Special Issue "Safe and Reliable AI for Smart Sustainable Cities"

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer and Engineering Science and Symmetry/Asymmetry".

Deadline for manuscript submissions: closed (22 December 2021).

Special Issue Editors

Dr. Ivan Izonin
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Guest Editor
Department of Artificial Intelligence, Lviv Polytechnic National University, Lviv, Ukraine
Interests: artificial neural networks, few-shot learning, ensemble learning, non-iterative learning algorithms, engineering and medical applications
Prof. Dr. Stephane Chretien
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Guest Editor
Laboratoire ERIC, Université Lyon 2, France
Interests: statistical learning, classification and clustering, optimisation algorithms, engineering and biomedical applications
Dr. Ali Ebrahimnejad
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Guest Editor
Department of Mathematics, Islamic Azad University Qaemshahr Branch, Qaemshahr, Iran
Interests: fuzzy optimization, data envelopment analysis, network flows, multi objective decision making, multi attribute decision making

Special Issue Information

Dear Colleagues,

Today, most of the world's inhabitants live in cities. The development of ICT and other technologies creates favorable conditions for the government and municipalities to build smart city systems for various purposes. The main aim is to increase the level of comfort of living in smart cities. The latest developments in computational intelligence, powerful hardware development, and the ability to process extremely large datasets collected using millions of connected multisensory devices, open up new opportunities for the development and improvement of all smart city systems. This creates unique opportunities for effective promotion and support of the transformation of urban areas; however, there are still several requirements to be addressed for the development and operation of such systems.

Experts are increasingly considering the concept of the smart sustainable city that involves all the benefits of smart cities, as it focuses on a continuous transformative process. It must ensure the sustainable development of a smart city and open up different types of capacities for its inhabitants. To implement this concept, it is necessary to develop stable, secure, reliable, and interoperable infrastructure systems to support ICT-based applications and services. In today's post-industrial society, the creation of such infrastructure systems requires the combined use of IoT and Big Data technologies as well as artificial intelligence tools. The automation of many processes in smart city subsystems depends on the reliability and security of the AI-based solutions underlying them. These two conditions are critical for smart sustainable city systems, because the wellbeing and safety of people depend on them.

This Special Issue will cover safe and reliable AI-based solutions, which rely on fast and accurate processing of various sensory data for the control and sustainable development of smart city subsystems for different purposes. We welcome applied solutions using various AI methods and tools that demonstrate readiness for practical application in various systems and services of a smart sustainable city.

Topics include, but not limited to:

  • IoT-based solutions for data collection, aggregation, and transmission
  • Machine learning and cognitive computing for supporting smart city's services
  • Modernization of the telecommunication infrastructure in smart cities
  • Reliable AI for service delivery in ICT infrastructure
  • Self-adaptation and self-management in IoT-based smart systems
  • Big data management and analytics in complex systems
  • Technology-enabled and integrated transport and logistic systems
  • Pollution and waste management in urban ecosystems
  • Electricity reliability, efficiency and power stability in urban areas
  • Resource-efficient solutions for smart municipal management services
  • Safe software and integrated solutions for smart sustainable cities
  • Emerging technologies for the development of sustainable cities

Dr. Ivan Izonin
Prof. Stephane Chretien
Dr. Ali Ebrahimnejad
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 papers will be 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. Symmetry 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 1800 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

  • IoT
  • reliable AI
  • safe software
  • smart sustainable city
  • artificial neural networks
  • telecommunication infrastructure
  • ICT technologies
  • machine learning
  • big data
  • smart transport
  • smart grids

Published Papers (5 papers)

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Research

Article
Applying Ateb–Gabor Filters to Biometric Imaging Problems
Symmetry 2021, 13(4), 717; https://doi.org/10.3390/sym13040717 - 19 Apr 2021
Viewed by 636
Abstract
This article presents a new method of image filtering based on a new kind of image processing transformation, particularly the wavelet-Ateb–Gabor transformation, that is a wider basis for Gabor functions. Ateb functions are symmetric functions. The developed type of filtering makes it possible [...] Read more.
This article presents a new method of image filtering based on a new kind of image processing transformation, particularly the wavelet-Ateb–Gabor transformation, that is a wider basis for Gabor functions. Ateb functions are symmetric functions. The developed type of filtering makes it possible to perform image transformation and to obtain better biometric image recognition results than traditional filters allow. These results are possible due to the construction of various forms and sizes of the curves of the developed functions. Further, the wavelet transformation of Gabor filtering is investigated, and the time spent by the system on the operation is substantiated. The filtration is based on the images taken from NIST Special Database 302, that is publicly available. The reliability of the proposed method of wavelet-Ateb–Gabor filtering is proved by calculating and comparing the values of peak signal-to-noise ratio (PSNR) and mean square error (MSE) between two biometric images, one of which is filtered by the developed filtration method, and the other by the Gabor filter. The time characteristics of this filtering process are studied as well. Full article
(This article belongs to the Special Issue Safe and Reliable AI for Smart Sustainable Cities)
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Article
Performance Analysis of Wireless Local Area Network for a High-/Low-Priority Traffic Ratio at Different Numbers of Access Categories
Symmetry 2021, 13(4), 693; https://doi.org/10.3390/sym13040693 - 15 Apr 2021
Cited by 1 | Viewed by 508
Abstract
The performance of Wireless Local Area Network (WLAN) is highly dependent on the processes that are implemented in the Medium Access Control (MAC) sublayer regulated by the IEEE 802.11 standard. In turn, various parameters affect the performance of the MAC sublayer, the most [...] Read more.
The performance of Wireless Local Area Network (WLAN) is highly dependent on the processes that are implemented in the Medium Access Control (MAC) sublayer regulated by the IEEE 802.11 standard. In turn, various parameters affect the performance of the MAC sublayer, the most important of which is the number of stations in the network and the offered load. With the massive growth of multimedia traffic, research of the network performance depending on traffic types is relevant. In this paper, we present the impact of a high-/low-priority traffic ratio on WLAN performance with different numbers of access categories. The simulation results show different impact of high-/low-priority traffic ratio on the performance of the MAC sublayer of wireless LANs depending on different network-sizes and on network conditions. Performance of the large network with two access categories and with the prevalent high-priority traffic is significantly higher than in the case of using four categories on the MAC sublayer. This allows us to conclude that the performance improvement of the large network with the prevalent high-priority traffic can be achieved by an adaptive adjustment of the access categories number on the MAC sublayer. Full article
(This article belongs to the Special Issue Safe and Reliable AI for Smart Sustainable Cities)
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Article
Parallelization of Finding the Current Coordinates of the Lidar Based on the Genetic Algorithm and OpenMP Technology
Symmetry 2021, 13(4), 666; https://doi.org/10.3390/sym13040666 - 13 Apr 2021
Viewed by 494
Abstract
The problem of determining the position of the lidar with optimal accuracy is relevant in various fields of application. This is an important task of robotics that is widely used as a model when planning the route of vehicles, flight control systems, navigation [...] Read more.
The problem of determining the position of the lidar with optimal accuracy is relevant in various fields of application. This is an important task of robotics that is widely used as a model when planning the route of vehicles, flight control systems, navigation systems, machine learning, and managing economic efficiency, a study of land degradation processes, planning and control of agricultural production stages, land inventory to evaluations of the consequences of various environmental impacts. The paper provides a detailed analysis of the proposed parallelization algorithm for solving the problem of determining the current position of the lidar. To optimize the computing process in order to accelerate and have the possibility of obtaining a real-time result, the OpenMP parallel computing technology is used. It is also possible to significantly reduce the computational complexity of the successive variant. A number of numerical experiments on the multi-core architecture of modern computers have been carried out. As a result, it was possible to accelerate the computing process about eight times and achieve an efficiency of 0.97. It is shown that a special difference in time of execution of a sequential and parallel algorithm manages to increase the number of measurements of lidar and iterations, which is relevant in simulating various problems of robotics. The obtained results can be substantially improved by selecting a computing system where the number of cores is more than eight. The main areas of application of the developed method are described, its shortcomings and prospects for further research are provided. Full article
(This article belongs to the Special Issue Safe and Reliable AI for Smart Sustainable Cities)
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Article
The Additive Input-Doubling Method Based on the SVR with Nonlinear Kernels: Small Data Approach
Symmetry 2021, 13(4), 612; https://doi.org/10.3390/sym13040612 - 06 Apr 2021
Cited by 4 | Viewed by 634
Abstract
The problem of effective intellectual analysis in the case of handling short datasets is topical in various application areas. Such problems arise in medicine, economics, materials science, science, etc. This paper deals with a new additive input-doubling method designed by the authors for [...] Read more.
The problem of effective intellectual analysis in the case of handling short datasets is topical in various application areas. Such problems arise in medicine, economics, materials science, science, etc. This paper deals with a new additive input-doubling method designed by the authors for processing short and very short datasets. The main steps of the method should include the procedure of data augmentation within the existing dataset both in rows and columns (without training), the use of nonlinear SVR to implement the training procedure, and the formation of the result based on the author’s procedure. The authors show that the developed data augmentation procedure corresponds to the principles of axial symmetry. The training and application procedures of the method developed are described in detail, and two algorithmic implementations are presented. The optimal parameters of the method operation were selected experimentally. The efficiency of its work during the processing of short datasets for solving the prediction task was established experimentally by comparison with other methods of this class. The highest prediction accuracy based on both proposed algorithmic implementations of a method among all of the investigated ones was defined. The main areas of application of the developed method are described, and its shortcomings and prospects of further research are given. Full article
(This article belongs to the Special Issue Safe and Reliable AI for Smart Sustainable Cities)
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Article
Modeling of the Schemes for Organizing a Session of Person–System Interactions in the Information System for Critical Use Which Operates in a Wireless Communication Environment
Symmetry 2021, 13(3), 391; https://doi.org/10.3390/sym13030391 - 27 Feb 2021
Viewed by 648
Abstract
In this article, for the first time, a new mathematical model of the schemes for organizing a session of person–system interactions between the registration center server of the information system for critical use (ISCU) and the terminal of the person-user in a wireless [...] Read more.
In this article, for the first time, a new mathematical model of the schemes for organizing a session of person–system interactions between the registration center server of the information system for critical use (ISCU) and the terminal of the person-user in a wireless communication environment are presented. In contrast to the existing literature, this article uses the mathematical apparatus of queuing systems to describe the schemes of organizing the stochastic process of a session of person–system interaction in discrete or continuous time, namely, models of the type Geo/Geo/1 with group arrival and ordinary service for the case of discrete representation of time and models of the type M/G/1 for the case of continuous time representation. The use of the mathematical apparatus of queuing systems in the studies made it possible to obtain analytical expressions for comparing formalized schemes for organizing the person–system interaction according to such functional characteristics as the average time of downloading a finite number of data blocks into the terminal of the target person-user (average time that the request spent the server of the information system). Full article
(This article belongs to the Special Issue Safe and Reliable AI for Smart Sustainable Cities)
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