Software Engineering for Internet of Things: Architectures, Technologies, and Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 26971

Special Issue Editors


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Guest Editor
School of Computing and Communications, Lancaster University, Bailrigg, Lancaster LA1 4YW, UK
Interests: software engineering; software evolution; Internet of Things; mobile security; software architecture

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Guest Editor
School of Business, University of Southern Queensland, Springfield Central QLD 4300, Australia
Interests: Software Engineering; Information Systems; Design Science Research

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Guest Editor
BISITE Research Group, Edificio Multiusos I+D+I, University of Salamanca, 37007 Salamanca, Spain
Interests: artificial Intelligence; machine learning; edge computing; distributed computing; Blockchain; consensus model; smart cities; smart grid
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Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is driven by interconnected sensors and devices that provide a platform to manage heterogeneous things such as humans, systems, services, and devices. A survey[1] by Gartner had predicted that by 2020, the world will become home to 20 billion internet-connected things, with worldwide revenue from IoT systems expected to reach 750 billion by 2025. The rapid proliferation of IoT systems is primarily due to portable devices that unify hardware, networks, and software to enable things that collect, process, and exchange contextualised data to support smart applications. The development of innovative solutions for IoT hardware and IoT networks is important; however, the true potential and business value of IoT lie with software (i.e., supporting data and logic) that enables the manipulation and dynamic adaptation of IoT systems. Due to the inherent complexity and heterogeneity of IoT systems, one of the critical challenges is to develop processes, algorithms, tools, and frameworks, etc., for the engineering and development of IoT applications, systems, and platforms.

Software Engineering[2] (SE) as per the ISO 9001:2015 standard provides principles and practices to support the engineering lifecycle, i.e., the design, development, evaluation, and maintenance of complex and large-scale software-intensive systems.

The aim of the proposed Special Issue is to promote research and practices at the intersection of IoT and software engineering—synergising software and system-level engineering—to architect and develop IoT systems that are resource-, cost-, and energy-efficient. This Special Issue aims to find answers to some fundamental questions, such as: How can software engineering methods and techniques support the engineering and development of IoT systems? What software tools, technologies, processes, and architectures could be exploited to engineer IoT? Which systems, domains, and applications can benefit from software-driven IoT?

This Special Issue aims to bring together academic research and industrial practices in areas such as architectural models, tools, technologies, and their applications to engineering IoT systems. The proposed Special Issue primarily focuses on:

- Architectures: System- and software-level architectures that support models, patterns, processes, and languages to architect and develop software-intensive IoT applications and systems.

- Technologies: Platforms, infrastructures, and implementation technologies that are driven by software engineering to develop, deploy, and operationalise IoT.

- Applications: Real-world systems and scenarios that apply software engineering principles and practices to engineer IoT that can address the challenges of smart systems, cities, societies, and infrastructures.

References

[1] M. Hung. Leading the IoT - Gartner Insights on How to Lead in a Connected World. Gartner, Inc., 2017

[2] Software engineering - Guidelines for the application of ISO 9001:2015 to computer software. https://www.iso.org/standard/74348.html

Prof. Dr. Rashid Mehmood
Dr. Aakash Ahmad
Dr. Mahdi Fahmideh
Prof. Dr. Juan M. Corchado
Guest Editors

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Keywords

The topics of interest include, but are not limited to, the following:

  • Empirical Studies on SE for IoT

          Survey-based studies, systematic reviews, and mapping studies
          Industrial findings and experience reports
          Validation and evaluation research
          Systematic mapping studies or systematic literature reviews
          Empirical studies and metrics

  • Software Processes for Developing IoT Requirements engineering

          Software design and development
          Software testing
          Things analysis
          Maintenance, evolution, and dynamic adaptation

  • Software Architectures for IoT Reference architectures

          Architectural patterns and styles
          Processes and frameworks
          Frameworks and product lines

  • Algorithms for Self-managing and Adaptive IoT Self-management

         Self-healing
         Dynamic adaptation
         Fault tolerance
         Artificial intelligence techniques for sustainable IoT

  • Tools and Technologies to Develop IoT Prototypes and tool support

          Mobile computing-based IoT
          Development environments, frameworks, and tools
          Programming languages and frameworks

  • IoT Development Challenges Things and sensors connectivity

          Hardware and software mapping
          Developing IoT-driven Big Data applications
          Flexibility and compatibility of things and algorithms
          Security and privacy issues for IoT software

  • IoT Applications Smart cities

          Urban services
          Smart healthcare
          Smart emergency response systems
          Smart traffic management systems
          Smart homes and buildings

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Published Papers (4 papers)

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Research

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20 pages, 1175 KiB  
Article
An Embedded Software Development Framework for Internet of Things Devices
by Camilo Lozoya, José Miguel Díaz, César Rodríguez-Esqueda, Claudia Prieto-Resendiz and Alberto Aguilar-Gonzalez
Electronics 2022, 11(24), 4158; https://doi.org/10.3390/electronics11244158 - 13 Dec 2022
Viewed by 3498
Abstract
Internet of things (IoT) devices are mostly ubiquitous in this day and age, and it is hard to imagine a life without them, especially in the productive sectors (industry, agriculture, and automotive) and in our daily life activities (consumer electronics, home automation, and [...] Read more.
Internet of things (IoT) devices are mostly ubiquitous in this day and age, and it is hard to imagine a life without them, especially in the productive sectors (industry, agriculture, and automotive) and in our daily life activities (consumer electronics, home automation, and intelligent buildings). The high demand for these devices has created significant competition to provide them at the best price, at the right time, and with the best features. The trend in which these devices have increased their product features has resulted in their embedded software being more complex, leading to extended development and testing times. Consequently, as the types of advanced IoT products keep diversifying, the field maintenance of all the different models deployed grows more complicated. This paper proposes an embedded software development framework for IoT devices independent of the microcontroller architecture, the compiler, and the development environment. This framework allows having a common software baseline between different projects, which shortens the learning curve, development time, and module validation while allowing code reuse for embedded software professionals. A proof-of-concept evaluation is also presented to demonstrate the efficiency and reliability of the obtained embedded software code for a simple but representative IoT application. Full article
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38 pages, 7390 KiB  
Article
Improving Fault Tolerance and Reliability of Heterogeneous Multi-Agent IoT Systems Using Intelligence Transfer
by Vyas O’Neill and Ben Soh
Electronics 2022, 11(17), 2724; https://doi.org/10.3390/electronics11172724 - 30 Aug 2022
Cited by 6 | Viewed by 2873
Abstract
Driven by the ever-growing diversity of software and hardware agents available on the market, Internet-of-Things (IoT) systems, functioning as heterogeneous multi-agent systems (MASs), are increasingly required to provide a level of reliability and fault tolerance. In this paper, we develop an approach to [...] Read more.
Driven by the ever-growing diversity of software and hardware agents available on the market, Internet-of-Things (IoT) systems, functioning as heterogeneous multi-agent systems (MASs), are increasingly required to provide a level of reliability and fault tolerance. In this paper, we develop an approach to generalized quantifiable modeling of fault-tolerant and reliable MAS. We propose a novel software architectural model, the Intelligence Transfer Model (ITM), by which intelligence can be transferred between agents in a heterogeneous MAS. In the ITM, we propose a novel mechanism, the latent acceptable state, which enables it to achieve improved levels of fault tolerance and reliability in task-based redundancy systems, as used in the ITM, in comparison with existing agent-based redundancy approaches. We demonstrate these improvements through experimental testing of the ITM using an open-source candidate implementation of the model, developed in Python, and through an open-source simulator that tested the behavior of ITM-based MASs at scale. The results of these experiments demonstrated improvements in fault tolerance and reliability across all MAS configurations we tested. Fault tolerance was observed to improve by a factor of between 1.27 and 6.34 in comparison with the control group, depending on the ITM configuration tested. Similarly, reliability was observed to improve by a factor of between 1.00 and 4.73. Our proposed model has broad applicability to various IoT applications and generally in MASs that have fault tolerance or reliability requirements, such as in cloud computing and autonomous vehicles. Full article
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Review

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33 pages, 4275 KiB  
Review
Machine Learning-Enabled Internet of Things (IoT): Data, Applications, and Industry Perspective
by Jamal Bzai, Furqan Alam, Arwa Dhafer, Miroslav Bojović, Saleh M. Altowaijri, Imran Khan Niazi and Rashid Mehmood
Electronics 2022, 11(17), 2676; https://doi.org/10.3390/electronics11172676 - 26 Aug 2022
Cited by 40 | Viewed by 16259
Abstract
Machine learning (ML) allows the Internet of Things (IoT) to gain hidden insights from the treasure trove of sensed data and be truly ubiquitous without explicitly looking for knowledge and data patterns. Without ML, IoT cannot withstand the future requirements of businesses, governments, [...] Read more.
Machine learning (ML) allows the Internet of Things (IoT) to gain hidden insights from the treasure trove of sensed data and be truly ubiquitous without explicitly looking for knowledge and data patterns. Without ML, IoT cannot withstand the future requirements of businesses, governments, and individual users. The primary goal of IoT is to perceive what is happening in our surroundings and allow automation of decision-making through intelligent methods, which will mimic the decisions made by humans. In this paper, we classify and discuss the literature on ML-enabled IoT from three perspectives: data, application, and industry. We elaborate with dozens of cutting-edge methods and applications through a review of around 300 published sources on how ML and IoT work together to play a crucial role in making our environments smarter. We also discuss emerging IoT trends, including the Internet of Behavior (IoB), pandemic management, connected autonomous vehicles, edge and fog computing, and lightweight deep learning. Further, we classify challenges to IoT in four classes: technological, individual, business, and society. This paper will help exploit IoT opportunities and challenges to make our societies more prosperous and sustainable. Full article
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9 pages, 773 KiB  
Review
Monitoring of Cardiovascular Diseases: An Analysis of the Mobile Applications Available in the Google Play Store
by Hanna Vitaliyivna Denysyuk, João Amado, Norberto Jorge Gonçalves, Eftim Zdravevski, Nuno M. Garcia and Ivan Miguel Pires
Electronics 2022, 11(12), 1881; https://doi.org/10.3390/electronics11121881 - 15 Jun 2022
Cited by 1 | Viewed by 2094
Abstract
Cardiovascular diseases have always been here, but there has been an increase in their numbers over time. Even though there are in the digital world a few applications to help with this kind of problem, there are not enough to fulfill the needs [...] Read more.
Cardiovascular diseases have always been here, but there has been an increase in their numbers over time. Even though there are in the digital world a few applications to help with this kind of problem, there are not enough to fulfill the needs of the patients. This study reviews mobile applications that allow patients to monitor and report cardiovascular diseases. It presents a review of 14 mobile applications that were free to download in Portugal and classified and compared according to their characteristics. The selection criteria combined the following keywords: “patient”, “cardiac/or heart”, “report”, and (“tracking” or “monitoring”). Based on the analysis, we point out the errors of the applications and present some solutions. To finish, we investigated how mobile applications can help patients track and self-report cardiovascular diseases. Full article
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