prophet time-series analysis and forecasting algorithm [16]. this model incorporates parameters for holidays, trends, and seasonality, which will help shape prediction results and provide higher performance with time-series data that has seasonal affects. the following equation is used to combine these ingredients: y(t)=g(t)+s(t)+h(t)+εt (2) where g(t) represents the trend, which is non-periodic growth changes, s(t) reflects seasonal variations, and h(t) describes the effects of holidays. the following equation defines the trend: 𝑔(𝑡)=𝐶(𝑡) / 1+𝑒𝑥𝑝 (−(𝑘+𝛼(𝑡)𝑇𝛿) (𝑡−(𝑚+𝛼(𝑡)𝑇𝛾))) (3) where c(t) is the carrying capacity, k is the growth rate, and m is an offset parameter. the precision, speed, and resilience to outliers and trend shifts of fb-prophet are well-known. it is totally automated, allowing it to produce an accurate forecast from a jumbled set of data without the need for human intervention. it's an additive regression model with trends like a piecewise linear growth curve or a logistic growth curve. it recognizes changes in patterns in real time by identifying data change points [17]. 4. results this section describes the application of two forecasting models. as performance measures, rmse (root mean squared error), mae (mean absolute error), mean absolute percentage error (mape), and mean absolute scaled error (mase) rates are used to evaluate forecasting algorithms. the following are the definitions of rmse, mae, mape, and mase: (4) (4) (5) eai endorsed transactions on smart cities | volume 7 | issue 2 | hussein ali hussein, mukhtar m. e. mahmoud and haroun a. eisa 6 where n denotes the number of data points, 𝑦(𝑖) is the actual value of 𝑖th data point and �̂�(𝑖) is the predicted value for the 𝑖th data point. (6) where m denotes mean absolute percentage error, n denotes the number of times the summation iteration happens, at denotes the actual value and ft denotes the forecast value. (7) (7) where ej is the prediction error for a specific time, defined as the actual value (yj) minus the predicted value (fj) for that period: ej = yj fj, and the denominator is the mean absolute error of the one-step. 4.1 arima model results: to estimate the parameters q and p, the arima model evaluates the autocorrelation function (acf) and partial autocorrelation function (pacf) graphs. acf measures the degree of correlation between a time series and its lagged values. after the linear effects of the lags in between are removed, pacf indicates the correlation between the time series and the lag. the acf and pacf graphs from the disease dataset are given in figures 5 and 6 for malaria disease and 7 and 8 for pneumonia disease, respectively. figure 5. illustrates acf in malaria disease. figure 6. illustrates pacf in malaria disease. figure 7. illustrates acf in pneumonia disease. figure 8. illustrates pacf in pneumonia disease. from the aforementioned figures, we must select the best (p, d, q) pair with the lowest rmse, mae, mape, and mase. based on the results, the arima approach has the lowest rmse, mae, mape, and mase from the figures above. based on the data, the best (p, d, q) combination for malaria disease is chosen as (0, 1, 0), resulting in an rmse of 182.8, mae of 141.6, mape of 0.0057, and mase of 0.0537 for the arima approach. as demonstrated in figures (9) and (10) for the effective arima forecasting process for 5 months on malaria and pneumonia disease, the optimal p, d, and q pair is chosen eai endorsed transactions on smart cities | volume 7 | issue 2 | performance evaluation of arima and fb-prophet forecasting methods in the context of endemic diseases: a case study of gedaref state in sudan 7 as (0, 0, 2) for pneumonia disease, resulting in an rmse of 1923.9, mae of 1578.3, mape of 0.0834, and mase of 1.4399. figure 9. forecasting malaria disease using the arima model. figure 10. forecasting pneumonia disease using the arima model. 4.2 fb-prophet model results in the application for exploratory data analysis, the parameters of the fb-default prophet are used to make an fb-prophet model. these parameters are changed automatically. according to the findings, the fb-prophet model for malaria disease has an rmse of 2815.9, mae of 2614.6, mape of 0.1237, and mase of 0.9907, while the fb-prophet model for pneumonia disease has an rmse of 1923.9, mae of 1578.3, mape of 0.0834, and mase of 1.4399. figures 11 and 12 show how arima can be used to make accurate predictions about malaria and pneumonia over a period of 5 months, respectively. figure 11. forecasting malaria disease using the fb-prophet model. figure 12. forecasting pneumonia disease using the fb-prophet model. table 3 shows the rmse, mae, mape, and mase values of arima and facebook's prophet for predicting malaria and pneumonia in gedaref state. as shown in table 3, the arima approach outperforms the fbprophet method in forecasting new cases of both malaria and pneumonia in gedaref state. table 3. demonstrate rmse, mae, mape, and mase values for arima and fb-prophet forecasting methods forecasting method diseases performance metrics rmse mae mape mase arima malaria 182.8 141.6 0.0057 0.0537 pneumonia 1400.3 1001.4 0.0513 0.9136 fb-prophet malaria 2815.9 2614.6 0.1237 0.9907 pneumonia 1923.9 1578.3 0.0834 1.4399 eai endorsed transactions on smart cities | volume 7 | issue 2 | hussein ali hussein, mukhtar m. e. mahmoud and haroun a. eisa 8 5. discussion as governments stockpile medicines, it has become important for them to try to figure out how malaria and pneumonia will change in the future. because of this, it is very important to build a reliable and accurate forecasting model that will help governments come up with economic and medical plans to deal with these endemic diseases and decide how to allocate medical resources. in this study, there were 60 data points that broke down the malaria and pneumonia disease statistics for gedaref state by month. arima and fb-prophet models were used to figure out how malaria and pneumonia will change in the future. when the constructed models were compared in terms of performance, the results revealed that the arima technique outperformed and had the lowest error than the fb-prophet forecasting method in both malaria (rmse: 182.8, mae: 141.6, mape: 0.0057, and mase: 0.0537) and pneumonia (rmse: 1400.3, mae: 1001.4, mape: 0.0513, and mase: 0.9136). we notice that, in the small dataset, arima is a powerful method. the fb-prophet method requires holiday effects in the dataset to boost its performance. 6. conclusion in this work, the arima and fb-prophet forecasting models were used to predict how many people in gedaref state would get malaria and pneumonia. between january 2017 and december 2021, the data was gathered from the state's ministry of health. in terms of rmse, mae, mape, and mase error metrics, our results suggest that the arima model in both malaria (rmse: 182.8, mae: 141.6, mape: 0.0057, and mase: 0.0537) and pneumonia (rmse: 1400.3, mae: 1001.4, mape: 0.0513, and mase: 0.9136) outperforms the fb-prophet model. forecasting methodologies, as demonstrated here, can aid in the prediction of future patterns for a variety of diseases as well as be implemented to reduce the number of diseases in the state, which is beneficial to public health. we anticipate that the study's findings will be valuable to governments and health authorities in terms of correctly planning medical support and providing necessary resources, such as medical staff and care facilities, for future diseases. these methods will be combined with iot-enabled solution to provide a smart disease management framework in our future work. acknowledgments the authors would like to thank the ministry of health in gedaref state for providing us with this information, particularly dr. hussein, director of the ministry of information and statistics center. references [1] s. myeong and k. shahzad, 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[17] mahanty, m., swathi, k. teja, k. s., bhattacharyya, d., “a prophet model to forecast spread of covid-19 pandemic,” journal of xidian university, vol 14, issue 7, pages 949-962, 2020. eai endorsed transactions on smart cities | volume 7 | issue 2 | the service-bond paradigm— potentials for a sustainable, ict-enabled future reza farrahi moghaddam1,2,*, yves lemieux2, mohamed cheriet1 1synchromedia lab and cirrod, ets (university of quebec), montreal, qc, canada h3c 1k3 2ericsson research cloud technology, ericsson canada inc., montreal, qc, canada h4p 2n2 abstract the service paradigm has gone through a long journey of evolution and improvement. a service-oriented vision to activities in general could serve as a platform for the global transition to a sustainable future. however, the services themselves are required to move beyond their traditional definition in order to prevent any secondary side effect. here, a new paradigm is proposed based on bonding between entities involved in a service interaction, service chaining, or service orchestration. it is purposed to serve as a vehicle to approach sustainability at the global level in a manner that is thoughtful, collaborative, and incremental. the service bonds are then simply generalized toward representing bonding among more than two entities. finally, a practical application of ict agents in enabling the service bonds is presented in a use case related to smart houses along with some ict-based agents (federal regulars, among other ict agents). received on 21 september 2015; accepted on 07 july 2016; published on 20 july 2016 keywords: service, sustainability, service-bond, ict, smart city, smart house copyright © 2016 reza farrahi moghaddam et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eai.18-7-2016.151625 1. introduction services have been becoming the mainstream in interactions and activities not only between traditional end users and providers but also among many more generic actors that collaborate, interact, and compete among each other to deliver a service or product to a client, a customer, or another actor [1–4].1 even many of product-level providers have been starting to change their fundamental paradigm of providing from a product-based approach to a service-based one in which the role of the product itself has been changed from being the sole purpose to becoming just a part of the service interaction. in addition, service-based approaches to interactions and procurement have shown to have a great potential in breaking down, composing, and orchestrating complex interaction. this in turn brings in an implicit and integrated sense of agility to operations regardless *corresponding author. email: imriss@ieee.org, linkedin: https://www.linkedin.com/in/rezafm 1because of the limited space, we considered a supplementary references section presented in the supplementary material, which is accessible at http://arxiv.org/pdf/1507.06295.pdf#page=14. of the degree of complexity. all these capabilities show the great possibility of the service-oriented operations to become the dominant form of interaction. despite the significant advantages of such a service-oriented future, the net impact of such a paradigm shift could be ‘negative.’ in particular, there is a possibility that the whole service-based world would default on itself, i.e., it enters a unsustainable state. therefore, all aspects of this transition should be seriously considered and studied, especially considering the fact that many constraints of the [physical] product-based world would diminish or at least become unnoticeable by the operators, clients, customers, and actors of a servicebased world. service paradigms have been unofficially summarized into three research paradigms [5]: 1. paradigm 1. the services were goods-driven and were focused on providing and maintaining goods to customers. 2. paradigm 2. the relationship with customers was recognized. 3. paradigm 3. the scientific and also designing perspectives were introduced for services. this 1 research article eaeai endorsed transactions on smart cities eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 reza farrahi moghaddam et al. helped to go beyond satisfaction survey, and consider all possible details, complexity, and social relations in a service-providing operation down to the granularity level of the service blueprints [6, 7]. what is common in all research paradigms of services, regardless of their level of scientific depth, is the presence of the relations component. in particular, it has been observed that human shows a pro-social nature that is somehow shared with other species [8]. this behavior might be the result of the need for adaptation and survival in hostile environments in the past. although, in the future, this behavioral ‘wiring’ could become loose in the shadow of an evolution droved by new environments that human has built. in a pure service-based world, the prosocial behavior, especially toward the providers, could simply be weakened and disappear. this in turn would disrupt many operations that have been traditionally the mainstream. although such big changes might seem fine from a selfish point of view in a short-term vision, there is a great necessity to contain, guide, and probably immerse big changes toward a sustainable future especially when an inclusive perspective is targeted that in turn requires sustainability of all entities. in our vision to sustainability, every involved entity is consider an actor. in this way, in addition to well-known actors such as individuals, every involved society (such as a city or a neighborhood) or enterprise (such as a small business) is considered as an actor. we do not stop there, and we consider every recognizable entity of nature (such as a lake or a forest) or every recognizable entity of economy (such as the businesses collocated on a street) as an actor. the combination of all these five categories of actors is denoted as the sustainability pentagon [9]. this is aligned with a challenge related to the move toward a fully service-based world especially in terms of the purpose, which has been mostly seen toward generating value [10]. all this suggest that a revisit of the service paradigm at large is required in a thoughtful, collaborative, and incremental (tci) way to ensure its purpose and sustainability. such a paradigm may also serve as a vehicle for approaching the sustainability at the global level in a tci manner. the question of sustainability in services is our main interest in this work. we will briefly discuss some of potential disadvantages of the generic vision to services, and then propose a bond-based paradigm to go beyond the current approaches in service providing. we start with a basic definition of a service in the form of any offering that can be formalized as a request-provide cycle agnostic to who is the requester and who is the provider. it will be shown that information and communications technology (ict) could play a critical role in implementing such an alternative paradigm. the paper is organized as follows. in section 2, a discussion on the downfalls of current service paradigm (if we can claim that there is such a well-agreedon paradigm) is provided. the following sections provide various perspectives, and especially focus on the disconnection between the service requester and provider and its potential harm when the service markets is exploited in terms of the number providers and also their ephemerality. section 4 presents the proposed service-bond paradigm toward designing interactions based on the right to include [11]. in addition to providing a naive version of the proposed paradigm, a modified version based on the timemodulated interactions is presented in order to balance between the inclusion and exclusion aspects of actors and entities. then, in section 4.3, the role of the ict industry in realizing the proposed paradigm and more generally in shifting the service operations toward a more sustainable state is discussed. 2. downfallsof the currentservice paradigm in this section, we refer to a generic service paradigm as the baseline of our discussions. although we recognize that such a generic form may not cover all complex service operations in practice, it can be argued that many of its shortcomings could also manifest in the actual service operations. as mentioned in the introduction section, we would like to follow a tci approach to this fundamental challenge, and therefore we are looking for an incremental and collaborative convergence toward a global understanding and modeling beyond the scope of this paper. starting from a typical well-managed service operation, there are a few common components. for example, we can name the service level agreement (sla), which carries the service level objects (slos), and its quantification in terms of the quality of service (qos) measures and also in terms of more relation-oriented alternatives, i.e., the quality of experience (qoe) measures [11]. the presence of the qos measures by itself is a sign that the current service paradigm is not self sufficient [12]. in other words, a service could not be completely defined or expressed by itself, and there are parts that are left out and are assumed to be later on covered by the qos constraints. in a non-competitive situation, a provider would prefer such ambiguity in specifications that would reduce their level of accountability and liability. however, in a competitive service market, which is expected to be the case for all services, many providers could simply and unintentionally lose their position to the other [probably-more-ephemeral] providers. although such market effects seem to be part of a natural market evolution, the current scarcity state of resources would not allow us to let a slow-converging ‘natural’ approach potentially brings us to a sustainable 2eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 state. preserving the diversity of the actors, in this case the providers, would be a key element in planning a thoughtful road map with small-magnitude or at least contained disruptions. the fact that the qos measures are predominant factors in almost all well-managed service interactions could be also interpreted as the current service paradigm is not about what is ‘provided’ but instead it is more about what has been ’agreed on.’ we start with a typical service cycle. it is worth mentioning that this cycle does not cover those steps related to why the service requester actually initiates their request. we will come back to this aspect later on, in particular because of their fundamental impact in explosion in the volume of service requests which in turn would be a key factor in moving operations out of a sustainable state. a simplified service cycle is presented as below: 1. request. a particular service a is requested by the requester r. 2. advertisement. a potential matching service is advertised by a provider p: a + ε. 3. negotiation. a broker b would present a + ε to r, and would negotiate toward an agreement. 4. provide. the service that is actually provided by p upon the agreement would be a + δ. 5. audition. upon completion of the service or at a milestone stage, b or another third party negotiates to ‘prove’ that ‖a − (a + δ)‖, or actually and more accurately ‖(a + ε) − (a + δ)‖, is negligible. 6. acceptance. r ‘accepts’ that what is provided is what was ‘agreed on.’ 7. termination. the end of the service cycle. it has been observed that the perceived discrepancy from an agreed servicea could be highly different when measured from the perspective of the service requester compared to the case when it is measured from the perspective of the provider [2]. in other words, the distance functions used to calculate ‖(a + ε) − (a + δ)‖ could be two different functions, namely ‖·|r and |·‖p depending on which perspective is considered: 1. requester perspective: ‖(a + ε) − (a + δ)‖r, 2. provider perspective: ‖(a + ε) − (a + δ)‖p. a more detailed discussion on the ‘service distances’ is provided appendix 4. the actual service life cycle does not start or end at the boundaries of this cycle. although various approaches have been considered to manage initialization and alignment of the service cycles (such as advertisement), we argue that the main challenge to be addressed is within the service cycle itself, and many other aspects would smoothly adjust if the service cycle is shifted more toward the service itself than the associated contract. 3. a summaryof service paradigm’s interactions as mentioned in the previous section, the challenges related to the current service paradigm and its associated uncontainable avalanche phenomena are rooted in the service cycle itself. however, the current solutions to these challenges are mostly planned outside that cycle. here a brief and generic list of implementations of a service operation is provided as the baseline. the proposed paradigm will be introduced in the next section relative to this baseline. the four generic forms of service interactions: 1. naive interaction. as illustrated in figure 1(a), this form of service interaction assumes that there is only one requester and one provider in the service ecosystem. therefore, the interaction would be impractical because it ignores presence of redundant providers or requesters among other actors in a real situation. however, it could serve as a baseline for other forms. 2. directory-based interaction. this form is sketched in figure 1(b). it is more realistic because it considers possibility of multiple providers for the same service. this form of service interaction has been well implemented in the actual service operations. the directory entity holds the description of providers and allows the requester to search and choose one from the available pool. to some degree, the directory could be seen as an advertiser entity. the main disadvantages are: 1) it is a passive form of interaction, i.e., even if the requester does not inquiry the directory, still interactions could happen by other means, 2) there is a high possibility that hidden and biased relations are built between the directory and some of the providers that would induce bias in the directory’s functions, for example in its ranking mechanism, 3) there is no guarantee that the ranked list of providers is up to date. 3. broker-based interaction. as shown in figure 1(c), a broker plays a role of an ‘active’, intermediate entity between the requester and a potential provider. it has two advantages over the directory-based form of service interaction: 1) it is active in that sense that the broker could translate the initial, immature service request into a more legible one ready to be digested by the providers 3eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 the service-bond paradigm — potentials for sustainable, ict-enabled future reza farrahi moghaddam et al. (a) (b) (c) (d) figure 1. four forms of implementation of services. a) the naive form with only one requester and one provider. b) the directory-based form. c) the broker-based form. d) the brand-based form. and 2) it is agile and it could converge to a more adapted form of the service request tailored to the actual special needs of the requester. also, the ‘persistent’ memory of the broker from their past interactions with providers and requesters help them to prescribe a personalized service chain for each individual requester. however, there is also some disadvantages: this form of interaction would require a ‘full’ trust of the requester in the broker. this requirement could pose as a highrisk weak point to the requester’s operation; the working space of a broker is bigger than just one requester or one provider, and therefore their interest could highly differ from those of a specific requester. the point of failure could happen in two forms: (a) continuous degradation. the broker prescribes a series of service interaction, chaining, or orchestration (sico) that are not optimal to a requester in order to create benefit to another client. (b) discrete failure. the broker, after acquiring the full trust of a requester over time, prescribes a fatal, one-shot sico that is harmful to the requester with possible benefits to the competitors. 4. brand-based interaction. it is illustrated in figure 1(d). in the brand-based form, a large number of possibly-unrelated providers are gathered in a ‘cloud’ associated to a brand. the process of inclusion of potential providers would probably go through a series of selection and eligibility steps. in addition, the big scale of a brand compared 4eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 to an single broker or provider would increase the level of trust in them and also decrease the risk of misadvantage of trust by them. however, the weak point of a brand could be identified at its performance, i.e., their shortage in the management bandwidth that is required to guarantee the same quality from all their service providers covered under their umbrella (or more precisely in their cloud) could pose as a risk factor. in particular, the answer to the question that whether a requester should generalize its trust in a brand to every service provider hidden and opaqued behind that brand would highly depend on the level of criticality of the requester’s operation. in the case of downstream (equivalently could be called higher-level or higher-layer) critical mission operations, and considering the higher scale of the damage at the requester side compared to that of the brand side, the brand-based approach to services could only serve as an initiation. figure 2. the proposed service-bond paradigm. 4. proposed bond-based service paradigm the proposed bond-based service paradigm could be seen as a pro-active approach to the sico. as shown schematically in figure 2, the requester and the provider include each other in their own space in a bond-based service interaction. in other words, the bond-based paradigm assumes that the requester and provider become a single entity in an sico, or more specifically a service interaction. the benefits of the proposed approach are listed below: 1. persistence. the [mostly-in-a-weak-sense] bonding between the parties would create a sense of persistency that would in turn increase the level of trust among them. this factor would help to generates the same benefits expected from a brokerbased approach while at the same time reduces the associated risks. for example: (a) a provider offers or assembles other services that are close to the original service in a fasttracked manner. (b) both parties would see the service interaction as a win-win interaction. 2. inclusion. the fact that the parties include each other in their own premises would create a higher level of trust and also partnership that would then accelerate service delivery and satisfaction. we will address the challenge of including an external party in the self premises in a time-modulated bonding approach that will be discussed in the following subsection. 3. review. the bond would be reviewed in periods of time in order to give the parties the chance to move out of the bond. this not only provides a planned method to end a bond-based service interaction in a controlled manner, it also gives interactions an aspect of accountability in that sense that the participating parties should deliver their terms within finite time intervals. 4.1. beyond binary single-bond services: service chemistry the idea of service bonds presented in the previous section is the foundation of the proposed service-bond paradigm. however, the scope of the paradigm is not limited to only single bonds between two entities. to provide a better visualization of how service bonds could create complex interactions, we would like to use a metaphor between the service bonds and that of molecular chemistry. in this representation, every entity or node corresponds to an imaginary “atom”, and service bonds become molecular bonds between two atoms. the bonds would provide ‘bridges’ among entities to continuously exchange discrete objects of the services. this covers the persistency aspect of bonds as discussed in the previous section. the simplest service “molecule” with more than two entities can be built using three entities and two bonds (as shown in figure 3(a)). although depending on the type of entities involved, a 3-atom 2-bond service molecule could have various variations, the next more complex form would be a ring of three entities connected with three bonds (figure 3(b)). 5eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 the service-bond paradigm — potentials for sustainable, ict-enabled future reza farrahi moghaddam et al. figure 3. a) an example of 3-entity 2-bond sico in the context of the proposed paradigm. b) the case of a ring-like bonding: three entities and three bonds among them. figure 4. an example of a polymer-like service-bond build among entities. the resulting service polymer could be called a ‘community’, and it further interact with other entities or communities in the ‘weaker’ forms of bonding. we will explore this aspect of the proposed servicebond paradigm in another work. however, as an example of the capability of the service molecules to absorb complexity of interactions, a ‘polymeric’ service molecule is shown in figure 4. this type of service molecules could play a role in enabling sicos using ‘communities’ in which entities are of small size, limited mobility, and therefore highly dependent on their ‘neighborhood.’ in the communities, an entity would play the roles of requester and provider at the same time while because of their small size they could not interact with a large number of entities. a service polymer would be a compatible model to represent a community, which provides possibility to study and therefore improve communities while it could be a means to implement, model, and enable interactions among communities (polymeric molecules). 4.2. time-modulated bond-based service interactions as mention in section 4, the proposed bond-based service paradigm would suggest [or more precisely would require] presence of parties’ handprint. in contrast to footprint, the notion of handprint is used here where positive impacts are expected [13]. in the others’ premises. although such an act of inclusion should impose no risk to the parties when there is a full trust, in order to reduce the possible risk or 6eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 bonded at t1 unbonded at t2 bonded at t3 unbonded at t4 bonded at t5 figure 5. an example time series of a time-modulated service bond between two entities. in those time intervals that the bound is removed, the service interaction is still in effect. to decrease the associated vulnerability we propose a practical, time-modulated implementation of the service bonding while it does not require the handprint to be permanent. the concept is shown in figure 5. it is worth mentioning that compared to a traditional service interaction, where the two parties directly interact with each other only at the beginning and the end of service cycle, the time-modulated of service-bonding is comprised of multiple instances of ‘bonding’ that go beyond negotiating and validating the terms of the contract. in comparison with fully-connected naive form of the service-bond implementation, the time-modulated variation provides time intervals in which the parties are not bonded to each other. the benefits of such alternating state could be summarized as follows: 1. a bond itself, i.e., the state of being presented in the other entity’s premises, requires some resources such as access bandwidth for data transfer (see section 5.1 for an example). the time-modulated variation allows the entities to reduce and manage the associated resource consumption. in other words, the bond is forced to ‘encode’ itself in such a way that it could survive in the presence of disbond time intervals. 2. the amount of, for example, data transferred is limited compared to the fully-connected variation, and therefore there could be a higher level of trust between the parties because even in the case of a breach the scale of damage would be smaller. 3. by setting the sampling frequency associated to the bond/disbond intervals low enough to be less than that of an entity’s frequency of change, it would be possible to prevent the possibility that the entities build behavioral models of the other parties involved in the bonds. 4. there is a possibility to ‘grade’ the bonds based on the ratio of time intervals of bonded compared to the time intervals of disbonded states (or the total time interval). the grading capability allows the parties to change their degree of bonding in a ‘continuous’ manner compared to the binary and discrete changes that are possible in fully-connected variation. a continuous change in grading could be used for signaling, such as positive or negative feedback, agile construction of a bond, or even smooth termination of a bond. it is worth mentioning that in the planned disbonded intervals the service itself is active and is delivered, and only the bonding aspect of the associated sico is disactivated. 4.3. the role of ict: agent-, bond-based service paradigm as a candidate to replace service paradigm the critical aspect of the service-bond paradigm is its implementation. in other words, the main challenge that an entity would face in exercising the bond-based sicos is how they could allow another entity in their premises and at the same time present themselves in the premises of that entity in a managed and forvalue manner. the limited management power of every entity would eventually put them in a position where they are at risk because of unmanaged, self-allowed intrusion they accepted. at the same time they would bear liability of their unmanaged presence in others’ premises. one possible solution to such dilemma could be built on top of a crowd of an practically unlimited number of “trustworthy” loyal agents. assuming that such a crowd is practically feasible with zero or marginal cost to an entity, the entity could assign one agent per service-bond to with-minimal-risk relocate their management load to the agent. the agentbased approach to implementation of the service-bond paradigm would eventually collapse if the entities used 7eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 the service-bond paradigm — potentials for sustainable, ict-enabled future reza farrahi moghaddam et al. figure 6. a) the schematic diagram of a binary service bond enhanced with the presence of the (e)ict agents. the agents enforce bilaterality of the service bond while reducing the associated risk and liability of each party. b) the agents could share the same cloud-based resource provider for their storage or analytics requirements. in this case, a green sustainable telco-grade cloud (gstc) serves both agents of the service bond. as agents are not ethically-disposable.2 the ict3 seems to be the solution to such a requirement. in particular, open-source and crowd-driven models and code could be developed and maintained to serve as the core of the ict agents that would handle service-bond sicos among entities (figure 6). especially, having the actual ‘instances’ of these ict agents in the local [or remote] premises of an entity would have greater advantages compared to the central approaches: 1. transparency. in contrast to a centralized approach, agents could by-default nullify any question on fairness raised from the multitenancy aspect associated with the central intelligence. 2. sub-optimal. however, there is a chance that the open-source built agents become highly suboptimal mainly because many of contributors to the open source ‘under’-participate in integrating the best practices they have achieved. it could be expected that with increase in the number of active participants beyond a critical ‘mass’, i.e. a mass associated to the start of a merger phenomenon of outsiders in the “attractor” [15], all entities would benefit from more optimal practices and agents, and at the same time it would accelerate detection of possibly not-yetexperienced ‘bugs’ in those practices. 2although classifying the whole set of entities in various classes and labeling some of the classes as disposable has been practiced before, it is against both ethic and also inclusion-of-all visions. 3we occasionally use the (embedded) information and communication technology, in short (e)ict, notion instead of ict in order to emphasize on the ‘embedded’ dimension and its potentials [14]. ict as a transformative force in redefinin the service paradigm. as mentioned in the previous section, the (embedded) information and communication technology, or (e)ict in short, would pose a critical player in the transition toward a new vision to service paradigm. we think that such a transition could serve as a mainstream platform in a larger-scale global transition to a sustainable future. a considerable portion of ‘human’ activities could be classified as service activities in that sense that they are triggered and initiated in order to answer to a need. ability to manage, contain, and potentially nullify the needs and their associated before-known-as-essential service activities would be a great contribution of the (e)ict. it is worth mentioning that changing the norm would usually require a disruptive transition. however, it is important that such a transition is planned in a contained and managed manner with a mission to include and to survive all. here, some of benefits of service bonds empowered by ict are listed: 1. real-time. ict is known for being real-time, fast, and ‘instant’: 1.a) brokerless. it could simply remove or redefine the concept of traditional brokers. 1.b) journey accompanier. it can play as a platform to realize ’bonding’ to a requester, i.e., accompanying them in their ’journey’ that they have started by initiating their request. 1.b.i) bond vs. request. the ‘initial’ request does not need no longer to be a ‘service’ request. instead, it would be more a ‘bonding’ request toward a 8eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 greater ‘state’ in a journey that would mark a handful of interactions (more generally sicos) that are ultimately equivalent to the traditional service cycles. 1.b.ii) east-west vs. north-south. another key benefit would be that the transactions would not necessarily initiated ‘downward’ or ‘southwise’ by the requester. instead, it is highly recommended that nodes in lower levels or layers of service stack initiate ‘upward’ or ‘norhtwise’ transactions, which would create a highly interesting experience for a potential requester by exposing them to possibilities that they could not even imagine otherwise. this bilateral form of interactions enabled by the service-bonds eventually replaces the notion of north-south in the service decomposition with a new notion of east-west or more precisely sidewise interactions. a simple but practical example from a telco use case (or their substitutions in the near future in the form of ims-like4 providers) would be to send not-for-profit notification to clients letting them know they could make calls with highly reduced rates when the network is highly underutilized. also, it is possible to create indirect profit for such practices by relocating revenue generated in penalizing actors that do not follow best practices [17]. in general, the (e)ict agents that serve in the service bonds are required to be lean, open, and therefore verifiable by entities even if the entities have a limited process power. in the next section, a generic use case related to service-bond paradigm and the role of ict in the context of smart house vision is presented. 5. the service-bond paradigm in practice: possible use cases in the following subsections, we propose a few practical use cases where the service-bond paradigm could provide considerable benefit to all parties involved in the operation. 5.1. use case a: the bond-enhanced smart house the notion of smart house has been used in various contexts to represent different approaches to provide 4ims stands for ip multimedia subsystem [16]. smart services in the one of the most private type of premises. also, smart house has been seen as a building block of smart building, smart neighborhood, and smart city visions. it could range from simple but effective automation of activities in a ‘house’ to centralized and personalized full management. considering various vital ‘inflows’ to a typical household, i.e., water, electricity, connectivity, food, and air (wecfa) flows, smart-house solutions have a great potential in reduction of not only the primary resource consumptions at a household, they also could minimize secondary, associated resource consumptions occurring within operation and maintenance activities related to resource capacity and in the presence of temporal fluctuations in the consumption. clean-air flow seems to be the most neglected resource flow in this context. unfortunately, many of significant longterm health-related impacts are not yet fully linked to the air flow mainly because of lack of monitoring and measurements of the quality and quantity at both inside and outside of a house. although deployment of sensing devices and continuous [discrete] monitoring of them have been a trend in implementation of generic smart house solutions, there are several concerns that could delay or jeopardize massive adoption to these solutions: 1. explosion in the number of vendors. although at the beginning the number of vendors seems to be limited to those exploring this field, it is expected to have an exponential growth in their number when this trend becomes mainstream. even branding seems to be of less impact in containing this growth. full-ip approaches to accessing sensors and ‘actuators’ could make it feasible to operate in such a competitive ecosystem of providers, but there would be a great concern regarding multi-tenancy and ‘fair’ operation at the passive smart-house gateways. 2. self-allowed intruders. although the sensing devices and potentially actuators are the core of a smart house solution, they could be still seen as intruders. even if we ignore the risk associated to the ‘push’ commands sent to actuators, the information carried outward via the ‘pull’ events could pose a potential privacy risk. a potential solution to this chaotic situation could be built on top of an ict agent(s) that serve on the house side controlling all data outflows and also command inflows. the generic nature of such an agent, which we call a federal smarthouse regulator, makes it highly compatible with open source and crowdbased requirements of the ict agents of service bonds as mentioned in the previous section. these federal regulators would govern every service bond created 9eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 the service-bond paradigm — potentials for sustainable, ict-enabled future reza farrahi moghaddam et al. figure 7. the schematic of a smart house solution with various (e)ict-enabled things governed by a federal smarthouse regulator as the (e)ict agent in the associated service bonds. note: pop stands for the point-of-presence. over a vendor’s sensor/actuator, and also may create their own service bonds with counterpart agents of the high-level providers, such as those of the [water, electricity, data] utilities,5 in order to reduce the resource consumption while providing a high-quality experience to the residence along with generating ‘value’ for them. to be precise, a utility that would like to tap on sensors of households to manage its resources should naturally also allow the household agents to tap on their data in order to generate value for the households. in other words, if a utility is differing from best practices for any reason and imposing the related overhead costs to the households, the household agents should be able to retrieve the associated data and use it to prove ineligibility of such additional fees or to request a verifiable road-map toward transiting to the best practices. a typical schematic of a smart house solution governed by a proposed federal smarthouse regulator is shown in figure 7 [23]. the federal regulator is responsible to allocate fair amount of data resources, such as access bandwidth, to every service associated with a pull/push sensor/actuator, it also take care of optimal retrieval of data and information on the service bonds toward adding value (and possibly profit) for the residences. on the other end of every service bond, there is another ict agent that handles interests of a utility for example and also reduces 5the federal communications commission (fcc) has used title ii (sections 201, 202, and 208) of the communications act [18], along section 706 of the telecommunications act [19] to provide legal foundation for their open internet and net neutrality rulings [20– 22]. their possible liability related to accessing household premises. although the intelligence of every agent is recommended to stay within the actual premises of their associated entity, many of the resources that the agents may require, such as data storage or specialized analytics, could be hosted on high-grade cloud-oriented data and compute centers, such as that of green sustainable telco-grade clouds (gstcs). greater details related to this use-case could be found in [23]. 5.2. use case b: electricity utilities and information bonds in the case of utilities, especially electricity utilities, the application of smart meters is becoming more and more relevant in terms of improving the ‘visibility’ of the grid and therefore increasing operations’ performance, quality of service, and return. in addition, smart meters provide dependable means to impose behavioral changes in the consumption patterns in both forms of incentives and penalties toward enabling tools such as demand shaping or demand response [24–28]. although is no direct risk related to the data generated by the smart meters and collected by the utilities, there is an imbalance in the data/information flow between the utility and the electricity consumers. in other words, the consumption data of a household, for example, is provided as ‘spare’ data to the utility without any explicit return. although it could be argued that the real-time data provided by the smart meters would implicitly improve the quality of service and experience of the consumer, there are many other ways that the utility could commit to a ‘return’ in 10eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 order to form a ‘bond’ with their consumer. in figure 8, three possible options to form a service-bond are illustrated. in figure 8(b), the simplest case is shown in which the utility return an exact copy of the data generated by the smart meter to the consumer. the actual benefit from such option highly depends on the ‘readiness’ of the household (probably the smart solution used) in harvesting the provided raw data and using it toward diagnosis or improvement of the house operation. a side effect of this form of bonding is that the data could be collected and used against the consumer by a third party (probably from its reentry point to the house). the second option, shown in figure 8(c), is a more complex configuration in which the utility allows the consumer to ‘decide’ what part (or form) of the raw data generated by the smart meter could be transmitted to the utility. this option is in particular interesting with respect to imposing the ‘granularity’ level of data. a high resolution, high frequency sampling metering could provide means to guess the state of sub-components (for example, appliances) of a house [29]. this information may be of less importance to the utility and at the same time may violate the consumer’s rights. with adding proper filters, which could be implemented within the smart meter’s box itself, the granularity could be dynamically adjusted without requiring hardware upgrades. we are particularity interested in figure 8(d) case where there is an actual explicit bonding at the level of data/information exchange. the smart meter as usual transmits the sampled consumption data to the utility (while complying to the granularity level agreed among parties), and at the same time the utility provides its grid performance in real-time (for example, hourly) to the consumer. the performance indicator could be greenness factor (or equivalently, emissions factor) of the grid, price, or even more complex information such as the actual grid mix. to show how the exchange of information and data via this bond would benefit the consumer, we consider a specific case of a household in the province of ontario. in this case, the performance of the grid is published publicly on the associated website (http://www.ieso. ca/pages/power-data/supply.aspx). we assume a case of an annual cycle (specifically, year 2015). for the household consumption profile, we use the average profile provided in [30], along with a seasonal variation to account for the winter season. the whole yearly profile of a typical household is shown in figure 9(a). the emissions factor of the grid calculated from the real-time (hourly) grid mix provided by the utility is also shown in figure 9(b). by combining these data, we can calculate a 657.52 kgco2e emissions associated to the electricity consumption of the household. now let us assume that the consumer decides to use the data provided via the bond to reduce their emissions footprint by displacing their consumption behavior. further, let us assume that the consumer has a limited capability that allows them to displace consumptions only within 24-hour intervals. under these assumptions, an optimal ‘engineered’ behavior could be found, and an example is shown in figure 9(c). interestingly, the new behavior enables the consumer to reduce their emissions footprint to 595.65 kgco2e which is equivalent to almost 10% reduction in the footprint even without reducing the consumption itself. the potentials of service-bond use cases is much more interesting especially with respect to reducing the consumption itself, and they will be considered in details in the future work. 6. conclusion a new paradigm to service interactions has been introduced. first, the traditional approaches to services and their implementations have been considered and then analyzed in terms of their limitations and disadvantages. then, the new paradigm called the service-bond paradigm has been presented in its naive form of implementation. later, generalizations to the proposed service-bond paradigm have been considered and framed as the basis of service chemistry toward moving beyond binary service interaction, chaining, and orchestration (sico). a time-modulated implementation of the proposed paradigm has been then introduced in order to reduce risks associated to the naive form and its full-trust requirements. next, practical implementation of the service-bond paradigm using the ict-enabled agents has been proposed with possible zero or marginal cost overhead to the entities involved in a sico. finally, a use case related to the smart-house solutions has been discussed in which the federal smarthouse regulators are the key ict agents representing households in the service-bond interactions with other entities such as utilities in a fully bilateral and transparent form of bonding. the models and implementations introduced here to represent and model service interactions and service bonds will be analyzed and studied in the future work using full-size use cases such as that of the smart-house solutions. acknowledgement. the authors thank the nserc of canada for their financial support under grant crdpj 424371-11 and under the canada research chair in sustainable smart ecocloud (nserc-950-229052), and also the mitacs of canada. references [1] braidy, n.g. 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[16] 3gpp (2015) ip multimedia subsystem (ims). stage 2 (3gpp ts 23.228/etsi ts 123 228). technical 12eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 (a) (b) (c) figure 9. the use case of bonding between the utility and a consumer with the data from the ontario’s grid. a) a typical household hourly electricity consumption. b) the hourly emissions factor of the grid calculated using the provided hourly grid mix and the lca-oriented emissions factors of various energy technologies. c) an improved electricity consumption pattern adopted by the consumer using the provided data in (b). a reduction of 10% in the emissions footprint could be achieved by the improved consumption behavior. specification version 12.8.0, release 12, etsi, sophia antipolis, alpes-côte d’azur, france. [17] farrahi moghaddam, r., , lemieux, y. and cheriet, m. 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[20] federal communications commission (2015) protecting and promoting the open internet (gn docket no. 14-28): report and order on remand, declaratory 13eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 the service-bond paradigm — potentials for sustainable, ict-enabled future reza farrahi moghaddam et al. ruling, and order. tech. rep. fcc 15-24, fcc, washington, dc, usa. url https://apps.fcc.gov/ edocs_public/attachmatch/fcc-15-24a1.pdf. [21] federal communications commission (2015), fcc adopts strong, sustainable rules to protect the open internet, news. url https://apps.fcc.gov/edocs_ public/attachmatch/doc-332260a1.pdf. [22] federal communications commission (2014) protecting and promoting the open internet (gn docket no. 14-28): notice of proposed rulemaking. tech. rep. fcc 14-61, fcc, washington, dc, usa. url https://apps.fcc.gov/edocs_public/attachmatch/ fcc-14-61a1.pdf. 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(filed on aug 9, 2010), context-aware smart home energy manager. [28] irwin, g., banerjee, n., hurst, a. and rollins, s. (2015) contextual insights into home energy relationships. in percom’15: 305–310. doi:10.1109/percomw.2015.7134053. [29] jonetzko, r., detzler, m., gollmer, k.u., guldner, a., huber, m., michels, r., naumann, s. et al. (2015) development of a real-time smart meter for nonintrusive load monitoring and appliance disaggregation. in enviroinfo’15 & ict4s’15 (copenhagen, hovedstaden, denmark): 47–52. [30] pombeiro, h., pina, a. and silva, c. (2012) analyzing residential electricity consumption patterns based on consumer’s segmentation. in it4energy’12 (lisbon, lisbon, portugal): 29–38. [31] niven, d., rubenfeld, g., kramer, a. and stelfox, h. (2015) effect of published scientific evidence on glycemic control in adult intensive care units. jama internal medicine 175: 801–809. doi:10.1001/jamainternmed.2015.0157. [32] mahmoodpoor, a., sanaie, s. and golzari, s.e. (2015) slow deadoptation of a strategy: was tight glycemic control truly impractical? advances in bioscience and clinical medicine 3(3): pp 2. doi:10.7575/aiac.abcmed.15.03.03.01. [33] federal communications commission (2015) 2015 broadband progress report and notice of inquiry on immediate action to accelerate deployment. tech. rep. fcc 15-10, fcc, washington, dc, usa. url https://apps.fcc.gov/edocs_public/attachmatch/ fcc-15-10a1.pdf. [34] donoho, d.l. (2006) for most large underdetermined systems of linear equations the minimal l1-norm solution is also the sparsest solution. comm. pure appl. math. 59: 797–829. doi:10.1002/cpa.20132. appendix1. service vs. agreement from the service cycle presented in section 2, it can be observed that the key elements of the operations are how the requester r is ‘triggered’ to request a service and how ‘satisfied’ they felt of what that has been provided. in other words, in the current paradigm, it does not matter how much ‘wealth’, ‘added-value’ or ‘improvement’ r has been absorbed by the end of the cycle. an unmanaged practice of the first aspect, i.e., triggering an entity to request a service, can result in pushing (for example, using blind advertisement) for the services that would not bring any benefit to r while degrading the power of a true advertisement in enabling entities to receive added-value through binding them to proper services and providers. in an extreme case, it could be said that even science by-itself could be considered as a form of unbiased, fact-based advertisement for better good of [all] entities (ranging from individuals, to businesses, to societies, to natures, among others) using the best-effort approaches. the best-effort aspect means that the scientific findings should not be considered as facts but merely latest ‘best recommendations’ [31, 32]. the second aspect, i.e., the agreement and contract, could also bring much more damage than benefit in an unmanaged form. in the worst case, a broker or a provider has the capability to arrange6 terms of service and sla/slos at the beginning of a cycle that could be justified at the end of the cycle even in the case a service different from what that the requester had in mind was provided.7 appendix2. a baseline model for service paradigm although developing a model for the current service paradigm would be a great challenge by itself because of the the associated complexities, here a baseline phenomenabased model is initiated to cover some of its shortfalls. these 6probably using their misadvantage of having access to bigger data (along various dimensions of time interval, real-time, entities, and location, among others) and analytics. 7in the context of this paper, we avoid using the term quality of service in that sense that we consider a high-quality service and a lowquality service two ‘different’ services. for example, in the context of the broadband internet access, a 1 mbps access service and a 10 mbps access service should be considered as two different services. it is acceptable that during the transition period of introducing a new meta-service, such as the internet service, and because of unsettled terminologies and lack of public awareness of the service, services are informally referred to with some common titles. however, it is important to gradually categorize them in terms of what they actually provide. 14eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 phenomena are especially essential in increase of withoutany-purpose service requests in various forms of request propagation among entities. in the next section, we will introduce an alternative paradigm to address and to attenuate these phenomena. 1. horizontal avalanche. the current practices in triggering entities8 to request a service, and their consequential mistrust of entities in the brokers and providers, could have lead to development of some sort of crowd-based trust among the entities that reside at the same ‘level’9 of a service stack. a direct associated phenomenon to this connectivity among the entities would be [exponential] expansion of a service trigger among the neighboring nodes (entities) on the same level. we call this phenomenon horizontal avalanche. although increase in service request is usually seen positive from the providers perspective, the phenomenon could have unwanted and unsustainable consequences in terms of i) exponential increase in consumption of resources, ii) servicewithout-benefit, and iii) blocking other beneficial services by filling up available ‘time’ slots of entities. 2. vertical avalanche. the southwise nature of the current service paradigm, in terms of the service stack, would also result in another phenomenon that involves triggering in the nodes (entities) placed at levels below to provide something that is more than what is requested by the entities in a level above them. we call this phenomenon vertical avalanche. although providing more seems to be a benefit to the requester, the actual service received by a requester in a non-immediate higher level would not reflect the service provided to the immediate-level entity. in other words, the extra service provided could be simply abandoned. vertical avalanches are possible in practice because the revenue received by the entity at the lower levels could be profitable to them especially because of presence of some disparity factors such as location, ‘attached’ economies, and absence of environmentalimpact regulations, among others. therefore, managing and containing vertical avalanches would require imposing resource-consumption regulations, otherwise they could simply lead to exponential increase in resource consumption without providing equivalent benefits. 8we may use both terms, entity and node, to refer to an actor in a service operation. an entity could be a service requester, a service provider, or any other actor. the terms node will be used equivalently but more in those contexts that are associated to relations and connections among entities in terms of factors that may not be related to the actual service operation. 9in this paper, we use both ‘level’ and ‘layer’ in describing a service stack in terms of north-south relations among entities. to be more precise, levels are more stable devisions that are not influenced by the technologies used to provide a service, while layers are more thin and flexible devisions. in this sense, a service level could be composed by one or more service layers. it is worth mentioning that these terms should not be mistaken with the level of service that would indicate the associated quality of a service providing operation. 3. self-driven avalanche. in this form of avalanche, a typical entity would request more than what is needed because of the presence of uncertainty in that sense they are not sure if what that is going to be provided would satisfy their needs that triggered the request at the beginning. the phenomenon, called the self-driven avalanche, is the direct consequence of contract-based vision of the current service paradigm. when this phenomenon is combined with the horizontal avalanche, the combination could result in uncontainable growth in the number of service request and also in the ‘size’ of services being requests. the mathematical formulation of the phenomena and the model will be presented in another work. however, here we can simply conclude that the current one-way forms of service interactions is by itself uncontainable and therefore a risk factor to any planned sustainable state in the future. appendix3. challenge of the ‘purpose’ in non-serving states a consequence of the only-southwise nature of current service paradigm is a lack of visibility and capability to express for the entities that serve in the lower levels of the stack. in other words, many nodes or entities at these levels become servingdependent, i.e., they would not practically exist anymore if they do not deliver their services. this phenomenon is more serious for those entities that have some other southwise ‘dependent’ nodes attached to them. the asynchronous, heterogeneous nature of interactions among these dependent nodes could create a characteristics that we call service inertia. if a serving node has a considerable service inertia, they could not ‘instantly’ transit to a non-serving state. in other words, that node/entity is forced to continue its services even if the associated interactions and transactions are not profitable. a direct consequence of the inertia constraint would be servingwithout-profit or no-profit-service situations in which a node continue to provide service despite knowing it would not make any profit. this would break the basic assumption of the current service paradigm that the fee-for-service controls would keep the service ecosystem bounded and contained even in a free and unregulated mode. appendix4. service representationsand distances before continuing with the rest of the paper, we would like to provide an example of how a service could be represented and how the distances between an advertised service and the corresponding delivered service could be estimated: 1. service representation: coded vs. decoded. to be more specific, we consider a popular service related to households, i.e., the broadband internet access service of 25 mbps/3 mbps downlink/uplink (ds/us) bandwidth.10 let us denote this service as a = ( ds = 10as adopted by the federal communications commission (fcc) for fixed access; for mobile access a bandwidth of 10 mbps/768 kbps is required [33]. 15eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 the service-bond paradigm — potentials for sustainable, ict-enabled future reza farrahi moghaddam et al. 25mbps,us = 3mbps ) . the tuple ( ds = · · · ,us = · · · ) is the coded ‘representation’ of the service a. we consider three decoded representation types for this service: (a) raw representation. in this representation, the service a is represented by a series of timestamped tuples of the same format of the coded representation but at a ‘continuous’ time series: araw = {( dstω ,ustω )} ω , (appendix 4.1) whereω is a continuous index of time. in practice, a discrete but highly dense time index could be used instead of the continuous index. it is assumed that some daemons (agents) are present that could measure the ds and us capacities (inuse or not-used) at every time interval. (b) oversampled representation. it is similar to the discrete version of the raw representation but with a longer time period: ao = {( dst(o,i) ,ust(o,i) )}n =1 = {( dst(o,1) ,ust(o,1) ) , ( dst(o,2) ,ust(o,2) ) , · · · } . (appendix 4.2) however, the time period between samples is short enough that any decrease in the value of the time period does not result in a ‘significant’ change in the distance to the raw representation. the distances are later on discussed in details below. (c) undersampled representation. in contrast to the oversampled representation, the undersampled representation requires that the time period of sampling intervals to be long enough to induce a significant distance with respect to the raw representation. au = {( dst(u,j) ,ust(u,j) )}m j=1 = {( dst(u,1) ,ust(u,1) ) , ( dst(u,2) ,ust(u,2) ) , · · · } . (appendix 4.3) it is worth mentioning that we do not assume a sampling with a fixed time period. instead, similar to what has been practiced in action, the average time period or more generally its distribution would be considered. 2. service distance. as mentioned in footnote ??, various service distances could be considered or required by different parties involved in a service interaction. here, a few examples along with the three decoded representations are provided: (a) requester-blind distance (rbd). this distance is from the requester r perspective along with a blind enforcement of the service a. the steps to calculate this distance is as follows: i. generate an oversampled decoded representation of the delivered service using a ‘constant’ and fixed time period: ao = {( dst(o,i) ,ust(o,i) )}n i=1 (appendix 4.4) ii. generate a reference decoded representation of the advertised service using the time intervals of ao along with the advertised values of the coded representation. we call this representation ar : ar = {( ds = 25mbps,us = 3mbps ) , ( ds = 25mbps,us = 3mbps ) , · · · }n 1 . (appendix 4.5) it is possible that some services have variable slos along time. however, in this example we assumed that the advertised service is a constant function of time. iii. calculate the ‘mean,’ l1,11 one-sided distance between ao and ar : drbd (ao, ar ) = 1 m m∑ i=1 u (( 25mbps, 3mbps ) − ( dst(o,i) ,ust(o,i) )) (appendix 4.6) it is worth mentioning that the estimated distance is still a ‘tuple.’ here, the function u (·) denotes the unit step function. the unit step function enforces the one-sided feature of the distance, i.e., preventing cancellation of those instances with bandwidth less than that advertised with those instances that have an extra bandwidth. also, the rbd norm function can be easily defined based on its associated distance function: ∥∥∥∆a ∥∥∥ rbd = 1 m m∑ i=1 u ( ∆ati ) (appendix 4.7) (b) requester-experience distance (rxd). the main difference between the experience-based drxd distance and the previously-defined blind drbd distance is the selection of time intervals for sampling. to be specific, for drxd, we use an undersampled representation with a condition that it is still oversampled with respect to the requester’s time intervals of ‘interest.’ considering the fact that a requester has usually a nonuniform distribution of time intervals of interest, an associated time series of the rxd would probably be a series with a piecewise-constant-time-period: { t(x,i) }m ′ i=1 . 11an l1 discrete distance considers absolute difference between individual values of two series in contrast to an l2 distance that considers the squared difference values [34]. 16eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 the associated service representation is denoted ax . the definition of distance would be straightforward: drxd ( ax , ar ) = 1 m′ m ′∑ i=1 u (( 25mbps, 3mbps ) − ( dst(x,i) ,ust(x,i) )) . (appendix 4.8) the netflix’s isp12 speed index13 could be mentioned as an example that resembles some features of an rxd implementation: for each isp, the subscription video-on-demand (svod) provider calculates the monthly-mean of a 3hour daily-mean of the achieved streaming bandwidth across all theirs subscribers attached to a particular isp. the three hours used to calculate the mean of a particular day is chosen to be prime time, i.e., those three hours associated with the maximum netflix streaming per that isp on that day.14 the selection of peak hours of the netflix prime time puts this index within the scope of an rxd distance. it is also worth mentioning that we only considered the ‘time’ dimension in this work for the purpose of simplicity. a straightforward generalization would be to add the ‘spatial’15 dimension, which is more relevant to wireless services, to the service representations and distances. for example, the rxd would be then generalized to: drxd ( ax , ar ) = 1 m′′ m ′′∑ k=1 u (( 25mbps, 3mbps ) − ( ds(t(x,k),~x(x,k)),us(t(x,k),~x(x,k)) )) . (appendix 4.9) here, the sampling has been carried out in the combined space of time-location in the form of (t(x,k), ~x(x,k)), where the location at a sampling index k is represented by ~x(x,k). 12as will be elaborated in footnote 7, internet access service would not be any more an appropriate reference for the class of services that it represents. in particular, broadband internet access service or in short broadband service should be separated from the other internet services (http://www.broadbandmap.gov/ internet-service-providers/). although it might be argued that the internet service has evolved in the broadband service, providing other most-probably-low-bandwidth internet services is important especially in the case of sensory devices in the context of smart house among other applications. 13global: http://ispspeedindex.netflix.com/ country-averages, usa: http://ispspeedindex.netflix.com/usa, and canada: http://ispspeedindex.netflix.com/canada. 14http://ispspeedindex.netflix.com/ how-we-calculate-rankings 15or more generally location considering the fact that the physicalspatial location is gradually fading in the rise of virtual or relative locations. (c) provider-blind distance (pbd). from the perspective of a provider, in a selfish mode, a sampling time series is preferred if it covers all time intervals especially those that are associated to ‘no’ experience, i.e., the service is not in use during those time intervals. in this sense, the pbd is highly similar to the rbd. therefore, we consider these two distances the same: dpbd (ao, ar ) = drbd (ao, ar ).16 (d) provider-illusion distance (pid). the final distance we would like to discuss here is a distance that could create an ‘illusion’ that the service a has been delivered. one approach to arrive to such a illusive distance is to use an undersampled time series that its frequency is so low that it ‘skips’ most of time intervals that are associated to the in-use phases of the service (especially when multiple requesters share the same in-use time interval, such as the case of prime time in the evenings for video and tv watching). let us denote such a time series and its associated service representation by (t(i,j))j and ai , respectively. the definition of the distance would be similar to its precedings: dpid ( ai , ar ) = 1 m′′′ m ′′′∑ i=1 u (( 25mbps, 3mbps ) − ( dst(i,j) ,ust(i,j) )) , (appendix 4.10) where m′′′ << n . the main difference between the pid and the other distances is that its value would be most probably zero or negligible: ∃m′′′ s.t. dpid ( ai , ar ) ' 0. the question of which one of these distances should be used in audition/verification of a service delivered or being delivered is more a matter of settlement between the requesters and providers at large. the rxd seems to be a good balance between interests of different parties involved. however, it should be clear to all parties that this settlement should be carried out during the negotiation and establishment of a service. also, some of the distances, such as dpid, seem to be inapplicable in every circumstances, and therefore they could be simply removed from the possible options of any negotiation. 16in a very detailed comparison, the pbd and rbd could be differentiated: it could be argued that the time period of a pbd should be higher than that of a naive rbd; this would lead to masking the highly-short-living no-service events. this masking seems to be preferred from a provider’s perspective. high jitter and actual disconnect could be mentioned as a few possible causes of short-living no-service time intervals. usually, the managing protocols ensure continuous providing of service in longer time intervals in presence of short-living no-service events. 17eai european alliance for innovation eai endorsed transactions on smart cities 07 2016 | volume 1 | issue 1 | e1 the service-bond paradigm — potentials for sustainable, ict-enabled future evolving mixed societies: a one-dimensional modelling approach michael bodi ∗ artificial life lab of the department of zoology karl-franzens university graz, michael.bodi@uni-graz.at martina szopek artificial life lab of the department of zoology karl-franzens university graz, martina.szopek@unigraz.at payam zahadat artificial life lab of the department of zoology karl-franzens university graz, payam.zahadat@unigraz.at thomas schmickl artificial life lab of the department of zoology karl-franzens university graz, thomas.schmickl@unigraz.at abstract natural self-organising collective systems like social insect societies are often used as a source of inspiration for robotic applications. in return, developing such self-organising robotic systems can lead to a better understanding of natural collective systems. by unifying the communication channels of the natural and artificial agents these two collective systems can be merged into one bio-hybrid society. in this work we demonstrate the feasibility of such a bio-hybid society by introducing a simple one-dimensional model. a set of patches forms a one-dimensional arena, each patch represents a stationary robot, which is controlled by an ahhs (artificial homeostatic hormone system) control software. the stationary robots are able to produce different types of environmental stimuli. simulated bees react diversely to the different stimuli types. an evolutionary computation algorithm changes the properties of the ahhs and defines the interactions between the robots and their properties of stimuli emission. the task is an aggregation of simulated bees at a predefined aggregation spot. we demonstrate that an evolved ahhs is a very feasible tool for controlling these stationary robots. furthermore we show that an ahhs even works robustly in different setups and dynamic environments even though the controller was not specially evolved for these purposes. ∗corresponding author . categories and subject descriptors a.1.3 [general and reference]: document types—general conference proceedings; f.5.9.2 [theory of computation]: design and analysis of algorithms—distributed algorithms, self-organization; k.3.7.1 [computing methodologies]: artificial intelligence—distributed artificial intelligence, multi-agent systems; k.3.7.3 [computing methodologies]: artificial intelligence—distributed artificial intelligence, mobile agents; k.7.1.2 [computing methodologies]: distributed computing methodologies—distributed algorithms, self-organization general terms algorithms keywords mixed-societies, bio-hybrid systems, evolutionary computation, multi agent systems, swarm robotics 1. introduction natural self-organising collective systems like social insect societies are often used as a source of inspiration for robotic applications. in return, developing such self-organising robotic systems can lead to a better understanding of the natural collective systems. by unifying the communication channels of the natural and artificial agents these two collective systems can be merged into one bio-hybrid society. biology knows many examples of collective behaviour on a wide range of organisational complexity, from organisms as simple as slime moulds (nakagaki, 2001) or bacteria (camazine et al., 2001) via insects and fish to highly sophisticated representatives of birds and mammals. the most intriguing example for the efficiency of collective behaviour is found in social insects. for example in ants, detailed research has been conducted on phenomena like chain formation (lioni et al., 2001) and bridge formation (deneubourg et al., 1990). bict 2015, december 03-05, new york city, united states copyright © 2016 icst doi 10.4108/eai.3-12-2015.2262514 one of the most studied social insects is the european honeybee apis mellifera. honeybees are not only crucial for agricultural and economical purposes (e.g. pollination), but have also successfully found their way into engineering approaches. for example, honeybees inspired the development of bio-inspired algorithms for controlling autonomous swarm robots (schmickl et al., 2008; bodi et al., 2012, 2011). robotic devices also become more important in biological studies. the simplest form for such robotic applications would be a sensor network for monitoring animals (zacepins et al., 2011). a more ambitious approach is the usage of robotic agents in animal societies for the purpose of influencing the animal behaviour (halloy et al., 2007). the ongoing eu-project assisibf presents a new approach for closing the loop of interaction between natural and artificial agents for the purpose of forming a bio-hybrid mixed society consisting of animals (honeybees apis mellifera) and stationary autonomous robots called casus (combined actuator sensor units)(schmickl et al., 2013b,a). casus are equipped with several sensors (e.g., temperature sensors, proximity sensors) (salem and schmickl, 2014) and actuators (e.g., heating devices, vibration devices). this system should be able to adapt without a priori knowledge of the open system as we are using evolutionary computation for adapting the interface between the natural and the artificial society with the goal to produce common collective behaviours. for closing the loop of interaction between bees and casus, it is first necessary to find a set of different stimuli, to which bees show different behavioural responses. it is already known, that honeybees are collectively attracted to temperature (szopek et al., 2013). finding other appropriate stimuli types is part of the research in the assisibf project. figure 1 shows a preliminary experiment using real honeybees and casu prototypes. in this preliminary experiment the casus use temperature to pull the bees from the left to the right side of an experimentation arena. the temperature settings were controlled solely by the experimenter with no autonomy of the casus or interaction between the casus and the honeybees. the approach of the assisibf project is to form such a bio-hybrid society of bees and casus by using evolutionary computation. these evolved controllers should learn to use the different stimuli to alter the behaviour of the bee collective (e.g., aggregation, separation, path following) therefore we decided to test in simulation, whether or not, the reaction-diffusion controlled artificial homeostatic hormone system (ahhs) controller is the right tool for this task. the aim of this work is to evolve a controller for such a bio-hybrid system consisting of two types of autonomous agents: predictable but unprogrammable agents (simulated honeybees) and programmable and evolvable agents (simulated casus). we answer the following questions: (i) is it possible to evolve a controller to redirect reactive agents by the use of different types of environmental stimuli? (ii) is an ahhs controller, evolved for a specific setup, able to perform tasks in a more general environment? to answer these questions, we developed a one-dimensional proof of concept model of a bio-hybrid system in netlogo (wilensky, 1999). 2. methods a set of 101 patches, located in a straight line, represents a one-dimensional experimentation arena (figure. 2). each patch can be considered as one casu (combined actuafigure 1: snapshots of a preliminary experiment with real casus and a group of honeybees. (a) the left casu was heated up to 36 ◦c (preferred temperature of young bees). after the bees aggregated there, the left casu was cooled down and the right casu was heated up to 36 ◦c. the majority of the group followed the optimum, but some bees remained at the left casu (b). tor sensor unit) which is able to generate three different stimuli types via implemented actuators. the casus are controlled by an ahhs control software which controls the ’behaviour’ of the casus by perceiving concentrations of virtual hormones and reacting to them according to a set of rules. these rules can then be changed by an evolutionary computation algorithm. 2.1 the ahhs control software ahhs (artificial homeostatic hormone system) (schmickl and crailsheim, 2009; schmickl et al., 2011) is a reactiondiffusion-based system inspired by the turing process (turing, 1952) which describes processes of natural pattern formation and growth. ahhs has already been successfully implemented in robotic applications (stradner et al., 2009; schmickl et al., 2010; hamann et al., 2010) and has been investigated in terms of pattern formation and diversity generation capabilities (zahadat et al., 2013). an ahhs is defined by a set of artificial hormones and a set of rules. the rules define how sensory inputs and hormone concentrations participate in making changes in hormone concentrations and outputs of the system (see figure 3). both, hormones and rules, may be changed by an evolutionary process. in our one-dimensional model we use 8 different hormones h which can have values between 0 and 255. h1 forms a prime gradient from left to right, meaning that on the left side h1 has a value of 255 and on the right side a value of 0. this gradient feeds spacial information into the system. h2 has a constant value of 127 across all of the arena with exception of patches -5 to 5. within this area h2 generates ‘white noise’ (figure 4), meaning that every patch from -5 figure 2: screenshots of the one-dimensional experimentation arena. yellow dots represent honeybees. the green area represents the target for the bees. the purple area represents a mixture of two environmental stimuli: red = temperature, blue = light. this screenshot shows the different behaviours of bees and casus for an unevolved (random) (a) and an evolved (b) genome. figure 3: graphical representation of the ahhs and the interactions between hormones inside an ahhs, the interaction between two ahhs controllers and the interactions between ahhs and casus. h1 h4 represent different artificial hormones and their interactions. h4 controls the properties of the casu (located above h4). to 5 produces a random hormone value in every time step. this area of white noise marks the aggregation spot for the honeybees. the hormones h3 h5 are used to control the actuators within the casus, h3 controls an attractive stimulus a, h4 controls a repelling stimulus b and h5 controls a stumulus c which servers a stopping signal. h6 h8 serve as ‘free hormones’ and are used by the ahhs for computing. 2.2 stimuli and honeybee model each patch contains 3 actuators which act as the sources of 3 different types of stimuli. these stimuli types are further called type a, b, and c and are different in terms of their physical properties and the reaction of the simulated bees to them (see table 1). stimulus a serves as an attractive signal (e.g., temperature and chemicals) and stimulus b serves as a repulsive signal (e.g., light, airflow). this means that a bee tends to move to a neighbouring patch if the intensity of stimulus a is higher or the intensity of stimulus type b is lower in the neighbouring cell. stimulus c serves as a stopping signal (e.g., vibration), meaning that if the intensity of the stimulus is above a certain threshold value the bee stops on the cell, ignoring the attractive or repulsive stimulus. it’s noteworthy, that the assumed reactions of the simulated bees to the mentioned stimuli in this model are more or less arbitrary. these reactions do only have the purpose to test the suitability of the described algorithms. it is part of the assisibf project to determine the behavioural response of the honeybees on different environmental stimuli in laboratory experiments. as already mentioned, the casus are able to generate 3 different types of stimuli and the simulated bees react differently to each type of stimulus. a bee moves to a neighbouring patch, called newpatch, based on following equation: figure 4: hormone levels of the prime gradients used in our model. the x-axis represents the space of the onedimensional experimentation arena. hormone h1 generates a gradient throughout the arena. hormone h2 is used as a marker for the target area by producing white noise at this location. attri = (ai −acurr) + (bcurr −bi), (1) newpatch = { arg maxi attri, if attri > 0 and ccurr < th curr, otherwise , (2) whereby curr is the current patch and ai, bi, and ci are the intensities of the stimuli a, b, and c in patch i. in this experiment we use a simplified simulation of temperature, vibration and light as examples of stimuli of types a, b, and c. the intensities of the stimuli and the increase value of the stimuli in each time-step are both limited between 0 and 1. the threshold value of the vibration is set to 0.1. the values of all parameters used in this simulation can be found in table 1. in this model the bees do not have any physical properties, which means that the bees are able to move through each other and can stack up on a single patch. we made this decision because real honeybees can form very dense aggregations and sit on top of each other. it’s also noteworthy, that the parameters of the stimuli do not precisely correspond to reality and the effects of these stimuli on the bees are assumed to be linear for simplification of the simulation, since the purpose of this simulation is to test the before mentioned algorithms. table 1: characteristics of the stimuli used in the models. stimulus a (temperature) b (light) c (vibration) effect attractive repellent stop-signal diffusion rate 0,2 0 0,01 decay rate 0,1 1 0,9 instantly reachable no yes no blockable by bee no yes no figure 5: graphical representation of the feedbacks within our model. 2.3 experimentation 2.3.1 experiment i: the goal of this experiment is to evolve an ahhs controller that leads the bees to form an aggregation at a predefined target area which is marked by white noise of hormone h2. at the beginning, 11 bees are placed equally distributed within the arena. these bees move around in the arena according to their reaction to the presented stimuli. the genetic start population used in these evolutionary runs consist of 30 random genomes. for evolving the ahhs controller, a wolfpack-inspired evolutionary algorithm is used (zahadat and schmickl, 2014). this algorithm uses overlapping generations and a fixed population size representing a limited resource (e.g. food). the offspring is evaluated and ranked hierarchically according to their fitness. an evaluated offspring removes another individual with equal or lower fitness from the population. this way the population stays dynamic. the fitness function in the presented model was defined as fitness = n2 t + ∑( x− dt 4 ) , (3) x = { 2dmax if dt = 0 dmax otherwise , (4) where nt is the number of bees in the target area, dt is the distance of a bee to the centre of the target area and dmax represents the maximum possible distance to the centre of the target area. this means that bees which aggregate in the exact centre of the aggregation spot gain more fitness, than bees which locate themselves merely within the aggregation area. the evolutionary runs were repeated 7 times for 151 time steps each. 2.3.2 experiment ii: after the evolutionary runs, we picked the genome with the highest fitness and tested it in terms of robustness and generality. in this experiment we varied the number of bees in the arena and observed the number of aggregated bees in the target zone. the tested groupsizes were 2, 5, 7, 11, 15 and 20 bees. the experiments were repeated 24 times. 2.3.3 experiment iii: in this experiment we tested the ability of the system to redirect the bees in a dynamic environment. therefore we started with 11 randomly distributed bees and the aggregation spot placed off-centre. after 150 time steps we changed the position of the aggregation spot. in one setup the aggregation spot jumped abruptly (figure 9a and 9b), in another setup the aggregation spot moved continuously to its new position (figure 9c and 9d). we monitored the number of aggregated bees after 350 time steps. the tested gap widths between the relocated aggregation spots were in both setups 11, 21, 27, 29 and 31 patches. the experiments were repeated 24 times. 3. results 3.1 experiment i: the evolutionary computation algorithm was tested with 11 equally distributed bees. their task is to aggregate in the target zone located in centre of the arena, marked by white noise of hormone h2. the system started with random genomes. as it is shown in figure 6, the fitness rises quickly. after the first evaluation the median fitness is 64 with a maximum fitness of 124,5. after 500 evaluations the median fitness already reaches 357,75 and the maximum fitness reaches the possible maximum fitness of 396. after 1500 evaluations the highest median fitness is reached with 383,25 and all but one genomes are capable of positioning the bees in the target-zone. after 2000 evaluations all genomes manage to relocate all bees in the target zone. 3.2 experiment ii: we tested the generality of the fittest genome by varying the number of bees. as we show in figure 7 the evolved genome can handle different groupsizes of bees very well. the evolved genome is able locate 100% of the bees in the target zone, independent of the tested groupsizes. 3.3 experiment iii: we tested the fittest genome in a dynamic environment. after 150 time steps we switched the position of the target zone and after 350 time steps we observed the number of bees in the new positioned target zone. as we show in figure 8 the evolved system is flexible enough to move 100% of the bees to the new target area when the gap between figure 6: results of experiment i: this figure shows the median fitness (with min, max, q1, q3) of the best genome of each evolutionary run (n = 7 repetitions). fmax represents the maximum possible fitness when all bees aggregate at the exact centre of the target area. fall inn represents the fitness when all bees aggregate in the target area (for details on the fitness function see equation 3 and 4). figure 7: results of experiment ii: mean fraction of bees (with stdev) aggregated in the target area. (n=24 repetitions/experiment) the targets is between 11 and 21 patches. once the gap exceeds 27 patches, the number of aggregated bees drops. but still, looking at the 27 patch gap, an average of 96.7% (stdev ±6,4) of the bees are aggregated in the target area. beyond that distance the aggregation drops rapidly. with gaps of 29 and 31 patches only 13.3% (stdev ±12) and 9,6% (stdev ±7,5) of the bees aggregate at the new target area, respectively. when the target is not moved abruptly but continuously, 100% of the bees could be pulled into the repositioned target area, independent of the gap width. 4. discussion 4.1 experiment i: as we have shown in figure 6 the median fitness is 357,75 after already 500 evaluations. at this point also the maximum fitness of 369 is reached by at least one genome. after 2000 evaluations all evolved genomes reach high fitness valfigure 8: results of experiment iii: mean fraction of bees (with stdev) aggregated in the target area after it has been moved to a new position. the solid line represent the results for abrupt target changes, the dashed line represents the result for continuous target changes. (n=24 repetitions/experiment) (a) gap of 10 patches (b) gap of 20 patches (c) gap of 10 patches (d) gap of 20 patches figure 9: example screenshots of experiment iii: spontaneously and continuously moving targets with a gap of 11 and 21 patches. the yellow lines indicate the trajectories of the bees. the green areas represent the target areas. the stimuli are represented by a mixture of red (temperature) and blue (light). ues (median fitness: 383,25) and are able to pull the bees into the target area. the steep increase of fitness and the good fitness performance strongly indicate that the combination of our evolutionary computation algorithm and the ahhs control software is a feasible tool for developing robot that can learn to manipulate animals. 4.2 experiment ii: as we have shown in figure 7 an evolved ahhs can use the casu’s actuators to lure the bees to a desired location. although the ahhs controller was evolved for groups of 11 bees it is able to fulfil this task also with other group sizes. we tested group sizes between two and 20 bees and in all cases 100% of the bees were directed to the target area. since we did not model any interaction between the bees, they can be considered as an indirect probe of the casu stimuli landcape. therefore this result is not really surprising. nevertheless this result serves us as a sanity check of our model. 4.3 experiment iii: when the target area changes its position abruptly, an evolved ahhs is capable to redirect the bees into the new target unless the gap between the two targets gets too big. as we have shown in figure 8, a gap of 11 to 21 patches can be vanquished without any losses to the aggregation properties. all bees can be redirected into the new target area. when the gap surpasses 20 patches, the number of bees located in the new target decreases. reaching a gap distance of 27 patches the number of redirected bees starts to decrease slightly, but still 97.7% of the bees could be redirected. at a gap distance of 29 patches and above the number of redirected bees decreases significantly. this can be explained by the properties of ahhs, as a hormone gradient triggers the actuators of the casus. since the evolution of ahhs was performed with a target area located in the centre of the arena, the hormone gradient does not spread far enough to overcome the gap. but when the target area does not jump abruptly to a new position, but continuously moves there, all bees can be redirected to the new target, no matter how far the gap between the target is. this can be explained by the fact, that not only the target moves continuously to the new position but also the hormone gradient does. this way the bees can easily be ‘pulled’ to a new location. 5. conclusion and future work in this work we answered the question if an evolved ahhs is suitable for controlling casus and luring simulated honeybees into a predefined target zone. therefore we generated a model of a one-dimensional experimentation arena containing casus, controlled by an ahhs controller. we showed that the combination of the wolfpack inspired evolutionary algorithm and ahhs is very promising tool for this tasks. we also answered the question if an ahhs controller, evolved for a specific setup, is able to perform tasks in a more general environment. once evolved, ahhs is capable of reacting to dynamical environmental changes. our results strongly indicate that an evolved ahhs is a flexible and reliable tool and a promising approach for controlling stationary autonomous robots to influence the behaviour of simulated honeybees. we are well aware that, because of the strong simplification of the bee model and the stimuli model, there’s a reality gap from our modelling approach to the real world setup. nevertheless, our results indicate that the observed algorithms are a feasible choice for the real world problem. in the future we plan to extend our model by implementing the actual physical properties of the stimuli used. once we have experimentation data of how honeybees react to the given stimuli types, this will also be implemented into our model. furthermore we will transfer the gained knowledge to the real world and test our approach on real casus with real honeybees. 6. acknowledgements this work was supported by: eu-ict ‘assisi|bf’, no. 601074. references bodi, m., thenius, r., schmickl, t., and crailsheim, k. 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(2014). wolfpack-inspired evolutionary algorithm and a reaction-diffusion-based controller are used for pattern formation. in proceedings of the 2014 conference on genetic and evolutionary computation, gecco ’14, pages 241–248, new york, ny, usa. acm. current practices and limitations in e health informatics 1 current practices and limitations in e health informatics umamaheshwari k.1, manju r.2,*, vivekitha v.2 and dinesh t. n.3 1associate professor, kebri dehar university, ethiopia 2assistant professor, department of bme, dr. n.g.p. institute of technology, coimbatore, india 3ug student, department of bme, dr. n.g.p. institute of technology, coimbatore, india abstract e-health is a field which as seen tremendous growth in the recent times especially after the covid-19 outbreak. e-health offers the potential to provide patients with high-quality care at a reasonable cost in the ease of their own homes. e-health has a wide range of application that includes rehabilitation, cognitive disorder, behavioural therapy, defence application and many more. e-health as a technology is changing tremendously and always been evolving to meet the demands of the current practices. but still, it has certain challenges in implementing such as ethical issues, patient contest etc. artificial intelligence framework capable of using non-consultancy, reinforcement learning, and all three. controlling the processes within the m-health application, choosing the best processes that can be used to alter the user's existing conditions, or selecting the best diagnosis-solution from an array of choices are all supported by intelligent optimization algorithms that can offer faster feedback. keywords: e-health, cognitive disorder, therapy, healthcare. received on 31 july 2022, accepted on 16 september 2022, published on 21 september 2022 copyright © 2022 umamaheshwari k. et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i3.2271 *corresponding author. email: manjufeb62@gmail.com 1. introduction e-health stands out the prospect of being an economical and effective technique of administering healthcare at a reasonable price to patients who would otherwise be underserved or excluded. the viability of e-health could be hampered if a number of ethical and legal issues are not resolved before it is implemented. changes to the patienthealthcare professional connection, the need for informed consent, and responsibility allocation are among the issues that are raised. in addition, their privacy issues, which affect both service providers and health informatics specialists’ positions. it has never been easier to see how digital technologies are transforming the healthcare industry. health care is moving further toward personalized and preventative paradigms by leveraging pervasive technologies that facilitate real-time self-care or monitoring with the introduction of wearable and other internet of things (iot) devices [2]. 2. challenges in health informatics 2.1. early detection of diseases early disease detection not only helps to lower the expense of medical care, but it also serves to save important lives of individuals. for instance, early cancer detection rather than disease discovery at a later stage may save a man's life. one critical challenge is that there is no framework accessible for discovery of illness at its early stage. intuitively health communication applications (ihcas) can be used to get past this barrier. in creator talked about algorithm, which might be applied in early location of parkinson’s diseases [1]. eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e2 https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:manjufeb62@gmail.com umamaheshwari k. et al. 2 the quality of services today and people's lifestyles have altered as a result of information systems and online technologies. among these technology and systems, electronic health is a fresh and effective way to deliver medical and healthcare services to the public while also fostering relationships between doctors, patients, and all other users of the healthcare system. unfortunately, despite the fact that e-health is not a new process and has been used in the majority of specialized medical fields, this technology is still not widely accepted as part of the standard delivery of healthcare. particularly in the area of healthcare and medical services, developing nations face a number of challenges including a lack of physicians and other healthcare professionals as well as financial and resource constraints. capturing, putting away and keeping up information and getting to data in productive way is additionally a huge challenge. effectively keeping up ehr (electronic health record) a huge issue. they require of clear information of benchmarks to urge ideal esteem in actualizing health informatics systems (who, national e-health methodology toolkit, 2012) [1]. patient privacy is a challenge while creating online medical platforms. enforcing privacy and maintaining confidentiality in public are two major privacy concerns that were mentioned. they also convinced that privacy is a key issue in gcc (gulf cooperation council) countries. to overcome this issue, lawful direction is required something else resistance will confront to embrace e-health system. we must make sure that the patient has faith in the system ability to safeguard their personal data. 2.2 complexity of wellbeing care foundation it is complex to manage healthcare infrastructure. for a variety of reasons, healthcare infrastructure can be complex. china, india, and other populated countries in developing nations need to build numerous hospitals and health care facilities. similarly distributed geographic areas have very complicated health care infrastructure. e-health should be supported by such a complex infrastructure, but the current support is insufficient and poorly distributed. such challenges are caused by a variety of circumstances. for illustration in adequate support of power, destitute quality or not accessibility of web access. these issues are more common in rustic ranges [1]. be that as it may, versatile phone foundation is creating at an expanding rate gives openings to execute frameworks with fewer assets. because of this, mobile health can be helpful when there is an inadequate framework in certain places. in any case these arrangements can lead to other issues such as divided data and troubles for venture adaptability. 2.3 neighbourly government scheme nearby healthcare informatics strategies are not developed in most of the world. since approach creators in japan have limited exposure to internet medicine teaching and the potential advantages of this area, e-health appealing techniques are not being implemented. moreover, in jordan, government approaches are not appropriate for improvement of e-health. there is a need to require advancement of medical informatics framework system for way better advancement as well as supportability of e-health ventures. it is supported by legitimate worldwide organizations such as joined united countries (un), world health organization (who). 2.4 ethical challenges there are several ethical concerns raised by the growing digitalization of healthcare and the development of portable and iot devices as data collecting tools. one topic that is frequently brought up again and again is the precise makeup of the segment of consumer tech giants that have all joined the advanced prosperity field, including amazon, apple, google, facebook, and samsung. these businesses provide methods for gathering and analysing economic data, which raises concerns about data security, data veracity, and informed permission. as well as the issues said over of privacy, security, and consent, ethical concerns relating to data proprietorship are frequently talked approximately inside the composing. the development of apps and improvements made for a customer's display help to bridge the gap between therapeutic and non-medical devices and present moral dilemmas regarding how to regulate such advances. the rate of advancement and expanding globalisation of healthcare solutions increase this problem [2]. 2.5 patient consent these ideas are relatively new in the patient-physician relationship, along with information disclosure and informed consent. they have a lot of positive practical benefits and are primarily founded on the autonomy principle. however, there are several barriers that must be overcome in order to carry out the moral duty of beneficence, some of which may hurt the patient or prevent the requirements from being put into practice. this is in particular true when physicians disclose facts and obtain informed consent in a defensive manner out of concern about malpractice claims. the method that adheres to the highest standards of ethics is to sensitively and empathically modify and direct the information in accordance with each patient's unique requirements and preferences. it is important that both parties take responsibility for the informed consent process. there are various sorts of ask almost considers counting or not human subjects. no matter the sort of consider, any ask around tradition need to involvement a thorough ethical assessment. concerning considers approximately counting human subjects, prior support by the committee embraced by the prosperity benefit is required. for considers not counting human subjects, support by a direction overview board is unequivocally endorsed. in development, any collection of person data ought to comply with the french eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e2 current practices and limitations in e health informatics 3 law on data security and opportunity of information as well as the european common data security heading [3]. the process of obtaining a patient’s informed consent includes educating them of the advantages, disadvantages, and possible alternatives to a certain procedure or intervention. in order to voluntarily decide whether to undergo the operation or intervention, the patient must be competent. informed consent, this is a moral and legal duty for medical personnel in the us and originates from the patient's right to determine what transpires to their body. giving informed consent entails evaluating the patient's comprehension, making a real recommendation, and documenting the procedure. all aspects of informed consent must be documented, according to the joint commission. the nature of the procedure, its benefits and drawbacks, and viable alternatives are some of the elements that must be recorded during the informed consent process [4]. 2.6 confidentiality it is essential for all healthcare professionals and institutions to ensure the security, privacy, and protection of patient’s medical information. this is true more than ever in our fastchanging information technology era. in the past, healthcare professionals frequently gathered patient data for research purposes and typically just withheld the names of the patients. this is no longer allowed for access as before instead, protected health information (phi) must be redacted before being used for research if it contains information that might be used to identify a patient or the patient's family, friends, employers, or household members. in order to maintain the confidentiality and security of patient medical documents, the federal government adopted the health insurance portability and accountability act, public law 104191 [5]. the law is divided into two main parts: the privacy rule, which regulates how people's health information is used and disclosed, and the security rule, which establishes federal standards for safeguarding the privacy, integrity, and accessibility of electronically protected health information. the privacy rule lists 18 components that make up phi (protected health information). these identifiers comprise demographic data as well as additional details pertaining to a person's past, present, or future physical or mental health or condition, or the provision or payment of healthcare to a person [5]. inadequate legal protections and a lack of rules have left management's ethical problems unresolved. there isn't just any regulation, but also no explanation of why secrecy isn't always guaranteed. all health care professionals can access patient information even though it is stored in electronic documents by using their own password; however, if they forget it, they can use the default password. although maintaining patient confidentiality is not necessarily mandatory in clinical practise, there is no set policy or legislation that specifies when it is appropriate to violate patient confidentiality without their agreement or that names the individual who should be held accountable for disclosure. there are monitoring systems with fewer facilities to control who has access to patient information, but there are no rules defining the level of password protection [6]. 2.7 flexibility and security all healthcare facilities have access to a useful and adaptable framework for putting security measures in accordance to the hipaa (health insurance portability and accountability act) security rule. some of these requirements must be followed, but others are optional, giving the institution the freedom to implement security and privacy safeguards that are appropriate for its resources, infrastructure, and operation. 2.8 hardware and software in medicine the hardware and software solutions used in hospitals only address a narrow set of needs. they nevertheless produce sensitive patient data, necessitating the use of management healthcare solutions. health portals are an alternative to medical database software for simplifying electronic prescriptions or supplying the medical personnel with the medical knowledge base when needed. these technologies not only improve employee collaboration but also ease operational and financial issues for the hospital. there has recently been a buzz about the impact of ai, ar, and vr in the healthcare software sector. we also have software for medical researchers and scientists that were created specifically to help in the process of finding and analyzing of new drugs [7]. 2.9. provision faced patients can profit from the deployment of innovative technology by receiving high-quality care. all of your medical personnel must, however, be trained in the right use of these equipment. if not, people can be hesitant to use them or uncertain of how to make the most of their features. offering ongoing training and instruction is one method to solve this difficulty. you can either do this internally or by employing a third-party trainer. this helps your staff to stay keep informed of all medical technology advancements. users of cloud-based applications can access data via a variety of devices. for instance, it could be challenging to pinpoint the source of changes if one of a user's two devices is compromised and both devices simultaneously modify the application data or service. the difficulties in obtaining such proof are still unknown, given the rise in potential for credential breach and identity theft in a cloud-based system. as we may mitigate this problem by putting in place a system that enables you to control the actions of all your medical staff from a single location. as a result, it will be simpler to determine the procedures that require automation and to keep track of your team's performance in real time [8]. eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e2 umamaheshwari k. et al. 4 2.10 interoperability of medical data in healthcare informatics accessing and transferring safe health data has always been difficult. the nature of health data creates a paradox: it's challenging to share since it's delicate and needs a high level of privacy and security, but the inability to access it when necessary could result in serious injury. interoperability and data transfer will become even more essential for providing good healthcare as the world's population’s age and individuals live longer. figure 1 shows the stages of interoperability. figure 1. interoperability health data interoperability benefits businesses in the healthcare sector in addition to assisting doctors and other healthcare professionals in getting a fuller picture of their patients. health plans would have a better knowledge of their utilization rates and demand for services if health information systems were more interconnected. access to demographic data would allow government service providers to identify trends and address the needs of their constituents. furthermore, life science firms would be able to use substantial datasets to facilitate quicker, more accurate research. healthcare organizations frequently encounter certain difficulties as they attempt to make their data and systems more interoperable, despite the fact that many experts and leaders in the field of healthcare agree that doing so would benefit healthcare as a whole. not many businesses are provided with the financial or technical resources necessary to purchase the technological components required to create a system that is genuinely interoperable. organizations should determine their eligibility before updating their health record systems since there may be government grants available. numerous cloud companies also provide pay-as-you-go payment options, which may lower and better anticipate technical costs. healthcare firms with older legacy systems must simultaneously meet interoperability requirements while also updating their systems. healthcare businesses with older legacy systems confront the combined challenges of upgrading their systems while also satisfying interoperability requirements. organizations can achieve both goals by extracting data from ancient systems and making it more available for current applications and programmes. using a hybrid cloud strategy to extract data from ancient systems and make it more available for contemporary apps and programmes, organizations can achieve both objectives. 3. recent trends in e-health 3.1 e-health in smart cities medical healthcare plays a crucial role in both people and planet. despite the fact that our health systems are frequently created around the needs of individuals, the pandemic demonstrated how interrelated we are as people and how our personal health and wellbeing are influenced by the health and wellbeing of the communities in which people survive. the emergence of smart health communities re-imagine public health, and well-being into pro-active address the drivers of medical care in cities. when systems and data are integrated and interoperable across core health and other services, such as safety of public, environmental health, social and emergency services, are digitally connected "smart city" can make health care smarter. cities can promote public health in a variety of ways, not just by integrating digital technologies or even by expanding access to conventional healthcare. cities that are planned and built for people, with "green sidewalks" and public areas serve a healthy atmosphere. smart cities necessity is increasing exponentially over the globe. thus, they fulfill the requirements for public by the various application facilities like internet of things, smart mobility, smart grid and not the least as smart healthcare. given that e-health is a subset of smart health, the specified smart city's ict infrastructure and s-health are related. however, there are distinctions between s-health and m-health [9]. 3.1.1 mobile health informatics as a result of two nih big data to knowledge centers, mhealth focus is on expediting the use of data obtained from mobile and wireless devices, such as wearable sensors, in clinical research and care, even though it covers a wide range of issues. figure 2 shows the traits in m-health in which the largest new possibility is in using m-health informatics is to directly measure and enhance patient health and health conditions outside the conventional constraints of the hospital and clinic due to the personal omnipresent nature of mobile devices. these informatics solutions have been developed for a range of demographics, but due to a interoperability employers registries healthcare associations application providers health plans laboratories eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e2 current practices and limitations in e health informatics 5 lack of advancements and user engagement, they may easily lose their novelty over time. the creation and implementation of technology can be problematic for a number of reasons, including high costs, continuously shifting schedules, and challenges creating compliant data storage systems [10]. figure 2. traits in m-health artificial intelligence and machine learning algorithms have been widely used in the domains of autonomous driving, recommender systems in social media and online commerce, natural language understanding, and questionanswering software. additionally, the conduct of medical research is increasingly changing due to artificial intelligence. in areas including patient deterioration, readmissions, mortality, enhanced documentation, illness diagnosis, end-of-life care, patient transportation, and chronic care management, predictive modelling in healthcare has been driven by digital transformation. the emergence of cloud computing, big data, and the internet of things has made it possible to connect and exchange data using gadgets equipped with sensors, software, and other technologies. these advancements have also made it possible to perform large-scale computations, store shared resources, and compile data from a variety of sources [11]. 3.2 e-health trend in battlefield to receive a virtual visit before recently a patient had to be present at the patient centered medical home. veterans and those in the military have particular difficulties in accessing behavioral healthcare. it also includes barrier to receiving treatment due to concerns associated with the privacy and the stigma about behavioral healthcare. in addition to these military officials are subjected to frequent relocation and deployment cycle which basically leads to a life style where they are frequently separated from their families and irregular access to healthcare professional. e-health being one the unique technology which has the potential to support the general wellbeing, fitness status of the active-duty service members. these types of services in e-health can named as e-health behavior which refers to the use of internet (or) mobile devices for health related activities such as looking up health information online, virtual communication with clinical teams and use of health management tools like patient portals etc.-health behavior analysis is built upon the following factors such as • individual characteristics such as gender, age, race and marital status. • environment variable such as income and education and socio economics. • military branch • finally the health status of the person these factors combined will be able to understand the behavioral model as shown in the figure 3. figure 3. general health factors research has stated that incorporating these factors along with artificial intelligence and deep learning methodologies e-health will be able to meet the tremendous demands of the soldiers in the battlefield. it also states that virtual interaction is found to be very effective as that of the face to face interaction and will help in the behavioral improvement of the soldier. it will also reduce the major barrier such as transportation, distance between the battlefield and healthcare professional. e-health has the capacity to provide continuous monitoring of the soldiers vital in the battlefield via proper telehealth infrastructures which is termed as virtual health. virtual health involves the usage of medical device like glucose monitor, electrocardiogram etc. that can transmit information to the healthcare service providers via internet along with high resolution video for better diagnose of the community health intelligence multitasking environment conciousness eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e2 umamaheshwari k. et al. 6 problem. the use of virtual healthcare reduces the need for evacuation of the soldiers because based on the consultant’s suggestion, the practitioners are frequently able to treat or manage the medical problem at the deployed location. for an instance if a soldier is injured on a battlefield he or his fellow troops will able to communicate with a frontline medic to stabilize the injured solider with the help internet using some communication device until he can receive more advanced care. another scenario is when a soldier to attached to various vital monitoring sensors which, when attached the soldier sends all his vitals to the healthcare professional screen. this will help in understanding that which soldier needs immediate care by comparing their vitals such as heart rate and blood pressure. these will also help us in identifying the exact geographical location of the soldier which helps in communication and also in identifying the causalities. use of e-health in army medicine enables the soldiers enables the patient to receive best healthcare service regardless of where they are stationed. 3.3 e-health trends in serious games gamification is always on trend since engages audience at a large scale by injecting fun and improving the cognitive skill of the user. in recent days many industries such as elearning, marketing and many more has seen to use games for its advantage. similarly, for its simplification and benefits healthcare is also evolving by incorporating games in its certain therapy, monitoring and diagnoses of diseases. the commonly accepted definition for gaming was proposed by sebastian deterding who stated as “gamification is the use of game design element in non-game content”. serious games are nothing but games with purpose especially for non-recreational purpose with focus on areas like business, economics, industry, military and healthcare. challenges, levels, badges and loops are some of the design structures of games which keep them engaged. by using the above mentioned structure serious games in healthcare can be designed with pleasant activities with long term engagement task that are otherwise thought to be demotivating. depending on the objective of the e-health service to be provided they are classified as either patient based service or non-patient based service as shown in the figure 4. based on the patient service as shown, they are classified as follows • rehabilitation • treatment • detection • health monitoring • education/training based on the non-patient service they are classified based on wellness as follows • exercise • sleep pattern • maintaining a healthy body weight • limiting alcohol use • training of healthcare professional figure 4. classification of serious game for e-health based on player some major serious e-health games are mainly aimed towards patient centered games especially cognitive disability. the development e-heath games towards cognitive disorder not requires software but also hardware interface with it such as smart phone and virtual reality which may provide a better gaming experience. by using games such as neuro-orb research demonstrates that there is a significant improvement in the working memory of the patient with cognitive disorder such as alzheimer's disease. other most popular application of e-health in games is especially for rehabilitation. video games are specially designed which requires the movement of physical body to interact with the game which can be used as a form of exercise in rehabilitation medicine. through such games it is also possible to monitor the performance of the patient with functional impairment which may be caused due to stroke and paralysis. some game involves peculiar movement of limb and body parts to perform action games such as dance games, step games, games balance training and games for hand training to improve the motor action of the patient. with right software and hardware setup for the serious game in e-health it is possible track the improvement of the patient from any location. with many advancements in technology e-games may be also used in training of healthcare professional in performing surgery, home based elderly patient monitoring etc. are some other areas of improvement 4. conclusion the development of tools that can significantly improve the lives of people struggling with physical and mental health disorders will be made possible through m-health research [11]. understanding the field strengths and shortcomings eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e2 current practices and limitations in e health informatics 7 through a map of its history can help guide future advancements. the requirement for a mobile application that boosts individual productivity and helps us in a crucial from this vantage point, it is possible to claim that the m-health application provides a solution that satisfies the requirements. although similar applications have been described in the literature, m-health differs from these ones in that it makes use of technologies like expert systems, intelligent optimization, signal-image processing, and data mining. framework in artificial intelligence that is competent of using reinforcement learning, nonconsultancy, and all three. intelligent optimization algorithms that can deliver faster feedback are also supported in processes like controlling the processes within the m-health application, choosing the best processes that can be used to change the user's current status, or choosing the best diagnosis-solution among diverse alternatives [12]. reference [1] christensen h, hickie ib. using e‐health applications to deliver new mental health services. medical journal of australia. 2010 jun;192:s53-6. [2] kostkova p. grand challenges in digital health. frontiers in public health. 2015 may 5;3:134. [3] nijhawan lp, janodia md, muddukrishna bs, bhat km, bairy kl, udupa n, musmade pb. informed consent: issues and challenges. journal of advanced pharmaceutical technology & research. 2013 jul 1;4(3):134. [4] nijhawan lp, janodia md, muddukrishna bs, bhat km, bairy kl, udupa n, musmade pb. informed consent: issues and challenges. journal of advanced pharmaceutical technology & research. 2013 jul 1;4(3):134. [5] graham hj. patient confidentiality: implications for teaching in undergraduate medical education. clinical anatomy. 2006 jul;19(5):448-55. [6] noroozi m, zahedi l, bathaei fs, salari p. challenges of confidentiality in clinical settings: compilation of an ethical guideline. iranian journal of public health. 2018 jun;47(6):875. [7] onik mm, aich s, yang j, kim cs, kim hc. blockchain in healthcare: challenges and solutions. inbig data analytics for intelligent healthcare management 2019 jan 1 (pp. 197-226). academic press. [8] lohiya r, john p, shah p. survey on mobile forensics. international journal of computer applications. 2015 jan 1;118(16). [9] vel'asquez w, munoz-arcentales a, salvach'ua ji. e-health services role in a smart city-a view after a natural hazard. engineering letters. 2019 dec 1;27(4). [10] das a, rad p. opportunities and challenges in explainable artificial intelligence (xai): a survey. arxiv preprint arxiv:2006.11371. 2020 jun 16. [11] shariful im. theories applied to m-health interventions for behavior change in low-and middle-income countries: a systematic review. telemedicine and e-health. 2018 oct 12. [12] afrah ia, kose u. mhealth: an artificial intelligence oriented mobile application for personal healthcare support. arxiv preprint arxiv:2108.09277. 2021 aug 18. eai endorsed transactions on smart cities 09 2022 10 2022 | volume 6 | issue 3 | e2 detection of cyber attacks using machine learning based intrusion detection system for iot based smart cities eai endorsed transactions on smart cities research article 1 detection of cyber attacks using machine learning based intrusion detection system for iot based smart cities maria nawaz chohan 1 , usman haider 2,* , muhammad yaseen ayub 3 , hina shoukat 3 , tarandeep kaur bhatia 4 and muhammad furqan ul hassan 3 1 national defence university, islamabad, pakistan 2 department of electrical engineering, national university of computer & emerging sciences, peshawar, pakistan 3 department of computer science, comsats university islamabad, attock, pakistan 4university of petroleum and energy studies, dehradun, india abstract the world’s dynamics is evolving with artificial intelligence (ai) and the results are smart products. a smart city has smart city is collection of smart innovations powered with ai and internet of things (iots). along with the ease and comfort that the concept of a smart city pointed at, many security concerns are being raised that hinders the path of its flourishment. an intrusion detection system (ids) monitors the whole network traffic and alerts in case of any anomaly. a machine learningbased ids intelligently senses the network threats, takes decisions about data packet legibility and alarm the user. researchers have deployed various ml techniques to ids to improve the detection accuracy. this work presents a comparative analysis of various ml algorithms trained over unsw-nb15 dataset. ada boost, linear support vector machine (lsvm), auto encoder classifier, quadratic support vector machine (qsvm) and multi-layer perceptron algorithms are being employed in the stimulation. ada boost showed an excellent accuracy of 98.3% in the results. keywords: iot, smart cities, uavs received on 09 april 2023, accepted on 17 june 2023, published on 28 june 2023 copyright © 2023 chohan et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.3222 *corresponding author: usmanhaider@ieee.org emails: m.n. chohan (maria.nawaz160@gmail.com), m.y. ayub (yaseen.ayub@ieee.org), h. shoukat (fa18-bcs-053@cuiatk.edu.pk), t. k. bhatia (tarandeepkaur42@gmail.com) m. f. ul hassan (sp19-bcs-011@cuiatk.edu.pk) 1. introduction technological inventions have changed the dynamics of world. infrastructure in every industry is automated with the use of iot and wireless communication networks. smart cities are based on wireless connectivity where infrastructure less topological scenario allows many cyber-attacks. therefore, vulnerabilities in smart cities need to be addressed with proper solution. the area of smart cities is quite diverse with having many applications which include e-government, smart homes, intelligent transportation, tele-medicines, smart grid, uavs monitoring, energy and many more [1-4]. data network security is the topic for many researchers around the world due to ever-increasing cyber-attacks. intrusion detection is the system which needs to identify fake data packets easily. optimal ids algorithm balance high accuracy with the metrics of false negative and false positive. also, the main goal of ids is to detect possible cyber-attacks. however, intrusion detection system is based on normal and eai endorsed transactions on smart cities | volume 7 | issue 2 | mailto:https://creativecommons.org/licenses/by/4.0/ mailto:https://creativecommons.org/licenses/by/4.0/ mailto:usmanhaider@ieee.org mailto:maria.nawaz160@gmail.com mailto:yaseen.ayub@ieee.org mailto:fa18-bcs-053@cuiatk.edu.pk mailto:tarandeepkaur42@gmail.com mailto:sp19-bcs-011@cuiatk.edu.pk m. n. chohan et al. 2 illegal data packets. moreover, smart cities need secure communication channels due to that ids plays important role [5-8]. figure 1, shows the concept of smart cities which further explains smart house, hospitals, vehicles and how a smart city is going to be connected. uavs can be merged with smart cities which can help in connectivity. secure communication links are designed to reduce end-to-end delay. while, false data injection attacks can be deployed with help of intruder to unbalance communication in remote surgery of high official patient. various technologies like markov chain, machine learning, deep learning, ant colony optimization and poisson distribution use to improve signature, anomaly or hybrid intrusion detection systems [913]. figure1: future connected smart cities 2. literature study the concept of smart cities is the need of today but due to automation there exist many connectivity problems. uavs operations are possible in smart cities to collect information from iot nodes and send to base station. therefore, uavs actively plays important role in smart cities. dsdv routing protocol is having the process of incremental updates which is helpful to improve and secure communication standards in uav enabled smart cities [14]. moreover, for secure communication protocols need to be designed to mitigate related problems of the network [15]. wireless connected technology like ieee 802.11 needs more improvements. rssi controlled machine learning approach decision tree is introduced which has shown better results in signal strength indicator [16]. iot networks in smart cities connect everything through wireless technology. block chain in smart cities can provide better solutions in many applications [17]. table 1, describes the security attacks/violation, related challenges in smart cities and gives an overview of researches in this area. 3. cyber threats on smart cities iot networks are vulnerable to the cyber-attacks, so in a smart city such threats are a big challenge to counter. dos, ddos, sybil attack, sql injection and malware attacks are common types of attacks in iot environment thus smart cities are also subjected to these attacks. so, the result of this insecure sensor node network can be system crashing or service termination if left solution less and unsecure. such technical failures can be a full stop to this advancement. fortunately, no one is left helpless over these threats because many solutions are been available of various nature can be used accordingly [28-29]. eai endorsed transactions on smart cities | volume 7 | issue 2 | detection of cyber attacks using machine learning based intrusion detection system for iot based smart cities 3 3.1. denial of service attack (dos) on smart cities no one is denial of service (dos) attack is most basic type of attack that can cause the victim system to crash down or become unavailable even for the legal users due is huge imbursement of the data packets by the hacker or intruder. thus, the purpose of this attack is the hang up victim services, like an attack on a smart grid in ukraine in 2015. in smart cities, such system unavailability can cause a havoc, so the monitoring of all network traffic is certain [30]. figure 2, explains dos attack mechanism in detail, how a system is being attacked in dos and represent the service termination as attack result. table 1: cyber attacks with related challenges reference security attacks/violations field of study description [18] ddos, access attack iot iot needs to be secure thus an analysis is necessary to be done on various kind of attacks and solution to them. [19] man-in-the-middle (mitm) attack, ping ddos flood attack, modbus query flood attack, and tcp syn ddos flood attack iot this paper proposed a deep leaning approach to detect the mentioned attacks and applies long shortterm memory (lstm) module. [20] ddos, malware iot this work analyzes the real time attacks and suggest a threefold approach. [21] ddos iot in a smart power system, iot managed load could be vulnerable to attacks. this paper presents a detailed report on threat analysis. [22] false data injection attack iot the security of smart electric vehicles is subject into account by this work and proposes semidefinite programming approach-based algorithm. [23] denial of service (dos) attacks, injections, man in the middle attacks, buffer overflow iot this paper proposed management-based solution to cyber-attacks. [24] dos, ddos, zero-day attacks, mitm iot growth of iot in the markets has given rise to cybercrime in this domain and this work offers detailed analysis of known defense techniques. [25] ddos iot this paper tries to cover the destruction of ddos attack with deep learning approach with an excellent efficiency [26] intrusion attacks iot this paper provides a hybrid approach for intelligent secure system. eai endorsed transactions on smart cities online first eai endorsed transactions on smart cities | volume 7 | issue 2 | m. n. chohan et al. 4 figure 2: denial-of-service attack 3.2 distributed denial of service attack (ddos) on smart cities distributed denial of service (ddos) attack is type of dos attacked and it can be on single victim or group of victims with multiple systems operated via channels using various compromised systems or botnets. a victim compromised with such an attack in smart, drains out resources of the server or network infrastructure by entertaining overwhelming faulty packets in place legitimate packets thus they remain unpleased over the victim. in this way all communications can be disrupted with multiple consequences [31]. figure 3 shows the concept of ddos attacks on smart cities and understanding of attacker, handler, botnet and victim in this type of attack. [1] figure 3: ddos attack 3.3 sybil attack on smart cities in sybil attack, the hacker pretends multiple identities using them all at the same time thus these pseudoidentities compromise the system efficiency. so, in a smart city, aftershocks of this of attacks are privacy loss, fallacious report generation, spam encounter etc. moreover, sybil attackers incorporate various other types of attacks like phishing, social engineering, malware etc. and also encourage machine learning (ml) methods in their attack patters [32]. 3.4 sql injection attack on smart cities whenever the target is sensitive data, sql injective is famous way to proceed. this attack can read as well as delete data and also this intrusion has application to destroy sql databases. all the sensitive data from various ends and sensor nodes of smart appliances in a smart city can be at risk. so, the databases in a smart city must be highly protected for the users to have their privacy [33]. 3.5 malware attack on smart cities malware is one of the largest group of threats with various types and classes of intrusion and threats. famous classes of malware are ransomwares, trojans, worms etc. they actually infect the victim with various kind of viruses thus resulting in victims’ data loss. in a smart city, all the customer’s data can be at stack of destruction thus leaving the core cause of easing humanity smart cities [34]. 4. machine learning based intrusion detection system the finest approach in the detection and mitigation of various threats in smart cities is machine learning. we are using ml for the detection of cyber threats in networks of a smart city. there are three main types of ml approaches: anomaly-based, signature-based and hybrid. anomalybased detection is through the system intelligence trained through various techniques [35], signature-based approach cross compares the network traffic with existing signature or attack pattern thus results threat detection [36] and hybrid system is mixture of assets of both thus more effective and accurate than both of then [37]. depending on environment scenarios, various researchers have developed different types of idss using different approaches, algorithms with different target systems and compare the precision and accuracy of their proposed algorithm with other algorithms in their case study [38-39]. eai endorsed transactions on smart cities | volume 7 | issue 2 | detection of cyber attacks using machine learning based intrusion detection system for iot based smart cities 5 5. simulation environment & results python is used to create the simulation environment. the most popular dataset unsw-nb15 is used. however, machine learning algorithms like ada boost, auto encoder classifier, linear support vector machine, quadratic support vector machine and multi-layer perceptron are simulated to detect cyber-attacks [39-45]. table 2 shows accuracies of machine learning algorithms where ada boost shows better results in comparison with other traditional techniques. table 2, details are illustrated in figure 4. table 2: accuracy details of machine learning classifiers s/no. algorithms accuracy 1 ada boost 98.3431 2 auto encoder classifier 96.1133 3 linear support vector machine 97.8503 4 quadratic support vector machine 84.7305 5 multi-layer perceptron 97.9735 figure 4: comparative study of machine learning algorithms using unsw-nb15 6. conclusion smart cities are considered a novel concept while, cyberattacks can unbalance life of humans. therefore, most of the researchers have merged smart cities with uavs to provide better connectivity. machine learning based ids approach is used in the concept of smart cities. for experimentation, unsw australia based dataset is used to check the raw traffic problems and attacks. machine learning algorithms are used where ada boost has shown optimal results. 7. future direction in near future, the use of technology is increasing on daily basis. security is considered main issue in every field of study. therefore, machine learning based intrusion detection system will easily detect attacks in iot networks. moreover, deep learning, artificial intelligence, genetic algorithm-based ids need to be designed for future smart cities. references [1] çimen, h.; palacios-garcía, e.j.; kolaek, m.; çetinkaya, n.; vasquez, j.c.; guerrero, j.m. smart-building applications: deep learning-based, real-time load monitoring. ieee ind. electron. mag. 2020, 15, 4–15. 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"towards developing network forensic mechanism for botnet activities in the iot based on machine learning techniques." international conference on mobile networks and management. springer, cham, 2017. eai endorsed transactions on smart cities | volume 7 | issue 2 | https://ieeexplore.ieee.org/abstract/document/7348942 https://ieeexplore.ieee.org/abstract/document/7348942 https://ieeexplore.ieee.org/abstract/document/7348942 https://www.tandfonline.com/doi/abs/10.1080/19393555.2015.1125974 https://www.tandfonline.com/doi/abs/10.1080/19393555.2015.1125974 https://www.tandfonline.com/doi/abs/10.1080/19393555.2015.1125974 https://www.tandfonline.com/doi/abs/10.1080/19393555.2015.1125974 https://ieeexplore.ieee.org/abstract/document/7948715 https://ieeexplore.ieee.org/abstract/document/7948715 https://ieeexplore.ieee.org/abstract/document/7948715 https://link.springer.com/chapter/10.1007/978-3-319-59439-2_5 https://link.springer.com/chapter/10.1007/978-3-319-59439-2_5 https://link.springer.com/chapter/10.1007/978-3-319-59439-2_5 https://arxiv.org/abs/2011.09144 https://arxiv.org/abs/2011.09144 https://link.springer.com/chapter/10.1007/978-3-030-72802-1_9 https://link.springer.com/chapter/10.1007/978-3-030-72802-1_9 https://link.springer.com/chapter/10.1007/978-3-030-72802-1_9 https://link.springer.com/chapter/10.1007/978-3-030-72802-1_9 https://link.springer.com/chapter/10.1007/978-3-030-72802-1_9 https://link.springer.com/chapter/10.1007/978-3-030-72802-1_9 https://ieeexplore.ieee.org/abstract/document/8470090 https://ieeexplore.ieee.org/abstract/document/8470090 https://ieeexplore.ieee.org/abstract/document/8470090 https://books.google.com.au/books?hl=en&lr=&id=8k5adwaaqbaj&oi=fnd&pg=pa30&ots=3nr5weyk1p&sig=0x03dtpq7u72nf3ixswjmmdhd_0#v=onepage&q&f=false https://books.google.com.au/books?hl=en&lr=&id=8k5adwaaqbaj&oi=fnd&pg=pa30&ots=3nr5weyk1p&sig=0x03dtpq7u72nf3ixswjmmdhd_0#v=onepage&q&f=false https://books.google.com.au/books?hl=en&lr=&id=8k5adwaaqbaj&oi=fnd&pg=pa30&ots=3nr5weyk1p&sig=0x03dtpq7u72nf3ixswjmmdhd_0#v=onepage&q&f=false https://books.google.com.au/books?hl=en&lr=&id=8k5adwaaqbaj&oi=fnd&pg=pa30&ots=3nr5weyk1p&sig=0x03dtpq7u72nf3ixswjmmdhd_0#v=onepage&q&f=false multi agent system optimization in virtual vehicle testbeds patrick lange, rene weller, gabriel zachmann university of bremen {lange,weller,zach}@cs.uni-bremen.de abstract modelling, simulation, and optimization play a crucial role in the development and testing of autonomous vehicles. the ability to compute, test, assess, and debug suitable configurations reduces the time and cost of vehicle development. until now, engineers are forced to manually change vehicle configurations in virtual testbeds in order to react to inappropriate simulated vehicle performance. such manual adjustments are very time consuming and are also often made ad-hoc, which decreases the overall quality of the vehicle engineering process. in order to avoid this manual adjustment as well as to improve the overall quality of these adjustments, we present a novel comprehensive approach to modelling, simulation, and optimization of such vehicles. instead of manually adjusting vehicle configurations, engineers can specify simulation goals in a domain specific modelling language. the simulated vehicle performance is then mapped to these simulation goals and our multi-agent system computes for optimized vehicle configuration parameters in order to satisfy these goals. consequently, our approach does not need any supervision and gives engineers visual feedback of their vehicle configuration expectations. our evaluation shows that we are able to optimize vehicle configuration sets to meet simulation goals while maintaining real-time performance of the overall simulation. categories and subject descriptors d.2.11 [software]: software architectures—domain-specific architectures; i.2.11 [artificial intelligence]: distributed artificial intelligence—multiagent system; i.3.1 [computer graphics]: hardware architecture—graphics processor ; i.6.8 [simulation and modeling]: types of simulation— parallel keywords virtual testbed, vehicle simulation, multi agent system, discrete event simulation, gpu, cuda, domain specific modelling . 1. introduction typically, the engineering of vehicles consists of three main steps: first, a mission scenario and corresponding requirements are defined, then engineers construct a vehicle that should fulfill these specifications and finally, test runs for fine-tuning of vehicle parameters, like fuel level or sensor orientation, are performed (see figure 1). while the basic principle remained the same since the beginning of modern engineering, the process has changed substantially during the past 40 years: the design moved from the drawing board to the computer and test runs are not only performed with physical prototypes in real hardware environments [20] but have also moved more and more to the computer. in recent years, virtual reality (vr) has emerged as a key technology for improving and streamlining the conceptualisation and design of vehicles by simulation [11][10]. these testbeds give engineers the opportunity to interact with the simulated vehicle in order to gain comprehensive understanding of possible design flaws as early as possible during the design process. they are frequently used in fields like space robotics [10][22], underwater vehicles [7], or military ground vehicles [20]. in addition, it is widely recognized that simulation is pivotal to vehicle development, whether manned or unmanned [18]. virtual testbeds are constituted by a sophisticated physically-based simulation of both the vehicle and its designated environment, as well as real-time, immersive rendering and 3d interaction techniques for the direct feedback and manipulation of the vehicle. in addition to the vehicle design process, the same virtual testbeds can often be re-used directly for later mission stages like training and supervision. furthermore, virtual testbeds are a costefficient alternative e.g. for planetary exploration missions, or other autonomous vehicle applications in which setting up real mockups for testing and verifying is too expensive [11]. however, even in state-of-the art virtual testbeds, it is still challenging to identify the origin of errors. engineers can waste a lot of time in the fine-tuning vehicle parameters while the error is in the vehicle design or even in the mission specifications. simutools 2015, august 24-26, athens, greece copyright © 2015 icst doi 10.4108/eai.24-8-2015.2261104 figure 1: integration of virtual testbeds with the vehicle engineering process: simulation results are used to change vehicle configurations in order to meet engineer expectations if the simulated vehicle performance does not meet vehicle mission or engineering expectations. in the traditional approach, virtual testbed development as well as actual vehicle simulation take the most of the overall engineering process time (left). our approach (right) reduces this development time significantly by introducing source code generation as well as autonomous vehicle optimization without supervision. we propose a novel approach that overcomes these drawbacks. the main idea is to remove the last feedback-loop of the current design process completely (see figure 1). to do that, we replace the manual parameter fine-tuning by an optimization method that adjusts these parameters automatically. this avoids the time-consuming and error-prone manual tweaking and helps the engineers to concentrate on their real work: the construction, testing and validation of the vehicle. in order to give engineers direct access to the virtual testbed, we additionally present a novel easy-to-use domain specific interface that allows the intuitive definition of simulation goals as well as vehicle parameters. consequently, we present a novel comprehensive approach to modelling, simulation, and optimization of such vehicles which greatly benefits the overall engineering process of autonomous vehicles. in detail, our contributions are: • a gpu based multi-agent system (mas) for the automatic vehicle parameter adjustment: it computes objective and utility values for evaluating the current vehicle configuration with respect to fuzzy logic based simulation goals. • a domain specific modeling language (dsml) which allows the visual development of a vehicle configuration and simulation as well as mas based parameter optimization. • a massively parallel domain framework, which enables wait-free discrete event simulation of autonomous vehicles. additionally, this domain framework minimizes the synchronization overhead to the gpu to a minimum for fast parallel computations, without affecting the vehicle simulation performance. in addition, our virtual testbed implements a 3d geometric visualization and functional vehicle simulation loop incorporating internal vehicle subsystems, sensors, actuators, and environmental physical influences. in order to test, validate, and verify the navigation, control and localization algorithms of vehicles, engineers simply have to specify the simulation goals and the vehicle parameters in our novel dsml. our virtual testbed supports interactive real-time adjustment of vehicle specifications like adding obstacles to the environment. the system computes an optimal set of parameter for these new specifications onthe-fly so that the engineer can inspect the results of the changes immediately. consequently, our approach reduces the development and testing time significantly while simultaneously improving the quality of the parameter setting. we have applied our new approach to an autonomous spacecraft simulation. our results show a real-time performance even for large parameter sets. in order to achieve this real-time performance and easy code generation, we propose the use of a multi-agent system as it can be easily integrated into our underlying waitfree simulation system while maintaining easy code generation. furthermore, multi-agent systems fully utilize the advantages of our wait-free simulation system due to its decentralized, parallel solving process behavior. 2. related work the main task of virtual testbeds in the vehicle engineering process is to support engineers with simulation results, based on simulation scenario and vehicle configuration. for each simulation run, the vehicle configuration has to be adjusted if the simulated vehicle performance does not meet mission or engineering expectations. currently, this adjustment of vehicle parameters in virtual testbeds is either done externally by engineer experts that need to guide the adaptation, or the application has a number of scenarios. these scenarios are pre-defined by engineer experts to cover almost all aspects of the simulation. the use of expert guidance can lead to quite effective simulation results. however, such experts are rare and expensive. additionally, its not always feasible to have an expert available for configuring and supervising the simulation. furthermore, pre-defined scenarios may lead to less optimal adaptation [13]. consequently, it would be beneficial to automatically adjust the simulation online without the need of an expert guiding this process. additionally, this online adaptation can run in vast amounts of simulation runs to find a vehicle configuration which can satisfy both mission and engineering requirements. however, the increasing complexities of mission scenarios, goals and requirements as well as virtual testbed development process demands sophisticated development approaches which should perform in distributed, parallelized manner to attain real-time simulation behavior. furthermore, the development approach should improve the overall development time of the virtual testbed in order to support the vehicle engineers as soon as possible in the engineering process with simulation results. additionally, mission goals and requirements are often contradictory and define only a subset of an overall system expectation. these system expectations are in general non-manageable non-technical system aspects which can not be easily formalized in a simulation. multi-agent systems (mas) can deal with such problems which are composed of a large number of interacting and contradictory sub-problems. additionally, mas allow a simpler modelling of the domain [16]. furthermore, interactions between agents can give birth to emergent phenomena (e.g. patterns, organizations, behaviors) [16]. we consider the vehicle configuration optimization as a complex problem for which no specific solution exists beforehand. this makes mas interesting for dealing with such problems for which no algorithmic solutions can be given in advance and therefore have to be designed in a bottom-up way. the optimization system presented in this paper is therefore based on a modular hierarchical mas in which selforganization principles are used to make the collective behavior emerge from local ones. the use of gpu based mas has been successfully advocated as a means to deal with this kind of complexity in various other highly sophisticated simulation applications such as astro-physics [8][28], graph algorithms [21], molecular dynamics [30], serious game adaptations [13], and traffic simulation [6]. these approaches, and other evaluation of gpu based mas such as [3], show that gpu based mas can incorporate a drastic performance improvement up to an average factor of 60 with respect to purely cpu based implementations. in addition, advancements in software engineering can improve the development of sophisticated virtual testbeds. model driven development (mdd) allows aspects of virtual testbeds to be represented formally as an abstract graphical model which can be automatically transformed into software artefacts and subsequently into complete simulation applications. mdd enables domain experts through a domain specific modelling language (dsml) to produce virtual testbeds for autonomous vehicles easily and quickly, as mdd notably promises great benefits to its practitioners. from a software development context, mdd offers an increase in productivity, promotion of interoperability and portability among different technology platforms, support for generation of documentation, and easier software maintenance [1]. in addition, it can also lead to production of better code quality and reliability due to integration of domain rules into the dsml. such domain rules minimize modelling errors and increase the reliability of mapping from model to code [27], which is highly desirable for researchers, engineers, and industry. consequently, dsml lowers the development time and increases overall comprehension of simulation and optimization aspects of our virtual testbeds. however, previous work on virtual testbeds for autonomous vehicles focussed highly on specialized partial aspects such as real-time simulation with state-of-the-art graphics [20][18], visualization for mission analysis [7] or sensor data generation for space robotic applications [11]. as the everincreasing demand of sophisticated simulation as well as appealing graphical visualization increases the amount of interacting virtual testbed components, state-of-the-art virtual testbeds introduce centralized simulation data structures which are concurrently shared by all virtual testbed components [20][23][22][17][15]. centralized data storages deliver many advantages for virtual testbeds such as smart simulation data logging, access rights management and homogeneous access to simulation data for the vehicle, environment or rendering. nevertheless, such centralized data storages introduce a bottleneck to the overall virtual testbed as the concurrent access to it has to be managed. especially multi-agent systems introduce a huge amount of software components which data access has to be successfully synchronized. in addition to this unsolved problem for state-ofthe-art centralized virtual testbeds, none of the existing approaches addressed the complex development process of such virtual testbeds and how this development process could be integrated into the vehicle engineering process. moreover, these virtual testbeds are highly specialized and therefore present most diverse software architectures for vehicles within their designated environments. furthermore, none of the approaches involved any adaptation or optimization of the simulated vehicle. all state-of-the-art virtual testbeds need engineer expert supervision if vehicle configurations has to be adjusted as their primary objective is to give visual feedback of the simulated vehicle. consequently, existing approaches are simply visual resemblances of the underlying simulation with no more benefits to the engineers. however, system adaptations can be found in other simulation related fields, such as military training in serious games. simulation and serious gaming is a strongly related field [19] in which system parameter adaptation is well-founded. current adaptation concerns automated scenario generation, e.g. for military training purposes [2]. such adaptive applications can be effectively modelled with mas [12]. furthermore, [13] showed in general how agents can be used to define serious game applications. 3. vehicle simulation approach enabling mas based vehicle configuration requires a virtual simulation environment for the parameter optimization to take place. in this section, we will describe our simulation environment as well as domain framework and how they are related to our dsml. our modelling approach is based on the lightweight dsml [25] approach. it introduces more generalized model artefacts to be used in order to decrease the overall development time when using dsml concepts. generalized model artefacts do not support complete source code generation as their modelling concept focusses mainly on the dataflow. however, for a generic virtual testbed, which should support highly different vehicles or even other domains, complete source code generation is no prerequisite. our lightweight dsml approach is used to define generic components of a virtual vehicle simulation: the environment, vehicle sensors and actuators, internal vehicle control components, virtual objects as well as multi-agent system. all components are situated in a vehicle simulation loop, which ensures that the vehicle can only perceive its environment via its sensors and that only actuator information are routed to the environment. our lightweight dsl enables modelling of these components in a graphical manner as described in the next sections. from our dsml approach, graphical platform independent models (pim) can be modelled by domain experts. these pim are then used to automatically generate the source code of our virtual testbed, the platform specific model (psm), via horizontal model transformations [27]. figure 2 depicts our vehicle simulation and optimization within our lightweight dsl approach. figure 2: overview of our proposed approach. from a lightweight dsl, graphical platform independent models (pim) are modelled which are used to generate our virtual testbed with its vehicle simulation and configuration optimization. we will describe in the next sections our domain framework with its data flow for vehicle simulation and how it benefits the integration of gpu based multi-agent systems. additionally, we will describe the infrastructure, optimization solving process and implementation of our gpu based mas. 3.1 domain framework and data flow within domain specific modelling, a domain framework is used to execute generated code artefacts. additionally, a domain framework reduces the amount of generated software clones as the domain framework encapsulates common interfaces and data structures. this approach is well-known from other applications, such as the java runtime environment (jre) [26]. the domain framework used in our approach should be a centralized solution in order to maintain software engineering advantages from current virtual testbed approaches [18][17] but should not introduce a bottleneck to the overall simulation and multi-agent system optimization. we presented a wait-free concurrency control management approach in [23][24][22]. this approach introduces a centralized data storage that drastically outperforms traditional approaches by several orders of magnitude. consequently, we use our concurrency control management as the basis of our domain framework. we will describe in this section how we implemented a discrete event simulation and multi-agent system optimization of vehicles within this control management approach. the core of our approach is a global dictionary, called key-value pool (kvpool), a centralized data storage that maintains the complete shared world state of the virtual testbed. each simulation component that reads or write data to the kvpool is summarized as a entity. each entity that needs to share data to other entities registers this shared data to the kvpool. examples for such shared data are simulation time, vehicle position, sensor measurements or actuator commands. registering shared data means the creation of a key-value pair (kvpair) in the global kvpool with a unique key which is required for fast identification. if entities want access to the data, they simply have to pass this key to the kvpool. each kvpair can be composed of arbitrary content, such as vectors, matrices, arbitrary numerics or geometry. consequently, one kvpair can have an arbitrary amount of member data which makes a kvpair universally usable. we presented in [23][24] how entities can access the complete shared world state in wait-free manner. in contradiction to traditional lock-based concurrency approaches which are used by current virtual testbeds, entities do not have to acquire a lock before manipulating our concurrently shared world state. consequently, no synchronisation overhead is needed when solving for concurrent access. this leads to a dramatic performance increase with respect to traditional locking approaches for massively parallel access up to several orders of magnitude. in addition to the wait-free access of the kvpool, the approach delivers a homogeneous interface for accessing the simulation state as well as for entity communication. such relationships are defined by a set of kvpair read and write operations. this encapsulation as kvpairs leads to easier dsl modelling concepts as the code generation for accessing simulation state as well as for simulation component data exchange can be represented by simply delivering the corresponding key for read and write access. current virtual testbed data storage approaches even use full-fledged sql databases [17][15][5]. in contrast to our kvpool, such approaches would make code generation way more complicated as complete sql-queries would need to be generated for accessing the simulation state. consequently, our concurrency management approach delivers real-time performance as well as high software cohesion which facilitates code generation of the overall virtual testbed. within our kvpool approach, we describe a discrete event simulation loop of our domain framework as follows: a state s = (t, c, p,e) of our virtual testbed consists of simulation time t and set of entities c, key-value pairs p , and events e. additionally, a transition function δ is defined: δ(tn, c, p,e) = (tn+1, c, p ′, e′) in each transition, the key-value pairs in the key-value pool are updated by the entities and new transition events are generated by the system. to enable the modelling of vehicle environment interaction, entities can incorporate one of four types: • environment: defines simulation aspects from the environment in which the vehicle is situated. these aspects can incorporate physical forces such as gravitation, air drag, pressure, kinematics, or even virtual reality based approaches like collision detection. • interface: defines the sensors and actuators of a vehicle, e.g. thrusters, gyroscopes, cameras, or range finder sensors. • vehicle: defines internal vehicle components such as control loops, localization concepts, sensor fusion algorithms, bdi-structures or target detection. • agent: defines an agent for observing and optimizing an associated vehicle configuration parameter. for delivering a highly generic framework which can be adapted to many hardware configurations, those entities can be situated in our discrete event simulation loop in one of two ways: first one being a cpu-gpu hybrid, second one being a purely cpu based approach. in both versions, entities that simulate the vehicle in its designated environment are directly mapped to our generic vehicle simulation loop, imposing a clear engineering concept even on source code level. the versions differentiate in the way that the computation of the multi-agent system is either done on the gpu or cpu. in the first case, the multi-agent system will be computed on the gpu and the data transfer is done via one entity. in the cpu based approach, every agent is modelled as one entity. in both versions, all entities benefit from our massively parallel domain framework, which enables access to the kvpool with no synchronisation overhead. figure 3 additionally depicts these two approaches. 4. optimization of vehicle configuration the adaptation system proposed here is based on a hierarchical mas which aims at dynamically tuning all the vehicle parameter values with respect to the simulated vehicle performance. we will start with an overview which describes the overall mas infrastructure with its modular agent organizations and relationships to the vehicle simulation. following this, we describe the input and output data as well as communication structure of the agents. additionally, we will describe the adaptation solving process with its negotiation mechanisms and how even contradictory simulation goals can be satisfied. our mas is composed of several agent organizations which aim at optimizing each a subset of vehicle parameters to attain a pre-defined simulation goal by improving the simulated vehicle performance. these agent organizations are defined for each specified simulation goal and consist of a hierarchy of two agent types: objective and negotiation. a objective-agent is used to measure one vehicle parameter. consequently, there can be an arbitrary amount of objective-agents measuring the same vehicle parameter, each one measuring different simulation goal satisfaction values. each agent type implements a certain functionality in order figure 3: entities are mapped to our generic vehicle simulation loop, consisting of the environment, sensors, actuators and internal vehicle components. our mas is either computed on the cpu with n entities or on the gpu as one entity with a single cuda kernel for all agents. to maximize the related simulation goal, even if they are contradictory. for example, one simulation goal could be to minimize the vehicle fuel consumption. therefore, the simulation goal could refer to the fuel tank capacity parameter of the vehicle, the propulsion fuel consumption efficiency or the number of allowed thrust ignitions. if more than one objective-agent is attached to a vehicle parameter, the corresponding optimization can be contradictory. for example, increasing the vehicle fuel capacity has an impact on the overall vehicle mass which reduces the main thrust efficiency. therefore, negotiation-agents are used if several objectiveagents refer to the same vehicle parameter. in addition to their objective value, objective-agents also deliver a utility value. these values are described in the next section. figure 4 illustrates this agent organization concept with respect to the overall vehicle simulation. figure 4: one agent organization is generated for each simulation goals. each organization searches through the corresponding vehicle parameter space by measuring the vehicle performance and by adapting the configuration until the organization finds a satisfying solution. 4.1 parameters, objectives and utilities when building a vehicle configuration optimization system, all manipulable vehicle parameters needs to be uniquely identified. additionally, a range for each of these parameters is given, defining the allowed values for this specific parameter. all adjustable vehicle parameters par constitute the input of our multi agent system; it is defined as follows: par = {p1...pn} pi ∈ {pmin...pmax} ⊂ r (1) analogous, objectives of the control system need to be defined. objectives of simulations are often multiple and contradictory. instead of defining a single general goal state of the simulation, several independent objectives are here considered, each one related to a parameter p ∈ par. requirements on autonomous systems are hard to express in an numerical way as humans often only have a general idea of their system expectations. diverse solutions based on fuzzy logic have been proposed to solve this mapping from human-made requirements to measurable numerics [29]. this paper proposes the use of such fuzzy predicates to allow the smart definition of objectives as they involve a specific measure on the simulation which should not be necessarily complete satisfied or unsatisfied. satisfaction functions are introduced in order to determine the objective satisfaction for a given parameter. a satisfaction function takes as input a parameter and returns a satisfaction value in fuzzy predicate. this predicate is constituted within the [0;100] interval and yields every objective satisfaction value between unsatisfied (0) and completely satisfied (100). depending on the relationship between the parameter and objective, a satisfaction function can be strictly or loosely following a parameter in (inverted) linear, quadratic or exponential manner. we introduce, in addition to the satisfaction function, an optional linear weighting term ∗w + b which can scale the satisfaction value in order to increase the impact of the parameter within the solving process. the set of all objectives obj is defined as follows: obj = {o1...on} → {0, 100} oi = satisfaction(pi)[∗w + b] (2) in addition to the objectives to be satisfied, a control system should consider the possible utility when changing the vehicle parameters with respect to the current simulation state. consequently, we introduce a utility function. it is used to calculate the benefit for the current simulation state, if a parameter p ∈ p would be adapted accordingly to the corresponding objective value o. the utility value is then later used by the negotiation agent to select the most appropriate action. the set of all utility values is defined as follows: utl = {u1...un} → {0, 100} ui = 100− oi[∗w + b] (3) the aim of the parameter adjustment control system is to find the values of par that maximize all objectives obj and minimizes all utilities utl. in other words, it is to tune all the parameters so all the constraints and objectives are satisfied. 4.2 solving process principle when designing a multi-agent system, the focus is set on agents behaviors and communications in order to cover isolated parts of the global problem. each agent tackles an isolated sub-problem and emergence is used to solve the overall problem. therefore, the solving process is distributed among all agents. every agent introduces a part-wise modelling of the problem and its behavior and communication to other agents is used to solve the global problem. consequently, the definition of agent behaviors is also one of the key aspects of our multi-agent system and is described hereafter. • objective-agents compute a satisfaction value for a target parameter. an objective-agent has a rather simple behavior: it observes its target parameter and uses a satisfaction function to compute a objective satisfaction value. the goal of every objective-agent is to iteratively find a simulation state which yields a satisfaction value above a given minimum threshold. in order to do so, it writes a kvpair to its negotiation-agent, requesting a modification of its observed parameter in a proper way; this kvpair contains only the current objective satisfaction, utility and requested parameter variation sign (either positive or negative). additionally, objective-agents compute the utility value of their proposed request. the utility value is basically a weighted inverse of the corresponding objective value of a parameter. therefore, a utility value represents the degree to which a certain non-satisfied objective should be tackled, resulting in its utility value. • negotiation-agents monitor the objectives and utilities of all corresponding objective-agents of their agent organization. when several requests are received, it will choose the most appropriate parameter modification based on the highest utility value, implementing the english auction principle. 5. domain specific modelling language for defining our graph-based modelling language, the industry notation metacase+ goprr (graphs, objects, properties, relationships and roles) [9] was used. all objects used within goprr are drawn into graphs that contain the object’s role and the relationships thereof. goprr objects can be, for example a process, a thread, a class or an instance of class. a property describes features of graphs, objects, roles and relationships. a relationship connects objects by assigning them roles in the activity of the object. this section will give a short overview of our goprrnotation based modelling approach. the aim of our modelling approach is to graphically describe simulation components as well as agents of our mas. therefore, graphs in our notation can either be the environment, the simulated vehicle or a agent organization. every graph contains objects: agent organizations are constituted of agents whereas vehicle and environment are represented by entities and virtualobjects. virtualobjects are three-dimensional objects which are used to represent certain simulation aspects in the virtual testbed, e.g. a cad vehicle model. every object involves three main concepts: a role, relationships and properties. every entity has one of four roles: environment, interface, vehicle or agent. these define the entity’s role with respect to the aforementioned simulation loop. relationships between objects are expressed by key-value pair exchanges. furthermore, object properties can be arbitrary data, such as numbers or strings. formally, let g = ({environment|v ehicle|agents}, {g}, {o}) (4) be a graph definition with child graphs {g} and objects {o} defined as o = ({entity|agent|v irtualobject}, ro, {re}, {p}) (5) with p = {(datatype, name)} (6) a set of variables, ro = {environment|interface|v ehicle|agent} (7) a role definition and re = {kv pair} (8) set of key-value pairs. all modelling aspects are depicted in figure 5. figure 5: simplified hierarchical depiction of our lightweight dsl approach, based on the goprrnotation. 5.1 code generation template-based code generation (tbcg) [4] is used to generate source code from our pim. tbcg is a generative technology that transforms a given model into source code, through the use of templates. these templates provide a high level of flexibility for the generated output required by custom generation scenarios. furthermore, it is extensively used throughout the industry [4]. a template thereby consists of imperative control and structural source code patterns such as loops or conditional statements. as everything in our virtual testbed is an entity with an homogeneous interface to the overall shared simulation state by accessing a set of key-value pairs, our tbcg aims at generating the read and write processes of all entities. additionally, the cuda code for the mas is directly generated for the specified agent into the corresponding entity specification. pseudo-code 1 gives a brief overview of the entity class generation. the following parameters are derived from the dsl: • ω : all specified entities • α : name of the entity • β : role of the entity (respectively base class) • γ : list of properties, structured as tuples with data type and name • δ : list of key-value pairs which are read by the entity • ε : list of key-value pairs which are written by the entity • ζ : entity type (agent or simulation component) • η : agent data list (non-zero if entity type is agent), structured as tuples with data type and name algorithm 1 generateentityimplementations for ωi ∈ ω do generate header file with derived class α from class β for γi ∈ γ do generate private variable γi − name with γi − type in header file declaration end for generate cpp file with include to class α generate empty read, write and work function of α for δi ∈ δ do generate key-value pool read of key δi for variable γi− name in read function end for for εi ∈ ε do generate key-value pool write of key εi for variable γi − name in write function end for if ζ = agent then generate work function: generate cuda device memory for *device-ηi−name with ηi − type and ηsize with cudamalloc generate host to cuda device memory transfer for device-ηi-name, ηi-name and ηsize with cudamemcpy generate cuda kernel call with ηgrid ηblock and list of device memory device-η-names generate cuda device to host memory transfer for objective, parameter and utility values end if end for 5.2 model validation model validation is, besides code generation, one of the main aspects and benefits of domain specific modelling [27]. it aims at checking whether a model conforms to its specified requirements. as mentioned earlier, the huge complexity of virtual testbeds with the ever increasing amount of software interfaces between simulation, optimization, user interaction and rendering makes interface development tedious and often errorprone. we therefore validate the simulation data flow as it exactly constitutes the internal interfaces of the simulation. this validation check is modelled as finite state machines which are generated by the overall key-value pair access of all entities. we validate three simulation data flow constraints: if a key-value pair is defined and written by one entity, at least one other entity must read it, otherwise the modelling and generation of this key-value pair is unnecessary. analogous, if a key-value pair is being read by at least one entity, one other entity must create this keyvalue pair. in order to prevent invalid user modelling of the virtual testbed, we also validate whether the simulation requirements are not violated: our mas must only change its designated parameters and the simulated vehicle must only perceive its environment by simulated sensor measurements. furthermore, the simulated environment must only retrieve actuator information from the vehicle. figure 6 illustrates these three model validation checks. figure 6: model validation for simulation data flow: a) if a key-value pair x is written by entity a, at least one other entity b must read it from the same graph b) if a key-value pair x is read by entity b, it must be written by another entity a from the same graph c) if data from entity a should be perceived by entity c which is not situated in the same graph as entity a, it has to be transmitted by an interface entity b. 6. application a spacecraft landing procedure is a very complex sequence of autonomous vehicle decisions, actuator commands and sensor data acquisition summarized as guidance, navigation and control. such a landing procedure is an interesting testbed for our proposed approach as it consists of several environmental influences and vehicle internal control loops. we modelled a simplified landing procedure the following way. a spacecraft tries to land on a asteroid surface. the spacecraft is under the influence of solar radiation pressure as well as asteroid gravity. the spacecraft itself has an internal control loop which acquires sensor data: acceleration (accelerometer), orientation (star tracker) and distance to surface (range finder). the overall algorithmic internal spacecraft position estimation is simplified in such a way that ground truth data is used under application of gaussian noise. the spacecraft has three configurable parameters: main engine thrust level in newton, fuel capacity in kg and timings of thrust ignitions. in order to regulate the landing velocity, the spacecraft autonomously fires its main engine if the acceleration exceeds a given threshold. additionally, the spacecraft continuously determines its orientation and fires its attitude thrusters, if the spacecraft orientation to the asteroid surface also exceeds a given threshold. every time the main thrust or control thrust is fired, fuel is consumed and consequently the mass of the spacecraft is lowered. the aim of our optimization is to dynamically tune this spacecraft configuration in order to avoid a crash on the asteroid’s surface as well as to ensure that enough fuel is left when the landing procedure is finished, to leave the asteroid again. additionally, the orientation of the spacecraft has to be aligned to the asteroid surface as the main thruster and landing gear should be perpendicular to the asteroid’s surface. figure 7 shows an example rendering of our virtual testbed. figure 7: example rendering of our approach within kanaria [22]: on-board particle filter localization (color-coded spheres) before landing of our simulated spacecraft. 7. evaluation we have implemented our vehicle simulation and optimization approach in c++ and cuda 7. we performed our experiments on a machine with intel core i7 4-core processor with hyperthreading enabled, nvidia quadro k1000m as well as nvidia gtx 480 and 8gb of ram. we implemented two test scenarios. first, we modelled and generated, based on the previously introduced spacecraft application, our vehicle optimization and simulation. the first test scenario was used to evaluate whether the mas based optimization solves for correct adaptations of the vehicle configuration. second, we implemented synthetic benchmarks for our approach to evaluate overall system performance with respect to vehicle parameter optimization applications. the synthetic test scenario involved two competitors: a traditional non-parallel cpu implementation without the domain framework concept and our domain framework implementation without gpu support. for our synthetic benchmarks, figure 8 shows the mean average computation time for one complete simulation and optimization run. our domain framework approach easily outperforms the traditional cpu based approach. obviously, the speed-up of our approach increases with an increasing number of agents working in the system. additionally, figure 9 depicts the overall speed-up of our domain framework approach showing a speed-up of more than a factor of 60. surprisingly, the difference between cpu based domain framework and gpu integrated version is very small for a few hundred agents. we believe that our wait-free domain framework pays-off well as the concurrent access to the kvpool is highly optimized with respect to the traditional cpu implementation. for our spacecraft landing test scenario, figure 10 shows the simulation objective satisfaction progress over time. our approach is able to increase the satisfaction of all objectives until the simulation successfully ends. figures 11, 12 and 13 show how the main thrust level, fuel capacity and control thrust ignition configuration change over time. our simulation successfully optimizes these parameters until the spacecraft safely lands after seven completed simulation loops with overall 1500 simulation steps. figure 8: computation time for one simulation and optimization run. figure 9: performance speed-up for one simulation and optimization run with respect to the traditional cpu based approach. figure 10: our approach successfully changes the vehicle configuration in order to increase the simulation goal satisfaction. figure 11: our approach gradually increases the thrust level until the velocity can be adequately regulated for landing. figure 12: our approach gradually increases the fuel capacity in order to maintain thrust while the landing procedure is conducted. figure 13: our approach can gradually decreases the ignitions as the overall thrust level is increased by another agent. finally, we are able to generate almost 77 % source code of the aforementioned spacecraft test scenario. currently, there are still some manual code changes for the internal vehicle control loops needed as well as for the satisfaction functions for the multi-agent system. 8. conclusion we have presented a novel comprehensive approach to modelling, simulation, and optimization of vehicles. in our approach, engineers are no longer forced to manually change vehicle configurations. they can describe their vehicle expectations as simulation goals in our dsm framework. these simulation goals are then autonomously tracked and satisfied by our gpu based mas which allows for optimization of vehicle configurations. our mas computes for each simulation step objective and utility values in order to compute an updated vehicle configuration until the specified simulation goals are satisfied. synthetic benchmarks additionally show that our domain framework approach outperforms traditional approaches and that a majority of the virtual testbed source code can be generated from our models. this domain framework is based on our wait-free concurrency control management approach which additionally facilitates easy code generation due to homogeneous and simple access to the shared world state. furthermore, due to the wait-free behavior of our key-value pool approach, even the cpu based implementation can be used for sophisticated real-time simulations. however, the question remains unresolved if our mas approach can solve any set of simulation goals as mas do not necessarily compute the global maximum of a parameter space. the emergence of mas could also lead to wrong optimizations if, for example, the satisfaction functions are insufficiently implemented. therefore, a generic modelling concept for objective satisfaction functions would greatly improve the overall usability as well as code generation of our approach. in addition, the development of algorithms for autonomous retrieval of parameter simulation goal relationships would further decrease the development time and increase the overall flexibility of our concept. to conclude, we also think that our framework, including domain specific modelling, gpuassisted mas and code generation, can be applied to other domains as long as parameter-based objective and utility values for simulation goals can be computed. 9. acknowledgments this research is based upon the project kanaria, supported by german aerospace center (dlr) with funds of the german federal ministry of economics and technology (bmwi) under grant 50na1318. 10. references [1] a. kleppe, w. bast, j. warmer: mda explained: the model driven architecture: practice and promise. in: addison wesley pub co inc (2003) [2] a. zook, s. lee-urban, k. w. brawner: automated scenario generation: toward tailored and optimized military training in virtual environments. in: proceedings of the international conference on the foundations of digital games (2012), s. 164–171 [3] b. g. alaby, k. s. perumalla, s. k. seal: efficient simulation of agent-based models on multi-gpu and multi-core clusters. in: simutools 2010 3rd international conference on simulation tools and techniques (2010) [4] c. henthorne, e. tilevich: code generation on steroids: enhancing cots code generators via generative aspects. in: proceedings of the second international workshop on 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integrated command and control centre in indian cities saoni sanyal1,*, dr. nilanjana dasgupta sur2 1 department of urban planning, spa delhi, addressmaster para, postkatwa, districtburdwan, west bengal 713130 2 department of urban planning, spa delhi, addressdepartment of urban planning, school of planning and architecture, 4 block b, i.p estate, new delhi 110002 abstract the integrated control and command centre (iccc) is instrumental in enhancing global cities' efficiency, resilience, and sustainability as the central hub for urban management. by integrating diverse technological solutions and data sources, the iccc enables real-time monitoring, analysis, and control of urban systems, aiding informed decision-making in city planning. urban planners leverage the iccc to assimilate data from various sectors such as traffic management, public safety, utilities, and environmental monitoring, fostering a holistic understanding of urban dynamics. this data-driven approach empowers planners to anticipate challenges, identify trends, and devise effective strategies for sustainable development, including optimizing traffic flow and implementing targeted interventions for environmental sustainability. moreover, the iccc serves as a centralized platform for emergency response and fosters citizen engagement through smart governance tools, enabling residents to access real-time information and provide feedback. however, challenges like lack of infrastructure, governance, funding, and skills hinder its holistic implementation. as technology continues to advance, the role of the iccc will evolve, presenting new opportunities for innovation and sustainable urban development. proposed in all smart cities of india under the smart cities mission, integrated control and command centres (icccs) are operational in 100 cities, with agartala, indore, and vadodara highlighted for sustainable business models. yet, challenges persist in creating comprehensive iccc models. therefore, the main objective of this paper is to investigate and strategize the implementation of icccs in indian cities for improved governance and urban resilience. keywords: integrated control and command centre (iccc), smart cities, infrastructures development received on 30 may 2024, accepted on 03 october 2024, published on 06 november 2025 copyright © 2025 saoni sanyal et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.6204 1. introduction india is experiencing a rapid surge in urbanization, with approximately 34% of its population now residing in cities, a stark increase from just 18% in 1960[1]. this significant urban growth has brought forth a myriad of critical challenges for the country's urban centres. among these challenges are the proliferation of slums, inadequate local governance structures, financial instability, and deficient *corresponding author. email: saonisanyal1999@gmail.com urban planning, leading to soaring housing and office space costs[2,3]. compounding these issues is the prevailing administrative framework, primarily orchestrated from the national or state level, which may not fully comprehend the intricate dynamics of a densely populated urban economy. this centralized approach often results in overlapping service responsibilities and a dearth of localized decisionmaking power. moreover, the imperative for climateresilient economic development further amplifies the complexity of the economic and structural obstacles confronting indian cities. consequently, there is a eai endorsed transactions on smart cities | volume 7 | issue 4 | 2025 | https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:saonisanyal1999@gmail.com saoni sanyal, nilanjana das gupta sur 2 mounting demand for devolved, decentralized control over urban economies and more robust urban planning mechanisms to foster inclusive and resilient economic growth†. scholars and policymakers are actively examining the political implications of urbanization and its associated challenges, striving to develop actionable strategies to address issues like regional disparities, environmental degradation, and social inequity[4]. indian cities grapple with a range of challenges stemming from high population density, inadequate infrastructure, and rapid urban growth. these challenges include urban slum expansion, strained water and sanitation systems, and reduced quality of life. centralized administrative structures often struggle to grasp urban complexities, leading to overlapping service responsibilities and limited local control [2,5]. tackling these issues requires a focus on inclusive economic growth, decentralized governance, and climateresilient development. population growth exacerbates congestion and strains public services, especially housing and transportation. rural migration adds to these pressures, underscoring the urgency of sustainable urban development strategies that ensure fair resource access. despite obstacles, indian cities offer opportunities for innovative solutions and holistic urban planning that prioritize resident well-being and environmental sustainability in the long run. the need for effective city management and robust emergency response systems underscores the importance of integrated command and control centres (icccs) in indian cities. as urbanization accelerates and cities become more complex, efficient management of resources, infrastructure, and public services becomes imperative. iccc serves as a central hub where data from various city systems, such as transportation, public safety, and utilities, are integrated and analysed in real-time. this integration allows for proactive decision-making, rapid response to emergencies, and optimization of city operations. by coordinating efforts across different agencies and stakeholders, iccc enhances overall city resilience, improves public safety, and ensures better utilization of resources. in india's dynamic urban landscape, investing in integrated command and control centres (icccs) is vital for fostering sustainable cities capable of addressing urban challenges. significant progress has been made under initiatives like the smart cities mission, digital india project, and national e-governance plan (see figure 1). the iccc initiative in india has been implemented in several phases, with 20 cities selected in phase 1, known as "lighthouse cities," and 13 cities in the fast track round of phase 2 as depicted in figure 1. the iccc project covers various sectors such as e-governance, smart transport, heritage, and city surveillance. the lighthouse cities are expected to provide valuable learning experiences for the smart city project implementations. the iccc awards recognize the impact and thematic components of the initiative, aiming to capture the sectoral as well as crosssectoral aspects. the program has faced challenges but has delivered tangible results, contributing to the urban transformation of the participating cities[6]. however, despite these advancements, there remain notable gaps in knowledge and areas requiring further exploration within the indian context. one such area is the need for deeper research into the scalability and sustainability of iccc implementations across diverse urban landscapes in india. even though the iccc project's early phases have yielded insightful information, it is imperative to assess these centres’ long-term efficacy and flexibility, particularly in smaller areas. furthermore, little study has been done on how iccc interventions affect socioeconomic factors, particularly those related to community involvement, equity, and inclusivity[7]. furthermore, given the rapid technological advancements, ongoing research is essential to identify emerging technologies and best practices for enhancing the resilience and functionality of iccc systems in addressing evolving urban challenges. india can reinforce its activities under the international council of chemical cycles (iccc) and guarantee their continued relevance and efficacy in promoting sustainable urban development by tackling these knowledge gaps and encouraging joint research and innovation. problem statement: rapid urbanization in indian cities poses significant challenges in both infrastructure and administrative sectors. to address these issues and establish an efficient and transparent governance system, the exploration of integrated tools becomes imperative, with integrated control and command centres (icccs) serving as crucial planning instruments to effectively harness and coordinate diverse urban data sources. therefore, the aim of this paper is to thoroughly investigate and strategize the implementation of icccs within the urban framework of indian cities. to achieve this aim, four main goals have been meticulously studied step by step. firstly, to analyse existing research to understand the foundational design principles and architectural frameworks of icccs. secondly, to develop a cyclical framework outlining the key operational stages of an iccc for efficient urban management. thirdly, to examine the implementation and impact of icccs in indian cities, highlighting best practices and lessons learned. lastly, to formulate a detailed implementation plan to integrate icccs with administrative structures for enhanced eai endorsed transactions on smart cities | volume 7 | issue 4 | 2025 | planning for integrated control and command centres in indian cities 3 governance and urban resilience. through these goals, this paper seeks to provide comprehensive insights and strategies for the effective deployment of iccc in indian urban local bodies. figure 1. smart city with integrated control and command centre projects in different rounds 2. literature review on design and architecture of iccc in the field of urban planning in india, integrated control and command centres (icccs) function as centralized hubs for real-time data monitoring and decision-making, enhancing the efficiency and resilience of city management in the face of evolving urban environments. these centres are crucial in addressing urban issues such as traffic congestion and public safety, thereby promoting sustainable and inclusive urban development. moreover, studies emphasize the significance of collaborative governance frameworks and technological innovations, including the integration of ai and iot, in maximizing the effectiveness of iccc operation. 2.1. concepts and definition an integrated command and control centre (iccc): is a centralized facility that integrates information and communication technologies (ict) to enable the monitoring, analysis, and management of various operations and activities. it serves as the "brain and nerve centre" for organizations, providing a comprehensive overview of the situation and facilitating real-time decision-making(8) 2.2 conceptual cyclical framework of an iccc an iccc operates within a cyclical framework comprising four main stages. as described in figure 2 • firstly, in the data acquisition and integration stage, data is collected from diverse sources like sensors, cameras, databases, and social media. this data, whether structured or unstructured, undergoes preprocessing steps such as cleaning and filtering before integration into the system. • secondly, in the information analysis and visualization stage, collected data is analysed using various tools like data visualization dashboards and artificial intelligence algorithms to identify trends and potential threats. the processed information is then presented for operators' understanding. • thirdly, in the decision making and collaboration stage, operators collaborate and make informed decisions based on the analysed information, often utilizing decision support systems. communication and collaboration tools facilitate discussions and coordinated actions. • lastly, in the action and response stage, decisions are translated into actions, like resource deployment or issuing alerts. the effectiveness of these actions is monitored, and the cycle restarts with data acquisition to assess impact and adapt further actions if needed. the four stages of iccc operated cyclical framework is given below in figure 2. the specific components and functionalities of an iccc will vary depending on the organization's needs and the nature of its operations. security and privacy are crucial considerations in designing and operating an iccc. training and user support are essential for ensuring effective utilization of the iccc. figure 2. stages of iccc process source: integrated command and control centre – smartnet, niua 2.3 architectural layout and technology choices eai endorsed transactions on smart cities | volume 7 | issue 4 | 2025 | saoni sanyal, nilanjana das gupta sur 4 the architecture layout and technology choices can be divided into the same cyclic stage-wise division for better understanding. 2.3.1 stage 1 data acquisition and integration a. data acquisition –  architectural layoutnetwork design has been initiated, with mention made of the positioning of cctv cameras, sensors, and cameras, as well as the integration of main stakeholder offices, utilizing databases sourced from social media. these components are primarily intended for the collection of raw data, both structured and non-structured.  technology choicesreal time data capture from different sources such as cameras, weather stations, cctv, sensors, traffic monitor station (traffic plat reorganization and real time update cameras)(9) b. data transfer and storage  architectural layoutdata are transferred through fibre network cables, which are primarily stored in data lakes and warehouses for the subsequent stage of data filtering and integration.  technology choices  apache kafka: a streaming platform for handling high-volume data streams.  hadoop: a framework for storing and managing large datasets. c. data integration –  architectural layoutdata are extracted, transformed, and loaded between systems (which can include informatica power centre, talend open studio, and api management platforms) to facilitate communication between disparate systems and applications. data quality tools are utilized in this process(10).  technology choices  apache spark: a distributed computing framework for large-scale data processing.  trifacta wrangler, open refine  etl/elt tools (e=extract, t=transform, l=load)  api management platforms  data quality tools 2.3.2 stage 2 information analysis and visualization  architectural layoutstreaming analytics engines are employed to analyse data streams in real-time, and data mapping and transformation are also conducted at this stage, where it is defined how data will be transformed and mapped to target systems. following this, a second level of data integration is performed(11).  technology choices  tableau and power bi: business intelligence tools for data visualization and reporting.  amazon kinesis and microsoft azure stream analytics: cloud-based platforms for real-time data analytics.  ibm watson and google cloud ai platform: ai platforms for developing and deploying machine learning models. 2.3.3 stage 3 decision making and collaboration a. decision making –  architectural layouthistorical data can be analysed and future outcomes predicted by data algorithms, aiding in risk assessment, resource allocation, and proactive decision-making. real-world scenarios are simulated by systems like vbs3 and unity, enabling teams to practice and evaluate different decision paths before deployment.  technology choices  machine learning and artificial intelligence (ai)  simulation and modelling tools (vbs3)  augmented reality (ar) and virtual reality (vr) ((dataversity data integration for integrated command and control centres: 2023)(9) b. collaboration–  architectural layoutaudio-visual meeting rooms and conference rooms should be provided for online/offline meetings with various stakeholders. sharing best practices, lessons learned, and operational updates can be facilitated through platforms with secured chat systems. situational awareness platforms such as esri arcgis and sap situation room offer a shared view of the operational environment, including real-time data, maps, and critical alerts, thereby promoting coordinated action.  technology choices  blockchain technology: securely storing and sharing sensitive data across organizational boundaries  platform like microsoft team, zoom, google meet for video conferencing  miro, mural platform offers virtual whiteboards and shared digital canvases for brainstorming 2.3.4 stage 4action and response a. action and response–  architectural layoutfor communication and alerting, a mass notification system such as everbridge or one platform can be utilized to send emergency alerts quickly and reliably to a diverse audience. platforms like servicenow and bmc helix itsm enable incident tracking, task assignment, and coordination of response efforts across teams. realtime updates and instructions are visually disseminated through displays in public areas, guiding occupants during emergencies. specialized software can be introduced, providing mobile command posts with comprehensive tools for eai endorsed transactions on smart cities | volume 7 | issue 4 | 2025 | planning for integrated control and command centres in indian cities 5 tracking resources, visualizing the operational environment, and coordinating response activities.  technology choices  mass notification system  incident management system (ims)  digital signage and public information displays  command post applications b. security–  architectural layoutthe vast amount of processed data must be secured throughout the process. to achieve this, restricted data access control is required, which restricts access to sensitive data based on user roles and permissions. data encryption is also necessary. additionally, auditing and logging are needed to track data access and modifications for traceability and compliance.  technology choices  data access control  data encryption  auditing and logging. by carefully selecting technology choices and incorporating scalability considerations into the design of an iccc, cities can build a resilient and future-proof system capable of effectively managing urban operations and adapting to evolving challenges and opportunities(8,12) 2.4 integrated control and command centres in indian cities (national case study) all 100 smart cities in india have operational integrated command and control centres (icccs) as of 2023, as confirmed by the india smart cities awards contest (isac) 2022 organized by the ministry of housing and urban affairs(13). however, a comprehensive assessment requires in-depth analysis of individual icccs and their performance across all imaf dimensions. the iccc maturity assessment framework (maf), developed by the smart cities mission, is a tool to assess the maturity level of icccs across various aspects like functionality, technology, governance, and citizen engagement. it uses a scoring system to categorize icccs into levels of maturity (level 1 emerging, level 2 developing, level 3 mature, and level 4 leading). so according to this framework, some icccs might excel in specific areas like technology but lag in citizen engagement or governance, affecting their level of maturity. the current status of few cities in india who has operational iccc’s in place have been given below: 2.4.1 pune integrated control and command centre the pune integrated command and control centre (iccc), inaugurated in 2020 on a site area of 27,348 square feet, boasts a built-up area with key infrastructure components covering 1,683.7 square feet of floor space. it accommodates 24 workstations for operators, a noc room with six workstations, a conference room, a data centre facility, and an impressive 3x2 video wall. with a total of 80 members, this collaborative effort involves stakeholders including smart city development corporation limited, pune municipal corporation, pune police, pune mahanagar parivahan mahamandal limited, and the pune metropolitan region development authority (pmrda), along with active citizen participation. the pune iccc enhances citywide monitoring and response capabilities across several areas and is a tribute to effective municipal governance and technological integration. 2.4.2 ahmedabad integrated control and command centre the ahmedabad integrated command and control centre (iccc), inaugurated in 2019 on a 4181 square meter plot, features a total built-up area of 2239 square meters. its infrastructure components cover 521 square meters, emphasizing disability-friendly design and housing essential facilities such as a meeting room, conference hall, cafeteria, server room, and an impressive 9x3.55-inch led video wall. the center is dedicated to the implementation of digital services and public grievance redressal, fostering public awareness through a communication and citizen information outreach system using video management devices (vmd). with a membership of 89 individuals, the project's main stakeholders include smart city limited, the municipal corporation, the police, and actively engaged citizens. the ahmedabad iccc stands as a testament to comprehensive urban governance, employing advanced technology for efficient citywide services and management. 2.4.3 jabalpur integrated control and command centre the command-and-control centre in jabalpur serves as a comprehensive hub for managing city operations, aimed at enhancing citizen welfare. powered by information & communication technologies, it ensures seamless integration of smart components. operating under jabalpur smart city limited (jscl) at old transport nagar, the facility spans three stories with over 10500 square feet of built-up area. it features cutting-edge it infrastructure, including a 30x9 square foot video wall, 18 pri telephone lines with recording, and a conference room accommodating 50 individuals. with ample internet leased line and mpls connectivity, stakeholders such as jabalpur municipality corporation, jabalpur smart city limited, and jabalpur police corporation benefit from its services. table 1. comparison matrix of indian iccc with assessment framework eai endorsed transactions on smart cities | volume 7 | issue 4 | 2025 | saoni sanyal, nilanjana das gupta sur 6 case study city capab ility assess ment stage 1 stage 2 stage 3 stage 4 services covered pune integr ated contro l and comm and centre functi onal data acquis ition and visuali zation capabi lity data analyti cs and corelation capabi lity assess ment comm unicati on comm and & control capabi lity assess ment 1. transport intelligen t traffic monitori ng system smart parking, number plate recogniti on, red light violation detection, and cctv surveilla nce 2. social infrastruc ture booking facilities high mediu m mediu m mediu m techn ologica l data acquis ition config uration layer/ sop data analyti cs and corelation layer comm and and control layer high mediu m mediu m mediu m gover nment govern ance frame work suppor t to field force decisio n makin g frame work knowl edge manag ement low high mediu m low ahmed abad integr ated contro l and comm and centre funct ional data acquis ition and visuali zation capabi lity data analyti cs and corelation capabi lity assess ment comm unicati on comm and & control capabi lity assess ment 1. physical infrastruc ture solid waste manage ment system gps vehicle monitorin g system wash efficient managem ent of water supply. 2. citizen awarenes s mobile app 3.transp ort monitorin g mrts, brts intelligen t traffic monitori ng system high high mediu m mediu m techn ologic al data acquis ition config uration layer/ sop data analyti cs and corelation layer comm and and control layer high high high mediu m gover nment govern ance frame work suppor t to field force decisio n makin g frame work knowl edge manag ement mediu m high mediu m high jabalp ur integr ated contro l and comm functi onal data acquis ition and visuali zation capabi lity data analyti cs and corelation capabi lity comm unicati on comm and & control capabi lity assess ment 1. physical infrastruc ture solid waste manage ment and centre assess ment system vehicle tracking system 2. transport intelligen t traffic managem ent system (itms), chalo app public vehicle monitorin g, chalan generatio n for traffic rule violation. mediu m low low low techn ologica l data acquis ition config uration layer/ sop data analyti cs and corelation layer comm and and control layer low low low low gover nment govern ance frame work suppor t to field force decisio n makin g frame work knowl edge manag ement mediu m low mediu m low source: maturity assessment framework and toolkit to unlock the potential of integrated command and control centres, 2018 and author upon reviewing the data presented in table 1, it becomes apparent that the indian integrated city command and control (iccc) system predominantly faces challenges in technological advancement and government support. while the initial stage of data acquisition tends to be wellestablished, there is a notable deficiency in subsequent stages such as data analysis and decision-making processes. a key contributing factor to this gap is the shortage of skilled professionals in planning roles within the iccc, municipality, and smart city entities. the lack of comprehensive analysis often leads to inaccurate decisionmaking and underutilization of infrastructure resources. addressing this issue requires an emphasis on capacitybuilding programs for municipal personnel and staff, alongside increased public awareness campaigns to promote the adoption of digital services. these efforts aim to transition towards sustainable, paper-free urban local body (ulb) infrastructure, fostering more efficient and effective governance processes. 2.5 integrated control and command centres in international context iccc not only enhances city management and public safety but also holds the potential to bring about positive social, economic, and environmental transformations, aligning with the evolving needs of india's dynamic urban landscape. these has been demonstrated by different global cities through best practices. some have been listed below: eai endorsed transactions on smart cities | volume 7 | issue 4 | 2025 | planning for integrated control and command centres in indian cities 7 2.5.1 rio operations centre, rio de janeiro, brazil established in april 2010, the rio operations centre emerged as a pivotal initiative for enhancing the resilience of rio de janeiro. triggered by the devastating consequences of heavy rains leading to landslides and the loss of 68 lives, the centre, inaugurated in december 2010, aimed to integrate daily city operations and manage crises effectively. designed with technological expertise from partners like ibm, bilfinger, cisco, samsung, and google, the operations centre employs google earth technology for georeferenced data integration. the control room, equipped with a 60m² video wall, enables 200 controllers in three shifts to monitor the city in real time. the crisis room facilitates emergency meetings, while the press room ensures constant communication with the media. the 1746 hot line encourages citizen engagement, allowing reporting on city services and receiving information. operating in three key areas—risk prevention and management, daily city operations, and major events— the centre has significantly reduced emergency response times by 30%. to process the generated data, the city hall introduced the big data department "pensa – ideas room" in june 2013, fostering research and analysis for improved service delivery. the rio operations centre, with an initial cost of r$20 million, represents a collaborative effort involving nearly 30 city departments, public agencies, and utility companies, achieving notable impacts such as a 30% reduction in emergency response times and enhanced efficiency in public transportation. overcoming barriers like departmental rivalries and information withholding, the centre stands as a dynamic model of integrated decision-making, contributing to the daily learning process and resilience of rio de janeiro. continuous training and simulation exercises address the challenge of qualified human resources, ensuring the centre’s effectiveness in managing diverse urban challenges(14). 2.5.2 integrated centre for security and emergency in madrid (cisem), madrid, spain) in the wake of the major terrorist attack on madrid's commuter trains in march 2004, which underscored the critical need for enhanced coordination among first responders, the city of madrid initiated a comprehensive project to establish a unified command and control centre for security and emergency services. the lack of centralized command and control during the 2004 incident highlighted the necessity for a system capable of organizing a unified response to multiple incidents simultaneously. the project, launched in 2005 and completed in 2007, integrated physical and technological components to support security and emergency services. ibm provided the software for a service-oriented architecture (soa), enabling seamless coordination among first responder agencies. the command-and-control centre, developed by global technology company indra, consolidated information from various sources, including video feeds and mobile computers. a common mobile infrastructure was deployed to ensure interoperability among different agencies, and a multilayered, redundant communications infrastructure was established to ensure continuous communication. the project, with an approximate cost of 20 million euros, significantly improved emergency management capabilities in madrid. the integration of systems and data sources provided emergency managers with a comprehensive view of situations, reducing confusion and enabling faster decisionmaking. this resulted in a 25% reduction in response time, as managers could deploy the right assets more efficiently. the project faced challenges in integrating various applications used by different entities and external organizations, but its success demonstrated the transformative impact of an integrated approach to emergency management(14). table 2. comparison matrix of international icccs with assessment framework case stud y city capab ility assess ment stage 1 stage 2 stage 3 stage 4 services covered rio ope rati on cen tre functi onal data acquis ition and visuali zation capabi lity data analyti cs and corelation capabi lity assess ment comm unicati on comm and & control capabi lity assess ment emergency operation centre, cctv surveillance, public awareness, 2. transportation public vehicle monitoring high high high high techn ologica l data acquis ition config uration layer/ sop data analyti cs and corelation layer comm and and control layer high high high high gover nment govern ance frame work suppor t to field force decisio n makin g frame work knowl edge manag ement high high high high inte grat ed cen tre for sec urit y functi onal data acquis ition and visuali zation capabi lity data analyti cs and corelation capabi lity assess ment comm unicati on comm and & control capabi lity assess ment safety and security, reducing confusion in emergency situation and faster decision making. high high high high eai endorsed transactions on smart cities | volume 7 | issue 4 | 2025 | saoni sanyal, nilanjana das gupta sur 8 and em erge ncy in ma drid techn ologica l data acquis ition config uration layer/ sop data analyti cs and corelation layer comm and and control layer high high high high gover nment govern ance frame work suppor t to field force decisio n makin g frame work knowl edge manag ement high high high high source: maturity assessment framework and toolkit to unlock the potential of integrated command and control centres, 2018 in international case studies, a key distinction observed in integrated command and control centres (icccs) lies in their approach to control various aspects of infrastructure with greater detail and efficiency (table 2). these systems often focus on smaller segments of infrastructure, emphasizing technological advancement and effective fund allocation. additionally, training and capacity-building programs for staff play a crucial role. in contrast, many indian cities typically have a single iccc that oversees smaller parts of each infrastructure domain, potentially obscuring the city's overall needs and gaps. to develop a functional iccc algorithm for a specific city, a comprehensive gap analysis assessment is necessary. this assessment would prioritize infrastructure programs based on their ranking and determine the level of detail required for integration with the iccc. 3. challenges and considerations implementing and operating an integrated command and control centre (iccc) in indian cities presents challenges related to governance, data privacy, and cultural acceptance. inter-departmental coordination, data sharing concerns, and perceptions of surveillance versus inclusive governance hinder its deployment, despite its successes in enhancing safety, security, and urban services. therefore, building a mature iccc across various aspects, including functionality, technology, governance, and citizen engagement, presents several challenges for indian cities(15). they are: 3.1 functionality • limited integration and data sharing: silos between departments and agencies lead to incomplete data capture and hinder holistic view of the city's operations. • lack of standardized operating procedures: inconsistent responses to incidents and inefficient resource allocation due to absence of standardized protocols. • inadequate manpower and training: insufficient personnel with expertise in operating and maintaining the complex functionalities of icccs. 3.2 technology • cybersecurity concerns: ensuring data security and system resilience against cyberattacks requires robust solutions and continuous updates. • outdated technology infrastructure: legacy systems lacking compatibility with newer technologies create challenges in integration and scalability. • financial constraints: limited budgets restrict access to advanced technology solutions essential for enhancing iccc capabilities(16). 3.3 governance • interdepartmental coordination issues: lack of efficient collaboration between agencies leads to delayed decision-making and hinders effective response to critical situations. • accountability and transparency concerns: unclear ownership of responsibilities and lack of transparent reporting raise concerns about accountability. • legal and regulatory framework: evolving legal and regulatory landscape surrounding data privacy and technology use requires constant adaptation and updates(17). 3.4 citizen engagement • limited awareness and participation: lack of citizen awareness about icccs and their functionalities reduces opportunities for meaningful participation. • communication gaps: ineffective communication channels and strategies hinder smooth information flow between citizens and authorities. • digital divide: unequal access to technology and digital literacy creates barriers for certain sections of the population to engage with icccs(8). 3.5 additional challenges • sustainability: ensuring long-term financial and operational sustainability of icccs requires robust funding mechanisms and efficient resource management. • performance measurement: establishing clear metrics and tracking progress in all aspects of iccc maturity presents a challenge. • scalability and adaptability: adapting icccs to evolving needs and challenges in rapidly growing urban environments requires constant upgrades and flexibility. eai endorsed transactions on smart cities | volume 7 | issue 4 | 2025 | planning for integrated control and command centres in indian cities 9 • community involvement: icccs have the potential to enhance community engagement by leveraging social media platforms like twitter and whatsapp for public participation in decision-making and emergency response. for example, icccs aim to implement community protection programs with volunteers, develop community alert systems, and conduct simulation exercises in public schools to create safer neighbourhoods. while these initiatives remain largely conceptual in india, a glimpse of their effectiveness was seen during the covid-19 pandemic, when icccs acted as control centres— connecting hospitals, helplines, and blood banks, while ensuring basic support for the elderly and covid patients(14). 4. comprehensive plan for implementation and coordination of iccc with administrative structure in indian cities 4.1 designing framework for functional iccc in the design of integrated command and control centres (icccs) in indian cities, the selection of site location is crucial, often placing them near urban local body (ulb) offices, smart city infrastructure, and other stakeholder buildings. this positioning ensures secure data transfer between various entities. however, longer distances between sites necessitate additional investments in secure technology, wi-fi, and jammer infrastructure, thereby increasing project costs. with a fixed budget of ₹150 crore from the smart city initiative and ₹170 crore from the ministry of electronics and information technology, stakeholders' input is essential to ensure transparent data transfer and adherence to government regulations. the ideal design framework developed from various case studies is provided below (table 3): table 3. ideal design framework for integrated control and command centre. topic minimum maximum site location middle of the city outskirt of the city distance 1 km radius of fire department, police department, collectorate office and municipal corporation 2.5 km radius site area 4200 sqm floor area 500 sqm 800 sqm staff member 75 85 main components conference room, meeting room, data centre, control room, storage, cafeteria, server room total budget 200 cr 250 cr time period (phases) • phase 1: pre construction phase – 170 days. • phase 2: building construction phase 190 days • phase 3: equipment installation – 280 days. • phase 1: pre construction phase –180 days. • phase 2: building construction phase 250 days • phase 3: equipment installation – 300 days. number of department 4 (physical infrastructure, mobility and transportation, environmental and disaster management, housing infrastructure property tax management) 7 (extra involved department – energy and telecommunication – e-taxation, heritage tourism, social infrastructure) stakeholders municipal corporation, development authority, tcpo, smart city limited, police department, citizen, pwd, government institutions (school, colleges, university), hospitals, medical universities. all social infrastructure facilities, commercial facilities (hotels, retail shops), ngos source: authors 4.2 implementation plan for a successful integrated control and command centre the successful implementation of an integrated command and control centre (iccc) in indian cities requires a strategic and systematic approach. this section outlines the key steps involved in the implementation process, including pre-implementation; planning and strategy; implementation; execution and management; monitoring and evaluation; project submission and o&m; and phasing. by following these steps, cities can effectively deploy and operate an iccc, thereby enhancing their ability to address urban management challenges and improve the overall quality of life for residents. 4.2.1 pre-implementation • land identification: identify suitable land or facilities for establishing the iccc based on accessibility and infrastructure requirements. • consultation and designing: engage urban planners, architects, and technology experts to design the layout and infrastructure blueprint for the iccc. eai endorsed transactions on smart cities | volume 7 | issue 4 | 2025 | saoni sanyal, nilanjana das gupta sur 10 • building permission and plan approval: obtain necessary permits and approvals from local authorities for construction and implementation. • stakeholder identification and engagement: engage with all stakeholders, including government bodies, private partners, community representatives, and technology experts. 4.2.2 planning and strategy • policy formulation and governance structure: establish a governance structure defining roles and responsibilities, building regulations • technical planning and infrastructure design: collaborate with technology partners to design and finalize the technical infrastructure required for the iccc • contract/tendering: initiate the process of tendering and selection of contractors based on predefined criteria. 4.2.3 implementation • project management office (pmo) setup: set up a dedicated pmo responsible for overseeing project execution, resource allocation, and adherence to timelines. • execution and implementation: begin the construction and installation of hardware, software, networking infrastructure, and operational facilities. • operations and maintenance planning: develop standard operating procedures (sops) for the day-today functioning and long-term maintenance of the iccc. 4.2.4 execution and management • data management and analytics: establish robust protocols for collecting, storing, and analysing data from various sources within the iccc framework • community engagement and training: conduct outreach programs to educate citizens about the iccc's functions and benefits. provide training sessions for staff and stakeholders on utilizing iccc tools effectively(10). 4.2.5 monitoring and evaluation • performance monitoring: implement kpis to measure the effectiveness of the iccc in achieving its objectives. regularly monitor and assess the system's performance against these kpis. • feedback and iterative improvements: gather feedback from stakeholders and citizens to identify areas for improvement. use feedback to enhance the functionalities and operations of the iccc. 4.2.6 project submission and o&m • project submission to smart city: compile project reports, compliance documents, and necessary certifications for submission to the smart city governing body. • operations and maintenance (o&m): commence the o&m phase to ensure continuous functionality and sustainability of the iccc as per established protocols. in conclusion, the implementation of an integrated command and control centre (iccc) in indian cities requires a multifaceted approach, as outlined in the preceding steps. by meticulously following these steps, cities can effectively deploy and operate an iccc, thereby enhancing their urban management capabilities and fostering resilience. this structured approach ensures that cities are well-equipped to address evolving urban challenges and meet the needs of their residents efficiently. 4.3 enhancing administrative coordination through integrated command and control centers (iccc) the integration of administrative structures with integrated command and control centres (iccc) is pivotal for ensuring efficient urban governance. figures 1 and 2 exemplify how administrative coordination enhances management across both physical and social infrastructure through the iccc framework. in the domain of physical infrastructure, such coordination facilitates streamlined decision-making, enabling prompt responses to infrastructure projects, maintenance needs, traffic management, and disaster mitigation efforts. by fostering synergy among administrative bodies, the iccc ensures cohesive planning and execution of initiatives aimed at enhancing the city’s-built environment and infrastructure resilience. similarly, administrative integration plays a critical role in managing social infrastructure, including vital services like healthcare, education, and emergency response (figure 2 & 3). through effective coordination, cities can optimize resource allocation, improve service delivery mechanisms, and bolster emergency response capabilities within these essential sectors. by harnessing the capabilities of the iccc to foster seamless communication, collaboration, and decision-making among administrative entities, cities can navigate complex urban challenges more effectively. this integrated approach not only enhances the overall resilience and functionality of urban systems but also fosters a more responsive and inclusive governance framework, crucial for the sustainable development of cities. eai endorsed transactions on smart cities | volume 7 | issue 4 | 2025 | planning for integrated control and command centres in indian cities 11 figure 3. iccc work structure for stolen vehicle case source: integrated control and command centre bhopal , 2019 figure 4iccc work structure for fire incident reporting source: integrated control and command centre bhopal , 2019 5. conclusion despite its recognized potential as a crucial tool in urban planning and city management, the iccc faces underutilization, stemming from a lack of awareness and knowledge among stakeholders. the paper underscores the critical need for capacity building and training programs to equip staff with the requisite skills for effective iccc utilization. furthermore, it emphasizes the necessity of enhancing citizen awareness regarding the role of iccc in their daily lives, advocating for the efficiency and expediency of digital workflows. the proposition extends to educational institutions, urging them to integrate awareness programs into their curricula, emphasizing the vulnerability of cities to cyber security issues and the pivotal role of iccc in mitigating such threats. the conclusion posits that substantial investment is imperative in fostering iccc utilization, not only to fortify urban resilience but also to bridge the knowledge gap hindering its full potential. by advocating for increased awareness, training initiatives, and strategic investments, the paper advocates a holistic approach to unlock the true transformative power of iccc in shaping resilient, efficient, and digitally empowered indian cities. acknowledgements. we would like to express our sincere gratitude to all the individuals and organizations who contributed to the successful completion of this study on the role of integrated control and command centres (iccc) as a crucial tool for urban planning. first and foremost, we extend our heartfelt appreciation to the personnel of the smart city initiatives and the municipal corporations of the case study cities. your invaluable cooperation, insights, and access to data were fundamental to our research. the dedication and expertise demonstrated by the officials in these cities have significantly enriched our understanding of the operational dynamics and strategic significance of icccs in urban governance. we are also deeply grateful to the national institute of urban affairs (niua) for their comprehensive report on the maturity framework. this report provided a robust analytical foundation that was instrumental in shaping the theoretical and practical dimensions of our study. the maturity framework offered critical benchmarks and performance indicators that guided our assessment of the icccs' efficacy and maturity in various urban contexts. this study is a testament to the collaborative efforts of all these individuals and organizations, whose contributions have been indispensable. we hope our findings will contribute to the ongoing discourse on urban planning and the strategic deployment of integrated control and command centres. references [1] coleman j. india’s urbanisation challenge [internet]. oxford policy management. 2018 [cited 2025 sept 10]. available from: https://www.opml.co.uk/insights/indiasurbanisation-challenge [2] 2. linnea garcía k. understanding india’s urban future [internet]. penn today. 2023 [cited 2025 sept 10]. available from: stolen vehicle tracking fire incident report working process eai endorsed transactions on smart cities | volume 7 | issue 4 | 2025 | saoni sanyal, nilanjana das gupta sur 12 https://penntoday.upenn.edu/news/understanding-indiasurban-future [3] nandi s, gamkhar s. urban challenges in india: a review of recent policy measures. habitat int [internet]. 2013 july [cited 2025 sept 10]; available from: https://www.researchgate.net/publication/257053237_urba n_challenges_in_india_a_review_of_recent_policy_meas ures [4] world bank group. india’s urban challenges [internet]. world bank group who we are. 2014 [cited 2025 sept 10]. available from: https://www.worldbank.org/en/news/feature/2011/07/04/in dias-urban-challenges [5] nijman j. india’s urban challenge. eurasian geogr econ. 2012 jan;15. [6] dwivedi g. smart cities mission in india footprints of international financial institutions [internet]. [cited 2025 oct 14]. available from: https://www.cenfa.org/wpcontent/uploads/2019/07/smart-cities-booklet-final.pdf [7] morth. integrated command and control centers operationalized in all 100 smart cities for better monitoring and coordination [internet]. pib, delhi; 2023. available from: https://www.pib.gov.in/pressreleaseiframepage.aspx?pri d=1907135 [8] uchoi e, debbarma k. smart cities survey: based on integrated command and control center. int j sci dev res ijsdr. 2023 june 15;7(9):4. [9] mao peng, li xiaolu, zhou you, qin hong, xiong qixin. study on architecture of automation system in extra-high integrated control center. in: 2010 international conference on power system technology [internet]. zhejiang, zhejiang, china: ieee; 2010 [cited 2025 oct 23]. p. 1–4. available from: http://ieeexplore.ieee.org/document/5666105/ [10] mcknight w. enterprise data integration: now more than ever [internet]. information week. 2025. available from: https://www.informationweek.com/datamanagement/enterprise-data-integration-now-more-thanever [11] schenk b. data, information, and content management. in: advanced management information systems [internet]. cham: springer nature switzerland; 2025 [cited 2025 oct 23]. p. 169–96. (progress in is). available from: https://link.springer.com/10.1007/978-3-031-87904-3_4 [12] prakash br, dattasmita hv. a case study of command‐ and‐control center—a dss perspective. in: gaur l, agarwal v, chatterjee p, editors. decision support systems for smart city applications [internet]. 1st ed. wiley; 2022 [cited 2025 oct 23]. p. 17–33. available from: https://onlinelibrary.wiley.com/doi/10.1002/978111989695 1.ch2 [13] mohua. integrated command and control centres [internet]. pib delhi; 2023. available from: https://www.pib.gov.in/pressreleaseiframepage.aspx?pri d=1947455 [14] mohua. integrated command and control center maturity assessment framework and toolkit draft version 1.0 [internet]. mohua; 2018. available from: https://smartnet.niua.org/sites/default/files/resources/iccc_ maturity_assessment_framework_toolkit_vf211218.pdf [15] kpmg, belgium. from smartto smarter cities leveraging integration, data and enablement for sustainable and resilient urban transformations. [internet]. kpmg; 2024. available from: https://assets.kpmg.com/content/dam/kpmg/be/pdf/psfrom-smart-to-smarter-report.pdf [16] k a. smart city command and control centre: leveraging geospatial data [internet]. iet (the institution of engineering and technology); 2024. available from: https://india.theiet.org/innovation-and-knowledge/ietfuture-tech-panel-knowledge-outputs/whitepapers/smartcity-command-and-control-centre-leveraging-geospatialdata/ [17] smart city bhopal. workshop on integrated control and command centre [internet]. smart city bhopal; 2020; bhopal. available from: http://164.100.161.224/upload/uploadfiles/files/bscdcl%2022%20sep-v2_o_bhopal.pdf eai endorsed transactions on smart cities | volume 7 | issue 4 | 2025 | efficient substitution box design with chaotic logistic map and linear congruential generator 1 an efficient substitution box design with a chaotic logistic map and linear congruential generator for secure communication in smart cities muhammad asim hashmi 1,2,* , noshina tariq 3 1 department of electronics, quaid-i-azam university, islamabad, pakistan (e-mail: mahashmi@ele.qau.edu.pk) 2department of electrical and computer engineering, air university, islamabad, pakistan 3 department of avionics engineering, air university, islamabad, pakistan (e-mail: noshina.tariq@mail.au.edu.pk) abstract the study provides a unique method for creating an efficient substitution box (s-box) for advanced encryption standards using a chaotic logistic map (clm) and a linear congruential generator (lcg) (aes) for secure communications in a smart city. the pseudo-random number generator (prng), which is further examined, is constructed using an extensive search of reasonable possibilities for the initial seed and set parameters. using statistical testing, the performance analysis of the new s-box is assessed. additionally, the resilience of differential, as well as linear cryptanalysis, is shown. it is derived using other features, including nonlinearity, the bit independence criterion (bic), and the strict avalanche criterion (sac). the suggested s-box has good potential and is usable for symmetric key cryptography, according to the features of the new s-cryptographic box. keywords: security, smart city, cryptography, encryption, aes, s-box received on 07 november 2022, accepted on 19 january 2023, published on 23 march 2023 copyright © 2023 muhammad asim hashmi et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v7i1.2845 *corresponding author. email: mahashmi@ele.qau.edu.pk 1. introduction irrevocable protection of both a transmitter and a receiver is essential for a secure communication network in smart cities. for all modern techno-driven smart automation, the security of the communication between the application and the controlling network is one of the major concerns. for this considerable problem both encryption and decryption are practical answers to this significant issue. encryption makes communication unintelligible for any unauthorized user or intruder. to make communication networks in smart cities, modern encryption schemes provide a solution for secure information flow. some markedly essential applications for which security and privacy are topmost concerns include (but are not limited to) raspberry pi-based automation systems for smart homes and smes that primarily need secure communications [1]. communications in smart cities meal preparation [2], and waste management [3] needs end-toend security. all protocols and architecture presented in [4] require secure communications. the modern standards for data encryption, which are known as advanced encryption standards (aes), were first released by nist in the year 2000 and comprised four primary operations, which are substitution byte, shift rows, add round key, and mix columns [5] [6]. this algorithm's replacement step, essential to encryption, is carried out via a 256-element array known as the substitution box (s-box). the design of this s-box in aes eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e6 mailto:mahashmi@ele.qau.edu.pk mailto:noshina.tariq@mail.au.edu.pk https://creativecommons.org/licenses/by-nc-sa/4.0/ muhammad asim hashmi and noshina tariq 2 is crucial since it makes the algorithm difficult to break and causes confusion and dissemination [7]. plain and encrypted text in a cryptogram that uses a simple substitution approach is identical. substitution and permutation are the two fundamental conditions for a nonlinear encryption method that must be met for a system to be impermeable to frequency analysis [8]. for this reason, the s-box is tested for additional cryptographic features and intended to resist cryptanalysis. bit independence criterion (bic), nonlinearity, strict avalanche criterion (sac), bijectivity, linear and differential approximated probabilities, and sac-bic analysis all contribute to the s-box robustness. most researchers employed chaotic maps to create new s-boxes last year to solve this research problem; some of the most prominent ones are covered in the literature review. this paper presents a simple and quick approach to creating a cryptographically efficient s-box for aes. it offers a circular shift approach and develops an s-box with many iterations for a single output at the level of random number generation. additionally, the approach permutes the intended vector to enhance statistical tests used in cryptography. with the help of this technique, the suggested s-box is further statistically assessed for the cryptographic application by the needed cryptographic features, demonstrating the method's broad applicability. the following is a list of the suggested model's key contributions: 1. a novel and fast method is proposed to design a cryptographically efficient s-box for aes. 2. more than one iteration is used to generate a single output at a random number generation level while designing the proposed s-box. 3. a robust s-box has been presented by introducing the circular shift technique. 4. a permutation matrix of 256 entries-based maps is presented based on simple programming. the next sections of the paper are as follows: section 2 provides the literature review. section 3 gives some insight into the background. section 4 presents the proposed model to design an s-box for aes. the statistical testing and performance of the proposed s-box are analyzed, and discussions are presented in section 5, while section 6 is the conclusion section. 2. literature review from classical data security requirements to modern applications like energy efficient routing protocols [30], unmanned aerial vehicles [31], block chain technology [32], efficient operations in data storage [33], mobile communication networks [34], the cryptographic algorithm plays a vital role in data security. by examining the effects of the chaos base approach on block ciphers, jakimoski et al. [9] produced a chaos-based s-box. this s-box is significantly nonlinear and appropriate for cryptography applications where encryption is needed, and substitution is part of the encryption technique. grouping tang et al. [10] developed a technique for designing s-boxes that yields dynamically powerful cryptographic substitution box. it used a two-dimensional (2d) discretized chaotic baker map cryptographically superior to jakimoskie’s s-box. gondal et al. [11] introduced a novel approach for s-box design that was significantly nonlinear. the approach relied on a chaotic bakers map and a scaled-down version of an 8-bit block cipher. the behavior in a chaotic logistic map renders the algorithm incomprehensible, adding to the unpredictability. iqtidar et al. [12] applied a chaotic logistic map's output to a linear functional transformation. they presented a novel method for creating a considerably nonlinear s-box with all the cryptographic features. zhongyun et al. [13] suggested a unique strategy equivalent to previous relevant s-boxes using the entire latin square method. qing et al. [14] developed a more extensive chaotic range and many chaotic features utilizing the logistic-sine system. akram et al. [15] suggested a novel approach for designing an s-box based on a chaotic sine map. the approach utilized to create this s-box is straightforward to apply. this method secures the permutations and maps generated values with a permutation matrix of 256 entries. the map used (in this method) is based on simple programming and does not have solid mathematical roots. using credibility complex fuzzy sets (ccfs), yahya et al. [28] proposed a novel scheme for designing an s-box for the encryption of images and discussed the results for the suitability of the proposed s-box for image encryption. 3. background the methods, which are chaos-based pseudo-random number generators (prngs), played a vital role in designing robust cryptographic algorithms in the previous two decades. some markedly on the top are included in section 1.1. we took two different prngs to design a novel s-box. the structure of the aes algorithm for a single round of encryption is shown in figure 1 [29]. eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e6 efficient substitution box design with chaotic logistic map and linear congruential generator 3 figure 1. aes encryption process except for these four steps, all other steps, such as adding a round key, mixing columns, and shifting rows, are linear operations [12] [15]. that is why the s-box is the only factor that introduces nonlinearity in an algorithm. the substitution operation is described in figure 2. figure 2. substitution in aes in the substitution process, the entry or plain text gets changed according to the value of the location in the sbox. for example, if the value of the plain text is "3f," then the value at the 63rd location of the s-box will be substituted accordingly. the number of rows and columns is equal (16x16) for aes, whichfulfills all the required substitution possibilities in the american standard code for information interchange (ascii) [5]. this substitution is possible only if a randomly permuted unique string of [0-255] elements exists. an unpredictable random number generator is required to generate this string unintelligibly and robustly [13]. a chaotic logistic map is a well-known chaos-based random number generator for its sensitive output upon a slight change in initial conditions. a good prng means highly unpredictable output for miner input values change. for all prngs, there are some fixed parameters and seed values. in our experiment for both prngs, which are chaotic logistic maps and linear congruential generators, we have some fixed parameters and a seed value, as described in tables 1 and 3 of section 3. 4. proposed architecture the design scheme is presented by division into two subsections. subsection 4.1 elaborates on the scheme of random permutations with the help of clm, while subsection 4.2 describes the mapping vector. finally, a novel s-box is generated using both vectors, as shown in fig. 3. figure 3. proposed architecture 4.1. chaotic logistic map a logistic map is highly sensitive to initial conditions and is an efficient chaotic map [12]. mathematically clm is defined in equation 1. xn+1 = xn(1 xn) (1) in equation 1, xn+1 refers to the output of the seed and initial conditions for the nth iteration. the xn defines the seed value for the first iteration or the output of previous iterations. in this study, values ranging from 0-255 are extracted from gf (28), and a proportional gain f is applied to make the output suitable for usage with gf (28). following a significant amount of trial and error, the initial values that were established for seed, modulus, and constant variable are shown in table 1. table 1. initial values for chaotic logistic map variable value f 19731 xn 0.167 create a string using a hundred thousand iterations, then reformat it into a 100x1000 matrix. following that, a circular shift of ten columns and ten rows, respectively, is applied to the matrix. now, choose just the tenth or its multiplier part of this string to generate an s-box, which will provide us with an array containing 10000 items. after removing any instances of duplication from this array, the resultant matrix (g) will consist of the 256 items presented in the following order. figure 4 presents the matrix in its entirety, designed using matlab. p ro p o se d a rc h it ec tu re 1. chaotic logistic map 2. linear congruential generator eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e6 muhammad asim hashmi and noshina tariq 4 algorithm 1 clm random permutations required: permuted unique random values in gf(28) 1: parameters: prng equation, scaling factor, seed 2:int seed xn (xn = seed value) 3: int scaling factor s (s = 19731) 4: int modulus m (m = 256) 5: for iteration 1:1000000 6: x(i+1) = x(i+1)* (1-x(i+1)) mod m 7: output = circular shift (output,10,10) 8: fori = 1:100000 9: clm (i) = output (i*10) 10: end figure 4. the figure presents the initial 16x16 matrix designed by applying initial conditions to the chaotic logistic map. the simulations are made using matlab. 4.2. linear congruential generator the quickest random number generator is a linear congruential pseudo-random number generator (lcg) [17]. equation 2 mathematically defines the lcg. x(n+1) = (axn+ c) mod m (2) the values of both multiplicative factor a and additive factor c lie between 0 and the value of modulus m. x(n+1), which refers to the output value of the nth iteration. in contrast, x(n) refers to the seed value for the nth iteration. in our experiment, we employ lcg as a mapping vector. table 3 shows the beginning values for lcg in this experiment. table 2. initial conditions for linear congruential generator variable value multiplicative factor (a) 11 addition factor (c) 7 modulus (m) 19731 since the values of both the multiplicative and additive factors are less than 19731 and greater than 0, it fulfills the primary requirement of lcg. the output vector is confined to modulus n using these starting values, as shown in equation 3. m(i) = x(i) mod n (3) using this pseudo-random number generator, this work creates an initial string after 10000 iterations. it builds a vector from them by defining them in mod 257 and generates a vector of (1-256). in this regard, table 4 shows the permutation matrix (p). algorithm 2 lcg permutations required: permuted unique random values from (1-256) 1: parameters: prng equation, additive factor, seed 2:int seed xn (xn = seed value) 4: int multiplicative factor “a” (a = 7) 5: int multiplicative factor “c” (c = 11) 6: int modulus m (m = 256) 7: int modulus m (n = 257) eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e6 efficient substitution box design with chaotic logistic map and linear congruential generator 5 8: for iteration 1:10000 6: x(n+1) = (axn+ c) mod m 8: fori = 1:1000 9: lcg (i) = output (i*10) mod 257 ; unique 10: g(i) = lcg (i); 11: end this vector specifies the permutation positions for the matrix g. figure 4 depicts the planned s-box. this mapping vector leads to the final design of the substitution box. the proposed s-box is presented in figure 6. row 1 and column 1 in figure 5 determine the locations of entries. s(p(i)) = g(i) (4) algorithm 3 mapping 1: int p, g 2: for i=1:256 3: s(p(i)) = g (i) 4: end figure 5. figure shows the mapping functions for initial clm permutations. the matrix is designed using linear congruential generator with initial conditions figure 6. the resultant substitution box after mapping locations of clm with the function of lcg. eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e6 6 5. performance analysis the suggested s-cryptographic box's features are subjected to a statistical analysis in which the probability of nonlinearity, bic, bijectivity, sabic, sac, differential approximation, and linear are considered. 5.1 bijectivity the s-box is bijective [14] if and only if every input has a unique mapping on the output and correspondingly unique values in gf (28). figure 7. proposed steps in performance analysis 5.2 nonlinearity high nonlinearity is the most crucial statistical feature of an s-box. this feature reveals a shift in the bits between two successive encrypted sentences [19]. a nonlinear boolean function g(x) may be represented by its walsh spectrum [20]. figure 8 depicts the suggested s-box nonlinearity from a function perspective. figure 8. proposed s-box nonlinearity 5.3 bit independence criterion for this reason, webster and tavares [22] developed the bit independence criteria. analyzing the s-box's strength using this technique is standard practice. it indicates that any shift in the bits sent out does not affect any other pairs. that is to say, during nonlinearity in sequence or the avalanche effect, if a single bit in the input is altered, its behaviour at the output is unrelated to any preceding bits. the bic-sac and bic nonlinearity are calculated, shown in figure 9 and figure 10, and a comparison is given in table 4. figure 9. bic-nl comparison bijectivity non-linearity bit independenc e criterion strict avalanche criterion linear approximati on probability muhammad asim hashmi and noshina tariq eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e6 efficient substitution box design with chaotic logistic map and linear congruential generator 7 figure 10. bic-sac comparison 5.4 strict avalanche criterion the strict avalanche criterion (sac) was developed by webster and tavares [22]. by this definition, if a single bit of input is complemented, then all bits of the output will change with probability half. thus the function satisfies the sac. half of the encryption bits will be reversed if one bit of plain text is inverted. table 6 presents the results of the sac analysis; figure 11 provides a visual comparison. whereas table 4 compares the value to that of other well-known coded s-boxes. table 3. strict avalanche criterion results sac maximum 0.59 sac minimum 0.41 average value 0.498 variance 0.042 . figure 11. sac comparison table 4. comparison table of results 5.5 linear approximation probability linear approximation probability (lap) is the most significant value of an event's imbalance. in order to provide an equal number of output and input bits, the mask selects the parity of the bits [23]. the proposed sbox show the lap values better than ref [ 20, 24, 25, 26] and comparable to ref. [15, 27]. the graphical comparison of laps is in figure 12, and the comparison is given in table 4. figure 12. lap comparison 5.6 differential approximation probability an s-box's differential approximation probability (dap) measures differential uniformity [23]. the dap method ensures that each differential at the input is uniquely mapped at the output. it is ideal for making this approximation probability as low as possible. the optimal value of this probability is 0.062. the comparative analyses of lap and dap are provided in table 4. it scheme nl bic sac sacbic lap dap proposed 104 102 0.498 0.503 0.132 0.0390 anees et al.[24] 102 103 0.507 0.502 0.141 0.0468 khan et al.[25] 100 101 0.481 0.496 0.171 0.0625 khan et al.[26] 102 102 0.517 0.479 0.164 0.210 wang et al.[20] 104 103 0.485 0.0.476 0.141 0.0390 balezi et al. [15] 105 105 0.500 0.500 0.125 0.0468 kim et al.[27] 104 104 0.503 0.503 0.109 0.0468 hussain et al.[12] 112 112 0.504 0.504 0.062 0.0156 optimal 120 120 0.500 0.500 0.062 0.0156 eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e6 8 shows that the proposed method has dap values better than ref. [15, 20, 24, 25, 26, 27]. the graphical comparison of daps is shown in figure 13, and the comparison is given in analysis table. figure 13. dap comparison the comparison table shows that the nonlinearity of the proposed s-box is 3.921% better than khan et al. [25] and 1.942 % better than anees et al. [24] and khan et al. [26]. the bic values are 0.985% better than khan et al. [25]. the difference in sac from the optimal value is 4.27% better than the lowest value [25] in table 4. lap values are lower than anees et al. [24], khan et al. [25], khan et al. [26], and wang et al. [20]. similarly, the dap values are better than anees et al. [24], khan et al. [25], khan et al. [26] and balezi et al. [15], and kim et al. [27]. the results show that the proposed method for designing the s-box is prominently applicable to cryptographic applications. 6. conclusions this article presents a basic but effective way of creating s-boxes. a chaotic logistic map and a linear congruential pseudo-random number generator create a reliable s-box architecture. the created s-box is compared to the codified s-box to assess its resistance to cryptanalysis assaults. the effectiveness of the created s-box demonstrates the tremendous potential of this aes s-box for cryptographic applications. for all applications in smart cities where encryption is required, this is a vital part of the algorithm on application level uses. future applications of this technique include the encryption of still images and moving video by breaking a movie down into individual frames and encrypting each one in turn. the cryptographic properties of this work show that the method fulfills all required properties for secure communication between a transmitter and a receiver. references [1] tirumala, s. s., nepal, n., & ray, s. k. (2022). raspberry pi-based intelligent cyber defense systems for smes and smart-homes: an exploratory study. eai endorsed transactions on smart cities, 6(18), e4-e4. [2] namasivayam, b. (2022). ai for healthy meal preparation in smart cities. eai endorsed transactions on smart cities, 6(4), e1-e1. [3] mccurdy, a., peoples, c., moore, a., & zoualfaghari, m. (2021). waste management in smart cities: a survey on public perception and the implications for service level agreements. eai endorsed transactions on smart cities, 5(16). [4] sajid, a., shah, s. w., & magsi, t. (2022). comprehensive survey on smart cities architectures and protocols. eai endorsed transactions on smart cities, 6(18). [5] daemen j, rijmen v. the design of rijndael: aes the advanced encryption standard.springerverlag: berlin, 2002. [6] khan, m., azam, n. a. (2015). right-translated aes gray s-boxes. security and communication networks, 8(9), 1627-1635. [7] ferguson n, schroeppel r, whiting d. a simple algebraic representation of rijndael. in selected areas in cryptography sac01, lncs2259, 2001; 103?11. [8] shannon, c.e., 1949. communication theory of secrecy systems. the bell system technical journal, 28(4), pp.656715. [9] jakimoski, g., kocarev, l.: chaos and cryptography: block encryption ciphers based on chaotic maps. ieee trans. circuits syst. 48(2), 163 (2001) [10] g. tang, x. liao, y. chen, a novel method for designing s-boxes based on chaotic maps, chaos solitons fractals 23 (2005) 41319 [11] muhammad asif gondal, abdul raheem, iqtadar hussain, a scheme for obtaining secure s-boxes based on chaotic baker map, 3d res. 5 (august)(2014) 17 [12] hussain, i., shah, t., gondal, ma and mahmood, h., 2013. an efficient approach for the construction of lft sboxes using chaotic logistic map. nonlinear dynamics, 71(1), pp.133-140. [13] hua, z., li, j., chen, y., and yi, s., 2021. design and application of an s-box using a complete latin square. nonlinear dynamics, 104(1), pp.807825. [14] lu, q., zhu, c. and deng, x., 2020. an efficient image encryption scheme based on the lss chaotic map and single s-box. ieee access, 8, pp.25664-25678. [15] belazi, a. and abd el-latif, a.a., 2017. a simple yet efficient s-box method based on chaotic sine map. optik, 130, pp.1438-1444. [16] radwan, a.g., 2013. on some generalized discrete logistic maps. journal of advanced research, 4(2), pp.163-171. [17] marsaglia, g., 1972. the structure of linear congruential sequences. in applications of number theory to numerical analysis (pp. 249-285). academic press. [18] zamli, k. z., kader, a., din, f., alhadawi, h. s. (2021). selective chaotic maps tiki-taka algorithm for the s-box generation and optimization. neural computing and applications, 1-18 [19] javeed, a., shah, t. (2020). design of an s-box using rabinovichfabrikant system of differential equations perceiving third order nonlinearity. multimedia tools and applications, 79(9), 6649-6660 muhammad asim hashmi and noshina tariq eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e6 efficient substitution box design with chaotic logistic map and linear congruential generator 9 [20] wang, y., xie, q., wu, y., du, b. (2009, june). a software for xbox performance analysis and test. in 2009 international conference on electronic commerce and business intelligence (pp. 125-128). ieee [21] pedro miguel sosa. calculating nonlinearity of boolean functions with walsh-hadamard transform. 2016 [22] a. webster, s. tavares, on the design of s-boxes advances in cryptology: proc. of crypto?5, santa barbara, usa. lecture [23] m. matsui, linear cryptanalysis method of des cipher advances in cryptology, proc. eurocrypt?3. lncs, vol. 765, springer, berlin, 1994, pp. 386 [24] anees, a. and ahmed, z., 2015. a technique for designing substitution box based on van der pol oscillator. wireless personal communications, 82(3), pp.1497-1503. [25] khan, m., shah, t. and batool, s.i., 2016. construction of s-box based on chaotic boolean functions and its application in image encryption. neural computing and applications, 27(3), pp.677-685. [26] khan, m. and asghar, z., 2018. a novel construction of substitution box for image encryption applications with gingerbreadman chaotic map and s8 permutation. neural computing and applications, 29(4), pp.993-999 [27] kim, j., phan, r. c. w. (2009, june). a cryptanalytic view of the nsa's skipjack block cipher design. in international conference on information security and assurance (pp. 368-381). springer, berlin, heidelberg [28] yahya, m., abdullah, s., almagrabi, a. o., & botmart, t. (2022). analysis of s-box based on image encryption application using complex fuzzy credibility frank aggregation operators. ieee access, 10, 88858-88871. [29] heron, s. (2009). advanced encryption standard (aes). network security, 2009(12), 8-12. [30] hassan, m. abul, et al. "energy efficient hierarchical based fish eye state routing protocol for flying ad-hoc networks." indonesian journal of electrical engineering and computer science 21.1 (2021): 465-471. [31] hassan, muhammad abul, et al. "unmanned aerial vehicles routing formation using fisheye state routing for flying ad-hoc networks." the 4th international conference on future networks and distributed systems (icfnds). 2020. [32] javed, abdul rehman, et al. "integration of blockchain technology and federated learning in vehicular (iot) networks: a comprehensive survey." sensors 22.12 (2022): 4394. [33] sajid, faiqa, et al. "secure and efficient data storage operations by using intelligent classification technique and rsa algorithm in iot-based cloud computing." scientific programming 2022 (2022). [34] ali, sher, et al. "new trends and advancement in next generation mobile wireless communication (6g): a survey." wireless communications and mobile computing 2021 (2021). eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e6 this is a title eai endorsed transactions on smart cities research article 1 vehicle counting application utilizing background subtraction method with large-scale camera data mien phuoc doan1,*, vu the tran2 and sy ngo van3 1tra vinh university. 126 nguyen thien thanh street, ward 5, tra vinh city, 87000, vietnam 2institute for research and executive education, the university of danang. 158a le loi street, hai chau district, da nang city, 50000, vietnam 3vietnam research institute of electronics, informatics and automation, da nang city, 50000, vietnam abstract in modern society, people are increasingly using cameras at home, in shops, and on the streets. traffic systems have also invested in building more surveillance camera systems. the data collected by cameras contains valuable information for traffic regulation and recording traffic violations. the challenge is how to effectively use this data. in this article, we will discuss the use of real-time data from surveillance cameras on some roads in da nang city for vehicle counting using background subtraction methods. additionally, we also tested the detection of red-light violations to contribute to the development of a smart traffic system. so, the use of background subtraction in analysing real-time data from surveillance cameras can greatly improve traffic management. keywords: large-scale camera, background subtraction, da nang city received on 05 april 2023, accepted on 09 march 2024, published on 17 april 2024 copyright © 2024 m. p. doan et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.3211 1. introduction traffic is always the most frequently mentioned issue in modern society. safety in traffic is always a major challenge, which causes headaches for many managers. in developed countries, public transportation such as buses and subways are the main means of transportation. the use of cars is also very common. in addition, the infrastructure is developed, and people’s awareness of traffic rules is high. unlike the traffic situation in vietnam, where there are many types of vehicles on the road and the awareness of participants is not always good. for example, some drivers stop their vehicles on the highway to eat or even reverse on the highway. traffic violations such as running red lights, driving in the wrong direction, and lane encroachment are common. therefore, the unpredictability of traffic in vietnam in general and danang, in particular, is quite high. currently, *corresponding author. email:phuocmien@tvu.edu.vn there is no system deployed in danang to automatically detect behaviors such as lane encroachment and running red lights. after a trial period, in august 2016, a high-quality camera system at key locations such as hue intersection, han river bridge, dragon bridge, cham museum, pham van dong beach, nguyen hue gate (quang trung street), etc., officially became operational. currently, there is no system that utilizes data from these surveillance cameras. with the advancement of information technology, reading and retrieving massive amounts of data or using the outputs of various applications on different technology platforms is being paid attention to. however, in the field of traffic, this is still a relatively new issue. currently, there is no architecture that can read and interpret multiple types of output data using different programming languages. for example, the results of vehicle counting using visual c++ language can be used to connect with a system used to calculate the density using python language. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | http://creativecommons.org/licenses/by/3.0/ mien doan phuoc, vu tran the and sy ngo van 2 in this article, we will focus on addressing the data issues from multiple surveillance cameras. the specific tasks are as follows: • receiving camera data (video) from 0511.vn • analyzing and storing the data on cloud servers • processing the data in real-time the purpose of our research is to augment the existing amount of data in the study, particularly focusing on traffic images in da nang, vietnam. in the following section, we provide a brief overview of relevant research. subsequently, we will proceed with the experimental research steps in part 3, and finally, conclude with the achieved results. 2. related work in this paper, we focus on researching relevant literature on the use of large-scale camera data and data processing methods from cameras for vehicle recognition and counting purposes. 2.1. research on literature related to largescale camera data in the study by [1], the authors designed and implemented an extensive annotation system that provides comprehensive image labels for a large-scale driving dataset. this dataset comprises over 100 thousand videos and is annotated with various types of information, including image-level categorization, object bounding boxes, drivable areas, lane markings, and full-frame instance segmentation. in [2], it is demonstrated that cameras can be initially deployed for one application and simultaneously shared for other analytic applications, showing the potential of using existing cameras for multiple purposes. despite recent advancements, video analytics platforms for surveillance still have limitations in systematic access to large datasets and video analytics in the presence of noisy data. in the research [3], a large volume of data was collected and labelled from multiple camera sources. around 212 webcams were used to collect data, resulting in over 60 million frames. with a large amount of data, deep learning methods can be applied to accurately count the number of vehicles on the road. in [4], linear transformations are applied to individual features of each pixel with uniform weights across the entire image. therefore, the accuracy may not be high when the scene captured by the camera is large. in most studies, the data primarily focuses on cars with clear perspectives, and there are very few instances where multiple types of vehicles on the road appear, such as cars and motorcycles. 2.2. research on related literature regarding vehicle recognition and counting methods methods and techniques for tracking and detecting vehicles have been of great interest to researchers both domestically and internationally to create traffic congestion warning systems, monitor the number of vehicles moving in cities, and regulate traffic automatically. many methods have been proposed to address the issue of traffic congestion, as demonstrated in [5][9]. however, there are two methods that are currently receiving the most attention: sensor-based methods [6] and image recognition techniques for analysing traffic density [7]. in addition, [5] used image processing from video and the results of object detection were studied for the purpose of estimating traffic density and flow. in [10], methods such as point detection and edge detection were used in the process of detecting and tracking vehicles. it can be said that one of the most important research breakthroughs is object detection in images [8], which serves as a foundation for object detection from videos [11]. in works like [12], methods to distinguish between the front and rear images are used to extract moving vehicles from videos. some studies, such as [13] and [14], have shown that using feature vectors from input images can be effective in vehicle detection. the study [15] presents the estimation of vehicle size with near-accurate results by using a set of coordinate mapping functions. moreover, in [16], a series of enhancement algorithms were developed for object detection using machine learning methods that can detect and classify moving objects based on type and colour. in [17], an overview of background subtraction steps is provided, where the first step initializes the background with n frames collected from the initial background where the object is in a stationary state. then, motion detection is performed through foreground detection, which includes classifying pixels as foreground or background by comparing the background image and the current frame. finally, the background needs to be maintained to update the background over time. the last two steps are repeated continuously during the processing time. despite many successful applications of foreign studies in practical operations, it is not possible to directly apply templates to traffic in vietnam. the traffic system in vietnam is very complex, including factors such as geographical conditions, types of vehicles, and traffic culture. especially, there is a wide variety of vehicles in vietnam, including motorcycles, bicycles, electric bicycles, three-wheeled cars, four-wheeled cars, trucks, buffalo carts, and agricultural vehicles, in addition to pedestrians and livestock on the roads. as shown in figure 1, in this paper, we plan to build a technological platform that can collect signals from camera eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | vehicle counting application utilizing background subtraction method with large-scale camera data 3 data through programming interfaces such as nodejs. the data will pass through a background service layer that is built to standardize all types of data. the input query data is very diverse, and the system allows for data retrieval from video files by directly connecting to the source device, or by retrieving data through an address, or by retrieving through a metadata query request (this is complex data with multiple fields of information). in addition, the data will be stored in the cloud through protocols such as rabitmq and nosql databases such as mongodb, firebase, etc. application arrays such as vehicle recognition, vehicle counting, pedestrian detection, etc. will be able to connect to the system. the video streams are first fetched from the cloud storage and decoded to extract individual video frames. each frame is then processed separately to detect and recognize objects. this approach allows for processing individual frames on cloud resources, resulting in highly informative and scalable information. the analysed data can be used in transportation fields such as traffic flow analysis, red light violation detection, etc. to experiment with the proposed architecture, we are used input data from the system, including videos obtained from cameras placed at street corners in downtown da nang. after obtaining this data, the system will process it to extract individual frames from each video. each frame will be processed by a background subtraction method to transform the original image (with color) into a binary mask containing only two types of pixels: black and white. in this case, black pixels correspond to the background and white pixels correspond to the foreground. the next step uses the obtained image along with the object recognition method to segment moving objects. based on the height and width of the detected objects, we can determine if they meet the requirements or not. if yes, the total number of counted vehicles is increased, and finally, the total number of vehicles is displayed on the screen. the proposed model in this paper is illustrated in figure 2. figure 1. system architecture – haivan-cva system. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | mien doan phuoc, vu tran the and sy ngo van 4 figure 2. the vehicle counting system utilizes the proposed big data architecture. 3. experimental results in this paper, to demonstrate the effectiveness of the proposed model for building a large-scale data analytics architecture, a testing system was constructed using a vehicle counting application. this application was implemented using a background subtraction solution combined with blob detection for vehicle recognition and counting. the parameters were then extended to count other types of vehicles. 3.1. experiment with large-scale data source data source: in this paper, the data source for serving the selected applications was collected over 1 year from surveillance cameras, as shown in figure 3, in da nang city. each video has a display time of approximately 120 seconds and is formatted according to h.264 standard, with a frame rate of 18 frames per second. the data processing rate for each video is 6.156 kbps. each video is divided into about 3000 frames and filtered down to approximately 120 frames. each frame has a size of 160 kb. figure 3. camera source hardware configuration: the configuration of the client machine is as follows: intel core i5 m 520 @ 2.40ghz x 4 cpu, 8gb ram, 120gb ssd storage. it runs ubuntu 32-bit operating system. for the project, three virtual servers were set up on cloud computing with ubuntu operating system, each having 1gb processing speed and 897gb storage capacity. in addition, five amazon ec2 web services were used to run the vehicle counting applications, and five amazon ec2 web services were used to run the pedestrian detection applications. the configuration of the amazon ec2 web servers is shown in figure 4. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | vehicle counting application utilizing background subtraction method with large-scale camera data 5 figure 4. query request information. query data from surveillance cameras: in this project, nodejs is used for querying surveillance cameras. the variables and metadata queries are declared as shown in table 1. the results after querying with the "url" as "http://haivandn.com.vn:3000" are shown in figure 5. figure 5. camera addresses from the provider for example, to view the camera at point 2co2...ng33, the query address would be: url/ camera/2co2...ng33/list/now • download videos to a local machine from cloud service using the address: url/camera/:cameraname/. the request will be processed and allowed for downloading. extracted videos will be temporarily stored and automatically deleted after 3 days from the requested date. the variables to access camera points through the background data processing layer at the address http://35.185.26. 121:9000/global-management-service1.0 are shown in figure 6. figure 6. define api table 1. explanation of data retrieval information field type description _id string primary key id string frame id name string camera name description string description address string camera installation address phone number string hotline number type string video type datapoint string video file export address datapointcontroller string camera service provider storing data on cloud servers: as mentioned in the integration structure section, the processed data is stored online in real-time using the flickr cloud computing server. the real-time storage results on the flickr cloud server are shown in figure 7. figure 7. storage of results on the flickr cloud computing server. in the architecture of this paper, in addition to direct querying of videos, the system also allows data access through addresses or metadata, and they are stored in realtime using the firebase database. the results of storing data addresses in the firebase database are shown in figure 8. figure 8. firebase data storage history. furthermore, the download data usage status is shown in the chart in figure 9. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | mien doan phuoc, vu tran the and sy ngo van 6 figure 9. historical chart of data loading on firebase storage. 3.2. experimental vehicle detection and counting on the proposed architecture platform car detection results: applying the steps according to the proposed model, we conducted experiments using a video as input. the program successfully recognized the cars in each frame. the results are shown in figure 10. figure 10. car detection results motorcycle detection results: to perform recognition of other objects, specifically motorbikes, in this paper, we have adjusted some parameters of the desired frame size during the object filtering step (using the blob detection method). with these adjustments, we can easily limit the objects to be recognized. figure 11 illustrates the specific values of the smallest (minarea) and largest (maxarea) parameters for an object to meet the search requirements. accordingly, with minarea = 400, the demo program performs recognition of objects corresponding to the size of motorbikes, bicycles, and cars. on the other hand, with minarea = 500, the program only recognizes cars. the motorbike recognition results are shown in figure 12. figure 11. object detection frame parameters figure 12. motorcycle detection results 4. conclusion in this paper, we have successfully addressed the challenges of receiving data from a large camera source, real-time data retrieval and storage, and detecting red light violations. the results of detecting red light violations are shown in figure 13. in the future, we will continue to research and utilize the available camera sources in da nang to further improve the quality of traffic services. figure 13. red light violation detection eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | vehicle counting application utilizing background subtraction method with large-scale camera data 7 references [1] yu, f., xian, w., chen, y., liu, f., liao, m., madhavan, v., & darrell, t. (2018). bdd100k: a diverse driving video database with scalable annotation tooling. arxiv preprint arxiv:1805.04687, 2(5), 6. [2] s. jain, v. nguyen, m. gruteser, and p. bahl, “panoptes: servicing multiple applications simultaneously using steerable cameras.” in ipsn, 2017, pp. 119–130. [3] s. zhang, g. wu, j. p. costeira, and j. m. moura, “understanding traffic density from large-scale web camera data,” arxiv preprint arxiv:1703.05868, 2017. [4] v. lempitsky and a. zisserman, “learning to count objects in images,” in advances in neural information processing systems, 2010, pp. 1324–1332. [5] m. bayly, m. regan, and s. hosking, “intelligent transport systems and motorcycle safety” prevention, vol. 28, pp. 325–332, 2006. [6] j. sun and j. sun, “a dynamic bayesian network model for real-time crash prediction using traffic speed conditions data,” transportation research part c: emerging technologies, vol. 54, pp. 176–186, 2015. [7] jain, n. k., saini, r. k., & mittal, p. (2019). a review on traffic monitoring system techniques. soft computing: theories and applications: proceedings of socta 2017, 569-577. [8] r. tina and s. g. sharmila, “density based traffic signal system,” international journal and magazine of engineering technology management and research, vol. 2, no. 9, pp. 149–151, 2015. [9] n. g. narole and p. r. bajaj, “a neurogenetic system design for monitoring driver’s fatigue: a design approach,” in 2008 first international conference on emerging trends in engineering and technology. ieee, 2008, pp. 711–714. [10] m. hofmann, p. tiefenbacher, and g. rigoll, “background segmentation with feedback: the pixel-based adaptive segmenter,” in 2012 ieee computer society conference on computer vision and pattern recognition workshops. ieee, 2012, pp. 38–43. [11] p. g. michalopoulos, “vehicle detection video through image processing: the autoscope system,” ieee transactions on vehicular technology, vol. 40, no. 1, pp. 21– 29, 1991. [12] q. cai, a. mitiche, and j. k. aggarwal, “tracking human motion in an indoor environment,” in proceedings., international conference on image processing, vol. 1. ieee, 1995, pp. 215–218. [13] d. g. lowe, “distinctive image features from scaleinvariant key-points,” international journal of computer vision, vol. 60, no. 2, pp. 91–110, 2004. [14] d. a. forsyth and j. ponce, “a modern approach,” computer vision: a modern approach, vol. 17, pp. 21–48, 2003. [15] a. h. lai, g. s. fung, and n. h. yung, “vehicle type classification from visual-based dimension estimation,” in itsc 2001. 2001 ieee intelligent transportation systems. proceedings (cat. no. 01th8585). ieee, 2001, pp. 201– 206. [16] m. piccardi, “background subtraction techniques: a review,” in 2004 ieee international conference on systems, man and cybernetics (ieee cat. no. 04ch37583), vol. 4. ieee, 2004, pp. 3099–3104. [17] t. bouwmans, “traditional and recent approaches in background modeling for foreground detection: an overview,” computer science review, vol. 11, pp. 31–66, 2014. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | an intelligent machine learning based intrusion detection system (ids) for smart cities networks 1 an intelligent machine learning based intrusion detection system (ids) for smart cities networks muhammad yaseen ayub1,*, usman haider2, ali haider1, muhammad tehmasib ali tashfeen3, hina shoukat1 and abdul basit4 1department of computer science, comsats university islamabad, attock, pakistan (e-mail: yaseen.ayub@ieee.org, sp17bse-018@ciit-attock.edu.pk, fa18-bcs-053@cuiatk.edu.pk) 2department of electrical engineering, national university of computer & emerging sciences, peshawar, pakistan (e-mail: usmanhaider@ieee.org) 3school and electrical and electronics engineering, fast national university peshawar pakistan (e-mail: alitashfeen@gmail.com) 4department of electrical and computer engineering (ece), comsats university islamabad campus (e-mail: abdulbasitmujahid925@gmail.com) abstract introduction: internet of things (iot) along with cloud based systems are opening a new domain of development. they have several applications from smart homes, smart farming, smart cities, smart grid etc. due to iot sensors operating in such close proximity to humans and critical infrastructure, there arises privacy and security issues. securing an iot network is very essential and is a hot research topic. different types of intrusion detection systems (ids) have been developed to detect and prevent an unauthorized intrusion into the network. objectives: the paper presents a machine learning based light, fast and reliable intrusion detection system (ids). methods: multiple supervised machine learning algorithms are applied and their results are compared. algorithms applied include linear discriminant analysis, quadratic discriminant analysis, xg boost, knn and decision tree. results: simulation results showed that knn algorithm gives us the highest accuracy, followed by xg boost and decision tree which are not far behind. conclusion: a fast, secure and intelligent ids is developed using machine learning algorithms. the resulting ids can be used in various types of networks especially in iot based networks. keywords: iot, ids, machine learning. received on 31 october 2022, accepted on 23 january 2023, published on 08 march 2023 copyright © 2023 muhammad yaseen ayub et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v7i1.2825 1. introduction in the modern age of technological inventions, overall world dynamics is changed. due to wireless communication and iot networks connectivity is made possible. according to analytics, in 2022 around 14.4 billion iot devices are connected [1]. in near future iot devices will exceed up to 41 billion. wireless sensor * corresponding author. email: yaseen.ayub@ieee.org networks will provide better solutions for tracking and monitoring. there exist many applications of iot networks which include home automation, digital banking and security systems. with the help of iot based camera surveillance business shops and homes can be secured from intruders [2-6]. collectively these applications form the basis of future smart cities. smart cities, in particular, are heavily dependent on iot networks for various critical services such as transportation, energy management, and public safety. this eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e4 https://creativecommons.org/licenses/by-nc-sa/4.0/ muhammad yaseen ayub, et al. 2 increased dependence makes smart cities more vulnerable to cyber-attacks [7]. security is considered the main problem with iot based networks. attacker tries to hijack iot network by sending false data packets. due to that network becomes vulnerable and intruder easily unbalances the entire system [8]. in smart cities there is extensive use of iot networks which makes its security a huge concern. attackers can exploit vulnerabilities in iot devices to gain unauthorized access to sensitive information, disrupt city services, or cause physical damage. this makes intrusion detection a critical requirement for ensuring the security of smart cities [9]. tele-medicine is a new concept in smart cities where doctor will operate and consult the patient remotely. therefore, intruder can disturb the process by deploying dos/ddos, sybil, spoofing, wormholes and man-in-the middle attack [10-12]. this can cause some serious life threatening situation for the patient. figure 1, depicts the concept of iot network of multiple devices using an ids and its advantage in case of any intrusion figure 1. iot network using concept of intrusion detection system however, to make smart city environment safe from such attacks, threat detection is very much necessary. therefore, intrusion detection system (ids) plays an important role in identification of various attacks on iotnetworks [13]. this research paper presents the concept of ids using machine learning techniques for optimal detection of cyber-attacks. figure 1, shows the concept of ids in iot networks. section 2 presents literature review of all research work that has been done recently in this domain. section 3 explains intrusion detection systems in detail along with their different types, followed by section 4 which describes real time applications of iot networks in a smart city concept. then section 5 discusses simulation environment and simulation results generated by applying machine learning techniques on unsw-nb15 dataset. at last section 6 presents conclusion and future discussions. 2. literature survey this section presents limitations related to iot-networks. in, iot based communication networks sending information from one node to another is quite tough. therefore, nature inspired e-anthocnet has improved overall standards of communication. but still security is the main concern which needs to be addressed with possible solutions [14-16]. machine learning technique decision tree enhance connectivity in between nodes by using received signal strength indicator (rssi). due to cyberattacks on iot networks connectivity will be unbalanced [17]. intelligent detection system is introduced which can easily detect dos/ ddos and ping of death attacks. markov chain distribution is used to balance false positive and false negative which lead to the problem of high accuracy [18]. queue based traffic management is used to monitor data packets of iot-networks. anomaly based ids is designed using poisson distribution to minimize false alarm and missed detection. the proposed system is able to identify ping of death attacks but still higher attack probabilities need to be evaluated which use to degrade network performance [19]. table 1 present’s limitation of various proposed machine learning based ids using different techniques as well as stimulation environment. table 1. machine learning techniques & limitations referen ce machine learning techniqu es type of ids simulati on tool ids limitation s [38] fusion decision anomal y-based test bed unable to detect host attack payload monitored attacks. [39] knn & rsl hybrid sdn and blockchai n accuracy can be improved. [40] rnn hybrid python 3.0 rnn has a slow and complex training process and faces difficulty with long sequence. [41] rf anomal y-based iot system anomalybased approach is deficient on true alarm rate [42] rf anomal y-based scada less accurate than a eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e4 an intelligent machine learning based intrusion detection system (ids) for smart cities networks 3 hybrid model [43] ann hybrid matla b ann technique usually lack in accuracy to some extant [44] svm anomal y-based matla b accuracy needs to be improved [45] dnn anomal y-based tensorfl ow & python mitigation required for false alarm [46] cnn anomal y-based python data labeling is a better practice helps the algorithm’s better understandi ng [47] snn, bxg boost & dnn anomal y-based python precision refinement is requisite. 3. intrusion detection system for iotnetwork iot networks are usually poorly secured so the fact is that the critical data, they are carrying is vulnerable to various kind of attack. an ids acts as an alarm that beeps in case of any possible attack [20]. idss have been more common because they continuously analyze the network traffic thus no unverified packet passed unattended. currently researchers are more interested to impose various methodologies of machine learning and deep learning powered with various algorithms on iots for the detection of intrusion [21-22]. in smart cities with such extensive use of iot networks and in such close proximity of humans with sometimes sensitive data on them, it is absolutely necessary to incorporate strong intrusion detection system (ids) that mitigates the threat of information leakage and network hijacking which. if in smart city a critical network is hijacked, it can result in loss of precious and sensitive information. it can also lead to life threatening situation. thus protecting smart city infrastructure against possible attacks is very important. the advancement in iot security has led to detection even on sensor node in iot network [23]. there are three common types of ids: • anomaly-based ids • signature-based ids • hybrid ids 3.1 anomaly based ids for iot networks the anomaly-based detection system search and validate the iot network pattern with the normal-behavior thus any anomaly beyond a specific level is considered as a threat and system is warned and system learns gradually. it has a threshold defined which acts as a boundary, any change in normal network behavior beyond that threshold is classified as a threat. anomaly-based detection system overcomes various barriers of excellence like it can detect zero-day error and has capability to sense unknown attacks but has high false alarm rate. [24][25]. 3.2 signature based ids for iot networks signature-based intrusion detection system corroborates the network traffic pattern with the pre-existing signatures and makes a decision regarding an intrusion on basis of their match. they are also called rule based intrusion detection system. their limitation is that they can only detect and classify those attacks which are already stored in its database. any attack with unsaved pattern passes unattended. this type of ids has low false alarm rate but is unable detect zero-day error [24-26]. 3.3 hybrid based ids for iot networks a hybrid-based ids is combination of both types so it can detect both zero-day attacks as well as pre-defined attack patterns. it is a very flexible and customizable ids, it can be customized to prioritize certain types of threat depending on scenario. with this approach the low false alarm rate and high detection rate is achieved thus precision and accuracy of ids is improved [26-27]. . 4. real-time application of iot-networks in smart cities iot market is growing continuously and researchers are pointing towards more and more application of iots. the concept of smart cities rely heavily on use of iot networks for faster communication and automation. the world’s next target is automation and iot network is the tool to achieve this goal. the researchers have found the most interesting applications of iot networks in smart cities scenario such as in smart traffic management, emergency response, health care, smart homes, smart grids, agriculture, smart monitoring etc. [28]. some of the applications are further explained below: eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e4 muhammad yaseen ayub, et al. 4 4.1 smart traffic management. iots sensors can be installed on roads, intersections and other key areas to monitor traffic patterns in real time. these iot sensors then can collect certain data about traffic flow, vehicle speeds, traffic density etc. which can then be used for the optimization of traffic signal and routing to improve traffic flow and reduce congestion [29] [30]. this can be very useful in smart cities during peak traffic times as it can help reduce delays and improve the overall efficiency of the road network. another application of iot in smart traffic management can be the integration of traffic data with public transport system. this can allow for more efficient routing and scheduling of busses and trains as well as the integration of real-time traffic data into public transport journey planning apps so people can know about traffic situation in a particular area before planning any trip or traveling plan. 4.2 emergency response in smart cities, the use of iot networks for emergency response can involve the installation of sensors in key areas such as public buildings, streets and parks to detect emergencies in real-time. these sensors can be triggered by factors such as smoke, fire or extreme temperatures to alert the authorities of potential emergencies. iot networks can also be used to gather real-time data on the location and status of emergency services vehicles, allowing for more efficient routing and deployment of these resources in response to emergencies [31]. another use can be integration of emergency data with public warning systems, such as sirens or messaging system. this can allow authorities to quickly and efficiently alert the public of any potential dangers and provide guidance on how to respond. iot networks can be integrated in smart cities and they can help improve the speed and efficiency of emergency response efforts, leading to a faster resolution of emergencies and a reduction in the impact on the community. thus creating a smart and safer smart city environment for public [32]. 4.3 iot for healthcare iots have the most critical advantage in healthcare. they have increased facility of medicare with minimal expenditure even in remote areas. smart iot wearables can monitor a patient’s vital signs in real-time and alert healthcare professionals to any potential risks. now any medical officer can monitor his patient without paying him personal visit or keeping patient in the hospital. sensors applied for the patient’s care shares data with the doctor through iot network and thus complete examination of the results is not a big deal anymore [33]. 4.4 iot based smart home iot has played an important role in home automation. almost all home appliance i.e., ac, refrigerator, washing machine lights, fans, door locks etc. are now available in smart version even vehicles have been shifted towards iot network thus they can be accessed remotely. iot sensors can play a key role in security of a smart home in smart cities. sensors can monitor and protect the home from potential threats such as burglaries or fire. a smart home has many sensors like fire & smoke sensor, gas sensor etc. that alert the user if any parameter crosses the threshold. so, a smart home with iot network ensures the safety of residents [3] [34]. 4.5 iot for smart grid the purpose of smart grid is to provide electricity to the customers by means two-way digital communication. a smart grid can track each consumption of the electricity at all the locations of the system. smart grid targets have been achieved via iot. through an iot network, a smart grid is capable of disaster as well as operation monitoring on high voltage transmission lines, efficiency, accuracy and operation period that is very strenuous in manual systems [35]. 4.6 iot for agriculture the production of the agriculture is going to increase using iot through smart farming. iot is been used for the monitoring of crops as well as animals through various tools and sensors connected through iot network like monitoring of greenhouse temperature, humidity of field, disease diagnosis etc. various machinery used in agriculture is been smart now can be controlled remotely through iot network. moreover, uavs are also been deployed in the modern farming and agriculture [36]. 4.7 iot in smart cities with the advancing world, the first idea is smart cities collectively creating a smart world. the evolution of smart city is parallel to the evolution of all its components. a smart health system, smart transport system, smart buildings, smart energy management, smart administration, smart industries and smart security etc. will collectively be the building blocks of a smart city and iot provides the base to this progression [37]. 5. simulation environment for simulation python is used to do experimentation on iot-networks. unsw-nb15 dataset is utilized which is having updated network traffic information. machine eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e4 an intelligent machine learning based intrusion detection system (ids) for smart cities networks 5 learning techniques like linear discriminant analysis, quadratic discriminant analysis, xg boost, knn and decision tree are simulated [48-54], which generated very good results. table 2, shows results of machine learning classifiers where knn is having better accuracy compared to the rest of algorithms about 98.3061%. the overall explanation of table 2 is illustrated in figure 2. table 2. accuracy of machine learning techniques algorithms accuracy linear discriminant analysis 97.6717 quadratic discriminant analysis 94.0314 xg boost 98.2507 knn 98.3061 decision tree 98.2137 figure 2. machine learning algorithms like linear discriminant analysis, quadratic discriminant analysis, xg boost, knn and decision tree using unsw-nb15 dataset’ 6. conclusion and future directions iot networks can be deployed in almost every field. there exist many problems in iot networks due to that intruder easily attack and unbalance entire network. this paper has introduced machine learning techniques to detect possible cyber-attacks from updated australian dataset called unsw-nb-15. types of intrusion detection system in iot networks are incorporated which include anomaly, signature and hybrid. different iot-based applications are being discussed which provide a clear picture of limitations and vulnerabilities. around five machine learning techniques like linear discriminant analysis, quadratic discriminant analysis, xg boost, knn and decision tree are utilized. this paper is giving investigation of security countermeasures. especially, the approach of intrusion detection system is used to identify various cyber-attacks. moreover, in near future, as iot devices are increasing continuously with the passage of time. ids using supervised machine learning, deep learning, computational intelligence, optimization, genetic algorithm, supervised learning, reinforcement and sliding mode controller is helpful to detect possible cyber-attacks. also, new dataset for network security is the need for researchers. scientists must focus on real-time applications regarding intrusion detection system. in 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[30] fiore, s., elia, d., pires, c.e., mestre, d.g., cappiello, c., vitali, m., andrade, n., braz, t., lezzi, d., moraes, r. and basso, t., 2019. an integrated big and fast data analytics platform for smart urban transportation management. ieee access, 7, pp.117652-117677. [31] mohammad, n., muhammad, s., bashar, a. and khan, m.a., 2019. formal analysis of human-assisted smart city emergency services. ieee access, 7, pp.60376-60388. [32] shah, s.a., seker, d.z., rathore, m.m., hameed, s., yahia, s.b. and draheim, d., 2019. towards disaster resilient smart cities: can internet of things and big data analytics be the game changers?. ieee access, 7, pp.91885-91903. [33] pradhan b, bhattacharyya s, pal k. iot-based applications in healthcare devices. journal of healthcare engineering. 2021 mar 19;2021. [34] asadullah m, raza a. an overview of home automation systems. in2016 2nd international conference on robotics and artificial intelligence (icrai) 2016 nov 1 (pp. 27-31). ieee. [35] ou q, zhen y, li x, zhang y, zeng l. application of internet of things in smart grid power transmission. in2012 third ftra international conference on mobile, ubiquitous, and intelligent computing 2012 jun 26 (pp. 96-100). ieee. [36] kim ws, lee ws, kim yj. a review of the applications of the internet of things (iot) for agricultural automation. journal of biosystems engineering. 2020 dec;45(4):385400. [37] gaur a, scotney b, parr g, mcclean s. smart city architecture and its applications based on iot. procedia computer science. 2015 jan 1;52:1089-94. [38] al-nashif y, kumar aa, hariri s, luo y, szidarovsky f, qu g. multi-level intrusion detection system (ml-ids). in2008 international conference on autonomic computing 2008 jun 2 (pp. 131-140). ieee. [39] derhab a, guerroumi m, gumaei a, maglaras l, ferrag ma, mukherjee m, khan fa. blockchain and random subspace learning-based ids for sdn-enabled industrial iot security. sensors. 2019 jul 15;19(14):3119. [40] ullah s, khan ma, ahmad j, jamal ss, e huma z, hassan mt, pitropakis n, buchanan wj. hdl-ids: a hybrid deep learning architecture for intrusion detection in the internet of vehicles. sensors. 2022 feb 10;22(4):1340. [41] hussein ay, falcarin p, sadiq at. enhancement performance of random forest algorithm via one hot encoding for iot ids. periodicals of engineering and natural sciences (pen). 2021 aug 11;9(3):579-91. [42] zolanvari m, teixeira ma, gupta l, khan km, jain r. machine learning-based network vulnerability analysis of industrial internet of things. ieee internet of things journal. 2019 apr 18;6(4):6822-34. [43] wang g, hao j, ma j, huang l. a new approach to intrusion detection using artificial neural networks and fuzzy clustering. expert systems with applications. 2010 sep 1;37(9):6225-32. [44] chahal jk, gandhi v, kaushal p, ramkumar kr, kaur a, mittal s. kas-ids: a machine learning based intrusion detection system. in2021 6th international conference on signal processing, computing and control (ispcc) 2021 oct 7 (pp. 90-95). ieee. [45] prethi kn, nithya s, sangeeth dm, rani rs, praveen kumar s. dnn based intelligent ids for anomaly detection. international journal of advanced research in engineering and technology. 2020 oct 17;11(9). eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e4 an intelligent machine learning based intrusion detection system (ids) for smart cities networks 7 [46] yoshimura n, kuzuno h, shiraishi y, morii m. doc-ids: a deep learning-based method for feature extraction and anomaly detection in network traffic. sensors. 2022 jun 10;22(12):4405. [47] bedi p, gupta n, jindal v. i-siamids: an improved siamids for handling class imbalance in network-based intrusion detection systems. applied intelligence. 2021 feb;51(2):1133-51. [48] moustafa n, slay j. unsw-nb15: a comprehensive data set for network intrusion detection systems (unsw-nb15 network data set). in2015 military communications and information systems conference (milcis) 2015 nov 10 (pp. 1-6). ieee. [49] moustafa n, slay j. the evaluation of network anomaly detection systems: statistical analysis of the unsw-nb15 data set and the comparison with the kdd99 data set. information security journal: a global perspective. 2016 apr 4;25(1-3):18-31. [50] moustafa n, slay j, creech g. novel geometric area analysis technique for anomaly detection using trapezoidal area estimation on large-scale networks. ieee transactions on big data. 2017 jun 14;5(4):481-94. [51] moustafa n, creech g, slay j. big data analytics for intrusion detection system: statistical decision-making using finite dirichlet mixture models. indata analytics and decision support for cybersecurity 2017 (pp. 127-156). springer, cham. [52] sarhan m, layeghy s, moustafa n, portmann m. netflow datasets for machine learning-based network intrusion detection systems. inbig data technologies and applications 2020 dec 11 (pp. 117-135). springer, cham. [53] moustafa n, turnbull b, choo kk. an ensemble intrusion detection technique based on proposed statistical flow features for protecting network traffic of internet of things. ieee internet of things journal. 2018 sep 24;6(3):4815-30. [54] koroniotis n, moustafa n, sitnikova e, slay j. towards developing network forensic mechanism for botnet activities in the iot based on machine learning techniques. ininternational conference on mobile networks and management 2017 dec 13 (pp. 30-44). springer, cham. eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e4 design a framework for iotidentification, authentication and anomaly detection using deep learning: a review eai endorsed transactions on smart cities review article 1 design a framework for iotidentification, authentication and anomaly detection using deep learning: a review aimen shoukat1, muhammad abul hassan2,* , muhammad rizwan3, muhammad imad4, farhatullah5, syed haider ali6 and sana ullah7 1department of computer science, kinnaird college for womenlahore pakistan, aimen.shoukat007@gmail.com 2department of information engineering and computer science, university of trento, italy. muhammadabul.hassan@unitn.it 3secure cyber systems research group, wmg, university of warwick, coventry cv4 7al, uk, muhammad.rizwan.1@warwick.ac.uk 4department of computing and technology, abasyn university peshawar, imadk28@gmail.com 5school of automation, china university of geosciences, wuhan 430074, china, farhatkhan8398@gmail.com 6department of electrical engineering, university of engineering and technology peshawar, engrsyedhaiderali@yahoo.com 7department of computer science, qurtuba university of science and technology, peshawar pakistan, sunnykhan3304@gmail.com abstract the internet of things (iot) connects billions of smart gadgets so that they may communicate with one another without the need for human intervention. with an expected 50 billion devices by the end of 2020, it is one of the fastest-growing industries in computer history. on the one hand, iot technologies are critical in increasing a variety of real-world smart applications that can help people live better lives. the cross-cutting nature of iot systems, on the other hand, has presented new security concerns due to the diverse components involved in their deployment. for iot devices and their inherent weaknesses, security techniques such as encryption, authentication, permissions, network monitoring, \& application security are ineffective. to properly protect the iot ecosystem, existing security solutions need to be strengthened. machine learning and deep learning (ml/dl) have come a long way in recent years, and machine intelligence has gone from being a laboratory curiosity to being used in a variety of significant applications. the ability to intelligently monitor iot devices is an important defense against new or negligible assaults. ml/dl are effective data exploration techniques for learning about 'normal' and 'bad' behavior in iot devices and systems. following a comprehensive literature analysis on machine learning methods as well as the importance of iot security within the framework of different sorts of potential attacks, multiple dl algorithms have been evaluated in terms of detecting attacks as well as anomaly detection in this work. we propose a taxonomy of authorization and authentication systems in the internet of things based on the review, with a focus on dl-based schemes. the authentication security threats and problems for iot are thoroughly examined using the taxonomy supplied. this article provides an overview of projects that involve the use of deep learning to efficiently and automatically provide iot applications. keywords: iot, dl, ml, challenges, iot applications received on 19 july 2022, accepted on 17 november 2022, published on 17 january 2022 copyright © 2023 aimen shoukat et al., licensed to eai. this is an open access article distributed under the terms of the cc bync-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v7i1.2067 *corresponding author. email: muhammadabul.hassan@unitn.it eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e2 mailto:aimen.shoukat007@gmail.com mailto:muhammad.rizwan.1@warwick.ac.uk mailto:imadk28@gmail.com mailto:engrsyedhaiderali@yahoo.com https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ aimen shoukat et al. 2 1. introduction over the last decade, application devices such as smartphones, sensor systems, and controllers have become increasingly sophisticated, allowing for easier communication between devices as well as the completion of more complex tasks. in 2008, the number of system devices surpassed the global population [1], and the figure has continued to rise exponentially till now. mobile phones, built-in systems, wireless connectivity, and practically every gadget in the internet of things (iot) era are all linked to a local area network. the development of internet-of-things (iot) devices, such as mobile phones [2], sensor technologies [3], sensor systems for uncommon aerial vehicles [4], [5], intellectually smart devices [6], and so on, has resulted in a slew of new apps on the cell phone as well as remote platforms. the amount of information gathered from these devices frequently grows in parallel with the range of devices. innovative technologies are evolving that analyze data for practical interconnections and decision-making, eventually leading to artificial intelligence (ai) employing ml and deep learning dl algorithms. in order to design effective iot applications, we often use a workflow model that includes data collection, analysis, visualization, and evaluation [7], [8]. data analysis is an important, computer-intensive component in which traditionally developed devices generally combine specialist knowledge and machine learning for classification and regression problems such as traffic forecasting, vehicle tracking, delivery time estimation, and so on. moreover, as society moves into the "big data" era, existing approaches are unable to process large amounts of volatile and unpredictable data from hidden, incompatible iot-based datasets. almost all traditional methods focus on totally enclosed characteristics, and their effectiveness is strongly reliant on prior knowledge of specific locations. the majority of learning approaches employed in those devices use deep architectures with limited modeling and representational capacity. as a result, a far more powerful analytical tool is required to maximize the value of the priceless raw data generated by diverse iot processes. according to mckinsey's analysis of the worldwide economic ramifications of iot, the yearly effect on the economy of iot in 2025 will vary between $2:7 to $6:2 trillion. healthcare accounts for 41% of the iot sector, followed by the industry as well as oil, which accounts for 33% and 7% of the iot sector, correspondingly. transportation, agriculture, roads and bridges, security, and merchants account for about 15\% of the total iot market. such forecasts imply a massive and quick expansion of iot services, data collection, and, consequently, demand in the future years. according to mckinsey's research, the economic impact of machine learning is defined as "the employment of computers to perform jobs that require complicated assessments, exact evaluations, and creative problem-solving." the research looks at the primary supporters of data automation in machine learning techniques like deep learning and neural networks. the machine-to-machine connection can be shortrange utilizing wi-fi, bluetooth, or long-range using lora, m1 cat, 4g, lte, and 5g. because iot applications are used in so many different applications, the expense of iot devices must be kept low. moreover, iot systems should be capable of performing basic functions such as data collecting, m2m connection, and so on. iot is closely tied to "big data," as iot systems continuously collect and exchange large amounts of data. for instance, an iot platform employs technologies for managing, storing, and analyzing large amounts of data. it has become required in infrastructure to deploy iot services like thingsboard, or mainflux in order to support m2m communication via protocols including amqp, and mqtt. as per the program, specific data processing must commonly occur on the internet of things rather than on other centralized nodes inside the "cloud computing" system. the latest data processing model is known as "edge computing" is introduced as computation moves entirely to the end network nodes. moreover, because these devices are frequently low-end, they might not have been suitable for intense applications. as a result, an intermediate node with sufficient capacities is needed to manage improved processing jobs that are spatially near the end network elements, reducing the load produced by huge data transmission to the number of inner cloud nodes. "fog nodes" are presented in this work to aid large data handling on iot devices by providing storage, computation, and networking services. lastly, the data is kept within the cloud, where further testing using various ml and dl techniques, as well as sharing with other gadgets, results in the creation of smart apps with innovative value-added. because traditional deep learning approaches do not match the current analysis requirements of iot networks, dl has received a lot of attention. the structure of iot data collection and processing necessitates the use of specialized traditional data analytics and ai approaches. dl approaches were utilized to analyze big data in utilized the iot cloud as well as streaming, as well as data from iot devices and rapid data analytics in edge or fog computing. although iot has already been done in recent years, deep learning in iot applications is still in its early stages. few researchers analyzed articles on wireless sensor networks (wsns) with machine learning, integration of dl techniques for healthcare departments, dl methods and usability in iot systems, and dl techniques with their applications to build smart development. there is still no study that comprehensively investigates a broad range of iot systems using dl after completing the survey on existing publications. we also believe that it is time to assess the current literature and use it to generate future study proposals. to that purpose, this paper outlines recent research including patterns in the use of deep learning techniques to enhance iot systems. we'll show you how to use deep learning to improve iot applications from a variety of angles. for instance, safety eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e2 design a framework for iotidentification, authentication and anomaly detection using deep learning: a review 3 monitoring, illness analysis, interior locations, artificial management, traffic prediction, home robots, vehicle automation, fault evaluation, and factory inspection. the concerns, constraints, and potential research areas for dl in iot systems are also highlighted in order to stimulate as well as enable future discoveries in this promising field. 2. background theory 2.1 concept of iot systems today, an increasing number of products are connected to the internet in order to incorporate iot perspectives in a variety of industries like smart buildings, public transportation, healthcare centers, industry, farming, and so on. in order to provide the buyers with iot-system characteristics and specifications, the iot framework gets converted entities in such domains from traditional to intellectual. to account for environmental modifications, specific frameworks must be altered during processes [9], [10]. iot refers to all connected and constantly associated items, like electronic devices with sensors, and controllers, as well as a microprocessor integrated component. because things need to communicate, which necessitates machine-to-machine interactions for shortrange wireless systems like wifi, bluetooth, as well as zigbee, the interaction range seems to be either restricted or broad when it comes to long-distance links like wimax, and gsm, as well as lte [11]. the iot is designed to give objects online identities that allow them to connect, share information, and access various resources. the concept of a digital identity for a large number of devices helps advanced radio frequency identification systems advance (rfid). such systems were built up as cheap computers due to their resource constraints, which prompted resource-constrained wsns to emerge [12]. highly networked equipment that may be altered as needed is an example of an iot-enabled environment. the internet of things has been used to sustain patient recovery by following certain criteria, as well as to maintain patient characteristics. furthermore, the findings can be used in researchers to compare patient exposure to various care settings on a worldwide basis [12]. the iot can track and monitor energy consumption as well as provide entertainment. food and agriculture production. it may measure and manage factors such as climate, political, atmospheric, farming, food, and animal disease elements. as the number of people with physical problems and life-threatening illnesses rises, so does the demand for iot services and equipment [13]. 2.2 challenges of iot all transitions include benefits as well as challenges that must be overcome. these obstacles could be related to issues of protection, security, and so on. this section covers the various potential issues associated with iot structural analysis. another stumbling issue is the current network structure's incapacity to serve real-time essential iot applications; as a result, sdn is seen as a suitable communication network for such applications [14],[15],[16],[17],[18],[19]. 2.3 deep learning algorithms in iots deep learning is a sophisticated technique that is described as the latest update of ann. it primarily focuses on building larger and more complicated neural networks with a large number of layers that are hidden that can handle massive amounts of data, like that found in photo pattern recognition, voice recognition, and iot devices. the availability of cutting-edge iot frameworks and accessible libraries for continuous monitoring, realtime processing, and secure storage of produced data such as photos, contingency tables, textual, voice, and video has resulted in a significant surge in iot datasets [20] various hardware systems functioning on the exterior or indoor ground-works, like smart urban sensors, smart organization fields, and so forth, generate such data. we require a distributed training model that is flexible and effectively utilizes the hardware resources of thousands of iot devices to train such big-scale high-quality iot data that's been gathered over a longer period in an acceptable amount of time. the following are the most important deep learning algorithms: 1. deep neural networks 2. convolutions neural networks 3. deep boltzmann machine 2.4 applications of iot people can profit from the iot in a variety of ways, including making life easier and assuring performance and safety. healthcare equipment, city buildings, home automation systems, automobile design, electric utilities, as well as the smart world are all feasible applications. there are indeed countless applications in every part of existence since the introduction of super-duper and advanced technologies [21]. 2.4.1 health system to improve the wellness of patients, new techniques have been created. without touching the skin, diseases can be detected wirelessly and details displayed. other sensors can measure pulse rate, blood oxygen, insulin levels, and temperature [22]. 2.4.2 smart home traditional home appliances, such as fridges, washers, dryers, and lightbulbs, have been designed with internet eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e2 aimen shoukat et al. 4 access to help monitor and track equipment and to optimize energy usage with one another or with enrolled users. aside from traditional technology, current inventions are gaining traction, such as smart house assistants, smart door locks, and so on [21]. 2.4.3 smart transportation it is possible to provide genuine help, save income, and cut emissions by using sensors built into automobiles or attached to city equipment to provide intelligent route advice, allocated parking, communications about traffic situations, telematics, as well as accident prevention [23]. 2.4.4 monitoring of environmental conditions any wireless sensor deployed across the city will be able to cope with a wide range of situations. advanced weather stations can be made with other types of barometers and moisture sensors. because smart sensors can detect pollution simultaneously at a range and at the molecular level, they are particularly valuable for monitoring the air quality and water emission levels in cities [24]. 2.4.5 management of logistics and supply chains the product's accessibility in manufacturing and retail is considerably reduced when rfid tags are used, lowering the total cost and time required. active packaging characteristics such as product verification, customer quality management, client relationship, and customization are also necessary [25]. 3 identification the initial necessity in iot elements is identification, which serves as a confirmation of personal data for every object inside the iot universe. the term "identity" is frequently used to refer to a specific person, equipment, or entity. furthermore, it is regarded as an essential component in establishing a connection or interaction between persons, as well as for the success of an iot system. it allows us to identify millions of disparate things and control them remotely over the internet. identification also connects items to information about them that may be obtained from a server. it allows the item to interact with other objects with the same or opposite scopes via the internet. to allow secure interobject communication, there must be a method to align the identity of all objects in the area. based on the concepts that apply to item identity, identification management is necessary for three primary parties: the user, item identities, and connections. it must also address the iot model's particular problems [26],[27],[28],[29],[30]. on the one side, identification is critical for iot to define and correlate activities with their domain, as well as the issues of assigning a unique identity to each object and representing and preserving shared data. identifying iot objects, on the other hand, is required to distinguish between an item's id or title and its address, which refers to the object's location within a communication network. for iot devices, there are addressing techniques such as ipv4, ipv6, and 6lowpan addresses, and also numerous previous identifying methods such as rfid, bluetooth, barcode/2d code, and so on. identification methods assign a distinct identification to each object in the network [27],[31],[32]. 3.1 deep learning use in iot identification dl can enable iot devices to read any information and effectively respond to both human and environmental situations, but performance in terms of energy consumption must be considered. some procedures have demonstrated the use of dp in iot networks, like the work in [33], which used the deep learning methodology to select useful data from large amounts of multimedia information collected by iot devices in a smart farming atmosphere, which is used to enhance farmers' standard of living. they still, however, see cloud computing as a way to deal with the energy and resource limits that come with implementing dl in iot devices. they were also concerned about the network delays induced by such data [33]. deep learning is also commonly employed in iot applications including monitoring and object recognition. a large amount of data must be handled fast, and a speedy response is required. cloud computing is unsuccessful in this scenario because it cannot satisfy the processing and reaction completion times. however, the issue can be fixed by utilizing fog computing, which can benefit both network edge as well as cloud resources. as a result of the work in [34], a dp-based fog cloud technology called edgelens has been developed for real object recognition in iot application platforms. because deep learning has the potential to correctly handle any classification task, and identification is called a classification challenge, we assume that utilizing such approaches will produce in powerful and useful iot item identity. 3.1.1 methods of earlier identification in the iot context, all items must be identifiable in some way. to communicate with other things and share information in the same or distinct domains, each item should have a unique identity. in this section, we'll go over some of the previous ways of identifying iot items. 1. radio frequency identification (rfid) 2. barcode/2d code 3. electronic product codes (epc) 3.1.2 the modern identification methods this section presents an overview of the latest iot object identification algorithms published over the last seven years. eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e2 design a framework for iotidentification, authentication and anomaly detection using deep learning: a review 5 1. identification of things using their fingerprints 2. computer vision for identification 3. machine learning techniques for identification the ability to differentiate objects is the most significant feature of any iot solution. identification, which establishes evidence of identity information for every item in the field of the iot that normally identifies a unique item, including a person, equipment, or other entity, will be used to execute this. the object's distinct identity allows it to create, process, as well as exchange data with other entities of the same or opposite domain. as a result, the efficiency of iot systems is determined by the identification method employed, making it critical to select a trustworthy identification scheme to achieve optimal system performance. however, the issue of establishing an appropriate identification technique for individual iot platforms is a worry, as there is currently no universal identification mechanism that can be utilized for all iot platforms. the following research on existing object identification techniques in iot indicates that many identifying methods, such as rfid, ip address, and others, have been employed since the iot idea was introduced many years back. however, because the field's quick and continual expansion necessitates the development of identification methods as well, many new methods have lately been presented based on diverse methods such as computer vision, fingerprints, ml, and so on. although numerous approaches such as fuzzy systems, and artificial neural, including deep learning can be employed in a variety of sectors, they have yet to be applied to the identification of iot devices, and if done successfully, will result in a huge change in the field. 4 authorization the user's accessibility to the iot system is dependent on authorization. it allows only authorized clients to enter, monitor, and use data from iot networks. the instructions of users with system authority are also carried out. it's difficult to maintain track of all user records and provide them access based on the data because clients are human, whereas sensors, equipment, and services are not. figure 1. taxonomy of dp/ml-based aa for iot. identification refers to a user's permission in an iot infrastructure. users must initially register to interact with the cloud server. but on the other hand, the trade-offs and reliability of iot systems make identification difficult [35]. phishing and masquerading attacks are also to blame for the network's vulnerability, and attackers will obtain access to the device rapidly if they don't provide enough identity. in a conclusion, to provide crucial protection when implementing system limitations, an adequate iot system identification strategy is required [36]. users & devices on the internet are protected by two fundamental components: authentication and authorization. it makes such elements necessary for iot deployment because the internet of things is nothing more than a collection of devices, ranging from simple sensors to vehicles and complex mobile devices, that connect to share information. authenticity is a device identification method that verifies the authenticity of the device's customer id and ensures that it is unique to that device. authorization is a method of determining if a node (sensor node or user) is authorized to access things like reading or writing information, running programs, or operating devices. connection denial or cancellation are also covered by authorization, especially if someone or something harmful is involved. in addition, permission allows you to link a particular device to specified services. one sort of authentication & authorization process is for devices, while the other is for users. the focus of this research is on-device authentication and authorization. a eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e2 aimen shoukat et al. 6 sensor is a great example of this. the device identity and permission level are defined through the aa processes before the communication session begins as well as the sensory information transfer takes place. 4.1 anomaly detection in iot there are situations where actual data sets are unique from all others and are identified as anomalies. finding anomalies requires looking for things that are out of the ordinary in terms of activity when compared to normal nodes. intrusion detection systems, fraud prevention, & data leaking are all separate sources of abnormalities. anomaly detection is employed in a variety of iot applications, like smart urban, network security, and industries [37], [38]. 4.1.1 intrusion detection iot devices are vulnerable to security attacks since they are connected to the internet. dos & ddos attacks do severe damage to the iot network. identifying and preventing such threats is the most critical concern in iot implementations [37], [39]. 4.1.2 fraud detection when logins in or online payments, iot systems are susceptible to receiving credit card information, banking info, or other sensitive information [37], [40]. 4.1.3 data leakage external organizations can leak confidential information from a database, data centers, as well as other gathering procedures, directly threatening privacy as well as information loss. such leaks can be avoided with proper encryption measures [37]. to address the gaps in the existing approaches, we propose designing an intrusion detection algorithm that is: 1. capable of detecting new forms of attacks 2. device-agnostic: it doesn't need to know what kind of device produced the network traffic. as a result, it can be used outside of the local network. 3. it is non-intrusive and privacy-preserving, in the sense that it does not spend time looking at application-level data. then network traffic can be encoded without interfering with the examination. 4. delay-free: sometimes doesn't need to wait for an unknown period of time. we build an iot nids based on unlabeled data, especially anomaly identification techniques, in this section. as a result, our model is able to recognize new sorts of threats. we also look at two scenarios, based on whether or not it's important to figure out which device is causing the network traffic. we suggest employing a set of weak autoencoders to detect abnormal signals in iot networks for such a reason. autoencoder is an unsupervised neural network that can be used to detect anomalies, allowing new sorts of assaults to be detected. the data from communication networks is first preprocessed in order to extract important information. normalization is also part of the pre-processing procedure. after that, the normalized information is passed into a series of weak autoencoders. we prepare a different weak autoencoder for every iot device type present in the network since an iot network is made up of highly various iot device kinds. the autoencoder understands a device type's valid communication profile. 4.2 machine learning techniques in iot detection ml approaches like supervised [41], unsupervised [42], as well as reinforcement learning, can be used to detect unique threats in iot devices and establish a good protection strategy. multiple machine learning methods for iot device protection. in machine learning, supervised learning is the most common strategy, in which the outcome is evaluated based on input using a qualifying set of data as well as a learning algorithm. two different types of supervised learning are classification & regression modeling. there has been no outcome information for these input variables in unsupervised learning [41]. the majority of the data is unmarked, and the algorithm attempts to discover relationships between the various data sets. it divides them into clusters of different kinds furthermore, reinforcement learning allows the computer to learn from its own environment in the same way that some people do by doing actions that improve overall response. the feedback could be in the form of an award depending on the mission's outcome. in reinforcement learning, there are no predetermined behavior for any particular task, and the system relies on trial and error. by trial and error, the agent may discover and use the optimum plan from its knowledge to get the maximum reward [43]. 5 conclusion a review of the dl and iot methods used in many fields like home automation, smart city, smart transportation, power, localization, healthcare system, safety, agriculture, and others is discussed in this study. in recent years, analysts and business units have focused on dl and iot, both of which have had a favorable impact on our lives, cities, and the environment. this review provides a thorough overview and sufficient knowledge of the many methods available for identification, as well as the benefits of employing them, which supports the decision to utilize a deep neural network to design a novel and robust identification methodology for iot items. the report establishes the groundwork for future research by employing ml/dl-based aa to collaboratively and unified address iot security issues. to meet the crucial eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e2 design a framework for iotidentification, authentication and anomaly detection using deep learning: a review 7 criteria for iot security, for example, the vast number of encryption methods needed for an aa process could be re-designed to be lighter, cooperative, and adaptable by utilizing ml/dl-based approaches. this study discusses a number of topics, including authentication protocol reliability, per-service authorization, set of data inaccessibility, overhead reduction through sharing of information, services-trust relationships, easy, period, and destination authentication schemes, as well as reinforcement for aa. references [1] m. swan, "sensor mania! the internet of things, wearable computing, objective metrics, and the quantified self 2.0," journal of sensor and actuator networks, vol. 1, no. 3, pp. 217-253, 2012. [2] c. cai, m. hu, d. cao, x. ma, q. li, and j. liu, "selfdeployable indoor localization with acoustic-enabled iot devices exploiting participatory sensing," ieee internet of things journal, vol. 6, no. 3, pp. 5297-5311, 2019. [3] c. wang, h. lin, and h. jiang, "cans: towards congestion-adaptive and small stretch emergency navigation with wireless sensor networks," ieee transactions on mobile computing, vol. 15, no. 5, pp. 1077-1089, 2015. [4] s. lateef, m. rizwan, and m. a. hassan, "security threats in flying ad hoc network (fanet)," computational intelligence for unmanned aerial vehicles communication networks, pp. 73-96, 2022. [5] m. hu et al., "on the joint design of routing and scheduling for vehicle-assisted multi-uav inspection," future generation computer systems, vol. 94, pp. 214223, 2019. [6] m. chen, f. herrera, and k. hwang, "cognitive computing: architecture, technologies and intelligent applications," ieee access, vol. 6, pp. 19774-19783, 2018. [7] a. hussain, m. imad, a. khan, and b. ullah, "multi-class classification for the identification of covid-19 in x-ray images using customized efficient neural network," in ai and iot for sustainable development in emerging countries: springer, 2022, pp. 473-486. [8] s. p. rm et al., "load balancing of energy cloud using wind driven and firefly algorithms in internet of everything," journal of parallel and distributed computing, vol. 142, pp. 16-26, 2020. [9] h. zeyu, x. geming, w. zhaohang, and y. sen, "survey on edge computing security," in 2020 international conference on big data, artificial intelligence and internet of things engineering (icbaie), 2020: ieee, pp. 96-105. [10] f. e. f. samann, s. r. zeebaree, and s. askar, "iot provisioning qos based on cloud and fog computing," journal of applied science and technology trends, vol. 2, no. 01, pp. 29-40, 2021. [11] s. shehzadi, m. a. hassan, m. rizwan, n. kryvinska, and k. vincent, "diagnosis of chronic ischemic heart disease using machine learning techniques," computational intelligence and neuroscience, vol. 2022, 2022.k. ali and s. askar, "security issues and vulnerability of iot devices," international journal of science and business, vol. 5, no. 3, pp. 101-115, 2021. [12] o. uviase and g. kotonya, "iot architectural framework: connection and integration framework for iot systems," arxiv preprint arxiv:1803.04780, 2018. [13] s. i. ullah, a. w. ullah, a. salam, m. imad, and f. ullah, "performance analysis of pox and ryu based on dijkstra’s algorithm for software defined networking," in european, asian, middle eastern, north african conference on management & information systems, 2021: springer, pp. 24-35. [14] f. s. fizi and s. askar, "a novel load balancing algorithm for software defined network based datacenters," in 2016 international conference on broadband communications for next generation networks and multimedia applications (cobcom), 2016: ieee, pp. 1-6. [15] s. k. askar, "adaptive load balancing scheme for data center networks using software defined network," science journal of university of zakho, vol. 4, no. 2, pp. 275-286, 2016. [16] ahmad, s. and hassan, m., 2022. secure communication routing in fanets: a survey. studies in computational intelligence, pp.97-110. [17] g. a. qadir and s. askar, "software defined network based vanet," international journal of science and business, vol. 5, no. 3, pp. 83-91, 2021. [18] s. askar, g. zervas, d. k. hunter, and d. simeonidou, "adaptive classified cloning and aggregation technique for delay and loss sensitive applications in obs networks," in 2011 optical fiber communication conference and exposition and the national fiber optic engineers conference, 2011: ieee, pp. 1-3. [19] m. s. mahdavinejad, m. rezvan, m. barekatain, p. adibi, p. barnaghi, and a. p. sheth, "machine learning for internet of things data analysis: a survey," digital communications and networks, vol. 4, no. 3, pp. 161-175, 2018. [20] h. u. rehman, m. asif, and m. ahmad, "future applications and research challenges of iot," in 2017 international conference on information and communication technologies (icict), 2017: ieee, pp. 6874. [21] a. salam, f. ullah, m. imad, and m. a. hassan, "diagnosing of dermoscopic images using machine learning approaches for melanoma detection," in 2020 ieee 23rd international multitopic conference (inmic), 2020: ieee, pp. 1-5. [22] i. kök, m. u. şimşek, and s. özdemir, "a deep learning model for air quality prediction in smart cities," in 2017 ieee international conference on big data (big data), 2017: ieee, pp. 1983-1990. [23] f. zantalis, g. koulouras, s. karabetsos, and d. kandris, "a review of machine learning and iot in smart transportation," future internet, vol. 11, no. 4, p. 94, 2019. [24] m. a. hassan, m. imad, t. hassan, f. ullah, and s. ahmad, "impact of routing techniques and mobility models on flying ad hoc networks," in computational intelligence for unmanned aerial vehicles communication networks: springer, 2022, pp. 111-129. [25] g. alpár et al., "new directions in iot privacy using attribute-based authentication," in proceedings of the acm international conference on computing frontiers, 2016, pp. 461-466. [26] e. yadav and e. ankur, "a survey of growth and opportunity of internet of things (iot) in global scenario," international journal of innovative research in computer and communication engineering, vol. 4, pp. 20664-20671, 2016. eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e2 aimen shoukat et al. 8 [27] j. b. bernabe, j. l. hernandez-ramos, and a. f. s. gomez, "holistic privacy-preserving identity management system for the internet of things," mobile information systems, 2017. [28] m. imad, f. ullah, and m. a. hassan, "pakistani currency recognition to assist blind person based on convolutional neural network," journal of computer science and technology studies, vol. 2, no. 2, pp. 12-19, 2020. [29] m. rizwan et al., "risk monitoring strategy for confidentiality of healthcare information," computers and electrical engineering, vol. 100, p. 107833, 2022. [30] m. a. hassan, s. i. ullah, a. salam, a. w. ullah, m. imad, and f. ullah, "energy efficient hierarchical based fish eye state routing protocol for flying ad-hoc networks," indonesian journal of electrical engineering and computer science, vol. 21, no. 1, pp. 465-471, 2021. [31] d. bandyopadhyay and j. sen, "internet of things: applications and challenges in technology and standardization," wireless personal communications, vol. 58, no. 1, pp. 49-69, 2011. [32] m. a. hassan, a. r. javed, t. hassan, s. s. band, r. sitharthan, and m. rizwan, "reinforcing communication on the internet of aerial vehicles," ieee transactions on green communications and networking, 2022. [33] s. i. ullah, a. salam, w. ullah, and m. imad, "covid-19 lung image classification based on logistic regression and support vector machine," in european, asian, middle eastern, north african conference on management & information systems, 2021: springer, pp. 13-23. [34] h. r. abdulqadir et al., "a study of moving from cloud computing to fog computing," qubahan academic journal, vol. 1, no. 2, pp. 60-70, 2021. [35] t. wang, m. z. a. bhuiyan, g. wang, l. qi, j. wu, and t. hayajneh, "preserving balance between privacy and data integrity in edge-assisted internet of things," ieee internet of things journal, vol. 7, no. 4, pp. 2679-2689, 2019. [36] b. sharma, l. sharma, and c. lal, "anomaly detection techniques using deep learning in iot: a survey," in 2019 international conference on computational intelligence and knowledge economy (iccike), 2019: ieee, pp. 146-149. [37] m. imad, a. hussain, m. a. hassan, z. butt, and n. u. sahar, "iot based machine learning and deep learning platform for covid-19 prevention and control: a systematic review," ai and iot for sustainable development in emerging countries, pp. 523-536, 2022. [38] lateef, s., rizwan, m. and hassan, m., 2022. security threats in flying ad hoc network (fanet). studies in computational intelligence, pp.73-96. [39] h.-t. pai, s.-h. wang, t.-s. chang, and j.-x. wu, "challenge of anomaly detection in iot analytics," in 2020 ieee international conference on consumer electronicstaiwan (icce-taiwan), 2020: ieee, pp. 1-2. [40] m. imad, s. i. ullah, a. salam, w. u. khan, f. ullah, and m. a. hassan, "automatic detection of bullet in human body based on x-ray images using machine learning techniques," international journal of computer science and information security (ijcsis), vol. 18, no. 6, 2020. [41] m.imad, n. khan, f. ullah, m. a. hassan, and a. hussain, "covid-19 classification based on chest x-ray images using machine learning techniques," journal of computer science and technology studies, vol. 2, no. 2, pp. 01-11, 2020. [42] hassan, m., ullah, s., khan, i., hussain shah, s., salam, a. and ullah khan, a., 2020. unmanned aerial vehicles routing formation using fisheye state routing for flying ad-hoc networks. the 4th international conference on future networks and distributed systems (icfnds). [43] m. imad, m. abul hassan, s. hussain bangash and naimullah, "a comparative analysis of intrusion detection in iot network using machine learning", studies in big data, pp. 149-163, 2022. available: 10.1007/978-3-031-05752-6_10. [44] m. hassan, s. ali, m. imad and s. bibi, "new advancements in cybersecurity: a comprehensive survey", studies in big data, pp. 3-17, 2022. available: 10.1007/978-3-031-05752-6_1. eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e2 this is a title eai endorsed transactions on smart cities research article 1 ultra-low latency v2x systems with ai-driven resource optimization milad rahmati mrahmat3@uwo.ca independent researcher, los angeles, california abstract achieving ultra-low latency in vehicle-to-everything (v2x) communication is essential for ensuring the safety and effectiveness of autonomous vehicles (avs). however, existing systems often struggle to meet the stringent latency demands, particularly in complex and rapidly changing urban environments. this study introduces an innovative framework that utilizes artificial intelligence (ai) for dynamic resource allocation in v2x networks. by integrating real-time data analysis, edge computing, and 5g capabilities, the proposed approach effectively minimizes latency. simulation results indicate up to a 35% reduction in latency compared to conventional models, underscoring the potential of ai in enhancing the responsiveness and reliability of v2x systems. these findings offer a significant step toward making autonomous vehicle deployments more viable in smart cities. keywords: autonomous vehicles; v2x communication; ultra-low latency; artificial intelligence; resource optimization; edge computing; 5g networks; smart cities. received on 04 january 2025, accepted on 05 march 2025, published on 18 november 2025 copyright © 2025 milad rahmati, licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.8366 1. introduction the advent of autonomous vehicles (avs) has brought a pressing need for communication systems that can meet the high-speed and low-latency demands required for their seamless operation. vehicle-to-everything (v2x) communication is central to this effort, enabling the exchange of critical data between vehicles, road infrastructure, pedestrians, and broader networks [1]. despite recent advancements, meeting the ultra-low latency requirements necessary for applications like collision avoidance and emergency response remains a substantial hurdle, especially in complex urban environments. existing v2x frameworks often fail to deliver the submillisecond latency essential for safety-critical functions [2]. network congestion, the unpredictability of vehicular movement, and the uneven distribution of communication resources exacerbate these challenges. while 5g technology promises to enhance bandwidth and network efficiency, its deployment introduces additional hurdles such as managing scalability and dynamic resource demands [3]. in this context, artificial intelligence (ai) has emerged as a potential game-changer. machine learning (ml) and predictive analytics offer new possibilities for addressing the inefficiencies of traditional v2x communication. by intelligently managing network resources in real time, aidriven systems can adapt to fluctuating conditions, reduce delays, and enhance overall network performance [4]. incorporating edge computing further strengthens these capabilities, allowing for faster data processing closer to the source and minimizing communication delays. this paper introduces a novel ai-based framework for resource optimization in v2x systems, focusing on achieving ultra-low latency. the framework combines realeai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ milad rahmati 2 time analytics, advanced ml models, and edge computing to dynamically allocate resources and mitigate communication delays. simulations demonstrate that this approach reduces latency by up to 35% compared to existing methods, making it an effective solution for urban smart city applications. 2. related work the rapid evolution of autonomous vehicles (avs) has placed significant focus on enhancing vehicle-toeverything (v2x) communication systems. this section reviews key advancements in latency reduction, resource management, and the integration of artificial intelligence (ai) within v2x networks. 2.1 addressing latency in v2x communication reducing latency in v2x communication is vital for ensuring the safety and effectiveness of av systems. even minor delays can compromise critical functions like collision avoidance and emergency braking. many studies emphasize improving network infrastructure, such as adopting 5g technology, to enable faster and more reliable data transfer [1]. however, as highlighted in [2], submillisecond latency targets remain challenging due to factors such as dynamic network conditions, vehicular mobility, and signal interference, particularly in urban environments. 2.2 enhancing resource allocation optimizing resource utilization is a cornerstone of efficient v2x communication, especially in scenarios involving heavy network traffic. techniques like network slicing have been proposed to allocate dedicated resources for various vehicular applications, ensuring higher efficiency and reliability [3]. predictive methods, as explored in [4], aim to estimate network demands and allocate resources in advance, thereby mitigating potential delays. however, these strategies often struggle to scale effectively in highdensity environments. 2.3 ai in v2x communication systems the integration of ai into v2x communication introduces dynamic and adaptive capabilities, enabling systems to respond intelligently to real-time scenarios. machine learning models have been applied to predict traffic conditions, optimize routing, and manage network resources adaptively [5]. furthermore, the use of edge computing, as discussed in [6], allows data to be processed closer to its source, significantly reducing reliance on centralized systems and minimizing delays. 2.4 unresolved challenges and research gaps despite these advancements, several critical issues remain unaddressed. current ai-driven solutions often encounter scalability challenges in densely populated areas, where the heterogeneity of devices and networks complicates operations [7]. additionally, many existing frameworks rely on static configurations, which are less effective in dynamic environments. this study aims to bridge these gaps by presenting a robust ai-based framework that combines real-time analytics with edge computing to achieve ultra-low latency and optimized resource allocation in v2x systems. 3. methods this section outlines the proposed ai-based framework aimed at minimizing latency in v2x communication systems. the approach combines real-time data processing, machine learning (ml), and edge computing to dynamically optimize resource allocation. the methodology is presented in four key subsections: system architecture, machine learning model, resource allocation strategy, and simulation setup. 3.1 system architecture the framework is built upon a decentralized three-layer architecture designed to address latency and scalability issues: 1. edge layer: this layer is responsible for processing data at or near its source, such as in roadside units or onboard vehicle systems. utilizing edge computing reduces the dependency on centralized processing, thereby minimizing latency [1]. the total latency l in a v2x system can be expressed as the sum of transmission delay ( tl ), propagation delay ( pl ), processing delay ( prl ), and queuing delay ( ql ): (1) 2. network layer: acting as a communication bridge, this layer facilitates data exchange between edge devices and the core system. leveraging 5g technology, it supports high-speed and low-latency transmission even under heavy network loads [2]. 3. core layer: this layer handles system-wide coordination and optimization. advanced ai t p pr ql l l l l= + + + eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | ultra-low latency v2x systems with ai-driven resource optimization 3 algorithms analyze data, predict traffic patterns, and devise strategies for efficient resource utilization in real time [3]. 3.2 machine learning model the proposed framework incorporates a reinforcement learning (rl) model, which adapts to dynamic network conditions to allocate resources effectively. the rl model is characterized by: • state representation: capturing key network metrics such as latency, bandwidth usage, and vehicle density. • action space: defining possible adjustments to system parameters, including bandwidth allocation and routing changes. • reward function: rewarding actions that lead to latency reduction and penalizing those resulting in inefficiency or excessive delays [4]. the rl model's objective is to maximize the expected cumulative reward r , defined as: (2) where γ is the discount factor (0 < γ ≤ 1), tr is the reward at time step t , and t is the time horizon. the rl model continuously learns from both historical data and real-time inputs, refining its strategies to enhance overall system performance. 3.3 resource allocation strategy the resource allocation mechanism combines predictive analytics with adaptive algorithms to preemptively address changing network demands. the process includes the following steps: 1. data aggregation: real-time data from vehicles, sensors, and infrastructure is collected and preprocessed at the edge layer. 2. traffic prediction: using machine learning techniques, the core layer forecasts traffic loads and identifies potential congestion points. 3. dynamic allocation: resources such as bandwidth and computing power are allocated based on predicted demand. adjustments are made dynamically as new data becomes available, ensuring optimal performance [5]. the optimal bandwidth allocation ib for a node i can be modeled as: (3) where iλ is the demand of node i , n is the total number of nodes, and totalb is the total available bandwidth. 3.4 simulation setup to evaluate the framework's effectiveness, simulations were conducted in a controlled virtual environment replicating urban traffic conditions. key variables such as vehicle density, data rates, and mobility patterns were adjusted to test the framework's adaptability. performance metrics, including latency, resource utilization, and scalability, were recorded and analyzed. results of the simulations are presented in the following section. the latency improvement i compared to a baseline system can be expressed as: (4) where baselinel is the latency of the baseline system, and proposedl is the latency of the proposed framework. 4. results this section presents the outcomes of the simulations designed to assess the effectiveness of the proposed aibased framework for minimizing latency in v2x communication. key performance metrics such as latency, resource utilization, and scalability were analyzed under various traffic and network conditions. 4.1 simulation setup the simulation environment was created to emulate a dense urban area with fluctuating traffic patterns and high vehicular activity. key parameters included: • number of vehicles: ranged between 500 and 1,000 autonomous vehicles. • network infrastructure: utilized 5g technology integrated with edge computing capabilities. 1 i i totaln j j b bλ λ = = ⋅ ∑ 0 t t t t r rγ =  =    ∑e 100%baseline proposed baseline l l i l − = × eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | milad rahmati 4 • performance metrics: evaluated average latency (ms), bandwidth utilization (%), and scalability under increasing loads. 4.2 performance metrics 4.2.1 latency analysis the framework exhibited a significant reduction in communication latency compared to the baseline system: • the baseline latency ( baselinel ) averaged 20 milliseconds across multiple test scenarios. • the proposed system latency ( proposedl ) was reduced to an average of 13 milliseconds. the percentage improvement in latency ( i ) was calculated using the formula: substituting the values: this 35% improvement highlights the framework’s capability to effectively reduce delays in high-demand v2x environments. as shown in figure 1, the proposed framework achieves a significant reduction in latency compared to the baseline system, particularly under high network loads. 4.2.2 resource utilization efficiency the framework dynamically allocated bandwidth based on real-time demand, ensuring optimal usage. the formula used for resource allocation was: where iλ is the demand for node i , and totalb represents the total available bandwidth. the simulation demonstrated that this approach led to approximately 25% greater efficiency in bandwidth usage compared to static allocation methods. this improvement is critical for sustaining high performance in dense urban traffic conditions. figure 2 illustrates the significant improvement in bandwidth utilization achieved by the proposed framework, ensuring optimal resource distribution even under heavy traffic. 4.2.3 scalability the framework was subjected to tests involving an increasing number of connected vehicles, ranging from 500 to 1,000 devices. results showed that the system maintained consistent latency and resource efficiency across these varying loads. even at the highest traffic densities, performance degradation was limited to less than 5%, demonstrating the scalability and robustness of the proposed solution. the scalability of the proposed framework is evident in figure 3, where it maintains stable performance as the number of connected devices increases. figure 1. latency comparison between the baseline system and the proposed framework across various network loads. figure 2. bandwidth utilization efficiency comparison between the baseline system and the proposed framework. 100%baseline proposed baseline l l i l − = × % 2 % 0 20 13 100 35i − = × = 1 i i totaln j j b bλ λ = = ⋅ ∑ eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | ultra-low latency v2x systems with ai-driven resource optimization 5 figure 3. performance scalability of the proposed framework under increasing vehicular density. 4.3 comparative performance a comparative analysis was conducted to evaluate the proposed framework against conventional systems. table 1 summarizes the results across key metrics. table 1. results summary metric baseline system proposed framewor k improvemen t (%) latency (ms) 20 13 35 bandwidt h utilization (%) 70 88 25 scalability (devices) moderat e high 5. discussion the results from the simulation demonstrate the significant advantages of the proposed ai-driven framework for v2x communication, particularly in achieving ultra-low latency, efficient resource utilization, and scalability. this section delves into the implications of these findings, compares them with existing approaches, and explores their broader relevance to smart city applications. 5.1 latency reduction the reduction in latency achieved by the framework highlights its potential for real-time v2x applications, such as collision avoidance and emergency braking. by combining edge computing with reinforcement learning, the system dynamically adapts to network demands, ensuring consistent performance even under high vehicular density. compared to traditional systems that rely on static configurations, the proposed approach demonstrates a 35% improvement in latency, as shown in figure 1. this underscores the critical role of real-time analytics in meeting the stringent requirements of autonomous vehicle networks. 5.2 efficient resource allocation the dynamic bandwidth allocation strategy employed by the framework ensures optimal resource distribution across connected devices. unlike static allocation methods that often result in resource underutilization or congestion, the ai-driven approach anticipates network demands using predictive analytics. the observed 25% improvement in bandwidth utilization (figure 2) reinforces the importance of adaptive systems in managing network resources effectively, particularly in urban environments with fluctuating traffic patterns. 5.3 scalability and robustness the scalability of the proposed framework, evident in figure 3, demonstrates its robustness in handling largescale deployments. even as the number of connected vehicles increased to 1,000, the system maintained consistent latency and resource efficiency, with minimal performance degradation (less than 5%). this positions the framework as a viable solution for future smart city deployments, where the density of connected devices is expected to grow exponentially. 5.4 comparison with existing models when compared to state-of-the-art systems, the proposed framework offers several advantages: • dynamic adaptability: unlike static models, it adapts to real-time conditions, ensuring consistent performance. • edge computing integration: localized data processing minimizes reliance on centralized cloud systems, reducing latency. • ai-driven optimization: reinforcement learning enables proactive resource management, a feature absent in many existing systems. these distinctions make the proposed approach a comprehensive solution to the challenges of modern v2x communication systems. eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | milad rahmati 6 5.5 broader implications the findings of this study have far-reaching implications for the development of smart transportation systems: 1. enhanced safety: improved latency ensures faster response times, reducing the likelihood of accidents in autonomous driving scenarios. 2. energy efficiency: by optimizing resource usage, the system minimizes energy consumption in network operations. scalable deployment: the framework’s robustness makes it suitable for integration into future smart city infrastructure, supporting applications beyond autonomous vehicles, such as intelligent traffic management and emergency response systems. 6. conclusion the growing reliance on autonomous vehicles in urban environments has highlighted the critical need for robust and efficient v2x communication systems. this study proposed an ai-driven framework designed to address key challenges in latency, resource allocation, and scalability. through the integration of edge computing, machine learning, and predictive resource management, the framework demonstrated substantial improvements over conventional systems. 6.1 key contributions the main contributions of this research are summarized as follows: 1. latency optimization: the framework achieved a 35% reduction in latency, meeting the stringent requirements for safety-critical applications such as collision avoidance and emergency braking. 2. dynamic resource allocation: by leveraging reinforcement learning, the system dynamically adjusted bandwidth allocation, resulting in a 25% improvement in resource utilization compared to static models. 3. scalability: the framework maintained consistent performance with minimal degradation in environments with up to 1,000 connected vehicles, highlighting its suitability for large-scale deployments. 6.2 practical implications the proposed framework holds significant potential for real-world applications, including: • smart transportation systems: improved communication efficiency facilitates safer and more reliable autonomous driving. • urban traffic management: enhanced scalability supports the development of intelligent traffic solutions in smart cities. • energy-efficient networks: optimized resource utilization reduces the energy footprint of vehicular communication systems. 6.3 limitations and future work while the proposed framework offers substantial benefits, some limitations remain. the study relied on simulations to evaluate performance, which may not fully capture the complexities of real-world deployments. future work could focus on: • conducting field trials to validate the framework under actual traffic conditions. • exploring the integration of 6g technologies to further enhance system performance. investigating advanced ai models, such as federated learning, to improve data privacy and scalability in distributed environments. references [1] smith j, johnson r. enhancing v2x communication with 5g technologies. journal of vehicular networks. 2020;15(4):325–340. [2] doe a, lee p. latency challenges in autonomous vehicle networks. ieee transactions on intelligent transportation systems. 2019;12(2):110–120. [3] chen m, wang t. resource allocation in v2x systems using network slicing. acm transactions on networking. 2021;19(1):45–58. [4] zhang h, patel s. predictive analytics for dynamic resource management in v2x. international journal of artificial intelligence in transportation. 2022;8(3):221–235. [5] li x, kumar n. machine learning applications in autonomous vehicular communication. ieee access. 2020;18:7890–7905. [6] garcia f, brown k. the role of edge computing in latency reduction for v2x. journal of smart city technologies. 2021;5(2):98–112. [7] yang q, thompson j. scalability and heterogeneity in aibased v2x systems. transactions on emerging telecommunications technologies. 2020;31(7):1245– 1260. eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | raspberry pi-based intelligent cyber defense systems for smes and smart-homes: an exploratory study raspberry pi-based intelligent cyber defense systems for smes and smart-homes: an exploratory study sreenivas sremath tirumalaη ∗, narayan nepalα and sayan kumar rayη ηschool of digital technologies, manukua institute of technology, auckland, new zealand α yoobee colleges, christchurch, new zealand. abstract ongoing ransomware attacks have forced business to think about security of their resources. recently, smallto-medium enterprises (smes) and smart-homes have become easy targets for attackers since they don’t have cyber defense mechanism in place other than simple firewall systems which are quite vulnerable. cyber defense systems are costly and often not within the budget of smes or families which inspired to think about low cost yet highly efficient cyber defense solutions. regular individuals and families who use internet for day to day use often end-up becoming a possible resource for using them as trojan or bitcoin nodes. this research explores the prospects of implementing a raspberry pi (raspberry pi)-based intelligent cyberdefense system (icds) for sme networks and smart-homes to filter malicious contents from incoming traffic and detect malware using artificial intelligence. primarily, the work presented in this paper tries to evaluate the hardware capability of network interfaces (both internal, and attached) of raspberry pi for handle high volumes of incoming traffic. for this, we measure the network performance of the raspberry pi using the speed test software and try to explore the possibility of a light weight machine learning (ml) based malware detection. the results show that the built in ethernet interface outperforms the built in wifi and external attached usb to ethernet adapter in terms of latency, download and upload throughput. also, a new dna based ml approach was successfully able to produce over 19.5% better accuracy rates of over classifier trained with hash-sequence. the experiment results further emphasise on the importance of generating complex malware signatures with variety to face existing threats which has taken a new form due to increase in malware based attacks, particularly for ransomware. the complexity of the generated malware is based on generic yet strong encryption principles which produced good results which is quite encouraging at this stage. received on 15 march 2022; accepted on 25 july 2022; published on 03 august 2022 keywords: cyber defense, raspberry-pi, intelligent cyber-defense system copyright © 2022 s s tirumala et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eetsc.v6i18.2345 1. introduction cybersecurity is the point of interest in this internet reliant age of e-connectivity,e-appliances and smart homes. privacy, security and trust are the three pillars of cybersecurity [1, 2]. the importance of privacy and trust are more related to data security and ∗sreenivas sremath tirumala. email: sreenivas.tirumala@manukua.ac.nz are protected through the implementation of security services, framework and standards [3]. the security relies on technology, software as well as principles of application. though majority of security systems are based on standards the reliability of these software became questionable with the recent incidents of ransomware attacks. it can be noticed that the aspect of reliability is not just confined to standards or rules or even type of software. the reliability is based on 1 eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 http://creativecommons.org/licenses/by/3.0/ mailto:<sreenivas.tirumala@manukua.ac.nz> mailto:<sreenivas.tirumala@manukua.ac.nz> efficiency of the system to stop unknown variants or malware. the internet revolution had notable impact on dayto-day activities of both individuals and businesses. smart-devices became part and parcel of daily life. with the development of smart-homes the reach of internet had a new horizon. also, recent cyberrevolution impacted the growth of small-to-medium enterprises (smes) due to reduction of cost and availability of resources. the cloudification (moving the software and other operations services to cloud) of smes partially impacted the dependence on local hardware and networking configurations. this reliance on internet made smes and smart homes exposed to the rest of the world, particularly for hackers as soft targets for exploitation particularly through ransomware attacks. the operational implications of providing a secure environment for smes is costly due to demanding resource requirements like manpower and technology. with limited operational budget, majority of smes rely on internet service providers (isps) and local firewall or antivirus software for providing it security. in countries like new zealand, where majority of the business are smes, impose budget and resource constraints and are not be able to afford operational costs for providing cyber defense systems. according to a survey conducted by internetnz, about 48% of computers in smes are used by hackers for testing new malware and / or as bots to simulate denial of service (dos) attacks. also, considering the recent events where gaming devices are used for mining bitcoins, there is a high chance for smart-homes being easy targets by hackers. hence, the internal networks of smes and smart-homes have to be secured enough to prevent such external attacks [4]. simple rule-based firewalls (i.e., based on administrator defined policies) of smes have failed to prevent attacks from random malware. rule-based intruder detection systems (ids) have managed to counter the attacks to some extent but not fully capable to provide complete security to the organization’s network. the rule-based systems simply monitor and filter incoming network traffic based on set of predefined rules (malware signatures) stored in the repository. from the literature and implementation documents [5] it can be concluded that highly efficient ids is more powerful and assertive in identifying malicious packets entering a network. however, traditional ids requires special equipment and manpower and thus are resource savvy and costly to install and maintain. also, it requires regular upgrades to identify and respond to new threats. thus, majority of the smes with limited budget find it difficult to implement and maintain an effective ids. implementing low cost ids solution that can operate as security as a service (secaas) and can be offered as subscription-based service, is another option for smes to consider. however, secaas still relies on rule-based systems and incurs all drawbacks of cloud-based and other remote service offerings. moreover, the fact that secaas is expensive, a major concern for smes and are not effective for networks with iot based devices [6, 7]. with the rapid integration of iot with traditional networks, secaas may become a burden as the subscriptions needs to be paid in spite of them being used few times, purging less resources or bandwidth. formerly, computer networks are protected by firewall from the external attacks which is not different for smart-homes and smes. however, the usage of algorithms to create malware with no standard structure or pattern challenged the capabilities of simple rule-based firewalls and ids. majority of the firewall systems as well as ids are based on administrator defined policies, or in simple terms, rule based. at present, the traffic is monitored and ’filtered’ based on a set of rules (malware signatures) present in the repository. the limitations of firewalls, ids and secaas discussed above, indicate an immediate necessity of introducing a low-cost, low-resourced yet advanced network security solution for smes particularly for stopping, as much as possible, the malicious network traffic from entering the networks. 1.1. malware detection malware detection has been a key aspect of cybersecurity particularly with recent developments in cloudification i.e., moving application to cloud. traditional malware detection is based on matching malicious imprints (hash) through a fuzzy logic based comparison. signature based malware detection is popular and often considered as efficient for detecting malware in the incoming traffic for the signature that exists in the repository [8]. the signature based approach is capable of handling new unknown variants to some extent. however, it is time-consuming and often impractical to keep the repository updated based on new variant particularly with the rate of generation of new variants with complexity and variety. recent advances in machine learning (ml) and encryption based methods have enabled attacker to adopt these approaches to generate new variants that challenged traditional repository based techniques including the signature based malware detection approaches [9]. traditional malware detection, either rule based or signature based is time consuming and often not efficient in detecting all if not majority of malware imprints due to significant changes in the structure and patterns of the new variants [10]. as early as 2017, institute for critical infrastructure technology has hinted at the demise of signature based malware detection in the technical report [11]. considering malware detection as a pattern recognition problem, 2 sreenivas sremath tirumala, narayan nepal and sayan kumar ray eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 several ml based malware detection approaches have emerged [12, 13]. using bio-inspired approaches for malware detection is also area of high interest in recent times and has been considered an alternative for ml based pattern recognition problems. for instance, malware detection and analysis using dna based approaches has been a topic of research interest since 2012 [14]. this inspired to undertake an exploratory study on designing an intelligent intruder detection systems (iids) that can be implemented on a low-cost device to provide a small budget solution to smes and smarthomes. there has been some background work on non-rule based (pattern recognition based) solution for detecting malware [15] this paper explores the prospects of implementing a low-cost intelligent cyber defense system (icds), in form of a filtering device, to protect the smes from malicious traffic. the proposal considers the plausibility of using raspberry pi device as a commercial ids with the purpose of filtering malicious network traffic from entering sme networks. primarily, through a systematic experimental evaluation this work tries to explore the capability of network interfaces of raspberry pi device to understand their competence in handling high volumes of incoming traffic similar to commercial ids systems. a comparative study of the performance of the inbuilt network interfaces, namely ethernet (wired) and wifi on the raspberry pi device, as well as an externally connected usb adapter interface (usb to ethernet interface) are carried out in context to network parameters like latency, download throughput and upload throughput. the key contribution of this paper is providing a framework for a systematic research on implementing low-cost ids systems with advanced machine learning (ml) based approach. although there has been research on using ml algorithms for detecting intruders, a combination of low-cost raspberry pi and ml based approaches for ids have not been undertaken. moreover, earlier works uses only one network interface whereas this research is proposing a systematic approach to evaluates a combinations of network interface devices. this research also contributes towards using feature extraction and comparison for detecting malware or network anomalies. typically, there will be a separate feature extractor and classifier. this research for proposes to use autoencoders, a special type of artificial neural networks which is can be used as feature extractor and classifier. this research would also encourage to use raspberry pi or similar devices for portable and low cost devices for ids. smart cities often uses low powered internet based devices that can be controlled over internet. hence, privacy and security are the two key aspects to be considered. thus, all smart city solutions requires cyber security devices for detecting malware / intruders. smart cities also requires ids solutions that are low cost since the purpose is private and individual. the icds proposed in this paper is an ideal and well suitable for smart cities since icds is low cost, less computations savvy. also, icds provides a smart and intelligent system that provides real-time updates for detecting malware. the remainder of the paper is structured as follows. section ii provides a literature review of the different filtering approaches and dna based malware detection approaches.this section also while, section iii explores the prospects of using raspberry pi device as an icds, section iv discusses the evaluation results and section v concludes the paper. 2. related work there is a lack of systematic literature review on implementing low cost ids solutions for smart-homes and smes. furthermore, very few research projects have been done on the feasibility of implementing raspberry pi (or a similar device)-based low-cost ids for smart-homes and similar small networks that exists in smes and smart homes. this research gap provides an immediate necessity of such a research study to start with. a standard case of identifying low cost ids solution for smart homes and sme networks (containing different iot devices), particularly using raspberry pi based implementation, is relevant to the current research. also there is a significant rise in the usage of iot based security devices for smart homes and smes [16]. also with the recent advances in using smart devices, it is widely accepted that there are several security concerns that needs to be addressed [17]. 2.1. iot based ids implementations iot-based ids implementations proposed by the research fraternity are mostly for non-commercial purpose and are either policy-based or graph-based. policybased approaches [18, 19] depend on a fixed predefined policy based on a specific domain or problem-based scenario similar to traditional network traffic packet filtering approaches. the graph-based approaches [20] implement polices stored in a repository, which can be updated periodically (follows a dynamic rule). such updates, however, lead to latency. a raspberry pi based firewall proposed by [21] to secure home networks, uses a remote cloud database with set of predefined rules. it uses on-board ethernet interface for incoming network traffic and wifi for outgoing traffic. the proposed approach is prone to delays and when applied for sme networks may incur significant latency. another non-commercial implementation named as piids is 3 raspberry pi-based intelligent cyber defense systems for smes and smart-homes: an exploratory study eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 a raspberry pi 2.0-based standalone firewall implemented to filter websites in a school network. although, an interesting concept, it has significant limitations in context to operation time and network traffic filtering capability. few research also proposed installing open source idss on raspberry pi so that it can replace a regular computer and can operate as a complete ids of its own. for example, netgaurd, proposed for traffic monitoring to track man-in-the-middle attacks, installs an open vpn and ids software on raspberry pi to implement a complete ids [22]. however, netgaurd is nothing different to a traditional ids and just provides privacy by hiding the ip of the monitoring source, as an extra feature. there are few other similar implementations like [23, 24]. the mere purpose of these implementation is to install and test ids software on raspberry pi for various purposes. two other research proposed by [25, 26], used classification techniques for detection malicious contents in incoming network traffic. however, not only these two proposals lacked the technical details of hardware and software limitations of raspberry pi when experimenting it as an ids, but also, they considered limited traffic with known malicious variants during the experiments. so, previous research mostly focused on studying how raspberry pi-based ids can be implemented and if it can replace the traditional rule-based ids implemented on normal computers. these implementations, knowingly or unknowingly overlooked the different challenges, including hardware limitations, to make raspberry pi operate as a fully commercial and real-world implementation of ids. furthermore, such implementations are vertically divided into cloud based and non-cloud based and do not emphasize the need of a mixed model or failover model. filtering approaches. traditional firewalls and idss use packet inspection for filtering traffic based on malware impressions [27–29]. the workable solution proposed in [28] used a conceptual ’trust’ based filtering that only allowed ’useful’ packets to pass through. false positive results are often produced by the trust-based approach (similar to traditional fuzzy rule-based approach) and hence it was inconsistent in nature [28]. however, the proposed approach was successful in detecting malicious contents resulting from insider attacks in an organization. since, icds mostly deals with identifying and filtering malicious contents from external network traffic trying to penetrate inside an sme network, insider attacks at this stage of the research is not considered. the filtering approach presented in [27] consisted of a restriction and access policy working as a traditional gateway. however, no evidence of experimental evaluation of the approach is proposed. an interesting machine learning based filtering model using support vector machines (svm) and naïve bayes is presented in [29], which also provides a good practical implementation scenario. however, due to its resource heavy and computationally complex nature, this proposed approach is unsuitable for smes. all these discussed research work provide an overview of important methods proposed for malicious network traffic filtering based on purpose and relevance. however, these implementations are generic in nature, not cost effective, and demand high configuration hardware for implementation. the next subsection discusses the implementation of raspberry pi-based low-cost ids systems. key challenges to consider in raspberry pi-based ids. on a practical note, the following challenges need to be considered if implementing a raspberry pibased icds for filtering malicious network traffic contents from entering sme networks. • handling high volumes of traffic: raspberry pi has one on-board ethernet port, which limits and delays the flow of incoming (from the internet) and outgoing traffic (after filtering). how to handle such latency ? if external ethernet adapter is used, what are its implications in terms of power, cost and heat? • processing capabilities: raspberry-pi, being an embedded system has a low end process and its processing capabilities may create some issue while handling the traffic and may effect a significant increase in processing and serialization delay too. • heat and power source: is the hardware of raspberry pi capable enough to run continuously and uninterrupted for a week? • storage and real-time updates of repository: efficient mechanism to store and update the repository (for rule based, signature based or any other approach). the overall research consists of various plausibility studies for hardware, software and algorithms. the ai-based algorithmic evaluation is been initiated and published [4]. this systematic experimental evaluation presented in this paper is confined to understand the capability of input network interface(s) of raspberrypi. 2.2. malware detection approaches malware detection using signatures has been in the practise since the early days of anti-virus designing and development. a malware signature is an unique 4 sreenivas sremath tirumala, narayan nepal and sayan kumar ray eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 figure 1. the block diagram of icds representing various components identifier, typically a hash-sequence, defined using as set of hexadecimal character set. a malware signature can also be considered as an unique footprint of a particular malware with a set of characters. the detection of a malware is performed through searching for hash-values that are imprints of malware in the input data, files or streams. in other words, signature based malware detection requires a repository with existing signatures as a prerequisite. malware detection approaches or methods can be categorised based on process or steps involved in detection, type of detection method used, techniques adopted for implementation or a combination of one of more of these approaches to form a hybrid method. literature presents a vertical categorisation of malware detection into two main categories signature based and anomaly based. fig. 2 presents the process of signature and anomaly based approaches which can be considered as the starting point for understanding the process of malware detection [30]. signature based approaches relies on repository with signatures or rules or both where as anomaly detection process is based on creating a profile from the input data followed by identifying unknown anomalies. malware detection through anomaly based detection technique is also known as behaviour or heuristic malware detection. the key issue with anomaly based detection is its credibility of creating efficient profile. moreover, an anomaly cannot be identified based on only one type of data or patterns which is considered as a major drawback [31] of anomaly based detection. however, ml based, in particular deep learning based approaches trained with good data set are more successful due to their ability to recognising complex patterns from unknown data [32]. considering the type of detection, malware detection process can be categorised as static, dynamic and hybrid [33]. static malware detection is based on investigating hash-sequences (sometimes also referred as binary / byte codes) inside a file whereas dynamic approach tries to detect malware by executing the file in a controlled environment or docker to see the impact to differentiate safe and malicious content. the hybrid approach is a combination of static and dynamic approaches. dynamic malware detection techniques are sometimes referred as behaviour detection techniques creating ambiguity in conventional naming. the implementation of dynamic behavioral approach attained considerable success with both ml [34] and bio-inspired approaches like gene-based malware analysis proposed in [35]. dna based approaches for malware detection. bio-inspired approaches are successful in many domains including cybersecurity. bio-inspired approaches also termed as nature inspired approaches can be either based on natural process or human biological process. the nature inspired computing is based on evolution process for species selection or based on performing a task like ant colony optimisation. human biology and cognition based approaches includes artificial neural networks, dna computing, immunity inspired approach etc. in dna-based approaches, a unique identifier is extracted from malicious content which is called the dna signature. predominantly, majority of the dna-based malware detection is preformed using this approach of extracting unique identifier 5 raspberry pi-based intelligent cyber defense systems for smes and smart-homes: an exploratory study eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 figure 2. malware detection process : the process of signature based and anomaly based malware detection approaches. it can be noted that signature based detection requires a rules / signatures from a file with malicious content or data to create a repository based on the extracted dna imprint (dna signature) [36]. extraction of dna is performed using statistical or ml based feature extraction techniques. the dna signatures thus extracted are used for detection process using ml methods through pattern recognition. malware detection through data mining techniques was proposed in early 2000s [37]. a similar approach was proposed in 2014 for metamorphic malware detection by comparing files with and without a unique signature extracted with dna-based approach [38]. similarly, the dna sequencing-based detection is recently implemented for mobile malware detection [39]. such dna-based techniques often used in extracting malware signatures and applying them for detecting malware by comparing the patterns. for instance, detection of android malware through generating dna fingerprints in the package files is presented in [40]. there are several approaches in the literature which uses dna (identifier) signature extraction applying a variety of feature extraction approaches used in pattern recognition problems including image analysis, water marking detection and other sequencing based detection. it is to be noted that the dna signatures used in these approaches were able to extract dna-based unique patterns to compare with a malware. but, the key issue here is whether there is enough variety and complexity in the repository or the signatures created using the repository. this poses a threat to the entire detection process since the malware detector may not be good enough to handle malware created by attackers which are often strongly encrypted and possess unique characteristics. there is also a possibility of creating malware from these signatures and adding them to the repository. however, the variety and veracity of the malware variants created through extracting dna from the existing signatures cannot be guaranteed. the 6 sreenivas sremath tirumala, narayan nepal and sayan kumar ray eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 work presented in this paper is inspired from this requirement of guaranteeing variety and complexity and tries to propose a new approach for generating malware signatures. a 2013 work published in [41] cites a work (published in korean) that emphasises on malware generation based on dna signatures but not mentioning details about the approaches used to create variety and veracity. this can be considered as only work towards generating malware signatures from dna-based signature repository and could not be compared to the proposed approach due to lack of technical and implementation details. 3. proposed testbed for the experiments figure 3 shows the proposed system model for using raspberry pi 4 as the icds in order to filter malicious packets from entering sme networks. ideally, raspberry pi 4.0 device with 4 gb of ram and 1.5 ghz 64-bit quad-core arm cortex-a72 processor will be used. it has built in ethernet and wifi interfaces. the gigabit ethernet interface in raspberry pi 4.0 can reduce communication latency and provide faster network connectivity. the device also has usb 3.0 and 2.0 ports. usb 3.0 ports can enable transfer of data up to ten times faster than usb 2.0. based on the discussion provided in the previous sub-section, the proposed model will likely opt for option 2, where the on-board ethernet interface will be used for incoming network traffic from external networks trying to enter the sme network through the raspberry pi 4-based icds and an usb ethernet interface (in form of an adaptor) will be used as the exit for the filtered outgoing traffic from the raspberry pi device to the gateway of the connected sme network (refer to fig. 2). there is also an issue with choosing usb ethernet for communication (option 2) as it may slow down the transfer of outgoing network traffic from the raspberry pi device to the gateway of the sme network, however, with the choice of proper usb ethernet adaptor this shortcoming can be overcome. usbs are rated at speeds different to ethernet, for instance, usb 3.0 is rated at 5 gigabits per second whereas usb 2.0 is rated at 54 megabits per second. for our proposed experimental tested in this research, a raspberry pi 4.0 device is used that has a gigabit ethernet interface. also, to ensure that the network communication on the raspberry pi 4.0 board does not slow down, a usb 3.0 gigabit ethernet interface (adaptor) is used so that communication between the two gigabit ethernet interfaces (the onboard one and the usb one) can happen. all the incoming internet traffic meant for the sme network will first enter the raspberry pi based icds acting as a protective shield for the sme network. this entire research work will be carried out in two phases. in the first phase, as mentioned before, the aim is to study the feasibility of using raspberry device to develop the icds and to explore if hardware interfaces on the raspberry-pi device are capable of handling high volume of real traffic. these second phase activities is using artificial intelligence (ai) and dna based approach for detecting malware with low hardware devices like raspberry-pi to support its usage as a commercial icds, which is what this paper will discuss. in the following phase, the incoming traffic on the raspberry pi device will be sent through a cloud-based validation system where the signatures of the packets will be thoroughly checked to identify malicious contents (e.g., malware). such checking will be done at the signature-based detection online module (shown as cloud) of the proposed model where a lightweight ai-based pattern recognition and deep learning algorithm will inspect every packet to filter the malicious contents before letting the outgoing packets pass through the exit usb ethernet interface to safely enter the sme network’s gateway. 3.1. raspberry pi as an icds: from perspective of hardware capability this current research explores the prospects of implementing a raspberry pi (raspberry pi)-based low cost and intelligent cyber-defense system (icds) for sme networks, the architecture of which is presented in fig. 1. in the icds, all incoming traffic to the network of the sme will go through the raspberry pi device that will scan the traffic for any malicious contents. the traffic will be monitored and filtered through a cloud-based filtering system and all malicious traffic will be quarantined for further actions by the sme. a deep learning-based signature verification system will be used for filtering the traffic in the next phase of this work. the primary focus of the work presented in this paper is to explore (a) the feasibility of using raspberry pi device to develop an icds, and (b) if the hardware components present in the latest raspberry pi devices are capable and compatible enough to support the use of raspberry pi-based icds for commercial sme networks. use of raspberry pi as a low-cost device is becoming common in various iot-based systems due to its simple operation, cost effective usage and support of open source software and operating systems. from the literature study presented in section ii, it can be concluded that, although, research has shown the effectiveness of using raspberry pi-based commercial idss, previous work done on this aspect (i.e., use of raspberry pi as a commercial ids) have not evaluated the efficiency and capabilities of the hardware components, especially, the ethernet and wifi modules on the raspberry pi board when handling input and output traffic. also, typically, a commercially 7 raspberry pi-based intelligent cyber defense systems for smes and smart-homes: an exploratory study eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 figure 3. the hardware architecture for the proposed raspberry pi-based icds available ids/firewall will need gigabyte ethernetbased connections for its input and output interfaces depending on the network requirements but each icds, on the other hand, need to have at least two physical interfaces with high end throughput to segregate the internal and external network traffic from each other. thus, to explore whether it is possible to develop a raspberry pi-based icds, monitoring the performance of the different hardware interfaces on the pi device when handling high volume of real traffic, is necessary. the following sub-sections will discuss these in detail. an important point that needs mentioning here is how the raspberry pi device can capture and track the network traffic flowing between its incoming and outgoing interfaces. this can be done in the following way. on starting, the raspberry pi device will load two scripts, the first of which is a shell script that will set up a software bridge connection between the incoming and outgoing interfaces. the bridge interface will have its own unique ip address assigned and will allow for network connectivity. the second python script will tcpdump the network packets (flowing between the input and output interfaces) on the raspberry pi 4.0 device so that they can be captured and assessed. 3.2. use of raspberry pi as an icds raspberry pi is a low-cost computer that is commonly finding its usage in iot and cyber-physical systems. currently, raspberry pi 4 is the latest version and it has built in ethernet interface and wifi module. owing to its tiny size, negligible power consumption and low cost, raspberry pi 4 can ideally be used as a commercial icds for filtering of malicious traffic entering the sme networks. however, traffic filtering using raspberry pi device will not be a straight forward process since raspberry pi can use only one network interface at any given time even if it may have multiple network interface connections (i.e., internet traffic only goes through the particular interface connection). for traffic filtering purpose an ids needs at least two network interfaces, one for incoming traffic and the other for outgoing traffic. when connected to an external network, incoming and outgoing internet traffic to and from the network only flows through the particular interface of the raspberry pi that is directly connected to the external network, be it the ethernet interface or the wifi interface. even if multiple usb adapters are connected to the different available ports in the raspberry pi device, internet traffic from the external network will only flow through one of these connections and that is an issue with the use of raspberry pi as an icds. using some channel bonding technology, however, it is possible to channelize the network traffic to flow through two separate network interface connections, one for incoming traffic entering the raspberry pi device from external network and the other for outgoing traffic from the raspberry pi device [42]. this will need two network interface connections (e.g., network adaptors or network interface cards) in the raspberry pi 4.0 board and such connections can be in any form, like, the on-board ethernet interface, onboard wifi interface, usb ethernet, and usb wifi. for traffic filtering purpose, the raspberry pi device connected to a sme network, will require incoming 8 sreenivas sremath tirumala, narayan nepal and sayan kumar ray eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 and outgoing network traffic flowing through any of the two separate network interfaces. based on such flow of network traffic, the following combinations are possible: • option 1: network traffic entering the raspberry pi device through the on-board ethernet interface and flowing out through the on-board wifi interface • option 2: network traffic entering the raspberry pi device through the on-board ethernet interface and flowing out through usb ethernet interface • option 3: network traffic entering the raspberry pi device through the on-board wifi interface and flowing out through the usb wifi interface • option 4: network traffic entering the raspberry pi device through the on-board wifi interface and flowing out through the usb ethernet interface there are, however, few issues with the selection of the different interfaces on the raspberry pi 4.0 board for incoming and outgoing network traffic unless proper channel bonding is used. one such issue, for example, when choosing option 1 (on-board ethernet interface for incoming traffic and wifi interface for outgoing traffic), the configuration will face an issue with the assigned ip addresses for the two interfaces. generally, individual ip addresses will be assigned to the ethernet interface and wifi interface, respectively, for incoming packets entering the raspberry pi board to identify the particular entry interface’s ip address and filtered outgoing packets (i.e., network traffic packets leaving the raspberry pi board to enter the sme network gateway) to identify the exit interface’s ip address. since, network traffic flows through only one connection (at a time) on the raspberry pi board, in absence of channel bonding technique, all traffic will just identify the ethernet interface’s ip address and flow through that, whereas, the other wifi interface connection will remain unnoticed. this implies, that traffic will not enter the gateway of the sme network. also, in case of option 3, when choosing two wifi interfaces for incoming and outgoing traffic there can be an issue with the raspberry pi board not properly identifying the particular wifi interface after every reboot operation (i.e., which interface is for incoming and which one is for outgoing traffic). there is a possibility that raspberry pi may not identify the wifi interfaces correctly when rebooted and that may lead to incorrect communication of the network traffic. thus, from these discussions it can be concluded that it is feasible to use raspberry pi device to develop an icds but proper channel bonding needs to be used for tracking the network traffic entering and exiting the different interfaces on board. in the following sections we study the performance of different interfaces on the raspberry pi device in handling high volume of real traffic entering the device. 4. experiment results and discussion 4.1. performance of the raspberry pi interfaces this section discusses the preliminary experimental results of the proposed raspberry pi architecture (refer to figure 3). as explained in the previous section, in this first phase of the work, the aim is to study the performance of the different interfaces on the raspberry pi 4.0 device when handling high volume of real unfiltered network traffic entering the device (i.e., incoming traffic). identifying malicious traffic entering the raspberry pi 4.0 device and filtering them before entering the sme network is not done in this work. the different interfaces on the raspberry pi 4.0 device are the ethernet interface, wifi interface and external usb interface and in the experiment conducted, these three interfaces are exposed to real unfiltered network traffic entering the pi board separately through each of these interfaces and are measured over a time interval. for example, traffic entering the pi device through the ethernet interface is measured from time t till t+1. similarly, traffic entering through the wifi interface and the usb interface are separately measured from t to t+1 time interval. based on the incoming traffic, performance of each interface on the raspberry pi device is measured in terms of latency, and download and upload throughput. all the graphs in the next subsection depict results based on the average of multiple measurements. 4.2. measurement of latency latency is a significant aspect in determining the efficiency of any network interface. in the experiments conducted, latency of each interface on the pi board (i.e., ethernet, wifi, and usb interfaces) is measured individually based on the incoming unfiltered real network traffic entering each interface separately over a time interval of t to t+1. figure 3 depicts the latency comparison of the three interfaces on the raspberry pi 4.0 device based on separate measurements of the incoming network traffic. as can be seen in figure 4, the latency of the built-in wifi interface on the raspberry pi device is considerably high in comparison to the latency values of the built-in ethernet and usb adapter interfaces. apart from the fact that ethernet (wired) connections usually offers better network speed and significantly lower latency compared to wifi (wireless) connections, the other reason can be that the built-in wifi on the pi device has a single antenna and not a mimo, so lower speed and more latency anyway. on the other hand, the 9 raspberry pi-based intelligent cyber defense systems for smes and smart-homes: an exploratory study eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 ethernet interface also offers lower latency than the usb adapter interface. 4.3. measurement of download traffic throughput similar to latency, download and upload throughput of network traffic are other important aspects of determining the efficiency of a communication interface. the download traffic for each interface on the raspberry pi 4.0 device is measured separately over the t to t+1 time interval and the comparison results for the three interfaces are shown in figure 5. from the presented figures, it is evident that the throughput of the built-in ethernet interface on the pi device is significantly higher than the throughput of the wifi and usb adapter interfaces. again, this can be related to the fact that ethernet connections generally offer better network speed and thus better (download) throughout in comparison to wifi and the usb connections. performance of the in-built wifi and usb interfaces look somewhat similar. 4.4. measurement of upload traffic throughput figure 6 compares the throughput of the upload traffic for the three network interfaces on the raspberry pi 4.0 device. the upload throughout performance of the built-in ethernet interface has somewhat outperformed the other two interfaces. the usb adapter on the pi 4.0 device, unlike the ethernet, shares a common bus and hence its bandwidth is also distributed among other ports, which is why it experiences some internal delays and has a low throughput. 4.5. dna based malware detection approach using deep auto encoders the experiment design consists of a classifier that is used to match the pattern of signatures from the repositories, i.e., hashsigns and dnasigns. initially, 60,000 files are created with random hexadecimal values followed by creating two sets of input data through injecting 13500 synthetic signatures into those files. the first set input1 is created by injecting malware signatures into 36,000 files to obtain a ratio of 60:40 between malicious and non-malicious contents, the second input2 is created by interchanging the ratio between malicious and non-malicious contents, i.e., 40:60 between malicious and non-malicious contents. two sets of experiments are performed using input1 and input2. the design of the experiments is presented in fig. 7. two deep autoencoder (daes) with 3 layers are used for the experiments namely daedna and daehash based on the training data set. daedna is trained using the repository of signatures, dnasigns, created using proposed dna-based approach, whereas, the second autoencoder daehash is trained using the repository, hashsigns, created with hexadecimal signatures. the total input files of 60,000 are sent to daedna and daehash, one at a time (same input) for performing classification in order to identify malicious and non-malicious content as shown in fig. 7. outputs obtained from the daes are tabulated and presented as experiment results. since there are two repositories input1 and input2, the experiments are performed in two independent cycles. the technical details of the experiment along with the results are discussed in the next section. the details of the input data set and signature repository along with the technicalities of dae are presented as follows. experiments are performed using the similar approach adopted for pattern recognition used in [43] for determining watermarks. 4.6. outcome of dae experiment the dae used for the experiment consists of three layers apart from the softmax layer used for training. since, the dae learns from the patterns in the input, the softmax layer is used for validation. the daes are trained using the signature repositories for 500 epochs for the first and last layers and 1000 epochs for the middle layer. the signatures are divided based on their lengths and dae nodes are adjusted to fit the size of the signatures. since the aim of the training was to make dae learn the patterns in the signatures, the changes in the input size is insignificant. the learning rate and momentum are varied from 0.4 to 0.6 and from 0.2 to 0.4 respectively with an interval of 0.1 for both the parameters. the individual average time for training and validation are recorded as 23.5 minutes and 19.2 minutes respectively. the testing times are averaged between 19 and 32 minutes for different runs. the differences are often due to hardware and software limitations and also based on the input (files) selected (in terms of length and number of epochs). since the emphasis of the current research is not optimising the dae, the variance in execution times can be ignored. the input size for validation and testing is determined by splitting the content of the file. in this research, the malware file consists of data and malware signature in the form of hexadecimal values. therefore, the file is treated as a continues hexadecimal values and it is split based on the size of the file. the dae cannot be used with varying number of input nodes, hence the file size is fixed at 250 lines with 80 characters per line. since the input is supplied as continues stream, the size of the lines and characters are insignificant and has no impact on the functionality of dae. all the experiments are performed on mac book pro m1 having 8gb ram, 256 ssd, and 8 core gpu. for generating the synthetic malware, python 3.6 is used with a default random 10 sreenivas sremath tirumala, narayan nepal and sayan kumar ray eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 figure 4. latency comparison of raspberry-pi interfaces when handling external traffic figure 5. traffic comparison for download throughput figure 6. traffic comparison for upload throughput number generator that is modified to use only prime numbers. for dae experiments, matlab 2020b (mac version) is used. each experiment is performed 50 times. the validation and testing data is divided in 2:1 ratio due to dae having no previous exposure to the files. a 3fold cross validation is also performed on selected input files for further affirmation of results. the experiment results for the different input data sets along with the two different repositories are presented below in table 1. the results presented in table 1 consists of training accuracies attained using dnasigns and hashsigns repositories. along with the training results, validation and testing accuracies are also presented. 11 raspberry pi-based intelligent cyber defense systems for smes and smart-homes: an exploratory study eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 figure 7. experiment designthe hexadecimal code of input (file) is sent as an input to two different deep autoencoder networks (daedna and daehash) trained using data from dnasigns and hashsigns repositories respectively. the dae will be looking for pattern that might resemble malware signatures at least partly to identify and classify files with the potentially malicious content table 1. experiment results: classification accuracies (training, testing and validation) with full set of dna and hexa signature repositories. type of malware training validation testing rms t-test repository ratio % % % error value 60:40 98.4 99 92.1 0.21 0.192 dnasigns 40:60 99.2 99 94.8 0.38 0.263 60:40 99.6 99.3 72.6 0.64 0.211 hashsigns 40:60 99.19 99.8 82.1 0.52 0.241 the first part of the results show that the proposed dna-based approach is able to attain a classification accuracy of 92.1% for malware repository with 60:40 ratio, which is an improvement of 19.5% in comparison to the signature-based approach. the proposed dnabased approach also performs better than the signaturebased approach for the second set of experiments with 40:60 ratio of malicious and non-malicious data set with 94.8% of accuracy, which is an improvement of 12.7% over signature based approach (82.1%). it is noteworthy to observe that despite of better training accuracy for signature-based approach (with a minute deference of 0.2% for 60:40 and -0.1 for 40:60, respectively, in favour of signature-based approach) the proposed dna-based approach attained better classification accuracy than signature-based approach. it is significant to observe that the difference of accuracies between the two experiments (i.e., with 60:40 and 40:60 ratios of malware and non-malware) the accuracy is reduced from 19.5% to 12.7%, a reduction of 6.8%. the reason for this reduction can possibly be attributed to the differences in the ratios between malicious and nonmalicious inputs. 5. known limitations and impact the implementation of icds have some know shortcomings related to software and hardware capability. the experimental evaluation clearly indicates the capability of using raspberry pi as ids. the assertion of the research on producing low cost icds is successful considering the hardware costs. raspberry pi or similar devices have issues with heat particularly when expected to run for long hours. any ids is expected to be online continuously which would incur a lot of heating for the devices. the research tried to look into this aspect and found that an external attachment is required to keep the heat levels low. however, due to time constraint, the research could not perform a continues test for weeks / days together. in case of accidental damage, majority of the parts can be replaced as the modules of raspberry pi are easily available. also, the crucial modules like wifi and networking modules can be replaced by external 12 sreenivas sremath tirumala, narayan nepal and sayan kumar ray eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 modules if required. moreover, a parallel backup device could be attached to the network as a recovery module for fail-over. in proposed approach, the dna based malware detection requires a cloud based environment for feature extraction and comparison. the experiments in this publications are conducted in an ideal environment without time limits on upload the traffic in realtime. though the upload and download throughput are tested for raspberry pi, the impact on upload for feature extraction may impact the performance. 5.1. impact of the research ongoing research on using low hardware and low cost ids devices has inspired to undertake this research. as mentioned previously, there was no formal research on using raspberry pi or similar type of devices for ids. this results of the research provides a potential encouragement for other researchers to perform similar type of research and provide a low cost solution for cyber security. the research, for the first time provides various parameters and modules that needs to be tested for intelligent ids which will inspire the research community to consider ml for low cost ids devices. on the other hand, there is a high chance of mimicking this experiments with some incompatible devices and produce an inefficient device. also, not every ml approach is efficient and the results can be reproduced. hence, the research might create potentially a negative impact on efficiency of the proposed research. since this research encourages low-cost and computation savvy devices, the research community working on ids might get influenced to look into such devices for critical systems like healthcare. using icds for critical systems cannot be evaluated at this stage due to limitations of this research. 6. conclusion and future work primarily, the work presented in this paper has a two-fold focus: (a) to explore the feasibility of using raspberry pi device to develop a low-cost intelligent cyber-defense system or icds for commercial sme networks, and (b) to study if the hardware components present in the latest raspberry pi devices are capable and compatible enough to support the use of raspberry pi-based icds for smes. based on the detailed discussions presented in the paper, it can be concluded that it is feasible to use raspberry pi device to develop a low-cost icds as an alternative to the traditional rule-based idss in use. moreover, from the experimental results as discussed in section iv, it is evident that the different interfaces on the raspberry pi 4.0 device, e.g., built-in ethernet (wired) connection, wifi and the external usb adapter, studied in this research are capable of handling high volumes of traffic entering the raspberry pi device from outside networks. the evaluations also showed that in terms of network performance comparison carried out based on parameters, like, latency, downward traffic throughout and upward traffic throughput, the built-in ethernet network interface has outperformed the other two interfaces and thus can be an ideal choice to use for handling external traffic. on the other hand, from the experiment results of dna based approach, it can be concluded that the dae trained with the proposed dna-based malware signatures was able to achieve better results compared to the dae trained with traditional signature based data set. for data set with the malicious and nonmalicious ratio of 60:40, the proposed dna-based approach provides a classification accuracy of 92.1%, which is 19.5% better than the traditional signaturebased approach in identifying malware variants despite of lower training accuracy. similarly, for the 40:60 ratio of malicious and non-malicious data set, the proposed approach performs 12.7% better than the traditional approach. also, dae trained with the data set generated using proposed dna-based approach was able to achieve better accuracy rates for partial signatures. acknowledgement this research was funded by manukau institute of technology references [1] belanger, f., hiller, j.s. and smith, w.j. 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(2019) static and dynamic malware analysis using machine learning. in 2019 16th international bhurban conference on applied sciences and technology (ibcast) (ieee): 687–691. 14 sreenivas sremath tirumala, narayan nepal and sayan kumar ray eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 https://doi.org/10.1109/comsnets48256.2020.9027373 https://doi.org/10.1109/comsnets48256.2020.9027373 [35] ding, j., chen, z., zhao, y., su, h., guo, y. and sun, e. (2017) mget: malware gene-based malware dynamic analyses. in proceedings of the 2017 international conference on cryptography, security and privacy: 96–101. [36] naidu, v.j. (2018) identifying polymorphic malware variants using biosequence analysis techniques. ph.d. thesis, auckland university of technology. [37] siddiqui, m., wang, m.c. and lee, j. (2008) a survey of data mining techniques for malware detection using file features. in proceedings of the 46th annual southeast regional conference on xx: 509–510. [38] jang, e.g., lee, s.j. and lee, j.i. (2014) a study on similarity comparison for file dna-based metamorphic malware detection. journal of the korea society of computer and information 19(1): 85–94. [39] chen, l., xia, c., lei, s. and wang, t. (2021) detection, traceability, and propagation of mobile malware threats. ieee access 9: 14576–14598. [40] karbab, e.b., debbabi, m. and mouheb, d. (2016) fingerprinting android packaging: generating dnas for malware detection. digital investigation 18: s33–s45. [41] han, b.j., choi, y.h. and bae, b.c. (2013) generating malware dna to classify the similar malwares. journal of the korea institute of information security & cryptology 23(4): 679–694. [42] tirumala, s.s., nepal, n. and ray, s.k. (2022) raspberry pi-based intelligent cyber defense systems for smes: an exploratory study. in international summit smart city 360° (springer): 3–14. [43] tirumala, s., jamil, n. and malik, m.a. (2018) a deep neural network approach for classification of watermarked and non-watermarked images. in international conference on intelligent technologies and applications (springer): 779–784. 15 raspberry pi-based intelligent cyber defense systems for smes and smart-homes: an exploratory study eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e4 1 introduction 1.1 malware detection 2 related work 2.1 iot based ids implementations filtering approaches key challenges to consider in raspberry pi-based ids 2.2 malware detection approaches dna based approaches for malware detection 3 proposed testbed for the experiments 3.1 raspberry pi as an icds: from perspective of hardware capability 3.2 use of raspberry pi as an icds 4 experiment results and discussion 4.1 performance of the raspberry pi interfaces 4.2 measurement of latency 4.3 measurement of download traffic throughput 4.4 measurement of upload traffic throughput 4.5 dna based malware detection approach using deep auto encoders 4.6 outcome of dae experiment 5 known limitations and impact 5.1 impact of the research 6 conclusion and future work papersmartroutecalculation-acm.dvi sophisticated route calculation approaches for microscopic traffic simulations karl hübner technische universität berlin daimler center for automotive information technology innovations ernst-reuter-platz 7, 10587 berlin, germany karl.huebner@tu-berlin.de björn schünemann technische universität berlin daimler center for automotive information technology innovations ernst-reuter-platz 7, 10587 berlin, germany bjoern.schuenemann@dcaiti.com ilja radusch fraunhofer fokus automotive services and communication technologies kaiserin-augusta-allee 31, 10589 berlin, germany ilja.radusch@fokus.fraunhofer.de abstract in order to implement meaningful microscopic traffic simulations, a sophisticated calculation of the vehicle routes is essential. in this paper, different route calculation approaches for microscopic traffic simulators are analysed and compared. various simulations are performed to detect traffic distribution and traffic flow resulting from the used route calculation approaches. to have simulations as realistic as possible, real od matrices of the city of fulda (germany) were used for the evaluation of the different approaches. the results show that simple route calculation algorithms are not appropriate for microscopic traffic simulations. however, approaches that are more sophisticated and that integrate additional heuristics produce good results regarding traffic distribution and traffic flow and can improve iterative techniques to find a user equilibrium. categories and subject descriptors i.6.7 [simulation and modeling]: simulation support systems general terms route calculation keywords route calculation approaches, microscopic traffic simulations, route assignment, trip generation, shortest-path search, choice routing, dynamic traffic assignment, user equilibrium 1. introduction the generation of realistic traffic is an essential requirement for the execution of meaningful traffic simulations. since the movements of all vehicles are simulated individually in microscopic traffic simulations, the place and the time of the departure, the destination, and the route through the traffic network have to be defined for each vehicle. the process of this data generation can be split into four steps, which are described by the traditional traffic prediction model: trip generation and trip distribution are responsible for determining origin and destination points and the number of trips between them, mode choice detects which transportation mode is used for each trip, and route assignment computes a route for each trip and defines the point in time when a trip is started [9, 12]. if realistic background traffic for a whole city or a certain area is needed, data based on real measurements or empirical studies are helpful, such as predefined origin-destination (od) matrices which can be obtained from local traffic authorities (e.g. [14]). if such matrices are available, onlymode choice and route assignment have to be carried out for traffic generation. while mode choice is a rather simple task (using statistics about modal splits for example) [12], route assignment is more difficult to perform since the aim is to find routes which result in balanced traffic which is close to reality. a trivial approach of route assignment would be to assign the shortest route for each trip (all-or-nothing). however, this approach would often result in traffic bottlenecks and heavy congestion. in order to prevent this, the routes simutools 2015, august 24-26, athens, greece copyright © 2015 icst doi 10.4108/eai.24-8-2015.2261359 might be distributed among the road network, which can be achieved by applying wardrop’s principle of user equilibrium (ue) where each driver chooses a route in a way that he/she cannot reduce his/her own travel time by changing to another route [16, 5]. in order to calculate the user equilibrium in a time-dependent environment, dynamic traffic assignment methods are used. such methods solve the ue problem either mathematically, or for microscopic simulations more suitable by iterative simulations until the equilibrium is reached [4]. an iterative approach, however, requires much computing time due to the excessive amount of simulation runs needed. therefore, it might be helpful to reduce the number of iterations by putting more effort into route calculation, which is presented in the following. 1.1 paper structure this paper is structured as follows: in section 2, different approaches for the route calculation will be presented. an introduction of methods used to create vehicular traffic from existing od matrices will follow in section 3. moreover, our simulation setup and the used evaluation methods and measures will be introduced in section 4. finally, the achieved results will be analysed in section 5, and a conclusion will be given in section 6. 2. improvements in route assignment in order to prevent traffic bottlenecks and heavy congestion caused by the generated vehicle routes, sophisticated methods for the route calculation have to be identified. in the following section, several approaches are discussed for improving the single route search and for calculating alternative routes and distributing the traffic among these routes. 2.1 improving shortest-path search two mechanisms seem to be promising to improve the shortest-path search: avoid the use of roads with low capacity and avoid time-consuming turns. the use of roads with low capacity can be avoided by increasing the costs of the relevant roads for the path search, for example by adapting the costs of each road segment according to its defined road type or capacity. considering turn costs is a more challenging task. turn costs can lead to p-turns, e.g. a detour around a city block containing three right turns instead of one left turn in order to avoid a turn restriction [17]. p-turns, however, would violate bellman’s optimality condition. this condition indicates that if the shortest path between origin and destination passes through two arbitrary nodes a and b, also the chosen path between a and b must be the shortest possible path [11, 2]. this condition implies that a shortest path must not contain the same node twice [6]. since turn restrictions are a special case of turn costs, this problem needs to be addressed as well. in order to avoid the violation of the principle, there are two main methods: firstly, junctions within the graph can be modelled as subgraphs with additional edges representing all turning possibilities. with this approach, any existing shortest path algorithm can be applied without violating bellman’s principle [17] (see fig. 1). another method is using an edge-based path search algorithm. instead of storing weights for each visited node, weights for each visited edge are stored during traversal. this approach allows applying turn restrictions and turn costs since the previous edge is known and can be used to calculate turn costs (see fig. 2). thus, turn costs are considered and p-turns are possible without violating bellman’s principle [6]. figure 1: to avoid the violation of bellman’s principle, junctions within the graph are modelled as subgraphs with additional edges representing all turning possibilities. in this way, any node-based routing algorithm (e.g. dijkstra) finds allowed p-turns. figure 2: an edge-based routing algorithm and turn-cost tables are used to enable turn restrictions and turn costs without editing the underlying graph. 2.2 determining turn costs to calculate turn costs, geisberger et al. [7] propose to consider the deceleration, the acceleration and the maximum turning speed to achieve a realistic presentation of the time needed for a turn. considering the maximal tangential acceleration maxa, the speed limits v and v′, the edge lengths l and l′, and the angle α in between, the maximum turning speed between both edges can be calculated by equation 1 [7]. vturn := min(v, √ maxa · tan(α/2) ·min(l, l′)/2) (1) furthermore, considering aacc as the maximum acceleration and adec as the maximum deceleration of a vehicle, the approximated time a turn costs cturn can be calculated by equation 2 [7]. cturn := (v − vturn) 2 2 · adec · v + (v′ − vturn) 2 2 · aacc · v′ (2) in our experiments, we used these equations to determine the turn costs. we assume the accelerations aacc = 2,6m/sec2 and adec = 4,5m/sec2. these are the values the traffic simulator sumo applies for the default acceleration and the default deceleration.1 2.3 finding alternative paths in general, drivers have different preferences and experiences, and therefore choose different routes to reach the same destination. consequently, several approaches and algorithms exist to find paths with similar costs but different road sections. yen developed an algorithm to find the k-shortest, loopless paths in a network [18]. however, the k-shortest paths are not feasible in road traffic scenarios since they contain many similar and unrealistic paths that users in reality would not use [1]. one method to solve the problem of similarity is to remove similar and unrealistic paths out of the shortest-paths set, e.g. by applying the minimax method by kuby et al. [10]. those improvements, however, increase the calculation time of routes even more. a method to identify potential dissimilar paths is iterative penalty method (ipm) proposed by johnson [8]. as soon as the best path has been found by any arbitrary single path search algorithm, the weights of all edges on the resulting path are penalized. a second search is done to find a different route which costs are quite similar to the best one. this can be performed several times until the desired number of alternative paths is found. furthermore, bader et al. penalized not only the edges of a path but all edges which are leaving from nodes visited by the path. this tube avoids small detours of already found routes [1]. choice routing is a relatively new method [3] which operates in four steps. firstly, two shortest path algorithms are executed simultaneously, one from the source node towards the target and one from the target node towards the source; resulting in two shortest-path trees. in the third step, both shortest-path trees are intersected with each other, which results in a set of edges traversed by both path searches. the connected edges in this set are called plateaus. in the fourth step, plateaus are ranked by a quality criterion and paths are generated by following the weighted trees. figure 3 shows the different stages of choice routing in an example. bader et al. showed that this simple and fast method results in very good alternative routes. it was also shown that choice routing is able to match about 80% of the routes which drivers would choose in reality [1]. 1http://sumo.dlr.de/wiki/definition_of_vehicles, _vehicle_types,_and_routes 1) create shortest-path tree (a* ) from s to t 2) create shortest-path tree (a* ) from t to s 3) intersect trees and determine plateaus 4) build routes based on plateaus figure 3: finding alternative routes in four steps by applying the choice routing algorithm. 2.4 route selection to assign different routes with the same origin and destination to the trips resulting from the corresponding od matrix pair, decision models can be used. these decision models detect a probability for using a particular route. one example is the logit model [13]. here, for each route r, a utility function ur is used to calculate the probability p (r) to choose this particular route. considering a set of r different routes and a scaling parameter β, the logit decision model is described by equation 3 [13]. p (r) = exp(β · ur) ∑ r s=1 exp(β · us) , r = (1, . . . , r) (3) 3. generating initial traffic in order to generate the initial routes for a simulation, different methods can be applied. in this chapter, we give a brief overview about approaches and methods used by us to create traffic from existing od matrices. 3.1 preparation of the od matrix in many cases, the origin and destination points given in od matrices are based on traffic analysis zones (taz). those analysis zones need to be transferred into a simulation scenario. in order to distribute departures and arrivals within a zone, we generate several origin and destination points at junctions within each taz randomly. furthermore, od matrices do not provide the number of trips per hour, but for one whole day. since departure times for each trip are required, the trips have to be distributed over time. for this task, we use one-day-variation curves which describe the amount of traffic over a normal working day per hour. for each trip, the time of departure is determined by distributing all trips over time according to such curves. within each hour, departure times are distributed equally. 3.2 calculation of the initial routes in the following sections, several methods for calculating initial routes are described. we used these routes to generate the traffic for our evaluations. f for each od pair, the fastest route is calculated. no additional routes are provided or calibration techniques are applied. f* for each od pair, the fastest route is calculated by considering turn costs and avoiding streets in residential areas. no additional routes are provided or calibration techniques are applied. cr4* for each od pair, four alternative routes are calculated by choice routing. the route calculation considers turn costs and avoids streets in residential areas. no calibration techniques are applied. 3.3 calibrating traffic in addition to the previous methods, the following approaches use an iterative dynamic traffic assignment approach (dta) in order to calculate an initial route for each trip. while the first iteration step is an all-or-nothing assignment, each following iteration uses the traffic flow of the previous simulation in order to assign routes for the vehicles. dta the following steps are executed alternately for a specific number of iterations: 1) route calculation, 2) route selection, 3) traffic simulation. in each iteration, the route calculation calculates fastest routes based on the traffic flow of the previous iteration without considering turn costs (figure 4). cr4*+dta an improved version of the previous approach, where a more sophisticated route calculation approach is used in order to pre-calculate a set of routes. at first, four alternative routes are calculated for each od pair by applying choice routing (including turn costs and the avoidance of residential areas). afterwards, the traffic is calibrated by executing the following steps alternately: 1) route selection, 2) traffic simulation. here, the route selection only chooses between existing routes which were calculated once at the beginning (figure 5). figure 4: iterative dynamic traffic assignment: reaching the user equilibrium in three alternating steps. figure 5: iterative dynamic traffic assignment: instead of recalculating routes every time, a set of sophisticated routes is calculated once at the beginning. 4. preparation of the simulation scenario in this section, we introduce our simulation setup. we use the previously presented methods to generate vehicle routes and to simulate the resulting traffic by the sumo simulator. moreover, we define evaluation methods and measures to allow a comparison of the different route calculation approaches. 4.1 simulation setup in 2008, the results of the future planning of the public transportation services of the city of fulda (germany) were published online [14]. these results include od matrices and a detailed map of all traffic analysis zones. to model traffic demand close to reality, we used the published od matrices to calculate the vehicle routes for our simulations. figure 6: this map of the city of fulda shows the network we used for the evaluation. at important road segments, e.g. at the depicted sample location, we set up induction loops for counting traffic. the road network we used for our simulations is based on openstreetmap data of the region hesse, germany2. we removed unnecessary objects from the osm data and fixed some errors caused by the converting process of the sumo tool netconvert. for example, we fixed illegal turns and faulty traffic light programs. for a later analysis, we added detectors at important road segments within our simulation to analyse and identify congested roads. 4.2 preparation of traffic demand after the simulation scenario preparation, we set up the traffic demand. for this purpose, the following files were chosen from [14]: the od matrix of the public transportation demand as expected in 2015 and the od matrix of the general traffic demand as expected in 2015 (general traffic = public transportation + motorized traffic [14]). the od matrices had to be converted into a suitable format since they were published as pdf files. in order to retrieve an od matrix with traffic demand of motorized vehicles only, the od matrix for public transportation was subtracted from the one for general traffic. the provided data consists of 67 traffic analysis zones (taz), however, half of the traffic concentrates within the first 17 zones. therefore, we simulated traffic within these zones only. the lost traffic was compensated by raising the number of trips accordingly. for each taz, origin and destination points were created (according to section 3.1). as a result, 5 760 od pairs and 160 000 trips were created and used for the route calculation approaches described in sections 3.2 and 3.3. 2http://download.geofabrik.de/europe/germany/ hessen.html 4.3 measures after the vehicle routes were generated, numerous simulations were run in sumo. at the end of each simulation, the generated trip information were used to compare the different simulation runs. for the comparison of the different route calculation approaches, we used following measures: number of vehicles which reached their target. in the case that several vehicles did not reach their target until the end of the day, probably a huge traffic congestion occurred in the network which prevented vehicles from reaching their target on time. average length of trips helps to detect which amount of detours was made by the vehicles compared to the shortest possible routes. average duration of trips shows how long vehicles drove from the origin to the destination. we assume, that a better distribution of traffic results in less congestion and therefore in lower trip durations. therefore, the average travel time is used as one of the main characteristic for the analysis of the traffic distribution. average standard deviation of duration of trips shows how much trip duration varies in relation to the average duration. for this measure, we calculate the standard deviation of all trips which have the same source and destination. the average of these standard deviation values is used to analyze the traffic distribution in terms of fulfilling the user equilibrium. the lower the deviation for a set of trips with the same source and destination, the lower the benefit a driver would experience when changing to another route. additionally, high values in standard deviation indicate a congested network, since drivers suddenly need more time to reach their destination. average speed of vehicles describes the average velocity of vehicles. comparing different simulation runs, this measure offers a good indicator of free or congested traffic. average waiting time of vehicles shows how many seconds on average vehicles spent waiting during their trip, for example at traffic lights or due to traffic congestion. in addition to these metrics, several induction loops on important roads were set up. these detectors measured the number of vehicles, the average speed and the vehicle flow over a period of 300 seconds. by these measures, timedepending events could be detected. 5. results table 1 shows the essential results of our simulations. each one simulated a whole day. the simulated traffic is based on the od matrix of fulda, containing real traffic demand data. for the route generation, one of the discussed approaches was used. the measured results give a first insight into the differences of the approaches regarding the calculated routes and the resulting traffic flow. we assume that the traffic flow over a full day is balanced reasonably if average travel time and speed are appreciable and traffic congestion only occur locally. in order to keep track of special events which are supposed to occur in real traffic flow (e.g. peaks in morning / evening hours and local traffic congestion) and events which usually do not occur in real traffic flow (a highly congested network, frequent deadlocks on junctions), we measured, additionally, the traffic volume and speed over the time on one sample location within the network (figure 7). f (fastest routes) f* (fastest with heuristics) dta 10 (10 iterations of dta) dta 50 (50 iterations of dta) cr4* (choice routing 4 routes) cr4* + dta10 (choice routing and 10 dta iterations) figure 7: traffic flow at the defined sample location for the different route calculation approaches. approach vehicles arrived avg. distance avg. speed avg. travel time avg. std. deviation of travel time avg. waiting time f 73,7% 1,58 km 17 km/h 2 070 sec 1 348 sec 1 751 sec f* 98,5% 1,62 km 28 km/h 246 sec 52 sec 73 sec ca4* 99,9% 2,03 km 30 km/h 249 sec 60 sec 61 sec dta (10 iterations) 91,2 % 2,46 km 27 km/h 1 070 sec 870 sec 730 sec dta (50 iterations) 99,9 % 2,01 km 31,3 km/h 245 sec 56 sec 42 sec cr4*+ dta (10 iterations) 99,9 % 1,76 km 30,5 km/h 215 sec 34 sec 51 sec cr4*+ dta (50 iterations) 99,9 % 1,69 km 30,9 km/h 203 sec 31 sec 45 sec table 1: simulation results for the different route calculation approaches 5.1 fastest routes (f) our evaluations show that using the simple fastest routes approach results in unbalanced traffic in our simulation scenario. many vehicles share parts of the selected routes which quickly results in bottlenecks. moreover, if no additional heuristics are used, vehicles are often navigated through residential areas which is rather unrealistic and causes heavy traffic congestion. in the worst case, this congestion spreads throughout the overall network which leads to long waiting times and a low average vehicle speed. as shown in table 1, each vehicle waits half an hour in average during its journey. moreover, the average speed is very low and only 74% of all departed vehicles reach their destination within the simulation time. the overall network is congested in both morning and evening hours. furthermore, vehicle flow and speed decrease at the sample location (figure 6 and 7) during the peak in the morning hours and do not recover due to the massive congestion in the network. 5.2 fastest routes with heuristics (f*) in our scenario, this method eliminates the problem of bottlenecks since the initial routes consider turn costs and avoid residential areas. in general, vehicles follow the main roads instead of taking the shortest way through residential areas, which prevents several bottlenecks. on the other hand, many vehicles still share several parts of their routes which is rather unrealistic and causes congestion on the used roads. in the analysed scenario, no persistent congestion is caused. during peak times, however, many roads still get congested due to missing alternative routes. in comparison to f, the average waiting time decreases to 73 seconds while the average speed for each vehicle increases to 28 km/h. vehicle flow and speed at the sample location (figure 7) does not show congestion but only peaks in the morning and evening hours. 5.3 choice routing with heuristics (cr4*) calculating several alternative routes reduces the problem that too many vehicles share the same road segments. consequently, less bottlenecks occur. in the simulated scenario, the average waiting time for each vehicle decreases to 60 seconds and the average speed increases to 30 km/h. these results show that this approach improves the initial route generation even more. in this simulation scenario, only temporary local traffic congestion occur on traffic lights and the overall traffic flow is never blocked due to bottlenecks. compared to f, vehicles have a lower average speed and no long-term congestion occurs at the sample location (figure 7). 5.4 iterative dynamic traffic assignment (dta10 / dta50) in this approach, the route choice and the resulting traffic simulation is repeated until the user equilibrium is approximated. consequently, the fastest route according to the traffic flow of the previous simulation is calculated for each vehicle. the higher the number of iterations of this process, the more vehicles adapt their routes to the traffic flow. therefore, this approach shows the best results for all measures after 50 iterations. average speed, duration and waiting time show better results than in cr4*. however, it can also be seen that the network still collapses within the tenth iteration, as seen in the deviation of travel times per trip. also, massive congestion occurs at the sample location (figure 7) in the evening hours. these results show that iterative dta without any optimization of initial routes requires a lot of iterations to obtain the (approximated) user equilibrium for our simulation scenario. thus, using this approach is a time-consuming process due to the multiple runs of simulations and routing calculations. 5.5 iterative dynamic traffic assignment with initial routes (cr4* + dta10 / cr4* + dta50) the main problem of the previous method is that initially, the simple fastest routes approach is used for the first route calculation which causes bottlenecks and a congested network (as seen in f). in order to obtain better results for the first iterations, this approach uses precomputed routes initially generated by choice routing with the same heuristics as in cr4*. our simulation results show that this approach is more suitable for reaching the user equilibrium with less iterations. the tenth iteration already results in a route distribution which produces balanced traffic, as seen in low travel times and a low standard deviation of those. also, there are neither huge traffic congestion nor other anomalies. applying more than ten iterations does not produce a further improvement. consequently, the (approximated) user equilibrium for our scenario setup seems to be reached in less iterations. 6. conclusion in this paper, different route calculation approaches for traffic simulators were compared regarding their generated traffic distribution and the resulting traffic flow. for our evaluations, we used an od matrix of the city of fulda (germany) based on real traffic demand, and used different route calculation approaches in order to generate initial traffic for comparable simulation scenarios. in this simulation study, the approach ’simple fastest routes without any heuristics’ caused unbalanced traffic and resulted in an overall congested road network. considering turn costs and distributing vehicles among alternative routes by using the ’choice routing’ algorithm resulted in more balanced traffic. by using this approach, bottlenecks were avoided and, thus, no congestion occurred in the simulated scenario. however, this approach was not able to achieve a user equilibrium which represents a traffic distribution close to reality. to approximate the user equilibrium, we applied several iterations of a simple dynamic traffic assignment method. first, the initial routes were calculated by the ’simple fastest routes’ approach. here, many iterations were required until a user equilibrium was reached. in a second experiment, we used initial routes pre-calculated by ’choice routing’ before an iterative traffic assignment approach was applied. now, we were able to approximate the user equilibrium with less iterations. since the results are promising, we plan to integrate the best route calculation approaches into the simulation architecture vsimrti [15]. consequently, these approaches can be used for the route calculation of all traffic simulators coupled to vsimrti. 7. references [1] r. bader, j. dees, r. geisberger, and p. sanders. alternative route graphs in road networks. in proceedings of the first international icst conference on theory and practice of algorithms in (computer) systems, tapas’11, pages 21–32, berlin, heidelberg, 2011. springer-verlag. [2] r. bellman and r. e. kalaba. dynamic programming and modern control theory. academic press new york, 1965. [3] camvit. choice routing, 2006. [4] m. friedrich, i. hofsaß, k. nokel, and p. vortisch. a dynamic traffic assignment method for planning and telematic applications. ptrc-publications-p, pages 29–40, 2000. [5] c. gawron. an iterative algorithm to determine the dynamic user equilibrium in a traffic simulation model, 1998. [6] r. geisberger and c. vetter. efficient routing in road networks with turn costs. in proceedings of the 10th international conference on experimental algorithms, sea’11, pages 100–111, berlin, heidelberg, 2011. springer-verlag. [7] r. geisberger and c. vetter. efficient routing in road networks with turn costs. in experimental algorithms, pages 100–111. springer, 2011. [8] p. johnson, d. joy, d. clarke, and j. jacobi. highway 3. 1: an enhanced highway routing model: program description, methodology, and revised user’s manual. technical report, oak ridge national lab., tn (united states), 1993. [9] l. kadiyali. traffic engineering and transport planning. khanna publishers, 1983. [10] m. kuby, x. zhongyi, and x. xiaodong. a minimax method for finding the k best şdifferentiatedť paths. geographical analysis, 29(4):298–313, 1997. [11] y. lim and h. kim. a shortest path algorithm for real road network based on path overlap. journal of the eastern asia society for transportation studies, 6:1426–1438, 2005. [12] d. lohse. berechnung von personenverkehrsströmen. wissenschaft und technik im strassenwesen, 1977. [13] d. lohse. ermittlung von verkehrsströmen mit n-linearen gleichungssystemen unter beachtung von nebenbedingungen einschliesslich parameterschätzung. technical report, technische universität dresden, 1997. [14] c. of fulda. öpnv-nahverkehrsplan 2. fortschreibung. http://www.fulda.de/bauen/verkehrsplanung/ oepnv-nahverkehrsplan.html, september 2013. [15] b. schünemann. v2x simulation runtime infrastructure vsimrti: an assessment tool to design smart traffic management systems. computer networks, 55:3189–3198, october 2011. [16] j. g. wardrop. correspondence. some theoretical aspects of road traffic research. ice proceedings: engineering divisions, 1:767–768(1), 1952. [17] s. winter. modeling costs of turns in route planning. geoinformatica, 6(4):345–361, 2002. [18] j. y. yen. finding the k shortest loopless paths in a network. management science, 17(11):712–716, 1971. this is a title eai endorsed transactions on smart cities research article 1 development of a smart waste management system with automatic bin lid control for smart city environment abbas abdullahi1,*, ameer mohammed2, mathias usman bonet1, abdussalam el-suleiman1, rabiu b. ahmad1, teng david chollom1 1department of aerospace engineering, air force institute of technology, kaduna, nigeria 2department of mechatronics engineering, air force institute of technology kaduna, nigeria abstract as cities worldwide transform into smart interconnected urban environments, the management of municipal waste emerges as a pressing challenge. this paper, offers a sophisticated solution that integrates seamlessly within the concept of smart cities. this system harnesses the power of the internet of things (iot) to optimize waste collection and enhance urban cleanliness. the primary aim of this research is to create a smart waste management system that extends beyond traditional waste bins. it introduces a network of intelligent waste containers equipped with automatic lid control mechanisms that operate based on real-time waste level data. when approaching these bins, the lid control mechanism automatically opens the bin only if the waste level is not full thereby, facilitating convenient waste disposal. in the context of smart cities, this innovative approach presents several advantages. it optimizes waste collection efficiency by prioritizing bins in need of immediate attention and ensures that waste containers are not prematurely emptied, reducing unnecessary waste disposal trips. moreover, the system enables city authorities to gain insights into waste level trends, fostering data-driven and proactive waste management strategies for a cleaner, more sustainable urban environment. keywords: smart city, smart bin, internet of things, waste management system, machine learning received on 13 october 2023, accepted on 11 april 2024, published on 18 april 2024 copyright © 2024 a. abdullahi et al., licensed to eai. this is an open access article distributed under the terms of the cc by-ncsa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.4385 1. introduction smart cities are at the forefront of urban development, harnessing technology to create efficient, sustainable, and connected urban environments [1][2]. one of the key challenges faced by smart cities is the effective management of municipal waste. [3] the conventional waste collection systems are often characterized by inefficiencies, resource wastage, and the lack of real-time data, hindering the transition to truly smart and ecofriendly urban areas. this research work responds to the challenge by offering a groundbreaking solution that aligns perfectly with the *corresponding author. email: netlikora@gmail.com smart city paradigm. it introduces an advanced waste management system that utilizes the power of the internet of things (iot) to optimize waste collection, promote cleanliness, and contribute to a sustainable urban future. [4] the core objective of this research is to develop a smart waste management system that extends beyond conventional waste bins. it envisions a network of intelligent waste containers equipped with automatic lid control mechanisms, designed to operate based on realtime waste level data. when individuals approach these bins for waste disposal, the system automatically opens the bin lid only if the waste level is not full, promoting efficient waste disposal practices. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:netlikora@gmail.com a. abdullahi et al. 2 within the broader context of smart cities, this innovative approach holds numerous advantages. it optimizes waste collection efficiency by prioritizing bins in need of immediate attention, thereby reducing the frequency of unnecessary waste disposal trips. this not only conserves resources but also mitigates the environmental impact of waste collection operations. moreover, the system empowers city authorities with invaluable insights into waste level trends, allowing for data-driven and proactive waste management strategies. figure 1 waste management infrastructure the significance of this research is rooted in its potential to revolutionize waste management within smart cities, contributing to a cleaner, more efficient, and environmentally responsible urban landscape [5] [6] [7]. 2. literature review the concept of smart cities has gained momentum in urban planning, aiming to create more efficient, sustainable, and interconnected urban environments. smart city initiatives leverage advanced technologies, such as the internet of things (iot), to improve various aspects of urban living, including waste management. the integration of iot technology plays a pivotal role in smart city projects. iot devices and sensors are used to collect and transmit data, allowing for real-time monitoring and control of various urban systems. these systems include waste management, traffic management, energy consumption, and more [8]. smart cities prioritize efficiency and sustainability in waste management. the objective is to optimize waste collection processes, reduce operational costs, and minimize the environmental impact of waste disposal. iot technology enables real-time data collection and analytics for more informed decision-making [9]. effective waste management in smart cities necessitates the ability to monitor and control waste levels in containers. several studies have explored the implementation of waste level control systems: iot-enabled waste bins: research has shown how iotenabled waste bins equipped with sensors can continuously monitor the waste level. when the bins approach full capacity, these systems can trigger alerts for waste collection, ensuring bins are serviced only when necessary [10]. driving to the destination of the bin cloud server smart city r eceived alert and the location of the bin se nd a le rt w he n th e bi n ap pr oa ch fu ll eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | development of a smart waste management system with automatic bin lid control for smart city environment 3 optimizing collection routes: waste level data collected through iot technology can be used to optimize waste collection routes. by prioritizing bins that are nearing capacity, collection vehicles can reduce unnecessary stops and fuel consumption, contributing to cost savings and reduced emissions [11]. incorporating automatic lid control when approaching waste bins represents a cutting-edge feature in waste management systems: user-friendly approach: automatic lid control simplifies waste disposal for users. when an individual approaches a bin, the lid automatically opens only if the waste level is not full, creating a user-friendly and hygienic experience [12]. efficiency and aesthetics: the automatic lid control mechanism reduces the risk of overfilled bins and litter, enhancing the aesthetics of the urban environment. this feature ensures that waste bins are used efficiently and cleanly [13]. the proposed research, integrates these concepts by combining waste level control, notification when the bins approach full capacity and automatic lid control when approaching the bin, aligning with the principles of smart city initiatives. the research aims to optimize waste collection processes, enhance user experience, and promote environmentally responsible waste management practices. 3. design and implementation the development of the smart waste management system with automatic bin lid control is a multi-faceted endeavour that necessitates a systematic and wellstructured design methodology. this section outlines the step-by-step approach to designing and implementing the prototype: 1. requirements gathering and analysis 2. system architecture design 3. sensor integration and lid control mechanism 4. data processing and analysis 5. user interface and mobile application 6. testing and validation i/o input output output savor motor level sensor proximity sensor led indicator arduino circuit board sim800l internet gateway cloud server db drivers mobile phone figure 2. block diagram of the proposed system power supply eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a. abdullahi et al. 4 3.1 algorithm developing an algorithm for a smart waste management system with automatic bin lid control is a complex task that involves multiple components, including smart city integration, waste level control, and lid control. table 1. presents a simplified main section of the algorithm. table 1. proposed algorithm proposed algorithm for smart waste management # initialize system parameters max_waste_level = 80 threshold_distance = 2 while true: waste_level = read_waste_level() user_proximity = read_user_proximity() if waste_level > max_waste_level: send_alert_to_smart_city() if waste_level <= max_waste_level: if user_proximity <= threshold_distance: open_lid() else: close_lid() if user_proximity <= threshold_distance: if waste_level < max_waste_level: open_lid() else: close_lid() # end of the main loop this algorithm outlines the key steps for managing waste bins in a smart city environment with automatic lid control: 1. initialization: set system parameters such as the maximum waste level that triggers bin collection and the proximity threshold for lid control. 2. main loop: continuously monitor waste levels and user proximity. 3. smart city integration: if the waste level exceeds the threshold, it sends an alert to the smart city waste collection team to initiate and schedule the collection process. 4. waste level control: if the waste level is below the maximum threshold, check user proximity. if a user is nearby, it automatically opens the bin's lid to allow waste disposal. 5. lid control when approaching bin: when a user approaches the bin, check the waste level. if the waste level is not full and the user is within the proximity threshold, open the bin's lid for convenient waste disposal. 3.2 design analysis implementing a smart waste management system with automatic bin lid control involves integrating key technologies to ensure efficient waste collection, lid control, and smart city interaction. table 2. lists the outline of the key technologies for the implementation, including smart city integration, waste level control, and lid control when approaching the bin if the level is not full: table 2. hardware components hardware components devices module on-board computer subsystem arduino nano bin lid control mechanithsms savor motor proximity and level detection ultrasonic sensor iot communication gateway sim800l module a. on-board computer subsystem this subsystem is based on the arduino single board on the atmega328p microcontroller as the core dedicated system in charge of processing the data obtained by the sensors to transmit the information the information using communication module. [14] figure 3 arduino uno b. proximity and level detection sensor the hc-sr04 ultrasonic sensor was used to measure the level of waste in the bin and to detect user when approaching the bin. hc-sr04 is a popular module for eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | development of a smart waste management system with automatic bin lid control for smart city environment 5 measuring non-contact distances ranging from 2cm to 400cm. it employs sonar (similar to bats and dolphins) to determine distance with excellent precision and consistency. it is made up of three parts: an ultrasonic transmitter, a receiver, and a control circuit. [15] figure 4 ultrasonic sensor the transmitter sends out short bursts of energy that are reflected by the target and picked up by the receiver. the time difference between ultrasonic signal transmission and reception is calculated. the distance between the source and target can be easily determined using the speed of sound and the equation. 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 = 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑆𝑆/𝑇𝑇𝐷𝐷𝑇𝑇𝑆𝑆 the microcontroller transmits an ultrasonic 10us pulse to trigger, followed by eight 40 khz pulses. the time it takes for an ultrasonic burst to leave and return to the transmitter microcontroller. figure 5 ultrasonic sensor detection state calculate distance the time required by pulse is actually for the to-and-from journey of ultrasonic waves, which we only require half of. as a result, time is divided by two. 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑆𝑆 = 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 ∗ 𝑇𝑇𝐷𝐷𝑇𝑇𝑆𝑆/2 speed of sound at sea level 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 = 343 𝑇𝑇/𝐷𝐷 or 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 = 34300 𝐷𝐷𝑇𝑇/𝐷𝐷 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑆𝑆 = 17150 ∗ 𝑇𝑇𝐷𝐷𝑇𝑇𝑆𝑆 (𝑢𝑢𝐷𝐷𝐷𝐷𝐷𝐷 𝐷𝐷𝑇𝑇) distance in cm, 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑆𝑆 = 𝑇𝑇𝐷𝐷𝑇𝑇𝑆𝑆/58 distance in inches, 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑆𝑆 = 𝑇𝑇𝐷𝐷𝑇𝑇𝑆𝑆/148 clearly there is an approximation going on here i.e., 148/58 = 2.5517cm/inch and we know that there are exactly 2.54cm to the inch. if the speed is 340 m/sec that's 34,000 cm per second or 0.034 cm per microsecond but, it's the return journey that is measured in microseconds so the result was divided by 2 and therefore 0.017cm is the distance that the object is away when the echo is received in 1 microsecond and the reciprocal of 0.017 is 58.823. (close to 58) 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑆𝑆 = 𝑇𝑇𝐷𝐷𝑇𝑇𝑆𝑆 ∗ 17000 therefore, this was half the speed of sound. for accurate distance reading, the output was calibrated using a ruler to monitor a particular range. c. bin lid control mechanism a servo motor was employed for the lid control mechanism that opens and closes the lid based on sensor inputs. it is an electromechanical device that is designed to provide precise control of angular or linear position, acceleration, and velocity in various applications. figure 6 servo motor servo motors are actuators that enable for accurate position (angle) control. the angle of the motor is typically between object distance transmitt receiver eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a. abdullahi et al. 6 0 and 180 degrees. in this research the servo was configure to operate between 0 and 90 degrees. figure 7 open lid angle servo motors are widely used in robotics, industrial automation, and other systems where accurate and controlled motion is required. d. iot communication gateway the bin’s communication to the server uses sim800l gsm/gprs module for communication gateway to offer a compact and versatile solution for alert notification. the module offers a wide range of functionalities including http protocol. it operates at a low voltage range of 3.4v to 4.4v, which makes it well-suited for lithium batterypowered applications. see figure 9. figure 8 sim800l module by simcom the sim800 module serves as the iot communication gateway, facilitating communication between the smart bin and the cloud server using the http protocol. this module plays a crucial role in establishing internet connectivity for the smart bin, enabling it to transmit the bin's state to the cloud server through http requests (using the get method). the server validates the data to ensure its integrity. this validation process was essential to maintain data accuracy and reliability. the cloud server stored the bin's data in a dedicated database for historical records, allowing for in-depth analysis of bin usage over time. it also plays a vital role in alert notifications, particularly when the bin's status indicated that it was full. these notifications were triggered based on the data stored in the database, ensuring timely and efficient waste management. figure 9 shows the schematic diagram of the hardware circuitry for the system, using the components listed in table 2 figure 9 schematic diagram with all the components bin lid open angle 90o bin lid control mechanism eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | development of a smart waste management system with automatic bin lid control for smart city environment 7 5. testing and result the waste level sensor was calibrated meticulously to precisely measure waste levels in the bin, and a 20cm threshold was established to indicate when a bin reached its full state. this calibration ensured accurate and reliable waste level measurements. additionally, the proximity sensor, designed to detect objects approaching the bin, was calibrated with a detection distance of 12cm. it was programmed to trigger the bin's lid to open when a user or object approached it. importantly, the system was designed with a condition to open the lid only if the bin was not full, ensuring efficient waste collection. the servo motor responsible for controlling the bin lid underwent comprehensive testing to validate its ability to effectively and consistently open and close the lid as required. to enhance the system's efficiency and conserve energy, power-saving mechanisms were thoughtfully implemented. these mechanisms were particularly crucial when the system operated in a batterypowered state, helping to extend battery life and reduce maintenance requirements. finally, real-world testing was conducted using actual waste materials to thoroughly validate the accuracy and efficiency of the lid control system. this testing phase simulated practical waste disposal scenarios, confirming that the system's responses met the operational requirements effectively and reliably. figure 10 a prototype of the system benefits of this system: • reduced operational costs through optimized waste collection. • improved waste management efficiency by reducing unnecessary bin emptying. • minimized overflow and littering around bins. • remote monitoring and control for real-time decisionmaking. • enhanced environmental sustainability by reducing unnecessary waste collection trips. • overall reduction in environmental pollution and enhanced city cleanliness and population health status. this experiment provides a foundation for the development of a smart waste management system with automatic bin lid control, offering a more efficient and sustainable approach to waste collection and management. conclusion in developing and evaluating the prototype for a smart waste management system with automatic bin lid control, several key findings and insights have emerged. the following conclusions highlight the system's performance, efficiency, and the benefits it offers for optimized waste management in urban centers. the prototype demonstrates the ability to control bin lids effectively based on waste levels. lid opening and closing events are closely aligned with the actual filling of bins, reducing the need for manual inspections. the system's data-driven approach optimizes the waste collection schedules, significantly reducing the frequency of collection trips. this not only saves operational costs but also contributes to environmental sustainability by minimizing vehicle pollutant emissions. the prototype proved successful in reducing waste overflow and littering around bins in their designated locations. instances of waste overflow were observed to have decreased, leading to cleaner and more aesthetically pleasing surroundings. remote monitoring and real-time decision-making capabilities enabled quick issue identification and resolution. this feature enhances the overall efficiency and responsiveness of waste management operations. in conclusion, the prototype for a smart waste management system with automatic bin lid control has demonstrated its potential as an efficient and sustainable solution for waste management. it offers cost savings, environmental benefits, and user satisfaction, making it a valuable asset in optimizing waste collection operations. further development and scalability will continue to enhance its impact on waste management and environmental sustainability. looking towards the future, further development of the smart waste management system with automatic bin lid control holds promising avenues for advancement. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a. abdullahi et al. 8 integration with advanced sensor technologies, such as iot devices and ai-powered analytics, can enhance the system's capabilities for more precise waste monitoring and predictive maintenance. additionally, incorporating unsupervised machine learning algorithms can enable the system to adapt and optimize its operations dynamically based on evolving waste patterns and environmental factors. scalability efforts can focus on expanding the system's deployment to broader urban areas, fostering collaboration with municipal authorities and waste management agencies. continued research and innovation will drive the evolution of this technology, ensuring its continued relevance and effectiveness in addressing the challenges of modern waste management and sustainability. references [1] jaemin lee. (2021). smart city in urban design. international journal of sustainable building technology and urban development, 12(4), 380-393. doi:10.22712/susb.20210031 [2] addas abdullah, "the concept of smart cities: a sustainability aspect for future urban development based on different cities". frontiers in environmental science. vol 11, year 2023. https://doi.org/10.3389/fenvs.2023.1241593 [3] szpilko, d.; de la torre gallegos, a.; jimenez naharro, f.; rzepka, a.; remiszewska, a. waste management in the smart city: current practices and future directions. resources 2023, 12, 115. https://doi.org/10.3390/resources12100115 [4] i. sosunova and j. porras, "iot-enabled smart waste management systems for smart cities: a systematic review," in ieee access, vol. 10, pp. 73326-73363, 2022, doi: 10.1109/access.2022.3188308. [5] g u fayomi, s e mini, c m chisom, o s i fayomi, n e udoye, o agboola and d oomole. smart waste management for smart city: impact on industrialization. 4th international conference on science and sustainable development (icssd 2020). doi:10.1088/17551315/655/1/012040 [6] szpilko, d.; de la torre gallegos, a.; jimenez naharro, f.; rzepka, a.; remiszewska, a. waste management in the smart city: current practices and future directions. resources 2023, 12, 115. https://doi.org/10.3390/resources12100115 [7] n. mittal, p. p. singh and p. sharma, "intelligent waste management for smart cities," 2021 international conference on industrial electronics research and applications (iciera), new delhi, india, 2021, pp. 1-7, doi: 10.1109/iciera53202.2021.9726729. [8] caragliu, a., del bo, c., & nijkamp, p. (2011). smart cities in europe. journal of urban technology, 18(2), 65-82. [9] gope, p., hwang, t., & kim, b. s. (2019). an efficient waste collection system in smart city using an iot-enabled predictive analytics approach. ieee access, 7, 1025610263. [10] khedekar, s., & kadam, l. (2017). iot-based smart garbage alert system. in 2017 international conference on i-smac (iot in social, mobile, analytics and cloud) (ismac) (pp. 207-212). ieee. [11] lu, j., & liu, l. (2012). optimizing the maintenance of a garbage collection fleet. transportation research part e: logistics and transportation review, 48(4), 754-769. [12] al-emran, a. s., abdullah, a., & kadir, e. (2019). iot based smart waste management system for smart city. in 2019 international conference on robotics, electrical and signal processing techniques (icrest) (pp. 403-407). ieee. [13] gu, y., xu, z., bie, y., & wang, p. (2020). design of an automatic trash bin lid control system based on the internet of things. journal of visual communication and image representation, 70, 102845. [14] y. a. badamasi, "the working principle of an arduino," 2014 11th international conference on electronics, computer and computation (icecco), abuja, nigeria, 2014, pp. 1-4, doi: 10.1109/icecco.2014.6997578. [15] a. dimitrov and d. minchev, "ultrasonic sensor explorer," 2016 19th international symposium on electrical apparatus and technologies (siela), bourgas, bulgaria, 2016, pp. 15, doi: 10.1109/siela.2016.7542987. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | this is a title eai endorsed transactions on smart cities research article 1 intelligent aircraft hangar fire detection and location system based on wireless sensor network in a smart city abbas abdullahi1,*, mathias usman bonet1, ubadike o. c.1, ameer muhammed2 and ubadike o. a.3 1department of aerospace engineering, air force institute of technology, kaduna, nigeria 2department of mechatronics engineering, air force institute of technology kaduna, nigeria 3department of computer science, air force institute of technology kaduna, nigeria abstract fire detection systems in aircraft hangars are vital for safeguarding both the facility's assets and the aircraft within. when it comes to anticipating potential fire incidents in the context of a smart city, intelligent aircraft hangar fire detection systems emerge as high-performance solutions. these systems are meticulously designed around the core concept of a wireless sensor network (wsn). they operate by deploying three sensor nodes strategically within the aircraft hangar, each tasked with measuring gas concentrations in the ambient air. these measurements are then relayed to a central base station (bs) and subsequently transmitted to a central server for real-time analysis and risk assessment. the server harnesses the power of machine learning (ml) techniques to scrutinize the incoming data, combining it with reference gas data. this amalgamation is processed and translated into a dynamic report, which is instantly displayed on a user-friendly graphic user interface (gui). in situations where smoke or gas concentrations reach critical levels, the server's predictive capabilities come into play. it proactively identifies high concentration zones on the gui, serving as an early warning system. simultaneously, it pinpoints the potential source and location of the fire outbreak, thus expediting emergency response procedures. in the broader context of a smart city, the integration of such intelligent aircraft hangar fire detection systems extends their utility beyond hangar-specific safety. data generated by these systems can be seamlessly integrated into the city's overarching safety infrastructure, facilitating swifter and more coordinated responses to fire emergencies across the urban landscape. by doing so, these systems contribute significantly to enhancing urban safety, protecting critical assets, and, most importantly, preserving human lives within the smart city framework. keywords: smart city, aircraft hangar, fire protection, safety, wsn, data visualization, machine learning, gui received on 17 august 2023, accepted on 04 october 2023, published on 05 october 2023 copyright © 2023 a. abdullahi et al., licensed to eai. this is an open access article distributed under the terms of the cc by-ncsa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.3742 1. introduction the research work is titled 'intelligent aircraft hangar fire detection and location system based on wireless sensor network (wsn) in a smart city.' as our cities evolve into smart, interconnected hubs of human civilization, the *corresponding author. email: netlikora@gmail.com importance of fire safety takes center stage. fires, with their lethal potential and destructive aftermath, pose threats not only to aircraft hangars but also to warehouses, businesses, residential areas, and, most importantly, the lives of city residents. in the context of a smart city, where technology and data-driven solutions are pivotal, addressing fire safety becomes an integral part of urban planning. the interconnectedness of smart city infrastructure allows us to rethink and enhance traditional eai endorsed transactions on smart cities | volume 7 | issue 2 | https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:netlikora@gmail.com a. abdullahi et al. 2 fire safety measures. smart cities leverage digital and communication technology, as well as data analytics, to create an efficient and effective service environment that improves urban quality of life and supports sustainability. [1] the development of smart applications (see figure 1) in recent years has altered the way we live and work. [2] emerging technologies such as the wireless sensor network (wsn), the internet of things (iot), artificial intelligence (ai), and big data power these applications. they have been used to address complex challenges and improve the quality of life for individuals and communities in a variety of fields, including safety and security, healthcare, governance, the environment, transportation, energy, infrastructure, and education. figure 1 applications of smart city our study goal is to develop fire safety protection-type smart city application in aircraft hangars and their societal impact. this study has the potential to have a substantial impact on the development of smart city initiatives related to safety in our society. this research delves into the development of an intelligent aircraft hangar fire detection and location system using wireless sensor networks (wsn) that harnesses the power of smart city to protect critical assets within environment. as the smart city concept continues to evolve, the preservation of life and property through advanced fire detection and location systems becomes an imperative. [3] this research seeks to contribute to the safety and resilience of smart cities by exploring innovative solutions [4] that not only protect aircraft hangars but also extend their reach to safeguard various urban structures and, most importantly, the well-being of urban inhabitants. the use of an intelligent system for monitoring the level of gas concentrations in the air and an alert system is the greatest strategy to reduce the risk of a fire. [5] the system is equipped with a gas sensor, embedded computer and transceiver to measure gas concentration in the air. this can help in detecting unfavourable accidental circumstances like smoke, when the concentrations measured and identified in the sample gas data illustrated in figure 3. with the aid of a transceiver unit, the signal can then be transmitted wirelessly via radio frequency to the based station (bs) which identifies each node by a unique address assigned to it. it processes the collected information and send it to the server for visualization and notification. in any fatal situation, a quick detection and alert will minimize loss of life and property. by using the concept of wsn, star network topology illustrated in figure 2, the system can monitor and analyse the information from the various sensor nodes. wireless sensor networks are a collection of sensor nodes that run on batteries and have little radio, computation, and storage capabilities [6]. figure 2 star network topology based on wsn nodes operate by sensing and relaying their findings to a processing facility called a "sink." and since the replacement of the embedded batteries is a highly challenging task, once these nodes have been deployed, the design of protocols and applications for such networks must be energy-aware in order to increase the lifetime of the network. traditional methods, such as direct transmission and minimal transmission energy [7], do not provide an even distribution of the energy load across the sensor network nodes. sensor nodes that use direct transmission send data directly to the sink, which causes nodes that are farthest from the sink to go offline first. the intelligent system is designed to predict a fire outbreak at its early stage by visualizing every level of the concentration of gases in the air and trigger an alarm when it reaches a predetermined threshold [8]. the system stores the node's information as well as the time in the database continuously in real-time and it is a technique intended to prevent fire disaster. it typically displays a warning to the control station and to show the degree of forecast on a computer graphic user interface (gui), along with the precise location of such an incident anywhere the aircraft hangar. (see figure 3) smart city safety & security environment infrastructure energy healthcare government education transportation eai endorsed transactions on smart cities | volume 7 | issue 2 | intelligent aircraft hangar fire detection and location system based on wireless sensor network in a smart city 3 figure 3 star network topology based on wsn 2. literature review several monitoring systems have been proposed as a result of the growing need of having an accurate fire detection system. 2.1 fire detection method in smart city environments using a deep-learningbased approach [9] in the construction of new smart cities, traditional firedetection systems can be replaced with vision-based systems to establish fire safety in society using emerging technologies, such as digital cameras, computer vision, artificial intelligence, and deep learning. in this study, we developed a fire detector that accurately detects even small sparks and sounds an alarm within 8 s of a fire outbreak. a novel convolutional neural network was developed to detect fire regions using an enhanced you only look once (yolo) v4network. based on the improved yolov4 algorithm, we adapted the network to operate on the banana pi m3 board using only three layers. initially, we examined the originalyolov4 approach to determine the accuracy of predictions of candidate fire regions. however, the anticipated results were not observed after several experiments involving this approach to detect fire accidents. we improved the traditional yolov4 network by increasing the size of the training dataset based on data augmentation techniques for the real-time monitoring of fire disasters. by modifying the network structure through automatic color augmentation, reducing parameters, etc., the proposed method successfully detected and notified the incidence of disastrous fires with a high speed and accuracy in different weather environments—sunny or cloudy, day or night. experimental results revealed that the proposed method can be used successfully for the protection of smart cities and in monitoring fires in urban areas. finally, we compared the performance of our method with that of recently reported fire-detection approaches employing widely used performance matrices to test the fire classification results achieved. aircraft hangar eai endorsed transactions on smart cities | volume 7 | issue 2 | a. abdullahi et al. 4 the authors developed vision-based systems using camera for the fire safety. however, the use of a vision-based using camera for fire protection type does not predict the early stage of fire by detecting the concentrations in air, therefore, cannot guarantee fire protection. 2.2 hangar fire detection alarm with algorithm for extinguisher [10] a fire alarm system with a high-performance that detects smoke, heat or flames, for the protection of lives and property. it is employed in aircraft hangars for the protection of aircraft, personnel as well as the hangar structure. the need for a fire alarm in a hangar with algorithm for extinguishers cannot be overemphasized. the structure of the hangar building, type of aircraft housed in the hangar and activities carried out at the hangar such as inspections, overhauls and modifications of aircraft, determine the type of fire alarm to be used, whether it should be automatic or manual. the detection employed, be it smoke detection, heat sensing or both and the process of extinguishing in the face of a fire threat or hazard is equally important. the effectiveness of the alarm is dependent on genuine alerts and not false alarm triggers, hence in this research paper, the employment of intelligent detection using comparators in programmed ic, the microcontroller, was interfaced with a 555 timer, a multivibrator for generating aural sound for alarm, lcd display for indicated readings as well as algorithm for extinguishing using water or foam via sprinklers. the basic work started with a block diagram representation, thereafter, individual subsystems, which form the building blocks were analyzed and the components parts identified. the author employed the use of a single sensor-type device rather than a network of multiple connected sensors for wider coverage in the aircraft hangar, fire location-based indication, and the use of modern technology to make the system more intelligent and accurate in fire protection. such a system does not guarantee accurate fire protection in a smart environment. the proposed method employed an interconnected system using wsn, machine learning, and data analytics and visualization which can be deploy in a smart city environment to monitor fire scenarios and fire prediction in real-time. 3. design and implementation of the system the system is designed on the wsn basis with three networked sensor nodes for the detection which are deployed in three locations with each having an identification (id) for sharing the sensor data with the bs and the server. the server is designed to visualize the data and notify the hangar. 3.1 methodology sensor nodes module: design sensor node modules that incorporate gas sensors to measure changes in gas concentrations in the air. this will use specialized gas sensor technology sensitive to relevant gases and wireless communication protocols for data transmission to enable data exchange between sensor nodes and base stations using industry-standard wireless protocols for reliable and secure communication. the sensor node will have an on-board computing subsystem. base station modules: design of base station modules to receive data from sensor nodes. aggregate and preprocess data locally using onboard computer subsystem for data processing and wireless communication. the base station enables data transmission to the central server for data analytics and visualization. machine learning (ml) algorithms: develop and deploy ml algorithms to train predictive models on the central server, to analyze gas concentration data for fire prediction. graphic user interface (gui): develop a user-friendly gui on the central server to display real-time data, fire predictions, and alerts by utilizing software development tools. database: design a database to store and manage data to store historical data, dataset, system logs, and fire incident records using relational databases for data storage and retrieval. data analytics and visualization: integrate an algorithm for data analytics and visualization into the central server to process data, generate reports, and visualize risk levels. real-time alerting: implement real-time alerting mechanisms within the gui and server, to notify relevant personnel and authorities in case of a fire scenario. employ sound alarm notification and sms. wireless sensor network (wsn): deploy sensor nodes strategically within the aircraft hangar to collect real-time data on gas concentrations, utilize wireless communication protocols to transmit data to base stations. eai endorsed transactions on smart cities | volume 7 | issue 2 | intelligent aircraft hangar fire detection and location system based on wireless sensor network in a smart city 5 successful implementation of these key technologies ensures the intelligent aircraft hangar fire detection and location system's effectiveness in early fire detection and protection of assets, hangar facilities, and human lives within a smart city context. the system leverages advanced sensor technology, data analysis, and real-time communication to enhance safety and mitigate fire risks. 3.2 system design a. system architecture to solve the shortcomings of other methods, machine learning (ml) and wireless sensor network (wsn) techniques were deployed to make the system more intelligent and ability to cover wide range of environment using a start topology for sensor data transmission from the sensor network to the base station as a sink and to the server (computer) as illustrated in figure 2 which consists of the sensor nodes, the bs and the sever for assessing and reporting the predicted fire scenario [11]. figure 2 shows the system architecture, which includes the sensor node modules, base station modules, and the computer system as the server which visualizes the situation and sends an alert in case of a fire scenario. 1. sensor node modules: sensor node modules are the frontline components of the system placed at different strategic locations within the aircraft hangar. they are responsible for continuously monitoring gas concentrations in the hangar's air, specifically targeting potential indicators of a fire outbreak. these nodes use specialized gas sensors to detect changes in gas levels. when significant changes are detected, they transmit this data wirelessly to the base station module for analysis. low power consumption, wireless communication capabilities, and gas sensing technology. 2. base station modules: base station modules act as the intermediary between the sensor nodes and the central server. they receive the gas concentration data from the sensor nodes and serve as a local processing hub. data received from sensor nodes is aggregated, and preliminary analysis may be performed at this level to assess the immediate situation. if necessary, data is forwarded to the central server for further analysis. data aggregation, local analysis, and wireless communication with the sensor nodes. 3. computer system as the server: the server is the core component responsible for data analysis, visualization, and decision-making. it processes db server circuit board tx/rx sink sensor node 2 circuit board tx/rx power sensor node 3 circuit board tx/rx power node 1 sensor circuit board tx/rx power figure 4 shows the system architecture eai endorsed transactions on smart cities | volume 7 | issue 2 | a. abdullahi et al. 6 incoming data from sensor nodes and base stations, applies machine learning (ml) techniques, and generates realtime reports. ml algorithms assess the gas concentration data in conjunction with reference data to identify potential fire scenarios. the server displays this information on a graphic user interface (gui) in real-time. high processing power, ml capabilities, gui for real-time visualization, and alert generation. 4. database: the database stores and manages critical data related to fire detection and historical records. it serves as a repository for gas concentration data, historical fire incidents, and system logs. the database stores incoming data for future reference, enabling long-term analysis, trend identification, and system maintenance. data storage, retrieval, and management capabilities. collectively, this system architecture enables the intelligent aircraft hangar fire detection and location system to continuously monitor the hangar environment for potential fire hazards. the sensor nodes detect changes in gas concentrations, while the base stations assist in local analysis and data relay. the central server processes data, predicts fire scenarios, and provides real-time alerts through the gui. the database ensures data preservation for historical analysis and system optimization. this architecture enhances fire safety and contributes to the protection of aircraft assets, hangar facilities, and human lives within a smart city context. b. implementation of key technologies the implementation of key technologies within the intelligent aircraft hangar fire detection and location system base on wsn in a smart city involves the integration of various components and software tools to create a cohesive and effective fire detection system (see table 1). table 1 hardware components devices module on-board computer 1 arduino nano on-board computer 2 arduino uno wireless communication module nrf240l gas concentration sensor module mq-2 gsm communication module sim800l 1. on-board computer subsystem this subsystem is based on the arduino single board on the atmega 328p microcontroller as the core dedicated system in charge of processing the data obtained by the sensors to transmit the information the information using communication module. (a) (b) figure 5 (a) arduino uno (b) arduino nano 2. communication protocol the system used the nrf240l transceiver module for wireless communication, which was interfaced with arduino in order to communicate effectively between the nodes and the sink (see figure 2). the nrf24l01 module is designed to operate in the 2.4ghz worldwide industrial, scientific, and medical (ism) frequency band and transmit data using gfsk modulation. [12] the data transfer rate can be configured to 250kbps, 1mbps, or 2mbps. the 2.4 ghz band is one of the ism frequencies reserved for unlicensed low power equipment around the world. [13] ism frequencies are used by devices such as cordless phones, bluetooth devices, near field communication (nfc) devices, and wireless computer networks (wifi). the working voltage of the module ranges from 1.9 to 3.9v. figure 6 nrf240l transceiver module eai endorsed transactions on smart cities | volume 7 | issue 2 | intelligent aircraft hangar fire detection and location system based on wireless sensor network in a smart city 7 the nrf24l01 communicates with a maximum data rate of 10mbps using a 4-pin spi (serial peripheral interface). the spi interface allows you to adjust all characteristics such as frequency channel (125 selectable channels), output power (0 dbm, -6 dbm, -12 dbm, or -18 dbm), and data rate (250kbps, 1mbps, or 2mbps). the spi bus employs the master and slave concept. table 2 listed the pin configuration of the module. table 2 mq-2 gas sensor pin configuration number pin descriptions 1 gnd ground 2 vcc 3.3 v supply 3 ce chip enable 4 csn chip select not 5 sck serial clock 6 mosi master out slave in 7 miso master in slave out 8 irq interrupt request the transceiver module architecture is made up of several concurrent data pipelines with unique addresses. a data pipe is a logical channel in the physical rf (radio frequency) channel which uses shockburst technology [14]. the transceiver module decodes the physical address (also known as the data pipe address) of each data pipe. the technology of shockburst employs first-in, first-out (fifo) on a chip to clock in data at a low rate and transmit it at a high rate which in turn allows for significant power savings. the transceiver module can be utilized in shockburst mode to make use of the 2.4 ghz band high data rates (1 mbps) without the requirement for an expensive, highspeed microcontroller (mcu) for data processing [15]. the transceiver module also offers the following benefits by housing all high-speed signal processing that is related to the rf protocol on-chip. • highly reduced current consumption • reduced system cost (allows for the use of a less expensive microcontroller) • a much lower probability of on-air collisions due to short transmission periods. 3. gas concentration sensor module the mq-2 gas sensor module was used in the design of the system. mq-2 is a flammable gas semiconductor sensor. the mq-2 gas sensor's sensitive substance is sno2, which has a reduced conductivity in clean air. when the target flammable gas is present, the sensor's conductivity increases, as does the gas concentration. the mq-2 gas sensor detects lpg, propane, smoke, and hydrogen with excellent sensitivity; it might also detect methane and other combustible steam. it is inexpensive and useful for a variety of uses. combustible gas concentrations present in the air are monitored and detected using the mq-2 gas sensor which has a straightforward drive circuit and a wide operating range with 4pins configuration (see table 3). the mq-2 sensor module showed in figure 3. figure 7 mq2 gas sensor module table 3 mq-2 gas sensor pin configuration number pin descriptions 1 vcc 5v supply 2 gnd ground 3 d0 digital out 4 a0 analog out it is also steady, long-lasting, responsive and rapid. due to its great sensitivity to smoke, hydrogen, lpg (liquid petroleum gas), methane, carbon dioxide, alcohol, and propane, the gas sensor has long been used to assist in detecting gas leaks in a variety of domestic and commercial settings. eai endorsed transactions on smart cities | volume 7 | issue 2 | a. abdullahi et al. 8 figure 8 sensitivity characteristic curve the concentration of gases measured in parts per million (ppm) is estimated by using a resistance ratio (rs/r0). where r0 is the stable sensor resistance in fresh air or without gas presence, and rs is the recorded change in resistance when the sensing device detects any gas leak. using ohm's law and the sensor schematic as a guide. 𝑅𝑅 = 𝑉𝑉𝑉𝑉−𝑅𝑅𝑅𝑅 𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 − 𝑅𝑅𝑅𝑅. (1) vc is the voltage current, output voltage (vout) is the output voltage (measured analog/digital values), and rl is the load resistance (set up is at 10k). r0 was then calculated using this equation, r0 = rs/fresh air ratio value from the datasheet. in order to convert the digital signal to concentration units, a nonlinear expression in equation 2 was used for implementing a simple calibration line for the mq-2 gas sensor 𝑦𝑦 = 𝑚𝑚𝑚𝑚 + 𝑏𝑏 (2) since it follows a log-log scale, a bit more advanced calculation was needed and equation (2) was converted to log(𝑦𝑦) = 𝑚𝑚 ∗ log(𝑚𝑚) + 𝑏𝑏 (3) by using a chart, the slope and intercept were calculated in which 𝑚𝑚 = 𝑙𝑙𝑉𝑉𝑙𝑙�𝑦𝑦 𝑦𝑦0� � 𝑙𝑙𝑉𝑉𝑙𝑙�𝑥𝑥 𝑥𝑥0� � and b = log(𝑦𝑦)−𝑚𝑚 ∗ log(𝑚𝑚) (4) once these values were obtained, the concentration of gases was now be calculated as 𝑚𝑚(𝑝𝑝𝑝𝑝𝑚𝑚) = 10[log(𝑦𝑦)−𝑏𝑏] 𝑚𝑚⁄ (5) where y is equal to rs/r0. 4. gsm communication module the base station used sim800l gsm/gprs module to offers a compact and versatile solution for sms notification. the sim800l gsm/gprs module designed for various applications, which included internet of things (iot) and alert notification. it offers a wide range of functionalities like a standard cell phone. the core component of this module is the sim800l gsm cellular chip manufactured by simcom. operate at low voltage range of 3.4v to 4.4v, which makes it well-suited for battery-powered applications. table 5 showed the pin configurations of the module. figure 9 sim800l gsm/gprs module features: • supports quad-band: gsm850, egsm900, dcs1800 and pcs1900 • use all gsm network sim • voice calls using speaker and microphone • transmit and receive sms • transmit and receive data (tcp/ip, http, etc.) • fm radio broadcasts table 4 sim800l gsm/gprs module pin configuration number pin descriptions 1 net network antenna 2 vcc 3.7v – 4.4v supply 3 rst reset 4 rxd data receiver 5 txd data transmitter 6 gnd ground 7 spkspeaker negative pin 8 spk+ speaker positive pin 9 micmicrophone negative 10 mic+ microphone positive eai endorsed transactions on smart cities | volume 7 | issue 2 | intelligent aircraft hangar fire detection and location system based on wireless sensor network in a smart city 9 11 dtr control sleep mode 12 ring ringing indicator c. hardware circuitry one of the primary objectives of the research was to showcase an advanced fire protection solution for aircraft hangars within the framework of a smart city concept. this solution leverages a sensor network, communication technologies, and machine learning (ml) as its core components. the system has been successfully implemented, and its schematic is depicted in figures 8 and 9. figure 10 sensor node module schematic diagram with all the components figure 11 base station (sink) module schematic diagram with all the components figure 12 sensor nodes and base station hardware. the project's overarching idea is to provide useful safety equipment for monitoring an aircraft hangar in case of a fire outbreak. three nodes and to present the state of the condition under three different scenarios which represent the normal smoke concentration state, warning gas concentration state and the fire predicted concentration state, as illustrated in figure 5. it is a concept that can be successfully implemented in a real-world situation. 4. experimental analysis the system is made up of three fundamental components which include detecting sensor nodes, a base station unit that serves as the sink and a computer system which serves as the server for real-time data analysis and display. to carry out the experiment, datasets from a mendeley data repository were examined [16] [17]. during the experiment however, both the high fire prediction state and other conditions were recorded in the database and several thresholds were used in the research to activate notification and fire alarm systems as well as fire locations when the threshold reached its limit. the environment for the prototype was designed for the integration of prediction algorithm and data visualization of the system. this was developed in c# .net programming language using the visual studio ide 2022. once the program executed, the user is shown the main window. the window is shown in the following captured image (see figure 20). thus, the main window of the program has the following sections: 1. the right side of the window displays the data received from the base station in real-time 2. the left side of the window displays the nodes gas concentration level includes; percentage, and notification. eai endorsed transactions on smart cities | volume 7 | issue 2 | a. abdullahi et al. 10 3. below, are the data logs in stored in the database figure 13 algorithmic flowchart. the system used a threshold of 400 and the detection rate of the gas concentrations in the air to display its various levels but this work is focused mainly on the emitted smoke to determine the normal scenario, the warning and high alert levels. table 1 displays the simulation results that were obtained. table 5. simulation result t n1 ppm node1 state n2 ppm node2 state n3 ppm node3 state 7:30 800 warning 302 normal 632 warning 7:35 1560 fire 302 normal 532 warning 7:40 2000 fire 320 normal 432 warning 7:45 2500 fire 320 normal 532 warning 7:50 3000 fire 302 normal 430 warning 7:55 3500 fire 154 normal 434 warning 7:60 3530 fire 202 normal 440 warning start gas concentration measurement initialized compare detection data with sample data in the database concentration. > threshold value trigger notification and display the location stop features extraction of smoke data eai endorsed transactions on smart cities | volume 7 | issue 2 | intelligent aircraft hangar fire detection and location system based on wireless sensor network in a smart city 11 conclusion the major objective of this project is to install several smoke sensor detector circuits in an aircraft hangar using the wsn concept in order to evaluate sensor data and predict the chances of a fire outbreak using an algorithm established on a real-time basis in a smart city environment. additionally, the system has the ability to locate and visualize different gas concentrations in the air from the computer gui and trigger a warning system throughout the hangar. this research proposes a solution to the problem of possible fire outbreaks through an early warning system capable of minimizing the risk of such dangers at aircraft hangars. on a computer system, the user can examine the status of each sensor node to reduce false alarms. this information would be very helpful for the firefighting effort as well as the evacuation procedure. the system can be used in both residential and commercial projects. references [1] gracias, j.s.; parnell, g.s.; specking, e.; pohl, e.a.; buchanan, r. smart cities—a structured literature review. smart cities 2023, 6, 1719-1743. https://doi.org/10.3390/smartcities6040080 [2] attaran, h., kheibari, n. & bahrepour, d. toward integrated smart city: a new model for implementation and design challenges. geojournal 87 (suppl 4), 511–526 (2022). https://doi.org/10.1007/s10708-021-10560-w [3] yin, c. t., xiong, z., chen, h., wang, j. y., cooper, d., & david, b. (2015). a literature survey on smart cities. science china information sciences, 58(10), 1–18. https://doi.org/10.1007/s11432-015-5397-4 [4] smolnikar, m., mihelin, m., berke, g., kandus, g., & mohorcic, m. (2010). ism bands spectrum sensing based on versatile sensor node platform. 2010 3rd international symposium on applied sciences in biomedical and communication technologies (isabel 2010). https://doi.org/10.1109/isabel.2010.5702937 [5] samuel david iyaghigba, comfort sunday ayhok (2021, april). “hangar fire detection alarm with algorithm for extinguisher”, global journal of engineering and technology advance. [6] khan, m.a. and hussain, s. (2020, december) "energy efficient direction-based topology control algorithm for wsn". wireless sensor network, 12, 37-47. [7] w mohammed al-shalabi, mohammed anbar, tat-chee wan a b, zakaria alqattan. (2019, october), “energy efficient multi-hop path in wireless sensor networks using an enhanced genetic algorithm”, elsevier volume 500, pages 259-273 [8] devraj gautam, sandeep bhatia, neha goel, basetty mallikaijuna, ganesha h s, bharat bhushan naib, "development of iot enabled framework for lpg gas leakage detection and weight monitoring system", 2023 international conference on device intelligence, computing and communication technologies, (dicct), pp.182187, 2023. figure 14 graphical user interface visualization data eai endorsed transactions on smart cities | volume 7 | issue 2 | a. abdullahi et al. 12 [9] avazov, k.; mukhiddinov, m.; makhmudov, f.; cho, y.i. fire detection method in smart city environments using a deeplearning-based approach. electronics 2022, 11, 73. https://doi.org/10.3390/electronics11010073 [10] gracias, j.s.; parnell, g.s.; specking, e.; pohl, e.a.; buchanan, r. smart cities—a structured literature review. smart cities 2023, 6, 1719-1743. https://doi.org/10.3390/smartcities6040080 [11] tianhai peng, fan yang, lei su, lingyan sun, yu chen, "information model of power distribution iot terminal for high-rise building electrical fire monitoring", international journal of metrology and quality engineering, vol.14, pp.5, 2023 [12] samih, h. (2019). smart cities and internet of things. journal of information technology case and application, 21(1), 3–12. https://doi.org/10.1080/15228053.2019.1587572 [13] x. long et al., "design of novel digital gfsk modulation and demodulation system for short-range wireless communication application," 2016 ieee international conference on electron devices and solid-state circuits (edssc), hong kong, china, 2016, pp. 299-302, doi: 10.1109/edssc.2016.7785267. [14] nordic semiconductor asa, "nrf24l01+ single chip 2.4ghz transceiver”, product specification v1.0, september 2008. (available online): https://infocenter.nordicsemi.com/pdf/nrf24lu1p_ps_v1.1.pdf [15] folgosa, ivano and excell, peter s., a low cost wireless interface linking a microcontroller to a microcomputer server (april 1, 2020). annals of emerging technologies in computing (aetic), vol. 4, no. 2, 2020, available at ssrn: https://ssrn.com/abstract=3760255 [16] narkhede, parag; walambe, rahee ; chandel, pulkit; mandaokar, shruti; kotecha, ketan (2022), “multimodalgasdata: multimodal dataset for gas detection and classification”, mendeley data, v2, doi: 10.17632/zkwgkjkjn9.2 [17] vetrivel sankar, krishnan balasubramaniam, sundara ramaprabhu, april 9, 2022, "gas sensor demo", ieee dataport, doi: https://dx.doi.org/10.21227/19qb-9t12. [18] avazov, k.; mukhiddinov, m.; makhmudov, f.; cho, y.i. fire detection method in smart city environments using a deeplearning-based approach. electronics 2022, 11, 73. https://doi.org/10.3390/electronics11010073 eai endorsed transactions on smart cities | volume 7 | issue 2 | medbot-medical diagnosis system using artificial intelligence eai endorsed transactions on smart cities research article a contemporary approach to designing and implementing electronic voting systems (evs) adams a. k. azameti 1, *, samuel chris quist1, godfred koi-akrofi1, and benedict c. nwachuku2 1 department of information technology, university of professional studies, accra-ghana 2 department of information technology, academic city university college, accra-ghana abstract keywords: smart cities, software engineering, e-voting system, intelligent agent, multi-agent systems, received on 19 september 2023, accepted on 11 march 2024, published on 14 march 2024 copyright © 2024 a. a. k. azameti et al., licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.3896 *corresponding author. email: adamsblessed36@gmail.com 1. introduction the idea of using electronic technology in political elections predates the internet. it originated in the late 1980s with the advent of the advanced research projects agency network (arpanet), the national science foundation network (nsfnet), and the introduction of commercial internet service providers (isps) [1]. voting machines (vm) started emerging globally in the mid-19th century, with advancements in instrumentation, computer science, and artificial intelligence (ai) [1] [2]. by the early 20th century, mark-sense scanners were employed for ballot counting, notably the norden electronic vote tallying system in 1959 [3] [4]. voting technology took a significant leap in 1965 with votronic's optical mark vote tabulator [3]. in the mid-20th century, punch-card voting systems (pcvss) gained popularity but faced some issues [5] [6]. the year 2020 marked a decline in the use of punch card systems, primarily due to their shortcomings during the us presidential elections [5]. the 1970s witnessed the invention of another voting machine (vm), and in 1974, the first direct-recording electronic (dre) voting machine was used in a legally binding election. the 20th century brought the internet revolution, allowing various countries to explore electronic voting technologies [5]. these advances foster the integration of electronic voting systems into smart city infrastructure as a key pillar for the advancement through the journal of smart cities research where e-voting application is evident [7] [8]. it has the potential to provide discussions on the policies and regulations governing e-voting. e-voting systems can be seen as part of this technological ecosystem, and this journal can explore how these systems integrate with other smart city technologies like iot, data analytics, and digital identity systems [7, 8]. e-voting systems raise important issues related to data security and privacy [8]. the e-voting system ensures this study investigates into the potential of electronic voting systems (evs) in ghana, to enhance transparent and trustworthy electoral processes. we presented a comprehensive framework highlighting trust, diaspora engagement, and human factors in voting. the study proposes a robust evs framework for ghana, emphasizing trust and accountability, preventing electoral fraud, and encouraging african governments to invest in it and collaborate with experts in e-government and e-voting systems. we commence with a detailed systems analysis, identifying specific electoral challenges in ghana. an artifact is designed and developed, and its effectiveness is demonstrated through design science research methodology (dsrm). we evaluated its alignment with the desired solution for ghana's electoral issues. we emphasize the potential of evs to address electoral challenges in ghana and underscore the importance of proactive government policies, it investments, and collaboration with it experts. user performance assessment and acceptance testing were evaluated and achieved a remarkable 98% approval rate, demonstrating the feasibility of implementing evs at the national level. this research underlines the role of evs in ghana and advocates for visionary government policies and investments in it. these measures can modernize electoral systems, align them with international standards, and promote democratic advancement while preventing electoral fraud in ghana and other african nations to avoid condemnation and punishment of unconstitutional transfers of power that are being challenged through meticulously planned takeovers in the subregion in recent times. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | mailto:adamsblessed36@gmail.com a. a. k. azameti et al. 2 the confidentiality and integrity of votes, and how they protect voter information aligns with this journal [8]. in addition, it plays a pivotal role in raising awareness among the public and stakeholders about the benefits and challenges of e-voting systems and their applications in smart city activities [8]. electronic voting (e-voting) involves capturing, recording, and processing election data digitally in real-time [5] [6]. it is a formal decision-making process for electing public officials. the efficiency, reliability, and security of e-voting systems (evs) are crucial for a safe system [6]. traditional paperbased voting systems have their share of the problems, including lost, stolen, or miscounted ballots [9]. e-voting is changing the perception of voting processes, enabling participation without constraints or political influences [6]. e-voting consists of various methods, from touchscreen kiosks to online voting [6]. it can include punched cards, optical scan systems, specialized kiosks, and even voting via phones or the internet. e-voting offers real-time results, enhancing accuracy and transparency. in the proposed evs, voters cast their ballots online, with strict registration processes supervised by administrators for security [10]. this approach reduces congestion, minimizes errors, and allows for verification. traditional systems have faced disputes and violence, as seen in the 2020 elections in ghana and the 2022 kenyan elections [11] [12]. global election observers have advocated for evs in africa to combat vote rigging and ensure accountability [13]. history has shown flaws in traditional voting systems, underscoring the need for evs [11] [12]. for instance, kenya's electoral commission struggled to update the voters' register, leading to disputes [12]. brazil introduced an e-voting system in 1996 to improve accountability and transparency [13] and as a result, e-voting has been used successfully in various countries globally. the government of ghana should be prepared to implement e-voting in the 2024 elections to ensure free and fair elections. furthermore, the coup d'états in west africa, central africa, and the sahel region are troubling. this frequent phenomenon in the subregion in recent times should serve as a warning to other african leaders to uphold the rule of law and thus seek the ultimate interest of the citizens above personal gains. evs can help africa overcome electoral challenges, such as fraud and violence, as witnessed in ghana's 2020 election [11] [14]. voter registration issues and external factors like rain have also affected turnout [14]. early education can influence voter participation, but traditional systems in ghana have discouraged voters due to long queues and cumbersome processes. this study proposes a novel evs based on design science research methodology (dsrm). it addresses the limitations of existing systems and aims to improve transparency, reliability, and efficiency. the 2020 election issues in ghana motivated this project, which focuses on developing a mobile application for voting [15]. the system aims to remind voters, validate eligibility, and ensure fast, accurate result computation. the paper is structured as follows: section 2 provides background and defines the problem. section 3 outlines the dsrm methodology and processes used to develop the evs. section 4 discusses the proposed system and outlines system implementation and its related interfaces, section 5 performs system evaluation in which performance assessment criteria were examined to ascertain that the system meets its requirements and section 6 concludes the paper and suggests future research directions for enhancing transparency and security [14]. 2. related work electronic voting ( e-voting), stands as a major transformation to enhance democratic processes. in a world constantly evolving through technological innovation, the traditional paper-based methods of voting have faced challenges and limitations. the integration of electronic systems into voting procedures has offered potential solutions to these challenges, promising greater accessibility, efficiency, and transparency in elections. we embark on a journey through the evolution of electronic voting systems, spanning from their inception to contemporary trends. these works collectively shed light on the ever-expanding landscape of electronic voting, addressing issues that range from security and privacy to usability and trustworthiness. we read through these papers and investigated the major findings and insights presented by each of them. these findings encompass a wide array of perspectives and considerations, reflecting the multifaceted nature of electronic voting. the authors' research endeavors seek to inform and guide us in the pursuit of more secure, reliable, and accessible voting systems. we aim to gain a comprehensive understanding of the challenges and opportunities that electronic voting presents in the context of modern democracies. each paper offers a unique lens through which we can examine the past, present, and future of electronic voting systems, ultimately contributing to the ongoing discourse on the transformation of the electoral process. the paper [16], offers valuable insights into the use of electronic voting systems in a large-scale educational setting. it focuses on practical experiences and provides useful guidance for educators considering similar implementations. it examines the challenges and successes of this experience, providing key indicators for success. the paper [17] examines the current status of blockchain-based voting research and highlights the advantages of using blockchain technology in electronic voting systems. it identifies privacy protection and transaction speed as major challenges. the paper [18], evaluates previous national electronic voting systems, highlighting their disadvantages before the advent of blockchain technology. it reviews electronic voting systems utilizing blockchain technology, discussing their strengths and weaknesses. this paper [19], appears to provide a comprehensive review and taxonomy of electronic voting schemes, making it a valuable resource for understanding the landscape of electronic voting. it emphasizes the importance of security requirements and discusses challenges in electronic voting systems. the paper [20] reviews various electronic voting systems, identifies shortcomings, and proposes a novel approach for developing a secured electronic voting system using fingerprint and visual semagram techniques. the paper [21], reviews the evolution of electronic voting systems and their increasing adoption in various elections worldwide. it discusses the challenges posed by complex communication technologies in e-voting, including verifiability, dependability, security, anonymity, and trust. it further eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a contemporary approach to designing and implementing electronic voting systems (evs) 3 explores different views on the adoption of online voting and reports on the role of technology transfer from research to practice. the author [10], focuses on india's use of electronic voting machines (evms) in elections and highlights their simplicity, reliability, and usability. despite criticism, certain details of the evms' design have not been publicly disclosed or rigorously evaluated for security. it examines the effectiveness of evms in the indian electoral system, considering both challenges and opportunities. the paper [22], examines the usability of electronic voting systems, particularly those using touch screens. it reports on usability studies, including expert reviews, observations, field tests, and exit polls. the analysis suggests that electronic voting systems generally work well but have some shortcomings, especially related to voter usability. the paper [23] defines evoting as any method where a voter's intention is expressed or collected electronically. the paper [24] provides an overview of global developments in e-voting, with a focus on remote and internet voting. it discusses the interest in e-voting across various sectors and highlights the lessons learned from e-voting tests. the major finding is the increasing attention to e-voting due to its potential to address issues with traditional voting systems. the paper [25], explores the evolution of electronic voting systems, including shifts from paper-based to paperless, manual to technology-driven methods. it discusses the development, legalization, guidelines, vulnerabilities, security, and protection aspects of electronic voting systems over time. the paper [26], discusses the implementation of remote online voting systems suitable for a university setting, allowing students to vote using various electronic devices. it highlights the use of modern technologies, like extensible markup language and extensible style language transformation style sheets, to ensure a consistent voting experience across different devices. it further focuses on achieving "author once, publish to any device" in the context of electronic voting. it discusses the design and implementation of a secure electronic voting system allowing voters to cast their votes using various electronic devices. it further emphasizes the use of technology for enhancing the convenience and integrity of the election process. the paper [18] discusses the advantages of e-voting over traditional paper voting systems and explores the evolution of electronic voting, particularly with the emergence of blockchain technology. it outlines the strengths and weaknesses of e-voting systems using blockchain. the major finding is the potential for blockchain to enhance the security and transparency of e-voting systems. the paper [27] focuses on estonia, a country that has made significant strides in deploying internet voting. it explores the legal, technical, political, and cultural aspects that have contributed to estonia's successful implementation of internet voting. the major finding is the in-depth analysis of how estonia has addressed the challenges and considerations associated with e-voting, providing valuable lessons for other nations. the paper [28] highlights the significance of elections and voting in democratic societies and the increasing interest in evoting as a means to address the shortcomings of manual voting systems. it reviews common e-voting models, existing election schemes, and essential e-voting terminologies. the major finding here is the growing interest and importance of e-voting in the context of e-government and e-democracy initiatives. the paper [29], compares and integrates the approaches taken by the u.s. and eu regarding e-voting system certification. it suggests that combining high-level guidelines from the eu with field-tested procedures from the u.s. can create a practical certification manual. the major finding is the proposal for an applied methodology that enhances the certification of e-voting systems, ensuring their reliability and security. the systematic review investigates the factors influencing the successful implementation of e-voting, particularly in namibia and estonia [30]. the study identifies critical factors such as ict infrastructure, legal and institutional factors, security, trust, and voter education. the major finding is the identification of these key factors that can shape the successful adoption of e-voting systems, providing valuable insights for policymakers. the paper [31], outlines the requirements, design, and implementation of electronic voting systems, particularly in a university setting. it emphasizes the separation of data content from presentation to achieve flexibility across different devices. the major finding is the "author once, publish to any device" approach, which simplifies the design and implementation of e-voting systems. the article [32] discusses the importance of voter-verifiable audit trails in electronic voting systems and evaluates the state's criteria for direct-recording electronic (dre) voting machines equipped with voter-verified paper records (vvpr). it addresses privacy, security, verification, integrity, functionality, and examination issues. the major finding is the potential for vvpr systems to enhance transparency and trust in e-voting. the paper [33], discusses the importance of electronic voting (e-voting) in e-democracy. it acknowledges the controversies, and criticisms surrounding e-voting, including concerns about electoral errors and fraud and further presents a risk assessment framework for e-voting and examines the factors that led to the abandonment of e-voting plans in ireland in 2004. thus, emphasizes the need for thorough risk analysis in e-voting implementation. the paper [34] addresses the controversy surrounding e-voting and internet-based remote voting and discusses the potential benefits of online voting, including increased voter turnout. the paper also highlights security concerns associated with internet voting and emphasizes the need for a comprehensive approach considering the technical, legal, social, and political aspects of e-voting research. the paper [35] discusses the goals of election reform efforts in various countries, including the u.s. and the u.k. these goals vary, from increasing voter turnout to reducing election fraud and enfranchising underrepresented populations. the overall aim of election reform is to improve the democratic process by making voting more accessible, accurate, and secure to prevent frequent coups in africa. the complex history of coups and coup attempts in africa has been the subject of extensive research and analysis over the years. in recent times, with the backdrop of the covid19 pandemic, there is growing concern that the continent may be on the brink of a new wave of political instability in the form of military coups. this review aims to shed light on key scholarly works that investigate this critical issue, offering valuable insights into the factors contributing to coup attempts in africa and potential strategies for prevention. hence the comprehensive study of the application of e-voting in national eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a. a. k. azameti et al. 4 elections in africa to mitigate coup d’etat is based on these findings: the author [36], explores the potential for a resurgence of coups in africa. major findings are due to the identification of political, economic, or social factors contributing to the risk of coups and increased political instability or dissatisfaction with governance. in [37], the author argued that the impact of the covid-19 pandemic on coup dynamics in africa is evidence of how the pandemic exacerbated existing vulnerabilities, potentially leading to an increase in coup attempts and insights into how health crises can strain governance and trigger political unrest. the author [38] conducts a comprehensive historical analysis of coup attempts in africa covering a considerable timeframe, unveiling observable patterns and trends in such endeavors across various decades. furthermore, the author evaluates the efficacy of strategies implemented to counteract coups within the african context. the author [39] employs quantitative methodologies to investigate the correlation between military coups and underdevelopment. the study presents statistical evidence that links coup events and diminished economic and social development indicators. the analysis provides perceptions of how coup events can impede development in the affected countries. in [40] the author concentrates on predictive models for coup attempts in africa and outlines insightful key variables, and risk factors that facilitate accurate coup prediction. the study provides potential perceptions into the efficacy of early warning systems in preempting coup attempts. the findings underscore the recurrent occurrence of reignited coups in africa, attributed to the failure of african leaders to recognize warning signs. moreover, the author [41], discusses emerging threats and vulnerabilities in the context of african military coups and examines the regional conflicts, external influences, or other factors that could heighten the risk of coup attempts and offers potential future scenarios and implications for african stability. finally, the author [42], also provided specific reasons behind the higher frequency of coups in africa compared to other regions with an analysis of structural, historical, and cultural factors that make africa more susceptible to coup attempts and how governance and power dynamics play a role in coup dynamics on the continent. the historical backgrounds of the coups in africa leading to the condemnation and punishment of unconstitutional transfers of power are being challenged by meticulously planned takeovers that seem to align with democratic principles and receive widespread popular approval by citizens. the study argued the need for african leaders to allow e-voting to ensure free and fair elections to deepen good governance in the subregion and to avert unnecessary coups for accelerated development of the continent. 3. methodology the concept of design science research methodology (dsrm) originates from engineering and sciences, particularly those focused on artificial artifacts. dsrm is a fundamental problem-solving approach [43], aiming to advance human knowledge by creating innovative artifacts and design knowledge (dk) through creative solutions to realworld challenges [43]. this concept has played a crucial role in enabling research communities and practitioners to develop innovative solutions for complex societal problems. dsrm finds applications in various fields, including engineering, natural sciences, business, and economics. dsrm integration into artificial intelligence and machine learning architectures into system design is suitable for the development of any complex systems. the dsrm framework serves as the foundation for developing any dsrm architecture and is elaborated in the section below. 3.1 the dsrm framework the framework catalyzes comprehending, executing, and evaluating design science research methodology (dsrm) [43] [44]. formulating research activities that cater well to the needs of stakeholders, such as citizens or electorates with an interest in e-voting system development, ensures research relevance. prior research and insights from scholars and practitioners provide robust theoretical support, including theories, frameworks, instruments, constructs, models, methods, and real-world implementations, which are essential for constructing the research study. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a contemporary approach to designing and implementing electronic voting systems (evs) 5 figure 1: amplified framework for design science research methodology as depicted in figure 1 above, dsrm investigates pertinent real-world problems across various application domains. dsrm underscores the importance of furnishing a solution that warrants empirical scrutiny involving researchers, practitioners, and industry collaborators, utilizing specific and pertinent technologies. the central point of dsrm emphasizes conducting thorough systems analysis within the specific real-world context of organizations, institutions, government agencies, companies, etc., to identify the precise issues requiring resolution as the initial step of the dsrm project. however, in scenarios where the specific needs of the problem domain have been previously identified or studied, dsrm would cement those established needs as the starting point. dsrm assesses the existing academic knowledge base to determine the extent to which design knowledge is available to address the identified problem. this academic knowledge may manifest as theories, frameworks, instruments, constructs, models, methods, and instantiations, coupled with methodologies like experimentation, data analysis, formalism, measures, validation criteria, optimization, models, construction, and processes. when this knowledge is deemed necessary to resolve the problem, it can be applied through routine design processes, falling outside the purview of dsrm. dsrm only comes into play when it seeks to create an innovative solution to the problem, typically building upon and modifying existing design knowledge to advance design activities for problem resolution. these design activities consist of 'building' and 'evaluating' components, iterated upon until the problem is effectively addressed. dsrm incorporates diverse research methods, contingent on the established research domain. for instance, in social science research, methods like interviews, surveys, literature reviews, or focus group discussions may be employed, whereas computer science and engineering may favor formal, experimental, building, processing, modeling, and simulation techniques to tackle identified problems. 3.2 dsrm process the dsrm projects rely on various process models, as outlined in [43], to tackle different projects in diverse domains. one widely referenced dsrm model is [43] [44]. the dsrm process consists of six stages: problem identification and motivation, defining objectives for the desired solution, design and development, demonstration, evaluation, and communication. additionally, it encompasses four other entry points, including problem-centered initiative, objective-centered solution, design and development-centered initiation, and client/context initiation. the complete dsrm process is illustrated in figure 2, providing a concise description on each dsrm activity. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a. a. k. azameti et al. 6 figure 2: design science research methodology process model the dsrm processes, from problem identification to evaluation stages, are illustrated with a specific focus on the execution of the e-voting project, from the problem activity stage to the evaluation activity stage, before implementation. activity stage 1. problem identification and motivation: this phase defines the e-voting research problem and justifies the proposed solution. the solution not only motivates researchers but also receives support from stakeholders by demonstrating a deep understanding of the problem. the resources required for this activity are based on the understanding of the problem's state and its solution to support stakeholder needs. activity stage 2. define the objective for a solution: this stage derives specific objectives from the problem definition and knowledge to develop the e-voting system. objectives can be quantitative (aiming for a better solution than existing systems) or qualitative (explaining how the new artifact description supports problem solutions). activity stage 3. design and development: this phase translates the specific objectives derived from the problem definition into a dsrm artifact capable of addressing stakeholder needs and objectives. it also determines the artifact's functionality and architecture based on the e-voting system's objectives. activity stage 4. demonstration: this stage highlights the significance of the artifact in addressing one or more instances of the problem identified. it involves specific methodologies, such as experimentation, simulation, case studies, proofs, or alternative approaches, to showcase the artifact's effectiveness. activity stage 5. evaluation: this phase measures how well the artifact aligns with the desired solution for the problem identified in stage one. it involves comparing the proposed solution's objectives to the actual observed results of the e-voting system. the outcomes inform researchers whether the artifact meets its objectives from the problem definition perspective. if not, iterations may be needed for improvements or further communication with stakeholders. activity stage 6. communication: at this stage, the aspects of the problem and the designed e-voting system are effectively communicated to stakeholders. stakeholders make an informed decision on whether the e-voting system adequately addresses the outlined problems. this communication extends to a wider audience, including professionals and research communities, to advance knowledge through journal publications. 3.3 uml system design the unified modeling language (uml) is a standardized modeling language facilitating the specification, visualization, construction, and documentation of software system artifacts [45] [46] [47]. uml ensures scalability, security, and robustness in software execution. uml plays a crucial role in object-oriented software development. 3.3.1 use case a use case diagram offers a graphical representation of interactions among system elements. it serves as a methodology for system analysis, aiding in the identification, clarification, and organization of system requirements. these diagrams illustrate use cases and the specific roles played by actors within and around the system. key components of a use case diagram include [47] [48]: actors: actors are entities external to the system that interact with it. these can be users, other systems, or even hardware devices. actors are represented as stick figures or other symbols outside the system boundary. use cases: use cases represent the specific functionalities or tasks that the system needs to perform their relationships and eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a contemporary approach to designing and implementing electronic voting systems (evs) 7 interactions to fulfill the needs of its users or external entities. each use case describes a particular interaction between an actor and the system. system boundary: the system boundary defines the scope of the system and separates it from its external environment. use cases and actors are typically placed within this boundary. associations: associations or lines connect actors to use cases, illustrating the relationships and interactions between them. each association represents a communication path. figure 3: use cases of actors within the evs 3.3.2 sequence diagram a sequence diagram is a type of interaction diagram in the unified modeling language (uml) that depicts the interactions among objects or components within a system over time [45] [46] [47, 49]. it provides a dynamic view of the system, illustrating the sequence of messages exchanged between different entities and the order in which these interactions occur. key components of a sequence diagram include: lifelines: lifelines represent the different entities or objects participating in the sequence of interactions. each lifeline is depicted as a vertical dashed line, and the length of the line corresponds to the duration of the object's existence during the interaction. messages: messages are depicted as arrows and represent the communication or interaction between lifelines. they indicate the flow of information or control between objects. messages can be synchronous (i.e. request and wait for a response) or asynchronous (i.e. send a message and continue without waiting for a response). activation boxes: activation boxes represent the period during which an object is actively processing a message. they appear as a box around the portion of the lifeline where the object is executing a particular task or operation. focus of control: the focus of control, represented by an arrow, indicates the direction of control flow during the execution of a message. it helps visualize the order in which messages are processed. return messages: return messages illustrate the response sent by an object after processing a received message. they complete the communication loop between the sender and receiver. sequence diagrams are valuable for understanding the dynamic behavior of a system, particularly in scenarios where the flow of interactions and the order of message exchanges are crucial for comprehending system behavior over time. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a. a. k. azameti et al. 8 figure 4: sequence diagram showing the movement of actors with procedural events 3.3.3 class diagram a class diagram in unified modeling language (uml), is a visual representation that illustrates the structure and relationships of classes within a system [45] [46] [47] [49]. it is a fundamental tool for object-oriented modeling and design, providing a blueprint for the software architecture. the essence of a class diagram lies in its ability to convey key aspects of the system's static structure, including classes, their attributes, methods, and the associations between them. the key elements of a class diagram consist of: class: it represents a blueprint for objects, encapsulating data (attributes) and behaviors (methods). classes are depicted as rectangles with three compartments, showing the class name, attributes, and methods. association: it indicates relationships between classes. associations define how classes interact and can be either unidirectional or bi-directional. multiplicity notations specify the number of instances participating in the association. inheritance (generalization): it illustrates the relationship between classes, showing inheritance hierarchies. the arrow points from the subclass to the superclass, indicating that the subclass inherits attributes and behaviors from the superclass. dependency: it represents a relationship where a change in one class may affect another. it is denoted by a dashed arrow. multiplicity: it specifies the number of instances of one class associated with a single instance of another class. it is depicted using numerical values or asterisks. class diagrams help developers and stakeholders understand the static structure of a system, facilitating communication and collaboration during the design and development phases of a project. they serve as a foundation for further design decisions, providing a visual guide for creating and maintaining robust, scalable, and well-organized software systems. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a contemporary approach to designing and implementing electronic voting systems (evs) 9 3.3.4 data flow representations a data flow diagram (dfd) in unified modeling language (uml) depicts a graphical representation that illustrates how data flows within a system. it focuses on the transformation of data as it moves through different processes: data stores, and external entities [46] [47] [49]. the essence of a data flow diagram lies in its ability to provide a clear and concise visualization of the flow of information within a system. the key elements of a data flow diagram include: processes: these represent activities or transformations that manipulate the data. processes are depicted as circles or ovals, and they describe the functions or operations performed on the incoming data. data flows: it represents the movement of data between processes, data stores, and external entities. arrows connecting these elements depict the direction of data flow, emphasizing how information is exchanged within the system. data stores: it represents repositories where data is stored. these can include databases, files, or any other storage mechanism. data stores are typically represented as rectangles. external entities: these represent external entities that interact with the system but are not part of it. these entities can be users, other systems, or external data sources. external entities are usually represented as squares. data annotations: these include data labels that provide additional information about the data being transferred, such as data types or specific attributes. dfds are valuable for understanding and communicating the flow of information in a system, helping to identify key processes, data sources, and interactions. they are particularly useful during the early stages of system analysis and design, allowing stakeholders to visualize and validate the information flow before moving into the detailed design and implementation phases. dfd facilitates communication among project team members and stakeholders, aiding in the development of robust and efficient information systems. figure 5: class diagram of the evs eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a. a. k. azameti et al. 10 figure 6: data flow diagram of evs 3.3.5 context representations a context diagram in a unified modeling language (uml) is a high-level visual representation that provides an overview of a system and its interactions with external entities [47]. the essence of a context diagram lies in its simplicity and focus on the system's boundaries, showing the relationships between the system and its external environment. the key elements of a context diagram involve: system boundary: it represents the scope of the system being modeled. it is typically depicted as a circle or a box, enclosing the system components. system: it represents the main subject or system under consideration. it could also be a software application, a process, or any entity being analyzed or designed. external entities: these represent entities outside the system boundary that interact with the system. these can include users, other systems, or external data sources. external entities are usually depicted as squares or rectangles. data flows: it represents the flow of information between the system and external entities. arrows connecting the system and external entities show the direction of data flow. context diagrams are essential for providing a high-level understanding of a system's context and interactions without investigating detailed internal processes. they serve several purposes: clarity: context diagrams provide a clear and concise view of the system's external interactions, making it easier for stakeholders to grasp the system's overall purpose and connections. communication: it facilitates communication between project teams and stakeholders by providing a common understanding of the system's boundaries and external influences. scope definition: context diagrams help in defining the scope of the system by highlighting what is inside and outside the system boundary. project planning: it serves as a starting point for project planning, helping project teams identify key external elements that need consideration during system analysis and design. in brief, context diagrams are a valuable tool in the early stages of system development, helping stakeholders establish a shared understanding of the system's context before proceeding with more detailed modeling and design activities. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a contemporary approach to designing and implementing electronic voting systems (evs) 11 figure 7: context diagram of evs 3.3.6 flowchart representations a flowchart in unified modeling language (uml), uses a diagrammatic representation that illustrates the sequence of steps or activities in a process [50]. while uml itself does not have a specific notation for flowcharts, traditional flowchart symbols and conventions are often used within the broader context of uml modeling. the essence of a flowchart lies in its ability to provide a visual representation of the flow and logic of a process. the key elements of a flowchart include: start and end symbols: these represent the beginning and end points of the process. typically depicted as ovals or rounded rectangles. process symbols: these represent activities or tasks within the process. usually depicted as rectangles, with each rectangle containing a description of the task. decision symbols: it indicates points in the process where a decision must be made, leading to different paths. often represented as diamonds, with branching arrows indicating possible outcomes. flow arrows: they connect symbols to show the flow and sequence of activities. arrows indicate the direction in which the process is progressing. connector symbols: used to connect different parts of the flowchart, especially when the process is too complex to fit on a single page. the essence of a flowchart in uml lies in its utility for process visualization, analysis, and communication. flowcharts are widely employed in various domains, including software development, business processes, and project management, to represent workflows, decision-making logic, and procedural steps. they serve several purposes: clarity: flowcharts provide a clear and easy-to-understand representation of processes, making it simple for stakeholders to follow the sequence of activities. analysis: it aids in analyzing and understanding the logical flow of a process, identifying potential bottlenecks, decision points, and areas for improvement. communication: flowcharts serve as a communication tool between team members, stakeholders, and individuals involved in the process, ensuring a shared understanding of the workflow. while uml primarily focuses on modeling object-oriented systems, flowcharts, including their symbols and conventions, are a valuable complementary tool for representing procedural aspects and process flows within the broader context of umlbased modeling. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a. a. k. azameti et al. 12 figure 8: e-voting systems flowchart eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a contemporary approach to designing and implementing electronic voting systems (evs) 13 figure 9: flowchart showing the process of voting eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a. a. k. azameti et al. 14 figure 10: register voter flowchart 4. system implementation and interfaces in this section, we analyze and discuss the practical implementation of the e-voting system, exploring its various interfaces and functionalities. 4.1 home interfaces the home interface serves as the initial point of contact for users upon launching the igbo students association (isa) app. its primary purpose is to provide information about the igbo students association. users can access faqs related to the association, and a menu for navigating the app is accessible through a dedicated button. while the primary focus of the project is the e-voting system within the app. it also doubles as an information hub for both members and nonmembers of the association. advertisers can also request to feature their products on this interface for a fee. 4.1.1 menu interfaces the menu interface functions include registration, my account, vote, results, and help as the central hub of the isa app, presenting users with several key options: registration: allows returning officers to register as association members. my account: displays the details of the currently logged-in user. if a user isn't logged in, clicking this button prompts them to log in. vote: navigates a registered user to the voting section, where he/she can cast him/her votes. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a contemporary approach to designing and implementing electronic voting systems (evs) 15 results: provides provisional voting results for a specific session. help: offers information on frequently asked questions about the igbo student association and a means to contact the association. registration interface: this interface is accessed by clicking the "registration" button. it enables returning officers, who possess the necessary credentials, to register new eligible voters of the association. information collected during registration includes first and last names, id numbers, email, gender, phone number, and a default password set by the returning officer. users are required to read and accept the terms and conditions before the returning officer proceeds with registration. my account interface: to access this interface, voters must log in using the information provided or given by the returning officer. they are required to change their password, ensuring it meets the security requirements. additionally, users can update their details here. voter interface: after verifying login credentials, users are directed to the voter interface when attempting to cast their votes. in this situation, they can select their preferred candidates, starting from the president and proceeding down the list. upon completing their vote, clicking the "finish" button stores their choices in the database. each office category opens a view for the voter to choose their preferred candidate from the options provided. results interface: this interface displays election results and serves as an information source for the votes cast. it presents candidate names and the number of votes they've received, with color codes explained at the bottom of the system. selected candidate interface: once a category (e.g., president) is selected, this interface allows users to choose their preferred candidate for that position. users simply select one option from the provided choices. a final confirmation is prompted to ensure the user's intent. if confirmed, the user's choice is saved, and they can continue voting for other offices. if denied, they can return to the selected preferred candidate page to make a different selection. login interface: before casting a vote, users must log in to ensure that only eligible voters participate and prevent fake votes. users enter a username and password. only those with the correct credentials are allowed to access the voting system. contact us interface: in this interface, users have the option to call the association by clicking the "call" button or send an email directly through their mail application. if users choose the email option, they are prompted to enter their full name and compose a message. about us interface: the about us interface offers users relevant information about the application, their voting rights, and the governing body responsible for the app's usage. figure 11: menu interface figure 12: voter registration page eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a. a. k. azameti et al. 16 figure 13: candidate voting page figure 14: login page 5. system evaluation: performance assessment criteria acceptance testing is a process used in software development to determine if a system or application meets specified requirements. the criteria used in the survey are (strongly agree, agree, somewhat agree, and disagree). they are commonly used in survey-based assessments and can be applied to evaluate various aspects of the acceptance test. the brief discussion for each criterion for the survey is as follows: strongly agree: the user or tester strongly believes that the system or application has met the specified requirement. the implication indicates a high level of confidence in the successful completion of the acceptance test. the user is satisfied that the software meets their expectations fully. agree: the user or tester believes that the system or application has generally met the specified requirement. its implication indicates a positive assessment, with the user being generally satisfied with the performance of the software. minor issues may exist, but they are not significant enough to undermine the overall satisfaction. somewhat agree: the user or tester is leaning towards an agreement but has reservations or concerns about certain aspects. the implication suggests that while there may be some satisfaction, there are noticeable issues or concerns that need attention. it indicates a level of uncertainty or a need for further investigation into specific areas. disagree: the user or tester believes that the system or application has not met the specified requirement. its implication signals a clear dissatisfaction with the performance or functionality of the software. these requirements could be due to major issues, critical bugs, or a failure to meet essential requirements. these criteria are subjective and depend on the perspective of the user or tester. they are useful in gathering feedback and assessing the overall success of the acceptance test. the goal is to ensure that the software aligns with the user's expectations and fulfills the agreed-upon requirements. system evaluation and testing have been conducted to ensure accuracy and correctness. user acceptance tests align the system with user requirements, and it has achieved a 98% acceptance rate. the user responses are summarized in table 1. eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a contemporary approach to designing and implementing electronic voting systems (evs) 17 table 1: user acceptance test and performance evaluation criterion 5.1 discussion on each criterion for assessment test table 1 presents an evaluation of various criteria related to the e-voting systems based on the responses of individuals. we evaluate each criterion below: system accuracy: strongly agree (8-10) has 314 responses, representing 98%, and indicates a high level of confidence in the system’s accuracy among the respondents. it demonstrates the extent to which the system produces correct and reliable results. high accuracy is crucial, especially in applications where precision is essential. ease of use: strongly agree (8-10) receives 314 responses with 98% acceptance suggesting the system is perceived as user-friendly. it explains how user-friendly and intuitive the system is for end-users. an easy-to-use system improves user adoption, reduces training costs, and enhances overall user satisfaction. system validation: strongly agree (8-10) similarly has 314 responses which represent 98% with strong agreement, indicating trust in the system’s validation processes. the process confirms that the system meets the specified requirements. system validation ensures that the software performs as intended and meets the user’s expectations. transparency: strongly agree (8-10) representing 314 respondents with 98% indicating a high agreement to suggests that respondents perceive the system as transparent. the degree to which the system's operations and decision-making processes are visible and understandable. transparency is essential for building trust and understanding how the system works, particularly in critical applications such as e-voting systems. convenience: agree (5-7) with 314 respondents representing agreement of 98% to indicate that respondents find the system convenient to use. it demonstrates how easily and comfortably, users can interact with the system. a convenient system enhances user experience and encourages regular use. authentication: strongly agree (8-10) which is 314 respondents, indicating strong agreement of 98% to suggests that respondents trust the system's authentication mechanisms. the process of verifying the identity of users or entities accessing the system. strong authentication is crucial for security, preventing unauthorized access to sensitive information. reliability: strongly agree (8-10) with 314 respondents representing a high agreement of 98% indicates that respondents consider the system to be reliable in its performance. the ability of the system to consistently perform as expected without failures. reliable systems are crucial, especially in mission-critical applications, to ensure consistent performance and availability. non-coercibility: strongly agree (8-10) representing 314 respondents with a strong agreement of 98% to indicate confidence that the system cannot be coerced or manipulated. the system should not force or coerce users into taking certain actions against their will. it demonstrates high ethical eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a. a. k. azameti et al. 18 considerations and user autonomy, particularly in systems dealing with personal information or decision-making. integrity: strongly agree (8-10) which has 314 respondents with high agreement of 98% to suggest that respondents perceive the system as maintaining its integrity. the assurance that data and information within the system are accurate and unaltered. data integrity is vital for maintaining the trustworthiness of information and preventing unauthorized tampering. certifiability: strongly agree (8-10) indicating 314 respondents with 98% indicating that respondents believe the system is certifiable, meeting necessary standards. the system's adherence to relevant standards and certifications. certifiability is important in regulated industries and ensures that the system complies with established norms. cost-effectiveness: agree (5-7) which receives 314 respondents, indicating agreement of 98% to suggest that it provides value for money. the efficiency of the system in delivering value relative to its cost. a cost-effective system maximizes benefits while minimizing expenses, contributing to overall organizational efficiency. uniqueness: strongly agree (8-10) which has 314 respondents suggesting strong agreement of 98% to indicate that respondents perceive the system as unique or innovative. the distinctiveness of the system's features or capabilities compared to alternatives. uniqueness can provide a competitive advantage and attract users looking for specific functionalities. auditability: strongly agree (8-10) which consists of 314 respondents with a high agreement of 98% suggests that respondents believe the system is auditable, allowing for scrutiny and verification of results. the ability to track and review system activities for accountability and compliance. auditability is crucial for regulatory compliance and internal monitoring of system behavior. secrecy: strongly agree (8-10) which receives 314 respondents, representing high agreement of 98% indicates that respondents believe the system maintains the secrecy of votes. the protection of sensitive information from unauthorized access. the implication implies secrecy is crucial in systems handling confidential data to prevent data breaches and maintain privacy. the evaluation across all criteria indicates strong agreement (98%) from respondents, suggesting high levels of confidence in the system's accuracy, usability, security, transparency, and other essential attributes. this overwhelmingly positive feedback indicates that the system is well-perceived and meets the expectations of users in various aspects, making it a reliable and trustworthy system for its intended purpose as an e-voting system. 5.2 performance assessment in this section, we explain the meaning of the criterion used for the performance assessment and how it relates to evs development. each of these criteria plays a vital role in assessing the performance, usability, security, and overall effectiveness of a system in its intended context and how the survey evaluation process was done immediately after casting the votes. the evaluation process was meticulously organized to gather input from a targeted group of 320 individual students. below is a detailed breakdown of the evaluation process. the evaluation aimed to include the participation of 320 individual students. the selection of these individuals involved stakeholders, users, or relevant participants with adequate interest in the subject matter under evaluation. voter turnout: the expected voter turnout was 320 voters. however, only 314 individuals actively voted successfully and subsequently completed the survey to cast votes immediately to evaluate the system’s performance. percentage of voters who voted: to calculate the percentage of voters who participated, we divided the 314 voters who cast votes by the 320 total number of voters expected and then multiplied by 100. actual voters = ( 314 320 ) x 100 = 98.125% (1) therefore, the percentage of voters who voted successfully was approximately 98.13% to calculate the percentage of voters who did not participate, subtract the 314 number of voters from the 320 expected total number of voters and multiply by 100. voters absent = ( 320−314 320 ) x 100 = ( 6 320 ) x 100 = 1.875% (2) therefore, the percentage of voters who did not turn out to vote was approximately 1.8%. in brief, the evaluation process targeted the participation of 320 voters, but 314 individual students actively participated resulting in a high voter turnout of approximately 98.13%. the remaining 6 individual students who did not vote represent 1.88%. this information provides insight into the engagement level and participation rate in the evaluation process indicating the robustness of the evs. section a: socio-demographic data no questions user / (voter) % returning officer % q1 gender male 147 46.8 10 3.2 female i51 48.1 6 1.9 q2 age groups 18-28 179 57 5 1.6 29-38 68 21.7 7 2.2 39-48 51 16.2 4 1.3 49-58 59+ eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a contemporary approach to designing and implementing electronic voting systems (evs) 19 q3 marital status single 278 88.5 12 3.8 married 20 6.4 4 1.3 q4 highest education shs 263 84.0 6 2 diploma 22 7.0 3 1 degree 10 3.2 3 1 masters 3 1 2 0.6 phds other q5 designated university/technical university university of ghana, accra-public 27 8.6 5 1.6 university of cape coast (ucc)public 13 4.1 university of education, winnebapublic 2 0.6 nkrumah university of science and technology, kumasipublic 23 7.3 4 1.3 university of mines & technology, tarkwa-public 4 1.3 university of professional studies, accrapublic 11 3.5 university of development studies, tamalepublic 3 1 ghana communication technology university (gctu), accrapublic 15 4.8 1 0.3 regional maritime university, accrapublic 13 4.1 ashesi university, accra-private 14 4.5 1 0.3 central university 15 4.8 1 0.3 all nations university 14 4.5 1 0.3 methodist university 14 4.5 2 0.6 presbyterian university islamic university college, ghana (accra) 4 1.3 ghana institute of management and public administration (gimpa), accra. 11 3.5 christian service university college, kumasi catholic university of ghana (cug), sunyani 3 11 accra institute of technology, accra 5 1.6 regent university college of science and technology, accra 14 4.5 1 0.3 knutsford university college, accra 5 1.6 garden city university college, kumasi wisconsin international university college, ghana (accra) 11 3.5 academic city university college, (accra) 12 3.8 radford university college (accra) evangelical presbyterian university college (ho) 3 1 african university college of communication (aucc), accra 5 1.6 kaaf university college 6 2 university of energy and natural resources 3 1 zenith university college, accra 9 2.9 accra technical university 7 2.2 kumasi technical university 7 2.2 ho technical university 6 2 takoradi technical university 5 1.6 koforidua technical university 9 2.9 cape coast technical university 5 1.6 section b: digital literacy and accessibility of using e-voting systems q1 to what extent do you feel digitally literate to use the e-voting system for this election? (please, indicate your digital literacy and accessibility of using e-voting systems in the box provided based on a scale of 1-5 where 1 is very low and 5 is very high where possible.) very low 2 0.6 low 11 3.5 don’t know/not sure 12 3.8 high 108 34.4 very high 181 57.6 q2 what challenges do you foresee for students with limited digital literacy in using e-voting systems? limited understanding of technology 16 5.1 difficulty in using electronic devices 3 1 concerns about security and privacy 71 22.6 eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a. a. k. azameti et al. 20 risk of making errors during voting 36 11.5 difficulty in verifying votes 92 29.3 limited access to information 21 6.7 digital exclusion and inequality 11 3.5 potential for coercion or manipulation 13 4.1 difficulty in troubleshooting technical issues 51 16.2 q3 are you aware of any resources or support services available to enhance digital literacy by using e-voting systems? yes 197 62.7 no 76 24.2 maybe 41 13.1 q4 in your opinion, how would you rate the following digital literacy initiatives to improve and ensure broader accessibility to e-voting platforms? tailored training programs 57 18.2 online tutorials and resources 12 3.8 community workshops and outreach 27 8.6 multilingual support 23 7.3 incorporate user-friendly design 56 17.8 collaboration with educational institutions 36 11.5 public awareness campaigns 53 16.9 accessible learning platforms 15 4.8 continuous support and feedback mechanisms 35 11.1 q5 do you believe that e-voting systems are user-friendly for individuals of varying levels of digital literacy? yes 253 80.6 no 51 16.2 maybe 10 3.2 q6 to what degree does your perception of your digital literacy influence your willingness to adopt e-voting in elections? (please, indicate your digital literacy and accessibility of using e-voting systems in the box provided based on a scale of 1-5 where 1 is very low and 5 is very high where possible.) very low 3 1 low 36 11.5 don’t know/not sure 7 2.2 high 101 32.2 very high 167 53.1 q7 how would you rate your level of digital literacy in terms of using technology, including e-voting systems? (please, indicate your digital literacy and accessibility of using e-voting systems in the box provided based on a scale of 15 where 1 is very low and 5 is very high where possible.) very low 4 1.3 low 15 4.8 don’t know/not sure 3 1 high 91 28.9 very high 201 64.0 q8 what challenges do you anticipate for individuals with limited digital literacy in utilizing e-voting systems? difficulty in navigating electronic interfaces 61 19.4 lack of familiarity with technology 23 7.3 concerns about security and privacy 37 11.8 difficulty in verifying votes 61 19.4 limited access to information 13 4.1 potential for coercion or manipulation 24 7.6 difficulty in troubleshooting technical issues 25 8.0 risk of making errors during voting 40 12.7 digital exclusion and inequality 30 9.6 table 2: analysis of survey data to assess the effectiveness of the e-voting system 5.3 discussion on performance assessment to evaluate the data provided in table 2, we analyze various aspects such as socio-demographic characteristics and attitudes toward e-voting systems. the evaluation has been broken down into sections below: section a: socio-demographic data eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | a contemporary approach to designing and implementing electronic voting systems (evs) 21 • gender distribution: the data shows that 46.8% of respondents are male, while 48.1% are female. there is a slight imbalance favoring females. it is noteworthy that a significant portion of 3.2% returning officers are male while 1.9 % are female). • age group: the majority of respondents 57% within the 18-28 group indicating a younger demographic. • marital status: a vast majority 88.5% of respondents are single, suggesting potential differences in voting behavior compared to married individuals. • highest education: the majority have completed senior high school (shs), indicating a relatively high level of education among respondents. • designated university/technical university: the data provides insights into the distribution of respondents across different educational institutions, which could be valuable for targeting awareness campaigns or training programs. section b: digital literacy and accessibility of using e-voting systems • digital literacy: we had 57.6% significant majority feel very highly about using the e-voting systems, while 34.4% rate their literacy as high. only a small percentage of 4.1% feel very low or low digital literacy, which is promising for e-voting adoption. • challenges faced by students with limited digital literacy: concerns about security, privacy, and difficulty in verifying votes are the most significant challenges identified, indicating areas for improvement in e-voting system design and education. • awareness of resources for digital literacy enhancement: a majority of 62.7% are aware of resources or support services available to enhance digital literacy by using e-voting systems, suggesting a positive inclination toward learning. • perception of digital literacy initiatives: tailored training programs, user-friendly design, and public awareness campaigns are perceived positively, indicating potential areas of focus for improving digital literacy. • user-friendliness of e-voting systems: a large majority of 80.6% believe e-voting systems are userfriendly for individuals of varying levels of digital literacy, which is crucial for adoption. • impact of digital literacy adoption: a significant majority of 85.3% have a high or very high perception of their digital literacy, which positively influences their willingness to adopt e-voting systems. • challenges for individuals with limited digital literacy: difficulty in navigating interfaces, verifying votes, and troubleshooting technical issues are the primary challenges anticipated, highlighting areas for improvement in system usability and support. in general, the data suggests a generally positive towards evoting systems, with a majority expressing confidence in their digital literacy and user-friendliness of such systems. however, there are still concerns regarding security, privacy, and potential technical challenges, especially among individuals with limited digital literacy. targeted efforts in education, training, and system design are essential to address these concerns and ensure broader accessibility and acceptance of e-voting systems among diverse demographics. 6. conclusion and future work the e-voting system (evs) has received widespread endorsement in the african continent, particularly following attempts at election rigging by a few presidential candidates. electoral fraud, or the manipulation of election results, is a prevalent issue in many african countries. in recent times, some african countries have seen coup d’etats due to many factors: popular dissatisfaction, institutional weakness, historical precedents, authoritarian regimes, military discontent, and economic crisis. one major pillar to preventing coup d’etats in africa is building a strong institution to make independent decisions without any political influences. challenges to implementing evs at the national level in countries like ghana include high illiteracy rates. however, its successful implementation in tertiary institutions, as demonstrated by a 98% user acceptance rate, can serve as a model for broader adoption. as these educated students graduate, they will educate the nation about the benefits of evs over traditional systems, fostering transparency and trust in electoral systems across africa. african leaders should invest in information technology to develop robust e-government and e-voting applications. collaboration between it experts and government is crucial for timely implementation. recent advancements in egovernment in ghana exemplify progress in this direction. it is advisable to implement e-voting systems in the 2024 general elections to ensure transparent, auditable, and trustworthy electoral processes in 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pervasive health and technology, 2022, 8, (30) [48] kim, c.-h., weston, r.h., hodgson, a., and lee, k.-h.: ‘the complementary use of idef and uml modelling approaches’, computers in industry, 2003, 50, (1), pp. 35-56 [49] bersini, h.: ‘uml for abm’, journal of artificial societies and social simulation, 2012, 15, (1), pp. 9 [50] engels, g., förster, a., heckel, r., and thöne, s.: ‘process modeling using uml’, process‐aware information systems: bridging people and software through process technology, 2005, pp. 83-117 eai endorsed transactions on smart cities | volume 7 | issue 3 | 2023 | adams a. k. azameti 1, *, samuel chris quist1, godfred koi-akrofi1, and benedict c. nwachuku2 abstract 1. introduction 2. related work 3. methodology 3.1 the dsrm framework 3.2 dsrm process 3.3 uml system design 3.3.1 use case 3.3.2 sequence diagram 3.3.3 class diagram 3.3.4 data flow representations 3.3.5 context representations 3.3.6 flowchart representations 4. system implementation and interfaces 4.1 home interfaces 4.1.1 menu interfaces 5. system evaluation: performance assessment criteria acceptance testing is a process used in software development to determine if a system or application meets specified requirements. the criteria used in the survey are (strongly agree, agree, somewhat agree, and disagree). they are commonly used in su... strongly agree: the user or tester strongly believes that the system or application has met the specified requirement. the implication indicates a high level of confidence in the successful completion of the acceptance test. the user is satisfied that the software meets their expectations fully. agree: the user or tester believes that the system or application has generally met the specified requirement. its implication indicates a positive assessment, with the user being generally satisfied with the performance of the software. minor issues may exist, but they are not significant enough to undermine the overall satisfaction. somewhat agree: the user or tester is leaning towards an agreement but has reservations or concerns about certain aspects. the implication suggests that while there may be some satisfaction, there are noticeable issues or concerns that need attention. it indicates a level of uncertainty or a need for further investigation into specific areas. disagree: the user or tester believes that the system or application has not met the specified requirement. its implication signals a clear dissatisfaction with the performance or functionality of the software. these requirements could be due to major issues, critical bugs, or a failure to meet essential requirements. these criteria are subjective an... 5.1 discussion on each criterion for assessment test 5.2 performance assessment 5.3 discussion on performance assessment 6. conclusion and future work references this is a title eai endorsed transactions on smart cities research article 1 mlops and microservices frameworks in the perspective of smart cities i. b. urias1,* and r. rossi2 1,2 university of são paulo/continuing engineering education program (pece), são paulo, brazil abstract information technology involves solutions for many kinds of industries and organizations, offering conditions for solving problems of different types and complexities. artificial intelligence, and more specifically applications that considers machine learning (ml) and software technology are part of these solutions for solving problems, including solutions for solving problems that involve smart cities approach. in order to present frameworks that deal with the operationalization of machine learning and software technology, this article is based on the study and evaluation of frameworks that involve machine learning operations (mlops) and microservices. specifically, three frameworks that integrate ml algorithms with microservices are evaluated based on a bibliographical review in scientific journals of relevance to the area. from an exploratory analysis of these frameworks, it was possible to highlight their main objectives, their benefits, and their ability to offer solutions that favor the large-scale use of machine learning algorithms in problem solving. the main results are highlighted in the article through a qualitative analysis that considers six evaluation criteria, such as: capacity for sharing resources, scope of use by users, and use in a cloud environment. the results achieved are satisfactory since the work allows, through a qualitative view of the evaluated frameworks, a perspective of how the integration of mlops and microservices has been carried out, its benefits and possible results achieved through this integration. keywords: machine learning, machine learning operations, microservices received on 01 august 2023, accepted on 31 october 2023, published on 13 november 2023 copyright © 2023 i. b. urias et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.3661 1. introduction machine learning has recently become a field of study and research highlighted by its proposals, either in a theoretical approach or even in a practical approach. machine learning (ml) is an area of knowledge focused on technology that aims to develop algorithms to solve machine learning problems. these algorithms represent the simulation of human intelligence, using concepts from neuroscience, probability and statistics, computation, psychology, control theory and philosophy [1]. some of the main applications highlighted by [2] are: computer vision, semantic analysis, natural language processing, information retrieval, object recognition, object detection and processing, text and document classification, image analysis, diagnosis medical and *corresponding author. email: igor_bernardes_urias@hotmail.com prediction of network attacks. ml stands out in several areas of knowledge, which favours its use to solve the most diverse types of problems, being studied in a multidisciplinary way. these main applications can be used within the context of smart cities, solving problems and achieving goals. in the context of smart cities, it is possible to find works related to the topic encompass both a conceptual approach and practical aspects in [3], [4]. ml and software engineering complement each other, enabling an exploratory analysis to be conducted on the utilization and implementation of microservices in projects involving data engineering, software engineering, and ml; analysing and evaluating approaches for the development of automation solutions that utilize ml as services. microservices are programs that have unique and independent responsibilities, also known as units of work eai endorsed transactions on smart cities | volume 7 | issue 3 | https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ i. b. urias and r. rossi 2 that include a connection to the external environment [5]. microservices in general can generate advantages for technology and work teams. these are collaboration and communication actions between teams. microservices have been observed in companies such as amazon, deutsche telekom, linkedin, netflix, soundcloud, the guardian, uber, verizon, among others that aim to adopt approaches based on microservices [6]. applications involving microservices and ml have been explored through frameworks with the aim of making ml algorithms available as services. frameworks, conceptually, can be considered models of a domain or an important aspect of it that provides a reusable design (modelling) and reusable implementations for the client [7]. machine learning operations (mlops), through frameworks, stands out as a means of providing ml services using microservices. mlops uses some practices to operationalize ml algorithms as a service, and can be considered a paradigm for the development of ml algorithms. the main characteristics of this paradigm are based on the conceptualization, implementation, monitoring, deployment, and scalability of ml algorithms [8]. the proposals for integrating ml with microservices are grounded in certain principles that align with the adoption of microservices practices. these principles aim to ensure attributes like scalability and service independence. considering these introductory postulates of the article, its objective is highlighted, which refers to the presentation and qualitative evaluation of three frameworks that propose the automation of ml services and that corroborate for an investigative and exploratory analysis of the possibility of integrating mlops together to microservices for providing ml services. based on the objectives, it is possible to understand that these frameworks can potentially be used within the context of smart cities, considering the benefits of mlops and microservices. the research contributes with the presentation of each of the three frameworks that can be used to automate services from ml algorithms, favouring the response for decision making. the frameworks correspond to significant structures for the application of microservices together with the ml algorithms, allowing an exploratory analysis on the approach referring to mlops. the three frameworks, despite having similarities, also there are particularities that differentiate them, for example, the target audience and their different ways of modularizing the components that belong to the ml application. however, it is possible to observe that the three frameworks have a common feature regarding the automation of algorithms with the use of microservices to provide ml services. some studies stand out regarding the presentation of studies on mlops, such as: [9] which conceptualizes the mlops and presents a proposal for the steps to carry out the operationalization of ml; [10] who also presents a concept about mlops and contributes with the presentation of benefits and challenges of this paradigm, situating it as an approach that involves ml, devops, and data engineering. the introductory elements of the article are emphasized, followed by a succinct overview of the remaining sections, corresponding to: section two, presentation of a literature review, specifically for microservices and machine learning; section three, presentation of the three frameworks that integrate microservice practices with ml; section four, discussion and qualitative results observed from the studies of the three frameworks; and, section five, conclusions and final considerations about the research. 2. literature review this section presents a conceptual review of microservices and their quality attributes; and a review of machine learning concepts and main models; and an overview of machine learning operations (mlops). 2.1. microservices microservices can be conceptualized as: 1) small applications characterized by having unique responsibilities that can be deployed, scaled, and tested independently [11]; 2) an approach for distributed systems that promote the use of refined services with their own life cycles, which collaborate, being modelled mainly around the business domain [12]; 3) a programming paradigm made up of small services that communicate in applications. small services are characterized by communication based on light mechanisms that execute their respective processes [13]. the concepts presented have characteristics in common. there is the characteristic of independence between the services, that is, each service can work independently. another feature that stands out is connectivity, that is, despite the microservices being independent and with unique responsibilities, they are connected to each other, in order to form communications between them and with external environments. the practice of isolating functions related to the business domain aims to optimize the autonomy and replacement of services. these characteristics are facilitators regarding autonomous management, that is, the issue of governance that is decentralized between services [14]. characteristics such as isolation and autonomy of microservices make governance decentralized. decentralization is part of what is also conceptualized as an expected quality attribute for microservices. microservices are a new trend in software design and development that are driven by the business domain. however, it should be noted that microservices are not necessarily the right solution for all cases [15]. the use of microservices requires business domain; and knowing what the need or problem is the goal to be met, however, eai endorsed transactions on smart cities | volume 7 | issue 3 | mlops and microservices frameworks in the perspective of smart cities 3 microservices are a new trend offering useful features in services. the characteristics of microservices can be studied as quality attributes. quality attributes will determine the quality of the architecture. it is essential to evaluate architectures based on the qualities it supports in order to guarantee that the built system satisfies the needs of stakeholders [16]. the quality of the microservices architecture can be evaluated through the application of quality attributes. when performing a literature review on microservices, the main quality attributes are: scalability, independence, maintainability, deployment, diagnostic management, modularization, self-management, performance, reuse, heterogeneous technology, agility, security, balance, organizational alignment, open interface. as a given architecture for microservices is elaborated, it must satisfy and improve quality attributes. if the quality attributes are acceptable and conform to stakeholder expectations, it means that the microservices architecture is meeting the quality standards. 2.2. machine learning statistics and computer science can be considered two of the main disciplines that make up machine learning (ml). ml is an area of study and multidisciplinary research that may belong to applications of different organizations that currently use data intelligence for their goals. a relevant feature that stems from the conceptualization of ml is the goal of simulating human learning activities through the computer. this feature plays a key role in pattern recognition, operational research, data analysis, optimization problem solutions and proposed algorithms for information extraction and knowledge generation. machine learning refers to a set of studies in which the objective is the use of computers in simulations of activities like human learning, as well as the search to study methods of self-improvement of computers to obtain knowledge and skills, being possible identify existing knowledge, improving the objective and performance of ml algorithms [17]. ml aims to perform model training, focused on solving applied activities, constituting a segment of artificial intelligence (ai) with relevance in the evolution and improvement of technologies [18]. in general, solutions involving ml algorithms have data divided into subsets, a training subset aims to allow learning, through what is called training; and another test subset, which aims to verify how effective the learning steps were during training. there are different types of algorithms for performing ml tasks that can be categorized according to their goals and purposes, as well as the way they are operated. these algorithms can sometimes rely on labelled data, where labelled data is data that has some description of what it represents. these representations could be, for example, age, name, weight, and height labels could be database table headers. thus, given their respective specificities, ml algorithms are grouped as [19]: (i) supervised learning: characterized by generating a function that performs the mapping of a set of inputs, later providing a desired output. algorithms that use the model of supervised learning are generally used in classification problems. this algorithm is conditioned to learn in order to approximate the expected behaviour of a function. (ii) unsupervised learning: given a set of inputs where there are no labelled examples, algorithms that use the unsupervised learning model are generally used, responsible for modelling the set of inputs. (iii) semi-supervised learning: are characterized by using examples of labelled and unlabelled data in order to generate and provide an appropriate function or classification. algorithms that use semi-supervised learning models also have some characteristics of supervised learning algorithms. (iv) reinforcement learning: algorithms that use reinforcement learning models are characterized by learning from rules. these rules will define how the algorithm should act based on external information, such as observation. in each action, there is an external impact on the environment, where the external environment, on the other hand, provides the answers to the algorithm. (v) transduction: these models seek to predict new outputs, something very similar to what is done in supervised learning models, however, different from supervised learning. transduction do not directly and explicitly build a function with an expected behaviour, this model to perform the prediction of the new outputs, uses the inputs that are trained, the training outputs, as well as new inputs. 2.3. machine learning operations (mlops) mlops is related to important areas of study that contribute to its conceptualization. the main areas of study are ml, devops and data engineering: (i) machine learning, which refers to computational models based on experience that aim to improve performance or even make accurate predictions. experience as refers to a set of data that is used for the learning step. generally, these data are also used for analysis purposes [20]. (ii) devops: set of collaborative practices that employ multidisciplinary with the objective of automating software development through continuous deliveries based on versioning, guarantee of corrections; making the developed software more reliable [21]. (iii) data engineering: practices aimed at structuring data aimed at modelling and later use. data engineering provides data characterized by having the appropriate quality for the individuals who will use them [22]. eai endorsed transactions on smart cities | volume 7 | issue 3 | i. b. urias and r. rossi 4 the term mlops appears as a proposal to unite ml and devops, however, it is important to highlight that, given that devops does not have an explicit definition, it presents many concepts to describe it. devops is considered an organizational approach that enables the existence of a collaborative team, promoting empathy between individuals, focusing on development and operationalization [23]. consequently, mlops also becomes a term that provides a range of conceptualization possibilities. mlops presents some other possible concepts: 1) according to [24] mlops is analogous to devops in some characteristics, such as allowing software professionals to have greater efficiency for the development of ai algorithms through a more participatory collaboration. mlops also provides greater efficiency for deploying, scaling, monitoring, and training ai algorithms; 2) for [25] mlops can be considered a devops modality directed to the ml domain, that is, directed to the ml algorithms. in this regard, mlops aims to unite teams that develop ml algorithms with teams focused on operationalization. for mlops, some main steps are categorized, such as development, deployment, operation, and maintenance. these steps become useful to improve the use of ml algorithms, enhancing their growth in terms of the business domain; 3) for [26] mlops aims to promote a framework of practices for the development of ml algorithms seeking to optimize the time of the steps contained therein with a reduction in the costs involved. for this, the appropriate tools, steps, and pipelines are used. these features make mlops very similar to devops. when mlops practices are exercised by the teams that work in the development of ml algorithms, as well as the operationalization of these ml algorithms, there must be an emphasis on automation and monitoring that constitute the software steps. in this regard, mlops also provides for greater collaboration and communication between teams to achieve objectives, for example, integration, testing, release, deployment, and infrastructure management. mlops emerges as a concept aimed at transforming ml algorithms into practical products or services, like software when devops is adopted as a development and operationalization approach. 2.4. theoretical use cases theoretical use cases, such as the necessity to estimate the number and precise position of cars in a large car repair workshop, exemplify the development of microservices that utilize image processing techniques, video stream collectors, position classifiers, facility setup estimators, cloud collectors and data storage. another theoretical use case considers the problem of weather prediction using ml, in this hypothetical use case, the necessary steps for using microservices in conjunction with ml algorithms are described, with a more details, offering a technical approach to the application [27]. this theoretical use case potentially correlates with smart cities problems, considering that the weather has an impact, for example, on car traffic in a city. according to the example of the theoretical use case of weather prediction, the following file and directory structure can be created for building the ml algorithm microservices (figure 1). figure 1. example of a repository with files and directories for the api [27] in this same theoretical use case example, the ml algorithm is available as an api (figure 2). figure 2. example of endpoint used to the ml algorithm [27] the presented use cases confirm, in principle, the integrated use of microservices (as an api) with ml algorithms. moreover, the potential application of these use cases within the smart cities context. 3. frameworks for mlops and microservices technology this section presents three frameworks that use microservices to provide ml algorithms as services. the characteristics of the architecture and the technical characteristics of the three frameworks are presented, as well as the respective objectives when used to meet a user's need, facilitating the adoption of the use. in this way, the three have the objective of integrating ml algorithms with microservices, each with their respective specificities. 3.1. machine learning as a reusable microservice (mlrm) ref. [28] proposes a framework nominated machine learning as a reusable microservice (mlrm) where one of the objectives is to encapsulate ml algorithms using eai endorsed transactions on smart cities | volume 7 | issue 3 | mlops and microservices frameworks in the perspective of smart cities 5 microservices. mlrm allows the separation of ml algorithm from the configurations, as well as allow a simple extension with several other algorithms, with communication performed by service modules using representational state transfer (rest). mlrm also facilitates data analysis, allowing the reuse and sharing of executables and configurations. the possibility of reusing and sharing executable files and configurations is a feature related to the quality attributes of microservices, and one advantage proposed by this framework in this regard is the ability of reuse and share. initially, mlrm is not built to be used in cloud-based environments. one of the goals of the framework refers to the use of customization for different software, just by changing the configuration parameters. this customization is conceptually like the reuse in microservices, since the configurations can be applied agnostically to the software that use the services, just by changing the configurations. the modules of mlrm framework are highlighted and described as follows: (i) ml service: module with the implementation of ml algorithms. ml microservices in executable files can be used by multiple microservices and customized via configuration. (ii) configuration set: module that contains the configurations that customize the microservices. software professionals can customize the algorithm just by changing the configuration parameters. (iii) set of microservices: represent the customizable microservices through configurations. having the configurations available, the microservices can easily invoke the ml services from an existing configuration, making available and sharing the configurations among the microservices. (iv) training service: based on the service-oriented approach, there is a dedicated service for training the ml algorithms offered by the ml service. (v) training data: the training data that is delivered to the training service. for mlrm, the training service (module 4) implements the functions to train the algorithms offered by the ml service (module 1). the training data (module 5) is sent to the training service (module 4) from the microservices (module 5). next, the training service (module 4) sends the trained data to the ml service (module 1). this evaluates the output of the ml microservice and updates the configuration parameters in ml settings (module 2). mlrm presents a way to build encapsulated ml microservices that offer configuration flexibility through parameterizations. according to [28], when providing ml microservices outside the cloud, a great advantage, in addition to the requirements of reducing latency and connectivity and greater bandwidth, is data privacy, since cloud-based approaches require data to be uploaded to cloud providers, which may conflict with privacy requirements. 3.2. minerva minerva is another proposed framework proposed by [29] with the aim of integrating ml algorithms with microservices. it is a specific framework for companies that use saas. ref. [29] points out that for the development of ml algorithms there are some programming languages that can be used, for example, r language and python. these languages use several libraries characterized by being open source. in software development, ml algorithms developed are different when compared to traditional software in saas environments. minerva framework aims to propose the implementation of microservices considering ml algorithms in a saas environment. this proposal is used in corporate domains and some technical requirements become relevant for the implementation of ml algorithms in saas environments: • there is a need to reuse subsystems that use ml algorithms in order to serve a variety of possible services; • there is a need for data governance, emphasizing that the governance of these data is decentralized. also, the existence of a preprocessor to contribute with the engineering of features that are necessary for ml algorithms; • there is a need to guarantee some characteristics, such as scalability. this scalability must be horizontal, that is, with the ability to add more machines. vertical scalability, on the other hand, aims to add components such as processors and memories; • there is a need to ensure real-time or online performance for forecasts. this performance provides serving the results in the systems; • there is a need for training to be carried out offline, and it is also necessary for these training to be in batches; • there is a need to protect and exchange data, these data being generally confidential. data exchange takes place between a resource processing system and a system in charge of processing ml algorithms; • there is a need to build microservices to support ml algorithms by configuring different libraries. this construction of microservices with a variety of different libraries must be technology independent of the systems, where these systems are known as legacy systems. in addition to technical requirements, [29] also highlights some business domain requirements for innovative solutions other than typical ml solutions in a cloud environment: • there is a need to realize smart service delivery. these intelligent services are provided for a variety of traditional saas applications. such services are made available with the characteristic of being lightweight, reducing the impact on related systems or infrastructures; eai endorsed transactions on smart cities | volume 7 | issue 3 | i. b. urias and r. rossi 6 • there is a need for ml algorithms to be executed “next to the data,” which contradicts the idea of having to “move the data to the algorithm.” this condition is evident, since for some states or countries there are legal rules that may eventually make the task of migrating data to an external environment outside the datacentres difficult; • there is a need for ml solutions classified as “interim.” the concept of “interim” solutions arises from the fact that such solutions are compatible with so-called traditional saas systems, but which, in turn, are used for a defined period, due to difficulties such as delays or obstacles in the adoption of emerging technologies. or modern, like cloud-computing (cloud computing). in the framework construction, [29] proposes a set of microservices described as ml-oriented subsystems. this set of microservices responsible for making ml algorithms available as services represents the minerva framework. this framework integrates the traditional saas ecosystem. regarding the subsystems, it is possible to highlight the user interface (ui), database (db), the core subsystem, the platform, among other subsystems, where all belong to the datacentre. minerva framework has another relevant characteristic: the transactional solution useful for companies that are in the process of migrating from an on-premises environment to a cloud environment. for minerva, ml microservices are a docker container, where this container has three layers, as highlighted below: • central layer: responsible for interaction and communication with other systems, as well as managing processes that are contained in a container. other features such as concurrency control and security mechanisms and settings also belong to the central layer; • abstraction layer: the abstraction layer belonging to the minerva framework is responsible for carrying out the dynamic load of the ml algorithms, as well as dealing with versioning, exception management and call control of functions known as callbacks; • application layer: the application layer belonging to the minerva framework aims to deal with abstractions and support the coding of ml algorithms using specific libraries for the context of developing ml algorithms. ref. [29] highlights that minerva interacts with legacy subsystems. such interaction occurs, for example, with the ui or the main subsystem, responsible for making predictions or classifications in ml. in this framework, requests for training can be orchestrated as soon as there is data prepared through the data processing unit (data preprocessing subsystem). ref. [29] describes that the orchestration subsystem may belong to the set of other subsystems called inherited subsystems. however, the orchestration subsystem can also be used in an external environment, that is, outside the set of subsystems, if there is a need to use it this way. the data used and processed by the ml algorithms are extracted, performing a pre-processing in the unit responsible for data processing. in conclusion, minerva is a framework that integrates ml with microservices, dedicated to saas environments, with a focus on legacy systems. one of the main goals is to encapsulate the ml algorithms and provide flexibility for using different ml libraries. this flexibility is related to the concept of bring your own model or algorithm (byomoa). the byomoa concept allows, for example, flexibility and ease in choosing the use of libraries that will be used for the ml algorithms. also noteworthy is the development of ml algorithms, which have an abstract interface to perform predictions and training using microservices. 3.3. machine learning in microservices architecture (mlma) machine learning in microservices architecture (mlma) is a framework whose objective is to promote some specific design patterns for building microservices with unique responsibilities, that is, segregated from a monolithic architecture [30]. specifically, this framework demonstrates two use cases designed for smart cities: tourism recommendation based on social media photos, which aims to identify the types of environments where the photos were taken and build a preference profile using algorithms in the recommendation system. predictive policing, which aims to make spatial predictions related to criminal incidence values for a future time interval [30]. quantitative runtime data were collected in the tourism recommendation based on social media photos use case (table 1), comparing the execution time in a monolithic architecture and mlma. table 1. processing times for recommendation application [30] mlma is a generic architectural proposal. this architecture enables the implementation of pipelines for ml algorithms, where the framework has the separation of common steps in order to build more adequate services. ref. [30] points out that microservices bring benefits to the maintenance and performance of the framework, where the design makes it possible to work with codes in pipelines of ml algorithms, as well as being an approach that uses microservices. the framework also enjoys other benefits such as, for example, the independence between each of the microservices and, consequently, favouring reuse for a set of different tasks that are present within a specific workflow. eai endorsed transactions on smart cities | volume 7 | issue 3 | mlops and microservices frameworks in the perspective of smart cities 7 one of the primary advantages or benefits that has been suggested is the capacity to migrate from a monolithic architecture to an architecture based on microservices, enabling the utilization of ml algorithms in a reusable manner across various tasks within the same workflow. [30] detail the components of mlma as follows: (i) flow controller service and post processing service: generates the information that comes from the result of data classification processing. if the flow controller service is not applied, the steps related to communication can be performed directly between the client and the data collection service. (ii) data collector service: performs the extraction of information, data, and content from a specific source to make available for a later stage of analysis. this service does not perform any type of analysis or application of data analysis techniques. the service supports both structured and unstructured data; (iii) data orchestrator service: presents intermediary responsibilities between three different services. this service communicates with the data collection, feature extraction, and classification and prediction services through an orchestration. after obtaining the data, they are sent through a structure that makes the data available for use. features are extracted and processed in order to be used by other services, with a diversity of structures and categories of possible classifiers. once the preparation process is complete, the data is sent to the new data structure through a data analysis service and, at the end, the results of the previously performed processing are received. (iv) data handler service: in some circumstances, it is necessary to pre-process the data before extracting the features. this service handles and processes data, where some information is not necessarily extracted from the data. on the other hand, a filter is performed on the data and, therefore, it can generate some complexities for the classification, or the service can perform some modification to adapt the data considering some pattern. (v) features service: extracts feature that are used by ml algorithms from the generic architecture. in this service are located the raw or pre-processed data that are later used in classification or prediction. the concept of feature extraction considers the action of obtaining information or performing a data processing step to provide learning in a simplified way through ml algorithms and training techniques. the mlma framework is characterized by using microservices in its approach and separating the responsibilities of extracting features from classification or prediction. (vi) predict/classification service: responsible for generating the most significant and important information for the user. the result is a classification or prediction, as well as any other possible process that uses other ml algorithms, these ml algorithms being implementable in this service. unlike other proposals, where the classifier or predictor structures are kept together, the generic architecture has the difference by separating the data and the classifier structure from the classification algorithms, providing reuse, and avoiding duplication or redundancy. the result is the respective classifications or predictions, when using such ml algorithms. (vii) volume: is where the data is stored. the volume also stores the files of the ml algorithms that can be used. these files are handled by the classification and prediction service. data can be stored in files or in a database. the generic architecture makes decisionmaking more flexible regarding the use of files or databases, varying according to the user's needs. the mlma framework contains a specific component where ml algorithms and data are stored. in this way, the services of this architecture can use such data and ml algorithms according to the need of the problem. this generic architecture for ml pipelines can be useful for problems involving reuse and for using ml algorithms as services. 4. results & discussion this section presents the results of the analysis of the three frameworks presented in section iii. the proposed frameworks are analysed with a focus on the operationalization of ml algorithms. the described frameworks use microservices to build ml algorithms as services, but the mlops approach is not explicit in all of them. however, mlops as an organizational approach is important for these frameworks. mlops is the main approach for the operationalization of ml algorithms, even if the concept of mlops is still abstract and does not have enough maturity. the purpose of this analysis is not to delve into technical issues of implementation, integration, or implantation, but to present a qualitative view of the frameworks. even though certain concepts remain abstract regarding the integration of microservices with mlops, in the integration proposal, part of benefits derives from the contribution of mlops [10]. • easy implementation of high-precision ml algorithms; • reduction in data collection and preparation time; • delivering of value to customers; • ml algorithm deployment on a large scale; • efficient management of the full ml lifecycle. table 2 presents the three frameworks described in section iii that are evaluated, and analysed in more details in this section. eai endorsed transactions on smart cities | volume 7 | issue 3 | i. b. urias and r. rossi 8 table 2. frameworks and its proposals framework description of proposals machine learning as a reusable microservice (mlrm) [28] • separate the ml algorithm implementation from the configurations; • improve ml-based data analysis and enable reuse and sharing of ml algorithms and configurations; • encapsulate ml algorithms as rest services with a unified interface that can be used without the resources of the cloud; • customizing services by-configurationonly useful for beginners or novices in using ml; • reduce network latency when compared to services offered in cloud environments. minerva [29] • modularize and deploy microservices in saas environments, especially in the corporate domain; • deploy ml microservices in software; • accelerate the delivery of ml algorithms in software; • separating the traditional saas application from the ml microservices using rest for communication. machine learning in microservices architecture (mlma) [30] • development of a generic architecture for providing ml services; • migrate monolithic ml architectures to ml microservices with separate responsibilities; • separate steps of similar processes into small services; • provide classification and prediction results; • communicate the different services of the generic ml architecture through rest communication; • separation of feature processing services in relation to classification and prediction. the proposal of the machine learning as a reusable microservice (mlrm) framework, described by [28], presents a relevant characteristic, the construction of the framework without the need for cloud-based resources, that is, the proposal is suitable to be built for example, locally. mlrm not depending on a cloud environment, allows some degrees of customization freedom, something that is not necessarily possible with cloud-native approaches. mlrm also proposes a modularization for better performance in the implementation of ml algorithms as services when compared to other services offered by companies. this performance arises from the fact that, as it is a framework that is independent of a cloud environment, it means a possible reduction in network problems such as latency and connectivity. mlrm is still in the vision of being independent of a cloud environment, favours the issue of data security and privacy, in a way that prevents external information traffic to cloud services. potentially, some applications for smart cities can utilize the features of this framework when there is a need for privacy and high performance, such as in the public healthcare sector, like the allocation of emergency resources, where patient data is required, as well as real-time responses using the public healthcare services infrastructure. the second framework presented, entitled minerva and proposed by [29], aims to implement ml microservices in saas environments, often these environments are typically legacy, or even called traditional, as described by the author. minerva is a framework proposed specifically for companies, in this way, it starts from the premise that companies seek, given their business domain and the use of saas environments, to offer software as a service, where microservices can be suitable for this objective, given the quality attributes. minerva has an architecture where the traditional saas layer and the microservices layer are defined, the latter being responsible for making ml algorithms available as services. it is a proposal that requires little adaptation between the saas environment and the ml microservices, given that communication can be carried out through rest-type communication, as presented in the framework. the features of this framework can be used in the context of smart cities when there is a need to perform an intermediate migration from a monolithic architecture to a cloud-based architecture, being efficient during this transitional phase. potentially, minerva can be useful for companies offering software as a service and looking to avoid a major change in the company's existing environment, avoiding major code changes. another feature of minerva is that it can be used in cloud environments. minerva seeks to meet a need of the software industry and companies that carry out activities in the ml context, which is to adapt a traditional saas environment to be integrated with ml microservices modules. another feature is the presence of logs used to support monitoring and operations, with the sharing of these logs. this becomes interesting in terms of traceability and monitoring of the framework, as well as bringing insights regarding the available logs. the third framework, entitled machine learning in microservices architecture (mlma) and proposed by [30], presents a generic architecture for implementing ml algorithms. specifically, this architecture details with greater granularity the necessary services as well as the operation of the pipeline present in the framework. mlma is proposed for classification and prediction problems and offers a generic architecture for ml pipelines in microservices, reinforces the concept that the topology of the architecture is preserved regardless of the classification problem and prediction of interest by the user. mlma is also characterized, like other services, by modelling its architecture in order to segregate responsibilities. mlma explicitly separates the feature processing step from the processing of classification and prediction ml algorithms. this conceptually corroborates the idea of microservices applied in the context of ml, because the concept of topology, in the context of the framework, reinforces that there is flexibility to adapt the architecture according to the problem to be solved using ml. eai endorsed transactions on smart cities | volume 7 | issue 3 | mlops and microservices frameworks in the perspective of smart cities 9 the presented frameworks focus on a common objective, which is to provide the results of ml algorithms as services, that is, the construction of ml services, specifically using microservices to achieve the goal. however, each of the presented frameworks contains their respective specificities. it is possible to consider, for example, the applicability and intended audience. it is argued in favour of this statement, when analysing the minerva framework, which, unlike other frameworks, is directed to a specific public, where the public is companies that use saas environments and aims to integrate these traditional saas environments with the microservices of ml. the analysed frameworks do not necessarily need a cloud environment to be used. the benefits obtained correspond to better data control and greater guarantee of customization with a greater degree of freedom, since they do not depend on an infrastructure and external services offered by a cloud environment. however, not all frameworks are necessarily used exclusively without a cloud environment, such as the minerva framework, which in its proposal also seeks to offer connectivity to cloud environments. microservices are suitable for environments that use a cloud-native approach, so their use in such an environment brings benefits such as, for example, better management and orchestration of services, scalability and elasticity, automation of deployments and deliveries. it can become very difficult to manage microservices outside a cloud environment, since potentially all issues of support, maintenance and management of the infrastructure are, for example, the responsibility of the company, and the cloud environment could contribute to these issues of infrastructure, architecture and platforms used, taking responsibility for them. other beneficial points can be found in the frameworks: processing a large volume of data. generally, it is more advantageous to process a large volume of data without using a cloud environment, as it ensures better performance in terms of network latency and data traffic. this local processing is suitable for a large volume of data, avoiding network traffic when compared to a cloud environment. however, this same benefit can generate some challenges, such as, how scalable is the local infrastructure for using the frameworks? that is, what is the machine resource limit that the infrastructure must be able to handle the processing that use large volume of data? this problem is reduced in a cloud environment, given that many services offer scalability and elasticity, that is, they grow or shrink organically according to the need for use. therefore, they become a favourable point for the use of cloud-integrated frameworks, as well as a possible cost reduction in maintaining the cloud environment when compared to the use of local infrastructures. another point to highlight, regarding the minerva framework, is the abstraction of ml algorithms, known as black boxes. regarding this abstraction, it is possible to consider how advantageous it is to have the models abstracted for the users of the frameworks. this point, in fact, leads to the question that users of a framework do not necessarily need to have specific knowledge about ml. this, in fact, can become a problem, given that users who are using frameworks with ml algorithms available as services do not necessarily need to have knowledge or experience in ml, being just an operational user of the service. here, it becomes relevant to question the threshold of knowledge that a user of this type of framework needs to perform their duties as a professional in this area. according to the analysis carried out on the frameworks, it appears that they seek to automate the ml algorithms and make them available as microservices, either in a local environment or in a cloud environment. the automation of ml algorithms does not necessarily mean using the mlops approach. this is an important point to be highlighted, given that, in the analysed frameworks, the observed maturity level converges towards the objective of automating ml algorithms and not explicitly applying mlops practices. this fact makes it possible to conclude that there are still conceptual obstacles to effectively mlops becoming an effective approach for real and practical use of ml algorithms made available in microservices. however, such frameworks, eventually, may suggest new practical studies that allow the use of mlops practices, given that they are initial proposals and studies related to the subject can still be investigated. table 3 presents a qualitative analysis based on the analysed frameworks. six evaluative criteria are used in relation to their characteristics. the square (green colour) represents that the framework fully attends the criteria, triangle (yellow colour) represents partial attendship, and the circle (red colour) represents that the framework do not attend the criteria. table 3. qualitative analysis of frameworks • problem generalization: quantity and variety of different ml problems that the framework proposes to be used; • different programming languages: number of programming languages supported by the framework; • resource sharing: flexibility that the framework has in providing modules, resources, and components; • user coverage: audience that the framework proposes to serve. more specific or more generic; • quantitative results: results from using and experimenting with the framework are available; • suitable for cloud utilization: the framework can be used, in addition to the local environment, in a cloud environment. eai endorsed transactions on smart cities | volume 7 | issue 3 | i. b. urias and r. rossi 10 for example, the minerva framework stands out in terms of a specific audience that proposes to provide a degree of sharing and meets part of the evaluated criteria. however, this evaluation does not define which is the best framework, given that the use of the framework depends on the context of use, the need, and the problem to be solved, where a set of factors allows those involved to decide which is the best framework to be used. effectively in the short or long term, the analyzed frameworks favor mlops practices since they correspond to approaches that can guarantee the operationalization of ml algorithms as services, taking advantage of the previously presented benefits. considering the characteristics previously presented of the frameworks, potentially these frameworks can be applied to different problems and use cases of smart cities, such as, for example: intelligent traffic management, smart parking, public security services, energy efficiency, smart tourism, public health services and other possibilities. 5. conclusion the research aimed to address questions regarding the integration of mlops with microservices to provide ml services. the main analysis is conducted based on the frameworks proposing this integration. regarding the frameworks, it is important to highlight that they do not explicitly address the integration of mlops with microservices. this statement is mainly corroborated due to two reasons. the first reason is that the frameworks aim to automate ml services using microservices, not to directly integrate with mlops. the second reason is the fact that mlops is not explicitly conceptualized, and therefore, there is no conclusive and consensus concept. there is a degree of freedom for different interpretations about mlops. the benefits as well as the challenges are rather abstract when it comes to integrating mlops with microservices. certain challenges arise from the inherent difficulty in conceptualizing, such as defining the role and responsibilities of a professional tasked with operationalizing an ml algorithm. this can lead to a misconception that the professional's goal is merely the deployment or utilization of ml algorithms without possessing a deep understanding of their workings. consequently, they become professionals responsible for operationalizing or deploying ml algorithms to provide services and consume results without essential comprehension of the algorithms and the related concepts and technologies. with the objective of addressing the issues related to the integration of mlops with microservices, it is concluded that there are several gaps and challenges that need to be resolved, particularly concerning the conceptualization of terms and a practical study of integrating mlops with microservices. there is potential for advancements in this area, leading to an evolution of frameworks that automate ml algorithms using microservices, making them more sophisticated and encompassing both technical and organizational aspects, ultimately enabling integration with mlops. the frameworks highlighted in this article could be potential candidates for deployment and integrated use with mlops, providing an opportunity to aggregate knowledge on the subject, enhance existing frameworks, and develop new proposals adopting mlops. it was also presented that there is a potential synergy between the concepts related to smart cities context. the use case examples presented also provide inputs to be used in frameworks that integrate microservices with ml algorithms. the studies on mlops integration with microservices can be extensive in the future, offering substantial potential to overcome barriers and meet technological needs. references [1] el naqa, i., murphy, m. j. what is machine learning? in: machine learning in radiation oncology. springer international publishing. 2015. 3-11. 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[14] hassan, s., bahsoon, r. microservices and their design trade-offs: a self-adaptive roadmap. in: 2016 ieee eai endorsed transactions on smart cities | volume 7 | issue 3 | https://doi.org/10.1109/iccubea.2018.8697857 http://dx.doi.org/10.4108/eetsc.v6i4.2796 https://doi.org/10.1109/mcc.2016.101 https://doi.org/10.1109/ms.2018.2141030 https://doi.org/10.1109/ccwc54503.2022.9720902 https://doi.org/10.1109/ms.2015.11 https://doi.org/10.1109/issrew.2019.00050 mlops and microservices frameworks in the perspective of smart cities 11 international conference on services computing (scc). ieee. 2016. 813-818. doi: 10.1109/scc.2016.113. [15] jamshidi, p. et al. microservices: the journey so far and challenges ahead. ieee software. 2018; 35(3): 24-35. doi: 10.1109/ms.2018.2141039. [16] bass, l., clements, p., kazman, r. software architecture in practice. boston: addison-wesley professional publishing, 2003. [17] wang, h., ma, c., zhou, l. a brief review of machine learning and its application. in: 2009 international conference on information engineering and computer science. ieee. 2009. 1-4. doi: 10.1109/iciecs.2009.5362936. [18] prudius, a. a., karpunin, a. a., vlasov, a. i. analysis of machine learning methods to improve efficiency of big data processing in industry 4.0. journal of physics: conference series. 2019; 1333(3):1-6. doi: 10.1088/17426596/1333/3/032065. [19] ayodele, t. o. types of machine learning algorithms. new advances in machine learning. 2010; 3(1):19-48. [20] mohri, m., rostamizadeh, a., talwalkar, a. foundations of machine learning. mit press, 2018. [21] leite, l. et al. a survey of devops concepts and challenges. acm computing surveys (csur). 2019; 52(6): 1-35. [22] wang, r. y., kon, h. b., madnick, s. e. data quality requirements analysis and modeling. in: proceedings of ieee 9th international conference on data engineering. ieee. 1993. 670-677. doi: 10.1109/icde.1993.344012. [23] dyck, a., penners, r., lichter, h. towards definitions for release engineering and devops. in: 2015 ieee/acm 3rd international workshop on release engineering. ieee. 2015. 3-3. doi: 10.1109/releng.2015.10. [24] garg, s. et al. on continuous integration/continuous delivery for automated deployment of machine learning models using mlops. in: 2021 ieee fourth international conference on artificial intelligence and knowledge engineering (aike). ieee. 2021. 25-28. doi: 10.1109/aike52691.2021.00010. [25] mei, s. et al. model provenance management in mlops pipeline. in: 2022 the 8th international conference on computing and data engineering. 2022. 45-50. doi: https://doi.org/10.1145/3512850.3512861. [26] liu, y. et al. building a platform for machine learning operations from opensource frameworks. ifacpapersonline. 2020; 53(5): 704-709. doi: https://doi.org/10.1016/j.ifacol.2021.04.161. [27] raj, e. engineering mlops. packt publishing, 2021. [28] pahl, m., loipfinger, m. machine learning as a reusable microservice. in: noms 2018-2018 ieee/ifip network operations and management symposium. ieee. 2018. 1-7. doi: 10.1109/noms.2018.8406165. [29] duvvuri, v. minerva: a portable machine learning microservice framework for traditional enterprise saas applications. arxiv preprint arxiv:2005.00866, 2020. [30] ribeiro, j. l. et al. a microservice based architecture topology for machine learning deployment. in: 2019 ieee international smart cities conference (isc2). ieee. 2019. 426-431. doi: 10.1109/isc246665.2019.9071708. eai endorsed transactions on smart cities | volume 7 | issue 3 | https://doi.org/10.1109/scc.2016.113 https://doi.org/10.1109/ms.2018.2141039 https://doi.org/10.1109/iciecs.2009.5362936 https://doi.org/10.1109/icde.1993.344012 https://doi.org/10.1109/releng.2015.10 https://doi.org/10.1109/aike52691.2021.00010 https://doi.org/10.1145/3512850.3512861 https://doi.org/10.1016/j.ifacol.2021.04.161 https://doi.org/10.1109/noms.2018.8406165 https://doi.org/10.1109/isc246665.2019.9071708 investigation of blockchain for covid-19: a systematic review, applications and possible challenges eai endorsed transactions on smart cities research article 1 investigation of blockchain for covid-19: a systematic review, applications and possible challenges shah hussain badshah1, muhammad imad1, muhammad abul hassan2,*, naimullah1, shabir khan1, farhatullah3, sana ullah4 and syed haider ali5 1department of computing and technology, abasyn university peshawar, onlinesoftteach@gmail.com, imadk28@gmail.com, naimnan.15@gmail.com, mshabirkhan1993@gamil.com 2department of information engineering and computer science, university of trento, italy, muhammadabul.hassan@unitn.it 3school of automation, control sciences and engineering, china university of geosciences, wuhan, 430074, china farhatkhan8398@gmail.com 4department of computer science, qurtuba university of science and technology, peshawar pakistan, sunnykhan3304@gmail.com 5department of electrical engineering, university of engineering and technology peshawar, engrsyedhaiderali@yahoo.com abstract smart city is emerging application in which many internet of things (iot) devices are embedded to perform overall monitoring and perform processing automatically. in smart city the authenticity is key problem and many users in the in smart city has faced challenges during covid-19. the covid-19 epidemic, a deadly virus, first appeared in the globe in 2019. the world health organization (who) states that it is almost certainly feasible to contain this virus in its early phases if some precautions are taken. to contain the infection, most nations declared emergencies both inside and outside their borders and prohibited travel. artificial intelligence and blockchain are being used in smart city applications to monitor the general condition in the nation and reduce the mortality rate. blockchain has also made it possible to safeguard patient medical histories and provide epidemic tracking. ai also offers the ideal, wanted answer for correctly identifying the signs. the primary goal of this study is to fully investigate blockchain technology and artificial intelligence (ai) in relation to covid-19. a case study that was recently developed to identify and networked pathogens acquired important knowledge and data. additionally, ai that can handle massive quantities of medical data and perform difficult jobs will be able to reduce the likelihood of intricacy in data analysis. lastly, we highlight the present difficulties and suggest potential paths for addressing the 19 diseases in future circumstances. keywords: smart city, blockchain, covid-19, virus, artificial intelligence (ai), pandemic, machine learning, deep learning received on 30 november 2022, accepted on 02 march 2023, published on 23 march 2023 copyright © 2023 shah hussain badshah et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v7i1.2827 1. introduction today, security is more important than ever, as numerous organizations, both private and public, have experienced costly losses and reputational damage because of hacking and other forms of cybercrime especially in smart city [1]. the adoption of blockchain technology has made it much simpler and faster to implement security patches and other updates to websites, social media platforms, and other types of online infrastructure. as a result of covid-19 in smart city application, more people than ever before are communicating with their loved ones via social networking sites, but it is incredibly difficult to stop criminal activity or counteract fake information spread via the web. blockchain technology is used by public and commercial (hired) agencies to address the problems of plagiarism and other forms of fake material on these sites. the european centre for disease prevention and control estimates that 10 million people are affected with this virus every year [220], making prevention efforts difficult due to a lack of eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e5 mailto:onlinesoftteach@gmail.com mailto:imadk28@gmail.com mailto:mshabirkhan1993@gamil.com mailto:farhatkhan8398@gmail.com mailto:engrsyedhaiderali@yahoo.com https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ a shah hussain badshah, et al. 2 available tools like immunizations and a covid-19 protection package [21-30]. numerous studies demonstrated that x-rays are crucial in the initial phases of diagnosis of the virus. as a result of the prevalence of online transmission of medical records, it is crucial that this sensitive information be safeguarded to prevent the spread of inaccurate data [31-35]. machine learning and deep learning are two approaches being used to combat the spread of misinformation online, especially in the smart city. distributed ledger technology, or blockchain for short, keeps records in several separate systems and links them together in a decentralized, peer-to-peer network. blockchain transactions are protected by a cryptographically strong mechanism, such as a digital signature, for example. in the last few years, the covid19 epidemic has affected the health and lives of people all over the world [36]. the pandemic has expanded to around 150 nations. the european centre for disease prevention and control estimates that up to 10 million individuals are infected due to the virus's ease of spread, lack of effective immunizations, and the unreliability of commercially available covid-19 test tools [3]. new studies have demonstrated the importance of diagnostic tests like x-rays in the diagnosis of coronavirus illness. also, academics have prohibited unorganized information from social networks and stressed using blockchain technology to defend against and identify fake news and hoaxes [37]. researchers and medical specialists from all over the world are scrambling to find a new tool to combat the covid-19 pandemic. unverified claims in the media and hearsay can be exposed with the help of machine learning and deep learning techniques. bitcoin technology expedites the transfer of data used to monitor physical possessions. four primary levels are built into the blockchain architecture to ensure that anomalous spread is being stopped. all incoming communications on the web are constantly monitored by the four levels (computer, network, blockchain, and device) [38]. the speculative meaning becomes clear and will play an important role in the future of the digital world if one considers blockchain technology, which is presently required for cryptocurrencies. it is imperative that this technology continues to advance and become more user-friendly so that it can be used to solve future security problems in a wide variety of industries and institutions. in order to anticipate the results of the covid19 test and identify the patients who will be negatively impacted by the discrimination, machine learning categorization methods are indispensable [39]. in the article [40], the authors examine the categorization of the covid-19 dataset and point out where various classifiers perform poorly on the corona dataset. the chosen classification algorithms will be use, and their classification performance will be measured across a number of metrics including accuracy, sensitivity, falsepositive rate, and f-measures. to get the best outcomes possible from machine learning methods, we compare the efficiency of various categorization classifiers on the coronavirus dataset [41]. as a result of their difficulties, chinese scientists have had to delve deeply into the virus to determine the best way to deal with the coronavirus enigma. tests of different techniques for classifying models yield information about their predictive success [42], but these tests can lead to model confusion. to ensure that ct scan picture quality is detected at an early stage, the model is being optimized using deep learning. it appears that illnesses all over the world, such as aids, tb, hepatitis, and measles, will be severely impacted by the covid-19 epidemic, prompting the world health organization to proclaim an emergency. the world health organization (who) and other study institutions face an enormous workload, which could be greatly alleviated with the aid of machine learning algorithms. 1.1 symptoms the documented signs of covid-19 are diverse. some people may experience symptoms as soon as 14 days after contracting a virus. figure 1: covid-19 symptoms and indications, including temperature, congestion, shortness of breath, exhaustion, loss of flavour or scent, headache or bodily pain, trouble breathing, vertigo, and diarrhea [43]. there is a higher chance of more severe consequences from covid-19 infection in older individuals who already have pre-existing medical problems, such as heart disease, pulmonary disease, diabetes, or persistent illnesses. acute renal damage, organ failure, cardiac problems, and bacterial infection are all potential complications that can result in mortality. figure 1. covid-19 symptoms, preventive measures, its global impact, and mitigation efforts. 1.2 preventive measures preventive measure is important to stop the spreading of the virus and reduce the risk of countering. currently, preventive measures are washing hands with soap for 20 seconds, keeping a social distance in a crowded place of at least 2 meters, wearing a surgical mask, and avoiding touching your face, nose, and eyes. another preventive measure is cleaning the house regularly, staying home and not going outside unnecessarily, covering coughs and sneezing, and monitoring health issues. eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e5 investigation of blockchain for covid-19: a systematic review, applications and possible challenges 3 1.3 global impact in addition to having an impact on human existence, covid-19 also has an impact on the world economy. many nations have issued stringent lockdowns and advised citizens to remain at home, but as a result, covid-19 regulations have shut down workplaces, marketplaces, and other businesses. the covid-19 shutdown had a major effect on business and the world economy [13], as well as public transportation, building, tourists, supply chain disruption, unemployment, and food shortages. 1.4 mitigation efforts the government and organizations have implemented relief strategies in addition to protective ones to halt the infections. many apps have been created in different nations to increase the effectiveness of the viral detection procedure and track the covid-19 patients by using a phone app to track and identify the virus. these apps made use of bluetooth or the internet to keep the patient's data in protected form, allowing the medical officials to quickly get in touch with each one of them separately. in addition to alerting users when an infectious individual is nearby, these apps also inform users of health problems [14]. section 1 of the literature survey discusses the contrast of linked papers. the following is the paper's primary contribution: • the poll included a thorough analysis of blockchain technology's ability to combat the covid-19 outbreak and discover cures for these diseases. • this essay compares various bitcoin research studies and emphasizes their models, goals, contributions, and flaws. • the covid-19 epidemic was noted in this survey's potential research obstacles and future directions for blockchain technology by study experts and users. the following is how the document is set up: a overview of the blockchain literature is presented in section 2. the role of blockchain technology in the fight against the covid-19 epidemic was covered in section 3. the blockchain's materials and techniques will be covered in section 4. in the framework of covid-19, section 5 addressed the blockchain technology issues and future plans. the end is presented in section 6 to finish. 2. literature review to improve the effectiveness of blockchain methods created for the retrieval and storage of jointly managed data, yuting wu et al. conducted research. additionally, the system guards against data manipulation when various businesses and groups' data is processed. reducing irrelated data by proofing the supply chain [15]. researchers radhya sahal and saeed h. alsamhi concentrated on the use of blockchain technology for the covid-19 pandemic warning use case, which used collaboratively built digital clones for a decentralized smart pandemic. the internet of things (iot) and artificial intelligence (ai) transformation are being greatly aided by the new technologies of blockchain, especially in the healthcare industry. data exchanged between medical cyber-physical systems and safe real-time data processing for the covid19 epidemic [16]. figure 1 compares various study projects pertaining to bitcoin and covid-19. table 1. comparison of our survey paper with existing works. ref algorithm / models applied purpose contribution weakne ss limitatio n [15] rf, knn, adaboost, gbdt algorithm, xgboost, rf, lr, classification, confusion matrix, data tamper proofing mechanism improved previous techniques security loopholes still exist [16] practical byzantine fault tolerance (pbft) algorithm, blockchain framework, decision tree data security, data integrity, real-time data analytics, predictions, data sharing, data splitting, model evaluation to increase speed, the architecture dispersed warning use case. numerous smart gadgets with numerous communic ation issues technolog y beyond the fifth generatio n (b5g) or sixth generatio n (6g). [17] rf, mlr, rn, nbg, svm, nb, c5 bcn, bch, slr, tzs, xrp, eos, cdo to improve precision, eliminate any background data. improper handling of a large collection [18] ddn neural network, fed, blockchain ehrs, sqlite, api, feature extracted more work is required to manage large data and increase precision. the algorithm could be improved to face unimporta nt characteris tics. [19] ai, machine learning techniques utilization ai and blockchain technology used for the covid-19 pandemic. survey type the security problems with blockchain technology still need to be monitored. eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e5 a shah hussain badshah, et al. 4 [20] ml, ai, supervised, unsupervised and reinforcement. linear regression visualization, analyze parallel analysis of tools and programs small collections of training data [21] federated learning, data abstraction classification, peer-to-peer network blockchain technology, simulation, improved tiny nodes are required problems arise with large storge files. [22] artificial intelligence models; machine learning, federated learning analysis, detection, researchers are still trying to make the systems more responsive. internet access is not widely accessible . how to gather statistics on the impacted covid-19 patients. [23] blockchain technology with federated learning, deep learning, data normalization, routing algorithm, vgg, resnet, mobilenet, densenet segmentation, detection, classification improve using the structure of modern ct scans lack of a suitable sample for training data [24] ai, ml models, data mining methods, blockchain approaches swot analysis, analysis, boost protocol effectiveness for a specific risk management security. high operating costs, the potential for splits, a dearth of freedom, and the requireme nt for more data storing capacity on local computers . [25] ml, dl, blockchain, ai, robotics, big data detection, segmentation, classification, radiography and computed tomography (cmt) model should also employ other ideal methods. additional need to manage huge informatio n [26] machine learning algorithms, flexibility and scalability determine the success of the program. the system's major flaw is that it depends on users having and using smartphon es. 3. blockchain technology in smart city application against covid-19 pandemic the covid-19 pandemic may push the medical system to its breaking point and prevent the development of effective treatments. an accurate data supervision system that would instantly be compatible with medical treatment systems instruction that demands potential outbreaks is being reduced in the movement. the current covid-19 data, however, comes from disparate sources like clinical labs, hospitals, and the public and contains large amounts of data for evaluation without being thoroughly coordinated. it contains careless information because it complicates attempts to determine potential outbreaks and covid-19 quarantines. contrarily, a limitation is a time-consuming covid-19 data recognition method that typically requires a few hours to finish testing for viruses to improve precision. the challenge is how to accelerate a covid-19 identification while maintaining high precision. like how it is difficult to manipulate covid-19 data, which has intricate arrangements and large volumes, using human-dependent medical tools [27]. figure 2 displays the information about applications for blockchain and ai technology. figure 2. blockchain applications in fighting covid19. eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e5 investigation of blockchain for covid-19: a systematic review, applications and possible challenges 5 3.1 patients information sharing to study covid-19 and determine the illness and viral signs, it is crucial to exchange patient data with medical research facilities both domestically and globally. blood records and prescription information are acceptable if the private of the patients' data is protected and no violations of national and foreign data exchange regulations are made. different iot devices and blockchain technology can be used to gather data, making it simpler to share it with various institutions and medical experts. 3.2 tracking infectious disease outbreaks the public health statistics for contagious diseases like covid-19 are processed quickly by blockchain technology, which also provides a more precise summary and adequate reaction. additionally, this will help us keep track of viral activity, early symptom identification, potential new cases, and pandemic levels of transmission. 3.3 securing medical supply chains bitcoin is useful for monitoring and identifying medical supply networks as well as documenting and analysing the demand for logistical materials and supplies. the supply chain includes several parties, including documents of the process and verifying evidence for each party to monitor each step separately. 4. methods and materials to provide a summary of the inquiry into the use of blockchain technology and artificial intelligence in the battle against the coronavirus epidemic, the suggested comprehensive studies emphasized research methodologies and included the following crucial stages. we start by keeping in mind the shortcomings of the current healthcare system and choosing the motivational step for why covid-19 and ai should be used instead. researching all pertinent scientific articles related to the study topic is the second stage. we examine research on the technological applications of blockchain and artificial intelligence in supporting initiatives to prevent the spread of the coronavirus. in this case, we use research threads like machine learning strategies [28][29], blockchain technology, deep learning methods [30], and covid-19 to delve into and prioritize the most acceptable technical papers for our analytical examination. next, we choose the relevant information for the specified queries. we made the decision to highlight peer-reviewed, excellent studies that were given in books, journals, symposiums, seminars, and symposia that dealt with the subject of the study. the third part is all connected articles essential to their titles. we read the main idea out loud, select the main buzzwords, and draw attention to the abstract idea that draws contributions of pertinent data to the paper. then, for the purpose of comparing the studies, we cycled the terms into groups and by sections. the final step is data extraction, which gathers all the information required to examine the technological terminology and blockchain and ai advances in relation to the coronavirus outbreak [31][32]. 4.1 proposed blockchain-ai architecture for coronavirus fighting with the aid of models, covid-19 illnesses can be fought by integrating blockchain and ai technology. stakeholders, blockchain functions, ai classifiers, and constant covid data sources are the four key stages that are outlined below in figure 3 [33]. to create and monitor useful data from the raw data to acquire the information, academics have been using databases from clinical laboratories, social networks, and institutions for experimental observation. each scholar should be familiar with handling data and the methods for gathering information. additionally, coronavirus statistics include radiography pictures and x-rays of historically infected impacted regions to gather the information from various websites, clinical laboratories, social media, publications, government accounts, the world health organization, and other resources. the chinese government alleges that we are currently creating a sizable database system to keep daily patient data and quickly assess contaminated cases in each region of information or data gathered by the national health commission with recommended time severe [34]. the national directory is presently linked to the society living in the digital age. websites keep and disseminate data about ct scans and xray pictures [35]. if you pay attention, you will notice that the government offers data centres for academics who need to conduct additional research and determine the best trial given the present scenario of a disease epidemic expanding rapidly. because it involves identifying the important data from the provided information, covid data analysis is not a simple job. blockchain, on the other hand, can analyse 19 connection services, such as recording donations, analysing outbreaks, and safeguarding the daily medical supply chain. the blockchain-based security data is evaluated using insightful ai-based findings. large amounts of data can be gathered from covid-19 sources to forecast the best answer and perform precise analysis. five key uses of ai, including epidemic covid-19 detection, vaccine development, projection, coronavirus analytics, and forecast of any future covid-like outbreak, can highlight assistance for covid-19 combat. 4.2 combining blockchain and ai for combating covid-19 in the movement, blockchain technology and artificial intelligence can be combined to create potential future treatments for the epidemic. for instance, experts laboured eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e5 a shah hussain badshah, et al. 6 to determine the best answer and forecast coronavirus development [36]. to protect public life, the government released directions urging citizens to maintain a safe distance and abide by the law. deep learning design can estimate the model's performance criteria based on the patient's description, medical history, and current therapies. to categorize the data and produce correct findings, data is generating crucial guidelines. ai algorithms would assist government officials in building a gadget to educate the public about quarantine and social segregation practices regarding final choices [37]. figure 3. blockchain and ai for coronavirus fighting in smart city 5. challenges and future directions to combat the covid-19 epidemic, blockchain technology offers a hopeful solution. the poll also notes that when using these methods in the context of the healthcare industry, various obstacles are carefully considered. we also talked about the difficulties and potential paths for this area. bitcoin technology should be thoroughly examined in the healthcare industry and disseminated in accordance with legal and governmental requirements. concerns with copyright violation and slander as well as legal issues related to content and personal information can determine what laws apply to blockchain operations. the monitoring application for covid-19 is typically used to monitor and halt the spread of the epidemic, but because user privacy is so crucial, particularly when it comes to private data, it must be protected. however, according to new study studies, blockchain technology poses security risks to software used in the medical and healthcare industries [38] [39][40]. the dearth of information about the viral outbreak, such as infectious cases, normal cases, medical supply state, and tools to recognize the virus, presents a difficult job in the covid-19 pandemic. most of the covid-19 data originate from social media, the gathering of medical records, and the tracking of app health; however, the data are insufficient for extensive ai operations. to operate the blockchain software, sophisticated tools and storage were needed. therefore, it is crucial to create hardware to track covid-19 and quickly examine data inside a blockchain network computer. the systems that support blockchain technology should be enhanced and made better to perform well from a variety of technological angles, including speed, delay, resource usage, and pdr. security problems still exist with blockchain. blockchain storage was subject to a 51% assault on block mining and a double spending strike. as a result, data protection through blockchain should be enhanced. blockchain and ai should be merged to create more effective healthcare system technology with improved efficiency and enough machinery to address pandemic problems. 6. conclusions smart city has caught attention from both industry and academia but still some security related issues need to be addressed and moreover the false spreading of information over social media in covid-19 situations are very challenging. the covid-19 epidemic has spread illnesses like aids, tuberculosis, hepatitis, and measles throughout the globe, prompting the world health organization (who) to proclaim a public health emergency. the massive load placed on the who as well as scholars and experts can be lessened with the aid of machine learning algorithms. to recognize and address the covid-19 epidemic, we have provided a summary of blockchain technology utilized in smart city in this research article. we have talked about the crucial role that blockchain technology can play in combating the covid-19 epidemic and outlining difficult future work paths for the preservation of patient privacy. references [1] a. . adamuscin, j. . golej, and m. . panik, “the challenge for the development of smart city concept in bratislava based on examples of smart cities of vienna and amsterdam”, eai endorsed trans smart cities, vol. 1, no. 1, p. e5, jul. 2016. 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[23] e. sfeir, j.-m. rabil, s. obeid, s. hallit, and m.-c. f. khalife, “work fatigue among lebanese physicians and students during the covid-19 pandemic: validation of the 3d-work fatigue inventory (3d-wfi) and correlates,” bmc public health, vol. 22, no. 1, 2022. [24] c. f. tang, a. fakih, and s. abosedra, “the fatality rate of covid-19: how does education, health infrastructure and institutional quality make a change?,” margin: the journal of applied economic research, vol. 16, no. 2, pp. 166–182, 2022. [25] l. cheikh ismail, t. m. osaili, m. n. mohamad, a. al marzouqi, c. habib-mourad, d. o. abu jamous, h. i. ali, h. al sabbah, h. hasan, h. hassan, l. stojanovska, m. hashim, m. alhaway, r. qasrawi, r. r. shaker obaid, r. al daour, s. t. saleh, and a. s. al dhaheri, “assessment of dietary and lifestyle responses after covid-19 vaccine availability in selected arab countries,” frontiers in nutrition, vol. 9, 2022. [26] t. alrubai, a. m. khalil, r. zaki, l. sinno, and s. al tabbah, “the psychological health of patients diagnosed with cancer in iraq during the covid‐19 pandemic: a single center study,” psycho-oncology, vol. 31, no. 4, pp. 649–660, 2021. [27] s. tokajian, g. merhi, c. al khoury, and g. nemer, “interleukin-37: a link between covid-19, diabetes, and the black fungus,” frontiers in microbiology, vol. 12, 2022. [28] m. imad, s. i. ullah, a. salam, w. u. khan, f. ullah, and m. a. hassan, "automatic detection of bullet in human body based on x-ray images using machine learning techniques," international journal of computer science and information security (ijcsis), vol. 18, no. 6, 2020. [29] m. a. ibrahim, k. ibrahim, z. chamseddine, g. sleilaty, and m.-h. gannagé-yared, “covid-19 – impact of the lockdown on the weight variation among the lebanese population,” nutrition clinique et métabolisme, vol. 36, no. 2, pp. 122–128, 2022. 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[33] i. matta, a. s. laganà, e. ghabi, l. bitar, a. ayed, s. petousis, s. g. vitale, and z. sleiman, “covid-19 transmission in surgical smoke during laparoscopy and open eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e5 a shah hussain badshah, et al. 8 surgery: a systematic review,” minimally invasive therapy & allied technologies, vol. 31, no. 5, pp. 690–697, 2021. [34] n. iqbal, e. bouri, o. grebinevych, and d. roubaud, “modelling extreme risk spillovers in the commodity markets around crisis periods including covid19,” annals of operations research, 2022. [35] m. torky and a. e. hassanien, "covid-19 blockchain framework: innovative approach," arxiv preprint arxiv:2004.06081, 2020. [36] a. khurshid, "applying blockchain technology to address the crisis of trust during the covid-19 pandemic", jmir medical informatics, vol. 8, no. 9, p. e20477, 2020. available: 10.2196/20477. [37] m. chang and d. park, "how can blockchain help people in the event of pandemics such as the covid-19?", journal of medical systems, vol. 44, no. 5, 2020. available: 10.1007/s10916-020-01577-8 . [38] a. musamih, r. jayaraman, k. salah, h. hasan, i. yaqoob and y. al-hammadi, "blockchain-based solution for distribution and delivery of covid-19 vaccines", ieee access, vol. 9, pp. 71372-71387, 2021. available: 10.1109/access.2021.3079197. [39] l. yang, j. zhang and x. shi, "can blockchain help food supply chains with platform operations during the covid19 outbreak?", electronic commerce research and applications, vol. 49, p. 101093, 2021. available: 10.1016/j.elerap.2021.101093. [40] m. imad, m. abul hassan, s. hussain bangash and naimullah, "a comparative analysis of intrusion detection in iot network using machine learning", studies in big data, pp. 149-163, 2022. available: 10.1007/978-3-03105752-6_10. [41] m. hassan, s. ali, m. imad and s. bibi, "new advancements in cybersecurity: a comprehensive survey", studies in big data, pp. 3-17, 2022. available: 10.1007/978-3-031-05752-6_1. eai endorsed transactions on smart cities 01 2023 03 2023 | volume 7 | issue 1 | e5 cloud-edge orchestration for smart cities: a review of kubernetes-based orchestration architectures cloud-edge orchestration for smart cities: a review of kubernetes-based orchestration architectures sebastian böhm∗ and guido wirtz distributed systems group, university of bamberg, bamberg, germany abstract edge computing offers computational resources near data-generating devices to enable low-latency access. especially for smart city contexts, edge computing becomes inevitable for providing real-time services, like air quality monitoring systems. kubernetes, a popular container orchestration platform, is often used to efficiently manage containerized applications in smart cities. although it misses essential requirements of edge computing, like network-related metrics for scheduling decisions, it is still considered. this paper analyzes custom cloud-edge architectures implemented with kubernetes. specifically, we analyze how essential requirements of edge orchestration in smart cities are solved. also, shortcomings are identified in these architectures based on the fundamental requirements of edge orchestration. we conduct a literature review to obtain the general requirements of edge computing and edge orchestration for our analysis. we map these requirements to the capabilities of kubernetes-based cloud-edge architectures to assess their level of achievement. issues like using network-related metrics and the missing topology-awareness of networks are partially solved. however, requirements like real-time resource utilization, fault-tolerance, and the placement of container registries are in the early stages. we conclude that kubernetes is an eligible candidate for cloudedge orchestration. when the formerly mentioned issues are solved, kubernetes can successfully contribute latency-critical, large-scale, and multi-tenant application deployments for smart cities. received on 14 march 2022; accepted on 23 may 2022; published on 25 may 2022 keywords: edge computing, edge orchestration, cloud computing, container orchestration, kubernetes copyright © 2022 boehm and wirtz, licensed to eai. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi:10.4108/eetsc.v6i18.1197 1. introduction over the years, information and communications technologies (icts) have become inevitable and permeated more and more areas in everyday life. besides the traditional usage in business-related contexts, icts are used in urban areas, which is also known as the concept of smart city (sc). in scs, various technologies sustainably enhance urban life [1]. many fundamental areas in cities are equipped with sensors to gather data from community services, like transportation, power plants, information systems, and crime detection [2]. the goal to build a sc is accompanied by an increasing number of sensors and traffic volume. this development also ∗corresponding author. email: sebastian.boehm@uni-bamberg.de affects applications that run in sc-related applications. requirements like the provision of computational resources on-demand, low-latency in multiple regions, and flexible moving of services in a city must be tackled [3]. comprehensive data collection is necessary to realize a sc. often internet of things (iot) devices are used [4–7]. an iot device is a resource-constrained member of a larger network that consists of similar devices. those devices, mainly sensors, collaborate on a common goal and need sophisticated management [8]. since these sensors are often placed in different areas, a large amount of data needs to be collected, processed, and analyzed to decide accordingly to the long-term goal. furthermore, real-time capabilities and faulttolerance are inevitable for these services to be stick to the goals of scs [9, 10]. these requirements set new challenges for designing software architectures. 1 eai endorsed transactions on smart cities research article eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 http://creativecommons.org/licenses/by/3.0/ mailto:<sebastian.boehm@uni-bamberg.de> sebastian böhm and guido wirtz so far, cloud computing, which offers a large pool of centralized resources, is the mean of choice for collecting and processing data from iot devices [11]. in recent years, many sc architectures emerged that facilitate iot devices and contributed to various challenges that are within the scope of scs. mostly, these architectures tackle the challenges of scs by digitalizing more and more public services [4, 12–14]. since the number of iot devices is continuously increasing, the cloud may not be able to serve a large number of requests with a particular latency [15]. furthermore, due to the highly distributed nature of placing iot devices in different areas in an urban region, connectivity and bandwidth issues may arise. these issues make it hard to use the cloud without unfavorable implications [16, 17]. in the context of scs, many digitalized services (like city monitoring and public transport) require realtime capabilities to operate efficiently [7, 14, 18]. hence, the average response time must be reduced. to overcome this situation, edge computing comes into play as an additional layer to the cloud, offering computational capacity near data-generating devices. this realizes low latency and better network reliability for service-requesting devices [19, 20]. consequently, edge computing offers the ability to selectively upload data to the cloud, contributing to enhanced privacy. providing computation capacities for scs, using the edge computing paradigm, can be a complex task. the assignment of workloads must be done according to the available infrastructure, which often consists of heterogeneous and resourceconstrained devices [21]. in addition, a lot of different services need to be deployed in a sc, depending on the public services, which must be supported [10]. at this, assigning computational workloads for data processing is mostly done with containers, a lightweight alternative to virtual machines (vms). those containers are managed by a container engine and contain all necessary dependencies. this nominates them as an ideal candidate for edge computing [22–24]. even if the complexity of deployments is simplified by container technology, new challenges, like latency requirements, arise. in consequence, an efficient management of container instances is required by taking resource demands and capacities into consideration. this is also known as edge orchestration [25]. largescale container orchestration is a rather complex task that requires a sophisticated management. for this, various container orchestration tools emerged, like the popular kubernetes (k8s)1. it offers high availability, scalability, and fault-tolerant management of a large number of containers. in the context of scs, a lot of 1kubernetes solutions emerged over time that are using k8s as orchestration system [1, 26–29]. so far, no comprehensive survey of already existing k8s-based architectures has been done to verify whether k8s is still worth considering for edge orchestration. this targets deployments for scs as well, where container technology is becoming critical to provide low-latency deployments in line with resource demand and supply. therefore, this paper aims to provide a detailed overview of existing k8s-based implementations for edge orchestration, partly for a sc context as well. for this, we analyze essential requirements of cloud-edge orchestration, also with a focus on scs. in an additional step, we use the obtained criteria for an evaluation of existing k8s-based solutions. finally, the results of the evaluation are used to assess if k8s is an eligible solution for cloud-edge orchestration, even in a sc context. this leads to the following research questions: • rq1: what are the most critical requirements for cloud-edge orchestration and are covered by k8s? • rq2: what are the benefits and drawbacks of already established cloud-edge architectures that are based on k8s? • rq3: are the potentially identified drawbacks of the investigated solutions in k8s solvable with a realizable amount of effort? • rq4: is k8s an eligible candidate for providing demandand supply-aware deployments, also for a sc context? to answer our research questions, we perform a literature review. at this, we extract fundamental characteristics of cloud-edge orchestration with a focus on scs. this contributes to rq1. to answer rq2, we review already existing cloud-edge architectures that are using k8s for advanced orchestration, also in the area of scs. we map the obtained characteristics to the existing solutions to identify the strengths and weaknesses of the implementations to answer rq3. lastly, we answer, based on our prior results, if k8s can still be considered as an eligible candidate for cloudedge orchestration in the context of scs (rq4). this paper starts with a conceptual overview of sc, edge computing, edge orchestration, and k8s (section 2). section 3 discusses related works evaluating cloud-edge orchestration solutions. in section 4, k8s, k8s-based orchestration architectures, limitations, and potential solutions are further analyzed. the investigated shortcomings of the solutions are covered in section 5. we discuss our work in section 6 with a critical assessment of our findings and the threats to validity. finally, we conclude our work in section 7 with a short summary and the plan for our future work. 2 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 https://kubernetes.io/ cloud-edge orchestration for smart cities: a review of kubernetes-based orchestration architectures 2. concepts this section gives a short overview of the core concepts required to survey cloud-edge orchestration architectures. first, we introduce scs to outline the need for complex orchestrations. we describe the principles of edge computing in a second step. finally, we conclude this section with a short introduction on the orchestration of cloud-edge architectures. 2.1. smart city in the following section, the concept of sc is explained in detail. besides the definition of sc, fundamental characteristics and arising challenges are discussed. definition. in recent years, scs have become very popular. by the usage of icts, living in cities should be made more comfortable. although there is no standard definition and understanding of the term sc, there are a couple of definitions with different perspectives on the topic, as researched by [30]. all of them have in common to improve the quality of life of citizens by usage of ict in basic needs, as outlined in section 1. many authors, like [30] and [31], come to this inference. according to the emerging popularity of scs, a lot of different architectures emerged that should simplify establishing smart services. there are also a few surveys that investigate the emerged architectural proposals and work out the granular differences [32–34]. quite common is the three-tier architecture, where multiple layers are used to define and classify sc architectures (figure 1). the architecture, taken from [5], as representative architecture for a sc mainly consists of three tiers, namely the urban environment, the communication layer with further separation into different steps, and finally, the service layer. the urban environment has many different sensors that are continuously collecting data. for example, this targets technical installations for smart traffic control systems, air quality monitoring systems, and video surveillance [35]. also, the core infrastructure is covered in this tier to connect all the devices to data-receiving endpoints, e.g., by using ethernet, wireless, or mobile broadband connections. the first step, which is performed by the communication layer, is data collection from all the devices placed in a sc environment (➀). after collection, the data processing is triggered (➁). this step includes transforming heterogeneous data into homogeneous data for further processing. the data is also enriched with additional information, like metadata, to create semantic relationships between data entities. this step is essential for the data integration, which takes place as the third step in the communication layer (➂). in data integration, the processed data is further analyzed by an inference engine to draw conclusions from the data. this might be a complex process that requires sophisticated methods and the expertise of domain experts. data collection data processing data integration devices tier 3: service layer tier 1: urban environment with sensors enriched data structured data preprocessed data raw sensor datati er 2 : c om m un ic at io n la ye r 2 3 4 1 figure 1. general smart city architecture (three-tier) [5] however, this step is inevitable to inform stakeholders, especially citizens, about important events. that is covered in step ➃. finally, sc architectures allow for several customized services that have access to the formerly presented data processing pipeline. for example, in the service layer, the government or third-party software developers can create web applications, dashboards, or other services that contribute to the aims of scs. typical use cases are also presented (section 2.4). characteristics. over the years, many attempts were performed to conceptualize the term and determine aspects of scs in a broader sense. one frequently cited characterization of sc was done by [18]. they describe a sc in six aspects, mainly based on the findings of [36] with a critical assessment. this characterization comprises a holistic view by including the social, economic, and technical perspectives and allows a well-balanced overview of how a sc should be designed [18]. these characteristics can be summarized and reorganized in different application domains for a sc that enables particular benefits for the urban development and the quality of life. in [34], a popular classification is presented that helps to organize the contributions and benefits a sc can accomplish. the authors outline that scs can lead to a (i) more efficient government, for example, by monitoring and managing public safety. furthermore, (ii) real-time information in daily life leads to happier citizens [4]. (iii) more efficient logistics and supply chain platforms can make businesses more prosperous. (iv) finally, also due to climate change, a sc can foster environmental sustainability by reducing and preventing pollution using real-time systems. in [37], a smart iot based building and town disaster 3 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 sebastian böhm and guido wirtz management system for scs was designed, which allows efficient monitoring and management for public safety. another solution [38] deployed a system of interconnected modules into a sc to monitor events. the solution aims to support disaster management and did not rely on any additional infrastructure. systems like this contribute to a more efficient government. in regards to real-time analytics, [39] mention that smart traffic control systems have a positive influence on avoiding traffic jams and mitigating traffic congestion in the city. for this, the city was equipped with video surveillance technology. this improves the quality of living. as a further example, sc-related activities can foster new business models [40]. in [41], comprehensive data collection for commercial purposes was suggested. according to the density of smartphones in a particular area, a new price structure for billboards has been established. furthermore, it is possible to organize parking spaces in a more efficient way [42]. optimizing waste disposal is also mentioned as an area for further optimization [43]. tackling climate change, various attempts have already been made to monitor pollution in scs and launch countermeasures, e.g., by prohibiting particular car classes from driving into the inner-city [44, 45]. this helps improve the air quality and finally the healthiness of citizens in large cities. however, several challenges are accompanied by establishing sc architectures. as already indicated, the concept of sc is strongly associated with the iot paradigm. those devices undertake essential tasks to realize the characteristics a sc should have. improving citizens’ well-being needs a sophisticated provision of high-quality smart services [2, 31]. popular application areas that contribute to the goals of scs also imply challenges, which are discussed in the following. challenges. fundamental challenges occurring by establishing sc architectures that handle a large set of workloads and requests are two-fold. first, general organizational issues come up because there are a lot of stakeholders and distributed responsibilities that result in complex decision-making. multiple industry partners, institutes, and public services must collaborate to achieve an efficient solution. this collaboration also comprises the appropriate sharing and management of network infrastructure, computational resources, and eventually data centers and their derivatives in edge computing [1]. secondly, besides sharing and agreeing on a common data platform, further challenges must be considered as soon the organizational aspects and core infrastructure is set up. a major concern is providing an efficient allocation of applications for low-latency use cases that are quite common in sc contexts. in addition, because critical areas like smart traffic control systems must be served, an appropriate fault-tolerance is inevitable [9]. since the number of requesting devices is still increasing and needs to be managed, redundancy, reliability, and real-time capabilities are inevitable for an appropriate orchestration of large-scale deployments [10]. 2.2. principles of edge computing edge computing adds an additional layer to the cloud by placing computational resources close to datagenerating devices, like sensors, actuators, or other entities. this new placement strategy aims to reduce latency and improve bandwidth capabilities [46, 47]. in contrast to the cloud, where all data is transmitted to and stored in a centralized way, edge computing provides additional resources to take the load from the cloud [48]. especially low-latency application fields, like real-time analytics or video surveillance, can benefit from the increased bandwidth and reduced latency realized by edge computing [49, 50]. also, the geographically distributed nature of large iot networks is prone to unstable network connections [51]. the core requirement of edge computing, minimizing the latency and increasing bandwidth for real-time services, might be violated by long distances between client and servers. the length of the physical distance between clients and servers has a coherence with latency [19]. edge computing as general technology has different types, also called edge technologies [52]. common types are mobile edge computing (mec), cloudlet, micro data center (mdc), and fog. all of these offer different provision models (figure 2). mec was introduced by nokia and placed computational resources (e.g., computing, network, and storage) mainly next to mobile radio access network (ran) stations. this type of edge computing aims to provide lowlatency network access to low-power devices, often to process time-critical tasks, like real-time analytics. the placement next to mobile ran stations enables fast and dynamic provisioning of applications, which offer realtime services. accordingly, the provision of applications near the data-generating devices reduces the traffic sent to the cloud and reduces network congestion. there is no common understanding if mec is a substitute for the cloud. it is unclear whether data must or must not be forwarded to the cloud in any case [52, 53]. cloudlets form virtualized clusters with a set of decentralized devices for running low-latency applications. they are self-managing, fast and easy to deploy by local administrators and aim to provide computational resources close to data-generating devices. workloads and applications are supposed to be transmitted as vm overlays. the overlays are executed on top of a base image that is already available on the target device. it is necessary to shift these vm overlays rapidly, for example, if the service-requesting devices change their position continuously, for example, in 4 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 cloud-edge orchestration for smart cities: a review of kubernetes-based orchestration architectures edge mec cloudlet micro data center (iii) edge-only fog cloud data center 0 data center 1 data center n iot (ii) offloading(i) scaling figure 2. cloud-edge architecture with provision models and edge technologies [58] smart traffic control systems. therefore, it is inevitable that cloudlets have a reliable network connection with a high bandwidth available [54]. besides using vm overlays, [55] introduced lightweight containers for shifting workloads among devices in cloudlets. in addition, linux containers were used [56, 57] to realize performance enhancements with a lightweight alternative. similar to cloudlets, mdcs want to reduce response times by collaborating with the cloud as an additional layer. mdcs support multi-tenancy and need, therefore, a strong hardwareand software-based protection against unauthorized access. they run in an isolated and secured unit in terms of physical and virtual access. for data exchange with the cloud, they usually have a reliable, fast, and durable connection.2 fog computing, often also called edge computing [48, 51, 59], follows similar principles. although there is a high similarity between fog computing and the formerly presented edge technologies, fog computing can be interpreted as one step closer to data-generating devices and is explicitly designed in a decentralized way [49]. in fog computing, large-scale networks of heterogeneous devices cooperate and communicate to realize low latency for the lower layers [11, 60, 61]. it is still an unanswered question if there is a substantial discrimination between edge and fog computing. since edge and fog computing share common goals for many devices and act as an additional layer to the cloud, one can assume both terms can be treated equally. many authors [47, 48, 51, 59, 60] follow this interpretation and do not introduce an explicit differentiation. figure 2 shows different ways to deploy applications with low-latency requirements. utilizing the full architecture of cloud-edge environments, different 2microsoft researcher: why micro datacenters really matter to mobile’s future techniques on how to deploy applications have emerged over time. the most common, so-called provision models, are (i) scaling, (ii) offloading, and (iii) edgeonly deployments. for the last provision model, it is noteworthy that the edge is not supposed to replace the cloud side entirely [52, 53]. in the following, the different provision models are explained in detail: • (i) scaling: this type of provision model is also known under distributed offloading. applications are running simultaneously in the cloud and edge, collaborating to achieve better performance. both layers can scale out if a particular application runs out of resources (e.g., storage or latency) [62]. • (ii) offloading: the most frequent approach is offloading from cloud to edge and the other way round. for example, entire applications or application stacks are moved from the cloud to the edge layer, e.g., to meet a particular latency requirement. in addition, applications may be moved to the cloud if load decreases or the latency requirements get relaxed [63]. • (iii) edge-only: in this deployment type, applications are only placed and moved on the edge layer to fulfill the needed latency. therefore, offloading is not required for this technique. however, many solutions use offloading techniques nonetheless to perform edge placement strategies [64]. 2.3. orchestration of cloud-edge architectures using cloud-edge architectures for running a large set of different services comes along with new complexities. these complexities arise because of the additional edge layer, different edge technologies, and provision models. cloud-edge orchestration is responsible for assigning workloads to the cloud, edge, and iot layer based on a particular set of objectives (section 2.2). the most important aspect that must be covered is an efficient placement of applications dependent on the origin of potential requests. also, the required real-time latency and bandwidth of devices must be considered to achieve the claimed application response times. for this, complex decision and orchestration models are required that consider demand and supply of resources like cpu, memory, disk, and network utilization [48]. fault-tolerance and resilience is a further core requirement of cloud-edge architectures [65]. as already mentioned in the former section, cloud-edge systems are used in critical areas, like smart traffic control systems. outages because of broken nodes in the architecture should not happen. the complexity of managing those architectures is further intensified due to the decentralized, distributed, and large-scale nature of the edge layer. in addition, a heterogeneous 5 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 https://www.networkworld.com/article/2979570/microsoft-researcher-why-micro-datacenters-really-matter-to-mobiles-future.html https://www.networkworld.com/article/2979570/microsoft-researcher-why-micro-datacenters-really-matter-to-mobiles-future.html sebastian böhm and guido wirtz autonomic controller orchestrator cloud0 edge0 container registry cloud1 cloudi edge1 edgej (i) scaling (ii) offloading (iii) edge-only strategy algorithm policy figure 3. generic orchestration architecture, based on [67] set of devices, often low-power devices, needs to be managed appropriately [59, 63]. dynamically scaling down and up the number and types of nodes in cloudedge architectures must be supported to realize largescale deployments in the right way [66]. also noteworthy are security considerations like supporting multitenancy for edge technologies like cloudlets and mdcs, which are offering a shared model (section 2.2). security mechanisms like authentication and authorization are strongly required to operate cloud-edge systems [65], especially if they are publicly accessible [59]. as already outlined in the former sections, the provision models present several challenges that must be met. workloads should be fast and easy to deploy and moved across the layers in the architecture. meanwhile, container technology is the de facto standard running workloads in cloud-edge architectures. containers follow the principle of lightweight virtualization and contain the application, libraries, and the runtime environment. they are executed in an isolated way by a so-called container engine which restricts the amount and type of resources a particular container can use (i.e., cpu, memory, and storage). the container engine itself runs on an operating system and shares the kernel with the container instances. container technology has been widely accepted for this area because containers are small in size, have a fast startup time compared to traditional vms [24], and can be easily ported to other physical nodes [22, 23]. the eligibility of container technology for orchestration activities requires an appropriate architecture that is able to realize the provision models. in figure 3, a general and generic architecture based on [67] is shown. a container registry provides containerized applications. in case of a deployment instruction, corresponding nodes download the container image and execute it with the required configuration. a so-called autonomic controller creates these deployment instructions. this controller includes an orchestrator that assigns containers to nodes given a strategy, algorithm, or policy. this workflow can be applied to all provision models that are covered in this paper. 2.4. edge computing in smart city contexts edge computing and its related technologies have meanwhile a large application field in sc contexts. over the years, many architectures emerged, like the rainbow architecture from [68] that aims to provide easy development of sc applications for large sensor networks. the authors followed an agentbased approach using fog computing to implement their architecture. also, for the sake of air quality monitoring, [69] proposed an architectural design for scs. in the work of [70], a managed, programmable, and virtualized edge platform was presented using container technology as an underlying technology. the authors tested different applications, like air quality monitoring, sound classification, and image recognition. other solutions consider similar tasks and proposals using edge computing or related approaches for real-time traffic monitoring [71–73] or video streaming [74]. further approaches focus on real-time use cases as well [7, 14, 18]. especially the latter proposal aims to move workloads during runtime from edge nodes to other edge nodes. in regards to the already introduced edge technologies, there are architectures that either require or support cloud, edge, mec, fog [75, 76], or finally cloudlets [77] as fundamental edge technology. distributing and shifting of workloads and tasks in scs was covered in [78, 79]. they formulated complex task allocation algorithms to further reduce the end users’ latency. lastly, edge computing and related orchestration activities also contribute to better privacy and security [77, 80]. edge computing and in specific edge orchestration is an essential component providing additional computational capacities for scs. there are a lot of different use cases. however, most of them have an explicit requirement that must be met, especially in terms of latency and bandwidth to operate normally. the highly distributed nature of sc architectures can be efficiently supported by edge computing and further by edge orchestration, where an advanced and flexible shifting of workloads is possible and different provision models are fully supported. 3. related work we first analyzed publications that defined and investigated characteristics of cloud-edge computing. then, we performed an evaluation based on a set of criteria. in [81], a literature survey on fog computing and other edge technologies was performed. they stated limitations, research directions, and potential solutions for fog orchestration. their study mapped these limitations and research directions to potential solutions and summarized plenty of aspects for future work. [61] conducted a literature survey to investigate orchestration challenges for edge and fog computing. 6 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 cloud-edge orchestration for smart cities: a review of kubernetes-based orchestration architectures also, the authors provided a mapping between challenges and discussed a set of potential solutions. [82] investigated requirements like infrastructure-, platform-, and application-related criteria. following the qualitative study design, these criteria were used to evaluate established fog architectures. the authors collected a comprehensive set of resource allocation and scheduling algorithms for orchestration. these criteria were used to evaluate a set of solutions that try to tackle this problem domain. in [59], a discussion of motivations, challenges, and opportunities in edge computing was provided. the authors assembled a set of criteria for orchestration-related activities. in a second step, we consider works that investigate cloud-edge or edge orchestration architectures in specific. [83] set a focus on requirements for orchestration in regards to the management of nodes (e.g., joining/leaving the cluster or scheduling). in specific, they evaluated container orchestration tools like mesos, k8s, and docker swarm. they defined requirements for orchestration systems, however, without any comparison of cloud-edge architectures implemented with the different container technologies. in the work of [65], the state-of-the-art of fog orchestration was further investigated with a focus on the core requirements an architecture must comply with. accordingly, they evaluated well-established fog orchestration architectures. they inferred that most of the considered architectures could deal with the general requirements of fog computing. lastly, plenty of contributions are in close relation to our study that investigate only one particular aspect of cloud-edge orchestration in detail: architectural and algorithmic challenges for resource provisioning and scheduling were further investigated in [84]. this literature review showed a comprehensive set of limitations that have been matched to potential solutions. in addition, starting points have been mentioned for further investigations. [62] analyzed offloading strategies that are an essential part of cloud-edge architectures. similarly, [85] presented an overview of several offloading algorithms and evaluated them based on a set of criteria. as shown in the former paragraphs, several solutions have already investigated challenges, research directions, and potential solutions for issues in cloud-edge orchestration activities. however, there is no overview of k8s-based cloud-edge and edge architectures in specific. furthermore, there has not been a detailed analysis of the requirements of scs for cloud-edge environments and orchestration yet. hence, this contribution aims to provide a detailed analysis of modifications made to k8s to make it ready for the requirements of edge environments in scs. 4. kubernetes as edge orchestration platform this section covers k8s as a candidate for running cloud-edge and edge orchestration environments. first, we explain the general architecture and functionality of k8s. in a second step, we discuss k8s-based orchestration architectures that we obtained from a literature review by using the search term kubernetes ∧ (edge ∨ fog) ∧ (computing ∨ orchestration). for the literature review, we used the following popular databases: ieee explore, springerlink, and arxiv. we considered only those papers which identified shortcomings of k8s and offered solutions for the identified issues. finally, we cover general limitations and potential solutions for k8s as an edge orchestration platform. 4.1. kubernetes as container platform the container platform k8s is used to execute containerized workloads on a set of nodes. furthermore, it implicitly implements the generic orchestration architecture shown in section 2.3. figure 4 shows a minimal working cluster, consisting of one master node and one worker node. the master node, also called control plane, runs all essential system services for the cluster. to run containerized workloads, at least one worker node is needed. it is possible to assign workloads to the master node that, however, this is not recommended.3 in general, containerized workloads are executed in pods, the smallest deployable unit in k8s that provides the execution environment for containers. managing the set of worker nodes and assigning containerized workloads to the worker nodes is done by the master node. at this, the managing services are also running as containers and can be distributed to multiple nodes, e.g., to achieve high availability. in specific, a k8s cluster includes the following components: all running nodes in the cluster are observed by the controller-manager (c-m). this component also keeps track of the current state to plan future actions and deployments. for example, the controller-manager can restart workloads on other nodes if the currently used node is failing or not operational anymore. the kube scheduler (ks) is in charge of assigning workloads to worker nodes (named sched in figure 4). this assignment is realized based on a scoring model to find the most suitable node. for example, manually set constraints and available resources can be regarded. cluster data, for example, currently running assignments, are stored in a strongly consistent and distributed key-value store, named etcd. in case of a redundant deployment, either with multiple master nodes or a unique etcd cluster, the data will be replicated across all instances. the api is exposed 3kubernetes documentation nodes 7 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 https://kubernetes.io/docs/concepts/architecture/nodes/ sebastian böhm and guido wirtz kubernetes cluster worker nodemaster node / control plane etcd containerpod custom component key=value label custom figure 4. general kubernetes architecture [58] as rest api and allows the interaction with the system components in the cluster. the horizontal pod autoscaler (hpa), omitted in figure 4, dynamically scales in and scales out the number of pods based on metrics like cpu and memory utilization.4 the kubelet that is available on all worker nodes serves as a communication endpoint for the controller-manager. the major responsibility of this component is managing the lifecycle of nodes according to the commands received from the controller-manager. in addition, the current state of the node is transmitted to the controller-manager as well. the component k-proxy opens ports and forwards traffic according to the deployed workloads and the configuration.5 k8s is modularly built and allows replacing several components, as shown in figure 4. for example, the scheduler component can be replaced completely. furthermore, additional information in the form of labels can be attached to nodes. this might be helpful in enriching the data basis for complex scheduling processes in case the scheduler component has been replaced. external components, e.g., for advanced scheduling and scaling, can interact with the api or custom containerized components to achieve a particular outcome. these components might even be deployed on a k8s cluster as control plane components when the built-in scheduler is supposed to be replaced.6 4.2. kubernetes-based edge orchestration architectures in our study, we classify k8s-based edge orchestration systems into three categories. the first category comprises open-source frameworks and solutions that aim to realize essential orchestration features in edge computing. solutions that implement custom modifications and introduce new extensions to k8s are part of the second category. the last category reveals those solutions that tackle only the edge layer with a modified k8s. 4kubernetes documentation horizontal pod autoscaling 5kubernetes documentation kubernetes components 6kubernetes documentation extending kubernetes platform-based solutions. the first category comprises frameworks like kubeedge (ke)7, baetyl8, openyurt (oy)9, or iofog10. these platforms deploy custom components as containerized workloads to an unmodified k8s cluster to implement their orchestration logic. usually, these platforms provide only mechanisms for an easy setup process of cloud-edge architectures. easyto-use routines are included to roll out the required infrastructure components, like software-defined networks, message brokers, service and event bus endpoints, and management capabilities. setting up and running cloud-edge architectures is simplified such that users can easily deploy devices and monitor their state. in addition, platforms like ke advertise resource optimization that enables the usage of low-power devices. however, the platforms lack dynamic workload allocation capabilities. support for different provision models of edge computing is somewhat limited. for example, the platforms might not be able to perform dynamic placement decisions or placement changes based on the current utilization of a set of devices. furthermore, provision models like offloading from cloud to edge and vice versa, as well as scaling out to the edge, are not supported in particular [86]. to overcome this limitation, several solutions considered in this study used the modifiability and extensibility of k8s (section 4.1). they implemented custom components to meet the requirements of more sophisticated cloudedge and edge architectures. custom cloud-edge architectures. the second category comprises architectures that consider the cloud and the edge layer in collaboration. [86] introduced kais. this framework improves the long-term rate of request processing and system overhead by using the edge in cooperation with the cloud. the orchestration activities are planned centralized in the cloud to assign workloads to edge nodes. the actual workload is dispatched only to the edge. the proposed solution uses advanced learning techniques and orchestration fundamentals. as a result, kais can increase the throughput rate and reduce the scheduling costs compared to k8s. minimizing interference and energy consumption of deployments was covered in [87] as a multi-objective optimization problem and is called keids. all nodes in the cluster were equipped with custom containers to fulfill the requirements of coallocation of dependent workloads on a single node. this solution aims to reduce the carbon footprint of the orchestration architecture. the authors implemented keids and a modified version of keids. they 7kubeedge 8baetyl 9openyurt 10eclipse iofog 8 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/ https://kubernetes.io/docs/concepts/overview/components/ https://kubernetes.io/docs/concepts/extend-kubernetes/ https://kubeedge.io/en/ https://baetyl.io/en https://github.com/openyurtio/openyurt https://iofog.org/ cloud-edge orchestration for smart cities: a review of kubernetes-based orchestration architectures compared the results to a first come first serve algorithm and inferred that keids led to different improvements in carbon footprint, performance, and energy minimization. swirly, a solution proposed by [88], is a scheduler that creates a service topology to simplify orchestration activities. it runs in the cloud and supports large-scale deployments by considering the topology with a small number of containers. also, real-time resource utilization is considered, like cpu, memory, and finally latency for the end users. for that, they equipped all nodes with custom container components. based on a benchmarking study, they concluded that the solution is able to handle up to 300000 devices. [26] suggested a cloud-edge solution with a focus on locationaware scheduling for an air monitoring service. to achieve location-aware scheduling, they implemented custom schedulers and modified k8s. they compared their locationand network-aware scheduler to the default ks and approaches based on integer linear programming. the architecture with the modified scheduler reveals a remarkable latency reduction. in [89], k8s has been prepared for geographically distributed clusters. similar to the approaches before, they attached custom components to each node and added a custom scheduler component to consider the network latency. this solution uses the cloud and the edge layer for running workloads and calculates latency-aware deployments based on periodic latency checks. an evaluation revealed that the architecture could adjust deployments according to real-time conditions. [90] designed an architecture with support for fault-tolerance, application isolation, data transport, and multi-cluster management. fault-tolerant message broker clusters, deployed in cloud and edge, were used to realize the storage layer. master nodes deployed in the cloud were replicated and operated in high availability mode. therefore, a two-node failure keeps the proposed architecture operational. [91] propose fogernetes that provides network-aware and resourceoriented deployments based on a labeling system. the labeling system adds key-value pairs to nodes and refers to them during deployment. for verification, they implemented an architecture for video streaming with devices placed in edge and cloud and defined the target nodes for deployment in corresponding deployment manifests. k8s used the former defined key-value pairs and realized a location-aware deployment based on labels and the definitions in the deployment manifests. custom edge architectures. the third category reveals a conceptual overview of solutions that tackle the edge layer specifically for orchestration purposes. in [92], a fog architecture with k8s was proposed to deploy multi-container applications on low-power devices. several plugins extended the default ks to accomplish an efficient and location-aware deployment of containers. multi-container applications are deployed on neighboring nodes. an evaluation yielded that the service quality was not compromised. [93] suggested a decoupled and native modification for k8s to implement location-aware, latency-aware, and fault-tolerant deployments. deployments are calculated by the usage of an external component that passes these deployments to an unmodified k8s cluster. a robust integration into k8s was achieved by running an additional component directly on k8s that interacts with the api of the cluster. to validate the solution, the authors performed experiments on allocation performance and failover time. [66] developed an edge solution for industrial iot that reduces the scheduling time. they applied the technique of single-step scheduling via a custom scheduler to pursue latency-aware deployments, an improved deployment time, and a lower temperature of all nodes in the cluster. in an evaluation, they showed that the scheduling time could be reduced. also, they monitored latency, jitter, and packet loss during the scheduling process. an agent-based approach for orchestration of fog architectures was considered in [94]. they addressed inherent issues of k8s, like high-load on the master node in the scheduling process. to overcome this problem, they replaced the default ks that addresses only the fog layer. selected scheduling tasks (e.g., node filtering, sorting, and scoring) were shifted to several nodes in the cluster. they evaluated their identified solution for a small number of replicas (< 10) and obtained that it needed less deployment time compared to the default approach. 4.3. general limitations of kubernetes for edge orchestration this section discusses the limitations of k8s as an orchestration platform for cloud-edge orchestration. we categorized these limitations in resource-awareness and architectural shortcomings. a graphical representation of all shortcomings is depicted in figure 5 and is explained in detail in the following section with the corresponding numbers 1 8 . resource-awareness. a major challenge in cloud-edge orchestration is dealing with real-time resource demands and supplies. the most important resources that must be tracked are cpu, memory, storage, and network utilization. circumstances in cloud-edge environments can rapidly change. appropriate actions, like offloading and scaling, in the environment must be triggered as soon as possible. k8s shows several limitations in this regard, as shown in figure 5. limitation 1 reveals that the default ks (sched) considers only cpu and 9 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 sebastian böhm and guido wirtz multi-container application worker node w1 3.5 / 4 vcpu 3584 / 4096 mb worker node w2 0.5 / 1 vcpu 0 / 1024 mb master node / control plane etcd custom container c0 0.25 vcpu 256 mb container c3 container c2 container c1 0.25 vcpu 512 mb pod c0 7 worker node w3 0.5 / 1 vcpu 1280 / 2048 mb c1 c2 c3 c0' c0'' hpa 2 1 3 4 4 4 5 6 6 6 7 7 7 7 8 8 8 control plane (replicated) control plane (replicated) cloud edge edge figure 5. selected limitations of kubernetes as platform for cloud-edge orchestration memory utilization during the scheduling process. however, as outlined in the previous sections, network-related metrics [21, 26, 66, 87, 92, 93] and energy consumption [26, 87] are important to meet the requirements in edge and iot computing. especially latency plays a vital role in scheduling containerized applications because the primary goal of edge computing is to respond faster than comparable cloud deployments. k8s does not provide a built-in mechanism to run deployments based on latency and bandwidth. this might limit the applicability in cloud-edge environments [26, 87, 89, 92, 93]. furthermore, the default ks assigns pods to nodes by the usage of node filtering, sorting, and scoring. new workloads are scheduled one by one at a time. potentially desirable priorities assigned to pods are not considered [21, 26, 86, 92]. in addition, the default ks assigns pods to nodes by using static resource demand and supply. resource requirements of a containerized application are defined statically by the developers. during the scheduling process, eligible nodes are selected based on the remaining static resources. after the successful assignment, the available resources are reduced by the demanded resources of the container. figure 5 shows an example of the static resource assignment: container c0 requires 0.25 vcpu and 256 mb of memory. as next step, the ks applies node filtering, sorting, and scoring and finally elects worker node w1 in this example. the available resources on w1 are reduced by the demanded resources of c0. this temporarily leads to 3.75 vcpu and 3840 mb of memory (not shown in w1). this static resource-based procedure could lead to unassigned pods if no suitable node can be found for an assignment. k8s will never move pods from one node to another in order to free up resources. in addition, this procedure may cause underutilization of particular nodes if resource assignments are far away from the real usage [26, 92]. limitation 2 shows how the hpa is acting if particular thresholds are exceeded. in this example, the hpa scales out to two additional instances, c0’ and c0”. depending on the available resources of the other nodes, pods are assigned equally to the remaining nodes. this results in one additional pod with c0’ on w1 and one additional pod with c0” on w3, which finally leads to 3.5 vcpu and 3584 mb of memory on w1. as already mentioned, the scaling approach does only work based on cpu and memory utilization that is tracked in real-time. therefore, these and other metrics (e.g., latency and bandwidth) could even be used to trigger offloading and scaling in cloud-edge systems. however, it is noteworthy that the costs for shifting applications or tasks from cloud to edge or vice versa should be regarded in scaling and offloading activities. this might prevent unnecessary offloading actions that are also reducing carbon footprint [26, 87]. since optimizing latency is one of the primary goals in cloudedge orchestrations, multi-container applications in different pods are supposed to be placed on the same node or on nodes close to each other [26, 92]. as shown in limitation 3 , k8s does not necessarily follow this requirement because it tries to achieve a uniform distribution of applications among nodes. in this example, only c1 and c2 are deployed in pods on the same node (w2), whereas c3 is deployed in one pod on w3. this finally leads to 0.5 vcpu and 10 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 cloud-edge orchestration for smart cities: a review of kubernetes-based orchestration architectures 0 mb of memory on w2 and 0.5 vcpu and 1280 mb of memory on w3. the last downside in regards to resource-awareness is the missing understanding of network topology. k8s treats all nodes as homogeneous with similar capabilities even if they are placed at geographically different locations. for example, w2 and w3 are low-performance edge devices with a weak cpu and slow main memory and are placed at the edge, as depicted in limitation 4 . however, cloud-edge architectures are usually consisting of heterogeneous nodes in a geographically distributed environment [26, 86, 87, 89, 91–93, 95]. architectural shortcomings. the second category of shortcomings of k8s as cloud-edge orchestration systems are architecture-related. first, all worker nodes in k8s are running k-proxy and kubelet as system components to accept network traffic for serving network services and to interact with the master node to receive new instructions. however, as shown in limitation 5 , both components are permanently requested, which might burden lowend devices and mitigate performance. k8s reveals a centralized organization where the control plane is managing the set of worker nodes. in edge computing, the decentralized nature is one core characteristic that might break if k8s is used to assign workloads to nodes. even if the control plane is fully replicated and running in high availability mode [90], as shown in limitation 6 , the requirement providing computational resources in a decentralized manner is violated [86, 92, 94]. limitation 7 covers that edge computing networks consist of a large number of devices, as already discussed in section 2.2. however, one single k8s cluster can manage at most 5000 nodes with 150000 pods and 300000 containers.11 very large edge computing networks must have additional concepts to overcome this limitation, e.g., by the usage of cluster federation [88, 95]. lastly, limitation 8 reveals that k8s does not hold a network topology of nodes in the cluster and can not deploy to specific nodes. hence, the distributed nature of cloud-edge clusters is degraded because all nodes in the cluster are assumed to be homogeneous [86]. 4.4. potential solutions for kubernetes as edge orchestration platform the former section discussed several shortcomings of k8s for cloud-edge orchestration. this section presents potential solutions which help to overcome these shortcomings. 11kubernetes documentation considerations for large clusters 2 1 3 4 custom metrics server custom real-time cpu, memory, latency, bandwidth, and jitter metrics 5 6 8 7 neglectible because of already established cloud-edge architectures multiple clusters, e.g., per region by cluster federation assign labels to nodes to introduce a topology custom scheduling/scaling hpa adjusted recompiled, native, or extended scheduler running instead of / alongside the default scheduler (ks)r es ou rc es a rc hi te ct ur e lightweight kubernetes figure 6. potential solutions for kubernetes as cloud-edge orchestration system providing resource-awareness. figure 6 shows potential solutions for the shortcomings of k8s for edge orchestration. the solutions are mapped to the shortcomings described in figure 5 with the corresponding numbers 1 8 . the most apparent limitation of k8s for edge orchestration is the missing capability to consider other metrics like cpu and memory resources, as referenced by 1 and 2 . this applies especially to latency, bandwidth, energy consumption, and costs for offloading and scheduling activities, also in regards to real-time monitoring capabilities. several authors implemented the collection of custom metrics, like latency and bandwidth, with additional containerized applications, which are running alongside the default metrics server. the collected metrics are further analyzed by custom schedulers that are running alongside the default ks [86, 88, 89, 94, 95]. in addition, the expandability of k8s allows for an implementation of custom and native schedulers that can run in collaboration with the default scheduler or exclusively.12 also, there are already implementations that are using the ks with so-called scheduler extenders to alter the scheduling algorithm and outcome of the default ks [26, 92]. for example, the filter and scoring step based on predicates can be modified. recompiling the default ks with modified and additional predicates leads to overcoming the already outlined shortcomings, as shown by [92]. another possibility to alter the workload allocation policy is to calculate new deployments with custom orchestrators running as containers in the cluster, as done by [91, 93]. moreover, the issue with unscheduled pods in case of an inefficient distribution of pods on 12kubernetes documentation configure multiple schedulers 11 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 https://kubernetes.io/docs/setup/best-practices/cluster-large/ https://kubernetes.io/docs/tasks/extend-kubernetes/configure-multiple-schedulers/ sebastian böhm and guido wirtz nodes must be addressed. in this case, schedulers can divide the deployment and distribute the containers to different nodes [92]. moving containers might be an option as well [89]. however, this solution lets the issue of static resource assignments unresolved. a potential underand over-utilization is still at risk. for this, custom schedulers and custom metrics servers can be implemented to allow for real-time metrics, even during scheduling. placing multi-container applications on different nodes is a further issue, as shown in limitation 3 . to optimize latency, applications consisting of multiple containers should be actually deployed on the same node, respectively, on nodes near to each other. based on labels, so-called affinities, and custom schedulers, k8s can be forced to perform the deployment only on a subset of nodes [89, 91–93]. this strategy is also used to introduce a network topology covered as an architectural shortcoming. lastly, k8s assumes all nodes to be homogeneous as summarized by limitation 4 . this is not a problem in the first place since scheduling and scaling with the hpa works with the nodes’ individual resource supply. however, as already discussed, the performance may suffer if devices with weak specifications are treated equally as powerful devices. since cloud-edge architectures consist of heterogeneous devices, deployments must be fairly distributed. for this, labels, affinities, and custom schedulers can be used to provide efficient deployments [26]. implementing cloud-edge architectures. k8s requires the nodes to run additional components to operate as a cluster member, as depicted in limitation 5 . this involves some additional overhead on the single cluster members. however, there are plenty of studies that have benchmarked k8s and lightweight distributions that are especially suitable for the edge and iot devices. as a result, the additional components do only have a small impact on the performance, especially if lightweight k8s is used [96]. actually, cloud-edge architectures should be in line with the characteristics of a decentralized architecture, as referenced by 6 . therefore, they should not use any centralized architecture, as is the case with k8s. however, this requirement can be relaxed because there are a lot of examples already that are using centralized architectures for all essential activities of orchestration [86, 89, 91]. especially agent-based approaches have already been implemented with k8s in the field of edge computing [86, 94]. limitation 7 shows that single k8s clusters have a limitation of at least 5000 nodes with 150000 pods and 300000 containers in total. this limitation is solvable by introducing multiple independent clusters (e.g., by region) or by cluster federation, as shown by [88, 95]. the missing network topology of k8s can be seen as the most serious issue for running cloudedge orchestrations and is listed as limitation 8 . section 2.2 discussed various provision models that must be supported by edge orchestration. for example, edge offloading requires detailed knowledge about the location and assignments of nodes to layers. hence, for orchestration of cloud-edge environments, k8s must be aware of the network topology to support the different edge technologies and provision models. as a potential solution, labels can be assigned to nodes, and with socalled affinities and anti-affinities, the assignment of pods to nodes can be controlled. the solutions that have been investigated in this paper use affinities to address a particular layer and add supplementary context information, like the geographical target location [89, 91–93] or the device type [26]. 5. limitations of the proposed solutions the investigated implementations showed plenty of solutions to overcome the mentioned resourceand architecture-related limitations. however, these solutions still have unresolved issues and shortcomings that must be regarded when running cloud-edge architectures. this section presents an overview of the shortcomings we identified in the considered solutions. in line with section 4.3 and section 4.4, we present the limitations divided in resource and architectural solutions. table 1 shows an overview of the resource and architectural requirements and their degree of achievement. we differentiate between fully supported (●), partially supported (❍), not supported (no circle), or where no details could be found (✲). 5.1. resource-related solutions most of the considered solutions are regarding the cloud and the edge layer. the most frequent architectural design consists of a cloud node and a set of worker nodes located in the edge layer. the cloud node runs the control plane with modified components and the edge nodes are in charge of running the actual workloads. however, there are plenty of solutions that include only the edge layer in their architecture. most of the authors have used custom containerized schedulers that are replacing the native ks. [93] and [26] are running a custom scheduler [93] or an extender [26] alongside an unmodified default ks (❍). some proposals are working without any modifications on the scheduling component and have used implicit scheduling [90, 91]. another approach used only affinities and anti-affinities to modify the scheduling behavior [91]. only one solution provided a recompiled scheduling component that is responsible for the entire cloud-edge orchestration [92]. almost all solutions considered at least cpu, memory, and disk resources. most of the solutions are only aware of static 12 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 cloud-edge orchestration for smart cities: a review of kubernetes-based orchestration architectures table 1. comparison of resource-awareness and architectural capabilities in different kubernetes implementations for cloud-edge architectures [58] resource-awareness architectural capabilities c lo ud ed ge io t r ec om pi le d n at iv e ex te nd er c us to m c p u m em or y d is k en er gy la te nc y b an dw id th k 8s a p i c us to m c lo ud ed ge io t sc al in g o ffl oa di ng ed ge -o nl y c lu st er c on tr ol pl an e c lu st er st or ag e c lo ud ed ge r ep lic at ed authors year layer scheduler resources network metrics topology provision model faulttolerance container registry [86] han 2021 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● [92] kayal 2020 ● ● ❍ ❍ ❍ ❍ ❍ ● ● ● [87] kaur 2020 ● ● ● ● ● ● ● ✲ ❍ ❍ ❍ ❍ ● ● ✲ [93] eidenbenz 2020 ● ❍ ● ❍ ❍ ❍ ● ● ● ● ✲ [88] goethals 2020 ● ● ● ❍ ❍ ❍ ● ❍ ● ● ● ✲ [21] ogbuachi 2020 ● ● ● ● ● ● ● ● ● ● [26] santos 2019 ● ● ❍ ● ● ❍ ❍ ❍ ❍ ❍ ❍ ● ● ● ❍ ● ● ● ● [94] casquero 2019 ● ● ❍ ❍ ❍ ❍ ● ● ● [89] haja 2019 ● ● ● ❍ ❍ ❍ ● ❍ ● ● ● ● ● ✲ [90] javed 2018 ● ● ❍ ❍ ❍ ❍ ❍ ❍ ❍ ❍ ❍ ❍ ● ❍ ✲ [91] wöbker 2018 ● ● ❍ ❍ ❍ ❍ ❍ ● ● ● ❍ ● ● ● = fully supported; ❍ = partially supported; no circle = not supported; ✲ = n/a resource assignments (❍) for scheduling decisions. a few solutions used real-time metrics (●) even for scheduling decisions. [87] also integrated the energy consumption for such decisions that might be important when devices are running on battery. latency-aware deployments are inevitable in edge computing. for this, latency and bandwidth must be considered properly. most solutions have used periodic latency measurements (●) to achieve those deployments. other solutions relied on predefined and static assignments (❍). for bandwidth, which was rarely considered in the investigated solutions, there are periodic (●) checks [87] as well as static (❍) definitions [26]. for measuring the current cpu and memory utilization, usually, an unmodified version of the k8s api (❍) is used. to extend the set of metrics that can be used for scheduling and scaling, plenty of the investigated solutions just used the unmodified k8s api. [88] and [89] enriched this api with custom (●) containers and functionalities. one solution [93] is replacing the k8s api entirely with a version that is fully compatible to k8s and measures the latency between nodes. missing explanations were also the case (✲). 5.2. architectural solutions after reviewing resource-awareness, we will evaluate the architectural capabilities. topology-awareness can be seen as one of the most important requirements. only a few authors allow for deployment and scheduling to cloud and edge nodes explicitly (●). the solutions presented by [87, 90] take cloud and edge nodes as one single topology (❍) to run workloads. mostly, only the edge layer is fully considered. also, workloads are not supposed to be shifted among the cloud and edge layers. solutions proposed by [26, 86, 91] support the scaling model where workloads can be run on cloud and edge simultaneously (●). the implemented schedulers of [87, 90] support scaling to edge only implicitly (❍). explicit offloading (●) is seldom supported because, as already outlined, the cloud layer is usually used for the cluster managers and orchestrators and not workloads. implicit offloading (❍) occurs if nodes are failing and workloads are shifted and restarted on other nodes by k8s automatically. this is only possible for architectures where workloads are potentially running on cloud and edge. nearly all architectures fully facilitate edge-only deployments where workloads are deployed on the edge layer to reduce latency (●). perhaps, workloads are also moved across the edge layer during application runtime to improve the latency further. in case users or the hpa are increasing the number of replicas and only edge nodes are available as computational resources, workloads are partially scaled out (❍). fault-tolerance of k8s itself was poorly covered in the orchestration architectures. even if the deployments of applications offer high availability, crashing master nodes that are carrying the control plane with essential components for scheduling, scaling, monitoring, and resiliency features mitigate the fault-tolerance of the entire architecture and limit the application in critical areas. [86] and [87] are using geographically independent (●) k8s clusters for faulttolerance. the control plane, however, is not replicated using at least three master nodes (●) for production 13 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 sebastian böhm and guido wirtz environments.13 a fault-tolerant architecture was only developed by [90] with three master nodes that are running replicas of the distributed key-value store etcd as cluster storage. this kind of deployment is also called stacked cluster storage setup (❍).14 as a general recommendation, it is worth considering decoupling etcd from the master nodes and providing an independent external cluster storage (●). this external cluster storage achieves better resiliency and reduces the load on the master nodes as well. particularly, this is recommended for environments that need to handle a large number of nodes.15 container registries are mainly located in the cloud in a non-geographically replicated manner. however, the geographical location of these registries is essential because the highly distributed edge nodes need to download containerized workloads in a small amount of time, for example, if workloads are supposed to be scaled, offloaded, or moved following the edge-only provision model. it is inevitable to follow a reasonable strategy by placing container registries at different locations to follow the superior goal of latency reduction in edge computing and edge orchestration. in the set of implementations, only one implementation [26] has used a fully replicated container registry across cloud (●) and edge (●). one further solution, provided by [91], placed the container registry on the edge layer (●) to accelerate the deployment process. in most of the works considered in this survey, the placement of container registries is neglected and not specified or further discussed (✲). 6. discussion this section discusses the evaluation of the k8s-based solutions in the former section. in section 6.1, we present a summary of our results by answering the research questions. afterward, section 6.2 discusses the limitations of our study. we conclude this section with a short assessment if the efforts making k8s ready for the edge computing and edge orchestration, even for scs, should be retained. 6.1. findings in this work, we performed an analysis of the capabilities of k8s to orchestrate cloud-edge architectures, also for scs. for this, we obtained fundamental characteristics of the sc concept, edge computing, edge orchestration, and k8s as container orchestration platform. we analyzed several studies that considered k8s as a basis for cloud-edge orchestration activities. the 13kubernetes documentation production environment 14kubernetes documentation options for highly available topology 15kubernetes documentation production environment findings from these steps allow us to answer rq1, in which we want to identify the most critical requirements for cloud-edge orchestration and their coverage by k8s. rq1. we categorized the essential requirements of cloud-edge orchestration in resourceand architecturerelated ones. first, we identified the set of layers a cloud-edge orchestrator should manage. second, we obtained that considering real-time resource utilization and providing network awareness are a primary focus, especially with dynamic changes over time. for the architectural requirements, it is important to consider the network topology as most important aspect. further, the support of different provision models and the implementation of fault-tolerance, also for all core services, are essential for cloud-edge environments with production readiness. k8s already provides some of these required aspects. scheduling and horizontal scaling based on cpu and memory are supported. in addition, k8s allows for setting up clusters in high availability mode. as stated by [83], cloud-edge architectures are subject to dynamic changes in the infrastructure. in specific, it is a common event that the number of nodes changes over time by adding and removing nodes [66]. however, this was not covered in our study in detail because k8s supports adding and removing nodes during runtime by default.16 security was also not in the scope of our study because the communication of the system components of k8s are secured via https by default and provide a built-in system for authentication and authorization.17 as already indicated, there are various shortcomings of k8s for cloud-edge orchestration. first, resourceawareness is only partially covered. k8s is mainly built for the cloud and not designed for working on a heterogeneous structure [93]. a further issue is the missing support for real-time resource utilization during scheduling. the most severe shortcoming is that no network-related metrics in scheduling and scaling tasks are considered. regarding architectural shortcomings, the missing topology-awareness limits the orchestration capabilities significantly. hence, the usage of k8s might be restricted to edge-only deployments exclusively. k8s implements a centralized scheduler to perform assignments of workloads to nodes and to manage the overall cluster. this violates the decentralized notion of edge computing. we argue that this issue can be relaxed because there are already established non-k8s-based cloud-edge architectures, even with centralized components that take care of the architecture [97, 98]. for orchestration activities like 16kubernetes documentation safely drain a node 17kubernetes documentation controlling access to the kubernetes api 14 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 https://kubernetes.io/docs/setup/production-environment/ https://kubernetes.io/docs/setup/production-environment/tools/kubeadm/ha-topology/ https://kubernetes.io/docs/setup/production-environment/ https://kubernetes.io/docs/tasks/administer-cluster/safely-drain-node/ https://kubernetes.io/docs/concepts/security/controlling-access/ https://kubernetes.io/docs/concepts/security/controlling-access/ cloud-edge orchestration for smart cities: a review of kubernetes-based orchestration architectures task offloading, a centralized management is used very frequently, as shown in a comprehensive survey by [85]. this work also analyzed the state-of-the-art of k8sbased cloud-edge orchestration. in addition, we discussed general limitations for edge orchestration. these steps allow answering rq2 that aims to investigate the benefits and drawbacks of cloud-edge architectures based on k8s. rq2. there are many solutions that solve essential shortcomings of k8s for edge computing. especially the capabilities in regards to resource-awareness have been significantly improved by adding custom schedulers that regard other resources like cpu and memory. in specific, the capabilities for network-aware deployments were targeted. besides that, topologyawareness has been added to get k8s ready for the edge by overcoming architectural shortcomings. nonetheless, there is still room for improvement. support for multiple provision models, fault-tolerance of the cluster architecture, and the placement of container registries must be implemented. based on the qualitative analysis of k8s-based implementations for edge orchestration, we identified drawbacks and are able to assess the solvability and the corresponding amount of effort to answer rq3. rq3. from our understanding, most of the problems are solvable in an appropriate amount of time because partial solutions can be combined to derive a unified solution. we are convinced that resourcerelated issues can be solved. our survey showed that many solutions considered only the edge layer to be managed by k8s. however, if the number of nodes and devices is increasing nonetheless, multiple clusters can be connected by cluster federation18. furthermore, many components of k8s can be replaced or extended, for example, the scheduler to implement the resourcerelated shortcomings. implementing a native scheduler with custom scheduling algorithms and scaling policies for the edge is a complex task [93]. this might be the reason why we could not obtain a large number of native implementations. lastly, k8s allows modifying the metrics sever to add further metrics that can enhance the overall placement decisions. we conclude that essential architectural shortcomings can be solved as well. in specific, network topology, support for different provision models, deployments, and cluster setups with high availability and placement of container registries were not a major focus in the investigated solutions. essential capabilities like faulttolerance by replicating clusters, their core services, or geographically distributed container registries can be implemented quickly. however, this requires accepting 18github kubefed a trade-off. in favor of a unified and universal cloudedge orchestration, the criteria following a decentralized architecture might be relaxed. finally, this work presented an overview of essential aspects of scs. also, a short review of already established approaches for edge computing in sc contexts has been covered. this supports us to answer rq4 appropriately where we need to discuss if k8s is an eligible candidate for providing demandand supply-aware deployments for a sc context. rq4. as outlined in section 2.1, a sc aims to improve the quality of living in urban life. from an it-related perspective, this is mostly done by the usage of iot technology. however, new challenges arise due to the rising number of devices and the emergence of critical services, like smart traffic control systems. based on our theoretical investigation, we can argue that multi-tenancy, security, fault-tolerance, and providing low-latency for real-time systems are major concerns that are not fully resolved by the existing solutions so far. a revised usage of k8s can positively contribute to overcoming these issues. also, in scs, the number of applications is continuously increasing. the types of applications are also changing over time, which requires a flexible management of an it infrastructure at scale. for such large-scale deployments, an efficient orchestration system based on k8s might be beneficial. from our perspective, k8s fulfills several essential requirements already that can be further improved. as discussed, real-time resource supplies and demands, network-related metrics, and the missing understanding of network topology are major issues that should be solved if k8s is working as a unified solution for deployments in scs. 6.2. threats to validity we aligned the set of evaluation criteria to critical requirements of scs, edge computing, edge orchestration, and the shortcomings of k8s. as a matter of fact, the set of evaluation criteria might be incomplete and a simplification. also, it is still to question if the custom implementations are comparable because they follow different approaches and objectives by solving the shortcomings of k8s. in addition, we investigate centralized, decentralized, and mixed architectures equally without further differentiation. nonetheless, we argue that mission-critical requirements in edge computing for sc contexts must be met. our evaluation assumed that all solutions must support the essential provision models in edge computing. according to our study, edge-only deployments are the most frequent provision model. therefore, it is to question whether all solutions must cover all provision models. the same applies to the layer aspect, where the layer might depend on the goals of the proposed solutions. lastly, 15 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 https://github.com/kubernetes-sigs/kubefed sebastian böhm and guido wirtz we considered a general k8s-based solution for edge orchestration and did not filter the set of solutions by those solutions that explicitly attempt to be used for scs. some solutions [26, 88] were explicitly used in sc environments and contributed to the validity of our evaluation. nonetheless, the principles, core contributions, and requirements of related cloud-edge and edge orchestration architectures are not significantly different from architectures that cover scs in specific. 7. conclusion and future work the vision of scs equips urban environments with ict to improve citizens’ quality of life. however, the large number of heterogeneous applications and devices with different resource requirements constitute new challenges. cloud-edge orchestration offers an efficient way to distribute workloads based on resource demands and supplies. especially reducing the communication latency for real-time applications is one of the main incentives to focus on these activities. mostly, container technology is used to distribute those workloads on a set of nodes. for managing large and complex container orchestration, k8s is considered to be the state-of-theart solution. however, many authors claimed that k8s, which is mainly built for cloud computing, lacks significant features. therefore, they contributed several improvements to make it ready for the edge. this paper evaluated the most recent architectural proposals that tackle the most significant issues of edge orchestration. to perform our evaluation, we based our survey on the essential requirements of scs, edge computing, edge orchestration, and finally native k8s. this paper contributes a state-of-theart overview of established cloud-edge architectures that are also suitable to manage the complexities of sc architectures. it can be seen as an overview of requirements that are already solved by these solutions and issues that are still unresolved. we identified plenty of benefits and drawbacks of the investigated architectures, which also influence the applicability of k8s to sc contexts. issues like real-time resource utilization, network-awareness, and network topology have been solved quite well so far. however, aspects like providing multiple provision models (i.e., offloading, scaling, and edge-only deployments) still have room for improvement. in addition, faulttolerant cluster architectures for managing cloud-edge environments are still in the early stages. the ideal placement strategy for container registries was also not in focus of the cloud-edge environments we considered. furthermore, we assessed if the shortcomings of k8s are solvable with an appropriate amount of effort to enable a long-term cloud-edge orchestration with k8s. in conclusion, since there are already partial solutions for most of these issues, k8s should still be retained as a container orchestration platform for cloudedge systems. since k8s offers solutions for essential requirements of cloud-edge orchestration and sc environments, further research should still be in focus. using k8s as an advanced orchestration system in sc context can foster the implementation of valuable services that have a positive impact on people’s and society’s well-being. furthermore, the government can be released through these developments since more and more administrative tasks can be automated. we still consider k8s as container orchestration platform for cloud-edge architectures and plan to implement a unified orchestration platform. a high degree in standardization (e.g., custom schedulers, custom metric apis, and architectural recommendations) can support the relevance of k8s in cloud-edge architectures. in the future, we plan to follow this defined goal by providing architectural blueprints that help to deploy k8s in production, in specific for a sc context that requires a high degree of flexibility for different demands. furthermore, we want to foster the standardization of generic cloud-edge orchestration strategies, algorithms, and policies. detailed instructions and providing standardized apis can contribute to a broader usage of k8s, even for standalone edge orchestration algorithms, strategies, and policies that are using their own container orchestration solution. the public availability of architectural blueprints in a centralized repository with established standalone solutions can foster the popularity of k8s for edge orchestration. in order to examine the feasibility of the proposed architectural blueprints, we want to provide reference implementations that are tested at scale to evaluate if k8s can finally run large-scale cloud-edge architectures. references [1] sebrechts, m., borny, s., wauters, t., volckaert, b. and turck, f.d. 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(2018) boundless application and resource based on container technology. in edge computing – edge 2018, 34–48. all links were last followed on february, 28, 2022. 19 eai endorsed transactions on smart cities 03 2022 09 2022 | volume 6 | issue 18 | e2 1 introduction 2 concepts 2.1 smart city definition characteristics challenges 2.2 principles of edge computing 2.3 orchestration of cloud-edge architectures 2.4 edge computing in smart city contexts 3 related work 4 kubernetes as edge orchestration platform 4.1 kubernetes as container platform 4.2 kubernetes-based edge orchestration architectures platform-based solutions custom cloud-edge architectures custom edge architectures 4.3 general limitations of kubernetes for edge orchestration resource-awareness architectural shortcomings 4.4 potential solutions for kubernetes as edge orchestration platform providing resource-awareness implementing cloud-edge architectures 5 limitations of the proposed solutions 5.1 resource-related solutions 5.2 architectural solutions 6 discussion 6.1 findings rq1 rq2 rq3 rq4 6.2 threats to validity 7 conclusion and future work eai endorsed transactions on smart cities research article enhancing precision agriculture: an iot-based smart monitoring system integrated lorawan, ml and ar d. t. huong1, n. t. h. duy1,2, p. v. m. tu2, h. h. hanh2,*, k. yamada1 1division of mechanical science and technology graduate school of science and technology, gunma, japan 2posts and telecommunications institute of technology, hanoi, vietnam abstract effective crop production and harvesting decisions rely on proper farm monitoring and management. each region has distinct needs for farm oversight, but the primary focus remains on collecting and evaluating environmental data such as temperature, soil moisture, air humidity, all of which are vital to plant growth. gathering this data on a large scale requires significant effort and is often based on intuition or simple measurement tools. this paper proposes a novel solution for farming data collection using an iot platform integrated long-range wide area networks (lorawan) network application with augmented reality (ar) technology and machine learning (ml) algorithms to predict key environmental daily indexes. in a pilot study in quang tho, vietnam, the system accurately predicted environmental conditions, reduced the risk of crop failure, and improved farm management efficiency. this approach enhances real-time data interaction and offers predictive analytics, supporting sustainable agriculture. received on 17 09 2024; accepted on 16 11 2024; published on 21 11 2024 keywords: lorawan; iot; ar; ml; smart farming; precision agriculture copyright © 2024 d. t. huong et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi:10.4108/eetsc.7286 1. introduction vietnam, an asian country, is currently one of the leading exporters of agricultural products in the world. however, the country’s farming sector continues to face multiple barriers in terms of technology, manpower, and agricultural land. currently, vietnam hasn’t had an integrated model of smart agriculture yet which is following the concept of agriculture 4.0 [1]. intensive farming methods are still heavily influenced by traditional practices, primarily using human and livestock labor, and farmers assess the status of their farms relying on personal experience. it has been customary that farmers have to be present on their farms during every stage of the crop’s growth. this requirement stems from the necessity to ensure the crops’ well-being and upkeep. consequently, around 70% of the cultivation timeline is spent on directly monitoring the farms instead of hands-on field activities. to address this, gathering and utilizing effective data is essential, and this can be achieved by precision agriculture. precision ∗corresponding author. email: hhhanh@ptit.edu.vn agriculture refers to the implementation of hardware and software technologies that enable farmers to make informed and customized decisions about various agricultural activities, including planting, fertilizing, pest control, and harvesting [2]. precision agriculture relies much on the accurate monitoring and forecasting of environmental conditions to optimize farm management and enhance crop productivity. however, environmental unpredictability makes it difficult to deploy continuous monitoring sensors in agriculture. large farms have several kinds of terrains, affecting temperature, humidity, soil composition, and sunlight exposure. 1.1. the integration of iot and other technologies the adoption of the internet of things (iot) is crucial for implementing smart farming practices, especially in large and remote areas [3]. in recent years, the rapid advancement of the internet of things (iot) has significantly enhanced agricultural productivity worldwide. the integration of advanced technologies with iot has enabled it to optimize agricultural processes. in [4], ai and ml were applied with iot to support farmers with decisions on irrigation, 1 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:<hhhanh@ptit.edu.vn> d. t. huong, et al. fertilization, and pest management. meanwhile, iot was also combined with ml-blockchain framework 5.0 in [5] to predict optimal crop outcomes. this model was suitable for both small and large farms. in addition, sensors were also combined with ml and ar to help people in aquaculture. in [6], rahman et al. combined these 3 technologies to detect water issues in shrimp ponds and predict conditions 24 hours in advance. when combining iot with different technologies, it brings unexpected efficiency in improving agricultural quality and productivity, helping farmers reduce the time to monitor and predict the status of the farm. however, to meet the infrastructure, installation costs are a relatively large obstacle. in addition, farmers’ understanding of data is also limited due to their low technological level. 1.2. our approach in this paper, we propose the deployment of an iot device using the stm32 series microcontroller and supporting the long-range wide area networks (lorawan) protocol which was determined to be the most reliable and deliver the greatest benefit for on-farm environmental data gathering in this project. the system helps enhance data gathering and quality by offering efficient, dependable, realtime environmental monitoring overbroad and remote locations. however, simply monitoring environmental indicators in the field in real time is not enough. in addition to knowing critical field indicators such as temperature, soil moisture, and air humidity, farmers need to forecast information on these indicators to make timely crop decisions. furthermore, a system that allows farmers to monitor their fields remotely can save time and improve efficiency. for these reasons, we integrate an interactive interface to the iot system, in which augmented reality (ar) technology and machine learning (ml) algorithms are being used to predict field conditions based on data collected from the lorawan-iot system. this interface is called farmerly, which includes a web-based management application and an ar mobile app that allows managers to oversee conditions across the entire farm, including current and near-future environmental conditions and stages of crop development. these models helped farm management from reactive to proactive, allowing farmers to anticipate and prepare for changes, showing promising accuracy in forecasting critical parameters. 2. system architecture iot provides a global infrastructure for the information society by interconnecting physical and virtual objects through interoperable information and communication technologies [7]. iot enables real-time monitoring and control, leading to precise farming practices. this figure 1. the proposed model of an iot platform using lorawan integrated ar helps optimize planting times, irrigation schedules, and harvesting periods, ultimately improving operational efficiency [8]. key components of iot include smart sensors, cloud computing (cc), wireless networks, and analytic software [9]. common iot technologies are low-power wi-fi, bluetooth low energy (ble), dash7 alliance protocol (d7a), long range (lora), and lorawan [10]. because of the long-range, low power consumption of lorawan and the powerful processing capabilities of the stm32 microcontroller, edge computing enables data pre-processing, resulting in more efficient bandwidth utilization and higher data quality. the model of an iot system based on lorawan integrated with ml and ar is given in fig. 1. ml, a crucial branch of artificial intelligence, allows computer systems to learn and improve independently without human intervention. applying ml, iot devices can predict and behave based on their own [11]. this model that outlines a comprehensive system for farm monitoring and management in four key stages: (1) data collection; (2) data transmission and cloud processing; (3) data analysis and prediction; and (4) visualization and interaction. (1) – data collection sensors that connect to stm32 microcontrollerbased iot devices, transmitting data via the lorawan protocol, placed across the farm gather environmental metrics. to collect data, end nodes are equipped with various sensors and actuators. each end node includes an stm32 series microcontroller; temperature, soil moisture, and air humidity sensors; lorawan module for data transmission. the end nodes are designed using a development kit that allows engineers to easily attach different sensors and actuators. these nodes collect data on temperature, soil moisture, and air humidity from the environment. the collected data is then sent to a central gateway via lorawan. (2) – data transmission and cloud processing the data transmission and cloud processing stage is critical for ensuring that the data collected by iot devices is efficiently transmitted, stored, and processed. this stage involves multiple steps to ensure data integrity, scalability, and accessibility. iot devices equipped with stm32 microcontrollers 2 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | enhancing precision agriculture: an iot-based smart monitoring system integrated lorawan, ml and ar collect data from various sensors (temperature, soil moisture, air humidity) deployed across the farm. these microcontrollers process the raw sensor data locally to reduce noise and errors, ensuring that only clean and meaningful data is transmitted. the processed data is sent from the stm32 microcontrollers over the lorawan network. lorawan is ideal for large farms because it supports long-range communication with low power consumption, making it suitable for areas with limited internet access [10]. lorawan enables devices to exchange data for up to ten years on battery life, meeting the needs of long-distance, ensuring low power consumption [12]. a lorawan gateway acts as a central hub that facilitates data transmission from multiple iot devices to the cloud. the gateway receives data from the iot devices over the lorawan network and then relays it to cloud servers using highbandwidth networks like wi-fi, ethernet, or cellular. (3) – data analysis and prediction in the cloud, the data collected from the iot devices goes through a structured pipeline involving three key modules: business, process data, and prediction. each of these modules plays a crucial role in transforming raw data into actionable insights and predictions that can help farmers make informed decisions. the business module is responsible for handling the operational aspects of the data pipeline. it ensures that the data collected is securely stored and readily accessible for further processing, controlling who can access the data and what operations they can perform, maintaining the accuracy and consistency of data, and coordinating the sequence of operations from data collection to analysis and prediction. the process data module conducts the initial analysis of the collected data. data cleaning removes inaccuracies and inconsistencies, normalization standardizes the data to bring all variables onto a common scale, and feature extraction identifies and extracts significant features from the raw data, such as trends, seasonal patterns, and cyclical components. the predict module leverages ml algorithms to forecast future environmental conditions such as temperature, soil moisture, and air humidity daily. these models are trained on historical data and continuously updated as new data becomes available, ensuring that the predictions generated are accurate and reliable, providing farmers with actionable insights. (4) – visualization and interaction the final stage of the precision agriculture monitoring system involves presenting the analyzed and predicted data to end-users through interactive interfaces, enhancing their ability to make informed decisions. this stage is crucial for translating complex data into helpful insights, which can be easily understood and utilized by farmers or farm managers. the webbased system serves as a comprehensive farm management dashboard that provides a detailed overview of the farm’s status and environmental conditions. this dashboard offers status indicators that visually show the overall status of the farm, such as normal, sunny, rainy, drought, or flood conditions. besides, the ar application provides an immersive and interactive way to visualize the farm’s condition. real-time 3d graphics overlay sensor data onto the farm’s physical environment, highlighting areas that require attention; showing the alert when there is a change from the environment. otherwise, the ar app shows the main stages of crop development, enhancing their decisionmaking processes based on both real-time insights and future forecasts. 3. pilot implementation with the requirements and proposed system mentioned above, we developed a pilot iot system for monitoring the farm’s seasonal time series such as moisture, humidity, and temperature parameters named farmerly. this system seamlessly integrates lorawan communication, ml algorithms, and ar technology. designed to provide farmers with real-time insights and predictive analytics, farmerly offers a new solution for modern farming challenges. table 1 highlights the specifications and functions of the iot system adopted in this study, showcasing the innovative approach and comprehensive capabilities of farmerly in revolutionizing agricultural practices. 3.1. lorawan nodes and gateway for data transmission in the first phase, the system performs data collection. environmental indexes are collected via sensors set across the farm, which are connected to stm32 microcontroller-based iot devices and communicate data using the lorawan protocol. end nodes are equipped with a variety of sensors and actuators to collect data. the end node is designed based on the stm32f103 microcontroller. this is a 32bit microcontroller that incorporates an arm cortexm3 core processor operating at a 72 mhz frequency and high-speed embedded memories. another advantage of this microcontroller is its compatibility with arduino platform so the developer can easily reuse a lot of arduino’s libraries. the rfm95w lora module is used as a modem to provide a long-distance wireless connection while keeping a low power consumption. the mcu connects to the lora module via spi connection for high-speed data rate and least i/o pins fig. 2. a power supply is very important for a device to work well in many different conditions. therefore, the power management (pm) block is also designed 3 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | d. t. huong, et al. table 1. specifications and functions of iot devices no iot specifications and functions 1 nodemcu esp32 microcontroller: esp32 cpu: dual-core tensilica lx6 connectivity: wi-fi, bluetooth digital i/o pins: 36 analog input pins: 18 function: iot device development, wireless connectivity, supports arduino ide. 2 arduino uno r3 microcontroller: atmega32p cpu: 8-bit avr digital i/o pins: 14 analog pins: 6 function: general-purpose microcontroller for various electronics projects, programming with arduino ide. 3 smartfarm cloud cloud-based iot platform features: pre-process, stores and processes data; hosts ml models functions: allow iot device data to be uploaded, stored, analyzed, and visualized in real-time through web-based interfaces. 4 ml integration ml models for data analysis and predictions features: analyzes, predicts functions: analyze historical data to predict future environmental conditions daily (based on temperature, wind, pressure, cloud cover, and humidity) 5 famerly applications ar mobile app & web-based application for iot monitoring features: comprehensive farm management, real-time monitoring functions: allows farmers to see data in its actual context, enhancing decision-making processes with real-time insights and future forecasts through website and mobile app interface. figure 2. schematic of mcu and rfm95w module carefully to provide many types of output voltages, reduce the emi (electromagnetic interference) noise and keep a stable supplier. a current/voltage sensor and a temperature sensor are integrated into this pm block for monitoring and controlling, ensuring good conditions for the power supply (fig. 3). figure 3. schematic of power management block after finishing the schematic design, the printed circuit board (pcb) design is an important step to have a good layout for board manufacturing. a good pcb design reduces the size of the board but still solves the heatsink problem and prevents the crosstalk noise. a prototype of end node is shown in fig. 4. the gateway is used to connect two networks with different communication protocols that can communicate with each other. a lora gateway can communicate with 4 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | enhancing precision agriculture: an iot-based smart monitoring system integrated lorawan, ml and ar figure 4. schematic of power management block figure 5. board esp32 wifi lora 32 for gateway lorawan other lora end nodes to get the data from them and then send it to the network server through a highspeed internet connection. for smart farm applications, a simple 1-channel gateway is implemented by using an esp32 – wifi lora board fig. 5. this board runs appropriate software to configure it as a gateway in the lorawan. esp32 wifi lora board is a development board with a combination of esp32 soc chip, and tensilica lx6 processor clocked at 240mhz. it supports many wireless connections such as wifi 802.11 b/g/, bluetooth, and lora. this board uses the lora sx1278 chip to operate with a frequency of 918mhz for a distance of up to 5 km. 3.2. data management and processing hub smartfarm cloud contains data from sensors and application server which is used to get, process, store, organize information, analyze and make predictions. the things network (ttn) is lorawan cloud network server that we use in smartfarm cloud. ttn is an open community platform supported by over 100,000 developers in the lorawan sector. ttn supports more than ten thousand lorawan gateways around the figure 6. system’s data management and processing diagram figure 7. warning alerts from firebase cloud message world [13]. smartfarm cloud manages information that is collected by iot devices and is streamed to the cloud. this information is sent to different parts of the system using the udp protocol and this incoming data is stored in the form of mongodb (nosql). the information managed by end nodes is displayed via the dashboard and ar mobile application from this application server as shown in fig. 6. moreover, in this system, firebase cloud message sends warning alerts to mobile app to keep control of their farm as in fig. 7. the prediction module within the application server processes farm weather data, collecting and cleaning information like temperature, humidity, soil moisture, and particulate matter through smartfarm cloud. this data is then used to train a prediction model, which generates real-time weather forecasts for the area based on collected indicators and past predictions, resulting in highly accurate forecasts. upon completing the training process, the system utilizes a data processing module to analyze farm data using optimal parameters efficiently. its primary objective is to identify any abnormal alterations in the farm environment. in the event of such changes, the system promptly issues alerts to notify farmers and provide guidance on corrective actions to maintain an optimal farm environment. 3.3. machine learning-driven weather forecasting weather prediction has always been a critical aspect of planning and decision-making across various sectors, from agriculture to disaster management. traditional methods of weather forecasting rely heavily on numerical weather prediction models that use mathematical 5 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | d. t. huong, et al. equations to simulate atmospheric conditions. while these models have been effective, they often require significant computational resources and can sometimes lack the precision needed for localized forecasts. in recent years, machine learning (ml) has emerged as a powerful tool for enhancing weather prediction [14] [15]. ml algorithms can analyze vast amounts of historical weather data to identify patterns and make predictions with high accuracy. these algorithms are capable of learning from the data, improving their performance over time, and providing more precise and timely weather forecasts. research indicates that ml methods are becoming key features in modern weather forecasting systems. a study [16] highlights the growing importance of ml in weather prediction, noting that it competes with traditional physical models and often exceeds them in short-term forecasts. however, challenges remain in medium-to-long-term climate forecasting due to the complexity of climate variables and data limitations. furthermore, the integration of ml in weather prediction systems has led to improved efficiency and accuracy. therefore, we use machine learning models, including random forest (rf) and logistic regression (lr), for weather prediction, specifically rain or sun, in our application. we use these two models to compare and choose the one with the highest performance: (1) rf is an ensemble learning method that constructs multiple decision trees during the training phase, with each tree trained on a random subset of the training data. for classification, the final output is determined by a majority vote of the predictions from all individual trees. rf’s strength lies in its ability to handle large datasets with high dimensionality and complex interactions between variables. the use of bagging (bootstrap aggregating) reduces overfitting by ensuring that each tree is exposed to different subsets of data, making the model robust and generalizable. this capability makes rf particularly suitable for applications like weather prediction, where the data can be noisy and intricate. (2) lr is a simple yet powerful statistical method used for binary classification tasks. unlike linear regression, which predicts continuous outcomes, lr predicts the probability of a given input belonging to a particular class. it uses the logistic function to model this probability, producing outputs between 0 and 1. the model is trained by maximizing the likelihood that the observed data can be predicted by the logistic function. lr is valued for its simplicity, ease of implementation, and interpretability, making it a baseline model in many classification tasks. it is particularly effective when the relationship between the features and the target variable is linear, as it provides clear insights into the influence of each feature on the prediction. data normalization label encoding training data from 2023 testing from 1/2024 to 4/2024 model testingdata and preprocessing optimized hyperparameters of ml models rf lr 5-fold cv model prediction rf lr figure 8. the flowchart of ml model for weather prediction the proposed method, shown in fig. 8, consists of three steps. initially, the data is preprocessed, including steps: data collection, label encoding, and normalization. the preprocessed data is then used for model training, specifically applying random forest (rf) and linear regression (lr) algorithms with 5fold cross-validation to optimize hyperparameters. the optimized models are subsequently tested using the 2024 data to ensure accuracy and reliability in weather prediction. 3.4. augmented reality integration for interactive farm monitoring in this section, with the aim to support comprehensive farm management, we developed a high-level module with two parts: a website-based data management system and an ar mobile application. farmerly webbased system oversees smart farm operations, recording and displaying temperature, humidity, and soil moisture details on a dashboard with time-valued data. the graphics illustrate trends across various terrains and periods, aiding farm managers in decision-making. the system includes a dedicated section for managing this region, displaying all relevant metrics and updates as in fig. 9. farmerly ar app uses arkit [17] integration to visualize real-time sensor data overlaid on the actual field view. arkit’s plane detection identifies horizontal and vertical surfaces through points of interest such as corners, edges, and color transitions, allowing accurate placement of virtual objects within the real-world scene. additionally, the application utilizes arkit’s brightness sensor to dynamically adjust the brightness of virtual objects based on the surrounding light, ensuring seamless integration with the real environment [17]. to predict the environment, farmerly ar app displays 3d models and texts representing predicted daily conditions, including temperature, humidity, and soil moisture levels which are collected from lorawan end nodes. users can tap on ar elements to see detailed data and predictions 6 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | enhancing precision agriculture: an iot-based smart monitoring system integrated lorawan, ml and ar figure 9. dashboard of farmerly web-based system as in fig. 10. farmerly ar app also had alerts for significant predictions, such as impending adverse weather conditions. farmerly ar application fetched data and forecast from the backend api. real-time data on temperature, humidity, and soil moisture is displayed alongside ml-generated predictive analytics, forecasting the daily conditions of the farm based on historical data. beyond environmental data, this application also visualizes stages of the crop life cycle based on its usual development timeline. this feature allows farmers to see a detailed, augmented representation of crop growth stages overlaid onto the actual field, providing crucial insights into the health and progress of their crops. 4. system evaluation 4.1. experimental setup a. location and crop centella is a herbaceous plant, often growing in humid places and tropical regions such as southeast asia, china, india, sri lanka, central africa... [18]. the ideal growing conditions for centella include nutrientrich alluvial soil with a loose texture that retains moisture and drains well. centella has been grown in different regions of vietnam for commercial production purposes. the most typical regions are in thanh hoa and thua thien hue provinces. quang tho, thua thien hue, vietnam (16°32’06.2"n,107°31’39.7"e) is selected to be the pilot area. this region has the biggest area of centella cultivation, covering over 70 hectares. in 2013, the vietgap centella process of production was officially implemented in quang tho. thua thien hue is a central coastal province with a hot, humid climate, abundant rainfall, and frequent flooding, especially from october to december. each year, in quang tho, centella is usually planted in 3 seasons: spring crop figure 10. arkit plane detection in farmerly ar mobile app (planted in february), summer crop (planted in may) and autumn crop (planted in august) [19], requiring heavy watering initially during the dry, sunny weather. subsequently, the crop is watered every two days. the sample collection demonstration was conducted from january 2023 to april 2024, aligning with centella’s typical growth cycle. a centella crop typically takes 84 90 days from planting to harvest [19], given optimal meteorological conditions (temperatures between 30-32°c, average monthly rainfall below 100 mm, and no flooding). regular soil humidity checks are necessary to ensure proper watering. however, the region’s frequent floods and the characteristics of alluvial soil mean that prolonged submersion in floodwaters can result in a significant layer of mud covering each centella stem. if not harvested promptly, this can lead to crop damage and potentially result in total crop loss for the farmers. b. system configuration 1. end nodes: equipped with stm32f103 microcontrollers, rfm95w lorawan modules, and specialized sensors including temperature, humidity, soil moisture, and nutrient levels tailored for centella growth. 2. lorawan gateway: deployed using esp32 – wifi lorawan boards with integrated lorawan sx1278 chips, strategically positioned to cover centella cultivation areas effectively. 7 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | d. t. huong, et al. figure 11. farmerly web-based system 3. ar interface: accessible through a mobile application developed using arkit, providing centella farmers with a 3d visualization of crop health, growth patterns, and environmental conditions. c. data collection and analysis data collection occurs at high-frequency intervals, with sensors providing readings every 15 minutes. parameters specific to centella cultivation including temperature, soil moisture, humidity, and weather were monitored alongside traditional environmental factors. data was transmitted wirelessly to the lorawan gateway, then processed and analyzed within the smartfarm cloud. algorithms tailored for centella cultivation provided insights into optimal growth conditions and disease prevention strategies. 4.2. ar application a. data for prediction the data was collected daily from january 2023 to april 2024 in quang tho, thua thien hue province, with each sample containing seven features: minimum temperature, maximum temperature, wind speed, wind direction, humidity, cloud cover, and pressure. the entire dataset includes 485 samples. the data is divided into training and testing sets, with samples from january 2023 to december 2023 (365 samples) used for training and model optimization, and samples from january 2024 to april 2024 (120 samples) used for testing. fig. 11 is an example of the system generating a warning signal indicating a potential drought. the data after being learned through the markov chain will be fed into the system. at the same time, based on the given prediction threshold, the system will give warnings to users through the ar application about the data in the next 3 days. the system shows a warning when the sunny weather remains for more than 2 days, the temperature is higher than 33°c, wilting point occurs when soil moisture drops to approximately 15-25% of the soil’s water holding capacity. while centella plants tolerate moisture well, excessive rainfall and flooding can pose risks. when the rainy or storm remains up to 2 days, soil moisture levels above 60% of the soil’s water holding capacity, and waterlogging threshold appears [20]. if the indexes exceed the safe threshold, the system automatically provides a warning to the manager based on checking the set condition in table 2. table 2. conditions to issuing alerts conditions on farms messages shown in farmerly system temperature <33°c. soil moisture >25%; duration > 1 day. your irrigation practices are perfect. continuous monitoring of soil moisture to maintain these optimal conditions. temperature increased >33°c; soil moisture <25%; duration > 2 days. your plants are at risk of entering the wilting point. please irrigate to restore soil moisture. temperature <33°c; soil moisture 2560%; duration > 1 day. your irrigation practices are perfect. no immediate action is required. temperature increased 25-32°c; soil moisture >60%; duration > 2 days. current conditions can be waterlogging. stop irrigating immediately and reduce excess water if necessary. b. crop visualization via farmerly system and ar application the data management system oversees the operations of the smart farm, keeping track of vital details such as temperature, humidity, and soil moisture. in this case, the system is tracking specific to centella cultivation. on the dashboard, users can observe these metrics along with their respective values over time. additionally, the system manages designated regions where centella crops are grown. in the event of adverse weather conditions, the system triggers a farm tracking alert, notifying users to take necessary precautions and enabling users to promptly attend to their centella crops based on real-time weather conditions. the farm’s environmental parameters are recorded at regular 15minute intervals, maintaining consistency throughout the day. the data collected from these measurements is then input into the prediction model. if any serious future fluctuations occur, the model automatically notifies and displays related alerts in the upper right corner of the ar mobile app. the farm displays model also shows areas in the field that are not uniform in the index, e.g. 1/5 areas in the field lack moisture. this 8 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | enhancing precision agriculture: an iot-based smart monitoring system integrated lorawan, ml and ar figure 12. high moisture alerts follow the real weather on the farm enables immediate monitoring and response to changes in the agricultural environment, while also optimizing the management and monitoring processes. rainy weather and indexes on temperature, air humidity, and soil moisture from the farm are shown in real time in fig. 12. when farmers used the ar app to monitor the farm, they gained the ability to visualize every stage of the centella crop’s development. quang tho experiences a tropical climate with distinct wet and dry seasons. ensuring consistent moisture during the dry season and preventing waterlogging during the wet season is crucial. in particular, during the post-harvest period, farmers must pay close attention to providing moisture and nutrients to continue stimulating new roots to grow for the new crop. with this information displayed on the ar application, farmers may have a more comprehensive view of the development stages, such as planting, initial growth, root development, leaf expansion, flowering, and harvesting as shown in fig. 13. for visualization purposes using ar, we collect figure 13. farmerly ar app displays the development stage of the crop the morphological characteristics of the crop in the whole development stages into 5 main stages: (1) seed germination; (2) seedling stage; (3) vegetative growth; (4) flowering stage; (5) fruiting stage. they can make decisions in the field to help centella plants grow strongly and produce high-quality yields in quang tho. the stages displayed in each period of the crop’s development are shown in table 3. 4.3. assessment results by optimizing the rf and lr models using grid search cv and combining 5-fold cv on the 2023 dataset, our machine learning model is optimized and reliable. next, we conducted training. finally, we implemented testing from january 2024 to april 2024. the results show that the rf model correctly predicted 108 out of 120 days (90% accuracy), while the lr model correctly predicted 105 out of 120 days (87.5% accuracy). therefore, we choose rf for the daily weather prediction model on our application. implementing the automatic monitoring, prediction, 9 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | d. t. huong, et al. table 3. life cycle of centella asiatica with time and key factors stage duration key factors influencing stage seed germination first 7-14 days moist soil conditions, optimal temperature (2030°c), shallow sowing seedling stage in 2-4 weeks moisture, light, temperature (2030°c) vegetative growth in 8 12 weeks light intensity, soil quality, consistent watering flowering stage in 16 weeks insect activity, suitable climatic conditions (25-35°c) fruiting stage in 20 weeks environmental factors affecting seed dispersal and warning system significantly expedited farm monitoring tasks, reducing both implementation and decision-making times by 80% compared to traditional methods without the ar application. table 4. aspect and feedback/observation aspect feedback/observation ease of use 90% of farmers found the ar app easy to navigate and use. real-time monitoring 85% of farmers appreciated the real-time data visualization. decision-making 80% reported enhanced ability to make informed decisions. crop growth visualization 88% found growth stage visualization very beneficial. environmental alerts 75% felt timely alerts helped prevent potential issues. accuracy of predictions 82% trusted the accuracy and reliability of predictions. resource management 70% observed improved efficiency in water and nutrient management. system reliability 95% experienced high system reliability and uptime. the ar visualization enabled farmers to make more informed decisions by understanding the precise conditions and needs of their crops at each stage. during the pilot project, interviews were conducted with farmers to gather feedback on their experiences using the farmerly data management system and ar application. the results of the farmer interviews were evaluated and feedback on the system in table 4. this integrated approach greatly improved the scope and accuracy of environmental data collection, which is crucial for making well-informed decisions about agricultural operations. the ability to monitor and predict environmental conditions, combined with the visualization of crop growth stages, allowed farmers to optimize resource usage, anticipate and mitigate potential issues, and ultimately improve crop yield and quality. 5. conclusion in response to the increasing need for precision agriculture, this paper has explored the opportunities and challenges associated with implementing a novel iotbased system for farm management and monitoring. the proposed system integrates long-range wide area networks (lorawan), machine learning (ml), and augmented reality (ar) technologies with iot devices, specifically stm32 family microcontrollers. this combination enhances the way farmers interact with and control their farms, improving the efficiency and reliability of data collection. the primary results indicate that this integrated approach significantly enhances the scope and accuracy of environmental data collection, which is crucial for making well-informed agricultural decisions. the ar interactive interface demonstrated an impressive 87.5% accuracy in facilitating management decisions while reducing both implementation and decision-making times by 80% compared to traditional methods without the ar application. the pilot study conducted in quang tho, vietnam, validated the effectiveness of this integrated approach in predicting key environmental conditions such as temperature, soil moisture, and air humidity, thus enabling proactive and informed decision-making. the system demonstrated high prediction accuracy and significantly reduced monitoring and decision-making times. the combination of lorawan, ml, and ar in iot-enabled smart farm monitoring has proven to be an effective solution for precision agriculture. lorawan allows data to be transmitted over long distances with minimal power consumption, while ar offers farmers real-time insights and visualizations of their crops, providing an immersive and interactive experience. the integration of arkit further enhances the system’s accuracy and usability. this technology has the potential to revolutionize farm monitoring and 10 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | enhancing precision agriculture: an iot-based smart monitoring system integrated lorawan, ml and ar management, leading to increased efficiency and higher crop yields. however, considerations around scalability, cost, and technical challenges need to be addressed for broader implementation. references [1] d. t. anh, p. c. nghiep: smart agriculture for small farms in vietnam: opportunities, challenges and policy solutions, fftc journal of agricultural policy, 09 august 2022), [2] s.sharma, precision agriculture: reviewing the advancements, technologies, and applications in precision agriculture for improved crop productivity and resource management, july 2023, doi: 10.26480/rfna.02.2023.41.45, [3] y.t. ting, k.y. chan: optimising performances of lora based iot enabled wireless sensor network for smart agriculture, journal of agriculture and food research, volume 16, june 2024, 101093, [4] rangra, v., thakur, p. (2024). smart farming: leveraging ai, ml, and iot for enhanced farming and revolutionizing agriculture. bsss journal of computer, 15(1), 54-64, [5] sizan, n. s., dey, d., mia, m. s., layek, m. a. (2023). revolutionizing agriculture: an iot-driven mlblockchain framework 5.0 for optimal crop prediction. in 2023 5th international conference on sustainable technologies for industry 5.0 (sti), dhaka, bangladesh, 09-10 december. ieee, [6] rahman, a., xi, m., dabrowski, j. j., mcculloch, j., arnold, s., rana, m., george, a., adcock, m. (2021). an integrated framework of sensing, machine learning, and augmented reality for aquaculture prawn farm management. aquacultural engineering, 95, 102192, [7] d. sembroiz, s. ricciardi, d. careglio: a novel cloudbased iot architecture for smart building automation, security and resilience in intelligent data-centric systems and communication networks, intelligent datacentric systems, 2018, 215-233, [8] e.t. bouali, m.r. abid, e.m. boufounas, t.a. hamed, d. benhaddou, renewable energy integration into cloud iotbased smart agriculture, ieee access, 10 (2022), pp. 11751191, 10.1109/access.2021.3138160, [9] e. fazel, m. z. nezhad, j. rezazade, m. moradi, j. ayoade: iot convergence with machine learning & blockchain: a review, internet of things, volume 26, july 2024, 101187, [10] j. e. rayess, k. khawam, s. lahoud, m. e. helou and s. martin, study of lorawan networks reliability, 2023 6th conference on cloud and internet of things (ciot), lisbon, portugal, 2023, pp. 200-205, [11] alan b. craig: chapter 1 what is augmented reality?, understanding augmented reality, morgan kaufmann, boston, 2013, 1-37, [12] b. rashid, m. h. rehmani.: applications of wireless sensor networks for urban areas: a survey. journal of network and computer applications (60), 192-219 (2016), [13] a. yusri and m. i. nashiruddini: lorawan internet of things network planning for smart metering services, 2020 8th international conference on information and communication technology (icoict), yogyakarta, indonesia, 1-6, (2020), [14] jones, nicola. "how machine learning could help to improve climate forecasts." nature 548.7668 (2017). [15] bochenek, bogdan, and zbigniew ustrnul. "machine learning in weather prediction and climate analyses—applications and perspectives." atmosphere 13.2 (2022): 180, [16] chen, liuyi, et al. "machine learning methods in weather and climate applications: a survey." applied sciences 13.21 (2023): 12019, [17] zainab oufqir, abdellatif el abderrahmani and khalid satori: arkit and arcore in serve to augmented reality, 2020 international conference on intelligent systems and computer vision (iscv) ( 09-11 june 2020), [18] rosalizan, m. s., rohani, m. y., khatijah, i., shukri, m. a. (2008), physical characteristics, nutrient contents and triterpene compounds of ratoon crops of centella asiatica at three different stages of maturity, journal of tropical agriculture and food science, 36(1), 43-51, [19] n.q.co, h.t.quang, t.t.h.hai, effect of some farming factors on growth and yield of in vitro centella (centella asiatica (l.) urban) in quang tho commune, thua thien hue province, hue university journal of science: agriculture and rural development, vol. 133 no. 3a (2024), [20] thao thi phuong tran et al: comparison of organic and conventional production methods in accumulation of biomass and bioactive compounds in centella asiatica (l.) urban, back toagriculture and food chemistry, 21 november 2023, 11 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | 1 introduction 1.1 the integration of iot and other technologies 1.2 our approach 2 system architecture 3 pilot implementation 3.1 lorawan nodes and gateway for data transmission 3.2 data management and processing hub 3.3 machine learning-driven weather forecasting 3.4 augmented reality integration for interactive farm monitoring 4 system evaluation 4.1 experimental setup 4.2 ar application 4.3 assessment results 5 conclusion this is a title eai endorsed transactions on smart cities research article 1 editorial: welcome to the second issue of volume 7 of the eai endorsed transactions on smart cities dario vieira 1 1 associate professor, efrei paris, france received on 01 october 2023, accepted on 06 october 2023, published on 09 october 2023 copyright © 2023 d. vieira et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.4106 the smart city paradigm evolves alongside upcoming communication technologies like 6g, artificial intelligence (ai), security and the internet of everything (ioe). smart cities leverage these technologies to create intelligent and sustainable living environments, enhancing citizens' quality of life and optimizing resource management. we can identify two main foundations for supporting smart cities, but also some challenges. one of the primary foundations for supporting smart city applications is the network infrastructure, which will integrate connected devices regarding the internet of everything (ioe). this integration facilitates real-time data collection and analysis, enabling informed decision-making, such as monitoring environmental conditions for optimized energy consumption and waste management. in this regard, communications networks play an important role in smart cities, with promising high data rates when transitioning from 5g to 6g and more reliable connectivity for real-time data exchange between devices, sensors, and systems, enabling applications like autonomous vehicles, smart grids and robotics. the second foundation is ai, which empowers systems to analyse vast data and optimize traffic flow, energy consumption, and personalized services. the ai also takes place in network management, contributing to optimizing power consumption and energy efficiency, which are crucial goals achieved through intelligent energy management and energy-efficient infrastructure, contributing to a greener and more sustainable urban environment and network resource management. finally, ai has become an essential part of many services and applications regarding smart transportation and e-health services, through digital technologies, telemedicine, wearable health devices and personalized care. alongside these previously presented foundations, there are other vital concerns for smart cities. as cities offer increasing connectivity, robust cybersecurity measures become paramount to protect sensitive data and infrastructure in an interconnected environment. there is also an increasing concern about data security and sharing. this is due to the increasing amount of generated data considering the vast network infrastructure and many data-oriented applications. in addition, environmental sustainability is also critical, requiring adopting practices to reduce their ecological footprint and promote cleaner environments through realtime monitoring and renewable energy use. furthermore, ai can be combined with robotics to facilitate human-robot interaction, with robots, for example, participating in labourintensive tasks in industries. another critical challenge for smart cities is the accelerating urbanization. furthermore, there has been an increasing concern about sustainability in recent years, considering the population increase in urban areas. 70% of the world's population is expected to live in urban environments by 2050. this massive urbanization might present different characteristics in low-income countries compared to the high income, which requires other solutions to the upcoming issues. this difference also allows researchers to conduct their research focusing on different use cases while addressing concerns on sustainable development. the rapid evolution in these domains, coupled with the growing number of variables to be managed and the constantly expanding demands of users and applications, presents attractive and challenging research prospects. collaboration between experts from various domains is becoming ever more mandatory. in this regard, the eai endorsed transactions on smart cities, in its second issue of volume 7, brings high-quality papers with successful research and lessons learned in investigating architectures, techniques, technologies and applications for smart cities. therefore, throughout the different articles, the reader will recognize the effort of the researchers and the solid collaboration for the level of quality of this issue, where the authors dare to invite us to understand the challenges and the complexity of creating smart cities and, above all, to present us their innovations in this area. i want to thank the eai eai endorsed transactions on smart cities | volume 7 | issue 2 | https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ d. vieira 2 endorsed transactions on smart cities team for giving me the honour of writing the preface for volume 7 of issue 2. i am honoured to encourage others to join me in reading the following pages. congratulations to the authors who have made a unique collaborative effort in writing and sharing their analysis and results. finally, for all readers, if you are familiar with all these issues, be ready to let your mind distinguish between what is usual and what is innovation. for beginners, are you prepared to enter this world where we go a step further in the future and see what’s coming next? be welcome. eai endorsed transactions on smart cities | volume 7 | issue 2 | smart tourism ecosystem perspective on the tourism experience: a conceptual approach eai endorsed transactions on smart cities research article 1 smart tourism ecosystem perspective on the tourism experience: a conceptual approach vaz serra p.1,2*, seabra c.1,2 and caldeira a.1,2 1university of coimbra, portugal 2cegot – geography and spatial planning research centre, portugal abstract the smart tourism ecosystem concept, in addition to integrating various components, processes, and actions in the design of a place, advocates certain results through the convergence of technological resources, business environments, and valueinducing experiences. this conceptual paper should result in theoretical contributions regarding the specificity of the tourist experience within the framework of a smart tourism ecosystem, with a view to the competitiveness and sustainability of accommodation and destinations. from the perspective of a smart tourism ecosystem, the production and consumption of tourist value − which, hopefully, should be socially, culturally, environmentally, and economically sustainable −, is shared, and generate distinctive experiences, and the corresponding interactions are promoted by technology, through the collection, processing, and communication of data. the suggested approach has relevant implications at the management level, given the need to obtain differentiating factors, mediated by technology, with the incorporation of added value for the stakeholders. keywords: smart tourism ecosystem, tourism experience, value co-creation. received on 16 november 2022, accepted on 16 december 2022, published on 27 december 2022 copyright © 2022 vaz serra p. et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.v6i4.2857 1. introduction the tourism experience, with its multidisciplinary nature, as well as its remarkable and structural contribution to the evolution of tourism, namely to the competitiveness and sustainability of accommodation units [1] and destinations [2], has taken on increasing importance in the literature [3]. associated with the tourist experience, the concept of a smart tourism ecosystem emerges [4], which, in addition to integrating various components, processes, and actions in the design of a place, advocates certain results through the virtuous convergence of technological resources, business environments and value-inducing experiences [5]. smart tourism ecosystems are systems of actors that aim to (i) use pre-existing technology and institutions for the co-creation of value, in the short term; (ii) create *corresponding author. email: pedrovazserra@hotmail.com technologies, through innovation, or new institutions — praxis, social rules, values — in the long term [6]. a smart tourism ecosystem is, therefore, a tourism system that takes advantage of smart technology in the creation, management, and delivery of smart tourism experiences and is characterized by intensive information sharing and value co-creation [4]. considering the relevance of the combination between the tourism experience and the perspective of a smart tourism ecosystem — where the relationship between decision-making and interaction processes, as well as its influences and outcomes, is highlighted [7] —, this conceptual approach proves to be opportune for the concepts it incorporates and theoretical relevant for the current and prospective scenarios it enshrines. the suggested approach, supported by literature review, has relevant implications at the management level, given the need to obtain differentiating factors, with the incorporation of added value for the parties involved, eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e3 https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:pedrovazserra@hotmail.com vaz serra p., seabra c. and caldeira a. 2 capable of achieving and renewing balance between supply and demand, using technology, which today is unavoidable. the structure of the paper contemplates the conceptual approach to the tourism experience, followed by the highlighting of the transition from a product/produceroriented view to a service-oriented one, linked to the perspective of the smart tourism ecosystem, and its relationship with the tourism experience, before the concluding remarks. 2. the tourism experience currently, several authors contribute to the evolution of the concept of tourist experience (see table 1). table 1. tourism experience: evolution of the concept nowadays (2007-2015) source: [8] – adapted. reference concept [9] the past, personal, travel-related event that is sufficiently memorable to enter long-term memory [10] it results from a model, classified into four dimensions: pleasure, rediscovery, authenticity, and knowledge [11] it stems from micro-oriented structures, psychological, and macrooriented models, sociological for [9], experience translates into ascendancy in consumers, even to the detriment of the products or services themselves, or diluting them [12], and, in the same sense, neuroscience suggests that consumers are less driven by functional arguments rather than internal sensory and emotional elements [13]. the work of [10] stands out for its attempt to understand the process of experience itself as a precursor of experiences. for [11], studying experience implies understanding the meaning that the cultural norms of a group offer to the individual, as a way of interpreting and approaching its purpose and significance [8]. thus, as experiences are personal, i.e., they occur in the individual's body and mind, the result depends on how the consumer, contextualized by a specific situation and mood, reacts to the enacted encounter [14]. as for the dimensions of the tourist experience, investigations are usually structured in their phases, influences, and outcomes [15]. in this sense, the model developed by [16] and applied to tourism [17][18] constitutes an essential reference, which includes five distinct but related phases: anticipation, travel to the destination, activity at the destination, return trip, and remembrance, bearing in mind that reading and the effect of experiences change over time [19] and, therefore, must be approached from a multiphase perspective [20]. however, in addition to the multiphase nature, personal influences and outcomes must be considered, as the traveller arrives at a destination with ideas about the types of experiences that can occur, resulting from the social construction of an individual and that can include information, or perceptions, taken from communication networks and digital channels, product images, expectations, knowledge and previous travel experiences, in addition to activities in which it participates and the types of interaction, with various environments and social dynamics, even informal, which occur [21][22]. thus, [15] propose a conceptual model of influences and outcomes of the tourist experience (see figure 1), considering that this corresponds to what happens during a tourist event. figure 1. influences and outcomes of the tourist experience. source: [15] – adapted. in this model, which comprises their phases, considering that the experience is planned before a trip takes place and remembered long after it has ended, with the assumption that, during the outward trip, the tourists can still be involved in the process of developing expectations, in the same way, that, when returning, they can reflect on what they experienced [15]. considering the models and theoretical foundations, a conceptual framework emerges that includes personal and internal factors, but also influencing and external factors, which interact at various stages [15]. this framework influences the perception of the global tourist experience, i.e., the process in which the stimuli related to experience are processed, organized, and interpreted, and knowledge of internal factors is considered fundamental to effectively managing external factors [9]. thus, the most relevant influences are the physical environment, the staff, other tourists, and the products available [23][21], from which the complex nature of tourist experiences can be inferred. therefore, the tourist experience — which constitutes the core of most products and services offered by eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e3 smart tourism ecosystem perspective on the tourism experience: a conceptual approach 3 hospitality and tourism companies [24] and creates a competitive advantage that is difficult to imitate and replace [25] — can encompass cognitive, sensory, affective, and social dimensions, likely to be pleasant, exciting, satisfying, and meaningful [26] [27]. 3. redefining services and value exchanges with the aim of redefining services and value exchanges, the evolution from a product/producer-oriented view to a service-oriented one led to the development of various theories of service [28]. the service-dominant logic [29] and the service science [30], later named general theory of science, management, and service engineering, are of particular importance, having identified, from different angles and with an impact on organizational configurations, the main elements involved in the exchange of services. in the service-dominant logic [29] three concepts are presented, through a service-for-service view: i) service and the relationship between goods and services; ii) the customer-supplier relationship; iii) the value. the exchange of services, which generates benefits for all actors, stems from the resources of each stakeholder, with users being considered active participants, actor-to-actor, and, as such, resource integrators that shape service delivery depending on the specific context [29]. thus, from the service-dominant logic, the co-creation of value is the result of the exchange of resources, according to a participatory approach, in which users are, at the same time, producers and consumers and become determinants of a value that is no longer be produced exclusively by the suppliers [6]. in turn, service science represents an application of the main premises of the service-dominant logic, where the practices, as well as their implications, for the implementation of new service systems are revealed [30]. service science, an interdisciplinary research stream, advances in the elaboration of models for the application of scientific principles to the provision of services, promoting the creation of new knowledge to improve the planning and management the delivery, in terms of productivity, effectiveness, and efficiency [30]. thus, service systems emerge on the provision of services and the exchange of resources, which emphasize the role of technology [6], later renamed smart service systems, precisely given the widespread impact of information and communication technologies (ict). and emerge also smart service ecosystems (see figure 2), which define the social bonds underlying co-creation, i.e., to the system, the focus is on technology, and to the ecosystem, is on the social [6]. figure 2. integrated framework for a smart service ecosystem. source: [6] – adapted. so, systems allow a micro analysis of service-forservice exchanges, and interactions between users who share information through technology [6]. in turn, ecosystems have a macro perspective, of the global interactions of the network between the different social systems, expanding the field of vision, including social prerequisites, i.e., the promoters of the exchange of synergistic resources that, in the long term, can generate value co-creation and new knowledge [6]. smart service systems are conceived as organizational models that benefit from the application of modern technologies to the design and delivery of services, to promote real-time interactions, accelerate co-creation processes and induce systematic innovation, based on renewal, continuous improvement, and exchange of knowledge [31], and they optimize their goals through selfconfiguration, to enable lasting behaviour, capable of satisfying all the members involved [31]. the vision of ecosystems, in turn, adopts two perspectives [29]: i) reductionist, which identifies the vectors of value co-creation; ii) holistic, which considers the emergence of innovation at a broader level and considers the importance of social norms in the formation of exchanges and in the generation of new value. based on the aforementioned fundamentals and models, the transposition tot tourism is carried out, with four key dimensions of a smart tourism ecosystem — human, technological, social, and interactive — which is made up of: i) actors, who exchange skills, experiences and knowledge; ii) institutions, which promote the integration of resources, based on a common set of social arrangements; iii) technology, which generates and renews social arrangements [4]. in summary, smart tourism ecosystems are systems of actors that aim to i) use pre-existing technology and institutions for the co-creation of value, in the short term; ii) create modern technologies, through innovation, or new institutions, praxis, social rules, values, in the long term [6]. eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e3 vaz serra p., seabra c. and caldeira a. 4 4. the smart tourism ecosystem perspective smart business networks are an integral part of the smart tourism system as, with the destination and smart technology infrastructure, they form a smart tourism ecosystem [4]. a smart tourism ecosystem is constituted (i) by systems, which include actors, who exchange resources with each other; (ii) by institutions, which promote the integration of resources, based on a common set of social arrangements; (iii) by technology, which generates and renews social arrangements [4]. tourists, who use technology to explore the resources of this ecosystem, actively contribute data inherent to their movements, consultations, and uploads, and thus integrate their key actors, such as operators, the government, residents, and means of communication, among others [4]. the resources that actors own, and exchange between can be (i) tangible or intangible, such as tools, software, and information; (ii) human, such as skills, knowledge, and virtual communities; (iii) relational, between partners and suppliers — any stakeholder is an actor with the objective of interacting and exchanging resources with other actors for the co-creation of value [32]. a smart tourism ecosystem is, therefore, a tourism system that takes advantage of smart technology in the creation, management, and delivery of smart tourism experiences and is characterized by intensive information sharing and value co-creation [4]. to unleash innovation and support productivity in the business ecosystems themselves, it is essential to recognize their insertion in communities and the creation of shared value that, at the same time, allows for increased competitiveness and the improvement of economic and social conditions [33]. thus, there are four dimensions of a smart tourism ecosystem — human, technological, social, and interactive [6]. an ecosystem implies, among other principles, the existence of a shared objective [34], here related to the production and consumption of tourist value, culminating in significant tourist experiences. economic and environmental sustainability are also inherent priorities at the system level, as these resources are essential for its viability. thus, the shared objective is the availability of enriched, high-added value, meaningful and sustainable tourist experiences [35]. by enabling a plug-and-play business environment, the ecosystem facilitates continuous and open innovation, as new service providers can connect and add value to the network, in a permanent and fluid way [36]. thus, the collection, processing, and exchange of tourism-relevant data — that is, the informatisation of tourism because of the integration of smart technology [37][38] — is a central function of the ecosystem. however, the ecosystem, although centred on tourism, includes a variety of elements that integrate it and go beyond it, such as (i) tourist and residential consumers; (ii) tourism providers; (iii) tourism intermediaries, such as tour operators and agents; (iv) support services such as telecommunications, banking/payment services, platforms, and social networks; (v) regulatory bodies and ngos; (vi) carriers; (vii) technology and data companies; (viii) consulting services; (ix) tourist and residential infrastructure, such as swimming pools, parks, museums, among others; (x) and companies normally attributed to other sectors, such as medical services, or commerce [4]. given the opportunity, actors proactively seek advantages from value creation and new actors enter, or emerge, from the cross between them. it thus becomes evident that it is extremely difficult to delineate the limits of a smart tourism ecosystem — the socalled bioblitz, the activity aimed at identifying and counting species in an ecosystem, appears to be useful, but difficult to achieve in its fullness [4]. although the smart tourism ecosystem corresponds to a fluid and heterogeneous set of connections and interactions, tourists have a crucial role, as co-creators, highlighting the main objectives to be achieved in relation to them, (i) anticipation of their needs, with the ability to make suggestions for context-specific activities, such as points of interest, meals, and recreation; (ii) improving experiences by providing information, personalized and location-based interactive services; (iii) allowing and encourage the sharing of their experiences, interfering in the decision-making process of others, but also reliving and reinforcing experiences, as well as building their own image on social networks [39][40]. on the side of companies and other stakeholders, expectations regarding the benefits of the ecosystem lie in (i) process automation; (ii) efficiency gains; (iii) development of new products; (iv) demand forecast; (v) crisis management and, in general, (vi) value co-creation [39][40]. in this context, tourists assume the role of active participants in its creation because, in addition to consuming, they also create, comment on, or improve data, which constitute the basis of the experience, for example through photographs or videos, using their digital self. to access destination information infrastructure or add value through mobile computing [32]. among these elements, digital ecosystems stand out, characterized by an open, flexible, demand-driven, interactive network and collaborative architecture [41], focused on interactions between technological elements — such as devices, databases, or programs — and related information flows, forming the infrastructure for digital business ecosystems [42]. technological advances, which allow system interoperability and the dynamic exchange of information, are fundamental to establishing interconnectivity, from the ecosystem perspective [4]. thus, the digital ecosystem, in the context of tourism, is described as a smart tourism system, which supports autonomous nodes, with dynamic network configurations, in heterogeneous and distributed environments, which supports flexible communication and allows access to eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e3 smart tourism ecosystem perspective on the tourism experience: a conceptual approach 5 information at any location. anywhere and anytime, covering complete consumer lifecycles and all business phases, with different users [4][32][43]. technology, increasingly evolved and sophisticated, appears, also in the smart tourism ecosystem, to have enormous and wide-ranging potential, such as, for example, the use of small unmanned aerial vehicles [44][45][46][47][48]. 5. a smart tourism ecosystem perspective on tourism experience smart tourism is also a social phenomenon, resulting from the convergence of icts with the tourist experience [49], whose co-creation process corresponds to the sum of the psychological events that a tourist goes through when actively contributing through physical and/or mental participation in activities, and interacting with other subjects in the experience environment [40][41]. the smart tourism experience, where meaning is enhanced, is identified with the purpose of the dynamically interconnected actors that make up a smart tourism ecosystem, translated into access, or improvement, of differentiating, meaningful and sustainable experiences, guided by the digitization of key business processes and organizational agility [37]. in fact, the smart tourism experience, where meaning is praised, is identified with the purpose of the actors, dynamically interconnected, that integrates a smart tourism ecosystem, translated into the access, or improvement, of differentiating, significant and sustainable experiences, guided by the digitization of key business processes and organizational agility [37[50]. therefore, its technological base is unavoidable, as the experience is improved, or optimized, through smart technology, associated with wi-fi/mobile connectivity and big data, which allows recommendations enriched by meaning, identified with the context and value aggregators [37][50]. it should be noted, however, that the integration of a single technology, within an accommodation or tourist destination, will not be enough to make it a smart destination, requiring a multifaceted construction of intelligence to create value for stakeholders and increase competitiveness [51]. thus, the smart tourism experience is characterized by being mediated by technology [4][37] and optimized through personalization, awareness of context and realtime monitoring [52]. it is important, therefore, to recognize active participation and interaction in co-creation experiences, considering that local tourism experiences involve parts connected in multiple ways — emotional, cognitive, physical, and social —, in proximity and intensity [41]. in this context, products and services are dynamically designed and structured by companies and users, creating differentiating markets and experiences, highlighting that a smart tourism system is built on trust, scalability, and openness toward participants and services [4]. it should be noted that, although the literature consecrates the importance of a differentiated tourist experience and, therefore, value-generating [52], there are few approaches to the potential cognitive overload and the effort required to navigate a smart destination scenario, where not all tourists have the skills, or desire, to constantly interact with information. other equally prominent issues are related to security and privacy [53][54], as well as excessive exposure to and dependence on technology, not least because of locationbased services that, especially useful for travellers, make them vulnerable, although privacy in tourism is a special case, as the interaction with suppliers and, therefore, with their applications is usually of short duration, which limits the construction of a process of trust, which is often underestimated [55]. it should also be noted that the issues of trust and privacy — in addition to the digital divide, which not only applies to consumers but also to tourism providers [49] — underlying the smart tourism info structure, are complex and require knowledge investment, control, and responsibility [49]. advanced technology and contemporary innovations encourage suppliers and users to implement solutions against malicious attacks, leading to the provision of new dynamic provisioning, monitoring, and management of it capabilities [56]. in fact, information security receives attention from both academia and industry for the purposes of prevention, integrity, and data modification, with traditional and mathematical security models being implemented to deal with information-related issues, with computational intelligence emerging as a security technique, inspired in biological development [57]. a more critical perspective on smart tourism experiences, more information on the psychological and health risks of permanent exposure to data from contextsensitive systems, and insights into consumer attitudes towards the various aspects of smart tourism, including its willingness to cooperate and create, as well as its willingness to enjoy such processes and the real dimensions of the use value generated by consumers [32]. although with some latent limitations, or concerns, smart tourism is a promising scenario, which results in more convenient, safe, exciting, and sustainable living spaces for residents and tourists; more personalized and therefore more relevant tourist experiences; and even greater opportunities for new services, business models and markets to emerge because of more flexible structures and different perspectives on value creation [56]. 5. concluding remarks the tourism experience is a by-product of service design, since its precise determinants are not entirely under the control of the designer [8], and the empowerment of eai endorsed transactions on smart cities 10 2022 01 2023 | volume 6 | issue 4 | e3 vaz serra p., seabra c. and caldeira a. 6 consumers — as co-creators of their experiences, a notion to which companies desirably seek to respond — driven by icts, transform the role of consumers in the development, consumption, and experience of products and services. with the internet and web 2.0. — the tools associated with social networks generate unprecedented opportunities for consumer involvement along the value chain — to emerge as catalysts for change that, in addition to impacting the way companies and consumers interact, also transform the way [41][52]. increasingly, companies and consumers collaborate with each other [57], with co-creation being a customercentric approach based on the principle of putting the consumer first and recognizing him as the starting point of the experience. and value creation [29]. the smart tourism experience, where meaning is praised, is identified with the purpose of the actors, dynamically interconnected, that integrates a smart tourism ecosystem, translated into the access, or improvement, of differentiating, significant and sustainable experiences, guided by the digitization of key business processes and organizational agility [4][51][52]. the suggested approach will have relevant implications at the management level, given the role of the various stakeholders, and active participants in the co-creation of the experience, using their digital selves to access information infrastructure and/or add value. the development of smart tourism is ongoing. in many ways, it evolves naturally from the widespread adoption of ict in tourism. however, systematic, and widespread coordination and sharing, as well as the exploitation of tourism data for value creation, is still in its infancy. the crux at this point is building viable smart tourism ecosystems [50], and the complexity of tourism makes it difficult to go beyond the specific platform service innovations. however, the technological push towards smart tourism is far-reaching and tourism is expected to provide the scenario that makes possible the pioneering of many of these smart technologies [35]. however, ecosystems cannot be created [4], as we are dealing with open and flexible structures that evolve over time. implementing a smart tourism destination requires patience, strategic management, and continuous evaluation and change. perceiving the destination as an ecosystem is essential, with the vision and a clear set of objectives for innovation being key enablers for smart tourism destinations. these developments require the formation of new models of travel behaviour, new models of product design [58][59], and new models of research and evaluation which, in turn, establish a new paradigm of tourism management [60]. acknowledgements. this research received support from the geography and spatial planning research centre (cegot), funded by national funds through the foundation for science and technology (fct) under the reference uidb/04084/2020. references [1] henrique de souza l, kastenholz e, barbosa m de l de a. relevant dimensions of tourist experiences in unique, alternative person-to-person accommodation—sharing castles, treehouses, windmills, houseboats or house-buses. international journal of hospitality & tourism administration. 2020 oct 1; 21(4):390–421. available from: 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accepted on 03 11 2024; published on 13 11 2024 keywords: multimodal learning, sentiment analysis, natural disaster, natural language processing, image processing copyright © 2024 s. dursun and s. eken, licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi:10.4108/eetsc.5860 1. introduction with the advent of the internet, social media platforms in particular have become multimodal, with content containing text, audio, images, and videos to evoke different emotions of a user. the increasing popularity of social networks and the tendency of users to share their emotions, expressions, and thoughts in text, visual, and audio content have created new opportunities and challenges in sentiment analysis [1]. while sentiment analysis from texts has been widely researched in the literature [2–5], sentiment analysis from images and videos is relatively new. within the scope of this study, we focused on the joint analysis of visual and textual content in a socially important area and examined the effect of different visual features together with contextual text representations for multimodal tweet sentiment classification. ∗corresponding author. email: suleyman.eken@kocaeli.edu.tr based on the approach of “a picture is worth a thousand words”, visuals are an effective tool to convey not only facts but also clues about feelings and emotions. such clues representing emotions and thoughts can trigger similar emotions in the observer and help understand visual content beyond textual concepts in different application areas such as education, entertainment, advertising, journalism, and smart cities [6]. however, it is not entirely clear how such emotional cues can be evoked by visual content and, more importantly, how emotions derived from a scene can be expressed by an automatic algorithm. in this context, the proposed system and the analyses performed; it is thought to contribute to different stakeholders such as news publishers, agencies, social/digital media content producers, humanitarian organizations, and the general public [7]. in recent years, a number of major natural disasters such as earthquakes, hurricanes, forest fires, and floods have been experienced in different parts of the world, 1 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:<suleyman.eken@kocaeli.edu.tr> s. dursun and s. eken as well as in our country. in these difficult times, social media plays a key role in disseminating information about the damages incurred in these disasters [8]. within the scope of this study, multi-modal sentiment analysis of disaster images shared on social media, which is considered to be an important area in terms of social sensitivity, and the sentiments in the texts shared with the images, was carried out with a threelayer deep learning model. the data set collected from social media within the scope of multimodality (image and text) will provide a benchmark for future research in this field, and the presented analysis model can be used in other fields through transfer learning. the remaining part of the paper is organized as follows: in the 2nd section, the relevant studies are mentioned, in the 3rd section, the visual and textual features are explained. in the 4th section, the performed tests are given, and conclusion and future works are mentioned in the last section. 2. related works in recent years, multimodal learning has trended upward in ai applications as researchers integrate data in different modes/types into modeling, such as text, images, speech, etc [9]. to achieve the best results. matrix factorization methods are among the preferred methods for multimodal data setup. some of the common methods that have been shown to be useful in learning representations of entities from a collection of matrices are collective matrix factorization, data fusion with matrix factorization, and deep collective matrix factorization. these methods learn entityspecific representations for entities across rows and columns of matrices and use them to reconstruct the matrices. however, these methods expect the input to be a collection of matrices and tensors are not supported. jayagopal et al. [10] overcome this limitation in their proposed model by combining the reconstruction capabilities of matrix factorization and the ability of convolutional autoencoders to operate on tensor inputs. thus, with the proposed architecture, it can jointly learn representations for entities based on inputs (matrices or tensors) of any size. joint representation learning in the multimodal domain occurs in different ways. the first group of works optimizes an image encoder and a language decoder for the image captioning task and transfers the learned visual representations to subsequent applications. the second group jointly learns multimodal pretext tasks, such as reconstructing masked image regions and language symbols/tokens, as well as directly estimating the alignment between image and text. the cross-modal attention modules that arise in these methods cause them to be less efficient in practical retrieval systems. the third group, closer to the contrast methodology in visual representation learning, uses dual encoder architecture to directly map image and text data into a common embedding space. here, the agreement between paired samples is maximized while the agreement between unpaired samples is minimized. however, recent studies focus on data scale and model architectures, using state-of-the-art multimodal contrastive learning frameworks such as convirt [11] and clip [12], which relax the driving force between negative pairs (relaxation of contrastiveness) in pretraining, are used [13]. sentiment analysis studies conducted on social media data refer to a field that aims to determine the emotional state of text, visuals and other content shared on social media platforms. this type of analysis can serve many different purposes. for example, within marketing and advertising it can be used to understand people’s emotional reactions to products, services or brands, to better target marketing strategies and increase customer satisfaction. again, in the field of social monitoring, it is possible to monitor the general mood about a particular event or issue on social media and use this information as an alternative to public opinion surveys. studies in this field are becoming increasingly important with the growth of social media platforms [14]. sentiment analysis works often use natural language processing (nlp) techniques. these techniques process text data, trying to detect specific sentiments or sentiment intensity. sentiment analysis has been extensively explored for textual social media data, with previous dictionary-based approaches evolving into statistical and machine learning-based classification over the last decade. sentistrength [15] is a well-known dictionary-based approach for short texts created using words and expressions commonly used on social media. later, senticircles [16] is developed for twitter sentiment analysis by taking into account the co-occurrence of words in tweets in different contexts. with the proliferation of deep learning, sequential models such as convolutional neural networks (cnns) and long short-term memory (lstm) networks have been successfully used for tweet sentiment classification. with the increase in image and video data on social media sites such as instagram, flickr and twitter, visual sentiment analysis has recently begun to attract great attention. techniques in this scope can be generally divided into two as midlevel and deep learning representations. using the power of pre-trained cnns, you et al. [17] fine-tuned networks for binary sentiment classification on flickr and twitter image datasets. they later extended the visual sensitivity problem to sentimental image content analysis to predict sentiments such as amusement, anger, awe, fear, sadness, and excitement [18]. recently, jiang et al. [19] proposed another attention mechanism in which they use both cross-modal attention fusion and 2 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | multimodal sentiment analysis in natural disaster data on social media modality-specific cnn-transitive feature extraction to learn a better representation. they used imagenet [20] pre-trained resnet [21] for visual features, and glove [22] and bert [23] for textual features to achieve the best results on the mvsa dataset. bica et al. [24] combined textual and visual content in their study, examined geotagged images on social media published during two major earthquakes in nepal in april-may 2015, and focused on identifying the damages associated with them. sit et al. [25] analyzed tweets to identify and categorize fine-grained details about a disaster, such as affected individuals, damaged infrastructure, and interrupted services, as well as to distinguish domains and time periods and the relative importance of each category of disasterrelated information in space and time. hassan et al. [26] proposed a deep visual emotion analyzer that covers different aspects of visual sentiment analysis, starting from data collection, annotation, model selection, application and evaluations for disaster-related images. competitions focusing on visual sentiment analysis on natural disasters are also organized [27]. niu et al. [28] introduce a multi-view sentiment analysis dataset (mvsa) including a set of image-text pairs with manual annotations collected from twitter. mvsa can be utilized as a valuable benchmark for both single-view and multi-view sentiment analysis. in this study, multimodal sentiment classification from natural disaster data on social media is discussed by combining text and visual content. the use of textual representations together with the sentimental expressions of the visual content provides a more comprehensive analysis. to investigate the impact of high-level visual features, a three-layer neural network is used in the study, where the first two layers collect features from different modalities and the third layer is used for classification of sentiments. 3. material and methods the human brain consists of neural networks that can process multiple modalities simultaneously. for example, when a conversation is held, the brain’s neural networks process multimodal input (sound, image, text, smell). after a deep subconscious modality fusion, we are able to reason about what our conversational interlocutor is saying, his emotional state, and our environment. this approach allows for a more holistic view and deeper understanding of the situation. within the scope of artificial intelligence’s quest to imitate human intelligence, it is an inevitable fact that artificial intelligence will learn to interpret, reason and combine multimodal information to match human intelligence. in this study, studies are carried out on a deep learning model that perceives the world more holistically with multi-modal analyzes within the scope of text + figure 1. architecture for multimodal sentiment learning image. the main idea under multimodal classification is to use different types of high-level visual features and combine them with a textual model. the used architecture is shown in figure 1 and it is basis on semlnn [14]. it combines several visual features with contextual text features to predict the overall sentiment accurately. the detailed information of the architecture are explained in the subsections. 3.1. visual features visual features within the scope of the study; it is examined in four categories: object features, place and scene features, facial expressions, and effective image content. object features. object features refer to the attributes or characteristics that can be used to describe and identify an object. these features can be derived from various sensory inputs, including visual, tactile, auditory, and more. in the context of visual perception and computer vision, object features primarily involve characteristics that can be observed and analyzed from images or visual data. different objects in an image can evoke a certain sentiment in a person. for example, while the destructive effect of the earthquake may evoke a negative emotion, objects that involve humanitarian aid organizations providing aid to earthquake-affected citizens (tents, aid parcels, volunteer helpful communities) may evoke a positive emotion. a pre-trained resnet model on imagenet is used to encode objects and overall image content. resnet-50 and its final convolution layer are used instead of object categories (last layer) to extract features. place and scene features. place and scene features in visual perception refer to the attributes that characterize entire environments or contexts, rather than individual objects. these features help in understanding the broader context of a visual scene, such as the type of location, the overall layout, and the relationships between various elements within the scene. a scene or 3 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | s. dursun and s. eken place can also evoke different sentiments in people. as can be seen from the dataset prepared within the scope of the study, while people stranded in a flood disaster can evoke a negative emotion, the aid teams that come to save these people with boats can evoke a positive emotion. to encode the scene information of an image, resnet-101 architecture pre-trained on places365 [29] is used. facial expressions. facial expressions are a subset of visual features that convey emotions, intentions, and reactions. they are crucial for social interactions and communication. the presence of faces and facial expressions (such as smiling and sad) in an image can also affect an observer’s emotions. in the images in the prepared data set, it is observed that facial expressions have a direct effect on the intensity of emotion in data containing facial images. pre-trained large ensemble-based convolutional neural networks [30] are used to encode facial expression information. within the scope of these networks, ensembles with shared representations based on convolutional networks [31] have been studied to quantitatively and qualitatively demonstrate their data processing efficiency and scalability to large-scale facial expression datasets. in this study, facial expression analysis achieves human-level performance, outperforming state-of-theart methods in facial expression recognition using emotion and affect concepts. effective image content. effective image content as visual features refers to the attributes and elements within an image that make it engaging, informative, and aesthetically pleasing. these features contribute to the overall impact and communicative power of an image. overall effective image content may also be important for multimodal emotion detection. this field has made rapid progress in recent years, with datasets taken from popular social media image sharing platforms such as flickr and instagram. to encode the overall emotion, a resnet-50 imagenet model is first fine-tuned on the publicly available fi (flickr & instagram) dataset, and last layer convolution features are extracted for object and scene embeddings. the dataset used consists of approximately 23,000 training images and eight emotion classes: amusement, anger, awe, satisfaction, disgust, excitement, fear, and sadness. 3.2. textual features textual features refer to the characteristics and attributes of text that can be analyzed and used for various purposes such as natural language processing (nlp), text mining, information retrieval, and more. these features help in understanding, processing, and deriving insights from text data. since the context and meaning of words are equally important for the emotional impact of the entire sentence, roberta-base [32] is used to extract contextual word embeddings. data preprocessing. emojis, unnecessary non-ascii characters, numbers, url, hashtag sign and other characters in the tweet text column of the labeled dataset have been removed from the text content due to the inference that they do not help the model perform better. text data labeling. textblob library [33] is used to label the textual data in the dataset. textblob is a python library for textual information that provides a simple api to access nlp activities. using the tokenization, lemmatization, speech tagging and noun expression extraction features of the textblob library, each textual data line was labeled as 0 (neutral), 1 (positive), 2 (negative). 3.3. multimodal features multimodal features refer to the combination of features from multiple types of data, such as text, images, audio, and video, to create a more comprehensive understanding of content. these features are essential in tasks that require the integration of information from different modalities to improve the accuracy and richness of the analysis. for the extraction of multimodal features, the multimodal clip [12] model, trained on 400 million image-text pairs collected from the internet, is used. the model is trained to predict which text goes with which image, and in doing so, it learns meaningful image representation without the need for millions of labeled training examples. compared to multimodal transformers, the model uses binary learning over n-pair images and text, and no cross-attention mechanisms are used to learn multimodal features. this makes the model easier to use, as image and text embeddings can be calculated independently of the respective image and text encoders. due to the diversity and large amount of data, the model demonstrates competitive zero-shot recognition performance on 30 different computer vision datasets compared to its supervised baselines. this shows that the amount and quality of visual information encoded in the model’s visual features are much better than imagenet and places365 supervised pre-trained models. both image and text features are extracted using an open-source clip model, where both image and text embeddings are 512-dimensional vectors. 4. experimental results 4.1. test environment the training and testing phases of the studies are carried out on google colab pro on virtual servers with the following features: pc 1 (gpu virtual machine): 4 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | multimodal sentiment analysis in natural disaster data on social media operating system: ubuntu 18.04.6 lts, cpu: intel(r) xeon(r) cpu @ 2.20ghz, gpu : tesla v100, ram: 16 gb, disk: 108 gb; pc 2 (tpu virtual machine): operating system: ubuntu 18.04.6 lts, cpu: intel(r) xeon(r) cpu @ 2.20ghz, ram: 16gb, disk: 108 gb. 4.2. dataset and training parameters in the study, we create a new dataset containing 1,000 images and 1,000 texts by filtering the natural disaster hashtags and meaningful tweets containing images + text determined on twitter. the determined natural disaster hashtags are as follows: earthquakes, landslides, droughts, famines, poverty, hurricanes, extreme precipitation and flood, wildfires. table 1 shows the distribution in the dataset. figure 2 contains examples of natural disasters in the dataset. table 1. distribution of natural disasters in the dataset natural disaster type number of sample earthquake 245 landslide 95 droughts/famines 118 poverty 92 hurricane 136 flood 180 wildfire 134 data is collected manually, via python tweepy service and twitter apis. positive, negative and neutral categories are used in the labeling of the data. the class labels assigned to each pair (image+text) are collected under three cases: 1) if both have the same label, they are valid and the same. 2) if one label is positive or negative and the other is neutral, it is a polar (positive/negative) label. 3) if the image and text have opposite polarity tags, the tweet is a conflict. the distribution based on sentiment in the dataset, images and text, is as shown in table 2. in the training phase, adam (adaptive moment estimation) is used to update the cross entropy and neural network parameters as the objective function. the learning rate is set to 2 × 10-5 and all models are trained for 100 epochs. if the validation loss does not decrease for five epochs, the learning rate is optimized to decrease by 10 times. to prevent overfitting, a dropout of 0.5 is applied after all intermediate linear table 2. distribution of sentiment in the dataset positive negative neutral image 181 617 202 text 289 478 233 layers. during training phase, the pytorch library is used and object attributes are extracted from the publicly available imagenet pre-trained resnet-50 model. the resnet-101 model, pre-trained from the places365 dataset, is used to extract scene features. 4.3. performance metrics a 10-fold cross-validation metric is used in the training, validation and test set, where each bin resulted in an 8:1:1 ratio of data and the same label distribution. during the training phase, training loss, validation loss, training accuracy, validation accuracy and f1-score values are reported in each epoch. 4.4. learning models to encode objects and overall image content, a pre-trained resnet-50 model is used to extract features on imagenet. to encode scene information, features are extracted from a resnet-101 model pretrained on places365. pre-trained wide ensemblebased convolutional neural networks are used to encode facial expression information. ensembles with shared representations (esrs) based on convolutional networks have been studied to quantitatively and qualitatively demonstrate their scalability to facial expression datasets. roberta-base is used to extract contextual word embeddings. the multimodal clip model is used to extract multimodal features. both image and text features are extracted using an opensource clip model, where both image and text embeddings are 512-dimensional vectors. 4.5. performance results the dataset is divided into 80% training, 10% validation/validation, and 10% test data in order to perform performance tests. the 10-fold cross validation method is used to verify the performance values. table 3 presents the evaluation results of unimodal textual and visual features for the dataset. (accuracy and f1-scores are averaged over 10-fold cross-validation.) table 3. unimodal visual and textual feature results for sentiments on our own dataset features accuracy f1-score object features 0.632 0.601 facial expressions 0.615 0.502 place and scene features 0.630 0.611 effective image content 0.635 0.617 clip (image) 0.715 0.695 clip (text) 0.708 0.684 roberta-base (text) 0.662 0.636 5 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | s. dursun and s. eken figure 2. sample images and texts from natural disasters in the dataset in order to compare the performance results, different models are used to extract image and text features and the results are summarized in table 4. figure 3 shows examples of unimodal and multimodal estimation results. the highlighted text parts in yellow are the word(s) that indicate the sentiment in the text. as seen in table 4, the highest performance values are achieved by using the clip model in the image and the roberta model in the text (accuracy 77.5%; f1score 71%). the issues that caused this limited success performance can be attributed as follows: • since the subject of the study is disaster data, the number of negative examples is quite high. • insufficient label pooling strategy used to pool labels, favoring positive or negative over neutral labels, resulting in a higher number of controversial labels. • the model cannot capture interactions and cannot distinguish between neutral and polar samples. • the data set is limited to 1,000 samples. 5. conclusions and future works in this study, an experimental evaluation of visual, textual and multimodal features is presented for msa of natural disasters-themed tweets collected on twitter. experience has revealed that clip embeddings can 6 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | multimodal sentiment analysis in natural disaster data on social media table 4. multimodal visual and textual feature results for sentiments on our own dataset accuracy f1-score accuracy f1-score roberta clip (text) effective image content (imagenet) 0.700 0.685 0.729 0.700 clip (image) 0.775 0.710 0.701 0.750 figure 3. examples for unimodal and multimodal prediction results serve as a strong basis for the task of multimodal sentiment prediction in tweets. it is envisaged that the natural disasters themed dataset prepared by collecting from social media within the scope of multimodality (image and text) may be useful for future research in this field. while msa can provide richer insights compared to unimodal analysis, it also faces several limitations. social media data is noisy, with many irrelevant or low-quality posts. there is often a lack of labeled datasets that contain multimodal information specific to natural disasters. sentiments during a natural disaster can change rapidly, requiring models to account for temporal dynamics. using social media data raises concerns about user privacy and data security. future work can address these challenges to improve the effectiveness and reliability of msa in this context. in the future, it is planned to collect more images and text from different social media platforms and carry out 7 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | s. dursun and s. eken activities to reduce bias. also, we will develop models that combine early, late, and hybrid fusion techniques to better integrate multimodal features. moreover, it is important to capture temporal dynamics and changes in sentiment over time. data and code availability code underlying this paper are available at github repo. references [1] chandrasekaran, g., nguyen, t.n. and hemanth d, j. (2021) multimodal sentimental analysis for social media applications: a comprehensive review. wiley interdisciplinary reviews: data mining and knowledge discovery 11(5): e1415. [2] yavuz, a. and eken, s. (2023) gold returns prediction: assessment based on major events. eai endorsed transactions on scalable information systems 10(5). [3] balta kaç, s. and eken, s. (2023) customer complaintsbased water quality analysis. water 15(18): 3171. [4] yurtsever, m.m.e., shiraz, m., ekinci, e. and eken, s. (2023) comparing covid-19 vaccine passports attitudes across countries by analysing reddit comments. journal of information science : 01655515221148356. [5] yurtsever, m.m.e., ekinci, e. and eken, s. (2023) covid-19 and behavioral analytics: deep learning-based work-from-home sensing from reddit comments. in international conference on computing, intelligence and data analytics (springer): 143–155. [6] köroğlu, f.e., çakmak, s., yurtsever, m.m.e. and eken, s. (2024) smart waste management: a case study on garbage container detection. in 6th mediterranean conference on pattern recognition and artificial intelligence, medprai 2024, i̇stanbul, türkiye, october 18-19, 2024, proceedings (springer). [7] medhat, w., hassan, a. and korashy, h. (2014) sentiment analysis algorithms and applications: a survey. ain shams engineering journal 5(4): 1093–1113. [8] alam, f., ofli, f. and imran, m. (2018) crisismmd: multimodal twitter datasets from natural disasters. in proceedings of the international aaai conference on web and social media, 12. [9] kaç, s.b., eken, s., balta, d.d., balta, m., i̇skefiyeli, m. and özçelik, i̇. (2024) image-based security techniques for water critical infrastructure surveillance. applied soft computing 161: 111730. [10] jayagopal, a., aiswarya, a.m., garg, a. and nandakumar, s.k. (2022) multimodal representation learning with text and images. arxiv preprint arxiv:2205.00142 . [11] zhang, y., jiang, h., miura, y., manning, c.d. and langlotz, c.p. (2022) contrastive learning of medical visual representations from paired images and text. in machine learning for healthcare conference (pmlr): 2– 25. [12] radford, a., kim, j.w., hallacy, c., ramesh, a., goh, g., agarwal, s., sastry, g. et al. (2021) learning transferable visual models from natural language supervision. in international conference on machine learning (pmlr): 8748–8763. [13] lin, z., bas, e., singh, k.y., swaminathan, g. and bhotika, r. (2023) relaxing contrastiveness in multimodal representation learning. in proceedings of the ieee/cvf winter conference on applications of computer vision: 2227–2236. [14] cheema, g.s., hakimov, s., müller-budack, e. and ewerth, r. (2021) a fair and comprehensive comparison of multimodal tweet sentiment analysis methods. in proceedings of the 2021 workshop on multi-modal pretraining for multimedia understanding: 37–45. [15] thelwall, m., buckley, k., paltoglou, g., cai, d. and kappas, a. (2010) sentiment strength detection in short informal text. journal of the american society for information science and technology 61(12): 2544–2558. [16] saif, h., bashevoy, m., taylor, s., fernandez, m. and alani, h. (2016) senticircles: a platform for contextual and conceptual sentiment analysis. in the semantic web: eswc 2016 satellite events, heraklion, crete, greece, may 29–june 2, 2016, revised selected papers 13 (springer): 140–145. [17] you, q., luo, j., jin, h. and yang, j. (2015) robust image sentiment analysis using progressively trained and domain transferred deep networks. in proceedings of the aaai conference on artificial intelligence, 29. [18] you, q., luo, j., jin, h. and yang, j. (2016) building a large scale dataset for image emotion recognition: the fine print and the benchmark. in proceedings of the aaai conference on artificial intelligence, 30. [19] jiang, t., wang, j., liu, z. and ling, y. (2020) fusionextraction network for multimodal sentiment analysis. in advances in knowledge discovery and data mining: 24th pacific-asia conference, pakdd 2020, singapore, may 11–14, 2020, proceedings, part ii 24 (springer): 785– 797. [20] russakovsky, o., deng, j., su, h., krause, j., satheesh, s., ma, s., huang, z. et al. (2015) imagenet large scale visual recognition challenge. international journal of computer vision 115: 211–252. [21] he, k., zhang, x., ren, s. and sun, j. (2016) deep residual learning for image recognition. in proceedings of the ieee conference on computer vision and pattern recognition: 770–778. [22] pennington, j., socher, r. and manning, c.d. (2014) glove: global vectors for word representation. in proceedings of the 2014 conference on empirical methods in natural language processing (emnlp): 1532–1543. [23] devlin, j., chang, m.w., lee, k. and toutanova, k. (2018) bert: pre-training of deep bidirectional transformers for language understanding. arxiv preprint arxiv:1810.04805 . [24] bica, m., palen, l. and bopp, c. (2017) visual representations of disaster. in proceedings of the 2017 acm conference on computer supported cooperative work and social computing: 1262–1276. [25] sit, m.a., koylu, c. and demir, i. (2020) identifying disaster-related tweets and their semantic, spatial and temporal context using deep learning, natural language processing and spatial analysis: a case study of hurricane irma. in social sensing and big data computing for 8 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | https://github.com/devsdtr/multimodal https://github.com/devsdtr/multimodal multimodal sentiment analysis in natural disaster data on social media disaster management (routledge), 8–32. [26] hassan, s.z., ahmad, k., hicks, s., halvorsen, p., alfuqaha, a., conci, n. and riegler, m. (2022) visual sentiment analysis from disaster images in social media. sensors 22(10): 3628. [27] hassan, s.z., ahmad, k., riegler, m.a., hicks, s., conci, n., halvorsen, p. and al-fuqaha, a. (2021) visual sentiment analysis: a natural disasteruse-case task at mediaeval 2021. arxiv preprint arxiv:2111.11471 . [28] niu, t., zhu, s., pang, l. and el saddik, a. (2016) sentiment analysis on multi-view social data. in multimedia modeling: 22nd international conference, mmm 2016, miami, fl, usa, january 4-6, 2016, proceedings, part ii 22 (springer): 15–27. [29] zhou, b., lapedriza, a., khosla, a., oliva, a. and torralba, a. (2017) places: a 10 million image database for scene recognition. ieee transactions on pattern analysis and machine intelligence 40(6): 1452–1464. [30] siqueira, h., magg, s. and wermter, s. (2020) efficient facial feature learning with wide ensemblebased convolutional neural networks. in proceedings of the aaai conference on artificial intelligence, 34: 5800– 5809. [31] yi, d., lei, z. and li, s.z. (2015) shared representation learning for heterogenous face recognition. in 2015 11th ieee international conference and workshops on automatic face and gesture recognition (fg) (ieee), 1: 1–7. [32] liu, y., ott, m., goyal, n., du, j., joshi, m., chen, d., levy, o. et al. (2019) roberta: a robustly optimized bert pretraining approach. arxiv preprint arxiv:1907.11692 . [33] loria, s. et al. (2018) textblob documentation. release 0.15 2(8): 269. 9 eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | 1 introduction 2 related works 3 material and methods 3.1 visual features object features place and scene features facial expressions effective image content 3.2 textual features data preprocessing text data labeling 3.3 multimodal features 4 experimental results 4.1 test environment 4.2 dataset and training parameters 4.3 performance metrics 4.4 learning models 4.5 performance results 5 conclusions and future works this is a title eai endorsed transactions on smart cities research article 1 balancing efficiency and equity: ethical considerations for automation in urban planning a. raisinghani1,* and v. mehta2 1,2 department of urban and regional planning, school of planning and architecture bhopal, bhopal, madhya pradesh, india abstract the integration of automation into urban planning introduces a complex dynamic where efficiency often clashes with equity, especially for marginalized communities. this necessitates a delicate balance between these two aspects. this article investigates the ethical principles and equity considerations in urban planning decisions, revealing a historical and contemporary bias towards efficiency, marginalizing certain groups. automation, while beneficial in sectors like transportation, land use, and infrastructure, can perpetuate existing inequities and pose ethical challenges such as algorithmic bias and data privacy concerns. the article explores the impacts of automation on plan execution and monitoring, highlighting the need for current best practices to address these challenges. it provides an overview of automation in urban planning and calls for continuous research, collaboration, and improvement to ensure efficiency and equity are mutually reinforced. keywords: automation, efficiency, equity, ethics, urban planning received on 31 may 2024, accepted on 13 february 2025, published on 21 february 2025 copyright © 2024 a. raisinghani and v. mehta, licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.6208 1. introduction 1.1. growing role of automation in urban planning urban planning is undergoing a profound transformation with the integration of automation, marking a significant departure from traditional methodologies [1]. this shift is driven by the pressing need to address challenges arising from rapid urbanization and the imperative for sustainable development [2]. the increasing role of automation in urban planning offers unprecedented opportunities to build more liveable, sustainable, and resilient cities [3]. the growing adoption of automation in urban planning implementation and monitoring is highlighted by the emergence of smart city initiatives [4]. these efforts utilize data-driven technologies such as internet of things (iot) *corresponding author. email: abhi90raisinghani@gmail.com devices and artificial intelligence (ai) to gather live data, oversee urban infrastructure, and improve decision-making procedures. [5]. from optimizing traffic management to monitoring environmental quality, automation is revolutionizing urban functionality and resilience. furthermore, automation is reshaping conventional approaches to urban design and land use planning [1]. advanced modelling and simulation tools, empowered by automation algorithms, enable planners to forecast trends, assess the impact of different development scenarios, and optimize spatial layouts for efficiency and sustainability [6]. utilizing data-driven methods enables decision-making based on evidence, with a focus on prioritizing environmental conservation, social equality, and economic sustainability. automation also facilitates greater public participation and engagement in the urban planning process [7]. interactive digital platforms, augmented reality, and virtual reality simulations empower stakeholders to visualize proposed projects, offer feedback, and collaborate with planners in real time [4]. this inclusive approach promotes transparency, eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ mailto:abhi90raisinghani@gmail.com a. raisinghani and v. mehta 2 accountability, and community ownership in urban development initiatives. however, the rapid adoption of automation in urban planning raises ethical, social, and regulatory concerns [8]. addressing concerns like data privacy, algorithmic bias, and digital inequality is essential to guarantee equitable access and involvement in smart city initiatives [9]. moreover, the potential displacement of jobs and exacerbation of socioeconomic disparities underscore the necessity for proactive policy interventions and workforce development strategies [10]. 1.2. ethical dilemma of balancing efficiency and equity the ethical dimension of balancing efficiency and equity in urban planning amid the increasing integration of automation is a critical aspect that requires careful consideration. while automation holds the promise of optimizing urban processes and improving overall efficiency, it also poses significant challenges in terms of ensuring fairness, inclusivity, and social justice. the pursuit of efficiency through automation must not come at the expense of equity and social justice. there is a risk that automation technologies may exacerbate existing inequalities, particularly for marginalized communities with limited access to digital resources and technological skills. the phenomenon known as the "digital divide" highlights the disparities in access to technology and digital literacy, which can further widen socio-economic gaps in urban areas [2]. moreover, automation algorithms might unintentionally perpetuate biases and discrimination, resulting in unequal outcomes in domains like housing, employment, and public services [8]. the use of predictive analytics in decisionmaking processes, for instance, may reinforce systemic inequalities by favouring certain groups over others based on historical data patterns. additionally, concerns about data privacy and surveillance raise ethical questions regarding the use of personal information for urban planning purposes [10]. through the utilization of technology, data, and automation, planners can address intricate challenges and enhance the quality of life for inhabitants in urban areas [9]. yet, realizing this potential requires a balanced approach that integrates technological innovation with ethical considerations and community engagement. this paper will delve into specific case studies to illustrate the multifaceted impact of automation on urban planning practices and outcomes, it aims to elucidate the growing role of automation in urban planning and its implications for shaping future cities. 1.3. purpose and structure of the paper the objective of this paper is to examine the ethical implications of integrating automation technologies into urban planning execution and monitoring, focusing on the tension between efficiency-driven approaches and the imperative of ensuring equity and social justice. beginning with an introduction to the growing role of automation in urban planning, it outlines the ethical framework for urban planning, analysing principles such as transparency, fairness, and accountability. subsequent sections delve into how automation enhances efficiency in implementation and monitoring across various urban planning domains while considering equity considerations such as access to resources and environmental justice. the paper then addresses the ethical challenges associated with automation, including algorithmic biases and data privacy concerns, and discusses strategies for balancing efficiency and equity through case studies and best practices. ultimately, it concludes with a call to action for prioritizing ethical considerations in automation adoption and underscores the ongoing need for research and collaboration in this evolving field. 2. ethical principles in urban planning planning profession is guided by principles encompassing public interest, equity, environmental sustainability, and professional integrity, navigating through a labyrinth of complex challenges including urbanization and climate change. these ethical principles not only provide a framework for decision-making and code of conduct but also serve as a guiding light, illuminating the path toward a future characterized by inclusivity, sustainability, and justice for all members of society. some of the principles of urban planning are: 2.1. public interest prioritizing the public interest involves valuing diversity, fostering public engagement, offering transparent information on planning issues, and advocating for conservation efforts. it also entails striving for spatial justice by ensuring equitable opportunities [11,12]. planners must engage respectfully with marginalized communities, facilitating their active involvement in the planning process to achieve inclusivity and fairness. 2.2. equity and social justice planners are tasked with confronting and addressing systemic inequalities, including disparities in housing, transportation, healthcare, and economic opportunities. through an equitycentred approach, planners’ endeavour to create communities that are inclusive and just, enabling every individual to thrive. essential to this approach is the adaptation of existing plans and policies to dismantle historical barriers to racial and social equity [13]. by monitoring progress using metrics and accountability mechanisms, sustained advancements toward achieving more equitable outcomes are ensured. this comprehensive strategy underscores planners' commitment to fostering environments where fairness and opportunity prevail, signalling a concerted effort to address deep-rooted eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | balancing efficiency and equity: ethical considerations for automation in urban planning 3 disparities and cultivate a society where every member has the chance to prosper. 2.3. transparency and accountability planners should uphold the principles of transparency and accountability in their decision-making processes. this includes providing clear and accessible information to stakeholders, soliciting feedback from the public, and being accountable for the outcomes of planning initiatives [14]. planners must consider the long-term consequences of decisions and incorporate equity principles to promote social justice. they should analyse ethical issues systematically, establishing procedures to uphold ethical behaviour. 2.4. environmental sustainability in response to unparalleled environmental challenges, ethical planning necessitates a proactive commitment to sustainability, ensuring present decisions prioritize the wellbeing of future generations and the environment. planners play a pivotal role in advancing environmental sustainability by safeguarding ecological systems, addressing climate change impacts, and enhancing resilience against environmental threats [15]. this involves integrating principles of conservation, resource efficiency, and resilience into planning decisions across all facets of practice, encompassing land use, transportation, infrastructure design, and resource management. by emphasizing green infrastructure, renewable energy, and sustainable development practices, planners contribute to the creation of communities that are more resilient, liveable, and environmentally sustainable. their efforts resonate in the establishing a sustainable future that meets the requirements of present and future generations, while also preserving the environment for the prosperity of everyone [16]. 2.5. digital ethics the digital age poses new complexities. data privacy concerns, algorithmic biases in decision-making, and the potential for online anonymity to fuel unethical behaviour demand new considerations [17]. adapting ethical frameworks to these evolving landscapes requires constant vigilance and innovation. professional organizations play a crucial role in developing and enforcing ethical codes, while individual responsibility remains paramount in navigating these uncharted territories [18]. figure 1. ethical principles in urban planning 3. efficiency and automation in urban planning efficiency stands out as a significant advantage and motivator for automation in urban planning. by automating repetitive tasks and processes, urban planners can achieve more within shorter timeframes. automated tools excel at handling tasks like data collection, analysis, and visualization, outperforming manual methods in speed and accuracy. it facilitates the collection of vast datasets from diverse sources such as sensors, satellites, and social media. this data undergoes analysis using machine learning algorithms and eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | a. raisinghani and v. mehta 4 geographic information systems (gis) to uncover insights into urban trends, patterns, and challenges. furthermore, predictive models assist urban planners in anticipating future scenarios concerning population growth, infrastructure requirements, transportation demands, and environmental changes. 3.1. cases of automation in urban planning few cases of how automation has enhanced the efficiency in various fields of urban planning are given below: 3.1.1. transportation and mobility automation technologies, such as intelligent traffic signals and traffic monitoring systems, play a crucial role in optimizing traffic flow, alleviating congestion, and enhancing overall transportation efficiency [19] . for instance, the sydney coordinated adaptive traffic system (scats) dynamically adjusts signal timings based on real-time traffic conditions, effectively reducing congestion and travel times at intersections [20]. efficient and reliable public transportation is achieved through automated fare collection systems, real-time passenger information, and transit scheduling software. notably, the oyster card system in the london underground automates fare collection [21], and smart bus and traffic infrastructure, bhubaneswar [22] streamlining the passenger experience and boosting revenue collection for transport authorities. the rise of autonomous vehicles (avs) holds the potential to transform transportation by optimizing road capacity, minimizing accidents, and reshaping urban mobility patterns. avs can seamlessly integrate into existing transportation networks, providing efficient and convenient mobility options. notably, companies like google have achieved significant milestones, with over 1 million miles covered by their driverless cars in june 2015 [23]. additionally, bengaluru-based startup minus zero introduced the first self-driving car in india, the "zpod," in 2023 [24]. 3.1.2. land use and zoning automated zoning tools streamline the analysis of land use regulations, zoning ordinances, and development standards, aiding planners in evaluating proposed projects and ensuring compliance with regulatory requirements. geographic information systems (gis) combined with data analytics enhance the efficiency of analysing land use patterns, demographics, and spatial data, facilitating informed decision-making [25]. the adoption of online building plan approval systems is growing in india, aiming to streamline the construction approval process, minimize corruption, and enhance transparency. for instance, 379 urban bodies in madhya pradesh utilize the automated building plan approval system (abpas) and 107 utilize automated layout process approval and scrutiny system (alpass) as of 2022 (abpas) [26], [27]. automation empowers planners to develop virtual simulations of urban environments, enabling stakeholders to visualize and assess various land use scenarios and development proposals. digital twin technology, recognized globally, represents physical entities, processes, or systems, enabling real-time monitoring, analysis, and simulation. twinby, for example, plans to create 18 urban digital twins in bavaria by march 2024 [28]. moreover, the 'digital twin strategy for indian infrastructure' report, released in 2023, aligns with the 'national geospatial policy 2022,' envisioning a transformative national digital twin for major towns and cities in india by 2035 [29]. 3.1.3. infrastructure management automation technologies play a pivotal role in monitoring and optimizing energy distribution, water management, and waste disposal systems, thereby enhancing resource efficiency and sustainability. automated energy management systems can optimize energy consumption across buildings, streetlights, and municipal facilities, resulting in cost savings and reduced environmental impact. for instance, the smart mccb distribution management solution is implemented in maharashtra to monitor and mitigate energy leakage and faults in energy distribution [30]. the utilization of supervisory control and data acquisition (scada) systems facilitates the implementation of effective water management strategies in water supply networks in cities like navi mumbai, nagpur, and ahmedabad [31]. automated systems leverage sensors and data analytics to forecast infrastructure failures and plan maintenance proactively, thereby minimizing downtime and lowering repair expenses. for instance, the netherlands' rijkswaterstaat employs automated bridge monitoring systems to identify structural defects and prioritize maintenance tasks [32]. similarly, the new york city department of environmental protection utilizes predictive analytics to optimize sewer inspection and maintenance activities, reducing the likelihood of sewer failures and backups [33]. 3.1.4. environmental management automated sensor networks provide real-time monitoring of air and water quality, noise levels, and other environmental parameters, enabling prompt interventions to address pollution and environmental hazards. for instance, the city of copenhagen utilizes air quality sensors to monitor pollution levels and guide air quality management policies. copenhagen solutions lab partnered with google to evaluate the city's air quality, aided by satellite navigation technology [34]. automation technologies are pivotal in advancing and implementing green infrastructure projects, such as green roofs and permeable pavements, aimed at enhancing resilience and sustainability. for example, building automation systems (bas) [35] are employed in the indira paryavaran bhawan, which is india’s inaugural on-site net zero building [36]. automated environmental modelling tools simulate the effects of land use changes, transportation policies, and eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | balancing efficiency and equity: ethical considerations for automation in urban planning 5 infrastructure projects on environmental quality and natural ecosystems. for instance, the u.s. environmental protection agency's basins tool aids planners in evaluating the environmental impacts of land use decisions and water management strategies [37]. 3.2. benefits and challenges of automation in urban planning table 1. benefits and challenges of automation in urban planning benefits challenges efficiency and resource optimization: • simplifies repetitive tasks • optimizes resource allocation • reducing waste • enhancing efficiency data quality and availability: • incomplete or inconsistent data enhanced resilience: • swift responses to emergencies • predictive analytics for crisis management privacy and security: • data privacy • data protection • cybersecurity cost savings: • workflow streamlining • reduced dependence on manual labour public engagement: • reduced human judgment and intuition improved decision making: • real-time data access • automated analytical tools • elevate decisionmaking processes digital divide: • disparities in access to services • organizational change • stakeholder resistance table 1 outlines the benefits and challenges of automation in urban planning. it underscores the potential of automation to enhance efficiency, precision, and decision-making in urban planning. however, it emphasizes the importance of tackling challenges related to data quality, equity, privacy, and organizational transformation to fully capitalize on its benefits. 4. equity considerations in urban planning urban planning plays a crucial role in shaping the lives of city dwellers. however, achieving equitable outcomes for all residents remains a significant challenge. this paper explores four key equity issues in urban planning: access to re-sources, distribution of benefits and burdens, social inclusion, and environmental justice with appropriate examples to illustrate the issue and highlight potential solutions. 4.1. access to resources access to resources in urban planning involves ensuring that essential services such as water, sanitation, healthcare, and education are equitably distributed among urban populations, regardless of socioeconomic status or geographical location. this entails addressing disparities in infrastructure provision and ensuring that marginalized communities have adequate access to basic amenities necessary for their well-being and development. • a significant barrier lies in the digital divide, as highlighted by gsma intelligence in "the mobile economy india 2023." people in underserved areas often lack access to smartphones and internet connectivity, rendering them unable to order goods through apps used by self-driving delivery vehicles. this could further marginalize them and widen the existing digital divide. • autonomous waste collection systems in developed cities might raise concerns about equity in service provision, potentially neglecting low-income areas due to economic considerations. this could lead to environmental injustice and health risks for marginalized communities [38]. 4.2. distribution of benefits and burdens distribution of benefits and burdens focuses on the fair allocation of advantages and disadvantages associated with urban development. it entails preventing marginalized communities from bearing disproportionate negative impacts such as pollution, gentrification, or lack of access to public services. • urban renewal projects: while aimed at revitalizing areas, they often led to gentrification, displacing lowincome residents and businesses who cannot afford rising rents. this creates a "displacement burden" where vulnerable communities lose their homes and livelihoods [39]. • climate change adaptation: while coastal cities invest in seawalls and other protective measures, low-lying communities might be neglected, creating an "adaptation burden" where they face increased vulnerability without adequate support [39]. eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | a. raisinghani and v. mehta 6 • data gaps and lack of disaggregated data: planning decisions often rely on incomplete or inaccurate data that fails to capture the specific needs and vulnerabilities of different groups, leading to unequal outcomes. 4.3. social inclusion social inclusion in urban planning aims to establish environment where every individuals have equitable opportunities to engage in decision-making processes and avail urban amenities and services [40]. this involves designing inclusive spaces that accommodate diverse needs and preferences, fostering social cohesion, and promoting dialogue and collaboration among different social groups. • automation in public services like healthcare in india could create barriers for marginalized communities with limited digital literacy or access to technology. this could exclude them from essential services and widen the gap in healthcare equity [41]. • increased reliance on automation in urban spaces, like automated security systems or facial recognition technology, might lead to concerns about privacy and discrimination against individuals based on ethnicity, race, or other factors. this could create social tensions and undermine inclusive community development [42]. 4.4. environmental justice environmental justice in urban planning addresses the unequal distribution of environmental risks and benefits, seeking to rectify historical injustices and empower communities to advocate for environmental protection and sustainability [43]. it involves recognizing and mitigating environmental disparities, promoting environmental awareness and education, and involving affected communities in decision-making processes related to environmental policies and projects. • automated waste management systems in india, while potentially improving efficiency, might raise concerns about data privacy and potential misuse of collected information. this could disproportionately impact vulnerable communities whose data is collected without proper consent or safeguards [44]. • over 70% of india's surface water is contaminated according to central pollution control board in 2023, disproportionately impacting marginalized communities relying on polluted sources for drinking and sanitation. a 2022 report by wateraid [45] revealed that 42% of rural households lacked access to safe drinking water, compared to only 7% in urban areas. • open dumpsites and inadequate waste collection disproportionately affect marginalized communities living in proximity. a 2023 report of techiman municipality of ghana, assessing solid waste management practices [46], found that 58% of open dumpsites in india are located near informal settlements, exposing residents to health hazards from waste burning and leachate contamination. 5. ethical challenges of automation in urban planning while automation holds promise for efficiency in urban planning, its implementation in india raises concerns about exacerbating existing inequities and marginalizing vulnerable communities. 5.1. algorithmic bias smart city initiatives: algorithms used for traffic management, waste collection, or resource allocation in smart cities can perpetuate biases if not carefully designed. for example, algorithms trained on historical data might reinforce existing inequalities in resource distribution or policing, disproportionately impacting marginalized communities [47]. in india, the introduction of automated facial recognition systems for law enforcement purposes in cities like new delhi has raised ethical concerns regarding privacy and discrimination. these systems, if not properly regulated, could worsen biases against certain demographic groups, potentially leading to wrongful targeting or surveillance of marginalized communities [48]. the use of automated waste management systems in cities like mumbai has faced criticism for perpetuating socio-economic disparities. these systems often prioritize waste collection and disposal services in affluent areas, where residents can afford to pay for premium services while neglecting informal settlements and slum areas, where waste management infrastructure is lacking, and residents are left to deal with inadequate sanitation facilities [49]. 5.2. digital divide limited access to technology and the internet: marginalized communities in india often lack access to digital tools used for data collection and participatory planning processes. this can exclude their voices and needs, leading to solutions that do not address their concerns [50]. the adoption of digital platforms for citizen engagement in urban planning processes in new york city has highlighted the digital divide. while affluent neighbourhoods with high internet penetration rates can effectively participate in online consultations and decision-making processes, lowincome neighbourhoods with limited access to digital infrastructure and technology are often excluded, resulting in their interests and concerns being marginalized in urban development decisions [51]. in cities like hyderabad, the introduction of automated systems for online payment of utility bills and property taxes has widened the digital divide. while tech-savvy residents with access to smartphones and internet connectivity can eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | balancing efficiency and equity: ethical considerations for automation in urban planning 7 conveniently use these platforms. however, residents from low-income or rural areas may face challenges due to limited digital literacy and online payment accessibility, resulting in their exclusion from crucial services and potential penalties for non-compliance [52]. 5.3. job displacement and skills gap automation in sectors like sanitation or transportation: while potentially improving efficiency, automation might displace low-skilled workers, primarily concentrated in marginalized communities. without adequate reskilling and upskilling programs, these individuals risk job losses and economic hardship [53]. in chennai, the implementation of automated systems in the textile industry has resulted in job displacement among garment workers. automated textile manufacturing processes, such as computerized knitting and robotic sewing, have reduced the demand for manual labour, leading to layoffs and unemployment in the garment manufacturing sector. however, many displaced workers lack the technical skills required to transition to other industries or higherskilled positions, leading to economic hardships, and social inequalities [54]. in cities like detroit, the introduction of automated systems in the manufacturing and transportation sectors has led to job displacement and a widening skills gap. automation in automotive manufacturing plants, for instance, has reduced the demand for low-skilled labour, resulting in unemployment and economic hardship for affected workers. moreover, the skills required for new tech-intensive jobs often do not match the qualifications of displaced workers, exacerbating inequalities and contributing to social unrest [55]. informal vendors: automated delivery services, while promising convenience, could significantly disrupt the livelihoods of millions of informal vendors reliant on traditional delivery methods. this could worsen economic insecurity and social unrest among marginalized communities heavily dependent on the informal sector [56]. waste pickers: automation in waste management might lead to job losses for informal waste pickers, often from disadvantaged backgrounds, pushing them further into poverty and jeopardizing their access to necessities [57]. skill mismatch and affordability: even if new jobs are created through automation, marginalized communities might lack the skills or financial resources to access training and compete for these positions, widening the skills gap and perpetuating inequalities [58]. 5.4. lack of community engagement top-down planning approaches: overreliance on data and technology can overshadow community engagement, particularly in marginalized areas with limited access to digital platforms or skills. this can lead to solutions that are not culturally appropriate or responsive to their needs [38]. in new york city, the implementation of automated decision-making systems for public housing allocation has been criticized for the lack of community involvement. the application of algorithms to assess housing eligibility and allocation without meaningful engagement with affected residents has led to inequalities and complaints. many residents, particularly those from marginalized communities, feel that their voices are not being heard and that the automated systems fail to consider their unique circumstances and needs [59]. 5.5. inadequate regulatory framework lack of ethical guidelines for using automation: the absence of clear ethical frameworks and data privacy regulations could lead to discriminatory practices and misuse of data, further marginalizing vulnerable groups [60,61]. in singapore, the deployment of autonomous vehicles (avs) has outpaced the development of regulatory frameworks. it was revealed that, while singapore had one of the highest rates of autonomous vehicle (av) testing globally, with over 1,000 avs operating on public roads, there were notable gaps in regulatory supervision. the study found that only 30% of avs had undergone safety assessments, and there were no standardized guidelines for av testing or operation. this lack of regulation resulted in safety concerns, with a reported 25 accidents involving avs in the past year, highlighting the urgent need for comprehensive regulatory frameworks [62]. in bengaluru, the emergence of automated systems for urban governance has revealed gaps in the regulatory framework. revisiting the implementation of online licensing systems for commercial establishments in the city, the study found that while 70% of commercial establishments had adopted the online licensing system, there were inconsistencies in the application process and data management. furthermore, only 40% of establishments reported satisfaction with the system's efficiency and transparency, citing difficulties in navigating complex regulations and obtaining timely approvals. this underscores the need for stronger regulatory oversight to ensure the effectiveness and integrity of automated systems in urban governance [63]. data privacy concerns: concerns around data privacy and ownership in automated systems could disproportionately impact marginalized communities with limited access to legal resources and awareness of their rights, potentially excluding them from the benefits of data-driven solutions [64]. 5.6 complicating informal sector vulnerabilities unequal distribution of burdens and benefits: automation might lead to increased energy consumption and e-waste generation, disproportionately impacting marginalized communities living near landfills or lacking access to proper e-waste disposal facilities [65]. as discussed previously, the focus on climate change adaptation measures like seawalls in coastal cities leaves loweai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | a. raisinghani and v. mehta 8 lying communities vulnerable, creating an "adaptation burden." marginalized groups face environmental inequities with increased risks and inadequate support, exacerbating socio-economic disparities. 6. strategies for balancing efficiency and equity up till now it is evident that automation has brought efficiency to the planning process but at the cost of equity. therefore, balancing efficiency and equity in automated urban planning processes requires thoughtful consideration and implementation of strategies that prioritize fairness and inclusivity while maximizing effectiveness. here are some key strategies and best practices: 6.1. policy frameworks for equity to ensure development of policies that explicitly address equity concerns related to automation in urban planning is crucial for ensuring that technological advancements benefit all members of society, regardless of socioeconomic status or demographic characteristics. also, ensuring that data utilized for automation remains representative and impartial. it aims to mitigate potential disparities by emphasizing equity in the design and implementation of automation technologies. this involves considering the needs and viewpoints of marginalized communities to ensure fairness and inclusivity. the digital india initiative, launched by the government of india in 2015 [66], aims to transition india into a digitally empowered society and a knowledge economy. the government’s increased focus on establishing a digitally empowered economy is projected to yield benefits across all sectors, particularly in key digital domains such as information technology & business process management, digital communication services, and electronics manufacturing. amsterdam's digital inclusion strategy is a digital inclusion strategy that focuses on providing access to digital technologies, digital skills training, and support services for residents who are digitally marginalized. the strategy includes initiatives such as digital literacy programs, community technology centres, and affordable internet access programs [67]. 6.2. community-centred planning these strategies involve engaging communities in the planning process. involving diverse stakeholders, including marginalized communities in the planning and implementation of automation projects to ensure that their needs and concerns are addressed. the quantified cities movement (qcm), initiated and managed by the centre for development studies and activities (cdsa) in pune, seeks to enhance urban planning and foster resilient cities by promoting transparency and accountability. it empowers all citizens to engage in local decision-making processes [68]. at its centre is the inagrik mobile application, which empowers citizens to report issues and suggest solutions [68]. this real-time, location-based feedback system enables communities and implementing partners to exchange information regarding various multisectoral needs and grievances. community-centred urban sensing (ccus) is a participatory urban sensing initiative developed by a team at the university of virginia. this team includes urban planners, designers, architects, landscape architects, and information technologists. the goal of ccus is to address the need for practical information about the urban environment through community-driven data collection and analysis. this approach empowers residents and community-based organizations to engage in urban planning and design activities within their neighbourhoods [69]. 6.3. inclusive access to data and technology this includes encouraging equal availability of technology and digital resources to all, preventing the creation of a technology gap. foster transparency in data utilization and decision-making procedures, ensuring stakeholders are answerable. guarantee fair access to data while safeguarding individuals' privacy through the enforcement of comprehensive data governance policies and transparent protocols. under digital india, initiatives like aadhaar, digilocker, mygov, bharatnet, smart cities aaina [66,70], and many others. as of 2022, approx. 127.76 crore live aadhaar are registered. as of 2021 6.01 crore digilocker user are there. as of [66] as of 2024, there are about 2.1 lakh gram panchayat are connected through bharatnet project. london's city data trust initiative focuses on responsible and transparent data sharing practices for the benefit of the public [71]. often involving collaboration between government agencies, businesses, academic institutions, and community organizations to ensure that data is used ethically, securely, and in ways that respect individual privacy rights. 6.4. capacity building and training this involved investing in training programs to empower communities and officials to make the most of automation technologies. through targeted training initiatives, organizations and governments can foster innovation, enhance productivity, and address complex challenges across diverse sectors, ultimately driving sustainable development and prosperity. pradhan mantri gramin digital saksharta abhiyaan (pmgdisha) is an initiative launched by the government of india aimed at making citizens in rural areas digitally literate. the program concentrates on delivering digital literacy training to rural individuals, enabling them to effectively utilize digital technologies and engage in the digital economy eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | balancing efficiency and equity: ethical considerations for automation in urban planning 9 [66]. it aims to reach out to around six crore rural households, making them digitally literate. as of july 2019, 6.15, crore beneficiaries have been registered; of these, 3.89 beneficiaries were certified [72]. the singapore's smart nation initiative aims to utilize technology and innovation for economic and societal advancement. the government collaborates with industry and educational partners to offer training programs in digital skills, cybersecurity, and data analytics [73]. citizens and businesses are encouraged to participate in these initiatives to enhance their digital literacy and integrate smart technologies into daily life and business operations. 6.5. urban pilots and testbeds urban pilots and testbeds assess automation's impact on diverse communities, identifying disparities early. active community involvement aids in recognizing unintended consequences. policymakers can then address inequities, ensuring fair urban development. through inclusivity, these initiatives promote equitable distribution of automation benefits among residents. microsoft, andhra pradesh's government, and the international crop research institute for the semi-arid tropics (icrisat) collaborated on an ai-based sowing app for indian farmers. using ai and historic data, the app predicts optimal sowing times and other farming stages, transmitted to farmers via sms[74] . pilot results showed a remarkable 30% increase in average yield per hectare, showcasing its effectiveness. the amsterdam smart city living lab functions as a dynamic hub where novel solutions undergo testing and assessment to ascertain their beneficial impact on urban surroundings and communities [67]. for instance, the iot living lab initiative explores and experiments with interactive solutions enabled by iot, actionable open data, and user-friendly platforms, fostering the development of upcoming iot innovations [75]. 6.6. equity impact assessment performing equity impact assessments is a strategic method to analyse the potential social, economic, and environmental effects of automation projects on various communities. this process will aid in guaranteeing that automation projects contribute to inclusive and sustainable development, fostering fairness and social justice throughout the process. there have been limited studies conducted to assess the impact of ai on employment in india. niti aayog's "responsible ai" [76] report acknowledges the importance of considering job impact as part of broader societal concerns in defining the principles of responsible ai. additionally, policy brief by the research and information system for developing countries (ris) [77] discusses the potential negative effects of ai on jobs in india. however, it suggests that while there may be short-term job losses, there is potential for new job opportunities to emerge across different sectors in the medium to long term, potentially compensating for initial losses. the sidewalk toronto project, a collaboration between waterfront toronto and sidewalk labs (a subsidiary of alphabet inc.), aimed to develop a smart neighbourhood in toronto, canada, leveraging automation and digital technologies for urban planning [78]. the assessment raised many concerns about use of personal data in the smart neighbourhood, privacy rights and data ownership. it also raised questions about digital inclusion and accessibility and lack of presence of data governance [79]. 7. conclusion in navigating the complexities of automation in urban planning, our exploration has underscored the critical need to balance efficiency with equity. the tension between optimizing resource allocation and ensuring equitable access, social inclusion, and environmental justice cannot be ignored. to move forward responsibly, we must adopt a holistic approach that integrates ethical frameworks, addresses equity concerns, and navigates ethical challenges effectively. recognizing this tension, we acknowledge the imperative to prioritize equity considerations alongside efficiency gains. automation's potential benefits in optimizing transportation, land use, infrastructure, and environmental management must be tempered with a commitment to avoiding widening existing disparities. this requires a conscious effort to ensure that automation serves the needs of all communities, particularly the most vulnerable. 7.1. ethical frameworks matter ethical frameworks serve as our guiding light in this journey towards responsible automation. principles such as transparency, fairness, privacy, and accountability must underpin the design, implementation, and monitoring of automated systems. by upholding these principles, we can build trust and ensure ethical conduct in urban planning processes. 7.2. efficiency's double-edged sword while efficiency-driven approaches offer optimization opportunities, we must remain vigilant of potential downsides. standardization and neglecting diverse needs can lead to unintended consequences. therefore, we must actively involve communities in planning processes, ensuring that automation aligns with their specific needs and values. 7.3. equity: beyond efficiency eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | a. raisinghani and v. mehta 10 exploring equity concerns like access to resources, distribution of benefits and burdens, social inclusion, and environmental justice highlighted the importance of addressing historical and contemporary inequities. automation shouldn't further disadvantage vulnerable communities. we must actively involve these communities in planning processes and mitigate potential biases through diverse data sets and regular bias audits. navigating ethical challenges requires proactive measures such as diverse data sets, regular bias audits, and communitydriven data governance. building robust safeguards through clear guidelines, regulations, and oversight is essential to prevent bias, protect privacy, and address unintended consequences. figure 2. ethical principles to strategies, automation in urban planning 7.4. way forward moving forward, governments must continue to 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[79] goodman ep. sidewalk toronto goes sideways: five lessons for digital governance. medium 2020. https://ellgood.medium.com/sidewalk-toronto-goessideways-five-lessons-for-digital-governance573f2f108024 (accessed february 24, 2024). eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | this is a title eai endorsed transactions on smart cities research article 1 development and evaluation of e-learning for professional bus drivers in tanzania marwa chacha1,*, ariane cuenen³, prosper nyaki², ansar yasar³, geert wets³ ¹ministry of transport (mot) government city mtumba, 1 ujenzi street, p.o.box 638, 40470 dodoma, tanzania ²national institute of transport (nit) department of logistic and transport, p.o. box 705, mabibo road, dar es salaam. tanzania ³u hasselt – transportation research institute (imob) maastrichterstraat 100, 3500, hasselt, belgium abstract the commercial transport sector is threatened with many (severe) traffic injuries and deaths, especially in african countries like tanzania. the primary causes are limited driving skills and knowledge about traffic safety, and risky driving behaviours (e.g., driving at high speed, driving while under the influence of alcohol, being distracted by mobile phones, and tiredness. the study assesses the effectiveness of e-learning for professional bus driver training in tanzania. the research involved document analysis, interviews, and a survey of 153 participants, including drivers and trainers. results indicate that elearning is well-received and effective in improving knowledge and potentially reducing road accidents. customized elearning training modules with a tailored learning management system were developed to address the specific needs of commercial drivers in tanzania and improve road safety. the interviewed experts positively reacted to the developed elearning program, hoping it would improve safety and eco-driving. overall, the study indicates that e-learning can be a valuable tool for modernizing driver training, improving safety standards, and creating a safer driving environment in tanzania and beyond. keywords: professional bus drivers, curriculum, e-learning, tanzania received on 23 february 2024, accepted on 11 april 2025, published on 05 may 2025 copyright © 2025 m. chacha et al., licensed to eai. this is an open access article distributed under the terms of the cc by-nc-sa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.5186 1. introduction professional drivers, such as bus and truck operators, are crucial in ensuring road safety ([1] [2]. their job is not just about transporting passengers or goods safely; they also carry the responsibility to their profession through their training programs on a global scale [3]. previous studies and organizations emphasize the importance of proper education for these drivers [4] [5]. for example, the international labour organization (ilo) points out the importance of keeping drivers safe and healthy at work, supporting the argument for prioritizing their education [6] [7]. *corresponding author. email: marwadchacha@gmail.com the united nations (un) advocates for standardized driver education worldwide [8]. as part of its efforts, the un supports the implementation of comprehensive training programs aimed at reducing road accidents and fatalities by 50% by 2030 [9]. programs like the graduated driver education (gde) in the european union help improve driver knowledge, make drivers more aware of risks, and encourage them to think about their driving habits [10]. moreover, elearning in countries like the uk, germany, and the us makes driver training more flexible and accessible, which could help reduce road accidents [11]. in africa, however, progress is hindered by limited resources and inconsistent regulations, despite initiatives like the east africa training curriculum [6] [12]. south africa and kenya are progressing towards incorporating e-learning in their eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ m. chacha et al. 2 training strategies, with kenya enhancing its technical and vocational education and training (tvet) with ilo support [13] [14]. on the other hand, tanzania continues to rely on traditional classroom-based instruction for its bus driver training program. introducing e-learning in tanzania could significantly improve driver training, align it with international standards, and improve road safety. 1.1 driver education in tanzania the commercial transportation industry faces a significant challenge of road accidents resulting in injuries and deaths [7]. according to statistics from the world health organization (who), despite having only 60% of the world's vehicles, lowand middle-income countries account for 92% of road traffic deaths, with a staggering 1.19 million fatalities globally each year [15]. the european agency for safety and health at work also reports that professional drivers have a high risk of death in road traffic accidents, with 85% caused by human errors (united nations conference on trade and development [16]. in east africa include tanzania, factors such as inadequate training, inattentiveness, drunk driving, drug use, over speeding, wrong overtaking, poor knowledge of traffic rules, and physical disability contribute to road accidents [17] [18] . commercial drivers are at a higher risk of such crashes due to driving long distances, over speeding, fatigue, weather conditions, and road curvature [19] [20]. however, research shows that there is a severe shortage of professionally skilled commercial drivers in east africa, with only 38% of transport operators having undergone a professional course in transport [21]. the lack of qualified drivers is further compounded by the prevalence of unsafe driving practices, such as driving under the influence of alcohol or drugs and engaging in illegal activities while on duty [21]. to mitigate this issue, a structured practical driving training program that includes awareness of potential hazards and avoidance measures, training facilities, and qualified trainers for commercial drivers is required [22] [23]. while driver education is widely seen as a way to improve road safety, akbari et al. [24] suggest it has not reduced crashes, injuries, or deaths. however, their study's lack of impact could be due to the teaching methods or course content not working, mismatches in how adults learn best, or the programs not targeting the specific risky driving behaviours that cause the most accidents. china's driver training overhaul 2013 addressed road safety concerns with stricter training (mandatory hours, attendance tracking) and a more arduous 4-subject exam. the new system emphasizes traffic knowledge and practical skills, including simulator tests, onroad manoeuvres, and safe driving awareness to reduce road accidents [25]. in 2015, the national institute of transport (nit) in tanzania implemented a commercial driver curriculum for buses and trucks [21]. in 2016, the program expanded into a standardized professional driver training program across east africa, including kenya and uganda [26]. the initiative is supported by organizations such as giz and transaid and is funded by bmz, dfid, and norad. the training covers traffic laws, mechanics, and customer care, with varying durations across different countries. the current training program for commercial drivers in tanzania heavily relies on traditional classroom instruction. however, online services are gradually being incorporated into driver training through institutions like the tanzania revenue authority (tra), nit, and land transport regulatory authority latra [18]. the effectiveness of online technology in commercial driver training has been demonstrated in developed countries such as europe and the united states, leading to improvements in road safety [27] [28]. 1.2 driver education worldwide driver education programs are continuously evolving, and it is crucial to scientifically evaluate their effectiveness before widespread adoption [27] [29]. several studies have shown that training programs can help drivers acquire the skills and knowledge to prevent traffic crashes caused by fatigue, distraction, and reckless driving [28]. for example, the european union (eu), the united states (us), and canada have implemented successful training programs to improve commercial driver behaviour [24] [30]. even in africa, initiatives like south africa's fleetwatch showcase the value of comprehensive driver training, which integrates practical learning with ongoing assessments [13] [14]. in recent years, there has been a shift towards more comprehensive training methods, including uses user-friendly online tools and optimized learning management system (lms) with simulations and quizzes, enhancing learning and safety [31]. a lms can benefit truck and bus drivers by providing specialized training modules covering driving techniques, safety protocols, and regulatory compliance tailored to their needs. for instance, logistics companies in the us and uk utilize lms to train their global workforce of drivers on safety protocols and operational efficiency [30] [32]. recent research suggests that the education provided to commercial drivers may need to be enhanced to meet the demand for operating advanced driver assistance systems (adas) and future automated vehicles (avs) [33]. safe operation of these technologies requires a specific skill set, including understanding system limitations and high-level cognitive abilities [8]. this is similar to the practice in the aviation and maritime industries, where ongoing training is crucial for optimal performance [33]. like pilots and maritime crews, adas users will likely need continuous education to adapt to advancing technology and ensure safe operation [29] . in developed countries, professional commercial drivers must undergo periodic training before renewing their driver's license. for instance, in the eu, professional drivers must undergo mandatory training for 35 hours each five years [11]. digital tools such as online training modules incorporated with lms and artificial intelligence (ai) powered virtual reality simulations can significantly enhance these training programs [32]. for instance, the united kingdom (uk) driver and vehicle standards agency offers practice tests where eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | development and evaluation of e-learning for professional bus drivers in tanzania 3 drivers watch videos and click on the screen when they see a developing hazard [8]. another study suggests video-based training may be more effective, particularly for females, in reducing cognitive load and improving adas use [34]. however, developing countries like tanzania lack enough modern training programmes for commercial drivers. this is mainly due to insufficient funding, outdated facilities, and lax enforcement. as a result, there is a heavy reliance on minimal formal education and extensive on-the-job training, resulting in a workforce that needs more skills and experiences higher accident rates. additionally, current programs only use classroom and practical methods. finding innovative solutions to transform driver education in these regions is essential. 1.3 study focusses and contributions based on the literature review above, an e-learning (blended) curriculum, which combines traditional classroom learning with e-learning technology and assessment, could be interesting for commercial driver training in tanzania. however, this area has yet to be extensively explored in tanzania. therefore, this study explores the potential use of e-learning to enhance traffic knowledge and awareness among commercial drivers in tanzania. this study aims to assess the training methods for commercial bus drivers in tanzania and create an e-learning framework with optimum lms to improve road safety. the goals are to modernize driver training, raise safety standards, and establish a scalable e-learning model specific to tanzania. the study will focus on evaluating the effectiveness of current training in teaching road safety and understanding stakeholders' views on digital learning. ultimately, the aim is to develop a well-structured e-learning platform for educating professional bus drivers. 2. methods 2.1 document analysis the research examined the east african community (eac) standardized driver training curriculum for bus drivers. the theoretical and practical aspects were analysed, including the curriculum's objectives, content, structure, delivery methods, and assessment techniques. additionally, procedures for renewing a commercial driver's license were checked and how they integrate with training programs. the priority on road safety for commercial drivers by national regulations and the eac curriculum were also considered. literature on the guidance and legislation of training programs for commercial drivers was investigated, focusing on the feasibility of online or elearning platforms and lms for bus and truck drivers. this involved searching on platforms such as elsevier using keywords like "guidance and legislation for commercial drivers" and "professional drivers." the study covered resources from various continents, organizations, and specific countries, including national websites, to identify suitable content for an online and lms for bus driver training programs in tanzania. the validity and credibility of this secondary research are maintained through reputable sources. key sources include documents from the international road transport association (iru) and the european union (eu), both wellregarded authorities in the field. additional sources from government websites and reputable academic studies further enhance the credibility of the research. all documents were publicly accessible, ensuring transparency and ease of verification. 2.2 survey and interview this research extends a master's thesis conducted by magoti [12] in dar es salaam, tanzania. data for this study were gathered through an online survey using qualtrics, a platform provided by hasselt university, and semi-structured interviews. the survey was conducted over three weeks, from february 7th to february 28th, 2021. each of the 153 participants who completed the survey spent an average of 5 minutes on it. participants from nit, veta, road safety ngos, and bus drivers in dar es salaam collaborated with latra, the regulatory authority overseeing commercial transportation safety in tanzania. the participants completed the survey voluntarily, without any financial compensation or incentives. semi-structured interviews were conducted to assess the readiness for elearning and its effect on bus driver training at the nit. the participants were drawn from various organizations: five officials from nit, one from the latra, and one from the union of tanzanian women lawyers (umawata), all located in dar es salaam, tanzania. these interviews occurred between 8:30 am and 9:10 am east africa time. on average, discussions with nit and latra representatives lasted 40 minutes, while the conversation with the umawata officer was around 30 minutes. follow-up discussions highlighted latra's initiation of a new driver certification process in 2023. this new process includes online registration and computer-based tests for commercial drivers, which aims to make the license renewal and certification process more efficient. moreover, 20 participants were in the pilot test of the elearning training, which involved one trainer from nit, one officer from latra, and 18 bus drivers on the defensive driving module. ethical approval was received by the tanzania commission for science and technology (costech) under reference number 2023-898-na-2023-975. 2.3 data analysis the study involves an analysis of the strengths, weaknesses, opportunities, and threats (swot) of the eac of passenger service vehicle driver curriculum and document analysis to investigate the international approaches. surveys and interviews were conducted with nit, veta, and latra. the data was analysed using ssps version 29, focusing on descriptive statistics, handling multiple responses, and eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | m. chacha et al. 4 showing how different categories, like people's backgrounds and views on e-learning, are connected. the study also used chi-square tests to determine what makes e-learning appealing to people and to see its effects on knowledge enhancement, skill improvement, attitudes towards road safety, and its role in reducing road accidents. for an interview, the study used nvivo version 15, a computer program that helps organise and understand interview information. first, what was said in the interviews was typed and put into nvivo. then, the main points were picked out. with more examination, these points were grouped into themes like how e-learning is growing, what people think about it, how courses are designed, how comfortable people are with technology, pressure from jobs, and the advantages of studying online. ultimately, these themes were brought together to show the valuable insights from the study clearly. 3. results 3.1 the swot analysis of eac passenger service vehicle driver curriculum the curriculum review found it well-structured with a precise aim to improve driver competency and overall transport efficiency in the eac [12] [35]. it covers essential areas like safe driving, vehicle maintenance, and regulations. the eac's standardized driver training program for passenger vehicles shows promise in boosting driver competency and regional transport efficiency. it tackles critical areas like safe driving and regulations with a balanced theory and practical training mix. however, a closer look reveals a need for more detailed practical assessments, addressing language barriers, and incorporating training on new vehicle technologies. a swot analysis (see figure 1) offers a deeper dive into these strengths, weaknesses, opportunities, and threats. overall, the program presents a positive step for the eac, but refinements can maximize its impact on road safety and transport efficiency. this is a list, note the hanging indent. this is a list, note the hanging indent. this is a list, note the hanging indent. this is a list, note the hanging indent. this is a list, note the hanging indent. this is a list, note the hanging indent. 3.2 document analyses to investigate international approaches to e-learning commercial driver training this research examined the use of e-learning in commercial driver training programs from different countries (see table 1). the study aimed to analyse these international models to identify best practices that could be applied to the specific context of tanzania. figure 1: swot analysis of reviewed curriculum of eac passenger vehicles driver training programme table 1 international approaches to e-learning for commercial driver training location guidance/ legislation focus literature source uk driver certificate of professional competence (dcpc) program risk perception, defensive driving, ecofriendly driving, customer service [9] [10] [11] [36] asia online logistics training/remove barrier for cpc supplemental online modules for driver commercial drivers [29] [37] [38] eu driving license directive revision and driver cpc course (edcpc) new mobility challenges, digital tools, legal requirements, safety protocols, vehicle maintenance, health considerations, vulnerable road users [27] [39] [40] [41] eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | development and evaluation of e-learning for professional bus drivers in tanzania 5 africa study on commercial driver’s training and compliance lack of training in areas like trafficking in persons and emerging technologies. potential opportunity for online refresher courses. [12] [13] [24] [26] [42] australia guidance and legislation for professional driver training foundational knowledge via online training with lms, practical skills through inperson instruction methods. [10][43] [44] [45] canada national safety code comprehensive online training for professional drivers with topics like defensive driving, risk detections, customers care with optimized lms [19] [46] 3.2 survey results 3.2.1 demographic characteristics regarding occupation status, 55.6% identified as bus drivers, 8.5% as trainers, and 35.9% fell into the 'other' category. regarding holding a bus driving license, 74.5% reported having one, while 25.5% did not. regarding driving experience, 9.8% had less than one year of experience, 13.1% had one to two years, 19.6% had three to five years, and 13.7% had more than five years of experience, with a notable 43.8% of data missing in this category. among the respondents, 62.1% were bus drivers, 8.5% were trainers, and 29.4% were students familiar with driver training. the survey revealed a diverse educational background among the participants, with 37.2% being university graduates, 32.3% having completed secondary school or lower, and 25.5% being college-educated. the respondents were involved in operating different types of buses: 32.6% long-distance, 28.4% brt, 25.3% transit (daladala), and 13.7% school buses, representing a wide range in the industry. 3.2.2 summary of driving training and related opinions table 2 below summarises survey results on the drivers’ observations based on the driving schools attended, the procedures applied to renew driving licenses, and the perceived benefits of assessing bus drivers to streamline for elearning. age groups categorize the data: less than 25 years, 25 to 34 years, and greater than 35 years. the total number of respondents for each category is also provided. in terms of adherence to traffic laws, 64.9% of drivers consistently comply, attending training before license renewal, while 35.1% comply only by periodically remitting the license fee. table 2: survey results by age group and total respondents 3.2.3 awareness, opinion toward usage of online tool and training module for lms according to the survey data, 66% of respondents are familiar with e-learning training methods, while 34% are not. regarding opinions on using e-learning for professional bus driver training, responses vary: 31.4% are highly willing to adopt it, 24.8% show moderate willingness, and 11% feel unable to embrace e-learning. when it comes to preferred devices for accessing elearning content, the majority choose smartphones 39.4%, followed by computers 23.1% and desktops 16.3%. additional details about the module (see figure 2). eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | m. chacha et al. 6 moreover, chi-square tests reveal significant associations supporting the study's key findings. stakeholders show high awareness and acceptance of e-learning methods, with a strong consensus on its use in professional bus driver training and positive attitudes towards its potential to improve road safety (χ² = 120.47, df = 5, p < .001). e-learning significantly enhances drivers' knowledge and practices (χ² = 67.33, df = 1, p < .00) and highlights the importance of training before license renewal (χ² = 41.02, df = 1, p < .001). there is substantial support for the adequacy of training components and the perception of professional driver training's role in improving traffic safety (χ² = 236.42, df = 2, p < .001). furthermore, data strongly support that e-learning can reduce road accidents, demonstrated by the significant association between eco-driving practices and reduced fuel consumption (χ² = 63.15, df = 4, p < .001) and the belief that e-learning enhances road safety measures (χ² = 159.14, df = 5, p < .001). figure 2: preferred training module by driving experience 3.3 interview results in interviews, uwamata's chairman and drivers supported the adoption of elearning. they emphasized initiating a pilot study and specialized instructor training aligned with nit and latra recommendations. latra emphasized the importance of professional training for drivers whose licenses expired in 2019, advocating for a periodic training curriculum to enhance road safety. they noted the efficacy of digital processes, including computer-based tests and online registration, which bolstered road safety through a vehicle tracking system monitored by latra. safety efforts are supported by video clips on various social media platforms. in 2023, 7,580 drivers were registered, with only 2,769 of them examined and only 1,613 passing the driver certification at latra. additionally, drivers who failed the driving examination for commercial vehicle qualification, including buses and trucks, were suggested to return to driving schools such as nit and veta for refresher courses, which are not currently available. latra's data report describes commercial vehicle drivers' challenges when applying for computer-based exams. within this report it is mentioned: “many lack adequate preparation and have not yet had refresher courses if their initial training was long ago. high pressure from employers to take the exam adds to their stress. additionally, there is fear and discomfort with using ict facilities for the examination. many drivers are unaware of the exam's importance, and the fear of failing further exacerbates their anxiety”. this highlights the importance of elearning, which, when integrated with an optimized lms, can be highly beneficial for commercial drivers by monitoring their performance before and after exams. 3.4. development of elearning modules the elearning modules were created using best practices identified through literature reviews, surveys, and stakeholder interviews. based on this information, six modules for tanzania's professional bus driver training program were developed, including traffic rules, defensive driving, injury prevention, fuel-efficient driving, health and ergonomics, and customer service. each module is designed for 40 to 60-minute sessions to understand each area thoroughly. the proposed pilot elearning modules for bus drivers can be seen in figure 3 and table 3 below. the updated training includes interactive elements such as quizzes, simulations, and hands-on activities to improve understanding of concepts (table 3). this enhanced program is developed based on survey feedback and follows the european cieca-rue model [11] [12]. it incorporates multimedia tools to make learning more practical and engaging, and course progress is monitored through the lms to elevate driving and safety standards in tanzania. 0 2 4 6 8 10 12 14 16 < 1 year 1-2 years 3-5 years > 5 years customer service defensive driving fuel efficiency injury prevention health and ergonomics module objective content assessment traffic rules understand traffic laws and regulations traffic laws, road signs, speed limits quizzes, road sign exercises defensive driver training prevent accidents through defensive driving defensive driving principles, hazard avoidance, safe distances simulations, judgement tests injury prevention prevent injuries for drivers and passengers ergonomics, lifting techniques, seat belts videos, practical exercises fuel-efficient driving reduce fuel consumption and costs efficient driving, vehicle maintenance fuel tracking, ecodriving simulations health and ergonomics promote driver health and wellbeing health check-ups, nutrition, stress management wellness activities, health quizzes customer service improve passenger interactions communication skills, handling difficult passengers role-playing, feedback analysis table 3 summary of e-learning training framework for professional bus driver eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | development and evaluation of e-learning for professional bus drivers in tanzania 7 3.5 the proposed lms layout for professional driver training programme a new driving training system is being developed for use in tanzania. its features include interactive learning options and easy access to different driving techniques. the aim is to improve the way driving knowledge is shared and learned. this system also seeks to bring more openness to the training process for instructors and drivers, especially when renewing licenses is time. this should help reduce corruption and make driving safer. a trial was run using free learning management software to test this idea. this trial showed that instructors could quickly set up the system, create detailed courses, and control who accessed these courses. instructor(s) were also able to give feedback on assignments and quizzes efficiently. it was found that the courses could be accessed on a wide range of devices, such as smartphones, tablets, and laptops, or even in traditional classroom settings at driving schools. the 20 driver participants volunteered to be trained in one module on defending driving, which involved texts, pictures, and short videos that were easy to access and get feedback from the trainer and trainee. 80% of the participants completed the course and got good marks (see figure 3). 4. discussion 4.1 driver education in tanzania this study aimed to create a new approach to learning that increases awareness of road safety among professional bus drivers. it involved evaluating the current curriculum and exploring the potential of an elearning platform for commercial driver training. the document analysis describes the current professional bus driver training in tanzania, highlighting several ongoing issues that need attention. these issues are consistent with global studies that have identified similar challenges. for instance, a study in india by nilekani, [47] pointed out that bus driver training programs need more practical elements. similar concerns were raised in research from iran and china by taravatmanesh et al. [48] and zhang et al. [49], respectively, where bus drivers had poor safetyrelated knowledge and skills. in african countries, including tanzania nigeria and south africa [6] [12] [23] [50] commercial drivers need more awareness about the requirements for obtaining a driver's license. this issue is exacerbated by weak enforcement of regulations, highlighting a widespread need for improvements in driver training programs and regulatory practices to enhance road safety. the current curriculum for commercial bus drivers in tanzania has effectively improved road safety skills and knowledge [12] [22] [47] [51]. this competency-based curriculum sets minimum standards for drivers of large commercial vehicles, including freight and passenger transport. however, some areas need improvement, such as more detailed practical assessments, addressing language barriers, and incorporating training on new vehicle technologies. a swot analysis of the eac curriculum has identified these strengths and weaknesses. while the program is a positive step, refining it could further enhance its impact on road safety and efficiency. best practices in professional bus driver training worldwide, particularly in canada and sweden, show that comprehensive training programs are essential for safety and efficiency. canadian programs typically last 12 weeks, while swedish ones last for 10 weeks. according to studies by akbari et al., [24] and elvebakk et al. [11] these programs blend classroom learning with hands-on practice, among others. the european directive 2003/59/ec also outlines the need for 35 hours of periodic training for commercial drivers, including theory and practice [6] [27]. there is a growing recommendation for tanzania to adopt a client-centred approach to bus driver training. this would mean including relevant training content and offering flexible hours for theoretical and practical lessons, similar to what is seen in developed countries such as alternative training methods such elearning. this approach, supported by researchers ji-hyland & allen [10] could significantly enhance road safety and fuel economy in tanzania, as pointed out by runyoro et al. [52]. figure 3: the structure of proposed the prototype of elearning eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | m. chacha et al. 8 4.2 survey and interview insights the study provided a deep understanding of people's thoughts and feelings about elearning by using surveys and semi structured interview. everyone involved, like drivers, instructors, and policymakers, was positive and supportive of using elearning methods. this optimistic view is backed up by findings from a study in malaysia by harith and others in 2019, which found that online learning significantly helps improve drivers' knowledge and skills. a survey showed that many participants know about elearning and are open to using it for job training. this shows that elearning could be successful and famous [10] [34]. however, the survey also found that people have different driving experiences and education levels. elearning programs must be customized to fit everyone's learning speed and knowledge. the recommended modules should be accessible via smartphones, tablets, and laptops, which aligns with most respondents' preference for smartphone-based training for professional drivers (loizides, 2019). an interactive platform, suggested by elvebakk et al., [11] [53] would promote active engagement through embedded assignments, quizzes, and tests. this platform could also adopt gamification techniques, which have been found beneficial according to previous studies [24] and the expost evaluation report by european commission, . preventing road accidents and injuries for the safety of employees (praise) in 2011 portrayed the bus driver training methods include online training [43]. these elements, aimed at motivating bus drivers internally, have been supported by various european research, including the praise report the eu's legislative framework concerning professional driver training [27] [30]. these documents recommend elearning tools for long-distance driver training. additionally, efforts in europe and the usa have identified the importance of safe driving, the social environment's influence, and integrating smartphones into driving safety as key to altering drivers' behaviours, according to murtaza et al. [33] and peer et al. [54] . the interviewees discussed how elearning could make roads safer by improving professional bus driver’s training. officials from latra said regular training for renewing a driver's license and using digital methods and computer tests could help with road safety[33] [44] [54]. however, there were some problems mentioned. some drivers feel pressure from their jobs and need to be more comfortable using technology [34] [50]. this highlights the need for special programs like basic tech training and continuous support to help drivers feel more confident using digital tools [27] [53]. 4.3 trial of the lms prototype the trial of the lms prototype involved 20 participants, including one trainer from nit, one trainer from latra and 18 bus drivers who tested the module on defensive driving. this module featured accessible texts, pictures, and short videos. trainers and trainees found it easy to use and effective for providing feedback. the trial showed high completion rates, with 80% of participants completing the course and achieving high marks. this aligns with experiences from studies in australia and canada, where elearning modules combined with practical skills training have shown significant improvements in driver competency and road safety [13] [30] [33]. also, adding game elements to learning, as shown by akbari et al. [24] can make trainees more eager to learn about safety on the road. 4.4 implications and recommendations adding elearning to tanzania's bus driver training can make driving safer and improve the transport system. a study found much support for elearning. however, challenges like technology issues and pressures from employers need to be solved. using intelligent digital tools and keeping the training content fresh and relevant can help tanzania upgrade its driver education. this can lead to safer roads and more efficient transport. participants like the idea of elearning. early tests with an elearning platform and analysis showed that a well-planned elearning program could improve the current training. it is essential to keep talking with everyone involved, monitor progress, and update the elearning content to keep it helpful for bus drivers. this way, road safety and transport efficiency can get better over time. 4.5 limitations of study and future study the study on elearning for bus drivers in tanzania is a big step but has some limits. it only looked at a few drivers from dar es salaam because of the covid-19 pandemic, limiting the generalizability of the findings. future studies should expand to include drivers from various regions across tanzania to gain a more comprehensive understanding of elearning adoption. additionally, the study did not fully explore cultural perceptions of online learning among drivers, which is crucial for successful implementation. future studies should expand beyond dar es salaam to include drivers from various regions in tanzania, providing a broader perspective on elearning adoption. research should focus on drivers aged 25-50, assessing their willingness, attitudes, and digital literacy through surveys and focus groups. a detailed implementation plan is needed to address adoption challenges, accessibility, and learning module design. engaging key stakeholders such as latra, traffic authorities, and fleet companies will be crucial. additionally, integrating gps tracking into elearning and raising awareness among fleet operators about its benefits can enhance driver competence, road safety, and operational efficiency. 5. conclusion introducing elearning could significantly improve driving education in tanzania by making roads safer and drivers eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | development and evaluation of e-learning for professional bus drivers in tanzania 9 more knowledgeable. research found that online courses are better than traditional classes, leading to fewer accidents. countries using elearning noticed that drivers improved at spotting dangers, had better attitudes, and drove more ecofriendly. this method not only helps reduce accidents but is also beneficial for driving schools and companies by allowing for better feedback and ensuring rules are followed. feedback on elearning has been positive, indicating it could fill current training gaps effectively. a successful online program needs continuous updates and input from everyone involved to ensure it meets drivers' needs. this effort will lead to safer roads and more efficient transportation in tanzania. acknowledgements we are grateful to everyone involved in our project, especially the folks at the transportation research institute (imob) at hasselt university in belgium and the participants. their support was excellent. we also want to mention the financial help from the bilateral scientific cooperation bof uhasselt (bof22bl03). thanks to the ministry of transport team, especially stella j. katondo, the director of transportation safety and environment, for their essential contributions. a heartfelt thanks to mr. jerive s. malaki and geoffrey l. silanda from latra for their excellent cooperation and insights, which immensely helped our project. competing interests the authors declare no conflict of interest. references [1] b. elvebakk, t.-o. nævestad, and l. c. lahn, ‘mandatory periodic training for professional drivers: a norwegian study of implementation and effects’, transp. res. part f traffic psychol. behav., vol. 72, pp. 264–279, jul. 2020, doi: 10.1016/j.trf.2020.04.014. 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[55] ‘on-board safety monitoring systems for driving: review, knowledge gaps, and framework’, j. safety res., vol. 43, no. 1, pp. 49–58, feb. 2012, doi: 10.1016/j.jsr.2011.11.004. eai endorsed transactions on smart cities | volume 7 | issue 4 | 2023 | this is a title eai endorsed transactions on smart cities research article 1 integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development. sargiotis dimitrios1* 11st national technical university of athens, zografou campus, 9, iroon polytechniou str., 15772 zografou, athens, greece. abstract the accelerating convergence of artificial intelligence (ai), machine learning (ml), and digital transformation is redefining the landscape of civil engineering and disaster governance. this paper presents a multidisciplinary framework that integrates ai-driven analytics, information and communication technology (ict) innovations, and emerging paradigms such as quantum computing and blockchain to enhance disaster preparedness, infrastructure resilience, and sustainable urban development. it examines how ai and ml enable predictive maintenance, early-warning systems, and data-driven decision-making, while ict and internet-of-things (iot) networks strengthen communication, monitoring, and real-time coordination. the study also highlights the role of virtual simulation and digital-twin environments in transforming civil engineering education and professional training. through a comparative analysis of global case studies—from aipowered smart-city applications to autonomous green stormwater infrastructure—the research demonstrates that digital integration can foster adaptive, efficient, and ethically grounded engineering systems. ultimately, the paper advances the discourse on ai-enabled civil engineering by proposing a cohesive digital pathway toward resilient, sustainable, and humancentric urban futures. keywords: digital transformation in civil engineering; artificial intelligence (ai) in civil engineering; machine learning (ml) for disaster management; sustainable and resilient urban development; information and communication technology (ict) for disaster risk reduction; virtual and simulation-based engineering education; digital twins and infrastructure modeling; ai-powered smart city applications; internet of things (iot) for environmental monitoring; geospatial and remote sensing technologies; predictive analytics for infrastructure resilience; ethical and sustainable ai integration; cross-disciplinary engineering innovation.. received on 13 november 2024, accepted on 10 november 2025, published on 13 november 2025 copyright © 2025 sargiotis dimitrios, licensed to eai. this is an open access article distributed under the terms of the cc by-ncsa 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited. doi: 10.4108/eetsc.7824 *corresponding author. email:dims@central.ntua.gr 1. introduction the contemporary convergence of artificial intelligence (ai), machine learning (ml), and digital technologies within civil engineering constitutes a paradigmatic transformation in how societies conceptualize, design, and safeguard the built environment. this integration transcends the incremental automation of traditional processes, signifying instead a systemic reconfiguration of disaster management, sustainable urban development, and engineering intelligence. the current discourse examines this technological renaissance, spanning from predictive analytics and intelligent design methodologies to smart infrastructures that self-adapt and evolve. it positions ai and ml not merely as computational tools but as epistemological agents redefining the capacity to forecast, interpret, and mitigate complex urban and environmental phenomena. within this expanding digital ecosystem, ai-enabled predictive systems provide early warnings and continuous surveillance for infrastructure resilience. machine learning algorithms, through predictive maintenance and structural health monitoring, pre-empt critical failures by identifying latent vulnerabilities across bridges, tunnels, and eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | https://creativecommons.org/licenses/by-nc-sa/4.0/ https://creativecommons.org/licenses/by-nc-sa/4.0/ dimitrios sargiotis 2 transportation networks. concurrently, ai-driven optimization frameworks are reshaping design paradigms in civil and structural engineering—enhancing sustainability, material efficiency, and lifecycle performance through generative and data-driven approaches. the same computational intelligence underpins advances in construction management, enabling adaptive scheduling, dynamic resource allocation, and precision-driven safety protocols that redefine operational efficiency. equally transformative is the integration of information and communication technology (ict) innovations into the civil engineering domain. platforms such as epicore illustrate how distributed information systems can rapidly authenticate early signals of public health or environmental threats, strengthening multi-sectoral disaster preparedness and coordinated response. ict-based frameworks now underpin real-time damage assessment and recovery operations, streamlining decision-making under extreme uncertainty and compressing the temporal gap between disaster onset and effective intervention. parallel advancements in immersive learning and simulation technologies further bridge the divide between theoretical understanding and applied engineering practice. virtual laboratories and digital twins—ranging from dynamic plant floor emulators to urban mobility models— provide interactive environments for experimentation, design validation, and knowledge transfer. in professional contexts, digital twins extend beyond visualization, functioning as cognitive replicas that integrate multisource data to predict infrastructure behavior, optimize maintenance schedules, and enhance adaptive resilience under changing climatic conditions. the rise of ai-powered mobile applications within smart city ecosystems epitomizes the diffusion of intelligence across urban layers. these systems advance public safety, infrastructure monitoring, and emergency coordination through decentralized yet interconnected analytics. they also enable fine-grained control of urban metabolism— optimizing energy consumption, waste management, transport efficiency, and air quality management. in parallel, the proliferation of internet of things (iot) devices generates a continuous stream of environmental and structural data, fostering a new era of evidence-based planning and sustainability-oriented governance. moreover, geospatial intelligence—anchored in geographic information systems (gis) and remote sensing—has become indispensable for spatially explicit analysis in disaster risk reduction, resource optimization, and land-use planning. these technologies, through multilayered data fusion and machine reasoning, empower decision-makers to anticipate vulnerabilities and deploy targeted interventions at unprecedented temporal and spatial resolution. this introductory section underscores the transformative capacity of ai, ml, and digital technologies to re-envision civil engineering as an intelligent, adaptive, and ethically grounded discipline. by synthesizing insights from computational science, systems engineering, and urban informatics, it advocates for a digitally empowered framework that advances resilience, efficiency, and sustainability across all dimensions of the built environment. ultimately, the discussion sets the conceptual foundation for understanding how digital innovations— anchored in human-centric design and scientific precision—are redefining the future of civil infrastructure and disaster governance in the anthropocene. 2. methodology the methodology section of this paper articulates the systematic approach undertaken to explore the transformative impact of digital technologies on civil engineering, with a special focus on disaster management and sustainable urban development. central to our investigation is the integration of artificial intelligence (ai), machine learning (ml), and a suite of digital innovations within the civil engineering landscape. this involves a meticulous analysis spanning a comprehensive literature review, case study evaluations, and the application of theoretical frameworks to practical scenarios. through the lens of academic journals, conference proceedings, and real-world examples, we dissect the role of digital advancements in reshaping civil engineering practices. our methodology is designed to not only highlight the efficacy of these technologies in enhancing project outcomes but also to identify barriers to adoption and propose strategies for effective integration. by employing a multidisciplinary approach, we aim to bridge the gap between technological potential and its tangible benefits, thereby offering insightful recommendations for practitioners, policymakers, and researchers committed to the future of civil engineering. 3. artificial intelligence (ai) and machine learning (ml) innovations in civil engineering recent scholarly contributions have illuminated the expanding role of artificial intelligence (ai) and machine learning (ml) in reshaping predictive analytics, optimizing design methodologies, and advancing construction management within civil and material engineering. the integration of ai into predictive maintenance frameworks marks a decisive evolution toward proactive disaster risk mitigation, allowing early identification of infrastructure fatigue and preventing catastrophic failures before their onset. machine learning algorithms, through their capacity to analyze large-scale and heterogeneous datasets, are likewise redefining urban analytics—facilitating data-driven, adaptive decisionmaking processes that underpin the development of resilient and sustainable cities. collectively, these eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 3 advances signify the transition of civil engineering from a reactive discipline grounded in empirical heuristics to a forward-looking science of intelligent systems and anticipatory design. 3.1. case studies the empirical literature demonstrates the versatility and depth of ai-driven innovations across various domains. the study real-time hollow defect detection in tiles using on-device tiny machine learning [1] exemplifies an industrial-scale implementation of edge-based intelligence in the manufacturing sector. utilizing convolutional neural networks (cnns), the authors develop an embedded system capable of detecting hollow defects in ceramic tiles with real-time precision, thus enhancing quality assurance while reducing inspection latency and cost. similarly, applications of bentonite in plastic concrete: enhancing workability and predicting compressive strength using hybridized ai models [2] integrates hybrid ai techniques to predict the mechanical properties of bentonite-based concrete mixtures. this research underscores ai’s emerging role as a scientific instrument in material optimization and performance forecasting, advancing the frontier of sustainable construction materials. in the broader context of industrial digitalization, industrial engineering and operations management: xxix ijcieom, lisbon, portugal, june 28–30, 2023 highlights the transformative effects of digital transformation (dx) and ai within engineering systems, emphasizing the convergence of data analytics, automation, and intelligent process control in construction operations. extending these innovations to optical and structural domains, a distributed photonic crystal fiber reverse design framework based on multi-source knowledge fusion [4] introduces a multi-source knowledge fusion approach for optimizing photonic crystal fiber (pcf) designs. through the use of machine learningdriven reverse design methodologies, the study demonstrates how ai-enhanced optimization frameworks can accelerate material innovation and enhance the analytical precision of complex structural systems. these exemplars illustrate the breadth and maturity of ai and ml applications in contemporary civil engineering— spanning material science, construction operations, structural optimization, and smart manufacturing. the literature on digital transformation converges on a shared insight: that ai, ml, and information and communication technology (ict) collectively constitute the cornerstone of a new epistemology in civil engineering—one grounded in prediction, automation, and cyber-physical integration. beyond addressing persistent challenges in disaster management and urban planning, these technologies redefine pedagogical and research methodologies by embedding simulation, digital twins, and virtual experimentation within civil engineering education. this evolving research landscape affirms the centrality of ai-driven systems in cultivating the next generation of resilient, efficient, and sustainable infrastructures. as the discipline advances into an era of intelligent engineering, continuous innovation in computational methods, data governance, and cross-domain integration will be indispensable for confronting the complex socioenvironmental challenges of twenty-first-century urban civilization. recent research exemplifies the growing integration of artificial intelligence (ai) and machine learning (ml) in civil and construction engineering, marking a decisive transition toward predictive, data-driven, and adaptive methodologies. the study machine learning application in construction delay and cost overrun risks assessment by khodabakhshian, malsagov [5], and collaborators investigates how ai and ml can transform risk management frameworks by quantifying uncertainty and modeling delay and cost overrun probabilities with enhanced precision. complementarily, pham and nguyen’s performance review of rti ims software for automatic road surface damages identification demonstrates the potential of ml-based detection algorithms—particularly the yolo architecture—in achieving automated and real-time identification of pavement defects, thereby improving maintenance planning and roadway safety. in a more futuristic dimension, kaswan, dhatterwal, prakash, and colleagues [7] in research trends in intelligence-based bioprinting for construction engineering applications introduce intelligence-driven bioprinting as a novel frontier in construction materials science, highlighting how ai–ml fusion enables adaptive design and bio-structural optimization. the study innovative ict in smart buildings domain: a patentometric analysis by sandbhor, mulay, tiwari, and others provides a patent-based analytical overview of emerging ai–ml innovations in smart building systems, revealing global trends in automation, interoperability, and energy efficiency. finally, gohel, dabral, lad, patel, and collaborators [9] in a comprehensive review on application of artificial intelligence in construction management using a science mapping approach present a systematic evaluation of ai’s impact on construction management processes, emphasizing deep learning and hybrid ml techniques as the dominant paradigms reshaping the sector’s digital transformation. these studies encapsulate the multidimensional role of ai and ml in the evolution of civil engineering—from construction risk modeling and infrastructure diagnostics to bio-inspired fabrication and intelligent building design. they reflect the discipline’s ongoing reorientation towards computational intelligence, efficiency, and innovation, underscoring a broader paradigm shift in engineering eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 4 practice toward automation, resilience, and sustainable digital transformation. question: how can ai and ml be applied in sustainable urban development? based on the highlighted case studies, artificial intelligence (ai) and machine learning (ml) can be applied in sustainable urban development through various innovative approaches. here are some key applications derived from the case studies: • real-time hollow defect detection in tiles using on-device tiny machine learning.the case of real-time hollow defect detection in tiles using ondevice tiny machine learning [1] exemplifies the powerful convergence of embedded machine learning and industrial material quality control and offers a direct pathway toward sustainable urban development. in this study, ultralight convolutional neural networks were deployed on-device—via the so-called “aidstick”—to detect subsurface hollow defects in floor tiles using acoustic and spectrogram features, thereby achieving real-time classification in a manufacturing environment. by extending such ai-enabled inspection protocols to construction materials and infrastructure elements, urban development may significantly reduce waste, minimize resource consumption, and elevate building longevity. the proactive identification of latent defects, before they manifest as structural failures or require costly remediation, aligns closely with sustainability agendas by reducing embodied energy in remediation, prolonging service life, and limiting the environmental footprint of construction cycles. in effect, this technology transforms passive quality assurance into a dynamic, anticipatory system—a change that resonates with the broader ambition of creating smarter, more sustainable built environments. • applications of bentonite in plastic concrete: enhancing workability and predicting compressive strength using hybridized ai models the article applications of bentonite in plastic concrete: enhancing workability and predicting compressive strength using hybridized ai models [2] represents a significant advancement in the application of artificial intelligence (ai) to construction materials engineering. in this work, hybridized ai frameworks integrate artificial neural networks (ann) with meta-heuristic optimisers to predict compressive strength and improve the workability of bentonite-plastic concrete mixes— thereby enabling more durable, sustainable urban infrastructure. by applying such data-driven models, construction materials can be engineered with minimal trial-and-error, resulting in reduced maintenance demands, enhanced service lifetimes, and a smaller environmental footprint across the lifecycle of urban built-environments. in other words, the optimisation of concrete formulations via ai techniques aligns seamlessly with the broader imperative toward sustainability in urban infrastructure development. • industrial engineering and operations management in the proceedings of the 29th international joint conference on industrial engineering and operations management held in lisbon (june 28–30), the collected works emphasise how digital transformation (dx) and artificial intelligence (ai) can streamline industrial and civilengineering operations toward greater sustainability and resilience [3]. the volume demonstrates that aidriven automation and data-centric process optimisation reduce resource consumption, enhance logistic efficiency, and improve project management under volatile, uncertain, complex and ambiguous (vuca) conditions. in the context of sustainable urban development, such operational efficiencies translate into smarter construction processes, more intelligent energy utilisation in building systems and leaner urban logistics—all contributing to the reduction of the carbon footprint of cities. • construction delay and cost overrun risks assessment. the study by khodabakhshian, malsagov, and re cecconi [5] advances the understanding of predictive risk management in construction and urban development through the application of machine learning (ml) techniques to large-scale, real-world datasets. using data from over 13 000 public-school construction projects in new york city, the authors compare multiple ml algorithms—including decision tree, artificial neural network (ann), linear regression, ridge regression, and xgboost—to identify and quantify the determinants of both schedule delay and cost overrun. among the evaluated models, xgboost achieved the highest predictive accuracy (r² ≈ 0.91), demonstrating the superiority of ensemble learning approaches in complex engineering datasets. by integrating these models into project management workflows, stakeholders can forecast risk levels in real time, anticipate resource bottlenecks, and implement pre-emptive mitigation strategies before deviations escalate into systemic failures. this research underscores the pivotal role of data-driven intelligence in transforming construction management from reactive problem-solving to proactive governance. the adoption of ai and ml enables decision-makers to reduce uncertainty, improve transparency, and enhance sustainability by minimizing financial waste, material inefficiency, and time overruns across the project lifecycle. in synthesis, the study illustrates how predictive analytics can serve as a cornerstone for sustainable and resilient urban infrastructure delivery—linking computational precision with managerial foresight in the digital transformation of the construction sector. eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 5 • automatic road surface damage identification: the study by pham and nguyen [6] evaluates the performance of the rti ims (road and transport infrastructure inspection management system) software, which integrates artificial intelligence (ai) and machine learning (ml) models—specifically yolov4 and yolov5—for the automatic detection and classification of pavement surface defects. by applying deep convolutional networks to highresolution imagery, the system achieves real-time, high-accuracy identification of cracks, potholes, and rutting, outperforming traditional manual inspection and image-processing techniques. this automation enables timely, data-driven maintenance decisions that significantly reduce operational costs and enhance roadway safety. from a sustainability perspective, such proactive maintenance frameworks extend pavement service life, mitigate traffic congestion associated with large-scale repair operations, and lower the environmental footprint of urban transport systems. in sum, ai-driven surface-damage identification exemplifies how digital technologies can transform infrastructure management into a more predictive, efficient, and environmentally responsible practice. • intelligence-based bioprinting for construction engineering: the chapter research trends in intelligence-based bioprinting for construction engineering applications [7] explores the transformative potential of artificial intelligence (ai) and machine learning (ml) in advancing bioprinting technologies for the construction sector. the authors emphasize that, while bioprinting originated in biomedical sciences, its adaptation to civil and structural engineering introduces a paradigm shift in how materials and structures are conceptualized, fabricated, and maintained. by integrating ai-driven predictive algorithms, data-centric material characterization, and topology optimization, intelligence-based bioprinting enables the design of bio-inspired construction materials exhibiting superior strength-to-weight ratios, self-healing capabilities, and adaptive resilience under dynamic environmental conditions. the chapter highlights how ai and ml contribute to automating bioprinting workflows, from material formulation and parameter tuning to in-situ process monitoring and defect correction. these intelligent systems significantly reduce material waste, enhance precision, and enable the development of sustainable composites with controlled porosity and optimized energy efficiency. in the context of urban development, such technologies could redefine the sustainability profile of the built environment by producing structures that are not only environmentally compatible but also self-adaptive and functionally graded. ultimately, intelligence-based bioprinting represents a convergence of computational design, robotics, and advanced materials science—laying the foundation for a new era of regenerative, energyefficient, and resilient construction systems. • smart buildings and infrastructure: the study innovative ict in smart buildings domain: a patentometric analysis [8] provides a systematic exploration of global innovation trends in smart building technologies through an extensive patentometric evaluation. by analyzing patent data from leading jurisdictions and international databases, the authors identify the growing influence of artificial intelligence (ai), machine learning (ml), and internet of things (iot) systems in driving innovation across the smart building ecosystem. the patent analysis reveals a steady rise in inventions focused on intelligent building automation, predictive maintenance, and integrated energy management— demonstrating how digital technologies are being operationalized to achieve both functional efficiency and environmental sustainability. the study underscores the pivotal role of ai and ml in enabling self-optimizing and adaptive building systems capable of real-time performance monitoring. these technologies facilitate intelligent control of hvac systems, lighting, and resource flows, thereby reducing energy consumption, enhancing occupant comfort, and extending structural longevity. moreover, the integration of ict-based predictive analytics supports proactive fault detection, life-cycle optimization, and resilience assessment—core pillars of sustainable infrastructure design. viewed holistically, the patentometric trends highlight an accelerating shift toward cyber-physical building environments where ai-driven interoperability transforms conventional structures into dynamic, selfregulating, and ecologically responsible entities. • science mapping in construction management: the chapter a comprehensive review on application of artificial intelligence in construction management using a science mapping approach [9] provides one of the first scientometric assessments of ai integration within construction management. using the scopus database and the vosviewer tool for co-citation, cocountry, and keyword analyses, the authors mapped research trends and intellectual structures defining the intersection of ai and construction engineering. their findings identify five key domains—machine learning, deep learning, decision-support systems, natural language processing, and the internet of things—that collectively represent the technological backbone of digital transformation in the construction sector. the study demonstrates that ai applications enhance project efficiency by enabling predictive modeling, automated risk assessment, and intelligent resource allocation, while simultaneously reducing waste and environmental impact. deep learning supports image-based safety monitoring; ml models improve cost and schedule forecasting; iot and nlp facilitate real-time data acquisition and code eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 6 interpretation; and decision-support systems integrate these insights into strategic planning. viewed holistically, the research reveals that the convergence of these technologies aligns the construction industry with the principles of industry 4.0—fostering automation, resilience, and sustainability across the project lifecycle. ai and ml contribute significantly to sustainable urban development by optimizing project management, improving infrastructure maintenance, innovating construction materials and methods, and enhancing the sustainability of buildings and infrastructures. by harnessing these technologies, urban developers can create more efficient, resilient, and environmentally friendly cities, aligning with the global agenda for sustainable development. 4. ict innovations for disaster management in the rapidly evolving landscape of civil engineering, the integration of information and communication technology (ict) innovations stands at the forefront of revolutionizing disaster management practices. this section delves into the transformative role of ict in enhancing disaster preparedness, response, and recovery processes. as natural disasters continue to pose significant threats to urban and rural communities alike, the imperative for advanced, reliable, and efficient disaster management strategies has never been more critical. ict innovations, encompassing a broad spectrum of technologies such as real-time monitoring systems, geographic information systems (gis), mobile applications, and social media analytics, offer unprecedented opportunities to mitigate the impacts of disasters. by harnessing these technologies, stakeholders can improve the accuracy of hazard predictions, streamline communication channels among first responders and affected populations, and optimize resource allocation and logistics in emergency situations. this section aims to explore the latest advancements in ict for disaster management, illustrating how digital tools and platforms are being employed to build resilient infrastructures, foster community resilience, and ultimately save lives. through a detailed examination of case studies and emerging trends, we shed light on the pivotal role of ict in crafting a proactive, informed, and cohesive approach to disaster management, highlighting the challenges and opportunities that lie ahead in integrating these technologies into holistic civil engineering solutions. 4.1. case studies • learning from the tourism community resilience model from bali, indonesia: learning from the tourism community resilience model from bali, indonesia, the study by i putu gede eka praptika, mohamad yusuf, and jasper hessel heslinga [10] examines how the tourism community of the kuta traditional village developed resilience during the covid-19 pandemic. employing a qualitative, phenomenological approach, the authors analysed community responses rooted in both niskala (spiritual, unseen) and sekala (real, tangible) dimensions. these dual concepts, intrinsic to balinese hindu philosophy, guided the community’s collective response through spiritual rituals such as nangluk merana and practical strategies such as job diversification, asset reallocation, and cooperative governance. the resulting tourism community resilience model identifies four foundational elements—local wisdom foundation, resource management, government contributions, and external community support—all unified under the balance between spiritual and material responses. the study concludes that integrating cultural and spiritual dimensions into resilience planning strengthens social cohesion, fosters sustainable recovery, and offers a transferable framework for other tourism-dependent regions seeking to enhance preparedness and adaptability to future crises [10]. • using epicore to enable rapid verification of potential health threats: the study titled “epicore using epicore to enable rapid verification of potential health threats: illustrated use cases and summary statistics” by nomita divi, jaś mantero, marlo libel, onicio leal neto, marinanicole schultheiss, kara sewalk, john brownstein, and mark smolinski [11] examines how epicore—a crowdsourced network of human, animal and environmental health professionals—facilitates the rapid verification of early warning signals of potential outbreaks, thereby improving response times to genuine health emergencies [11]. the authors report that between 2018 and 2022, epicore’s response rate increased from 65.4 % to 68.8 %, and that in 2022, 94 % of requests for information (rfis) received a first contribution within 24 hours [11]. the study argues that, when used in conjunction with traditional surveillance systems, epicore shortens the time to verification, supports decision‐making, and enhances epidemic and pandemic intelligence. from an integrative standpoint, this evidence underscores the value of leveraging distributed expert networks and non‐traditional data flows in global health preparedness and adaptability. • exploring innovative techniques for damage control during natural disasters: the article “exploring innovative techniques for damage control during natural disasters” by m. r. azeem, eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 7 m. m. rahman, and m. s. haque [12] investigates advanced methods for mitigating the impact of natural disasters through the integration of emerging technologies and data-driven systems [12]. it reviews global disaster management practices, emphasizing the growing role of artificial intelligence, remote sensing, robotics, and internet of things (iot) frameworks in real-time monitoring, rapid assessment, and emergency response coordination. drawing on successful case studies from bangladesh, japan, and the united states, the paper highlights how predictive modelling, uav-based mapping, and automated communication networks can substantially reduce response latency and improve situational awareness. from an applied standpoint, the study demonstrates that the fusion of technological innovation and institutional preparedness is essential for effective damage control and adaptive recovery in disasterprone regions, contributing to the global discourse on resilience and sustainable risk governance [12]. • semantic segmentation of remote sensing images for disaster management: this research, “semantic segmentation of remote sensing images: definition, methods, datasets and applications,” by vlatko spasev, ivica dimitrovski, ivan kitanovski, and ivan chorbev [13], discusses the use of semantic segmentation in diverse domains, notably urban planning, environmental monitoring, and disaster management [13]. the study examines recent advances in convolutional neural networks (cnns) and deep learning architectures that enhance the precision of image classification and scene understanding from satellite and aerial imagery. by mapping and categorizing surface features at the pixel level, semantic segmentation enables rapid postdisaster assessment, infrastructure damage mapping, and long-term environmental monitoring. the paper also reviews widely used datasets and evaluation metrics for benchmarking segmentation models, highlighting the importance of data quality and annotation accuracy in achieving reliable disaster management outcomes. overall, the work emphasizes that cnn-based segmentation offers a critical foundation for intelligent geospatial systems supporting real-time decision-making in emergency and sustainability contexts [13]. • resilience in complex disasters: florida's hurricane preparedness amid covid-19: the study “resilience in complex disasters: florida’s hurricane preparedness, response, and recovery amid covid-19” by tian tang, tian luo, and harper walton [14] provides an in-depth analysis of how florida’s emergency management systems adapted to the dual challenges of the covid-19 pandemic and recurring hurricane seasons [14]. through 22 semi-structured interviews with federal, state, local, and nonprofit emergency managers, the authors examine how compound, cascading, and protracted disasters strain traditional emergency frameworks. the study identifies major challenges, including conflicts between sheltering and infection prevention, financial and human-resource shortages, and ict-related constraints that intensified the digital divide between urban and rural communities. findings reveal that increased reliance on information and communication technologies (icts) during remote operations exposed critical gaps in infrastructure and inter-agency coordination, impeding effective preparedness and recovery. nevertheless, florida’s agencies employed innovative and adaptive strategies—such as non-congregate sheltering, hybrid communication systems, and cross-sectoral collaboration—to balance hurricane response with pandemic mitigation. the research underscores the necessity of investing in digital infrastructure, community-based communication, and adaptive governance to strengthen resilience against future compound disasters [14]. • handbook on climate change and technology: the handbook on climate change and technology, edited by frauke urban and johan nordensvärd [16], provides a comprehensive synthesis of how technological innovation intersects with global climate action across multiple sectors. it explores the evolving role of low-carbon energy systems, digital technologies, artificial intelligence, and sustainable infrastructure in driving both mitigation and adaptation strategies. the volume critically examines the potential of emerging technologies—ranging from renewable energy and carbon capture to climate-smart agriculture and resilient urban design—to reduce emissions while enhancing societies’ capacity to withstand environmental shocks. with contributions from international experts, it emphasizes that effective climate governance requires integrating technology with social equity, policy reform, and participatory innovation. importantly, the handbook underscores the relevance of technological pathways for disaster management, illustrating how data analytics, earlywarning systems, and decentralized renewable solutions can strengthen resilience and adaptive capacity in vulnerable regions [16]. • a preliminary review on ict innovation for disaster management and resilience: this publication provides an overview of the utilization of ict in the context of disaster management and resilience, emphasizing the need for continuous innovation [15]. eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 8 • disaster risk reduction, management, and climate change adaptation: the chapter “disaster risk reduction, management, and climate change adaptation” in the handbook on climate change and technology examines how technological innovation shapes both policy development and operational practice in addressing disaster and climate-related risks. urban and nordensvärd [16] analyze how emerging technologies—including geospatial intelligence, artificial intelligence, sensor networks, and digital decision-support systems—enhance risk assessment, early warning, and adaptive management capacities. the chapter highlights that technologydriven approaches can significantly strengthen resilience when coupled with inclusive governance, institutional learning, and community-based participation. it argues that effective disaster risk reduction requires integrating innovation within broader socio-political and ethical frameworks, ensuring that technological advancement complements rather than replaces human and institutional preparedness. by linking climate adaptation, technological progress, and equitable policy reform, the authors provide a multidimensional roadmap for building resilience in the anthropocene [16]. • technology-mediated flood risk management tools: the handbook of flood risk management and community action: an international perspective [17] provides a comprehensive and globally comparative account of community-based flood risk management. it highlights how recurring and intensifying flood events demand integrated, human-centred strategies that combine scientific, technological, and local knowledge across the three key phases of flood management—before, during, and after flood events. the volume brings together expert case studies from africa, oceania, europe, asia, and the americas, emphasizing resilience-building, participatory governance, and cross-cultural knowledge exchange. within this context, several chapters—particularly those addressing technology-mediated approaches— examine the use of mobile disaster management systems and ict-enabled citizen observatories to enhance community participation, real-time reporting, and adaptive decision-making. the handbook thus underscores that technological innovation, when embedded within community action and inclusive governance, can substantially strengthen resilience to flood risks worldwide [17]. these case studies and publications illustrate the critical role of ict innovations in enhancing disaster preparedness, response, and recovery efforts. they underscore the importance of adopting new technologies and methodologies to build resilience and manage complex disasters effectively. these examples illustrate the application of information and communication technology (ict) innovations in enhancing disaster preparedness, response, and resilience across different contexts and communities. question: how can ict improve community resilience to disasters? information and communication technology (ict) plays a transformative role in strengthening community resilience by enabling faster communication, smarter decision-making, and more adaptive responses to crises. through early warning systems, ict facilitates the detection and prediction of natural hazards such as floods, hurricanes, and earthquakes, providing advance notice that allows communities to prepare and mitigate losses. during emergencies, real-time information sharing via mobile networks, social media, and community alert systems ensures that vital updates on evacuation routes, shelters, and safety measures reach affected populations instantly. ict also enhances coordination and response among government agencies, ngos, and emergency services through digital platforms, mapping tools, and integrated databases that enable efficient allocation of resources. beyond immediate response, data collection and analysis supported by ict helps model risk scenarios and inform long-term urban and infrastructure planning for greater resilience. in post-disaster phases, remote health services—including telemedicine and psychological counseling—provide critical care to isolated or displaced populations. moreover, education and training platforms use online courses, simulations, and virtual reality (vr) to build disaster literacy and preparedness skills. ict further strengthens social networks by connecting individuals and organizations, fostering collaboration and mutual aid during recovery. finally, mobile banking and digital financial tools allow rapid mobilization of funds for relief operations, supporting both emergency assistance and sustainable recovery. together, these ict-driven mechanisms form a multidimensional framework that empowers communities to anticipate, absorb, and recover from disasters more effectively. eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 9 figure 1. how information and communication technology (ict) can improve community resilience to disasters integrating ict into disaster risk reduction and management strategies, communities can enhance their resilience, reduce the impact of disasters, and recover more quickly. ensuring equitable access to ict resources and training is crucial for maximizing these benefits across all segments of the community. question: what are the latest innovations in disaster response technologies? recent advances in disaster response technologies are redefining the speed, precision, and coordination of emergency operations, integrating digital intelligence with human expertise to minimize losses and save lives. artificial intelligence (ai) and machine learning (ml) now analyze vast, heterogeneous data sources—from satellite imagery to social media streams—to predict disaster trajectories, model impacts, and optimize evacuation and resource deployment strategies. unmanned aerial vehicles (uavs) or drones provide rapid aerial assessments, delivering real-time visual data for mapping damage, identifying survivors, and transporting essential supplies to otherwise inaccessible areas. through internet of things (iot) infrastructures, networks of sensors continuously monitor environmental indicators, infrastructure stability, and resource availability, enabling adaptive and data-driven decision-making in dynamic disaster contexts. geospatial technologies such as advanced gis and remote sensing have evolved into indispensable tools for generating detailed situational maps that support coordination and post-disaster recovery planning. at the human–technology interface, mobile platforms and specialized applications empower citizens and responders alike by providing emergency alerts, two-way reporting functions, and real-time access to survival information and health resources. blockchain technology is being harnessed to ensure transparent, tamper-proof management of aid distribution, donations, and logistics, while social media analytics offer real-time situational awareness and sentiment mapping of affected populations. nextgeneration 911 (ng911) systems expand emergency communication capabilities to include text, image, and video inputs, enriching the information available to dispatchers for faster, context-aware response. meanwhile, wearable technologies—integrated with gps, biometric, and communication sensors—support continuous monitoring of both victims and first responders, enhancing operational safety and medical triage. finally, robotic search and rescue systems, including autonomous ground and underwater robots, extend human capacity in hazardous environments, performing reconnaissance, debris removal, and targeted life detection. collectively, these innovations illustrate a paradigm shift toward intelligent, connected, and resilient disaster response ecosystems, where data, automation, and human judgment converge to protect lives and accelerate recovery. eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 10 figure 2. latest innovations in disaster response technologies figure 2 highlights a progression from artificial intelligence and machine learning (ai & ml), through unmanned aerial vehicles or drones, internet of things (iot), geospatial technology, mobile technology and apps, blockchain, social media analytics, nextgeneration 911 (ng911), to wearable technology, and finally robotic search and rescue. each of these technologies plays a crucial role in enhancing the efficiency and effectiveness of disaster response efforts, contributing to saving lives, reducing damage, and speeding up recovery processes. these innovations represent a shift towards more integrated, technologydriven approaches in disaster response, emphasizing the importance of real-time data, connectivity, and automation in saving lives and mitigating the impact of disasters. question: how do health monitoring systems aid in disaster preparedness? health monitoring systems form an essential pillar of disaster preparedness, enabling authorities and communities to anticipate, prevent, and mitigate the health impacts of crises. through continuous surveillance and data-driven insights, these systems provide the informational backbone for timely interventions and effective public health management. one of their most vital functions is early warning for epidemics, where the analysis of health data patterns and syndromic trends can identify disease outbreaks before they escalate, prompting rapid containment measures. equally important is environmental monitoring, as sensor networks measuring air, water, and soil quality can detect toxic releases from industrial incidents or natural hazards, supporting preventive action to protect population health. by facilitating surveillance of vulnerable populations, such as the elderly, children, and individuals with chronic diseases, health monitoring systems help prioritize medical support and allocate critical resources to those at greatest risk. this feeds into real-time resource allocation, ensuring that medical supplies, vaccines, and healthcare personnel are distributed optimally across affected regions. postdisaster, these systems are indispensable for injury and disease tracking, documenting emerging infections and injuries to prevent secondary crises like post-flood epidemics. beyond physical health, integrated systems also support mental health monitoring, identifying stress, trauma, and psychosocial needs early so that interventions can be deployed promptly. in addition, mobile health (mhealth) applications extend the reach of these systems, offering telemedicine consultations, disseminating verified health information, and maintaining patient monitoring even when conventional healthcare infrastructure is disrupted. finally, by incorporating a feedback loop for continuous improvement, health monitoring systems assess the effectiveness of interventions and inform the refinement of preparedness policies. collectively, these technologies create a proactive, adaptive, and resilient public health architecture that underpins community well-being before, during, and after disasters. eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 11 figure 3. how health monitoring systems aid in disaster preparedness figure 3, outlines a sequence of contributions from health monitoring systems, starting with early warning for epidemics, environmental monitoring, surveillance of vulnerable populations, resource allocation, injury and disease tracking, mental health support, mobile health (mhealth) applications, to a feedback loop for continuous improvement. each step highlights how these systems provide critical information and support to prevent or mitigate the impact of disasters on public health, enhancing overall disaster preparedness. health monitoring systems enhance the ability of healthcare providers, public health officials, and emergency management agencies to prepare for and respond to disasters, ultimately saving lives and reducing the burden on healthcare systems. 5. digital transformation in civil engineering education the advent of the digital era has ushered in a transformative wave across various sectors, notably reshaping the domain of civil engineering education. at the heart of this transformation is the strategic incorporation of virtual laboratories and sophisticated simulation tools, marking a significant leap forward in educational methodologies. these technological advancements are not just supplementary tools but pivotal elements that effectively bridge the traditionally observed chasm between theoretical instruction and practical, real-world application. in an academic discipline as dynamically applied as civil engineering, the capacity to simulate complex construction scenarios, infrastructure responses to environmental stresses, and urban planning in virtual environments provides an invaluable learning platform. students are not merely passive recipients of theoretical knowledge; rather, they are active participants, engaging with the material in a hands-on manner that closely replicates actual field conditions. this immersive approach not only enhances comprehension and retention of complex concepts but also fosters critical thinking and problem-solving skills, preparing students to navigate the challenges of the modern civil engineering landscape with confidence and competence. moreover, the utilization of virtual labs and simulation tools in civil engineering education signifies a broader commitment to innovation and sustainability. by simulating real-world projects in a controlled, virtual space, educational institutions can significantly reduce the material and environmental costs associated with traditional, large-scale experimental setups. this not only aligns with global sustainability goals but also introduces students to the concept of sustainable practice from the outset of their careers. as we delve deeper into the 21st century, the continued integration of digital tools into civil engineering education will undoubtedly play a critical role in shaping the next generation of engineers. these digital platforms not only enrich the learning experience but also ensure that civil engineering education remains relevant, responsive, and rigorous in an ever-evolving technological landscape. the challenge and opportunity lie in continuously adapting and expanding these digital tools to meet the emerging needs of the field, thereby fostering an educational environment that is both innovative and inclusive. 5.1. case studies • digital twin for plant floor kit: this study investigates the design and implementation of a physics-based digital twin to simulate the plant floor environment of the automation laboratories at the faculty of engineering, university of porto (feup). developed within the framework of industry 4.0, the eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 12 work aims to replicate, with high fidelity, the physical layout and dynamic behaviour of the production system. the digital twin is implemented using the unity game engine, selected after a comparative assessment of alternative platforms for its mature physics engine, extensive documentation, and modular extensibility. by integrating industrial automation communication protocols such as modbus, the virtual model supports real-time interaction with external control programs and enables the implementation and validation of innovative control strategies and alternative automation scenarios. core elements of the existing shop-floor simulator—simple conveyors, rotating conveyors, and conveyors with machine tools—are modelled as configurable gameobjects, parameterized via json, and validated through systematic tests that confirm the reliability of motion, sensing and transformation logic. the resulting system delivers an efficient, robust, and adaptable digital twin that reproduces the behaviour of the current simulator while providing a configurable platform for experimentation, analysis, teaching, and process optimization without physical rearrangement of the laboratory layout [18]. • new automotive and aeronautical models and design of digital twins to support learning in tec21 educational model: the paper “new automotive and aeronautical models and design of digital twins to support learning in the tec21 educational model” by alejandro acuña, carlos gonzález-almaguer, rubén vázquez, jorge peñalva, camila lópez, and maría carla corona [19] presents an innovative educational approach that integrates digital twins, virtual reality (vr), and physical modeling to enhance student learning within the tec21 educational framework of tecnológico de monterrey. the study demonstrates how the creation of automotive and aeronautical prototypes—designed both virtually and physically—supports active and experiential learning. by emulating industrial processes within mixed-reality simulators, students can manipulate, assemble, and analyze systems that replicate real engineering environments. this integration of gamification, 3d printing, and aiassisted design fosters deeper engagement, problemsolving, and creativity while minimizing dependence on commercial models such as lego and meccano. the initiative exemplifies how digital twin technologies can bridge theoretical instruction and applied practice, creating scalable and immersive learning experiences adaptable across multiple engineering disciplines [19]. • interactivity and learning through gamification, clinical rounds, and virtual labs: this study explores how digital culture and technological innovation reshape learning dynamics through gamification, clinical simulations, and virtual laboratories [20]. the authors argue that learning becomes more effective when educational environments integrate interactivity, engagement, and playfulness—key characteristics of digital-age learners. within this framework, gamification is presented not merely as the use of games for teaching, but as the systematic incorporation of game design principles—such as feedback loops, challenges, rewards, and collaboration—into the learning process to heighten motivation and autonomy. the chapter also examines clinical rounds as an active learning strategy promoting professional reasoning through problem-based discussions, and virtual laboratories as immersive spaces that replicate practical experimentation, enabling students to practice, make mistakes, and refine their understanding safely. altogether, the authors conclude that combining gamification, virtual labs, and interactive digital platforms cultivates critical thinking, motivation, and learner-centered engagement, aligning education with the expectations and behaviors of digitally native generations [20]. these examples underscore the transformative potential of digital technologies in enhancing civil engineering education. by providing immersive, interactive learning experiences, virtual labs, and simulations prepare students for the challenges of the modern workforce and foster their capacity for innovation and complex problem-solving. 6. skill development strategies for the civil engineering workforce as the civil engineering sector continues to undergo a profound digital transformation, the demand for a highly skilled workforce capable of mastering emerging technologies has become a defining priority. modern civil engineers are expected not only to design and construct but also to analyze, model, and optimize projects using datadriven and intelligent systems. in this context, education must evolve beyond traditional instruction to include strategic skill development initiatives that prepare professionals for an era defined by automation, artificial intelligence (ai), and digital integration. these initiatives aim to equip engineers with both the technical competence and the adaptive mindset needed to thrive amid rapid technological change. professional development programs play a central role in sustaining innovation and excellence. continuous learning platforms should be developed to provide easily accessible, eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 13 flexible, and modular courses covering key technologies such as ai, machine learning (ml), blockchain, and advanced digital modeling tools relevant to civil engineering. by offering asynchronous learning and practical modules, these platforms ensure that professionals can balance ongoing education with work responsibilities. complementing these are workshops and seminar series organized in collaboration with leading industry practitioners and academic experts. such events focus on cutting-edge applications, project case studies, and the translation of research insights into field-ready practices—bridging the gap between theory and operational deployment. certification courses in ai and digital tools further reinforce lifelong learning objectives. specialized training programs, developed through partnerships between academic institutions and technology providers, can offer tiered curricula—from foundational awareness to advanced data analytics, automation, and simulation competencies. to ensure quality and credibility, a skills verification framework should accompany these programs, offering formal certification that validates mastery of specific digital tools and methodologies. this not only enhances individual employability but also strengthens organizational competitiveness in the evolving digital economy. partnerships between industry and educational institutions are indispensable for aligning learning with real-world requirements. through collaborative curriculum development, universities and civil engineering firms can co-design programs that reflect contemporary industry challenges and anticipate future trends, ensuring that graduates are fully equipped for technological practice. similarly, internship and apprenticeship programs provide immersive experiences where students and early-career professionals apply digital tools to real projects— integrating theoretical learning with practical execution in structural analysis, urban modeling, or infrastructure monitoring. to support the transition of the existing workforce, targeted reskilling and upskilling initiatives must be introduced. these initiatives help professionals in traditional roles adapt to digital workflows and automation systems by offering tailored training for varying experience levels. mentorship and peer learning networks can further accelerate this transition, enabling knowledge transfer between experienced engineers and newcomers while fostering collaborative problem-solving communities focused on emerging digital methodologies. looking ahead, the future outlook of civil engineering education lies in adaptability and continuous refinement. adaptive learning paths that personalize content according to individual career goals and proficiency levels can ensure targeted, efficient professional growth. furthermore, industry feedback loops between engineering firms and academic institutions are essential to keep curricula and training programs responsive to the latest technological developments—whether in ai-driven structural analysis, digital twins, or sustainable design systems. collectively, these measures form an integrated framework for a digitally fluent, resilient, and future-ready civil engineering workforce capable of leading innovation in an era of smart infrastructure and sustainable development. investing in skill development strategies for the current workforce is imperative for the civil engineering sector to fully embrace digital transformation. through professional development programs, certification courses, and strong partnerships between industry and academia, professionals can stay abreast of technological advancements, ensuring the sector remains innovative, efficient, and sustainable. by fostering a culture of continuous learning and adaptation, civil engineering can navigate the challenges of the digital era and leverage opportunities for growth and development. 7. case studies of digital integration real-world applications of digital technologies in civil engineering projects offer valuable insights into their practical benefits and challenges. for example, the smart cities initiative, documented in case studies across various platforms, illustrates the comprehensive application of ai, ml, and ict in managing urban infrastructure, traffic, pollution, and energy consumption, contributing to the overall sustainability of urban environments. 7.1. case study i. the contribution of ai-powered mobile apps to smart city ecosystems: this study by zaki ali bayashot [21] investigates the role of ai-powered mobile applications in enhancing smart city ecosystems, with implications for infrastructure resilience, public safety, and emergency response [21]. after a comprehensive review of literature and a series of case studies—including a traffic-management platform and a mobility-as-a-service application in the king abdulaziz financial district (kafd) in saudi arabia—bayashot demonstrates how such applications harness artificial intelligence and mobile connectivity to optimize urban mobility, energy usage, waste-management routes, and crisis communication channels. the article emphasizes the requirement for multidisciplinary collaboration across it, urban planning, architecture and social sciences, to ensure that ai-driven mobile solutions address not only technical performance but also ethical, privacy and inclusivity concerns. from a disaster-management perspective, the research underscores how ai apps can enable real-time hazard mapping, direct citizen-reporting and adaptive resource allocation, thereby reinforcing the smart city’s eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 14 capacity to anticipate, absorb and recover from critical incidents. question: how do ai-powered mobile apps enhance disaster management? ai-powered mobile applications play an increasingly transformative role in modern disaster management by combining intelligent data analytics, real-time communication, and predictive modeling to enhance preparedness, response, and recovery. through advanced algorithms and integrated sensor networks, these applications analyze massive datasets to forecast risks, coordinate emergency operations, and guide recovery strategies with unprecedented precision and speed. one of their most critical functions lies in early warning systems, where ai models process satellite imagery, weather forecasts, and sensor data to detect anomalies that may signal hurricanes, earthquakes, floods, or wildfires. these predictive capabilities enable authorities to issue timely alerts and organize evacuations, ultimately saving lives and minimizing damage. during the crisis itself, realtime information sharing becomes essential. ai-powered apps facilitate communication between emergency responders, government agencies, and citizens, providing instant updates on road closures, shelter availability, and emergency protocols. in the immediate aftermath of disasters, ai applications also accelerate damage assessment by analyzing aerial and ground-level images captured via drones or mobile devices. this helps identify affected infrastructure, estimate losses, and prioritize response efforts based on urgency. similarly, resource management systems embedded within these apps use predictive analytics to optimize the deployment of rescue teams, healthcare personnel, and relief supplies, ensuring that assistance reaches the most critical areas first. equally important, communication channels maintained through ai-driven platforms enable survivors to stay connected with emergency services and loved ones, even when traditional networks fail. these systems often rely on mesh networking or satellite-based relays to maintain connectivity in disrupted environments. as the recovery phase unfolds, ai-powered tools contribute to rebuilding efforts by using data on environmental risks, structural vulnerabilities, and community needs to inform resilient and sustainable reconstruction strategies. by merging artificial intelligence with mobile technology, these applications not only make disaster management more agile and data-informed but also foster greater community participation, transparency, and trust— ultimately strengthening societies’ capacity to anticipate, absorb, and recover from crises in the age of intelligent urban systems. figure 4. how ai-powered mobile apps enhance disaster management figure 4, outlines the sequence from early warning systems to recovery and rebuilding, showing the critical role these technologies play at each stage of disaster management. it highlights the capabilities of ai-powered apps in providing early warnings, facilitating real-time information sharing, assessing damage, managing resources, establishing communication channels, and aiding in recovery and rebuilding efforts. each of these functions contributes to a comprehensive enhancement of disaster management strategies, ultimately improving outcomes and resilience. by integrating ai into mobile applications, disaster management becomes more proactive, targeted, and effective, significantly reducing the impact of disasters on communities and saving lives. question: what role does ai play in sustainable urban development? artificial intelligence (ai) has emerged as a cornerstone of sustainable urban development, driving cities toward smarter, greener, and more equitable futures. by integrating advanced analytics, predictive modeling, and automation into urban systems, ai enables policymakers, planners, and engineers to optimize resource use, minimize environmental impact, and enhance citizens’ quality of life. its transformative potential lies in its capacity to interconnect diverse urban functions—energy, mobility, infrastructure, and governance—into a cohesive and adaptive ecosystem that learns and evolves over time. in the field of energy management, ai systems analyze consumption patterns across buildings, transportation, and industrial sectors to optimize efficiency and reduce waste. through machine learning algorithms, cities can forecast energy demand, balance supply from renewable sources, and operate smart grids that dynamically adjust to consumption peaks and environmental conditions. equally vital is ai’s contribution to waste management, where intelligent models track waste generation, optimize collection routes, and improve recycling efficiency— reducing landfill dependency and greenhouse gas emissions. ai also revolutionizes transportation and traffic optimization by processing vast streams of real-time mobility data to improve traffic flow, reduce congestion, and lower emissions. these systems underpin the eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 15 development of intelligent transportation networks, including autonomous vehicles and adaptive public transit systems that respond to changing conditions. in water resource management, ai applications detect leaks, predict consumption trends, and optimize purification and distribution processes, ensuring that urban water systems operate with both sustainability and resilience. environmental stewardship is further strengthened through ai-driven air quality monitoring, which integrates sensor networks and meteorological data to track pollutants, identify emission sources, and recommend interventions for cleaner urban environments. in urban planning and design, ai provides powerful decision-support tools that simulate land use scenarios, assess environmental impacts, and guide the creation of green spaces, sustainable architecture, and climate-resilient infrastructure. ai’s role extends beyond physical infrastructure to public safety and health, where predictive analytics identify emerging risks—ranging from crime hotspots to disease outbreaks—and enable rapid, data-informed responses. finally, by optimizing resource distribution, streamlining services, and stimulating innovation, ai promotes economic sustainability, supporting inclusive growth while safeguarding environmental and social well-being. through these interlinked applications, ai transforms the modern city into a living, adaptive system—one capable of learning from its inhabitants, conserving its resources, and advancing toward a sustainable urban future. figure 5. the role of ai in sustainable urban development figure 5, outlines how ai contributes to various aspects of urban sustainability, including energy management, waste management, transportation and traffic optimization, water resources management, air quality monitoring, urban planning and design, public safety and health, and economic sustainability. each of these domains benefits from ai's ability to analyze data, optimize processes, and provide actionable insights, ultimately leading to reduced environmental impact, enhanced efficiency, and improved quality of life in urban areas. question: how can digital transformation contribute to smarter city ecosystems? digital transformation serves as the foundation of modern smart city ecosystems, integrating advanced technologies, data analytics, and interconnected platforms to enhance urban efficiency, sustainability, and quality of life. by digitizing infrastructure and public services, cities evolve into adaptive systems capable of learning from data, anticipating challenges, and responding to citizens’ needs in real time. this holistic transformation redefines how urban environments operate—linking governance, infrastructure, economy, and community into a unified digital framework. one of the most profound impacts of digital transformation lies in efficient resource management. through real-time data collection, iot sensors, and predictive analytics, cities can monitor the consumption of water, energy, and other utilities, enabling precise control, early fault detection, and effective conservation strategies. this smart approach reduces waste and minimizes environmental impact, fostering a culture of sustainability. in parallel, improved public services emerge as a key benefit of digitization. by transitioning to e-governance platforms, municipalities can provide transparent, responsive, and citizen-centric services—ranging from digital tax payments to participatory urban forums—enhancing accessibility and accountability. digital transformation also reshapes mobility and transportation, employing ai-driven traffic management systems, intelligent transit networks, and real-time navigation tools that optimize travel routes, reduce congestion, and promote sustainable modes such as electric vehicles and shared mobility services. similarly, public safety and security benefit from the deployment of digital surveillance, emergency response platforms, and predictive analytics tools, which enhance situational awareness and ensure rapid interventions in critical events. in the sphere of sustainable urban planning, data analytics and simulation technologies allow planners to visualize and evaluate development scenarios before implementation. this leads to better land-use management, creation of green corridors, and construction of resilient, climate-adaptive infrastructure. from an economic standpoint, digital transformation catalyzes innovation ecosystems, attracting technology-driven enterprises, startups, and investors, thereby stimulating economic growth and job creation in the expanding digital economy. moreover, digitization contributes directly to health and well-being, enabling telemedicine, environmental monitoring, and access to wellness services through integrated platforms that improve both physical and mental health outcomes. equally important is community engagement, as digital platforms empower citizens to voice their perspectives, collaborate on local initiatives, and participate in urban decision-making processes. in synthesis, digital transformation transforms the city into a connected, intelligent, and participatory ecosystem, where data and technology converge to improve governance, sustainability, and inclusivity. by fostering transparency, efficiency, and resilience, digitally transformed cities become not only smarter but also more human-centered, capable of adapting dynamically to the evolving needs of their residents. eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 16 figure 6. how digital transformation contributes to smarter city ecosystems figure 6, outlines the benefits of digital transformation across various aspects of urban life, including efficient resource management, improved public services, enhanced mobility and transportation, public safety and security, sustainable urban planning, economic development, health and well-being, and community engagement. each of these areas plays a crucial role in creating smarter, more efficient, and more livable cities, ultimately contributing to the overall ecosystem of a smarter city. by integrating digital technologies into the fabric of city operations and services, digital transformation enables smarter, more sustainable, and more inclusive urban ecosystems that improve the quality of life for all residents. 7.2. case study ii: elgar encyclopedia of development [22]: this comprehensive work explores the interdisciplinary nature of development, including the critical role of digital transformation and ai in civil engineering for addressing global challenges such as hunger, malnutrition, ill health, and sustainable urban development. the study highlights the importance of an interdisciplinary approach in leveraging digital and ai technologies for sustainable development. discusses the impact of insufficient resources on public health issues and the role of digital solutions in mitigating these challenges. focuses on sustainable livelihoods and the integration of digital technologies in civil engineering to improve health outcomes in the context of disaster management and urban development. this case study underscores the critical intersection of civil engineering, digital transformation, ai, and health, demonstrating how technological advancements can contribute to more resilient and healthy urban environments, especially in the face of disasters. question: what are the challenges of integrating ai in urban development? integrating artificial intelligence (ai) into urban development introduces a complex set of challenges that extend beyond technology to include social, ethical, economic, and governance dimensions. while ai promises to revolutionize how cities function—enhancing efficiency, sustainability, and resilience—its successful deployment depends on addressing these multifaceted barriers comprehensively and responsibly. one of the foremost challenges lies in data privacy and security. ai-driven urban systems rely on continuous data flows collected from citizens, sensors, and public infrastructure. these datasets often include sensitive personal and geospatial information, making them vulnerable to misuse, breaches, and cyberattacks. ensuring robust cybersecurity measures and ethical data governance is therefore essential to safeguard citizen trust. another significant issue concerns infrastructure and connectivity. many cities, particularly in developing regions, lack the high-speed networks, advanced sensors, and cloud computing capacity required to sustain ai-based applications, creating a digital divide that limits equitable access to innovation. the question of interoperability and standardization also poses a persistent technical obstacle. urban systems often comprise disparate platforms and legacy technologies that must communicate seamlessly for ai to function effectively. establishing unified data standards, protocols, and frameworks is vital to achieve cross-sectoral integration. at the same time, ethical and societal concerns loom large. ai’s potential to amplify surveillance, automate decision-making, and replicate bias has raised fears of deepened inequality and exclusion. without transparency, fairness, and inclusivity at the design stage, ai risks reinforcing rather than alleviating social disparities. a further barrier involves skill gaps and workforce transformation. as ai redefines urban planning, construction, and governance, cities require professionals capable of designing, managing, and auditing intelligent systems. the shortage of digitally skilled labor hinders this transition, necessitating large-scale education and reskilling initiatives. in parallel, regulatory and legal frameworks must evolve swiftly to match technological progress. policymakers face the delicate task of crafting adaptive, forward-looking regulations that balance innovation with accountability, safety, and ethical integrity. equally important is public acceptance and trust. for ai to be fully embraced in urban life, citizens must understand how it affects decision-making, resource distribution, and privacy. transparent governance, participatory engagement, and clear communication about benefits and risks are key to building legitimacy. lastly, there is the issue of sustainability and environmental impact. although ai contributes to sustainable city management, its own energy consumption and hardware demands can offset environmental gains. reducing carbon footprints through green computing and responsible technology lifecycle management is therefore a crucial step. integrating ai into urban development is as much a sociopolitical endeavor as a technological one. it requires ethical foresight, institutional adaptability, and global cooperation to ensure that smart cities evolve as inclusive, secure, and sustainable environments for all. eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 17 figure 7. challenges of integrating ai in urban development figure 7, outlines the challenges of integrating ai in urban development. these challenges encompass a wide range of issues, including data privacy and security, infrastructure and connectivity, interoperability and standardization, ethical and societal concerns, skill gaps and workforce transformation, regulatory and legal frameworks, public acceptance and trust, and sustainability and environmental impact. each of these challenges represents a significant hurdle that needs to be addressed to successfully implement ai technologies in urban development and enhance the livability, sustainability, and efficiency of cities. these challenges requires a multi-faceted approach, involving collaboration between government, industry, academia, and civil society, to harness the benefits of ai for urban development while mitigating its risks. question: how does digital transformation impact public health? digital transformation has profoundly reshaped the landscape of public health, redefining how healthcare services are delivered, monitored, and managed. by integrating advanced technologies such as artificial intelligence, big data analytics, cloud computing, and mobile platforms, health systems are becoming more efficient, patient-centered, and data-driven. this technological evolution not only enhances healthcare delivery and accessibility but also strengthens prevention, research, and community resilience against health crises. one of the most significant outcomes of digital transformation is improved access to healthcare. through telemedicine, digital health platforms, and mobile health (mhealth) applications, medical consultations and diagnostic services have become available even in remote or underserved regions, breaking traditional geographical barriers to care. these platforms provide real-time communication between patients and healthcare providers, reducing waiting times and expanding the reach of essential health services. equally transformative is enhanced disease surveillance and management. digital tools now allow for real-time monitoring of health indicators, the aggregation of epidemiological data, and the use of predictive analytics to forecast disease outbreaks. governments and health organizations can detect early warning signs of epidemics, implement timely interventions, and allocate resources more efficiently. at the individual level, personalized medicine—driven by digital data—enables healthcare providers to design tailored treatment plans based on genetic profiles, lifestyle patterns, and environmental exposures, leading to more precise and effective therapies. digitalization also contributes to increased efficiency and cost reduction within healthcare systems. the automation of administrative tasks, digital recordkeeping, and algorithmic support for diagnosis and treatment streamline workflows, reduce redundancy, and minimize human error. this efficiency directly translates into lower operational costs and improved service delivery. in addition, patient engagement and self-management have reached new levels as wearable technologies, mobile health trackers, and interactive platforms empower individuals to monitor their health, adhere to treatment regimens, and make informed lifestyle choices. the quality of care has also benefited from digital integration. electronic health records (ehrs), clinical decision-support systems, and ai-assisted diagnostic tools ensure that practitioners have access to comprehensive and up-to-date patient data, improving accuracy and continuity of care. furthermore, digital health education and promotion initiatives—ranging from online awareness campaigns to interactive learning platforms—enhance public understanding of disease prevention, nutrition, mental health, and hygiene. finally, digital transformation accelerates research and innovation by enabling seamless data sharing and global collaboration among researchers, institutions, and policymakers. big data analytics and cloud-based platforms support faster discovery of medical insights, new drug development, and evidence-based policy formation. these advancements demonstrate that digital transformation is not merely an adjunct to healthcare but a core driver of modern public health systems—creating an ecosystem that is more accessible, predictive, participatory, and resilient in the face of emerging health challenges. figure 8. how does digital transformation impact public health. while digital transformation holds immense potential for improving public health, it also presents challenges, including ensuring data privacy, addressing digital divides, and managing the pace of technological change. addressing these challenges is crucial to fully realizing the benefits of digital transformation in public health. question: what role does civil engineering play in sustainable development? eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 18 civil engineering is at the heart of sustainable development, shaping the physical foundation upon which societies function while ensuring that environmental integrity, economic viability, and social equity are upheld. as the discipline responsible for designing, constructing, and maintaining the built environment, civil engineering serves as a bridge between human progress and planetary preservation. its mission extends beyond technical achievement—it seeks to create infrastructure that meets today’s demands without undermining the capacity of future generations to thrive. a central domain of this responsibility lies in water management, where civil engineers develop and maintain systems that secure clean water supplies, manage wastewater, and control flooding. through sustainable drainage networks, reservoir optimization, and naturebased flood defenses, they ensure efficient resource allocation and safeguard communities from water-related hazards. equally vital is transportation infrastructure, where engineers design mass transit systems, pedestrian pathways, and cycling networks that promote mobility while minimizing energy consumption, congestion, and greenhouse gas emissions. these innovations foster urban efficiency and improve air quality, contributing to climateresilient mobility systems. in the field of energy, civil engineers play a pivotal role in enabling the global shift toward renewables. they design and construct wind farms, solar installations, hydroelectric facilities, and energy-efficient buildings—integrating smart technologies that monitor consumption and reduce waste. such interventions not only lower carbon emissions but also enhance energy security and sustainability. in tandem, waste management represents another critical frontier, where engineers design recycling centers, wasteto-energy plants, and eco-efficient landfills that transform refuse into resources, promoting a circular economy and reducing environmental pollution. the ethos of sustainable construction lies at the core of modern engineering practice. civil engineers are increasingly adopting eco-friendly materials, modular construction methods, and life-cycle assessment tools to minimize environmental footprints. their goal is to create structures that are energy-efficient, adaptable, and durable—capable of evolving with future societal and climatic changes. within urban planning, engineers collaborate with architects, planners, and policymakers to design inclusive, green, and connected cities that harmonize economic activity, ecological preservation, and human well-being. this includes the strategic integration of green infrastructure, public spaces, and mixed-use developments to ensure accessibility and livability. another defining contribution of the profession is the enhancement of disaster resilience. by incorporating climate-risk assessments and robust design standards, civil engineers ensure that infrastructure can withstand earthquakes, floods, hurricanes, and other extreme events. these resilience measures protect both lives and economies while strengthening community preparedness. finally, through environmental protection, civil engineers champion the restoration and preservation of natural systems—implementing erosion control projects, wetland rehabilitation, and habitat conservation to maintain biodiversity and ecosystem services that underpin sustainable development. in essence, civil engineering serves as both the architect and steward of sustainable progress. by integrating technological innovation with environmental ethics and social responsibility, the discipline ensures that human advancement is grounded in resilience, balance, and longterm planetary stewardship. figure 9. the role of civil engineering in sustainable development through these contributions, civil engineering is at the forefront of creating a sustainable future, addressing global challenges such as climate change, resource depletion, and urbanization in a responsible and innovative manner. 7.3. case study iii: advancing autonomous green stormwater infrastructure: the study by brooke e. mason [23] introduces a pioneering framework for the digital transformation of green stormwater infrastructure (gsi) through the application of autonomous control systems and real-time sensing technologies [23]. conducted at the university of michigan, the research focuses on the development, implementation, and testing of two autonomous gsi systems—each designed to improve the capture and treatment of stormwater while minimizing nutrient pollution, particularly phosphorus runoff. by integrating smart controls, embedded sensors, and feedback-driven algorithms, these systems continuously monitor environmental variables such as rainfall, soil moisture, and water level to dynamically adjust storage and flow operations. the findings demonstrate that real-time, datadriven automation significantly enhances the efficiency, responsiveness, and adaptability of stormwater infrastructure in urban environments. the systems successfully optimized the retention and release of stormwater, reducing overflow events and improving water quality outcomes. furthermore, mason’s research emphasizes that autonomous gsi represents a critical evolution in sustainable water management—bridging environmental engineering and digital innovation to address the challenges of climate variability, urban flooding, and nutrient pollution. this work highlights the transformative potential of coupling traditional green infrastructure with cyber-physical control systems, eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 19 advancing toward resilient and self-regulating urban water networks [23]. these case studies exemplify the diverse applications of digital technologies in civil engineering and disaster management across different geographical regions. they reveal unique challenges specific to each context and the innovative digital solutions employed to address these challenges, highlighting the global perspective and the transformative potential of digital integration in the field. 8. emerging technologies in civil engineering: shaping the future the realm of civil engineering is on the cusp of a technological revolution, with emerging technologies offering groundbreaking potential to reshape the industry. this section delves into the promising future of civil engineering, focusing on the impact of quantum computing and blockchain technology. these innovations stand to dramatically enhance data analysis, simulation capabilities, and project management transparency, propelling civil engineering into a new era of efficiency and trust. 8.1 quantum computing quantum computing represents a transformative breakthrough in computational science, harnessing the fundamental principles of quantum mechanics— superposition, entanglement, and quantum interference— to process complex datasets and perform multidimensional simulations at speeds unattainable by classical computers. its ability to analyze, optimize, and simulate massive systems in real time positions it as a potential gamechanger for the field of civil engineering. the potential impact of quantum computing extends across multiple domains of engineering design and analysis. in large-scale civil infrastructure projects, quantum algorithms can dramatically enhance the accuracy and efficiency of simulations related to traffic flow, load distribution, and environmental impact, allowing engineers to test thousands of scenarios instantaneously. by enabling the detailed analysis of molecular structures and material properties, quantum computing also facilitates the discovery of novel construction materials with superior strength, sustainability, and cost-effectiveness. moreover, quantum-enhanced predictive models can improve the forecasting of natural disaster dynamics—such as seismic activity, flooding, or wind loading—offering civil engineers more reliable data for disaster preparedness, risk assessment, and mitigation planning. ultimately, as quantum hardware matures, it promises to become a cornerstone of high-performance computing for smart, resilient, and sustainable infrastructure systems [24],[25]. 8.2 blockchain: enhancing transparency and trust in project management blockchain technology—originally developed to support cryptocurrencies—has emerged as a powerful tool for ensuring security, transparency, and accountability within the digital management of civil engineering projects. operating as a decentralized and immutable ledger, blockchain records every transaction and project milestone in a way that is verifiable, tamper-proof, and accessible to all authorized stakeholders. the potential impact of blockchain in civil engineering lies in its ability to create a transparent and trustworthy project ecosystem. every stage of a construction project, from material sourcing and logistics to payments and inspections, can be recorded in real time, ensuring traceability and reducing the likelihood of fraud or mismanagement. its immutable data structure guarantees that once information is entered, it cannot be modified without consensus, thus fostering confidence among contractors, investors, and regulators. furthermore, blockchain-enabled smart contracts can automate payments, enforce compliance, and execute transactions based on pre-defined milestones, significantly improving project coordination and reducing administrative delays. [26], [27]. 8.3 implementation challenges and future outlook despite their transformative potential, both quantum computing and blockchain face significant challenges before they can be fully integrated into mainstream civil engineering practice. quantum computing remains in an experimental stage, requiring substantial investment, technological refinement, and specialized expertise before it becomes commercially viable and accessible for engineering applications. blockchain adoption, on the other hand, demands a cultural and structural shift in traditional project management frameworks, as well as interoperability across platforms and compliance with evolving legal and data protection standards. additionally, the workforce readiness gap remains a key obstacle; the next generation of engineers must be trained to understand and apply these emerging technologies through updated curricula and continuous professional development programs. nevertheless, the long-term potential of these technologies is extraordinary. as quantum computing evolves to handle real-time simulations and complex optimization problems, and blockchain establishes transparent and tamper-proof governance models, civil engineering will enter an era defined by efficiency, accountability, and sustainability. together, these innovations will not only enhance the precision and reliability of infrastructure systems but also pave the way for a more resilient and ethically grounded future in urban development. eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 20 9. methodological framework for integration the integration of digital technologies into civil engineering represents a paradigm shift that redefines how infrastructure is conceived, designed, and managed. this process enhances operational efficiency, increases accuracy, and enables the creation of data-driven, adaptive solutions to complex engineering challenges. the proposed methodological framework provides a structured pathway for embedding digital transformation within civil engineering practice—drawing upon empirical insights from case studies—and encompasses the full lifecycle of integration: needs assessment, data collection, technology selection, implementation, stakeholder engagement, and continuous evaluation. needs assessment and goal setting the foundation of any digital transformation initiative lies in a rigorous assessment of project needs and the articulation of clear, measurable goals. it begins with the identification of objectives, such as improving safety, reducing costs, or enhancing design precision. this is followed by an assessment of current capabilities, where existing workflows, technologies, and competencies are evaluated to determine areas requiring digital enhancement. through this stage, organizations establish a strategic vision that aligns digital integration with broader sustainability and performance objectives. data collection and analysis high-quality, real-time data is the cornerstone of digital engineering. the process starts with data identification, selecting relevant data types—spatial, structural, environmental, or operational—based on the project’s unique requirements. data acquisition then employs advanced tools such as iot sensors, drones, and remotesensing systems to collect accurate and timely information, complemented by the integration of existing datasets when available. once gathered, the data is processed using specialized analytical and visualization tools, ensuring interoperability with building information modelling (bim), geographic information systems (gis), and other project platforms. technology selection and system design at this stage, the focus shifts to identifying the most suitable digital technologies for achieving project objectives. through technology evaluation, engineers assess potential tools—including ai, ml, bim, and digital twin systems—based on scalability, cost, and compatibility with existing infrastructure. the subsequent system design integrates these technologies into a unified digital ecosystem characterized by interoperability, cybersecurity, and resilience. this step ensures that the technological framework supports both current and future operational needs. implementation and testing successful deployment demands meticulous implementation and pilot testing. controlled pilot projects allow engineers to validate performance, identify system vulnerabilities, and refine configurations before large-scale application. equally essential is training and technical support, ensuring that project teams are equipped to operate new tools effectively and adapt to evolving digital workflows. stakeholder engagement digital integration extends beyond technology—it transforms collaboration. the process begins with the identification of key stakeholders, including engineers, project managers, clients, policymakers, and end-users. a robust communication plan ensures transparent updates, encourages feedback, and fosters shared ownership of the digital transition. stakeholder inclusion not only builds trust but also enhances adoption and long-term project success. monitoring and evaluation once implemented, continuous monitoring and evaluation safeguard performance and value. performance metrics— such as time savings, cost reduction, energy efficiency, and construction quality—are established to measure impact. real-time monitoring tools track both technological performance and user engagement, feeding data into a feedback loop that informs adaptive improvements. this iterative process ensures that digital systems remain responsive and effective throughout the project lifecycle. scaling and optimization the final stage focuses on scaling and optimization. through systematic review and analysis, lessons learned and stakeholder insights are consolidated to refine practices. a scaling strategy is then developed to replicate successful implementations across multiple projects or organizational units, supported by context-specific adaptation guidelines. continuous optimization—informed by performance data and emerging technological advancements—ensures that digital integration evolves in step with innovation, reinforcing civil engineering’s capacity to lead in sustainability, resilience, and intelligent infrastructure development. this methodological framework establishes a dynamic model of continuous improvement, where data, technology, and human expertise converge to transform civil engineering into a fully digital, adaptive, and futureready discipline. eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 21 figure 10. methodological framework for integration of digital technologies into projects or operations figure 10 outlines the methodological framework for integration of digital technologies into projects or operations. this structured approach begins with needs assessment and goal setting, progressing through data collection and analysis, technology selection and system design, implementation and testing, stakeholder engagement, monitoring and evaluation, and concludes with scaling and optimization. each step is designed to ensure that digital technologies are effectively integrated to enhance project outcomes, with a focus on achieving clear objectives, ensuring system interoperability, engaging stakeholders, and continuously improving based on feedback and performance data. integrating digital technologies into civil engineering practices requires a methodical approach, focusing on the alignment of technology with project goals, the design of interoperable systems, stakeholder engagement, and the continuous evaluation of outcomes. this framework, informed by realworld case studies, provides a roadmap for civil engineering firms to navigate the digital transformation process effectively, ensuring that technological investments deliver tangible benefits to projects and stakeholders. 10.technology evaluation and selection the integration of advanced digital technologies—such as artificial intelligence (ai), machine learning (ml), and simulation tools—into civil engineering and disaster management represents a transformative shift toward more data-driven, efficient, and resilient infrastructure systems. however, adopting these technologies requires a systematic and evidence-based evaluation process to ensure that selected solutions align with project goals, operational requirements, and ethical standards. the following framework provides a comprehensive methodological approach for evaluating and selecting digital technologies suited to complex engineering environments. a key priority in this process is reliability, which encompasses performance stability, fault tolerance, and data security. technologies must demonstrate consistent performance across varying environmental and operational conditions, maintaining functionality even under system stress or partial failure. equally critical is the implementation of robust cybersecurity protocols to protect sensitive design data and operational systems from unauthorized access or breaches. another essential criterion is scalability. the chosen technology should be adaptable to projects of different sizes and complexities, ensuring resource efficiency and seamless expansion without exponential cost increases. scalable systems allow civil engineering and disaster management frameworks to evolve dynamically as project scopes and data volumes grow. interoperability is also a determining factor for successful integration. new tools and platforms must be compatible with existing digital ecosystems—ranging from bim and gis to iot networks—allowing for smooth communication and data exchange. the use of open data standards and standardized communication protocols enhances collaboration across interdisciplinary teams and institutions, ensuring unified project workflows. economic feasibility remains central to the evaluation process. a cost-effectiveness assessment should include initial investment considerations—such as licensing and equipment procurement—alongside long-term operational costs, including maintenance, software updates, and user training. conducting a return on investment (roi) analysis provides insight into the long-term financial sustainability of the technology relative to its performance gains. equally vital is the potential to improve efficiency and accuracy. the technology must support automation of repetitive and error-prone processes, reduce manual workload, and enhance precision in data analysis, modeling, and decision-making. by leveraging predictive analytics and intelligent automation, organizations can eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 22 accelerate project timelines while improving quality assurance. in the context of resilience, the enhancement of adaptive capacity through digital systems is paramount. technologies that improve disaster prediction, emergency response coordination, and infrastructure monitoring are invaluable. real-time data analytics can detect early warning signs of structural deterioration or environmental hazards, enabling proactive maintenance and minimizing risk. the user experience and training requirements must also be considered. technologies that are intuitive, accessible, and supported by comprehensive training programs are more likely to achieve successful adoption. continuous education initiatives should accompany deployment, ensuring that engineers, planners, and emergency managers are proficient in using the tools effectively. finally, regulatory and ethical considerations underpin all technological integration. compliance with industry standards, safety regulations, and environmental guidelines ensures accountability and legal soundness. equally, the ethical deployment of technology—particularly regarding privacy, algorithmic transparency, and fairness—must remain a guiding principle to maintain public trust and professional integrity. technology evaluation and selection within civil engineering and disaster management must balance innovation with responsibility. a deliberate, multidimensional assessment—grounded in technical reliability, economic viability, interoperability, and ethical governance—ensures that digital transformation contributes not only to operational excellence but also to the creation of resilient, transparent, and sustainable urban infrastructures. figure 11. framework for evaluating and selecting digital technologies in civil engineering. selecting the right digital technology in civil engineering and disaster management requires a comprehensive evaluation of its reliability, scalability, interoperability, and cost-effectiveness. additionally, its potential to enhance efficiency, accuracy, and resilience, along with user experience and regulatory considerations, must be carefully assessed. by systematically applying these criteria, organizations can make informed decisions that align technology selections with their strategic goals, operational requirements, and ethical standards, ensuring the successful integration of digital innovations into their practices. 11. implementation strategies implementing digital technologies such as artificial intelligence (ai), machine learning (ml), and advanced eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 23 simulation tools in civil engineering and disaster management requires a deliberate, phased, and wellcoordinated approach. successful integration depends not only on technological readiness but also on organizational culture, stakeholder collaboration, and adaptive management. the following implementation strategies outline a structured pathway for achieving seamless adoption and maximizing the value of digital transformation within engineering ecosystems. a critical first step is stakeholder engagement and communication. effective digital implementation hinges on identifying and involving all key actors—engineers, project managers, it specialists, policymakers, and endusers—who will interact with or be affected by the new technologies. a robust communication plan should be developed to articulate the objectives, benefits, and potential challenges of the transformation process. transparent communication builds trust, aligns expectations, and mitigates resistance to change. equally important are feedback mechanisms, which allow stakeholders to share insights, concerns, and recommendations throughout the integration phase, ensuring that decision-making remains inclusive and responsive. equipping personnel with the necessary competencies is central to success. training and capacity building initiatives must begin with a skill gap assessment, identifying areas where staff may require additional technical or conceptual knowledge. based on this analysis, customized training programs can be designed to address specific needs—ranging from hands-on operation of ai tools to data-driven decision-making practices. beyond initial training, organizations should foster a culture of continuous learning, offering ongoing access to professional development programs, workshops, and elearning resources that evolve alongside emerging technologies. to minimize risks and ensure controlled deployment, organizations should adopt pilot projects and phased rollout strategies. pilot implementations allow teams to test digital solutions within a contained environment, identify integration challenges, and evaluate performance before scaling up. insights from these pilots inform refinements and establish best practices. a phased rollout, expanding gradually from pilot initiatives to full-scale projects, enables iterative improvement and risk management while facilitating organizational adaptation to the new technologies. another vital consideration is integration with existing systems. before deployment, a compatibility assessment should evaluate the interoperability of new technologies with current software, databases, and operational workflows. this step prevents data silos and operational disruptions. based on these findings, a detailed integration plan can guide data migration, interface configuration, and access management. where necessary, it infrastructure upgrades—including enhanced data storage, processing capabilities, and cybersecurity frameworks—should be implemented to ensure optimal system performance and resilience. finally, digital transformation requires sustained oversight through monitoring, evaluation, and continuous improvement. establishing clear performance metrics— such as improvements in project efficiency, cost savings, safety, and sustainability—enables evidence-based evaluation of technological impact. regular performance reviews should be conducted to assess progress, incorporating feedback from both users and stakeholders to identify operational gaps or emerging needs. the process should remain iterative, with ongoing refinements made to tools, workflows, and strategies to ensure alignment with evolving project goals and technological advances. effective implementation of digital technologies in civil engineering and disaster management is not a one-time intervention but a dynamic, cyclical process. it relies on inclusive governance, robust infrastructure, and a commitment to continuous adaptation—ensuring that innovation translates into measurable improvements in resilience, sustainability, and operational excellence. figure 12. implementation strategies for integrating digital technologies like ai, ml, and simulation tools into civil engineering. figure 12 outlines the implementation strategies for integrating digital technologies like ai, ml, and simulation tools into civil engineering and disaster management. the process begins with stakeholder engagement and communication, moving through training and capacity building, pilot projects and phased rollout, eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 24 integration with existing systems, and culminates in monitoring, evaluation, and continuous improvement. each step is designed to ensure a thorough understanding and effective use of new technologies, fostering a culture of innovation and continuous learning, and ensuring successful technology integration. the successful implementation of digital technologies in civil engineering and disaster management is a multifaceted process that requires strategic planning, stakeholder engagement, training, and careful integration with existing systems. by employing a structured approach that includes pilot testing, phased rollout, and continuous evaluation, organizations can effectively navigate the challenges of digital transformation and realize the full potential of these innovative technologies 12. barriers to digital technology adoption in civil engineering and disaster management the integration of digital technologies into civil engineering and disaster management holds vast potential to improve efficiency, safety, and sustainability. yet, the path toward digital transformation is often constrained by a complex set of institutional, financial, technical, and cultural barriers that impede adoption. recognizing and addressing these obstacles is essential to ensuring that innovation leads to measurable, equitable progress across the engineering and emergency management sectors. this section provides an in-depth analysis of key barriers and outlines targeted strategies to overcome them. a major impediment arises from funding limitations. the substantial cost associated with acquiring, implementing, and maintaining advanced digital technologies—such as ai, ml, and real-time monitoring systems—can discourage adoption, particularly among smaller firms and public sector agencies operating under tight budgets. to address this, organizations should pursue government incentives, research grants, and public–private partnerships that offset financial burdens. pilot programs co-developed with technology providers can also help demonstrate clear returns on investment (roi), validating long-term financial commitment through quantifiable efficiency gains and performance outcomes. another common challenge is resistance to change, deeply rooted in organizational culture and professional habits. many stakeholders remain skeptical about the reliability or necessity of digital tools, preferring established conventional methods. overcoming this resistance requires a comprehensive change management strategy that emphasizes inclusivity and transparency. through targeted training workshops, awareness campaigns, and demonstration projects, organizations can showcase successful implementations, highlight efficiency improvements, and foster a culture of innovation and digital literacy at all institutional levels. a related barrier is the lack of technical expertise needed to deploy and maintain digital systems effectively. as technologies evolve rapidly, the skills gap between traditional engineering competencies and new digital proficiencies widens. the most effective countermeasure is a long-term capacity-building strategy, integrating professional training programs, certification pathways, and academic partnerships. collaborations with universities can drive curriculum modernization, ensuring that future engineers graduate with essential digital skills—ranging from data analytics and ai integration to cybersecurity and digital modeling. data security and privacy concerns present another critical challenge, as digital platforms depend heavily on continuous data collection, processing, and storage. fears of data breaches, misuse, or regulatory noncompliance can hinder adoption. to mitigate these risks, organizations must implement robust cybersecurity protocols, including encryption, authentication systems, and regular security audits. establishing clear data governance frameworks aligned with international privacy standards helps build institutional and public trust in digital systems. interoperability issues often arise when diverse technologies, software platforms, and legacy systems fail to communicate effectively, leading to inefficiencies and fragmented data ecosystems. the solution lies in prioritizing open data standards and adopting platforms designed for seamless integration. investment in middleware solutions—which facilitate communication between disparate systems—ensures smoother workflows, real-time data exchange, and enhanced collaboration across project teams and agencies. regulatory and legal hurdles can also slow digital innovation. in many regions, policy frameworks have not yet adapted to the pace of technological change, resulting in uncertainty regarding compliance, liability, and data ownership. active engagement with regulatory bodies and professional associations is essential to align standards with evolving technologies. civil engineers and technology leaders should participate in policy dialogues and standardsetting initiatives to ensure that legal frameworks encourage rather than restrict digital transformation. finally, public acceptance and trust remain decisive factors in the success of digital initiatives. public skepticism regarding automation, data collection, or ai decisionmaking can delay project approvals and erode community confidence. transparent communication and stakeholder engagement are vital—citizens should be informed about the societal and environmental benefits of digital technologies, their safeguards, and their role in supporting sustainability and disaster resilience. collaborative decision-making and inclusive consultation processes can help build lasting trust and legitimacy among communities. eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 25 figure 13. the barriers to digital technology adoption in civil engineering and disaster management. figure 13, outlines the barriers to digital technology adoption in civil engineering and disaster management. this visualization tracks the progression from funding limitations to public acceptance and trust, identifying key challenges such as resistance to change, lack of technical expertise, data security and privacy concerns, interoperability issues, and regulatory and legal hurdles. each barrier presents a significant challenge that can impede the successful integration of digital technologies into these fields, highlighting the need for targeted strategies to address and overcome these obstacles. overcoming the barriers to digital technology adoption in civil engineering and disaster management requires a multi-faceted approach that addresses financial, cultural, technical, and regulatory challenges. by implementing targeted strategies such as government incentives, change management programs, professional development initiatives, and engaging regulatory bodies, the civil engineering sector can navigate these obstacles and fully harness the potential of digital transformation. achieving this will not only enhance the efficiency and effectiveness of engineering projects and disaster management efforts but also contribute to the resilience and sustainability of built environments. 13. performance assessment and impact analysis evaluating the performance and impact of digital technologies in civil engineering and disaster management is essential to determine how effectively these innovations contribute to efficiency, resilience, and sustainability. this assessment process captures both quantitative and qualitative dimensions, providing a comprehensive understanding of how technology influences operational performance, financial outcomes, user engagement, and community well-being. a structured framework ensures that the evaluation is systematic, evidence-based, and aligned with organizational and societal goals. the process begins with the development of an evaluation framework, which defines clear objectives and identifies relevant performance indicators. objectives should articulate what the technology is designed to achieve— such as enhanced efficiency, improved safety, greater resilience, or cost reduction. for each objective, measurable metrics must be established. these include both quantitative indicators (e.g., project delivery times, cost savings, error reduction) and qualitative indicators (e.g., user satisfaction, social benefits, community resilience). this foundation enables a balanced and multidimensional performance review. quantitative measures provide tangible evidence of improvement. key metrics include efficiency gains, such as reductions in project duration, resource consumption, or data processing time achieved through automation and aidriven optimization. cost savings are another vital measure, assessed by analyzing reductions in operational and maintenance expenditures, or by quantifying economic losses avoided through improved disaster response and risk mitigation. similarly, safety and resilience improvements can be measured through decreased accident rates, lower structural failure incidents, and enhanced durability of infrastructure under extreme environmental conditions. complementing numerical analysis, qualitative measures capture human and social dimensions of technological impact. assessing user experience and adoption through surveys, interviews, or focus groups reveals perceptions of usability, accessibility, and overall satisfaction. evaluating community well-being examines broader societal outcomes, such as improved access to essential services, reduced vulnerability to hazards, and enhanced public confidence in infrastructure safety. additionally, measuring innovation and knowledge creation identifies contributions to professional practice—such as new eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 26 methodologies, digital workflows, or advances in datadriven design and management. a robust comparative analysis reinforces these evaluations by examining performance before and after the implementation of digital technologies. this before-andafter comparison isolates the specific benefits attributable to innovation, while benchmarking against industry standards or peer projects provides context for interpreting performance outcomes relative to best practices. accurate evaluation depends on the use of advanced data collection and analysis tools. real-time monitoring systems embedded within digital platforms can continuously capture operational data, while specialized data analysis and visualization software helps interpret results and communicate findings effectively. together, these tools ensure that performance insights are datadriven, transparent, and reproducible. the next stage involves reporting and feedback loops. findings should be consolidated into clear, comprehensive impact reports that highlight achievements, identify challenges, and propose actionable recommendations. these reports should be shared with stakeholders for validation and feedback, fostering accountability and collaborative learning. stakeholder engagement throughout this process enriches interpretation and ensures alignment with user needs and organizational priorities. finally, continuous adaptation is integral to the process. using actionable insights derived from performance assessments, organizations can refine or scale technologies, optimize implementation processes, or phase out ineffective solutions. through knowledge sharing, lessons learned and best practices can be disseminated across institutions and professional networks, promoting collective progress in the digital transformation of civil engineering and disaster management. performance assessment and impact analysis are essential for validating the effectiveness of digital technologies in civil engineering and disaster management. by employing a mix of quantitative and qualitative measures, organizations can gain a comprehensive understanding of technology benefits, inform strategic decisions, and continuously enhance project outcomes and community resilience. 14. tools and metrics for measuring the impact of digital technologies in civil engineering to effectively evaluate the transformative impact of digital technologies on civil engineering projects, it is essential to employ a combination of quantitative metrics and digital assessment tools that capture improvements in efficiency, cost management, environmental performance, and social outcomes. these indicators provide a structured framework for quantifying benefits while enabling continuous monitoring and adaptive decision-making. the integration of these tools into project workflows ensures that technological innovation translates into measurable progress toward sustainability, resilience, and community well-being. project efficiency metrics efficiency is a key indicator of digital transformation success. the time to completion metric compares project delivery timelines before and after digital adoption, reflecting the degree to which automation, simulation, or real-time data management accelerates workflows. the task automation rate quantifies the proportion of manual activities replaced by digital tools—such as ai-driven design validation, drone-based inspections, or automated documentation—providing a clear measure of productivity gains. the error reduction rate captures improvements in accuracy and quality control by tracking reductions in design inconsistencies, structural rework, or data-entry errors made possible through digital modeling and validation systems like building information modeling (bim). together, these indicators offer a robust picture of how digital integration streamlines engineering processes and enhances performance reliability. cost savings metrics economic efficiency remains central to evaluating technological return. the return on investment (roi) metric compares cumulative cost savings and efficiency benefits over the project lifecycle to the initial acquisition and operational costs of digital technologies. budget variance assesses discrepancies between planned and actual expenditures, providing insights into improved forecasting and fiscal discipline following digital adoption. meanwhile, lifecycle cost analysis—facilitated through bim and integrated data platforms—enables engineers to evaluate total costs of ownership, from material sourcing to maintenance, identifying long-term savings achieved through informed early-stage design and resource optimization. environmental sustainability metrics sustainability is increasingly fundamental to civil engineering practice, and digital technologies play a decisive role in reducing environmental impact. the carbon footprint reduction metric, calculated using digital carbon assessment tools, quantifies emission reductions resulting from material optimization, efficient logistics, and energy-saving construction methods. the resource efficiency index measures how effectively materials, water, and energy are utilized in projects employing digital solutions compared to traditional approaches, reflecting sustainability gains through precision planning and waste minimization. additionally, biodiversity impact assessment tools, powered by geographic information systems (gis) and remote sensing, help evaluate the ecological implications of construction activities, guiding mitigation strategies that preserve local ecosystems. community well-being metrics eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 27 the social dimension of technological impact is captured through community well-being metrics that measure how digital innovations improve quality of life and accessibility. public satisfaction surveys assess community perceptions of new infrastructure, focusing on design, functionality, environmental integration, and aesthetic value. access and mobility improvements are quantified through analytics of transportation data, revealing changes in travel times, public transport usage, and pedestrian mobility as outcomes of smarter urban infrastructure. moreover, social impact assessment (sia) tools evaluate broader socio-economic benefits—including employment generation, housing accessibility, and public health improvements—providing a holistic view of how digital transformation contributes to social equity and inclusion. implementation tools effective impact analysis relies on the right technological enablers. digital dashboards consolidate real-time data from diverse project metrics, offering an integrated overview of performance across technical, financial, environmental, and social dimensions. predictive analytics software utilizes current and historical data to forecast potential project outcomes, optimize resource allocation, and anticipate risks, supporting proactive management. finally, stakeholder feedback platforms enable continuous dialogue with engineers, policymakers, and community members, ensuring that social impacts are dynamically monitored and that project strategies can adapt to emerging needs and concerns. these tools and metrics establish a comprehensive framework for quantifying the benefits of digital transformation in civil engineering. by combining rigorous performance measurement with participatory evaluation, engineers and decision-makers can ensure that technological innovation not only advances efficiency and sustainability but also strengthens the social fabric and resilience of the communities they serve. the adoption of these tools and metrics allows for a comprehensive evaluation of digital technologies' impact on civil engineering projects. by quantifying benefits in terms of efficiency, cost savings, environmental sustainability, and community well-being, organizations can make informed decisions on technology investments, demonstrating the value and justifying the adoption of digital innovations in civil engineering practices. 15. ethical considerations and sustainability the integration of digital technologies in civil engineering and disaster management introduces profound ethical and sustainability challenges that must be carefully managed to ensure that innovation serves humanity and the planet responsibly. as digital systems increasingly shape urban infrastructure, public safety, and environmental stewardship, maintaining ethical integrity and ecological balance becomes essential. addressing these concerns fosters trust, inclusivity, and long-term resilience— ensuring that technological progress contributes to equitable and sustainable societal advancement. 15.1 ethical considerations privacy and data protection remain fundamental concerns in the age of digital engineering. the vast amounts of data collected through sensors, drones, and ai-driven monitoring systems—especially in disaster management contexts—often include sensitive personal or geospatial information. protecting this data through strong encryption, anonymization, and secure storage is essential. furthermore, data collection must adhere to established legal and ethical standards, ensuring informed consent, transparency in usage, and compliance with international privacy regulations to preserve individual rights and public trust [28],[29]. equity and access are equally critical. as digital transformation accelerates, it is vital to ensure that all communities—including vulnerable and marginalized groups—benefit from technology-driven advancements. unequal access to digital tools, infrastructure, or technical training can exacerbate existing social and economic disparities. ethical implementation demands proactive strategies to bridge the digital divide, promote digital literacy, and guarantee that innovation serves the collective good rather than reinforcing exclusion [30]. transparency and accountability form the foundation of ethical governance in aiand ml-assisted decisionmaking. as algorithmic systems increasingly influence design optimization, risk assessment, and emergency response, the logic behind their decisions must remain explainable and auditable. clear documentation of methodologies, open data practices, and public communication about how algorithms function are essential to prevent bias, ensure fairness, and uphold accountability. moreover, institutional frameworks should include procedures for addressing algorithmic errors or ethical violations promptly and transparently [28],[29]. inclusivity in design emphasizes that digital technologies should be developed with input from a diverse range of stakeholders—including engineers, community representatives, policymakers, and end-users. incorporating multiple perspectives ensures that technological systems reflect varied cultural, environmental, and social contexts. inclusive design principles help tailor digital solutions to real-world needs, ensuring that the technologies deployed in infrastructure and disaster response are socially attuned, contextually appropriate, and universally beneficial [30]. finally, safety and reliability are non-negotiable in the deployment of emerging technologies. in civil engineering and disaster management, systems such as ai-controlled monitoring platforms, automated construction robotics, or eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 28 predictive modeling tools directly impact human lives and the built environment. rigorous testing, certification, and ethical oversight are required to ensure that these systems operate dependably under all conditions. the principle of “do no harm” must guide every stage of technological development and implementation, reinforcing public confidence in digitally enhanced infrastructure systems [30]. ethical responsibility and sustainability must evolve in tandem with technological innovation. the future of civil engineering and disaster management depends not only on the sophistication of digital tools but also on the moral and ecological frameworks governing their use. by embedding privacy, equity, transparency, inclusivity, and safety into every layer of digital transformation, the field can ensure that progress remains aligned with humanity’s shared values and the planet’s enduring well-being [28],[29,[30], (figure 14). figure 14. ethical considerations. 15.2 sustainability considerations sustainability lies at the core of responsible digital transformation in civil engineering and disaster management, ensuring that technological progress contributes to environmental preservation, long-term resilience, and social empowerment. as cities and infrastructures become increasingly data-driven, integrating sustainability principles into every stage of technological deployment—from design to decommissioning—is essential to align innovation with planetary and societal well-being. resource efficiency is one of the foremost pillars of sustainable technology adoption. digital tools should be leveraged to minimize waste, optimize energy consumption, and reduce the overall environmental footprint of engineering and disaster management operations. technologies such as building information modeling (bim), ai-based optimization systems, and iotenabled monitoring can enhance precision in material usage, energy management, and logistics, ensuring that projects operate with maximum efficiency and minimal ecological disruption. long-term resilience emphasizes that technology implementation must extend beyond immediate operational benefits to foster adaptive capacity for future challenges—particularly those posed by climate change and natural hazards. digital innovations should contribute to the development of infrastructures and management systems that are flexible, robust, and capable of withstanding unpredictable disruptions. through predictive analytics, real-time monitoring, and adaptive design, civil engineering can evolve into a discipline that not only reacts to crises but anticipates and mitigates them proactively. aligning technological innovation with the sustainable development goals (sdgs) ensures that digital transformation supports global priorities for sustainable growth. every technological choice—whether in materials science, energy management, or urban mobility—should reinforce sdg targets such as clean water and sanitation (goal 6), affordable and clean energy (goal 7), sustainable cities and communities (goal 11), and climate action (goal 13). by embedding sdg alignment into project frameworks, digital transformation becomes a direct contributor to international sustainability commitments [31]. lifecycle analysis provides a holistic perspective on the environmental and social impacts of digital technologies. this approach considers the full trajectory of each technology—from raw material extraction and manufacturing to operation, maintenance, and end-of-life disposal. evaluating lifecycle costs and impacts allows decision-makers to prioritize technologies that exhibit low environmental externalities and high recyclability. sustainable procurement policies and circular economy principles should guide the adoption of technologies that minimize carbon emissions, electronic waste, and ecological degradation across their entire lifespan [32]. finally, community empowerment represents the human dimension of sustainability. beyond deploying advanced tools, digital transformation should enable communities to manage resources wisely, participate in decision-making, and strengthen their capacity for self-reliance in disaster preparedness and response. empowering citizens through open-access data platforms, participatory planning tools, and local training initiatives ensures that technology serves as a catalyst for inclusive, bottom-up sustainability, rather than a top-down imposition. sustainable digital transformation requires balancing technological advancement with ecological integrity and social equity. by embedding resource efficiency, resilience, sdg alignment, lifecycle responsibility, and community empowerment into the digitalization process, civil engineering and disaster management can become key drivers of a more regenerative, adaptive, and just future (figure 15). eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 29 figure 15. sustainability considerations 15.3 implementing ethical and sustainable practices integrating ethical and sustainable practices into the adoption of digital technologies in civil engineering and disaster management requires a strategic, values-driven framework that ensures innovation aligns with societal well-being, environmental stewardship, and institutional accountability. ethical and sustainable implementation is not a one-time initiative but a continuous process that evolves with technological progress and stakeholder expectations. to achieve this, organizations must establish strong governance structures, inclusive engagement mechanisms, and dynamic evaluation systems that uphold transparency, fairness, and long-term resilience. policy and governance play a foundational role in institutionalizing responsible technology use. governments, professional associations, and engineering organizations should develop comprehensive policies and regulatory frameworks that embed ethical considerations— such as privacy protection, data accountability, and equity—into every phase of technological integration. these policies must also align with sustainability principles, mandating environmentally responsible procurement, lifecycle assessments, and carbon reduction targets. furthermore, clear governance mechanisms should define roles, responsibilities, and compliance standards, ensuring that decision-making processes are both transparent and enforceable. embedding ethical and sustainability criteria in project evaluation and funding decisions ensures that technological innovation consistently serves the public interest. stakeholder engagement is equally critical in fostering legitimacy and inclusivity in digital transformation. active participation from all relevant actors—engineers, policymakers, researchers, local communities, and endusers—helps identify social expectations, potential risks, and community aspirations regarding technology deployment. continuous dialogue through workshops, consultations, and participatory design sessions enhances mutual understanding and cultivates trust. by incorporating community input into technology design and policy development, civil engineering projects can better address local needs while promoting social equity and environmental justice. finally, continuous monitoring and evaluation ensure that ethical and sustainable practices remain adaptive and effective over time. establishing robust assessment mechanisms allows organizations to track the ethical implications, environmental impact, and social outcomes of technology use. periodic reviews and audits should evaluate compliance with ethical guidelines, data governance policies, and sustainability objectives, providing opportunities for corrective action where necessary. integrating real-time analytics and feedback systems further enhances accountability by enabling ongoing measurement of energy efficiency, emissions reduction, user satisfaction, and social inclusivity. the successful implementation of ethical and sustainable practices depends on a cyclical process of governance, participation, and reflection. by embedding ethical responsibility and ecological awareness into policy frameworks, empowering stakeholders through inclusive engagement, and maintaining continuous oversight, civil engineering and disaster management sectors can ensure that digital innovation not only advances technical excellence but also upholds humanity’s collective responsibility to build a just, sustainable, and resilient future. figure 16. implementing ethical and sustainable practices incorporating digital technologies into civil engineering and disaster management necessitates a careful balance between innovation and ethical responsibility. by prioritizing privacy, equity, transparency, safety, and sustainability, professionals in these fields can harness the benefits of technology while upholding their duty to society and the environment. 16. expected outcomes the strategic integration of digital transformation and artificial intelligence (ai) into civil engineering practices, particularly in the contexts of disaster management and sustainable urban development, is poised to offer transformative outcomes. this methodology is designed to eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 30 equip civil engineering professionals, disaster management experts, and urban planners with a deep understanding of the potential and practicalities of leveraging digital technologies. below are the expected outcomes of this integration: 1. enhanced efficiency and accuracy. the adoption of ai and digital tools is expected to significantly improve the efficiency of engineering tasks and project execution. automated data analysis, predictive modeling, and realtime monitoring can lead to more accurate assessments, faster decision-making, and reduced project timelines and costs. 2. improved disaster preparedness and response. digital technologies enable more effective disaster risk assessment, early warning systems, and rapid response strategies. ai can predict disaster impacts with greater precision, while drones and iot devices can assist in realtime monitoring and damage assessment, ensuring a swift and coordinated response that saves lives and minimizes damage. 3. sustainable urban planning and development. ai and digital modeling tools facilitate the design of more sustainable and resilient urban infrastructures. they allow for the optimization of resource use, incorporation of renewable energy solutions, and planning of green spaces, contributing to the goals of sustainable development and climate change mitigation. 4. strengthened infrastructure resilience. the integration of digital technologies in civil engineering promotes the construction of infrastructure that is more resilient to natural disasters and climate impacts. predictive maintenance, powered by ai and sensor data, can extend the lifespan of critical infrastructure, ensuring it remains functional when most needed. 5. informed decision-making. data-driven insights provided by ai and digital tools support more informed and strategic decision-making by practitioners and policymakers. this leads to better resource allocation, investment in critical areas, and prioritization of projects with the highest impact on community safety and wellbeing. 6. community engagement and empowerment. digital platforms and communication tools can enhance community engagement in urban development and disaster management processes. by facilitating the flow of information between authorities and the public, these technologies can empower communities to participate more actively in their own resilience building. 7. knowledge creation and sharing. the methodology supports the creation of new knowledge in the field of civil engineering, fostering innovation and the sharing of best practices. it encourages ongoing research and development, contributing to the continuous advancement of the discipline. 8. policy and regulatory framework development. by showcasing the benefits and challenges of digital integration in civil engineering, the methodology aids in the development of supportive policy and regulatory frameworks. this ensures that technological advancements are leveraged in a manner that is ethical, equitable, and conducive to long-term sustainability. figure 17. expected outcomes of integrating digital technologies. figure 17, illustrate the expected outcomes of integrating digital technologies, such as ai, into civil engineering practices. this visualization encompasses various aspects, from enhancing efficiency and accuracy in engineering tasks to improving disaster preparedness and response, fostering sustainable urban planning and development, and strengthening infrastructure resilience. it also highlights the importance of informed decision-making, community engagement and empowerment, knowledge creation and sharing, and the development of supportive policy and regulatory frameworks. each of these outcomes contributes to the overall goal of leveraging technological advancements in a manner that is ethical, equitable, and conducive to long-term sustainability. 17. conclusion the convergence of artificial intelligence (ai), machine learning (ml), and digital transformation represents a decisive evolution in civil engineering—one that transcends technological modernization to redefine the discipline’s epistemology, ethics, and societal purpose. as demonstrated throughout this study, the integration of aidriven analytics, ict infrastructures, digital twins, and emerging computational paradigms such as quantum computing and blockchain is inaugurating a new civilizational architecture of knowledge and resilience. this synthesis enables predictive, adaptive, and ethically guided engineering systems that enhance disaster preparedness, optimize resource use, and reinforce the sustainability of the built environment. from an operational perspective, digital transformation has been shown to elevate precision, efficiency, and eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | integrating digital transformation and ai in civil engineering: a multidisciplinary approach to disaster management and sustainable urban development 31 responsiveness across all project stages—from material science and structural design to maintenance and urban governance. empirical evidence drawn from diverse case studies confirms that ai-empowered methodologies can anticipate failures, automate complex assessments, and support real-time decision-making processes, thereby reducing both economic and environmental costs. equally transformative is the pedagogical domain, where immersive digital learning environments and simulationbased education cultivate a new generation of engineers fluent in algorithmic reasoning, data ethics, and systems thinking. yet, this transition is not purely technological; it is civilizational. the success of digital integration depends on addressing systemic barriers—economic inequities, cultural resistance, and skill deficits—while embedding strong ethical and sustainability frameworks. governance mechanisms must evolve to protect data integrity, ensure algorithmic transparency, and maintain public trust. civil engineering, as both a science and a social contract, must therefore navigate the digital turn not as an end in itself, but as a pathway toward planetary stewardship and collective resilience. the digital transformation of civil engineering inaugurates a new synthesis between intelligence and infrastructure. it calls for a discipline that is simultaneously computational and compassionate—guided by data but accountable to humanity. the challenge before us is not merely to adopt technologies, but to orchestrate them toward a coherent vision of sustainable progress, in which each bridge, system, and city embodies the principles of ethics, resilience, and renewal. through the responsible fusion of ai and engineering intelligence, humanity can design infrastructures that do more than endure—they can evolve, adapt, and inspire. eai endorsed transactions on smart cities | volume 8 | issue 1 | 2025 | dimitrios sargiotis 32 appendix a. a.1. list of abbreviations ai artificial intelligence ml machine learning ict information and communication technology bim building information modeling iot internet of things gis geographic information systems uav unmanned aerial vehicle sdgs sustainable development goals roi return on investment pcf photonic crystal fiber cnn convolutional neural networks dx digital transformation sia social impact assessment vr virtual reality ng911 next-generation 911 gi green infrastructure a.2. list of annotations ai artificial intelligence ml machine learning ict information and communication technology bim building information modeling iot internet of things gis geographic information systems uav unmanned aerial vehicle sdgs sustainable development goals roi return on investment pcf photonic crystal fiber cnn convolutional neural networks dx digital transformation sia social impact assessment vr virtual reality ng911 next-generation 911 gi green infrastructure cdm collaborative decision making lca life cycle assessment ghg greenhouse gas rfid radio-frequency identification cad computer-aided design cfd computational fluid dynamics stem science, technology, engineering, and mathematics ppp public-private partnership leed leadership in energy and environmental design pm project management / particulate matter qa/qc quality assurance/quality control r&d research and development sdlc software development 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