A survey on the model-centered approaches to conceptual modeling of IoT systems

Abstract

Internet of Things (IoT) is a system of connected objects, entities, devices, and components which share and transfer data over a network. Many papers are published on the topic of conceptual models in the IoT context, but it is difficult to assess the current status of the conceptual modeling approaches and methods for IoT systems. This paper presents an overview of the state of the art as well as discusses fundamental concepts, challenges and current research gaps with potential future agenda for conceptual modeling of IoT. Search facilities in the selected online repositories were used to identify the most relevant papers. The primary results were scanned and papers were selected according to the inclusion/exclusion criteria. Selected papers were assessed to extract data for the defined attributes. This paper confirms that there is a large body of research related to modeling of IoT systems. However, the results show that there is a lack of commonly agreed approaches and supporting formal methods for conceptual modeling of IoT systems. On the other hand, recent studies that apply model-based or model-driven development principles that use ontology or metamodel based approaches are promising due to systematic use of models as the primary means of a development process enabling for the dissemination of the methods further to the emerging fields such as smart cities, factories, transportation, hospitals, healthcare, hospitality and tourism, etc.

Full text

TYPE Mini Review
PUBLISHED 04 August 2023
DOI 10.3389/fcomp.2023.1035225
OPEN ACCESS
EDITED BY
Bernhard Thalheim,
University of Kiel, Germany
REVIEWED BY
Christian Kop,
University of Klagenfurt, Austria
Andreas Oberweis,
Karlsruhe Institute of Technology
(KIT), Germany
*CORRESPONDENCE
Deniz Cetinkaya
dcetinkaya@bournemouth.ac.uk
RECEIVED 02 September 2022
ACCEPTED 17 July 2023
PUBLISHED 04 August 2023
CITATION
Kohan S, Johnstone L and Cetinkaya D (2023) A
survey on the model-centered approaches to
conceptual modeling of IoT systems.
Front. Comput. Sci. 5:1035225.
doi: 10.3389/fcomp.2023.1035225
COPYRIGHT
©2023 Kohan, Johnstone and Cetinkaya. This
is an open-access article distributed under the
terms of the Creative Commons Attribution
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reproduction in other forums is permitted,
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copyright owner(s) are credited and that the
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No use, distribution or reproduction is
permitted which does not comply with these
terms.
A survey on the model-centered
approaches to conceptual
modeling of IoT systems
Sofia Kohan, Liam Johnstone and Deniz Cetinkaya*
Department of Computing and Informatics, Faculty of Science and Technology, Bournemouth
University, Poole, United Kingdom
Internet of Things (IoT) is a system of connected objects, entities, devices, and
components which share and transfer data over a network. Many papers are
published on the topic of conceptual models in the IoT context, but it is dicult
to assess the current status of the conceptual modeling approaches and methods
for IoT systems. This paper presents an overview of the state of the art as well
as discusses fundamental concepts, challenges and current research gaps with
potential future agenda for conceptual modeling of IoT. Search facilities in the
selected online repositories were used to identify the most relevant papers.
The primary results were scanned and papers were selected according to the
inclusion/exclusion criteria. Selected papers were assessed to extract data for
the defined attributes. This paper confirms that there is a large body of research
related to modeling of IoT systems. However, the results show that there is
a lack of commonly agreed approaches and supporting formal methods for
conceptual modeling of IoT systems. On the other hand, recent studies that
apply model-based or model-driven development principles that use ontology
or metamodel based approaches are promising due to systematic use of models
as the primary means of a development process enabling for the dissemination
of the methods further to the emerging fields such as smart cities, factories,
transportation, hospitals, healthcare, hospitality and tourism, etc.
KEYWORDS
conceptual modeling, Internet of Things (IoT), ontology, metamodel, model based
approach
1. Introduction
Internet of Things (IoT) has gained great interest in the last decade and the range of
IoT systems, which are connected objects, entities, devices and components that share and
transfer data over a network, is increasing. The number of available IoT devices, sensors, and
smart components are increasing rapidly due to its potential for future smart systems.
IoT consists of many small devices over a network, sometimes thousands or millions of
them. Sensors, network enabled devices, mobile devices, embedded systems, etc. are in the
core of IoT. Besides this, IoT has particular focus on the number of the devices, large scale
application, data sharing and smart functionality of the systems. In addition, IoT devices,
sensors, microprocessors, etc. are cheap when compared to computers or other hardware.
Hence, IoT has gained great interest within many disciplines so not only researchers and
big vendors but also small start-up companies or even interested individuals design and
develop IoT solutions. However, these cheap devices are only a part of a larger IoT system.
So, when we want to implement and test the whole system we will need hundreds, thousands
or sometimes millions of them. As a result, it is not cost-effective to test the whole system
running.
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Recently research communities have started to work on the
methods and tools to analyse and design IoT systems (D’Angelo
et al., 2017;Kecskemeti et al., 2017). Most of the related research
focuses on the modeling aspects and model-driven approaches
are proposed as a potential solution for large systems modeling
(Ciccozzi et al., 2017). On the other hand, there are challenges
especially related to scalability and dealing with heterogeneity of
IoT systems. The development of methods, tools, and procedures
to analyse and design IoT systems are still in progress.
A model can be defined as a wellformed, adequate, and
dependable instrument that represents a source system and
functions in scenarios of use (Thalheim, 2022). Although there are
many other definitions in the literature, there is a central property
for model being useful. A conceptual model is a concise and
purposeful consolidation of a set of concepts that are represented
by means of a modeling language or method (Mayr and Thalheim,
2021). Conceptual models are early stage artifacts that represent the
system of interest and provide requirements for a variety of more
specialized models such as analysis and design models (Bock et al.,
2017). The conceptual model must represent and specify the system
sufficiently to make all stakeholders in the project are comfortable
in using it as a means for understanding and discussing the system
(Robinson et al., 2015).
Systems modeling and conceptual modeling in particular,
provide solutions to understand and analyse systems as an effective
tool. It has been widely used especially in systems engineering
and has been proven to improve the communication and supports
requirements engineering and further activities. Although there are
existing studies that propose conceptual models in the context of
IoT, research about modeling techniques specific to the conceptual
modeling of the IoT systems is limited. There is still a research
gap to overcome the challenges caused by the wide range of IoT
devices and sensor behaviors (Markus et al., 2018). With traditional
approaches, adding new devices and sensors to the modeling
libraries require either programming or changing the modeling
platform. However, more flexible and extendable solutions are
required to configure the modeling tools and extend the libraries
easily when requirements change.
Many papers are published on the topic of conceptual models
in the IoT context, but it is difficult to assess the current status of
the conceptual modeling approaches and methods for IoT systems.
This paper presents an overview of the state of the art as well as
discusses fundamental concepts, challenges, and current research
gaps with potential future agenda for conceptual modeling of IoT.
Search facilities in the selected online repositories were used to
identify the most relevant papers. The primary results were scanned
and papers were selected according to the inclusion/exclusion
criteria.
This paper shows that there is a large body of research related
to modeling of IoT systems. However, the results show that there
is a lack of commonly agreed approaches and supporting formal
methods for conceptual modeling of IoT systems. Many models or
modeling approaches are alone insufficient for holistic analysis due
to the high degree of heterogeneity in IoT technologies, devices, and
the diverse application domains. On the other hand, recent studies
that apply model-centered approaches are promising. The outline
of the paper is as follows. Next section provides the background
information and literature review. Section 3 presents the mapping
study with the details of the process. Section 4 presents the results
and discusses the threats to validity. Finally, Section 5 concludes the
paper and suggests future research agenda.
2. Literature review
IoT systems connect objects, entities, devices, and components
which share and transfer data over a network. In the core of
IoT, there are sensors, network enabled devices, actuators, mobile
devices, embedded systems, etc. Communication networks such as
sensor networks or wireless ad hoc networks provide an underlying
infrastructure for implementing IoT and various technologies
such as WiFi, Bluetooth, ZigBee, cellular, etc. help to connect
different devices into the network. However, it is not easy to decide
which infrastructure and technology should be used due to the
wide and evolving variety of options and changing requirements
for many different types of systems. Moreover, IoT technologies
evolve over time and new functions and devices are introduced
increasingly.
Figure 1 shows an example IoT architecture to give an overview
of different layers in IoT implementation. Figure 1 illustrates the
elements of an IOT system on the bottom layer as things, devices
or sensors. On the network and communications layer, it shows
the underlying technologies and networking mechanisms that
facilitates the IOT system to connect and communicate. On the top
layer, the focus is on the business intelligence and data analytics.
At each layer, there are applications and services that helps to
implement the system. As well as security is the biggest challenge
to be addressed at each layer. Besides these, other functionality
and aspects can be added to this architecture such as process
management, service organization, etc. (Bassi et al., 2013).
Modeling IoT systems is gaining more importance due to the
recent developments in IoT related technologies and increasing
usage of such systems (Van Mierlo et al., 2018). Components
are equipped with ubiquitous intelligence and IoT applications
are designed to effectively fulfill a purpose such as monitoring
existing systems, data analytics, digital twin, predictive analysis,
optimization, etc. The challenge in analysing and designing IoT
systems lies in the availability of broad range of devices and the
difficulty of developing a fully integrated system with both physical
and digital components.
The goal of conceptual modeling is to improve our
understanding of a given problem and design better systems.
Conceptual models can be defined and tailored for different
domains and industries. Conceptual modeling can be carried
out at early stages of the development process so that there
is a common understanding among the stakeholders. System
components, objects, entities, etc. associated with their common
properties or attributes can be included as well as any characteristic
information. Actions or tasks among these system elements can
be defined too. Therefore, conceptual models can cover both
structural or behavioral aspects of a system. It is also important to
agree on the terminology, basic terms and common language to
better communicate at early stages and during the requirements
engineering stage. The most important role of a conceptual
model is to make all parties involved in a development project to
understand the models in the same way. Proper development of
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FIGURE 1
An overview of IoT architecture.
a conceptual model is critical for expressing the objectives of the
system.
Modeling is used as an instrument for managing complexity in
describing, analysing, and designing systems. Modeling techniques
or paradigms are mostly defined by the introduction of three
main elements: (1) modeling concepts (i.e., abstract syntax),
(2) diagrammatic representations (i.e., concrete syntax), and (3)
semantics of the concepts (Çetinkaya et al., 2015). For many
years, researchers have been using and promoting model-driven
and model-based approaches to improve software reusability and
productivity (Ciccozzi et al., 2017). Model-based or model-centered
paradigms have been introduced too to broaden and deepen the
scope of model-driven system development (Costa et al., 2016).
Model-Driven Development (MDD) is a software and system
development methodology that suggests the systematic use of
models as the primary means of the development process.
MDD introduces model transformations between the models at
different abstraction levels and proposes the use of metamodels
for specifying modeling languages formally. In MDD, models are
transformed into other models in order to (semi)automatically
generate the final source code. MDD promotes automated code
generation to increase the productivity, reusability and quality
during the software and system development process. For example,
metamodeling, model transformations, formal language theory,
systems theory, graph theory, conceptual modeling, and various
methods can be used to move from the concepts into code
(Çetinkaya et al., 2015).
The most common method to define modeling languages
is metamodeling, which is the process of complete and precise
specification of a modeling language in the form of a metamodel.
Metamodeling is highly related to Domain Specific Modeling
(DSM) whereas DSM raises the level of abstraction as symbols
in a domain specific language map to the concepts in a specific
domain. During the analysis and design of the complex systems,
DSM provides better communication between stakeholders,
effective representation of the concepts and consistency among
development artifacts. The related work in this area defines the
main concepts in IoT domain and provides an initial basis for
further research (Bassi et al., 2013;Fortino et al., 2017).
UML profiles are also commonly used whereas the profiling
mechanism offer a generic extension method for customizing UML
models for particular domains (Thramboulidis and Christoulakis,
2016). It uses stereotypes, tagged values and constraints applied to
specific model elements, such as within the class diagram. Agent
based approaches have been applied to IoT modeling to model
an IoT system as a multi agent system and to facilitate system
modeling and development by reducing design and development
time (Fortino et al., 2017). Overall, research related to conceptual
modeling of IoT systems is limited but has gained interest recently.
Hence, we have decided to apply a basic mapping study to review
the literature which is explained in the next section.
3. Mapping process
In this study, we applied the systematic mapping process
presented in Figure 2. The process is adapted from Brereton
et al. (2007) and Petersen et al. (2015). The primary studies were
searched, selected and evaluated according to the selected protocol.
After obtaining the initial pool of papers and pre-screening of the
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FIGURE 2
The mapping process for the review study.
papers, we refined the inclusion and exclusion criteria to select the
most relevant papers. Finally, we developed our map and analyzed
the extracted data. Our study mainly focuses on addressing two
research questions:
•RQ1. What have been the trends of the literature within the
field of conceptual modeling of IoT systems?
•RQ2. Which methods, techniques or tools are used while
applying model-centered approaches to conceptual modeling
of IoT systems?
3.1. Selection of the databases
Databases were selected due to selected repositories having
regular content update, paper availability and accuracy of the
results obtained by the search as well as being commonly used
databases in our field. We performed the search in the selected
databases in July 2022. Five academic publication repositories
were used:
•Scopus (https://www.scopus.com/search/form.uri?display=
advanced)
•ScienceDirect (https://www.sciencedirect.com/search)
•ACM (https://dl.acm.org/search/advanced)
•IEEE (https://ieeexplore.ieee.org/search/advanced)
•SpringerLink (https://link.springer.com/advanced-search)
3.2. Keywords and paper selection
To establish the search strategy based on the defined
research questions, two main terms were initially identified,
namely “Internet of Things” and “Conceptual Modeling”. Possible
variations such as abbreviations, e.g., IoT were also considered. The
queries are executed with AND operator within the title, abstract
and keywords.
We decided not to include “model driven” or “model based”
keywords in our initial search to cover the literature about
conceptual modeling in IoT whereas some papers may not apply
a model driven or model based approach specifically but they could
still be relevant. Selected papers were categorized according to their
contribution type to further analyse the papers employing MDD or
similar approaches.
Paper selection was done in two rounds. In the first round,
we got the primary results by searching using the keywords and
applying the inclusion criteria; and in the second round we checked
and removed duplicates and irrelevant papers. Inclusion criteria is
given below:
•Published as a journal paper OR conference paper OR book
chapter
•Published between January 2010 and June 2022
•Language: English
Number of primary results for each database are given below:
•327 - Scopus
•24 - ScienceDirect
•242 - ACM
•104 - IEEE
•155 - SpringerLink
After the first scan, irrelevant papers that simply have the
keywords but has no relation to the aim of this study were removed
according to the title and abstract as well as having a quick scan
of the paper. Papers were incrementally included into the mapping
dataset, i.e., if the paper is already included from another database
it is not added again.
At the end of the second round, 191 papers were selected in
total. Then, multiple or similar publications by the same authors
in different venues were eliminated and the latest available papers
were selected. A total of 177 paper were selected for further
analysis and papers have been downloaded and cataloged from
available online repositories. In the third round, papers were
eliminated if they are not relevant based on their contribution
type and do not address IoT or modeling, or the full text is not
available. As a result, 148 papers were included in the analysis.
The list of papers is attached to the submission and available upon
request.
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3.3. Attributes for data extraction
Papers were analyzed according to their application domain,
methods, and research objectives. Data extraction is done according
to the following attributes and questions:
•Contribution: What is the contribution of the paper?
•Methods: What is the modeling language or diagramming
technique used?
•New method: Does the paper propose a new conceptual
modeling language? (Yes/No/Partially)
•Application domain: What is the application domain if there
is an example or case-study?
•Tools: Are there any software implementation if there is a new
method proposed or any tool support? (Yes/No/Partially)
•Evaluation: Is the proposed model or method tested properly
or evaluated? (Yes/No/Partially)
Regarding the contribution of the paper, there were four main
categories as follows: (1) System design or overview, (2) Conceptual
model or case study, (3) Review, and (4) New modeling approach.
We did not exclude any aspects or certain views of modeling,
however it was evident that most of the papers were covering
different views but not all of the aspects. If the questions are
answered as (Yes/No/Partially), further explanation has been added
to identify the methods.
4. Results and discussion
4.1. Trends within the field of conceptual
modeling of IoT systems
Paper details were extracted from the search databases and cross
checked for any inconsistencies. In addition to the aforementioned
attributes in the previous section, we had standard attributes such
as title, authors, publication year, source title, etc. Looking at the
number of publications by year, it is evident that the interest in
conceptual modeling in the IoT context is increasing with 119 out
of 148 papers were published in the last 6 years.
Regarding the publication types, there were 40 journal articles,
2 book chapters, and 106 conference papers. During our analysis it
was very clear that most of the journal articles were published in the
last 6 years (only 3 articles before 2017) with the highest numbers
in 2021 and 2022. Although, we did not have an exclusion criteria
based on the quality of the papers, we could identify that the best
papers with the most relevant contributions were published in the
journals. Regarding the contribution of the papers:
1. 11% (16/148) of the papers present a system design, system
overview, or architectural diagrams,
2. 40.5% (60/148) of the papers present a conceptual model by
using various methods,
3. 11.5% (17/148) of the papers provide a review, discussion, an
approach, or state-of-the-art knowledge,
4. and 37% (55/148) of the papers propose a new modeling
language or method, UML profile, ontology, or metamodel.
First and second group of the papers present models
of IOT systems or case studies, focusing a specific part in
many cases. We then further investigated the last group of
the papers specifically to cover the model-driven approaches
in depth. In the last group of papers that propose a new
modeling approach, around 70% (39/55) of them proposes a
new modeling language and utilizes model driven approaches.
Used methods, techniques and tools are given in the next
section.
According to our analysis, in the context of conceptual
modeling of IoT, most commonly applied domains are
smart buildings including smart homes and offices, smart
agriculture, smart cities, healthcare, smart vehicles, Industry
4.0, and advanced manufacturing. There is also an increasing
interest on the simulation studies in this field (Diaconescu
and Wagner, 2015;Barriga et al., 2021). Some of the
simulation studies emphasize the use of model-driven
approaches for efficiency and productivity (Van Mierlo et al.,
2018).
4.2. Methods, techniques, and tools
Although conceptual models were sometimes represented by
using informal or non-standardized methods in the reviewed
papers, many of them used various methods or frameworks which
are listed below:
•Methods or techniques:
– UML
– Relational model
– Domain model
– Flow diagrams
– SysML
– Goal modeling
– DMN (Decision Model and Notation)
– ERD diagrams
– BPMN
– Colored Petri Nets
•Architectural frameworks:
– IoT Architecture (IoT-A)
– Unified Architecture Framework (UAF)
– Reference Model of Open Distributed Processing (RM-
ODP)
– OSI reference model
– Agile Modeling Method Engineering (AMME) framework
– APPARATUS framework and metamodel
•Standards:
– ISO/IEC 30141:2018 IoT Reference Architecture
– ISO/PAS 19450:2015 Automation systems and
integration—object-process methodology
– ETSI Multi-access Edge Computing (MEC)
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There was not any significant statistical data because each
research study used various techniques. However, we can say
that there is a trend toward using more semi-formal and formal
methods which is promising. For completeness of this study, we
have also listed the IoT solutions providers that are mentioned in
the reviewed papers below:
•Amazon AWS IoT platform
•Google IoT platform
•Microsoft azure IoT Hub
•IBM Watson IoT platform
•Intel IoT platform reference model
•Cisco IoT solutions
Papers that propose a modeling language for IoT either use a
metamodeling approach, ontologies, or UML. Most of the papers
present a simple case study to demonstrate the use of the proposed
language, while only a limited number of them discusses a formal
evaluation (Fitz et al., 2019;Barriga et al., 2021;Plazas et al.,
2022). A well developed modeling language is not the same as a
modeling method or modeling technique. Papers that present a new
modeling approach for IoT systems with a well-defined metamodel
is usually complemented with prototype tool development and
relevant evaluation approach (Cicirelli et al., 2018;Mavropoulos
et al., 2019;Walch and Karagiannis, 2019;Escamilla-Ambrosio
et al., 2021;Seiger et al., 2021;Erazo-Garzón et al., 2022). Analysis
on the methods and techniques provided insight about variety of
the model based tools. Popular MDD related tools are listed below:
•UML profiling mechanism and stereotypes
•Model-driven architecture (MDA) and metamodeling
approach
•Eclipse modeling framework (EMF)
•Eclipse GMF (Graphical modeling framework)
•OCL (Object constraint language)
•Protégé ontology editor
•ATLAS transformation language (ATL)
•OWL Web ontology language
•Acceleo code generator
4.3. Discussion
Challenges or research gaps are highlighted in the context
of the new or emerging topics such as edge or fog computing,
microservices architecture, context aware systems, real-time
systems, security modeling, etc. (Barriga et al., 2021;Escamilla-
Ambrosio et al., 2021;Machorro-Cano et al., 2022;Valderas et al.,
2022). Due to conceptual models are often not used explicitly in the
further steps of the development lifecycle, a big semantic gap exists
between the different models of the system. This gap causes a lack
of model continuity in many cases. Main challenges with modeling
IoT systems are the heterogeneity of scenarios, the variety of devices
and the need for scalability (D’Angelo et al., 2017).
Regarding the issues and challenges, the security and privacy
aspects in IoT and how to model these aspects were stated
as potential future work in several publications (Mavropoulos
et al., 2017;Maidl et al., 2019;Escamilla-Ambrosio et al.,
2021). Besides these, variability modeling and model checking
were also mentioned as challenging topics (D’Angelo et al.,
2017). Although there is a growing interest recently in the
field of IoT modeling, there is still no agreed solution to
overcome the initial challenges. The summary of potential future
agenda and research directions are given in the Conclusion
section.
4.4. Limitations to the study
In this study we searched five online databases; there may be
other relevant studies which are indexed in other databases. The
validity of the results can be assessed based on the unintended
human error and query results. Since not all information was
obvious to answer the established research questions, some data
had to be interpreted. Some studies may have been missed
due to being not available or the limitations of the search
engines.
5. Conclusion and future agenda
This paper presents an overview of the state of the art as well
as discusses fundamental concepts, challenges and current research
gaps with potential future agenda for conceptual modeling of IoT.
It focuses on the model-centered approaches to contribute to the
establishment of a common understanding of the concepts as well
as to compile a set of tools for modeling activities in the context
of conceptual modeling of IoT systems. This work can provide
a basis for a more comprehensive systematic review. Based on
the outcomes of this study and the trends in the literature, we
prioritized the potential future work into three main groups as
follows.
5.1. Formal approaches with model
checking features and extension
mechanisms
Model checking features and extension mechanisms for
existing modeling languages and methods are only partially in place
when the specifications are formally supported by metamodels or
ontologies. However, in many cases these features are implemented
as a proof of concept and checks only basic conditions or
rules. Especially, in the context of IoT, systems designers and
modelers can be supported in terms of checking component
interoperability and technical requirements at modeling level. This
can help to address the challenges involved in the entire IoT
application lifecycle. There is a need to support the design and
development of IoT systems that require modeling of reactive
and reconfigurable elements with dynamic variable structures.
Modelers can define the formal structural model of the system with
different alternatives and future implementations can be based on
this model.
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5.2. Model-driven simulation of IoT systems
To the best of our knowledge, there is not an existing
comprehensive metamodel for IoT in the literature. In addition,
research on metamodel based and model-driven simulation of
IoT is limited. Defining formal metamodel based transformation
rules to generate IoT simulation models or design models from
conceptual models can provide opportunities to test the IoT
systems before implementing them. This approach can be very
efficient and useful if you compare the cost of modeling and
the cost of actual development. Future research can focus on
both conceptual modeling and design of IoT systems which can
provide management of different types of IoT devices and their
relationships in a modular, extensible and configurable way.
5.3. Modeling security and privacy aspects
in IoT
There is an increasing interest in the literature related to
security aspects in IoT. However, the research on modeling the
security and privacy aspects in IoT has recently gained interest.
There are specific challenges in this context such as computing
platforms of IoT are usually constrained in memory and processor
resources. Hence, IoT devices may not support complex encryption
algorithms. Moreover, embedded devices may outlive crypto
algorithm lifetime. Considering the security and privacy aspects
early in the modeling stage can help to understand the risks earlier
and so to design the system accordingly.
As a result, there is a lack of commonly agreed approaches
and supporting formal methods for conceptual modeling of IoT
systems. On the other hand, recent studies that apply model-
based or model-driven development principles that use ontology
or metamodel based approaches are promising due to systematic
use of models as the primary means of a development process.
Author contributions
DC designed and performed the research and wrote the paper.
SK and LJ helped with extracting data from the selected papers
and completing the mapping study. All authors agreed with the
submitted version.
Funding
Bournemouth University provided support for the open access
publication fee via the research incentive.
Acknowledgments
We would like to thank B. Yildiz Cetinkaya for her
contributions during downloading and cataloging the papers.
Conflict of interest
The authors declare that the research was conducted
in the absence of any commercial or financial relationships
that could be construed as a potential conflict of
interest.
Publisher’s note
All claims expressed in this article are solely those
of the authors and do not necessarily represent those of
their affiliated organizations, or those of the publisher,
the editors and the reviewers. Any product that may be
evaluated in this article, or claim that may be made by
its manufacturer, is not guaranteed or endorsed by the
publisher.
Supplementary material
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fcomp.
2023.1035225/full#supplementary-material
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