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Recent Advances in IoT and Cyber/Physical System

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A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Systems".

Deadline for manuscript submissions: closed (20 March 2024) | Viewed by 9211

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Special Issue Editor

Dr. Shingo Yamaguchi

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Guest Editor

Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Yamaguchi, Japan
Interests: IoT; cyber security; AI; data science
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) and cyber-physical systems (CPS) are technologies that seamlessly connect the physical and cyber worlds and have the potential to fundamentally change our society. The rapid development of IoT and CPS has led to major innovations in a variety of application areas, including smart manufacturing, smart homes, smart cities, autonomous driving, and smart healthcare.

This Special Issue aims to address the latest technological advances in all aspects of IoT and CPS, including theory, tools, applications, systems, testbeds, and field deployments. Both theoretical derivations and practical developments of IoT and CPS systems are welcome. Reviews and surveys on the latest developments in IoT and CPS are also welcome.

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

IoT and/or CPS architectures;
IoT and/or CPS-enabling technologies;
Approaches and methodologies for the IoT and/or CPS;
Development processes of IoT and/or CPS applications;
Integration of IoT and/or CPS applications;
Fog and edge computing, cloud, and SOA for the IoT and/or CPS;
Machine learning, deep learning, AI, and analytics in the IoT and/or CPS;
Empirical studies on the IoT and/or CPS;
Software applied for the IoT and/or CPS;
Security and privacy for the IoT and/or CPS;
Communications and networking for the IoT and/or CPS;
Formal models, model-driven development, simulation for IoT and/or CPS;
Blockchain solutions for IoT and/or CPS;
Quantum-enabling technologies for IoT and/or CPS;
Applications and ecosystems, e.g., agriculture, economy, education, energy, and smart cities.

Dr. Shingo Yamaguchi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Internet of Things (IoT)
cyber-Physical Systems (CPS)
architecture and platform
methodologies
security and privacy
communications and networking
ecosystems
machine learning, deep learning, ai, and analytics

Published Papers (5 papers)

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Research

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33 pages, 418 KiB

Open AccessArticle

A User Study on Modeling IoT-Aware Processes with BPMN 2.0

by Yusuf Kirikkayis, Michael Winter and Manfred Reichert

Information 2024, 15(4), 229; https://0-doi-org.brum.beds.ac.uk/10.3390/info15040229 - 18 Apr 2024

Viewed by 394

Abstract

Integrating the Internet of Things (IoT) into business process management (BPM) aims to increase the automation level, efficiency, transparency, and comprehensibility of the business processes taking place in the physical world. The IoT enables the seamless networking of physical devices, allowing for the enrichment of processes with real-time data about the physical world and, thus, for optimized process automation and monitoring. To realize these benefits, the modeling of IoT-aware processes needs to be appropriately supported. Despite the great attention paid to this topic, more clarity is needed about the current state of the art of corresponding modeling solutions. Capturing IoT characteristics in business process models visually or based on labels is essential to ensure effective design and communication of IoT-aware business processes. A clear discernibility of IoT characteristics can enable the precise modeling and analysis of IoT-aware processes and facilitate collaboration among different stakeholders. With an increasing number of process model elements, it becomes crucial that process model readers can understand the IoT aspects of business processes in order to make informed decisions and to optimize the processes with respect to IoT integration. This paper presents the results of a large user study (N = 249) that explored the perception of IoT aspects in BPMN 2.0 process models to gain insights into the IoT’s involvement in business processes that drive the successful implementation and communication of IoT-aware processes. Full article

(This article belongs to the Special Issue Recent Advances in IoT and Cyber/Physical System)

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29 pages, 3649 KiB

Open AccessArticle

Real-World Implementation and Performance Analysis of Distributed Learning Frameworks for 6G IoT Applications

by David Naseh, Mahdi Abdollahpour and Daniele Tarchi

Information 2024, 15(4), 190; https://0-doi-org.brum.beds.ac.uk/10.3390/info15040190 - 29 Mar 2024

Viewed by 719

Abstract

This paper explores the practical implementation and performance analysis of distributed learning (DL) frameworks on various client platforms, responding to the dynamic landscape of 6G technology and the pressing need for a fully connected distributed intelligence network for Internet of Things (IoT) devices. The heterogeneous nature of clients and data presents challenges for effective federated learning (FL) techniques, prompting our exploration of federated transfer learning (FTL) on Raspberry Pi, Odroid, and virtual machine platforms. Our study provides a detailed examination of the design, implementation, and evaluation of the FTL framework, specifically adapted to the unique constraints of various IoT platforms. By measuring the accuracy of FTL across diverse clients, we reveal its superior performance over traditional FL, particularly in terms of faster training and higher accuracy, due to the use of transfer learning (TL). Real-world measurements further demonstrate improved resource efficiency with lower average load, memory usage, temperature, power, and energy consumption when FTL is implemented compared to FL. Our experiments also showcase FTL’s robustness in scenarios where users leave the server’s communication coverage, resulting in fewer clients and less data for training. This adaptability underscores the effectiveness of FTL in environments with limited data, clients, and resources, contributing valuable information to the intersection of edge computing and DL for the 6G IoT. Full article

(This article belongs to the Special Issue Recent Advances in IoT and Cyber/Physical System)

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15 pages, 2085 KiB

Open AccessArticle

EACH-COA: An Energy-Aware Cluster Head Selection for the Internet of Things Using the Coati Optimization Algorithm

by Ramasubbareddy Somula, Yongyun Cho and Bhabendu Kumar Mohanta

Information 2023, 14(11), 601; https://0-doi-org.brum.beds.ac.uk/10.3390/info14110601 - 05 Nov 2023

Cited by 2 | Viewed by 1579

Abstract

In recent years, the Internet of Things (IoT) has transformed human life by improving quality of life and revolutionizing all business sectors. The sensor nodes in IoT are interconnected to ensure data transfer to the sink node over the network. Owing to limited battery power, the energy in the nodes is conserved with the help of the clustering technique in IoT. Cluster head (CH) selection is essential for extending network lifetime and throughput in clustering. In recent years, many existing optimization algorithms have been adapted to select the optimal CH to improve energy usage in network nodes. Hence, improper CH selection approaches require more extended convergence and drain sensor batteries quickly. To solve this problem, this paper proposed a coati optimization algorithm (EACH-COA) to improve network longevity and throughput by evaluating the fitness function over the residual energy (RER) and distance constraints. The proposed EACH-COA simulation was conducted in MATLAB 2019a. The potency of the EACH-COA approach was compared with those of the energy-efficient rabbit optimization algorithm (EECHS-ARO), improved sparrow optimization technique (EECHS-ISSADE), and hybrid sea lion algorithm (PDU-SLno). The proposed EACH-COA improved the network lifetime by 8–15% and throughput by 5–10%. Full article

(This article belongs to the Special Issue Recent Advances in IoT and Cyber/Physical System)

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19 pages, 1366 KiB

Open AccessArticle

Fortified-Grid: Fortifying Smart Grids through the Integration of the Trusted Platform Module in Internet of Things Devices

by Giriraj Sharma, Amit M. Joshi and Saraju P. Mohanty

Information 2023, 14(9), 491; https://0-doi-org.brum.beds.ac.uk/10.3390/info14090491 - 06 Sep 2023

Viewed by 1634

Abstract

This paper presents a hardware-assisted security primitive that integrates the Trusted Platform Module (TPM) into IoT devices for authentication in smart grids. Data and device security plays a pivotal role in smart grids since they are vulnerable to various attacks that could risk grid failure. The proposed Fortified-Grid security primitive provides an innovative solution, leveraging the TPM for attestation coupled with standard X.509 certificates. This methodology serves a dual purpose, ensuring the authenticity of IoT devices and upholding software integrity, an indispensable foundation for any resilient smart grid security system. TPM is a hardware security module that can generate keys and store them with encryption so they cannot be compromised. Formal security verification has been performed using the random or real Oracle (ROR) model and widely accepted AVISPA simulation tool, while informal security verification uses the DY and CK adversary model. Fortified-Grid helps to validate the attested state of IoT devices with a minimal network overhead of 1984 bits. Full article

(This article belongs to the Special Issue Recent Advances in IoT and Cyber/Physical System)

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Review

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20 pages, 868 KiB

Open AccessReview

A Survey of Internet of Things and Cyber-Physical Systems: Standards, Algorithms, Applications, Security, Challenges, and Future Directions

by Kwok Tai Chui, Brij B. Gupta, Jiaqi Liu, Varsha Arya, Nadia Nedjah, Ammar Almomani and Priyanka Chaurasia

Information 2023, 14(7), 388; https://0-doi-org.brum.beds.ac.uk/10.3390/info14070388 - 08 Jul 2023

Cited by 4 | Viewed by 3516

Abstract

The smart city vision has driven the rapid development and advancement of interconnected technologies using the Internet of Things (IoT) and cyber-physical systems (CPS). In this paper, various aspects of IoT and CPS in recent years (from 2013 to May 2023) are surveyed. It first begins with industry standards which ensure cost-effective solutions and interoperability. With ever-growing big data, tremendous undiscovered knowledge can be mined to be transformed into useful applications. Machine learning algorithms are taking the lead to achieve various target applications with formulations such as classification, clustering, regression, prediction, and anomaly detection. Notably, attention has shifted from traditional machine learning algorithms to advanced algorithms, including deep learning, transfer learning, and data generation algorithms, to provide more accurate models. In recent years, there has been an increasing need for advanced security techniques and defense strategies to detect and prevent the IoT and CPS from being attacked. Research challenges and future directions are summarized. We hope that more researchers can conduct more studies on the IoT and on CPS. Full article

(This article belongs to the Special Issue Recent Advances in IoT and Cyber/Physical System)

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