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Design of Mathematical Model and Implementation of IoT Enabled Smart 

Secure Parking System 
 

1M.L.Keote, 2U.S.Ghodeswar, 3Bhuvneshwari Gathibandhe, 4Siddhi Khodankar, 5Anchal Shende, 6Tejas 

Zilpilwar 
1Department of Electronics And Telecommunication Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, 

India. klminal@rediffmail.com 
2Department of Electronics Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, India 

ghodeswarujwala83@gmail.com 
3Department of Electronics And Telecommunication Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, 

India. bhuvneshwarigathibandhe@gmail.com 
4Department of Electronics And Telecommunication Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, 

India. khodankarsiddhi@gmail.com 
5Department of Electronics And Telecommunication Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, 

India. shendeachal2002@gmail.com 
6Department of Electronics And Telecommunication Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, 

India. tejaszilpilwar@gmail.com 

 

 

Article History: 

Received: 28-03-2024 

Revised: 02-05-2024 

Accepted: 20-05-2024 

Abstract:  

The fast growth of cities and the resulting rise in traffic have made it necessary to create 

effective parking control systems. This paper talks about how to build and set up an Internet 

of Things (IoT)-enabled smart parking system. IoT technology is used in the suggested 

system to solve problems with current parking systems, like wasteful use of space, traffic 

jams, and damage to the environment. A detailed mathematical model is created to find the 

best way to assign parking spaces, cut down on the time it takes to look for open spots, and 

improve the overall user experience. The system design combines different Internet of Things 

(IoT) parts, like sensors, motors, and communication units, so parking places can be managed 

and watched in real time. The math model includes methods for allocating parking spots 

dynamically based on data from IoT sensors gathered in real time. The goal of this model is 

to guess where parking spots will be available, make the best use of those places, and cut 

down on the time people spend looking for parking. The technology also uses machine 

learning to look at old data and get better at making predictions over time. Details about how 

to implement are talked about in depth, such as the hardware setup, transmission methods, 

and program parts. A lot of models and real-life tests in a city are used to judge the system's 

success. The results show big changes in how parking spaces are used, less traffic, and lower 

pollution, all of which make cities more sustainable. The suggested smart parking system that 

uses the Internet of Things (IoT) is a cost-effective and scalable answer to today's parking 

problems. More work will be done in the future to improve the system's abilities using 

advanced machine learning techniques and to spread its use to more cities. This study shows 

that IoT technology has the ability to change the way cities work and make life better in 

smart cities. 

Keywords: IoT (Internet of Things), IR Sensors, RFID, NodeMCU, Smart Parking, Smart 

Cities, Android Application, Cloud Computing, Security and Privacy. 

 



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1. INTRODUCTION 

People moving into cities and buying cars at an exponential rate have created a major problem: how 

to handle parking in places with lots of people. Conventional parking methods don't always make 

good use of parking spots, which leads to traffic jams, lost time, higher emissions, and angry drivers. 

Putting together Internet of Things (IoT) technology with smart parking systems looks like a good 

way to solve these problems. This article talks about how an Internet of Things (IoT)-enabled Smart 

Parking System (SPS) was put into action. The goal was to change the way parking spaces are 

managed by tracking and improving them in real time. Setting up sensor networks all over the 

parking infrastructure is the first step in putting the IoT-enabled SPS into action. Sensors with 

technologies like ultrasound, infrared, or magnetic sensors are put in each parking spot in a way that 

lets the system know if a car is there or not. The data from the sensors is then sent directly to a 

central computer so that it can be processed and analyzed. 

 
Fig 1: Overview of IoT based Smart parking System 

 

The most important part of implementing SPS is building a strong software platform that can handle 

real-time data streams, do advanced analytics, and coordinate methods for allocating parking spaces. 

The software tool works with the IoT sensor network to make real-time data about parking usage that 

can be gathered and processed. It uses machine learning methods to guess how many parking spots 

are available based on past data, the day of the week, the time of day, and other factors. With these 

prediction analytics, the system can guess how many parking spots will be needed and best assign 

them based on that. The rise in car ownership in cities has caused a major problem: parking is hard to 

find, especially in residential areas, which takes a lot of time for people who live there. This study 

suggests a Smart Parking System that focuses on society. It would use IoT technology and an easy-

to-use app to simplify parking, improve safety, and make the best use of space. Traditional ways of 

managing parking in neighborhoods, like using security guards or resident-marked spots, are 



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inefficient and don't make things clear. Cutting-edge technology is built into our answer, which 

changes this completely: people use RFID cards to get in, and a mobile app controls servo motors. 

This app acts as a hub, showing in real time which slots are taken, making it easier for guests to park 

by inviting them, and making sure security and openness. At each slot, infrared cameras send 

information about the location of a car to the cloud, which updates information about occupation for 

tracking from afar. With ESP8266 microcontrollers making sure smooth Wi-Fi connection, our 

system lets you control motors from afar and get real-time updates, offering a safe, easy, and smart 

parking solution. This combination of RFID entry, app control, and usage tracking has a huge 

potential to improve parking and make living spaces more organized and stress-free for both 

residents and guests. 

2. LITERATURE SURVEY 

Putting together an IoT-enabled Smart Parking System means combining different technologies to 

better handle parking spots and make the user experience better. Recently, many studies have looked 

at different parts of these kinds of systems, mainly efficiency, real-time tracking, and how users can 

connect with them. Optimization of parking spot usage is a theme that comes up a lot in the writings. 

Based on real-time data, researchers have come up with methods and systems that could 

automatically assign parking spots [1]. For example, programs that use machine learning have been 

created to guess when parking spaces will become available. This lets parking resources be managed 

more efficiently. There have also been suggestions for optimization models that would cut down on 

the time it takes to look for parking, which would also cut down on traffic and pollution. Another 

important topic that has been written about is real-time tracking [2]. Internet of Things (IoT) 

monitors are used to track which parking spaces are occupied, which allows for management and 

tracking from afar. Ultrasonic sensors, thermal sensors, and magnetic sensors are some of the sensor 

technologies that have been studied [3].  

Each has its own benefits when it comes to accuracy and cost-effectiveness. Also, radio 

communication methods like LoRaWAN and MQTT make it easy for sensors and the central control 

system to send and receive data. Smart parking systems that use the Internet of Things (IoT) also 

take user involvement and contact into account when they are being designed. Mobile apps are being 

made to give users real-time information on available parking spots, help with directions, and 

reservation services [4]. System administrators can keep making the user experience better and adapt 

to changing user tastes by adding ways for users to give feedback, like scores and reviews. Also, 

studies show how important safety and security are in IoT-enabled Smart Parking Systems. To keep 

data transfer safe and user information safe, encryption and verification methods are used. Privacy-

preserving methods are being looked into to make personal data anonymous while still letting 

researchers learn useful things that can help improve the system. 

 

 

 

 

 

 

 

 



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Table 1: Related work Summary 

Method Approach Finding Limitation Scope 

Sensor-Based 

[4] 

Installation of 

IoT sensors in 

parking spaces 

Real-time 

detection of 

vehicle 

occupancy 

Costly hardware 

deployment 

Urban parking management 

Machine 

Learning [5] 

Training 

models on 

historical 

parking data 

Predictive 

analytics for 

parking space 

availability 

Dependency on 

data quality 

Predictive maintenance of 

parking infrastructure 

Data Analytics 

[6] 

Analysis of 

parking 

occupancy 

patterns 

Identification of 

peak parking 

demand hours 

Limited 

scalability 

Parking space optimization 

Mobile App 

Integration [7] 

Development 

of user-friendly 

applications 

Seamless access 

to parking 

availability 

information 

Compatibility 

issues with older 

devices 

Enhanced user experience 

Cloud 

Computing [8] 

Utilization of 

cloud servers 

for data 

processing 

Scalability and 

real-time 

processing 

capabilities 

Reliance on 

internet 

connectivity 

Centralized parking 

management system 

GIS 

Integration 

[12] 

Incorporation 

of Geographic 

Information 

Systems 

Spatial 

visualization of 

parking data 

Complexity in 

data integration 

Geospatial analysis of 

parking utilization 

Dynamic 

Pricing [9] 

Implementation 

of variable 

pricing 

strategies 

Optimization of 

revenue 

generation 

Resistance from 

users 

accustomed to 

fixed rates 

Revenue maximization for 

parking operators 

IoT 

Connectivity 

[10] 

Integration 

with existing 

IoT 

infrastructure 

Interoperability 

and seamless data 

exchange 

Security 

vulnerabilities 

Smart city integration 

Network 

Optimization 

[11] 

Routing 

algorithms for 

efficient 

parking 

navigation 

Reduced search 

time for available 

parking spots 

Dependency on 

accurate sensor 

data 

Traffic flow management 

within parking facilities 

User Feedback 

Mechanism 

[13] 

Incorporation 

of feedback 

mechanisms 

Improvement of 

system usability 

and reliability 

Bias in feedback 

collection 

Continuous system 

improvement based on user 

input 

3. SYSTEM DESCRIPTION 

The Smart Parking System for Societies is an Internet of Things (IoT)-based system that makes it 

easier to handle parking in apartment buildings. It has many hardware parts, like RFID readers, servo 

motors, IR sensors, and ESP8266 microcontrollers. It also has an easy-to-use mobile app that was 

made with the MIT App Inventor platform. The core system runs on a cPanel server and is made 

possible by PHP and MySQL. It handles user data and parking spot information effectively. At the 



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parking gate, where RFID cards are used for identification, servo motors open the gate and let the 

user in. The mobile app is the main way that users interact with the society, and it shows them in real 

time which parking spots are open. IR cameras constantly check to see which parking spots are 

occupied and manage the division of parking spots on the fly.  

 
Fig 2: IoT Based Smart Parking System – Flow Chart 

Fig. 2 shows a flow chart that shows the order of processes in an IoT-based smart parking system. At 

first, monitors check the state of parking spots and send information to a computer. This information 

is sent to the computer, which changes the database and sends real-time access to the mobile app. 

The app lets users check on the state of their parking, make bookings, and handle guest requests. The 

server reacts to what users do by changing the state of parking spots and, if needed, opening and 

closing gates.  

 

a. System Architecture: 

• The IoT-enabled Smart Parking System's system architecture is made to be flexible and 

scalable. This makes sure that hardware and software parts can talk to each other and work 

together without any problems. The design includes both hardware and software layers that 

make it easier for data and processing to move around in the system. 

• Microcontrollers, sensors, and motors are the most important parts in the physical layer. These 

devices talk to each other using different protocols, like Wi-Fi and HTTP, which lets them 

send data and take control of other devices. The software layer has parts like a mobile app, a 

web server, and a cloud platform that make it easier for users to connect with the system, 

process data, and handle it. 

b. Hardware Integration: 

• Assemble hardware components (ESP8266 boards, RFID reader, servo motors, IR sensors, 

power supplies) and connect them securely. Configure ESP8266 Wi-Fi settings and connect 

them to the server using HTTP libraries.Integrate IR sensors in each parking slot and 

configure them for accurate vehicle detection. Ensure stable power supply for each component 



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c. Software Development 

Make a user interface that is easy to understand and uses for showing real-time parking availability, 

user accounts, guest requests, and possible remote control functions. Use RFID or cellphone keys to 

let residents log in. Show the number of occupied parking spots on a map or in a list, handle calls 

from guests to park, and control parking slot gates from afar. Use built-in elements like buttons, 

maps, lists, and web elements to send HTTP requests to the main server and chat with it. Make API 

APIs that can handle HTTP calls from the mobile app and ESP8266 devices. Set up user registration, 

login, and profile management, and use a MySQL database to store information about parking spots. 

Take care of parking requests from guests, send real-time parking information, and give the mobile 

app instructions. Make sure security by authenticating users, encrypting data, and checking input. 

Using tools like ESP8266WiFi and ESP8266HTTPClient, you can make software that can connect to 

WiFi and make HTTP calls with the server. Read data from IR sensors, send it to the server on a 

regular basis, and get control orders to run servo motors. Leave comments and notes on your code so 

that it can be maintained in the future. 

4. PROPOSED METHODOLOGY 

A. Mathematical Model for an IoT-enabled Smart Parking System: 

Real-time data and advanced formulas will be used in the suggested mathematical model for an IoT-

enabled smart parking system to fix the problems and flaws of current parking systems. This model 

combines several parts and methods to make the best use of parking spaces, cut down on search time, 

and improve the user experience. IoT devices, like sensors, motors, and transmission units, are 

carefully put in the parking area to make up the system design. Each parking spot has sensors that 

check to see if there are cars there or not. These sensors then send this information to a central 

computer through a communication network. For example, actuators can be used to move fences or 

lights that show cars where to park. The central server takes in the information and uses optimization 

methods to make sure that parking spots are given out in the best way possible. 

The core of the mathematical model is formulated to minimize the total time vehicles spend 

searching for parking. Let N represent the total number of parking spots, Si the status of the ith 

parking spot (where Si=1 if occupied and Si=0 if vacant), and Ti the time taken to reach the ith spot 

from the entry point. The objective function can be expressed as: 

𝑀𝑖𝑛𝑖𝑚𝑖𝑧𝑒 ∑𝑖 = 1𝑁𝑆𝑖 × 𝑇𝑖 

𝑠𝑢𝑏𝑗𝑒𝑐𝑡 𝑡𝑜 𝑡ℎ𝑒 𝑐𝑜𝑛𝑠𝑡𝑟𝑎𝑖𝑛𝑡𝑠: 

∑𝑖 = 1𝑁𝑆𝑖 ≤ 𝑁 (𝑎 𝑝𝑎𝑟𝑘𝑖𝑛𝑔 𝑠𝑝𝑜𝑡 𝑐𝑎𝑛 𝑒𝑖𝑡ℎ𝑒𝑟 𝑏𝑒 𝑜𝑐𝑐𝑢𝑝𝑖𝑒𝑑 𝑜𝑟 𝑣𝑎𝑐𝑎𝑛𝑡, 𝑛𝑜𝑡 𝑏𝑜𝑡ℎ) 

𝑆𝑖 ∈ {0,1} 

B. Dynamic Allocation Algorithm: 

A dynamic allocation algorithm is developed to assign parking spots in real-time based on the 

incoming data. This algorithm prioritizes spots that minimize walking distance for users and balances 

the load across the parking facility to avoid congestion in specific areas. The algorithm continuously 

updates as new data is received, ensuring the model adapts to real-time conditions. 

 

 

 



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Process Model Step wise:  

1. Equation for Predicting Parking Space Availability: 

𝐴𝑣𝑎𝑖𝑙_𝑖, 𝑗(𝑡)  =  𝑓(𝑂𝑐𝑐𝑢𝑝_𝑖, 𝑗(𝑡), 𝑒𝑥𝑡𝑒𝑟𝑛𝑎𝑙 𝑓𝑎𝑐𝑡𝑜𝑟𝑠) 

• This equation predicts the availability of parking space i in parking area j at time t 

based on the current occupancy Occup_i,j(t) and external factors such as time of day, day of 

the week, and special events. 

2. Equation for Vehicle Detection: 

𝐷_𝑖, 𝑗(𝑡)  =  𝑔(𝑆𝑒𝑛𝑠𝑜𝑟_𝑖, 𝑗(𝑡)) 

• This equation represents the detection of a vehicle in parking space i of parking area j 

at time t based on sensor readings Sensor_i,j(t). 

3. Equation for Optimizing Parking Space Allocation: 

𝑂𝑝𝑡𝑖𝑚𝑖𝑧𝑒(𝑃𝑎𝑟𝑘𝑖𝑛𝑔)  =  𝑎𝑟𝑔𝑚𝑎𝑥_𝑖, 𝑗 𝐴𝑣𝑎𝑖𝑙_𝑖, 𝑗(𝑡) 

• This equation optimizes the allocation of parking spaces by maximizing the 

availability of parking spaces across all parking areas and spaces. 

4. Equation for Real-time Data Processing: 

𝐷𝑎𝑡𝑎_𝑝𝑟𝑜𝑐𝑒𝑠𝑠𝑒𝑑(𝑡)  =  𝑃𝑟𝑜𝑐𝑒𝑠𝑠(𝐷𝑎𝑡𝑎_𝑟𝑎𝑤(𝑡)) 

• This equation represents the processing of raw sensor data Data_raw(t) collected at 

time t to generate processed data Data_processed(t) for further analysis and decision-making. 

5. Equation for User Notification: 

𝑁𝑜𝑡𝑖𝑓𝑦_𝑢𝑠𝑒𝑟(𝑡)  =  ℎ(𝐴𝑣𝑎𝑖𝑙_𝑖, 𝑗(𝑡)) 

• This equation triggers a notification to the user at time t based on the availability of 

parking space i in parking area j. The function h determines the notification criteria, such as 

sending a notification when parking availability drops below a certain threshold. 

 

C. Block diagram of the system 

This figure 3 shows how IoT-based smart parking systems can be used as a basic part of building a 

smart city. The method helps make cities more sustainable by handling parking spots well, easing 

traffic, and cutting down on pollution. It makes life better, helps the economy grow, and encourages 

technology progress. 



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Fig 3: IoT Based Smart Parking System – Step towards Building Smart City 

 

Real-time data analytics and easy-to-use platforms make it easier to get around cities, showing how 

smart technologies can change the structures of cities. This progress is a big step toward making 

cities that are connected, efficient, and good for the environment, which are the main ideas behind a 

"smart city." 

These steps and numbers give a simple but complete picture of how the IoT-enabled smart parking 

system is set up and how it works. The IoT-enabled Smart Parking System shown in Fig. 4 uses 

sensors to find open parking spots and sends that information to a central computer that users can 

access for better parking management and guidance. 

 

 
Fig.4: Block Diagram of IoT Enabled Smart Parking System 

 



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a. Power Onset: 

Step: Start with a 12V power supply. Use an adapter to channel this power into the power circuit 

PCB. 

𝑉𝑖𝑛 = 12𝑉 

b. Voltage Transformation: 

Step: Employ the 7805 regulator IC on the power circuit PCB to convert the incoming 12V into a 

versatile 5V. 

𝑉𝑜𝑢𝑡 = 𝑉𝑖𝑛 − (𝑉𝑑𝑟𝑜𝑝) 

𝑤ℎ𝑒𝑟𝑒 𝑉𝑜𝑢𝑡 = 5 𝑎𝑛𝑑 𝑉𝑑𝑟𝑜𝑝 ≈ 7𝑉 

c. NodeMCU Integration: 

Introduce the NodeMCU into the system. Guide the transformed 5V energy through the NodeMCU, 

where it undergoes a magic transformation into a gentle 3.3V. 

𝑉𝑁𝑜𝑑𝑒𝑀𝐶𝑈 = 5𝑉 → 3.3𝑉 

d. Connect to LCD and IR Sensors: 

Establish connections from the NodeMCU to two primary components - an LCD and four IR 

sensors. Utilize I2C to facilitate communication between the LCD and NodeMCU. For the IR 

sensors, set up power LEDs and data LEDs for vigilant monitoring. 

𝐼𝐿𝐶𝐷 = 𝐼𝑁𝑜𝑑𝑒𝑀𝐶𝑈 × 𝑅𝐼2𝐶𝑉𝑁𝑜𝑑𝑒𝑀𝐶𝑈 

e. Smart Sensor Control: 

Enhance the IR sensors' functionality by incorporating a potentiometer for sensitivity control. 

Integrate a comparator IC into the potentiometer, adding an intelligent layer to the sensor system. 

𝑉𝐼𝑅 = 𝑅𝑡𝑜𝑡𝑎𝑙𝑅𝑝𝑜𝑡 × 𝑉𝑖𝑛 

f. Second NodeMCU Introduction: 

Introduce a second NodeMCU into the system architecture. 

𝑉𝑁𝑜𝑑𝑒𝑀𝐶𝑈2 = 5𝑉 → 3.3𝑉 

g. Connect to RFID Scanner and Servo Motor: 

Establish connections from the second NodeMCU to the VIPs of the system - the RFID scanner and 

the servo motor. Enable the RFID scanner to crosscheck scanned RFID tags with a backend 

database. 

𝐼𝑠𝑒𝑟𝑣𝑜 = 𝐼𝑁𝑜𝑑𝑒𝑀𝐶𝑈2 × 𝑅𝑠𝑒𝑟𝑣𝑜𝑉𝑁𝑜𝑑𝑒𝑀𝐶𝑈2 

h. Gate Opening Mechanism: 

Step: Employ the servo motor, under the second NodeMCU's control, to gracefully swing open the 

gate upon a successful RFID match. Allow the gate to remain ajar for a duration of 10 seconds, 

providing ample time for a car to enter. 

𝜃𝑠𝑒𝑟𝑣𝑜 = 𝑓(𝑅𝐹𝐼𝐷𝑠𝑐𝑎𝑛, 𝑡𝑜𝑝𝑒𝑛 = 10𝑠) 



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D. Secure Authentication 

Step 1: Generation of RFID Tag Unique Identifier 

• Let UID_RFID represent the unique identifier of the RFID tag. 

• The RFID tag's unique identifier is generated during manufacturing, typically 

consisting of a string of alphanumeric characters. 

Step 2: Encryption of Unique Identifier 

• Let K_AES represent the secret key for AES encryption. 

• The unique identifier UID_RFID is encrypted using the AES encryption algorithm with the 

key K_AES, resulting in the ciphertext C_RFID. 

𝐶_𝑅𝐹𝐼𝐷 =  𝐴𝐸𝑆(𝐾_𝐴𝐸𝑆, 𝑈𝐼𝐷_𝑅𝐹𝐼𝐷) 

AES MODEL  

𝑎: 𝐾𝑒𝑦 𝐸𝑥𝑝𝑎𝑛𝑠𝑖𝑜𝑛 

• 𝑇ℎ𝑒 𝑖𝑛𝑖𝑡𝑖𝑎𝑙 𝑠𝑒𝑐𝑟𝑒𝑡 𝑘𝑒𝑦 𝐾 𝑖𝑠 𝑒𝑥𝑝𝑎𝑛𝑑𝑒𝑑 𝑖𝑛𝑡𝑜 𝑎 𝑠𝑒𝑡 𝑜𝑓 𝑟𝑜𝑢𝑛𝑑 𝑘𝑒𝑦𝑠 {𝐾0, 𝐾1, … , 𝐾𝑁𝑟}𝑢𝑠𝑖𝑛𝑔 𝑡ℎ𝑒 𝑘𝑒𝑦 𝑠𝑐ℎ𝑒𝑑𝑢𝑙𝑒 𝑎𝑙𝑔𝑜𝑟𝑖𝑡ℎ𝑚: 𝐾𝑖 =

 𝐾𝑒𝑦𝑆𝑐ℎ𝑒𝑑𝑢𝑙𝑒(𝐾𝑖 − 1, 𝑖) 

𝑏. 𝐼𝑛𝑖𝑡𝑖𝑎𝑙 𝑅𝑜𝑢𝑛𝑑 

• 𝑇ℎ𝑒 𝑖𝑛𝑝𝑢𝑡 𝑝𝑙𝑎𝑖𝑛𝑡𝑒𝑥𝑡 𝑏𝑙𝑜𝑐𝑘 𝑃 𝑖𝑠 𝑋𝑂𝑅𝑒𝑑 𝑤𝑖𝑡ℎ 𝑡ℎ𝑒 𝑓𝑖𝑟𝑠𝑡 𝑟𝑜𝑢𝑛𝑑 𝑘𝑒𝑦 𝐾0: 

𝐶0 =  𝑃 ⊕  𝐾0 

𝑐: 𝑀𝑎𝑖𝑛 𝑅𝑜𝑢𝑛𝑑𝑠 (𝑀𝑢𝑙𝑡𝑖𝑝𝑙𝑒 𝑅𝑜𝑢𝑛𝑑𝑠) 

• 𝐸𝑎𝑐ℎ 𝑟𝑜𝑢𝑛𝑑 𝑐𝑜𝑛𝑠𝑖𝑠𝑡𝑠 𝑜𝑓 𝑓𝑜𝑢𝑟 𝑚𝑎𝑖𝑛 𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑜𝑛𝑠 𝑎𝑝𝑝𝑙𝑖𝑒𝑑 𝑡𝑜 𝑡ℎ𝑒 𝑠𝑡𝑎𝑡𝑒 𝑚𝑎𝑡𝑟𝑖𝑥 𝑆: 

𝑆𝑢𝑏𝐵𝑦𝑡𝑒𝑠(𝑆) 

𝑆ℎ𝑖𝑓𝑡𝑅𝑜𝑤𝑠(𝑆) 

𝑀𝑖𝑥𝐶𝑜𝑙𝑢𝑚𝑛𝑠(𝑆) 

𝐴𝑑𝑑𝑅𝑜𝑢𝑛𝑑𝐾𝑒𝑦(𝑆, 𝐾𝑖) 

• 𝑇ℎ𝑒 𝑡𝑟𝑎𝑛𝑠𝑓𝑜𝑟𝑚𝑎𝑡𝑖𝑜𝑛𝑠 𝑎𝑟𝑒 𝑎𝑝𝑝𝑙𝑖𝑒𝑑 𝑖𝑡𝑒𝑟𝑎𝑡𝑖𝑣𝑒𝑙𝑦 𝑓𝑜𝑟 𝑁𝑟 𝑟𝑜𝑢𝑛𝑑𝑠. 

𝑑: 𝐹𝑖𝑛𝑎𝑙 𝑅𝑜𝑢𝑛𝑑 

• 𝑇ℎ𝑒 𝑓𝑖𝑛𝑎𝑙 𝑟𝑜𝑢𝑛𝑑 𝑖𝑠 𝑠𝑖𝑚𝑖𝑙𝑎𝑟 𝑡𝑜 𝑡ℎ𝑒 𝑚𝑎𝑖𝑛 𝑟𝑜𝑢𝑛𝑑𝑠 𝑏𝑢𝑡 𝑑𝑜𝑒𝑠 𝑛𝑜𝑡 𝑖𝑛𝑐𝑙𝑢𝑑𝑒 𝑡ℎ𝑒 𝑀𝑖𝑥𝐶𝑜𝑙𝑢𝑚𝑛𝑠 𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑜𝑛: 

𝑆𝑢𝑏𝐵𝑦𝑡𝑒𝑠(𝑆) 

𝑆ℎ𝑖𝑓𝑡𝑅𝑜𝑤𝑠(𝑆) 

𝐴𝑑𝑑𝑅𝑜𝑢𝑛𝑑𝐾𝑒𝑦(𝑆, 𝐾𝑁𝑟) 

 

Step 3: Transmission of Encrypted RFID Data 

• The encrypted RFID data C_RFID is transmitted wirelessly to the RFID reader. 

Step 4: Reception of Encrypted RFID Data 

• The RFID reader receives the encrypted RFID data C_RFID. 

Step 5: Decryption of Encrypted RFID Data 

• Let K_Reader represent the secret key stored in the RFID reader. 

• The RFID reader decrypts the received ciphertext C_RFID using the key K_Reader, yielding 

the decrypted unique identifier UID_Decrypted. 

𝑈𝐼𝐷_𝐷𝑒𝑐𝑟𝑦𝑝𝑡𝑒𝑑 =  𝐴𝐸𝑆^ − 1(𝐾_𝑅𝑒𝑎𝑑𝑒𝑟, 𝐶_𝑅𝐹𝐼𝐷) 

Step 6: Verification of Unique Identifier 



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• The decrypted unique identifier UID_Decrypted is compared with the stored unique identifier 

in the authentication database. 

• If UID_Decrypted matches the stored unique identifier, the RFID authentication is successful. 

Otherwise, it is rejected. 

 

5. RESULT & DISCUSSION 

The implementation of the Smart Parking System for societies yielded notable improvements in 

convenience, efficiency, and security. Through the utilization of RFID cards and a mobile app-based 

entry system, residents experienced streamlined access to parking facilities, while real-time 

occupancy information facilitated efficient space utilization. The figure 5 Illustrates physical 

components like sensors, NodeMCU, LCD, servo motors, and RFID scanner integrated for efficient 

parking management. 

 

 
Fig 5: Hardware Model View of  IoT Enabled Smart Parking System 

This resulted in reduced search times for vacant slots and minimized congestion within the society. 

Moreover, the integration of RFID-based authentication and controlled gate opening mechanisms 

enhanced security, ensuring authorized access and transparency in guest parking management.  

 
Fig.6:-User Login Page 

Overall, the system demonstrated feasibility, scalability, and a positive impact on residents' parking 

experience. While the Smart Parking System showed promising results, several challenges and 



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considerations emerged for further discussion. These include addressing cost management issues, 

ensuring robustness against technology dependencies, and promoting user adoption.  

 

 
Fig.7:-User Registration Page 

Figure 6 shown the page where users log in that allows registered users to access the smart parking 

system through a safe interface. It asks users to enter their passwords, which makes sure they are 

who they say they are, improves security, and makes the user experience more personal. Figure 7 

shown, the User Registration Page lets new users make accounts and use smart parking services. It 

gets important information from users, checks their entries, and saves data safely. Registration is an 

important step in making parking options more specific and in keeping the system honest and 

accountable. 

 

 
Fig.8:-Live Parking Status. 

Ethical considerations such as data privacy, transparency, and social equity also warrant attention to 

maintain residents' trust and uphold fair practices. Additionally, potential enhancements like advanced 

features and sustainability measures can further improve the system's effectiveness and contribute to 

its long-term success. Discussions beyond technology, including collaboration with society 

management and ongoing evaluation processes, are crucial for ensuring the system remains relevant 

and beneficial to residents over time.For the integration of IoT in the project, we have developed an 

App. After Registration is done, the user can Login to the Application by entering the Username and 

Password. The status of the parking slot can be checked through the App, illustrate in figure 8. 

 

 



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Table 2: Comparison of Implementation of IoT-Enabled Smart Secure Parking System with Based model 

Evaluation Parameter Baseline Value Result Value 

Parking Space Utilization 70% 90% 

Search Time Reduction 10 min 3 min 

System Accuracy 85% 98% 

User Satisfaction 3 4.5 

Energy Consumption 100 kWh 70 kWh 

Compared to the base model, the comparison table shows the big changes that were made by using 

the IoT-enabled smart safe parking system. First, the number of parking spots used has gone up from 

70% to 90%, which means that the spaces are being used more efficiently.  

 
Fig. 9: Differences between the baseline and result values across all evaluation parameters 

Search time reduction has gotten a lot better, illustrate in fig. 9. The usual time it takes to find a 

parking spot has gone down from 10 minutes to just 3 minutes, which is better for users and better 

for traffic. The accuracy of the system has greatly improved, going from 85% to 98%. This means 

that real-time reports on the state of parking spots are more reliable and accurate. Also, user approval 

has gone up from 3 to 4.5, which shows that users are happier with the smart parking system's 

features and the experience they have with it. Also, the amount of energy used has gone down from 

100 kWh to 70 kWh, which shows that the system is more sustainable and efficient. In general, these 

data show that using the IoT-enabled smart safe parking system can help improve user happiness and 

make parking management more efficient, shown in fig10. 



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Fig. 10: Comparison across multiple variables simultaneously 

6. CONCLUSION  

This project proposes a smart parking system for societies, combining the power of IoT technology 

and a user-friendly mobile app to address the growing challenge of parking scarcity and inefficiency. 

By automating access control, providing real-time occupancy information, and facilitating guest 

parking management, this system aims to significantly improve the parking experience for residents. 

Enhanced Convenience: Residents gain seamless access through RFID cards and mobile app control, 

eliminating manual gate operations and unnecessary searching for vacant slots. Optimized Space 

Utilization: Real-time information guides users to available spaces, reducing congestion and ensuring 

efficient use of parking infrastructure. Secure RFID authentication and controlled access gates 

prevent unauthorized parking, enhancing overall security within the society. Transparent Guest 

Management: Residents can initiate and manage guest parking requests through the app, promoting 

transparency and control over guest access .Data-Driven Insights: Data collected from the system can 

be analyzed to understand parking trends, identify optimization opportunities, and inform future 

planning decisions. Further refine the system architecture to seamlessly accommodate larger 

societies and diverse parking needs. Integrate features like parking prediction, real-time navigation 

within the society, and payment options for guest parking.Sustainability. Explore the use of 

renewable energy sources to power system components and consider integrating carpooling or EV 

charging options. 

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