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Applied Sciences
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Technologies and Services of AI, Big Data, and Network for...
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Technologies and Services of AI, Big Data, and Network for Smart City

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 9795

Special Issue Editors

Prof. Dr. Jin-Woo Jung

E-Mail Website
Guest Editor
Department of Computer Science and Engineering, Dongguk University, Seoul 04620, Korea
Interests: informatics; computer science; intelligent systems; fuzzy logics
Special Issues, Collections and Topics in MDPI journals
Dr. Junho Jeong

E-Mail Website
Guest Editor
Computer Science and Engineering, Dongguk University, Seoul, Korea
Interests: information security; distributed system; privacy preserving; network security; secure software

Special Issue Information

Dear Colleagues,

Since ancient times, cities have been developed to be safe and convenient by applying various cutting-edge technologies. Today, AI, big data including bioinformatics and network technologies are transforming cities into safer and more convenient living spaces. Various applications and services could be provided to increase safety, convenience, health, quality of human life and efficiency by recognizing the environment through various sensors in the city, transmitting the collected data through the network, and analyzing the collected big data with artificial intelligence.

This special issue aims to present various original technologies and services in the areas of artificial intelligence, big data including bioinformatics, and networks to build a safe, efficient and convenient smart city.

Prof. Dr. Jin-Woo Jung
Dr. Junho Jeong
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. Applied Sciences 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.

Published Papers (4 papers)

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Research

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20 pages, 1860 KiB  
Article
Generating Synthetic Dataset for ML-Based IDS Using CTGAN and Feature Selection to Protect Smart IoT Environments
by Saleh Alabdulwahab, Young-Tak Kim, Aria Seo and Yunsik Son
Appl. Sci. 2023, 13(19), 10951; https://doi.org/10.3390/app131910951 - 04 Oct 2023
Cited by 1 | Viewed by 1459
Abstract
Networks within the Internet of Things (IoT) have some of the most targeted devices due to their lightweight design and the sensitive data exchanged through smart city networks. One way to protect a system from an attack is to use machine learning (ML)-based [...] Read more.
Networks within the Internet of Things (IoT) have some of the most targeted devices due to their lightweight design and the sensitive data exchanged through smart city networks. One way to protect a system from an attack is to use machine learning (ML)-based intrusion detection systems (IDSs), significantly improving classification tasks. Training ML algorithms require a large network traffic dataset; however, large storage and months of recording are required to capture the attacks, which is costly for IoT environments. This study proposes an ML pipeline using the conditional tabular generative adversarial network (CTGAN) model to generate a synthetic dataset. Then, the synthetic dataset was evaluated using several types of statistical and ML metrics. Using a decision tree, the accuracy of the generated dataset reached 0.99, and its lower complexity reached 0.05 s training and 0.004 s test times. The results show that synthetic data accurately reflect real data and are less complex, making them suitable for IoT environments and smart city applications. Thus, the generated synthetic dataset can further train models to secure IoT networks and applications. Full article
(This article belongs to the Special Issue Technologies and Services of AI, Big Data, and Network for Smart City)
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22 pages, 3532 KiB  
Article
A Simulation-Based Approach to Evaluate the Performance of Automated Surveillance Camera Systems for Smart Cities
by Youngboo Kim and Junho Jeong
Appl. Sci. 2023, 13(19), 10682; https://doi.org/10.3390/app131910682 - 26 Sep 2023
Cited by 1 | Viewed by 1045
Abstract
A surveillance camera is the typical device that makes up a surveillance camera system in a modern city. It will still be a representative surveillance unit in future scenarios such as in smart cities. Furthermore, as the demand for public safety increases, a [...] Read more.
A surveillance camera is the typical device that makes up a surveillance camera system in a modern city. It will still be a representative surveillance unit in future scenarios such as in smart cities. Furthermore, as the demand for public safety increases, a massive number of surveillance cameras will be in use in the future, and an automated system that controls surveillance cameras intelligently will also be required. Meanwhile, installing a surveillance system without any verification system might not be cost-effective, so a simulation that evaluates the system’s performance is required in advance. For this reason, we introduce how to simulate a surveillance area and evaluate surveillance performance in this paper to assess a surveillance system consisting of large amounts of surveillance cameras. Our simulator defined the surveillance area as a pair of two-dimensional planes, which depend on various camera-related configurations. Both surveillance areas are used to determine if the moving object belongs to the coverage of a surveillance camera. In addition, our simulator adopts several performance indices to evaluate a surveillance camera system in terms of target detection and quality. The simulation study provides comprehensive results on how various components of the surveillance system affect the performance of the surveillance system, leading to the conclusion that building a sophisticated scheme to control a large number of surveillance cameras can provide a cost-effective and reliable surveillance system for smart cities. Full article
(This article belongs to the Special Issue Technologies and Services of AI, Big Data, and Network for Smart City)
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11 pages, 16701 KiB  
Article
Fusing Context Features and Spatial Attention to Improve Object Detection
by Tianjia Liu, Jinsong Wu, Xuze Luo and Guangquan Xu
Appl. Sci. 2023, 13(7), 4250; https://doi.org/10.3390/app13074250 - 27 Mar 2023
Cited by 1 | Viewed by 1080
Abstract
Context features are mostly used to determine the boundary of a target, which allows one to better locate an object. In this paper, we propose the fusion of the spatial attention mechanism and contextual features to simulate the recognition of objects based on [...] Read more.
Context features are mostly used to determine the boundary of a target, which allows one to better locate an object. In this paper, we propose the fusion of the spatial attention mechanism and contextual features to simulate the recognition of objects based on the human eye, thereby improving the detection accuracy of detectors. We chose the PASCAL VOC2007+2012 general dataset to test the generality of our method and examined the improved accuracy of our proposed detector on various targets. Our method showed improved accuracy for small targets and partially overlapping targets. Our proposed model improved the detector’s accuracy by 3.34%. Full article
(This article belongs to the Special Issue Technologies and Services of AI, Big Data, and Network for Smart City)
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Review

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36 pages, 4582 KiB  
Review
An Overview of Cyber Threats, Attacks and Countermeasures on the Primary Domains of Smart Cities
by Vasiliki Demertzi, Stavros Demertzis and Konstantinos Demertzis
Appl. Sci. 2023, 13(2), 790; https://doi.org/10.3390/app13020790 - 06 Jan 2023
Cited by 17 | Viewed by 5623
Abstract
A smart city is where existing facilities and services are enhanced by digital technology to benefit people and companies. The most critical infrastructures in this city are interconnected. Increased data exchange across municipal domains aims to manage the essential assets, leading to more [...] Read more.
A smart city is where existing facilities and services are enhanced by digital technology to benefit people and companies. The most critical infrastructures in this city are interconnected. Increased data exchange across municipal domains aims to manage the essential assets, leading to more automation in city governance and optimization of the dynamic offered services. However, no clear guideline or standard exists for modeling these data flows. As a result, operators, municipalities, policymakers, manufacturers, solution providers, and vendors are forced to accept systems with limited scalability and varying needs. Nonetheless, it is critical to raise awareness about smart-city cybersecurity and implement suitable measures to safeguard citizens’ privacy and security because cyber threats seem to be well-organized, diverse, and sophisticated. This study aims to present an overview of cyber threats, attacks, and countermeasures on the primary domains of smart cities (smart government, smart mobility, smart environment, smart living, smart healthcare, smart economy, and smart people). It aims to present information extracted from the state of the art so policymakers can perceive the critical situation and simultaneously be a valuable resource for the scientific community. It also seeks to offer a structural reference model that may guide the architectural design and implementation of infrastructure upgrades linked to smart city networks. Full article
(This article belongs to the Special Issue Technologies and Services of AI, Big Data, and Network for Smart City)
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