14-##_Source Texts-454-1-18-20190814


Journal of Software Engineering Research and Development, 2019, 6:3, doi: 10.5753/jserd.2019.14  

  This work is licensed under a Creative Commons Attribution 4.0 International License.  

 

Towards a more in-depth understanding of the IoT 

Paradigm and its challenges 
Rebeca Campos Motta  [ Universidade Federal do Rio de Janeiro e LAMIH CNRS UMR 8201 | rmotta@cos.ufrj.br] 

Valéria Martins da Silva [Universidade Federal do Rio de Janeiro | vsilva@cos.ufrj.br ] 

Guilherme Horta Travassos  [Universidade Federal do Rio de Janeiro | ght@cos.ufrj.br ] 

 

Abstract 

The Internet of Things (IoT) is a new technological paradigm that brings together the physical and virtual 

worlds to provide software systems everywhere through daily life objects. The IoT can transform how we interact 

with the environment surrounding us, leading to a significant multidisciplinary technological shift. However, since 

it is a new field of research and development, there is a lack of consensus and understanding of its concepts and 

features, as we observed when engineering some software systems in the field. Therefore, we performed 

investigations to characterize IoT regarding its definition, characteristics, and applications, organizing the area and 

revealing its challenges, and research opportunities, focusing on software engineering for the IoT. A structured 

literature review of secondary studies supported the answering of three research questions: What is “Internet of 

Things”? Which characteristics can define an IoT domain? Which are the areas of IoT application? The structured 

literature review leads to 15 subsequent studies from which we recovered 34 definitions - discussed in the light of 

the technical evolution - 29 characteristics and several IoT application areas. Furthermore, the results include an 

IoT characterization based on identification, sensing, and actuation capabilities, besides a discussion of the relation 

between IoT and Cyber-Physical Systems (CPS), regarding other research areas and terms often associated with 

IoT aiming at to bring clarification to the field. In this work, we offer an essential overview of the IoT state-of-the-

art and a characterization, presenting issues that should be addressed to contribute to its strengthening and 

establishment. 

Keywords: Internet of things, Systems Engineering, Evidence-Based Software Engineering 

 

1  Introduction 

The Internet of Things (IoT) has emerged as a new 

paradigm where the software systems are no longer limited 

to computers but to a great variety of different connected 

objects, or specific users’ goals and closed environments. 

The interaction between humans and the cyber-physical 

world is changing since software can be deployed 

everywhere and in everything, such as cars, smartphones, 

clothes and in different environments (Atzori, Iera, and 

Morabito, 2010; Kraijak and Tuwanut, 2016; Datta et al., 

2017; Wortmann, Combemale and Barais, 2017; Cicirelli et 

al., 2018), characterizing the IoT domain and vision. It 

enables a pervasive interaction between connected things 

enhanced with identification, sensing, actuation, and 

processing capabilities, which enable them to interact with 

the environment. 

Together with the benefits proposed by the IoT paradigm, 

new challenges also arise. The constant evolution of the 

technology, application heterogeneity and diversity of 

devices, and other particularities such as a lack of division 

of roles, scale, and different lifecycle phases differentiate 

IoT applications from traditional ones (Patel and Cassou, 

2015). It can challenge the current software technologies to 

develop IoT applications and to consolidate such paradigm 

(Skiba, 2013; Zambonelli, 2016; Larrucea et al., 2017). One 

of the recurrent difficulties regards the natural IoT 

multidisciplinary and novelty. Since IoT it is a modern 

paradigm, some fundamental points are still under 

discussion and involve converging topics of different 

research streams (Motta, de Oliveira, and Travassos, 2018). 

In our previous research regarding ubiquitous (Spínola, 

Pinto and Travassos, 2008; Spínola and Travassos, 2012) 

and context-aware software systems (Matalonga, Rodrigues  

 

and Travassos, 2017; Santos et al., 2017), we have identified 

some gaps and the need for software technologies that can 

also be observed in the IoT domain. However, as a constant 

challenge in this area, the lack of a unified IoT perception 

together with some experiences on engineering IoT software 

systems motivate this research as a starting point for further 

investigation and development activities at our research 

group. In this scenario, we performed a structured literature 

review of secondary studies on IoT to understand the 

“Internet of Things” concept, as well as its characteristics 

and the application domains making use of it. Therefore, this 

research aims to characterize the Internet of Things 

paradigm, considering the scenario of invisible and 

pervasive complex systems that support daily activities in 

the world.  

This review intends to answer the following questions: 

What is the “Internet of Things”? Which characteristics can 

define an IoT domain? Which are the areas of IoT 

application? The primary goal of this review is to strengthen 

the IoT paradigm understanding, characterizing it based on 

its properties, and identifying the current IoT applications 

(the domains that are currently getting some benefit from the 

IoT domain) under the perspective of engineering IoT 

software systems. We made this decision since the 

advancement of technologies makes society highly 

dependent on engineered-based software systems. We aim 

to discuss the software engineering scenario in the IoT 

paradigm, being the results of this review the first step of 

research towards the understanding of engineering IoT 

software systems. Therefore, the intention is to promote a 

high-level discussion on identified IoT paradigm 

characteristics and give an overview of the area, aiming to 

promote a better perception of current development needs 

and opportunities in the area. 



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

Important works from the literature review supported our 

discussions and the answers to the research questions. There 

are many definitions for IoT available in the technical 

literature, and even though they are different, they share 

similar points. From this diverse content, it was necessary 

an understanding from our side of the IoT concept and what 

the “things” represent in the IoT context. Besides the IoT 

characterization, we discuss the relation among IoT, CPS 

and other related terms to highlight some points that lead to 

consider some areas as building blocks for IoT or, on the 

other hand, dependent on its evolution. 

The remainder of the paper is structured as follows. In the 

next section, the methodology is introduced, and we explain 

how it was applied in this study. Then, in Section 3, the 

results of the literature review are presented. These results 

are then further discussed in Section 4, together with the 

validity threats. The main conclusions from the paper are 

summarized in Section 5. 

2 Research Methodology 

The purpose of this literature review is to contribute to a 

more in-depth understanding of the Internet of Things and 

its challenges, identifying its definitions, characteristics and 

the current areas of use.  

2.1 Review Planning 

Before undertaking any literature review, it is essential to 

observe its necessity (Budgen and Brereton, 2006). 

Therefore, we started with an ad-hoc search looking for any 

existent secondary studies on IoT. Considering the IoT 

paradigm as a new motivating area for investigation, we 

decided to review the technical literature more 

systematically, adopting existing practices to compose our 

study plan. In our perspective, “secondary studies” are the 

studies which survey primary studies to present a bigger 

picture of a domain, the IoT in this case. All secondary 

studies that meet the selection criteria should be included; 

even it does not mention its research protocol.  

The research protocol followed the recommendations 

proposed by (Budgen and Brereton, 2006; de Almeida 

Biolchini et al., 2007) and, for the sake of space, have some 

of its details presented below. The research goal is GQM-

based (Basili, Caldeira and Rombach, 1994) defined as 

follows: To analyze the Internet of Things with the purpose 

of characterizing regarding its definitions, characteristics 

and application areas from the point of view of software 

engineering researchers in the context of knowledge 

previously organized and presented in secondary studies 

regarding IoT available in the technical literature. From this 

goal, we defined the research questions (RQ):  

(RQ1) What is the “Internet of Things”? 

(RQ2) Which characteristics can define an IoT domain?  

(RQ3) Which are the areas of IoT application? 

With this goal, the secondary studies were searched 

according to the following information:  

 Search Strategy - The search strategy used Scopus 
1combined with snowballing procedures. The Scopus 

was chosen as the search engine since it indexes several 

 
1 https://www.scopus.com/ 

databases of peer-reviewed sources, covering 

repositories such as IEEE Xplorer 2for example, and 

favor the repeatability of the search results (Matalonga, 

Rodrigues and Travassos, 2017; Santos et al., 2017). In 

turn, backward and forward snowballing refers to using 

the reference list of cited papers or the citations to a 

paper to identify additional sources of data, 

complementing and extending the initial set of papers 

(Wohlin, 2014). Also, as far as our experience shows, 

the strategy of using Scopus with snowballing 

procedures mitigates an eventual lack of content, 

avoids duplicated filtering work, and provides a 

representative set of papers to a characterization study 

such as this one (Motta, Oliveira, and Travassos 2016; 

Motta, Oliveira, and Travassos 2018). 

 Search String - Since the review focus is to retrieve 

information based on secondary studies, it was: 

TITLE-ABS-KEY (( "*systematic literature review"  OR  

"systematic* review*"  OR  "mapping study"  OR  

"systematic mapping"  OR  "structured review"  OR  

"secondary study"  OR  "literature survey"  OR  "survey of 

technologies"  OR  "driver technologies"  OR  "review of 

survey*"  OR  "technolog* review*"  OR  "state of 

research")  AND  ( "internet of things" OR "iot")). 

 Selection Criteria - Works presented as articles shall be 

available on the web, retrieved from the search engine 

and written in English. As the selection criteria we 

have: 

 Inclusion Criteria 

o Provide an IoT definition AND  

o Provide IoT properties  OR 

o Provide IoT application areas  

 Exclusion Criteria:  

o Duplicate publication/self-plagiarism OR 

o Register of proceedings 

 Selection Procedure - Read the title and abstract of each 

retrieved study and evaluate it according to the 

inclusion and exclusion criteria. Two distinct readers 

evaluated each secondary study. The studies 

acceptance criteria happened as follows:  

o All two readers accept: The study is included.  

o One reader accepts, and one is in doubt: The 

study is included.  

o One reader accepts or is in doubt, and one 

reader excludes: The study is discussed.  

o Two readers exclude: The study is not included. 

 Data Extraction - Data extraction aims to capture 

information from the selected articles to answer the 

proposed research questions. The data extraction form 

was proposed during the review planning and used 

throughout the process. The information was extracted 

as presented in Table 1. 

2 https://ieeexplore.ieee.org 



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

2.1 Review Planning 

The review process was executed according to the 

following steps: 

 Step 1 - Ad-hoc Search. It is based on the researcher’s 

experience without providing any explicit or planned 

process in comparison to a systematic literature review. 

The primary objective of the ad-hoc search was to 

verify the need to carry out an initial literature review 

on the target topic and identifying control articles to 

guide formulating a search string for further searches. 

Two researchers performed this step to identify the 

existence of any secondary study related to IoT. The 

search perspective was established from the Software 

Engineering point-of-view for paper reading and 

analysis. Since we identified secondary studies, we 

decided to review the existent articles instead of relying 

on primary studies. From the results of this ad-hoc 

search, three articles were selected as a starting point 

for the next step since they met the selection criteria 

(Atzori, Iera, and Morabito, 2010; Bandyopadhyay and 

Sen, 2011; Li, Xu and Zhao, 2015). 

 Step 2 - Scopus search. We organized the terms of the 

search string based on synonyms and similar terms. The 

search string was adjusted to recover the three articles 

which were previously selected. The total of items 

found was 76; the search was executed at the end of 

May 2017, considering the papers available in the 

database until this date. 

 Step 3 - Title and abstract reading. The list of 76 articles 

was reviewed to remove duplicates and proceedings, 

according to the selection criteria. The remaining 

articles were later read based on title and abstract and 

reviewed by a 3rd researcher with more experience in 

the research area. 24 articles were selected for further 

reading, considering the title and abstract reading, 

following the criteria established in the research 

protocol. 

 Step 4 - Full Reading. The two researchers read the full 

text of the 24 articles (12 for each, with crosschecking), 

considering the inclusion and exclusion criteria. Seven 

of them met the criteria, being those finally selected. 

 Step 5 - Snowballing. It refers to using the reference list 

of an article or its citations to identify additional 

material (Wohlin, 2014). In this step, we performed 

Backward and Forward Snowballing Sampling, 

tracking down references in the seven articles selected 

in the previous step and their citations. The total of 

articles was divided, and each researcher was 

responsible for performing the snowballing in part of 

the articles. Nineteen articles were identified as 

candidates, and the reviewers cross-checked the articles 

to be included considering the selection criteria. This 

step resulted in the inclusion of five new articles.  

 Step 6 - Review Update. The previous five steps were 

carried out between March and May 2017. The update 

was performed on December 2018 to cover new 

publications made available between 2017 and 2018. 

We re-executed the same string in Scopus and analyzed 

the results following the criteria previously established. 

The three reviewers conducted the update repeating 

Steps 3 and 4 for the new Scopus results and the 

forward snowballing (Step 5) for the whole set. This 

step resulted in the inclusion of three new articles.  

The review steps resulted in 15 articles, composing the 

final set: (Atzori, Iera and Morabito, 2010; Bandyopadhyay 

and Sen, 2011; Miorandi et al., 2012; Gubbi et al., 2013; 

Singh, Tripathi and Jara, 2014; Borgia, 2014; Whitmore, 

Agarwal and Da Xu, 2015; Li, Xu and Zhao, 2015; 

Madakam, Ramaswamy and Tripathi, 2015; Gil et al., 2016; 

Sethi and Sarangi, 2017; Trappey et al., 2017; Burhanuddin 

et al., 2017; Ray, 2018; Carcary et al., 2018). See the details 

of each step in Table 2. 

 

Table 1 Information extraction fields. 

Field Description 

Reference information Authors, title, year and venue 

Abstract Abstract 

IoT definition Verbatim, as presented in the article (Definition research-based derived or with reference) 

IoT related terms 
It is associated with other definitions (ubiquitous, context-aware, pervasive, machine-to-machine, 

and others) 

IoT application features 
Characteristics of particular traits, features, properties, attributes that make IoT what it is (that 

achieve the IoT definition/concept) 

IoT application areas The areas (and their related applications) that will benefit from the full IoT idea deployment. 

Development Strategies 

for IoT 
The used development strategies to build IoT software (requirements analysis, design, and so on). 

Type of study 
It is expected to have only secondary studies, represented by Survey, Systematic Literature 

Review, others. 

Study properties Protocol, Research Questions, search string, selection criteria. 

Challenges Open opportunities in practice or research  

Article focus Main concerns presented in the articles (architecture, security, and others) 

Things 
A list of the kind of things explicitly stated in the article (coffeemaker, refrigerator, incubator, and 

others) 
 



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

 

Table 2 Total of articles selected at each step of the review. 

Step Number of articles selected 

Step 1 - 

Step 2 76 

Step 3 24 

Step 4 7 

Step 5 5 

Step 6 3 

Final set 15 

3 Results 

The dataset contains papers from 2010 to 2018. It is 

possible to observe a growing interest in the area over the 

years. The results show that most of the available 

publications on technical literature were from 2015 to 2018, 

considering the period of search. Since it is a topic that has 

recently gained strength, both initiatives from industry and 

research are still in the early stages. Table 3 presents the 

study types considering the classification initially presented 

by the authors. 

Table 3 Study Types 

Type Studies 

Systematic 

Literature 

Review 

(Carcary et al., 2018) 

Literature 

Review 

(Atzori, Iera and Morabito, 2010; 

Miorandi et al., 2012; Singh, Tripathi and 

Jara, 2014; Li, Xu, and Zhao, 2015; Gil et 

al., 2016; Burhanuddin et al., 2017; Sethi 

and Sarangi, 2017; Ray, 2018) 

Literature 

Survey 

(Bandyopadhyay and Sen 2011; 

Madakam, Ramaswamy, and Tripathi 2015; 

Whitmore, Agarwal, and Da Xu 2015; 

Trappey et al. 2017) 

Not defined (Gubbi et al. 2013; Borgia 2014) 

Despite being a current trend, our initial research did not 

return secondary studies conducted systematically, nor did 

they present the methodology followed, nor the research 

questions that the papers intended to answer. The papers - 

except in (Whitmore, Agarwal and Da Xu, 2015; Carcary et 

al., 2018) - do not present the research protocol or make 

explicit the study properties (research questions, search 

strings, databases, selection criteria, selected articles, 

among others). For this reason, we have not performed a 

Quality Assessment since there is no methodology related 

information to be evaluated. Therefore, not performing the 

Quality Assessment represents a threat to this study validity. 

From this result, it is possible to observe the need to provide 

research data based on sound scientific methodology. 

Despite the evolution and enthusiasm that new technology 

can provide with recent developments such as IoT, the lack 

of scientific rigor it is still one of the significant challenges 

to strengthen the basis of Software Engineering knowledge 

(de Almeida Biolchini et al., 2007). This work was 

conducted by following established guidelines and in a 

protocolled way, accounting for the strength of the evidence 

found and its replicability. The questions that this review 

seeks to answer are aligned with the objective of 

characterizing IoT and with this result we aim to contribute 

to strengthening the discussions and evolution of the area.  

From the selected papers, seven essential topics were 

addressed (Figure 1): 

 Concepts - Presenting discussions regarding the 

fundamentals, definitions, and visions behind the IoT 

paradigm; Articles (Atzori, Iera and Morabito, 2010; 

Bandyopadhyay and Sen, 2011; Miorandi et al., 2012; 

Gubbi et al., 2013; Borgia, 2014; Singh, Tripathi and 

Jara, 2014; Li, Xu and Zhao, 2015; Madakam, 

Ramaswamy and Tripathi, 2015; Gil et al., 2016; 

Trappey et al., 2017; Carcary et al., 2018). 

 Technology - Introducing enabling technologies and 

solutions to develop and deploy IoT applications. 

Articles: (Atzori, Iera and Morabito, 2010; 

Bandyopadhyay and Sen, 2011; Gubbi et al., 2013; 

Borgia, 2014; Whitmore, Agarwal and Da Xu, 2015; 

Li, Xu and Zhao, 2015; Madakam, Ramaswamy and 

Tripathi, 2015; Burhanuddin et al., 2017; Sethi and 

Sarangi, 2017; Trappey et al., 2017; Ray, 2018). 

 Applications - Describing the current state of the 

existing solutions and the applications of different 

domains as well as future possibilities to be achieved 

by using IoT. Articles: (Atzori, Iera, and Morabito 

2010; Bandyopadhyay and Sen 2011; Bandyopadhyay 

and Sen 2011; Gubbi et al. 2013; Borgia 2014; Singh, 

Tripathi, and Jara 2014; Li, Xu, and Zhao 2015; 

Madakam, Ramaswamy, and Tripathi 2015; Whitmore, 

Agarwal, and Da Xu 2015; Sethi and Sarangi 2017; 

Trappey et al. 2017). 

 Open Issues and Challenges - Presenting opportunities 

for research and development aiming to evolve IoT. 

Articles: (Atzori, Iera and Morabito, 2010; 

Bandyopadhyay and Sen, 2011; Miorandi et al., 2012; 

Gubbi et al., 2013; Borgia, 2014; Singh, Tripathi and 

Jara, 2014; Li, Xu and Zhao, 2015; Whitmore, Agarwal 

and Da Xu, 2015; Burhanuddin et al., 2017; Carcary et 

al., 2018). 

 Architecture - Discussing possible implementations of 

IoT based on different architectures proposals. Articles: 

(Bandyopadhyay and Sen, 2011; Singh, Tripathi and 

Jara, 2014; Madakam, Ramaswamy and Tripathi, 2015; 

Whitmore, Agarwal and Da Xu, 2015; Gil et al., 2016; 

Sethi and Sarangi, 2017; Trappey et al., 2017; Ray, 

2018). 

 Characteristics - Making specific general features and 

requirements of IoT. Articles: (Borgia, 2014; Gil et al., 

2016).  

 Initiatives - Research organizations, industries, 

standardization bodies, and governments that have an 

interest or put some effort into IoT. Articles: (Miorandi 

et al. 2012; Gubbi et al. 2013; Borgia 2014; Madakam, 

Ramaswamy, and Tripathi 2015).  



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

 

Figure 1 Most common topics in the Articles. 

3.1 Studies Overview 

Gil et al. (Gil et al., 2016) reviewed surveys regarding 

IoT, focusing mostly on the context-aware feature and how 

both topics are related. The main difference from our work 

is that they lack a research methodology and the discussion 

revolved around the general purpose of the selected articles 

and the context-aware IoT. Another work that contains an 

analysis of the trends and coverage of the IoT literature is 

from Whitmore et al. (Whitmore, Agarwal and Da Xu, 

2015). It presents an area overview. However, it does not 

worry about answering research questions, describing open 

questions and future directions to assist researchers. It 

differs from our work which concerns the characterization 

of IoT regarding its definition and characteristics.  

Numerous IoT definitions exist in the technical literature 

due to different visions from the research community. Some 

authors (Miorandi et al., 2012; Gubbi et al., 2013) discuss 

IoT as an overall vision, while (Atzori, Iera and Morabito, 

2010; Bandyopadhyay and Sen, 2011; Borgia, 2014; Singh, 

Tripathi and Jara, 2014) describe that IoT is realizable by 

particular visions or pillars. The conceptualization of IoT is 

the focus of ( Miorandi et al. 2012; Gubbi et al. 2013; 

Madakam, Ramaswamy, and Tripathi 2015). Other topics 

are also presented, as a taxonomy for IoT (Gubbi et al., 

2013; Sethi and Sarangi, 2017), and IoT patents (Trappey et 

al., 2017).  

The works of (Burhanuddin et al., 2017; Ray, 2018) focus 

on the critical discussion related to architectural issues and 

options to deal with the immense number of interconnected 

devices as proposed in IoT. Besides, they also describe 

fundamental requirements along with implementation 

challenges and future directions. The work of (Carcary et 

al., 2018) argues that the adoption of IoT is not yet 

widespread and examines the existing literature on key 

determinants (drivers, benefits, barriers, and challenges) 

that influence the adoption of IoT by organizations.  

It is important to highlight that from the 15 selected 

secondary studies, none covers all the topics, showing that 

the researchers have distinct perspectives and concerns. 

However, together these studies provide a wealth of 

information to our research topic.  

The application of a sound research protocol in this work 

provides an improvement over the previous ones since some 

do not make clear the performed procedures. Besides, we 

offer a research protocol that can be replicated. In this work, 

we further improve the current state because we not only 

quantitatively point out the results but provide discussions 

and answers to research questions grounded in data. We also 

would like to highlight that one can value the findings and 

discussions in this article since we are relying on secondary 

studies. In this case, several primary studies reported in 

these 15 secondary studies support with evidence.  

3.2 Answering the research questions  

We based our analysis procedure on textual analysis, 

using codes to assign concepts to a portion of data, 

identifying patterns from similarities and differences 

emergent from the data extracted. Two researchers 

conducted it, with crosschecking to achieve a consensus 

with the analysis, to decrease potential misinterpretation and 

bias. A third researcher reviewed the extractions and 

findings. This process was performed through all the data 

extracted and lead to the discussions of the research 

questions proposed, presented in the following subsections. 

3.3 RQ1: What is the “Internet of Things”? 

The 15 selected papers supported the extraction of 34 

different IoT definitions. From the analysis of these 34 

definitions, we noticed that they followed a specific pattern 

in their structure in the concern of explaining the involved 

actors, requirements and the consequences of relations 

among actors as part of a system - not necessarily presented 

in all definitions. We considered this structure not to limit 

our interpretation, but to support a more thorough IoT 

conceptual understanding and thus finding an appropriate 

and updated definition for this work. We organized some of 

the definitions found in chronological order to observe how 

the concept has evolved. 

''An intelligent infrastructure linking objects, 

information, and people through the computer networks, 

and where the RFID technology found the basis for 

realization.'' Defined in 2001 by (Brock, 2001), cited by 

(Borgia, 2014). 

In this 2001 definition, we can observe that the idea is to 

connect objects, information, and people, where both 

objects and people can be actors in the system. It makes 

clear the network necessity as a way to connect the actors, 

and the realization was limited by the RFID identification 

technology (Finkenzeller, 2010), which represents the IoT 

vision starting point. 

“Internet of Things as a paradigm in which computing 

and networking capabilities are embedded in any 

conceivable object. We use these capabilities to query the 

state of the object and to change its state if possible.” 

Defined in 2005 by (ITU, 2005), cited by (Sethi and 

Sarangi, 2017). 

This definition from 2005 does not propose the use of any 

technology, like RFID, but includes the idea of expanding 

the original capabilities of an object through technology to 

perceive changes in the object’s states; it is only possible by 

addressing objects first, turning them identifiable. Once 

achieving that, it enables things to communicate 

automatically (Dunkels and Vasseur, 2008). It can be 

considered an evolution since this kind of requirement was 

not previously discussed.  

The next definition addresses the idea: 

“A world where things can automatically communicate 

to computers and each other providing services to the 



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

benefit of the humankind.” Defined in 2008 by (Dunkels 

and Vasseur, 2008), cited by (Atzori, Iera, and Morabito, 

2010; Gil et al., 2016). 

Another definition is:  

''A dynamic global network infrastructure with self-

capabilities based on standard and interoperable 

communication protocols where physical and virtual 

''things'' have identities, physical attributes, virtual 

personalities and use intelligent interfaces, and are 

seamlessly integrated into the information network'' 

Defined by in 2009 (Gusmeroli, Sundmaeker and Bassi, 

2015), cited by (Borgia, 2014; Whitmore, Agarwal and Da 

Xu, 2015). 

In this 2009 definition, we can see that the central concept 

of communication and integration remains. It leads to an 

effort to make things identifiable (network sense, not 

physically) and the introduction of requirements such as 

interoperability and integration in a seamlessly way. This 

definition also details what are the things in IoT, as things 

being virtual or physical, that can have different 

personalities and may use different communication 

protocols. 

“The basic idea of this concept is the pervasive presence 

around us of a variety of things or objects such as Radio-

Frequency Identification (RFID) tags, sensors, actuators, 

mobile phones, etc. which, through unique addressing 

schemes, are able to interact with each other and 

cooperate with their neighbors to reach common goals.” 

Defined in 2010 by (Atzori, Iera, and Morabito, 2010), 

cited by (Miorandi et al., 2012; Gubbi et al., 2013; Singh, 

Tripathi and Jara, 2014). 

This IoT definition from 2010 is one of the most used. It 

can be considered broader regarding the “actors, relations 

among actors, requirements and what enables” structure. It 

presents the vast amount and heterogeneity of actors that can 

engage an interaction, and a requirement to achieve that 

through unique addressing schemes. In this case, new actors 

are included, and we can observe that the sensing and 

actuation are other possible behaviors that a system can 

possess, differing from initial definitions. Therefore, these 

actors can cooperate to reach some goals.  

“Interconnection of sensing and actuating devices 

providing the ability to share information across platforms 

through a unified framework, developing a common 

operating picture for enabling innovative applications. 

This is achieved by seamless large-scale sensing, data 

analytics and information representation using cutting-

edge ubiquitous sensing and cloud computing.” Defined in 

2012 by (Gubbi et al., 2013). 

Once more, sensing and actuation have essential roles in 

IoT, as presented in this definition from 2012. The vast 

amount of data collection and sharing among actors can be 

a source to compose diversified, innovative applications. It 

makes clear the multidisciplinary nature of IoT, as the 

integration of different disciplines for the accomplishment 

of successful IoT systems, as there are areas that support or 

leverages it, such as data analytics, ubiquitous and cloud 

computing. 

“Everyday objects can be equipped with identifying, 

sensing, networking and processing capabilities that will 

allow them to communicate with one another and with 

other devices and services over the Internet to achieve 

some useful objective (…). Every day “things” will be 

equipped with tracking and sensing capabilities. When this 

vision is fully actualized, “things” will also contain more 

sophisticated processing and networking capabilities that 

will enable these smart objects to understand their 

environments and interact with people.” Defined in 2015 

by (Whitmore, Agarwal and Da Xu, 2015). 

Once the everyday things can sense the environment, they 

become more aware of what is around them, which 

characterizes context-awareness. In this 2015 definition, we 

see again that the primary concern in IoT is to leverage the 

connection among different things to achieve a system 

objective. Also, the authors explain that things in the IoT 

context are those objects equipped with identifying, sensing, 

networking, and processing capabilities, whereas other 

definitions exemplify things as being the providers of such 

capabilities, that is, tags, sensors, and actuators. 

In our understanding, things exist in the physical realm, 

such as sensors, actuators and anything that is equipped with 

identification (tag reading), sensing or actuation 

capabilities, which excludes entities in the Internet domain 

(hosts, terminals, routers, among others). The things should 

also have communication, networking and processing 

functionalities varying according to the systems 

requirements. As one can notice, the capabilities of the 

things evolved over time as observed from the definitions 

presented and the examples in Figure 2.  

 

Figure 2 IoT evolution. 

As things evolved, the understanding and discussions 

should also follow the changes. In the beginning, the things 

in IoT based systems were objects attached to electronic 

tags, so these systems present the behavior of Identification. 

Subsequently, sensors and actuators composing the systems 

enabled the Sensing and Actuation behaviors respectively. 

It means that an IoT system may have Identification, 

Sensing or Actuation behaviors, or a combination of them. 

The explaining of each behavior and examples of 

applications can be seen in Figure 3 and Table 4  



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

 

Figure 3  IoT behaviors. 

When discussing the previous definitions, it was 

necessary to distinguish the meaning of “identification” 

referred to objects. The reason is that an object can be 

identifiable in the sense of connectivity (e.g., throw IP 

addresses) or in the sense of physical identification when 

objects are tagged with electronic tags containing specific 

information, making it possible to identify objects through 

tag readers. Further, it is also relevant to elucidate the 

meaning of “actuation” as it may bring diverse 

interpretations. When focusing on the IoT context, the 

adequate meaning for “actuation” is precisely the one 

presented in Table 4. It is divergent from actions represented 

by methods in the object-oriented paradigm, and it is not 

related to objects’ processing capabilities mentioned in the 

IoT definition discussed previously. Actuation is 

exclusively related to the possibility of virtual intervening 

in the real world by mechanical means.   

It is important to note this distinction in IoT systems due 

to their capabilities since it is possible to have different 

compositions of systems. In an industrial plant, for example, 

identification tags are attached to products and provide real-

time location and status. Dashboards with the data recovered 

from products and machines (from a sensing activity) keep 

managers updated along the production line and the 

company are now able to monitor and control production 

almost automatically (actuation), including processing 

capabilities. It is a real-case scenario already deployed 

where the three behaviors and benefits of IoT can be seen, 

such as providing more process visibility, more accurate 

work and improving production effectiveness (Cisco, 2014). 

 

It is interesting to structure the characteristics and 

applications retrieved in this review within these three 

behaviors because IoT does not necessarily have to present 

all of them, but only one or a combination of them. It can 

clarify and delimitate IoT solutions contributing as a guide 

for their applications engineering. To answer RQ1 from the 

review results, IoT can be defined as a paradigm that allows 

composing systems from uniquely addressable objects 

(things) equipped with identifying, sensing or actuation 

behaviors and processing capabilities that can communicate 

and cooperate to reach a goal.  

3.4 RQ2: Which characteristics can define an 

IoT domain? 

The 15 papers provided 263 excerpts, which were coded 

following the principles of open coding, as described in the 

Grounded Theory (Strauss and Corbin, 1990), from what we 

identified 29 characteristics (Table 5). One point of 

discussion is that the authors do not define all the 

Table 4  IoT Behaviors. 

Behavior Description Example 

Identification 

The primary function is to identify 

things, by labeling and enabling 

them to have an identity, then 

recover (through reading), and 

broadcast information related to 

the thing and its state. 

Identifying patients with electronic tags (RFID) to be detected 

throughout hospitals using receivers (readers) placed in departments 

to accelerate the identification of empty beds (Kannry et al., 2007). 

Another example is the application of short-range identification 

technology for drug interaction and drug-allergy detection 

(Alabdulhafith, Sampangi, and Sampalli, 2013). It operates by 

identifying patients (NFC tags integrated into their wristband) and 

drugs (NFC tags integrated), each tag holding a unique ID. Nurses read 

the patient’s and drug’s NFC tag by using the smartphone’s NFC 

reader. Finally, the server verifies whether the patient is allergic to the 

drug or if there might be a potential interaction.  

Sensing 

The primary function is to sense 

environment information, requir-

ing information aggregation, data 

processing, and transmission. 

Enables awareness, thus acting as 

a bridge between the physical and 

digital world. 

 

To illustrate the capability of the sensor in the real world, one 

interesting application is from the geophysics area. Sensors have been 

deployed for long-distance volcanic monitoring, such as microphones 

and seismometers, collecting seismic and acoustic data on volcanic 

activity (Werner-Allen et al., 2006). 

Actuation 

Mechanical interventions in the 

real world according to decisions 

based on aggregated data or even 

upon actors’ right trigger; relay on 

responses to the collected 

information to perform actions in 

the physical world and change the 

object state. 

An example is the control of things, robots or even animals in the real 

world as in (Wark et al., 2007), where actuators are used in an attempt 

to prevent fighting between bulls in on-farm breeding paddocks by 

autonomously triggering stimuli such as audio warning signals or mild 

electrical when one bull approaches another. 



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

characteristics presented in the articles or referred to the 

original work defining them Table 6.  

Table 5 IoT Characteristics. 

Characteristics # 

All Characteristics Identified 29 

Characteristics not defined 20 

Characteristics defined 9 

 

 

The lack of definitions hinders the research and 

understanding of the area since we cannot know the feature´s 

meaning or what the authors meant by that. Although some 

characteristics such as Interoperability and Scalability are 

well defined, it is essential to establish a common 

understanding of the characteristics since they inspire 

different concepts when contextualized to distinct domains. 

Table 6 Characteristics not defined. 

Characteristic Cited by Reference 

Accuracy (Borgia, 2014; Burhanuddin et al., 2017) - 

Adaptability 

(Atzori, Iera, and Morabito 2010; Miorandi et al. 2012; 

Gubbi et al. 2013; Borgia 2014; Li, Xu, and Zhao 2015; 

Ray, 2018) 

(Nami and Sharifi 2007; Sampigethaya, 

Hackmann, et al. 2008; Poovendran, and 

Bushnell 2008; Lee and Sokolsky 2010; Azimi 

et al. 2011; Barro-Torres et al. 2012; Hur and 

Kang 2012) 

Availability 

(Atzori, Iera and Morabito, 2010; Bandyopadhyay and Sen, 

2011; Gubbi et al., 2013; Li, Xu and Zhao, 2015; 

Madakam, Ramaswamy and Tripathi, 2015) 

(Gluhak et al., 2011) 

Connectivity 

(Atzori, Iera, and Morabito 2010; Bandyopadhyay and Sen 

2011; Gubbi et al. 2013; Whitmore, Agarwal, and Da Xu 

2015; Gil et al. 2016; Burhanuddin et al., 2017; Ray, 2018; 

Carcary et al., 2018) 

(Weiser et al. 1999; INFSO D.4 2008; Conti 

2006; Dunkels and Vasseur 2008; Vermesan et 

al. 2009) 

Efficiency 

(Atzori, Iera, and Morabito 2010; Bandyopadhyay and Sen 

2011; Miorandi et al. 2012; Gubbi et al. 2013; Borgia 2014; 

Li, Xu, and Zhao 2015; Madakam, Ramaswamy, and 

Tripathi 2015; Sethi and Sarangi 2017; Trappey et al. 2017; 

Burhanuddin et al., 2017) 

( Hackmann et al. 2008; Sampigethaya, 

Poovendran, and Bushnell 2008; Lee and 

Sokolsky 2010; Azimi et al. 2011; Hur and 

Kang 2012; Barro-Torres et al. 2012) 

Extensibility (Bandyopadhyay and Sen, 2011; Li, Xu and Zhao, 2015) - 

Flexibility (Li, Xu, and Zhao 2015; Sethi and Sarangi 2017) - 

Manageability (Bandyopadhyay and Sen, 2011; Borgia, 2014) - 

Modularity (Bandyopadhyay and Sen, 2011) - 

Performance (Gubbi et al., 2013; Li, Xu and Zhao, 2015) - 

Privacy 

(Atzori, Iera, and Morabito 2010; Bandyopadhyay and Sen 

2011; Miorandi et al. 2012; Gubbi et al. 2013; Borgia 2014; 

Li, Xu, and Zhao 2015; Sethi and Sarangi 2017; Whitmore, 

Agarwal, and Da Xu 2015) 

(Xianrong Zheng et al., 2014a) 

Reliability 

(Atzori, Iera, and Morabito 2010; Bandyopadhyay and Sen 

2011; Miorandi et al. 2012; Gubbi et al. 2013; Borgia 2014; 

Sethi and Sarangi 2017) 

( Koren and Krishna 2007; Hackmann et al. 

2008; Hackmann et al. 2008; Lee and Sokolsky 

2010; Azimi et al. 2011; Hur and Kang 2012; 

Barro-Torres et al. 2012) 

Robustness (Atzori, Iera and Morabito, 2010; Miorandi et al., 2012) (Koren and Krishna, 2007) 

Scalability 

(Atzori, Iera, and Morabito 2010; Bandyopadhyay and Sen 

2011; Miorandi et al. 2012; Gubbi et al. 2013; Borgia 2014; 

Li, Xu, and Zhao 2015; Madakam, Ramaswamy, and 

Tripathi 2015; Sethi and Sarangi 2017; Burhanuddin et al., 

2017) 

(Gluhak et al., 2011) 

Smartness (Li, Xu and Zhao, 2015; Ray, 2018) - 

Sustainability (Borgia, 2014) - 

Traceability (Atzori, Iera and Morabito, 2010) - 

Trust 

(Atzori, Iera, and Morabito 2010; Bandyopadhyay and Sen 

2011; Borgia 2014; Li, Xu, and Zhao 2015; Sethi and 

Sarangi 2017) 

- 

Ubiquity (Carcary et al., 2018) - 

Visibility (Atzori, Iera and Morabito, 2010) - 
 



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

For instance, “Efficiency” is open to many interpretations 

even the IoT domain is on the focus, which can be related to 

object’s data collection efficiency, energy-efficiency, 

security-efficiency, information processing efficiency as 

well as service adaptability-efficiency. It makes it 

challenging to characterize IoT and to develop more suitable 

solutions that meet all the desired characteristics, since they 

were not defined, only listed. For the same reason, it is not 

possible to infer that the authors are discussing the same 

Table 7 Defined characteristics. 

Characteristic Cited by Reference 

Addressability: The ability to 

distinguish objects using unique IDs. 

 

(Atzori, Iera, and Morabito 2010; 

Bandyopadhyay and Sen 2011; Miorandi et al. 

2012; Borgia 2014) 

- 

Unique ID: It is necessary for 

unique identification for every 

physical object. Once the object is 

identified, it is possible to enhance it 

with personalities and other 

information and enable the control 

over it 

 

(Atzori, Iera, and Morabito 2010; 

Bandyopadhyay and Sen 2011; Miorandi et al. 

2012; Gubbi et al. 2013; Borgia 2014; Li, Xu, 

and Zhao 2015; Burhanuddin et al., 2017; Ray, 

2018) 

(Atzori, Iera, and Morabito 2010; 

Finkenzeller 2010; Gubbi et al. 

2013) 

Object Autonomy: Smart objects 

can have individual autonomy, not 

needing direct human interaction to 

perform established actions, while 

reacting or being influenced by 

real/physical world events. 

 

(Atzori, Iera and Morabito, 2010; Gubbi et al., 

2013; Madakam, Ramaswamy and Tripathi, 

2015) 

- 

Mobility: Object availability of 

across different locations. 

 

(Atzori, Iera and Morabito, 2010; 

Bandyopadhyay and Sen, 2011; Borgia, 2014; 

Sethi and Sarangi, 2017) 

(Akyildiz, Jiang Xie and Mohanty, 

2004; Sharma, Gusain and Kumar, 

2013) 

Autonomy: Refers to systems not 

needing direct human intervention to 

perform established actions such as 

data capture, autonomous behavior, 

and reaction. 

 

(Atzori, Iera, and Morabito 2010; Miorandi et al. 

2012; Gubbi et al. 2013; Borgia 2014; Li, Xu, 

and Zhao 2015; Burhanuddin et al., 2017; Ray, 

2018; Carcary et al., 2018) 

(Chlamtac, Conti, and Liu 2003; 

Nami and Sharifi 2007; Gusmeroli, 

Sundmaeker, and Bassi 2015) 

Context-awareness: The use of 

context to provide task-relevant 

information and/or services to a user. 

 

(Atzori, Iera, and Morabito 2010; Miorandi et al. 

2012; Gubbi et al. 2013; Borgia 2014; 

Whitmore, Agarwal, and Da Xu 2015; Sethi and 

Sarangi 2017; Ray, 2018) 

( Abowd et al. 1999; Schmidt and 

van Laerhoven 2001; Nami and 

Sharifi 2007; O’Reilly and Pahlka 

2009; Perera et al. 2014) 

Heterogeneity: Several services 

taking part in the system, which 

present very different capabilities 

from the computational and 

communication standpoints. 

 

(Atzori, Iera, and Morabito 2010; 

Bandyopadhyay and Sen 2011; Miorandi et al. 

2012; Gubbi et al. 2013; Borgia 2014; Li, Xu, 

and Zhao 2015; Burhanuddin et al., 2017; 

Carcary et al., 2018) 

(INFSO D.4 2008; Gluhak et al. 

2011; Nuzzo and Sangiovanni-

Vincentelli 2014) 

Interoperability: Interoperability is 

of three types: Network 

interoperability that deals with 

communication protocols. Syntactic 

interoperability ensures conversion 

of different formats and structures. 

Semantic interoperability deals with 

abstracting the meaning of data 

within a domain. 

(Atzori, Iera, and Morabito 2010; 

Bandyopadhyay and Sen 2011; Miorandi et al. 

2012; Gubbi et al. 2013; Borgia 2014; Li, Xu, 

and Zhao 2015; Madakam, Ramaswamy, and 

Tripathi 2015; Sethi and Sarangi 2017; 

Burhanuddin et al., 2017; Ray, 2018) 

(Panetto and Cecil 2013; Jardim-

Goncalves et al. 2013; Chengen 

Wang, Zhuming Bi, and Li Da Xu 

2014; Borgia 2014) 

Security: To ensure the security of 

data, services and entire IoT system, 

a series of properties, such as 

confidentiality, integrity, 

authentication, authorization, non-

repudiation, availability, and privacy, 

must be guaranteed. 

(Atzori, Iera, and Morabito 2010; 

Bandyopadhyay and Sen 2011; Miorandi et al. 

2012; Gubbi et al. 2013; Borgia 2014; Li, Xu, 

and Zhao 2015; Madakam, Ramaswamy, and 

Tripathi 2015; Whitmore, Agarwal, and Da Xu 

2015; Sethi and Sarangi 2017; Burhanuddin et 

al., 2017) 

(Sampigethaya, Poovendran, and 

Bushnell 2008; Lee and Sokolsky 

2010; Andreini et al. 2010; Andreini 

et al. 2011; Azimi et al. 2011; 

Barro-Torres et al. 2012; Hur and 

Kang 2012; Cirani, Ferrari, and 

Veltri 2013; Xianrong Zheng et al. 

2014b; Chasaki and Mansour 2015) 
 



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

issues, such as efficiency for instance, which from the 

sources can be regarding cost, size, resources or energy. 

Even with this lack of definition, the characteristics pointed 

out in Table 5 are relevant for the characterization scenario 

of IoT systems. In Table 6, we retrieve the characteristics 

pointed out by the authors (Cited by) and the original 

references used by them (Reference) some references may 

have been used by more than one author and null (-) in case 

of no reference. This distinction is because we can value 

more the characteristics referenced by others since it is 

possible to have more sources to strengthen the results. 

To continue with our research, we consider only the 

characteristics that made explicit their definitions (Table 7) 

These definitions came from our original material 

interpretation and compilation of the references cited. From 

the characteristics presented in Table 7, we can observe that 

some of them are fundamental to an application in order to 

fulfill our IoT definition: “a paradigm that allows 

composing systems from uniquely addressable objects 

equipped with identifying, sensing or actuation behaviors 

and processing capabilities that are able to communicate and 

cooperate to reach a goal”. Addressability, Unique ID, 

Heterogeneity, Interoperability, Mobility, and Security are 

the essential characteristics necessary for an application to 

follow the IoT paradigm. From this primary setting, an IoT-

based software system can be engineered with 

identification, sensing and/or actuation capabilities. Each 

one of them requires new characteristics. For instance, 

Context-awareness is required to enable sensing behavior, 

and Autonomy is needed in actuation behavior. 

Table 7 represents an initial set of IoT characteristics as 

defined in the technical literature. We wish to perform more 

extensive research for the characterization of the three 

behaviors since new characteristics specific to each one of 

the IoT applications may also be required. Having a clearer 

and well-defined set of characteristics can aid the 

development of applications with higher quality and support 

to quality assurance and assessment. 

3.5 RQ3: Which are the areas of IoT 

application? 

Several application domains will leverage the Internet of 

Things paradigm advantages. All the application domains 

are only examples of areas that benefit from IoT or are 

supposed to do it in the future. As declared in Whitmore et 

al. “the domain of the application areas for the IoT is limited 

only by imagination at this point” (Whitmore, Agarwal and 

Da Xu, 2015). 

Despite the application scenarios were described in 

different levels of detail, we tried to categorize some of them 

into the tree behaviors (Table 5) as presented in Table 8. 

Atzori et al. (Atzori, Iera, and Morabito, 2010)describe 

five domains: (A) Transportation and logistics, (B) 

Healthcare, (C) Smart environment (home, office, plant), 

(D) Personal/social and (E) Futuristic domain (whose 

implementation of such applications is still too 

complicated). Gubbi et al. (Gubbi et al., 2013) describe (A) 

Personal and Home, (B) Enterprise, (C) Utilities, and (D) 

Mobile domain. Also, there is a classification of the 

applications for Consumer (Home, Lifestyle, Healthcare, 

Transport) and Business (manufacturing, retail, energy, 

transportation, agriculture, and others) (Trappey et al., 

2017). Those domain categorizations can be a subpart of a 

categorization, which grouped the applications in three 

major domains (Borgia, 2014): (A) Industrial domain, (B) 

Smart city domain, and (C) Health well-being domain. They 

are not isolated from each other, but there is a partial 

overlapping since some applications are shared across the 

contexts. For example, tracking of products can be a demand 

for both Industrial and Health well-being domains. 

Table 8 Application type. 

Behaviors Application type 

Identification 

Touristic maps equipped with tags that allow 

NFC-equipped phones to browse it and 

automatically call web services, materials 

tracking to prevent left-ins during surgery 

(Atzori, Iera, and Morabito, 2010); patient 

triage, resource management and 

distribution (Gubbi et al., 2013); medical 

equipment tracking, secure access indoor 

environment management, personnel 

tracking, bike/car/van sharing, mobile 

tickets, luggage management, animal 

tracking, fast payment, warehouse 

management and inventory, identification of 

materials and goods (Borgia, 2014); 

verifying the authenticity of aircraft, storing 

health records (Bandyopadhyay and Sen, 

2011). 

Sensing 

Patient monitoring, remote personnel 

monitoring (health, location), sensors built 

into building infrastructure to guide first 

responders in emergencies or disaster 

scenarios or sensors built into infrastructure 

to monitor structural fatigue and other 

maintenance, sensing of water quality, 

leakage, usage and distribution, air pollution 

and noise monitoring, support to diagnoses, 

video/radar/satellite surveillance, road 

condition monitoring, product deterioration 

(Borgia, 2014); monitoring chronic disease 

using wearable vital signs sensors in body 

sensors (Bandyopadhyay and Sen, 2011). 

Actuation 

Room lighting changing, alarm systems, 

remote switching off electrical equipment 

(Atzori, Iera, and Morabito, 2010), 

temperature and humidity control (Gubbi et 

al., 2013), irrigation control (Borgia, 2014), 

muscle stimuli for paraplegic individuals 

(Bandyopadhyay and Sen, 2011). 

Hybrid 

Buildings adjusting locally to conditions 

while also taking into account outdoor 

conditions, Robot taxis that respond to real-

time traffic movements of the city, and are 

calibrated to reduce congestion at 

bottlenecks in the city and to service pick-up 

areas that are most frequently used (Atzori, 

Iera and Morabito, 2010), water waste 

management (Gubbi et al., 2013), parking 

system, traffic management (Borgia, 2014). 



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

4 Discussion 

4.1 The things in IoT  

Alongside the application areas, we also extracted the 

things, as we are interested in recovering what natural 

objects are currently in use under the IoT paradigm. In many 

cases, the authors listed usage possibilities and existing 

solutions based on IoT. Forty-one different things were 

extracted, and Figure 4 shows the ten most cited ones.  

 

Figure 4 Most common things in IoT. 

These are everyday objects enhanced with identification, 

sensing and actuation capabilities. For example, sensors 

attached to vehicles can collect information about the roads 

(e.g., about traffic density or surface conditions) reporting 

back to the city center and, from thing-thing interaction, a 

vehicle can communicate to another enabling smart parking 

and faster communication of problems in traffic.  

Extracting information on things from already deployed 

IoT applications has helped our research group to realize the 

innovative potential of this paradigm better. Also, the results 

of the real use of things and the examples of applications 

(such as those described in Table 8) might be a contribution 

- for practitioners working on innovative problem-solving 

projects - as a source of possibilities for stimulating 

thinking, creativity and to expand initial ideas. The three 

well-established behaviors (identification, sensing, and 

actuation) can support different usage scenarios varying 

according to the kind of objects used, data to be collected, 

business requirements and users’ need. For instance, a door 

lock with the “acting” behavior can open/close different sort 

of doors in different scenarios according to rules, e.g., from 

authentication by electronic tag reading, eyes or fingers 

scanning, humans/animals/robots proximity sensing and 

many other possibilities. 

Even though an IoT solution is taken as a massive amount 

of various connected objects of our everyday life, the three 

behaviors highlighted in this work are expressly the basis 

among IoT objects. Identifying and elucidating this 

common property is another contribution for practitioners, 

which can consider these three behaviors and issues 

concerned with them when idealizing, engineering and 

developing IoT-based systems. 

4.2 IoT Related Terms 

Internet of Things sometimes sounds like a buzzword, so 

some terms seem to be synonyms or even “aliases” 

(Madakam, Ramaswamy and Tripathi, 2015). However not 

every term can be used interchangeably for it. From the 

analysis and interpretation, we categorize the related terms 

as presented in Table 9. All the data extracted, and other 

details can be found in the research protocol 

(https://goo.gl/cTyzuT). 

 Related Technology - Technologies related to IoT 

supporting its development. 

 Related Areas - Other research areas that are frequently 

associated with IoT because they share some 

similarities or are considered IoT drivers. 

By looking at the related terms, we argue that the IoT 

paradigm proposal is to enable a connected world, believing 

that different research areas can also be enablers in a joint 

effort for research, development, and evolution. Also, there 

are areas which need further research to deal with the 

challenges of this novel paradigm. From our understanding, 

IoT is an umbrella combining the advances of many areas, 

and we discuss the points that make those areas connected 

to IoT or the convergence points that make some topics to 

sound as IoT synonyms. The definition of the terms is out 

of the scope of this discussion. From the table below we 

discuss only the Related Areas. 

Table 9 IoT Related Terms. 

Categories Terms 

Related 

Technology 

Cloud Computing  

Internet Protocol communication 

Middleware  

RFID  

Universal IDentifier architecture  

Wireless sensor networks 

 

Related 

Areas 

 

Ambient Intelligence 

Context-Aware Systems 

Cyber-Physical Systems 

Human-Computer Interaction  

Industry 4.0 

Internet of Computers 

Internet of Objects 

Internet of People  

Intranet/Extranet of Things  

Machine-to-Machine interaction 

Micro-electro-mechanical systems  

Network of Things 

Pervasive Computing 

Social IoT 

Ubiquitous Computing 

Web of Things 

 Ambient Intelligence - Ambient Intelligence is a 

developing technology that will increasingly make our 

everyday environment more sensitive and responsive 

(Madakam, Ramaswamy and Tripathi, 2015). 

According to (Miorandi et al., 2012), IoT may well 

inherit concepts and lessons learned in Ambient 

Intelligence, enabling Ambient Intelligence to a larger 

scale. 

 Context-Aware Systems - Considering our 

understanding of things those that are equipped with 

identification and sensing capabilities and are the 

bridge from the physical to the virtual realm. From 

identification technologies such as RFID, it is possible 



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

to get the identity and location of entities. Sensors 

enable sensing environment information such as sound, 

temperature, humidity, among others (Atzori, Iera, and 

Morabito, 2010). In our interpretation, these 

capabilities of things in IoT make the field of IoT 

related to Context-awareness, because from sensors 

and tag reading the environment and entities’ context 

information can be perceived (not explicit input to the 

system). Then such context information can be used to 

provide task-relevant information and/or services to a 

user (Abowd et al., 1999). Even though context-

awareness is considered an essential aspect of IoT 

(Sethi and Sarangi, 2017), it does not mean any IoT 

system is context-aware, at least information gathered 

are used as relevant resources for decision-making and 

for dynamically taking actions, such as systems 

customization. 

 Cyber-Physical Systems (CPS) - Cloud Computing, 

Wireless sensor network (WSN), M2M, IoT, and others 

are all fields that collaborate somehow to reach the 

broad goal of CPS, that is, “to bring the cyber-world of 

computing and communications together with the 

physical world” (Rajkumar et al. 2010; Madakam, 

Ramaswamy, and Tripathi 2015). According to 

(Miorandi et al., 2012), “a Cyber-physical 

infrastructure is the result of the embedding of 

electronics into everyday physical objects, making 

them ''smart'' and letting them integrate seamlessly 

within the global.” As discussed previously, we 

understand that WSNs are enablers for M2M and 

consequently for IoT. M2M systems are the precursor 

of CPS as devices allow the bridge between the 

physical and virtual world, in the same manner, M2M 

are the basis for the Internet of Things. It leads us to 

interpret IoT is a form of realizing CPS, and it is 

consistent with (Chen, 2012), who proposes that “CPS 

is an evolution of M2M by the introduction of more 

intelligent and interactive operations, under the 

architecture of internet of things (IoT)”. 

 Human-Computer Interaction - HCI is an area that 

needs further research to deal with this novel IoT 

context where human intervention is low or even 

absent. It usually involves the study, planning, and 

design of the interaction between people and computers 

(Madakam, Ramaswamy and Tripathi, 2015). 

 Industry 4.0 - IoT is described as a critical enabler for 

Industry 4.0 (Trappey et al., 2017). IoT has been 

deployed in factories and production environment, 

turning them more intelligent. It is leading toward the 

fourth industrial revolution. 

 Internet of Computers - Mentioned not as a synonym of 

IoT but as an orthogonal term (Gil et al., 2016). In their 

description Internet of Computers are traditional 

internet environments, where both leading data 

producers and consumers are human beings (not 

things). 

 Internet of Objects - Considering some of the IoT 

definitions found in the technical literature, we can 

interpret that “objects” and things are equivalent. For 

instance, “IoT implies that objects in an IoT can be 

identified uniquely in the virtual representations” (Li, 

Xu, and Zhao, 2015). In addition, “ [IoT is] the 

pervasive presence around us of a variety of things or 

objects – such as Radio-Frequency Identification 

(RFID) tags, sensors, actuators, mobile phones, etc.” 

(Wan et al., 2013) and ''a worldwide network of 

interconnected objects uniquely addressable, based on 

standard communication protocols” (Atzori, Iera, and 

Morabito 2010; Bandyopadhyay and Sen 2011; Gil et 

al. 2016).  

 Internet of People - the Internet of Things is not 

synonymous with the Internet of People as mentioned 

by Borgia (Borgia, 2014), but the author does not 

explain that. For this reason, we searched for works 

addressing this subject, and we could not find any 

consensus. Nevertheless, (Miranda et al., 2015) explain 

that IoT technology needs people-centric 

enhancements to achieve the more desirable IoT 

scenarios, that is, scenarios which consider people’s 

context, learning from it, reasoning and taking actions 

proactively. Therefore, achieving those desired 

scenarios requires moving from the Internet of Things 

to the Internet of People (IoP). Some essential features 

of IoP systems are: be social, be personalized, be 

proactive and be predictable.  

 Intranet/Extranet of Things - Intranet/Extranet of 

Things and IoT are not synonymous (Borgia, 2014). 

However, as far as we know, they share a broad 

concept, but the difference is that in intranet/extranet 

there is a restriction of connection for restricted areas, 

while on the internet the connections are publicly 

accessible. 

 Machine-to-Machine Interaction - M2M means no 

human intervention while devices are communicating 

end-to-end (Madakam, Ramaswamy and Tripathi, 

2015). It leads us to think that M2M and IoT are similar, 

but M2M is more a paradigm leading towards IoT 

(Atzori, Iera, and Morabito, 2010). M2M refers to 

technologies that allow both wireless and wired 

systems to communicate with other devices of the same 

ability (Wan et al., 2013). Unlike devices in IoT, in 

M2M they are meant to operate in a specific 

application, which means that M2M solutions do not 

allow the broad sharing of data or opened connection of 

devices into the Internet (Holler et al., 2014). 

 Micro-electro-mechanical Systems - MEMS 

technology is one of the enablers to develop miniature 

devices, which are capable of sensing, compute and 

communicate (Gubbi et al., 2013). When connected, 

these miniature devices form a Wireless sensor 

network, and, consequently, are crucial building blocks 

for developing machine-to-machine, IoT, among 

others. 

 Network of Things - Network of Things is similar to 

Intranet/Extranet regarding connection restrictions. It is 

referred to operate in a restricted local, within a work 

environment like an enterprise-based application. Only 

the owners use the information collected from such 

networks, and the data may be released selectively 

(Gubbi et al., 2013). 

 Pervasive or Ubiquitous Computing - These two terms 

are intimately connected. Some authors have addressed 

them interchangeably (Satyanarayanan 2001; Baldauf, 

Dustdar, and Rosenberg 2007; Spínola, Pinto, and 



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

Travassos 2008). Our interpretation of the relation 

between IoT and UbiComp is that IoT projects can be 

considered ubiquitous according to their adherence to 

ubiquity characteristics (Spínola and Travassos 2012). 

Such characteristics are context-sensitivity, adaptable 

behavior, service omnipresence, heterogeneity of 

devices, experience capture, spontaneous, 

interoperability, scalability, privacy and trust, fault 

tolerance, quality of service, and universal usability 

(Spínola and Travassos 2012). That is, ubiquity 

becomes a transversal property of IoT systems as they 

fulfill ubiquity characteristics. 

 Social IoT - The term Social IoT (SIoT) is mentioned 

as a new paradigm that has been proposed (Atzori, Iera, 

and Morabito 2010; Li, Xu, and Zhao 2015; Gil et al. 

2016; Sethi and Sarangi 2017). SIoT means that the 

things are seen now as “beings,” and the 

interconnections among them are compared to human 

social relations. The authors described the three main 

facets of a SIoT System: (i) The SIoT is navigable; (ii) 

A need for trustworthiness (relationship strength) is 

present between devices; and (iii) Models to study 

human social networks are similar to social networks of 

IoT devices. 

 Web of Things - It refers to the re-use of Web standards 

to connect and integrate IoT objects into the Web 

(Atzori, Iera and Morabito, 2010; Bandyopadhyay and 

Sen, 2011; Borgia, 2014; Madakam, Ramaswamy and 

Tripathi, 2015). 

It is possible to observe that the evolution of some areas 

and the collaboration among them enable the IoT paradigm 

realization. Once it is possible to develop small devices, 

embed intelligence, seamless communication, thing-thing 

interaction, wireless connections, and others, all of these are 

IoT enabling technologies. This discussion of terms related 

to the IoT paradigm might be a contribution for further 

investigations, which might depend on grounded concepts 

and clarity about convergence points that make other topics 

seem as IoT synonyms. In addition, practitioners and 

researchers can benefit from this discussion in the 

circumstances there are doubts on whether IoT is indeed the 

right term to consider for their software projects and/or 

future investigations. 

4.3 IoT Challenges 

To foster our discussions and research directions, one of 

the information extracted from the selected articles were 

challenges, which we understand as open opportunities in 

the industry or academia. The data extracted were analyzed 

based on Grounded Theory procedures (Strauss and Corbin, 

1990). The process started by retrieving the excerpts related 

to IoT challenges (the excerpts could be a word, a phrase or 

a full paragraph). The 15 papers provided 38 excerpts 

regarding IoT challenges. The 38 excerpts were organized 

into seven categories (Table 10). We used codes to assign 

concepts to a portion of data, with a constant comparative 

analysis to identify patterns from similarities and 

differences emergent from the data. This textual analysis 

was conducted by two researchers, with crosschecking to 

achieve consensus. The excerpts were organized in the 

categories, and we present each category with a definition 

and an example of an excerpt to support its comprehension. 

It is interesting to notice that the concerns are usually 

interrelated, confirming the multidisciplinary nature of IoT. 

For example: “For technology to disappear from the 

consciousness of the user, the Internet of Things demands 

software architectures and pervasive communication 

networks to process and convey the contextual information 

to where it is relevant” (Gubbi et al., 2013), this excerpt is 

coded for an architectural issue and network as well. 

Another example is “Central issues are making full 

interoperability of interconnected devices possible, 

providing them with an always higher degree of smartness 

by enabling their adaptation and autonomous behavior, 

while guaranteeing trust, privacy, and security” (IEEE, 

2004), which was coded both for interoperability and 

security issues. Provide solutions to the issues presented in 

the technical literature can be tricky to achieve due to the 

diversity of concerns, variety of devices and uncertainties in 

the area.  

From the findings recovered in this review, our research 

perspective will be directed to support the proposed 

definition: IoT is a paradigm that allows composing systems 

from uniquely addressable objects (things) equipped with 

identifying, sensing or actuation behaviors and processing 

capabilities that can communicate and cooperate to reach a 

goal. Our focus will be on looking at the perspective of the 

software orchestration necessary for the composition of 

systems that will rise in this contemporary paradigm. 

Despite our decision to direct the research, the article may 

contribute to other areas of research providing definitions, 

characteristics, and the challenges presented in this section. 

4.4 Threats to Validity 

Since only Scopus was used as a search engine, it may be 

missing some relevant studies, but from our experience, we 

know that it can give a reasonable coverage when 

performing together with snowballing procedures 

(backward and forward) (Matalonga, Rodrigues, and 

Travassos 2015; Motta, Oliveira, and Travassos 2016).  

In addition, a recurrent issue in literature reviews regards 

inconsistent terminology and restrictive keywords. We 

searched for other reviews and observed the terms used to 

compose our search string to reduce the researchers’ bias. 

Data extraction and interpretation biases were mitigated 

with crosschecking between two researchers and by having 

a third researcher to revise the results. All phases of this 

review were peer-reviewed; any doubt was discussed among 

the readers, to reduce selection bias. We have not performed 

a Quality Assessment regarding the research methodology 

of the selected studies due to the lack of information in the 

secondary reports. It is a threat to this study validity. 

 

 

 

 

 



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

5 Conclusion  

This work presented the research on the IoT paradigm, 

detailing the activities performed for the literature review, 

and analyzing the findings and discussions to answer the 

following research questions: (RQ1) What is “Internet of 

Things”? (RQ2) Which characteristics can define an IoT 

domain? (RQ3) Which are the areas of IoT application?  

As the IoT concept is currently under discussion, there are 

still significant issues regarding its understanding that need 

to be clarified and established. One contribution of this work 

is to present an organized perspective regarding the current 

state-of-the-art regarding the IoT paradigm. Besides, it 

allows observing which areas of application are making use 

of IoT (RQ3). All of these findings were related and 

summarized to enrich the IoT paradigm comprehension. 

From the discussion of RQ1, we understand that IoT is a 

paradigm allowing the composition of software systems 

from uniquely addressable objects equipped with 

identifying, sensing or actuation behaviors and processing 

capabilities that can communicate and cooperate to reach a 

goal. The idea of composing software systems from 

available components is not new, but one of the issues that 

set IoT apart is the scale at which it can be achieved and the 

actors involved in these new software systems. From this, 

shared concerns regarding the development and evaluation 

of such software systems should be reframed to cover the 

particularities of these new types of devices. A critical step 

towards it is to establish what quality characteristics should 

be contemplated. With the second research question, we 

moved forward in this direction. 

Regarding the IoT characteristics (RQ2), from the 

technical literature, we recovered 29 different attributes, 

from which this paper discussed nine of them with clear 

evidence from the sources of information. Considering that 

the results retrieved are from secondary studies, the 

characteristics represented reflect more than just the 15 

secondary studies, but rather the whole set of primary 

studies involved in them which can strengthen these results. 

The most commonly cited characteristics presented are 

Efficiency, Interoperability, Scalability, Privacy, and 

Security that reassure the definition reached in the paper. 

This work is the first step towards future investigations 

focusing on aspects such as software development and 

quality control of IoT. Apart from that, the grounded 

concepts, properties and terms related to the IoT paradigm 

can be a contribution to any future related research. Besides, 

the identification and discussions on already deployed 

applications and the three behaviors of things can contribute 

to practitioners in the processes of idealizing, engineering 

and developing IoT software systems. At last, it is expected 

Table 10  IoT Challenges. 

Category Example 

Architecture: Issues and concerns regarding 

design decisions, styles and the structure of IoT 

systems. 

“Finding a scalable, flexible, secure and cost-efficient architecture, able to 

cope with the complex IoT scenario, is one of the main goals for the IoT 

adoption.” (Borgia, 2014). 

Data: It refers to the management of a significant 

amount of data, and how to recover, represent, 

store, interconnect, search, and organize data 

generated by IoT from so many different users 

and devices. 

“This new field offers many research challenges, but the main goal of this 

line of research is to make sense of data in any IoT environment. It has 

been pointed out that it is always much easier to create data than to analyze 

them. With this in mind, new conceptual modeling, as well as new 

paradigms of data mining techniques will be crucial to provide value and 

meaning to initially empty Data.” (Gil et al. 2016). 

Interoperability: Related to the challenge of 

making different systems, software, and things to 

interact for a purpose. Standards and protocols 

are also included as issues. 

“The end goal is to have Plug n' Play smart objects which can be deployed 

in any environment with an interoperable backbone allowing them to blend 

with other smart objects around them.” (Gubbi et al., 2013). 

Management: The application of management 

activities, such as planning, monitoring and 

controlling, in the IoT system will raise the 

interaction of different things. 

“From the viewpoint of the network, IoT is a very complex heterogeneous 

network, which includes the connections among various types of networks 

through various communication technologies. The devices and 

methodologies for addressing things management is still a challenge.” (Li, 

Xu and Zhao, 2015) 

Network: Technical challenges related to 

communication technologies, routing, access and 

addressing schemes considering the different 

characteristics of the devices. 

“Designing an appropriate topology, routing, and MAC layer is critical for 

scalability and longevity of the deployed network” (Gubbi et al., 2013). 

Security: Issues related to several aspects to 

ensure data security in the IoT system. For that, a 

series of properties, such as confidentiality, 

integrity, authentication, authorization, non-

repudiation, availability, and privacy should be 

investigated. 

“Security issues are central in IoT as they may occur at various levels, 

investing technology as well as ethical and privacy issues [...] This is 

extremely challenging due to the IoT characteristics.” (Borgia, 2014). 

Social: Concerns related to the human end-user to 

understand the situation of its users and their 

appliances. 

“For a lay person to fully benefit from the IoT revolution, attractive and 

easy to understand visualization have to be created.” (Gubbi et al., 2013). 
 



 

Towards a more in-depth understanding of the IoT Paradigm and its challenges Motta et al. 2019 

the knowledge organized and presented in this paper can 

contribute to stimulating discussions and future 

investigations on providing software technologies to 

promote the engineering of high-quality IoT software 

systems.  

6 Declarations 

Abbreviations 

IoT: Internet of Things; CPS: Cyber-Physical Systems; 

RFID: Radio-Frequency Identification; MEMS: Micro-

electro-mechanical systems; M2M: Machine-to-Machine; 

HCI: Human-Computer Interaction. 

Availability of data and materials 

Details of the protocol are available in 

https://goo.gl/cTyzuT. 

Authors’ contributions 

We present a review supported by established guidelines 

and aims to contribute to the IoT field of with awareness, 

understanding of its concepts and features and a 

characterization regarding its definition, characteristics, and 

applications. We answer the research questions 

characterizing the area, present challenges and opportunities 

and we offer an essential overview of the Internet of Things 

state-of-the-art, presenting issues that should be addressed 

to contribute to its strengthening and establishment. 

Acknowledgments  

The authors thank CNPq and CAPES for supporting this 

research.  

Funding  

Prof. Travassos is a CNPq researcher (grant 305929/2014-

3). This study was financed in part by the Coordenação de 

Aperfeiçoamento de Pessoal de Nível Superior - Brasil 

(CAPES) - Finance Code 001. 

Competing interests 

The authors declare that they have no competing interests. 

Consent for participation and publication   

Not applicable. 

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