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Electronics
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Smart Electronics, Energy, and IoT Infrastructures for Smart Cities
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Smart Electronics, Energy, and IoT Infrastructures for Smart Cities

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: 1 August 2024 | Viewed by 5458

Special Issue Editors

Dr. Zheng Xu

E-Mail Website
Guest Editor
School of Computer Science, Shanghai University, Shanghai 201142, China
Interests: IoT; cloud computing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jemal Abawajy

E-Mail Website
Guest Editor
Faculty of Science, Engineering and Built Environment, Deakin University, Burwood, VIC 3125, Australia
Interests: cyber security; blockchain; internet of things; cloud computing; artificial intelligence applications in business
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The integration of sophisticated artificial intelligence technology into smart energy systems and grids, will require a multi-fold understanding of computational, economic and social issues. This kind of socio-technical platform and integration needs an initial definition of the domain and a well-grounded specification of the research problem. The quest for sustainable development has involved society, academia and industry in finding tangible solutions for the development of the world beyond the post-industrial society and its implications. Consequently, not only the new processes associated with the changes, but also the literature describing the resulted challenges have been enriched. The evolution of smart cities research integrates multidisciplinary contributions. Sophisticated disruptive technologies set new challenges for the investigation of sustainable models of economic development. The research issue of energy management is amongst of the core application areas for both smart cities research and disruptive technologies adoption. In our work, this investigation is a key research objective.

The artificial intelligence domain, with advanced machine learning and cognitive computing capabilities, seems to be a key to enabling unforeseen efficiency capabilities in the context of smart energy grids. This Special Issue intends to contribute with a novel approach for the development of a theoretical framework for a scientific debate on how AI can enhance the efficiency of the RE sector towards economic efficiency and sustainability. In the context of this Special Issue, which is related to future smart cities research, we contribute a new significant item in the research agenda: AI-driven RE services for maximum social impact and economic efficiency. The main contribution of this special issue will be the integration of social sciences research with advanced information systems research.

Subject of interests include, but are not limited to:

  • smart match of supply with demand for smart cities;
  • intelligent storage for smart cities;
  • centralized control system for smart cities;
  • smart microgrids for smart cities;
  • grid stability and reliability, safety operations;
  • accurate demand forecast and weather forecast;
  • efficient demand-side management;
  • energy storage operations;
  • market design and operations.

You may choose our Joint Special Issue in Smart Cities.

Dr. Zheng Xu
Prof. Dr. Jemal Abawajy
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

  • electronics
  • energy
  • IoT infrastructures
  • smart cities

Published Papers (4 papers)

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Research

30 pages, 3877 KiB  
Article
Detection of Vulnerabilities in Smart Buildings Using the Shodan Tool
by Sofía Mulero-Palencia and Victor Monzon Baeza
Electronics 2023, 12(23), 4815; https://doi.org/10.3390/electronics12234815 - 28 Nov 2023
Viewed by 1538
Abstract
Smart buildings, integral components of modern urban landscapes, are confronted with diverse vulnerabilities that jeopardize system robustness, cybersecurity, data confidentiality, and the well-being of the occupants. This work aimed to identify and evaluate vulnerabilities specific to smart buildings, introducing an innovative assessment approach [...] Read more.
Smart buildings, integral components of modern urban landscapes, are confronted with diverse vulnerabilities that jeopardize system robustness, cybersecurity, data confidentiality, and the well-being of the occupants. This work aimed to identify and evaluate vulnerabilities specific to smart buildings, introducing an innovative assessment approach leveraging the Shodan tool. The analysis comprised three stages: information collection, result extraction using Shodan, and vulnerability identification, culminating in a comprehensive evaluation. This study pioneers the use of Shodan for smart building vulnerability detection, together with databases and associated nomenclature, to serve as a robust foundational tutorial for future research. The findings yielded a meticulous analysis of primary security risks inherent in building systems, advocating for implementing targeted measures to mitigate potential impacts. Additionally, this study proposes an evaluation methodology encompassing metrics to gauge the effect of vulnerabilities on integrity, availability, and scope. By addressing insecure configurations, deployment inadequacies, and suboptimal cybersecurity practices, this framework fortifies smart buildings against potential threats. This study’s originality lies in its Shodan-centric framework, revolutionizing the approach to smart building applications and vulnerability detection. This research contributes to the field by identifying critical vulnerabilities and proposing effective mitigation strategies, thereby elevating the overall security and safety of interconnected smart spaces. Full article
(This article belongs to the Special Issue Smart Electronics, Energy, and IoT Infrastructures for Smart Cities)
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12 pages, 5115 KiB  
Article
Avoid Bogie Bearing Failure of IGBT Inverter Fed EMUs and Locomotives
by Liguo Wang, Xiujuan Yang and Xiangzhen Yan
Electronics 2023, 12(13), 2998; https://doi.org/10.3390/electronics12132998 - 07 Jul 2023
Viewed by 1170
Abstract
Three current paths are proposed, and theoretical analysis and laboratory tests are carried out to investigate the root causes of bearing failure in IGBT inverter-fed locomotives and EMUs. The three types of current paths that run through the drive unit bearings and axle [...] Read more.
Three current paths are proposed, and theoretical analysis and laboratory tests are carried out to investigate the root causes of bearing failure in IGBT inverter-fed locomotives and EMUs. The three types of current paths that run through the drive unit bearings and axle box bearings used on EMUs and electric locomotives are classified as the primary side current path, the main traction system current path, and the current path between the vehicles of the EMU or electric locomotive and the vehicles it hauls. The research found that the EDM current path in the main traction system caused by common mode voltage is distinguished as the main cause resulting in the failure of the bogie motor bearings or the bearings of the load connected to the motor shaft. The cause of common mode voltage is analyzed, and the thresholds of current density and voltage without causing bearing damage are analyzed and presented. The lab tests carried out on the bearings on the main traction system’s current path verified that the current path does exist. The proof to identify electric erosion, such as craters and washboards, and corresponding measures to prevent the failure of bogie bearings are proposed. Further research about the other two current paths is urgent and necessary. Full article
(This article belongs to the Special Issue Smart Electronics, Energy, and IoT Infrastructures for Smart Cities)
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12 pages, 1824 KiB  
Article
Cross-Perspective Human Behavior Recognition Based on a Joint Sparse Representation and Distributed Adaptation Algorithm Combined with Wireless Optical Transmission
by Xiaomo Yu, Long Long, Yang Ou and Xiaomeng Zhou
Electronics 2023, 12(9), 1980; https://doi.org/10.3390/electronics12091980 - 24 Apr 2023
Viewed by 719
Abstract
Traditional human behavior recognition needs many training samples. Signal transmission of images and videos via visible light in the body is crucial for detecting specific actions to accelerate behavioral recognition. Joint sparse representation techniques improve identification accuracy by utilizing multi-perspective information, while distributional [...] Read more.
Traditional human behavior recognition needs many training samples. Signal transmission of images and videos via visible light in the body is crucial for detecting specific actions to accelerate behavioral recognition. Joint sparse representation techniques improve identification accuracy by utilizing multi-perspective information, while distributional adaptive techniques enhance robustness by adjusting feature distributions between different perspectives. Combining both techniques enhances recognition accuracy and robustness, enabling efficient behavior recognition in complex environments with multiple perspectives. In this paper, joint sparse representation has been combined with distributed adaptation algorithm to recognize human behavior under the fusion algorithm, and verify the feasibility of the fusion algorithm through experimental analysis. The research objective of this article is to explore the use of the combination of joint sparse representation technology and distributed adaptive technology in the recall and accuracy of human detection, combined with the cross perspective human behavior recognition of wireless optical transmission. The experimental results showed that in the process of human detection, the recall and precision of the fusion algorithm in this paper reached 92% and 90% respectively, which are slightly higher than the comparison algorithm. In the experiment of recognition accuracy of different actions, the recognition accuracy of the fusion algorithm in this paper was also higher than that of the control algorithm. It can be seen that the fusion of joint sparse representation and distributed adaptation algorithms, as well as wireless communication light technology, are of great significance for human behavior recognition. Full article
(This article belongs to the Special Issue Smart Electronics, Energy, and IoT Infrastructures for Smart Cities)
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15 pages, 4135 KiB  
Article
Consensus-Based Distributed Optimal Dispatch of Integrated Energy Microgrid
by Shanna Luo, Kaixiang Peng, Changbin Hu and Rui Ma
Electronics 2023, 12(6), 1468; https://doi.org/10.3390/electronics12061468 - 20 Mar 2023
Cited by 2 | Viewed by 1164
Abstract
In recent years, the energy form of microgrids is constantly enriching, while the decentralization requirements of microgrids are constantly developing. Considering the economic benefits of an integrated energy microgrid (IEM), this paper focuses on the distributed optimal dispatch of IEM based on a [...] Read more.
In recent years, the energy form of microgrids is constantly enriching, while the decentralization requirements of microgrids are constantly developing. Considering the economic benefits of an integrated energy microgrid (IEM), this paper focuses on the distributed optimal dispatch of IEM based on a consensus algorithm. The microgrid structure and multi-agent system are combined organically to get the decentralized architecture of IEM. This paper takes the incremental cost rate of each unit in IEM as a consensus variable. Based on the consensus theory, iterative optimization is carried out to achieve the optimal economic operation and power supply-demand balance of IEM. The distributed optimal dispatch is realized, and the convergence of the algorithm is proved. The experiment is carried out with LabVIEW and MATLAB and verifies the effectiveness of the algorithm. The results show that the distributed optimal dispatch algorithm can effectively reduce the power generation cost of the integrated energy system. Full article
(This article belongs to the Special Issue Smart Electronics, Energy, and IoT Infrastructures for Smart Cities)
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