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Advanced Technologies for Smart Cities
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Advanced Technologies for Smart Cities

A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708). This special issue belongs to the section "Big Data, Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 22666

Special Issue Editors

Assoc. Prof. Michele Luglio

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Guest Editor
Department of Electronics Engineering, University of Rome “Tor Vergata”, Rome, Italy
Interests: network protocols; resource management; heterogeneous networks; 5G development
Dr. Mohamed Nabil Srifi

E-Mail Website
Guest Editor
Electronics and Telecommunications Systems Research Group, National School of Applied Sciences, Ibn Tofail University, Kenitra, Morocco
Assoc. Prof. Mounir Arioua

E-Mail Website
Guest Editor
National School of Applied Sciences, Abdelmalek Essaadi University, Tétouan 93000, Morocco
Interests: embedded system-based wireless communication; communication reliability and data compression in wireless sensor networks and IoT networks; smart environment and smart systems

Special Issue Information

Dear Colleagues,

Smart cities have become the emerging innovation of governments, institutions, and companies. Smart city is a concept applied to our living environments that incorporates the Internet of Things and other information and communication technologies as digital strategy, where citizens can improve the quality of their daily life through the experience of transformation of their surrounding environment. It identifies technology-intensive cities which provide the ability to gather, analyze, transmit, and disseminate information so as to transform services offered to the citizens, increase operational efficiency, improve the environment, and involve better decisions at the municipal level.

Information and Communication Technologies, including modern networks, are expected to perform an essential and decisive role in the sustainable development of new living environments. Smart cities are established relying on both prominent infrastructures (transportation systems, buildings, health systems, logistic systems, etc.) and advanced technologies where wireless communications and smart networks play a noteworthy intermediate role to connect smart systems (objects and sensors) together and to the Internet. Smart cities based on advanced communications technologies, which includes new generation networks, can provide leading services in everyday life such as e-services (education, health, commerce, and government), resource and environment management, real-time traffic monitoring, security, and safety.

Currently, information and communication technologies are significant for realizing the consistent vision of smart cities. However, it is still a complex and far-reaching development with many challenges in terms of design, optimization, standardization, sustainability, and interoperability. Therefore, there is a necessity to conduct research on further solutions to smart cities-assisted wireless communications and networks. 

This Special Issue focuses on original works, presented in the International Symposium on Advanced Electrical and Communication Technologies ISAECT2020 (www.isaect.org), on advanced technologies applied to smart cities, and current challenges and future opportunities in building smart networks and new wireless architectures in an efficient and sustainable way. Overall, the goal is to provide a thorough overview of the main topics around smart systems and advanced technologies and their envisioned integration in smart cities.

Authors of selected best papers presented in the International Symposium on Advanced Electrical and Communication Technologies ISAECT2020 (www.isaect.org) are solicited to submit an extended version of their works (at least by 50%) in all aspects of smart technologies and systems for smart cities applications. Submitted articles must not be currently considered elsewhere for publication.

The Special Issue seeks original contributions that address but are not limited to the following topics:

  • Smart systems, smart environments, and communication;
  • IoT networking and communication;
  • Space technologies;
  • Network infrastructure, applications, and services;
  • Architectures and protocols for smart cities;
  • Real-world deployments for IoT and smart systems;
  • Radio resource sharing;
  • Ad-hoc networking;
  • Interoperability issues on heterogeneous wireless communication;
  • Integration and co-existence of wireless communication and network technologies for smart cities;
  • Prototypes and testbeds of wireless communications and networks for smart cities;
  • Energy efficiency of wireless protocols and algorithms for smart cities;
  • Sensing technologies and applications for smart cities;
  • New architectures for WSN;
  • Low-power wireless technologies;
  • Routing and data transfer;
  • Security and privacy for smart systems and Internet of things;
  • Power consumption optimization;
  • Platforms and developments tools for a smart environment;
  • Data gathering, processing, and communication;
  • Distributed systems and smart networks;
  • Wearable technologies, visual sensing technologies;
  • Intelligent transportation systems and smart mobility;
  • Territorial intelligence;
  • Design and optimization of wireless heterogeneous networks for smart cities;
  • Cognitive networks and IoT for smart cities;
  • Smart grid in wireless networks for smart cities;
  • VANET communications.

Assoc. Prof. Michele Luglio
Prof. Mohamed Nabil Srifi
Assoc. Prof. Mounir Arioua
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. Journal of Sensor and Actuator Networks 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 2000 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 (3 papers)

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18 pages, 2427 KiB  
Article
Intelligent Machine Vision Model for Defective Product Inspection Based on Machine Learning
by Tajeddine Benbarrad, Marouane Salhaoui, Soukaina Bakhat Kenitar and Mounir Arioua
J. Sens. Actuator Netw. 2021, 10(1), 7; https://doi.org/10.3390/jsan10010007 - 28 Jan 2021
Cited by 74 | Viewed by 13007
Abstract
Quality control is one of the industrial tasks most susceptible to be improved by implementing technological innovations. As an innovative technology, machine vision enables reliable and fast 24/7 inspections and helps producers to improve the efficiency of manufacturing operations. The accessible data by [...] Read more.
Quality control is one of the industrial tasks most susceptible to be improved by implementing technological innovations. As an innovative technology, machine vision enables reliable and fast 24/7 inspections and helps producers to improve the efficiency of manufacturing operations. The accessible data by vision equipment will be used to identify and report defective products, understand the causes of deficiencies and allow rapid and efficient intervention in smart factories. From this perspective, the proposed machine vision model in this paper combines the identification of defective products and the continuous improvement of manufacturing processes by predicting the most suitable parameters of production processes to obtain a defect-free item. The suggested model exploits all generated data by various integrated technologies in the manufacturing chain, thus meeting the requirements of quality management in the context of Industry 4.0, based on predictive analysis to identify patterns in data and suggest corrective actions to ensure product quality. In addition, a comparative study between several machine learning algorithms, both for product classification and process improvement models, is performed in order to evaluate the designed system. The results of this study show that the proposed model largely meets the requirements for the proper implementation of these techniques. Full article
(This article belongs to the Special Issue Advanced Technologies for Smart Cities)
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21 pages, 15795 KiB  
Article
Novel Air Pollution Measurement System Based on Ethereum Blockchain
by Daniele Sofia, Nicoletta Lotrecchiano, Paolo Trucillo, Aristide Giuliano and Luigi Terrone
J. Sens. Actuator Netw. 2020, 9(4), 49; https://doi.org/10.3390/jsan9040049 - 17 Oct 2020
Cited by 20 | Viewed by 4838
Abstract
The need to protect sensitive data is growing, and environmental data are now considered sensitive. The application of last-generation procedures such as blockchains coupled with the implementation of new air quality monitoring technology allows the data protection and validation. In this work, the [...] Read more.
The need to protect sensitive data is growing, and environmental data are now considered sensitive. The application of last-generation procedures such as blockchains coupled with the implementation of new air quality monitoring technology allows the data protection and validation. In this work, the use of a blockchain applied to air pollution data is proposed. A blockchain procedure has been designed and tested. An Internet of Things (IoT)-based sensor network provides air quality data in terms of particulate matter of two different diameters, particulate matter (PM)10 and PM2.5, volatile organic compounds (VOC), and nitrogen dioxide (NO2) concentrations. The dataset also includes meteorological parameters and vehicular traffic information. This work foresees that the data, recovered from traditional Not Structured Query Language (NoSQL) database, and organized according to some specifications, are sent to the Ethereum blockchain daily automatically and with the possibility to choose the period of interest manually. There was also the development of a transaction management and recovery system aimed at retrieving data, formatting it according to the specifications and organizing it into files of various formats. The blockchain procedure has therefore been used to track data provided by air quality monitoring networks unequivocally. Full article
(This article belongs to the Special Issue Advanced Technologies for Smart Cities)
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13 pages, 403 KiB  
Article
Detecting System Fault/Cyberattack within a Photovoltaic System Connected to the Grid: A Neural Network-Based Solution
by Giovanni Battista Gaggero, Mansueto Rossi, Paola Girdinio and Mario Marchese
J. Sens. Actuator Netw. 2020, 9(2), 20; https://doi.org/10.3390/jsan9020020 - 20 Apr 2020
Cited by 13 | Viewed by 3661
Abstract
The large spread of Distributed Energy Resources (DERs) and the related cyber-security issues introduce the need for monitoring. The proposed work focuses on an anomaly detection strategy based on the physical behavior of the industrial process. The algorithm extracts some measures of the [...] Read more.
The large spread of Distributed Energy Resources (DERs) and the related cyber-security issues introduce the need for monitoring. The proposed work focuses on an anomaly detection strategy based on the physical behavior of the industrial process. The algorithm extracts some measures of the physical parameters of the system and processes them with a neural network architecture called autoencoder in order to build a classifier making decisions about the behavior of the system and detecting possible cyber-attacks or faults. The results are quite promising for a practical application in real systems. Full article
(This article belongs to the Special Issue Advanced Technologies for Smart Cities)
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