Smart Electronics, Energy, and IoT Infrastructures for Smart Cities

Zheng Xu; Jemal Abawajy

doi:10.3390/electronics14030407

and

¹

School of Computer and Information Engineering, Institute for Artificial Intelligence, Shanghai Polytechnic University, Shanghai 201209, China

²

Faculty of Science, Engineering and Built Environment, Deakin University, Burwood, VIC 3125, Australia

^*

Author to whom correspondence should be addressed.

Electronics2025, 14(3), 407;https://doi.org/10.3390/electronics14030407

This article belongs to the Special Issue Smart Electronics, Energy, and IoT Infrastructures for Smart Cities

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1. Introduction

The incorporation of advanced AI into energy and grids necessitates a comprehensive understanding of smart cities. The ubiquitous deployment of IoT has facilitated the proliferation of groundbreaking applications across diverse industries [1]. The smart grid, an evolving paradigm in contemporary power infrastructure, facilitates a bidirectional flow of electricity and data among peers within electricity system networks. The development and integration of this socio-technical platform require a clear definition and a solid formulation [2]. As a result, both the ongoing processes associated with these changes and the literature documenting the accompanying challenges have grown more diverse. Research on Smart Cities integrates contributions from multiple disciplines, while advanced disruptive technologies introduce new challenges when exploring sustainable economic models. Energy management is a central area of focus for both Smart Cities research and the implementation of disruptive technologies, making it a key objective of our study [3].

This Special Issue represents a pivotal application domain for both smart cities research and the implementation of disruptive technologies.

2. Brief Description of the Published Articles

To investigate the damage caused by storage tank explosions in urban chemical industrial parks, Wang et al. (Contributor 1) enable the intelligent prediction and prevention of risks within chemical industrial parks. Cui et al. (Contributor 2) investigated the likelihood of tank explosions causing harm by analyzing the progression of damage from such explosions. They presented an analytical approach to determine the most critical situation. Mulero-Palencia and Monzon Baeza (Contributor 3) pioneered the utilization of Shodan for detecting vulnerabilities in smart buildings, databases, and related nomenclature. Their findings are presented through a meticulous examination of the primary security risks inherent in building systems. Wang et al. (Contributor 4) pinpointed the EDM in the main traction system as the main cause of failure in bogie motor bearings or bearings linked to the motor shaft. By combining both techniques, recognition accuracy and robustness are enhanced, as was achieved in the research of Long et al. (Contributor 5), allowing for efficient behavior recognition in complex, multi-perspective environments. Luo et al. (Contributor 6) utilized the Integrated Energy Management (IEM) system as a consensus variable.

3. Conclusions and Further Directions

This Special Issue aims to present a theoretical framework that fosters scientific discussion on how IoT can improve the efficiency, economic viability, and sustainability of smart cities. Future research on smart city development should emphasize sustainable technological integration and citizen-centric methodologies.

Conflicts of Interest

The author declares no conflicts of interest.

List of Contributions

Cui, T.; Wang, Y.; Xu, G. The Storage Tank Explosion Damage and the Effectiveness of Control Measures in the Chemical Industrial Parks of Smart Cities. Electronics 2024, 13, 2757.
Wang, Y.; Cui, T.; Xu, G. Research on the Evolution Models and Risk of Disaster-Induced Storage Tank Explosions in a Smart City. Electronics 2024, 13, 2078.
Mulero-Palencia, S.; Monzon Baeza, V. Detection of Vulnerabilities in Smart Buildings Using the Shodan Tool. Electronics 2023, 12, 4815.
Wang, L.; Yang, X.; Yan, X. Avoid Bogie Bearing Failure of IGBT Inverter Fed EMUs and Locomotives. Electronics 2023, 12, 2998.
Yu, X.; Long, L.; Ou, Y.; Zhou, X. Cross-Perspective Human Behavior Recognition Based on a Joint Sparse Representation and Distributed Adaptation Algorithm Combined with Wireless Optical Transmission. Electronics 2023, 12, 1980.
Luo, S.; Peng, K.; Hu, C.; Ma, R. Consensus-Based Distributed Optimal Dispatch of Integrated Energy Microgrid. Electronics 2023, 12, 1468.

References

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