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Electronics
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New Insights of Internet of Things in Industry 4.0
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New Insights of Internet of Things in Industry 4.0

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

Deadline for manuscript submissions: 15 September 2025 | Viewed by 935

Special Issue Editors

Dr. Hu Yuan

E-Mail Website
Guest Editor
School of Computer Science and Mathematics, Kingston University, London KT2 7LB, UK
Interests: Internet of Things; cyber–physical systems; cyber security
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Carsten Maple

E-Mail Website
Guest Editor
Cyber Security Centre, WMG, University of Warwick, Gibbett Hill Road, Coventry CV4 7AL, UK
Interests: security in cyber physical systems; privacy enhancing technologies; human aspects of security; threat modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Introduction: Industry 4.0 represents the Fourth Industrial Revolution, where advanced digital technologies—such as the Internet of Things (IoT), cyber–physical systems, cloud computing, and artificial intelligence—are seamlessly integrated into manufacturing and industrial processes. This convergence transforms traditional production systems into smart factories that boast real-time monitoring, predictive maintenance, and data-driven decision-making, all contributing to improved efficiency, flexibility, and sustainability. The trend toward ubiquitous connectivity is reshaping supply chains and presents new challenges, including cybersecurity vulnerabilities, interoperability issues, and the need for standardized protocols.

In this Special Issue, we invite academic researchers to contribute original articles that explore these multifaceted dimensions. Potential research topics include IoT security and privacy in industrial environments, AI and machine learning integration for process optimization, developing interoperable cyber–physical systems, and creating digital twin technologies for enhanced simulation and control. We also welcome studies on human–machine interactions, the socio-economic impacts of Industry 4.0, and sustainable manufacturing practices. By bridging rigorous theoretical analysis with practical applications, your contributions will help advance our understanding of Industry 4.0’s transformative potential and set the stage for future innovations.

Dr. Hu Yuan
Prof. Dr. Carsten Maple
Guest Editors

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. Electronics is an international peer-reviewed open access semimonthly 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 2400 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)
  • Industry 4.0
  • cybersecurity
  • cyber–physical systems
  • data-driven decision-making
  • smart factories
  • digital transformation
  • interoperability
  • Artificial Intelligence (AI)
  • sustainable manufacturing

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Published Papers (1 paper)

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35 pages, 2826 KiB  
Article
AI-Driven Anomaly Detection for Securing IoT Devices in 5G-Enabled Smart Cities
by Manuel J. C. S. Reis
Electronics 2025, 14(12), 2492; https://doi.org/10.3390/electronics14122492 - 19 Jun 2025
Viewed by 700
Abstract
This paper proposes a novel AI-driven anomaly detection framework designed to enhance cybersecurity in IoT-enabled smart cities operating over 5G networks. While prior research has explored deep learning for anomaly detection, most existing systems rely on single-model architectures, employ centralized training, or lack [...] Read more.
This paper proposes a novel AI-driven anomaly detection framework designed to enhance cybersecurity in IoT-enabled smart cities operating over 5G networks. While prior research has explored deep learning for anomaly detection, most existing systems rely on single-model architectures, employ centralized training, or lack support for real-time, privacy-preserving deployment—limiting their scalability and robustness. To address these gaps, our system integrates a hybrid deep learning model combining autoencoders, long short-term memory (LSTM) networks, and convolutional neural networks (CNNs) to detect spatial, temporal, and reconstruction-based anomalies. Additionally, we implement federated learning and edge AI to enable decentralized, privacy-preserving threat detection across distributed IoT nodes. The system is trained and evaluated using a combination of real-world (CICIDS2017, TON_IoT, UNSW-NB15) and synthetically generated attack data, including adversarial perturbations. Experimental results show our hybrid model achieves a precision of 97.5%, a recall of 96.2%, and an F1 score of 96.8%, significantly outperforming traditional IDS and standalone deep learning methods. These findings validate the framework’s effectiveness and scalability, making it suitable for real-time intrusion detection and autonomous threat mitigation in smart city environments. Full article
(This article belongs to the Special Issue New Insights of Internet of Things in Industry 4.0)
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