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Selected Papers from the 12th International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT 2020)

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 26409

Special Issue Editors

Dr. Jiri Hosek

E-Mail Website
Guest Editor
Brno University of Technology, 616 00 Brno, Czech Republic.
Interests: modern wireless communications; 5G+ technologies and applications; Internet of Things; quality of service; Quality of Experience
Special Issues, Collections and Topics in MDPI journals
Prof. Yevgeni Koucheryavy

E-Mail Website
Guest Editor
Tampere University, 33720 Tampere, Finland.
Interests: 5G mobile communication; antenna radiation patterns; cellular radio; directive antennas; radio frequency interference; receiving antennas; stochastic processes; transmitting antennas; wireless LAN
Dr. Aleksandr Ometov

E-Mail Website
Guest Editor
Faculty of Information Technology and Communication Sciences, Tampere University, Tampere‎, Finland
Interests: wireless communications; information security; authentication; distributed systems; blockchain; resource-constrained devices; wearable technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 12th International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT 2020), https://icumt.info/2020/, was held this year as a virtual event on October 5–7, 2020. Authors of the papers presented at the ICUMT 2020 congress are invited to submit extended versions of their work to this Special Issue in the Sensors journal.

The aim of this Special Issue is to include selected papers from the ICUMT 2020 congress describing research from both academia and industry, as well as technical presentations in the areas of modern telecommunications, control systems, automation, and robotics targeted on newly emerging technologies, standards, services, applications, and business issues. Papers should be original and should focus on current topics relevant to the sensors community.

Dr. Jiri Hosek
Prof. Yevgeni Koucheryavy
Dr. Aleksandr Ometov
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. Sensors 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 2600 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

  • 5G+ wireless systems and services
  • Control Systems
  • IoT architectures and communications
  • Modern telecommunication technologies and applications
  • Robotics and industrial automation
  • Smart wearables and wireless computing.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

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20 pages, 1653 KiB  
Article
SCADA-Based Message Generator for Multi-Vendor Smart Grids: Distributed Integration and Verification of TASE.2
by Petr Ilgner, Petr Cika and Martin Stusek
Sensors 2021, 21(20), 6793; https://doi.org/10.3390/s21206793 - 13 Oct 2021
Cited by 2 | Viewed by 2248
Abstract
Recent developments in massive machine-type communication (mMTC) scenarios have given rise to never-seen requirements, which triggered the Industry 4.0 revolution. The new scenarios bring even more pressure to comply with the reliability and communication security and enable flawless functionality of the critical infrastructure, [...] Read more.
Recent developments in massive machine-type communication (mMTC) scenarios have given rise to never-seen requirements, which triggered the Industry 4.0 revolution. The new scenarios bring even more pressure to comply with the reliability and communication security and enable flawless functionality of the critical infrastructure, e.g., smart grid infrastructure. We discuss typical network grid architecture, communication strategies, and methods for building scalable and high-speed data processing and storage platform. This paper focuses on the data transmissions using the sets of standards IEC 60870-6 (ICCP/TASE.2). The main goal is to introduce the TASE.2 traffic generator and the data collection back-end with the implemented load balancing functionality to understand the limits of current protocols used in the smart grids. To this end, the assessment framework enabling generating and collecting TASE.2 communication with long-term data storage providing high availability and load balancing capabilities was developed. The designed proof-of-concept supports complete cryptographic security and allows users to perform the complex testing and verification of the TASE.2 network nodes configuration. Implemented components were tested in a cloud-based Microsoft Azure environment in four geographically separated locations. The findings from the testing indicate the high performance and scalability of the proposed platform, allowing the proposed generator to be also used for high-speed load testing purposes. The load-balancing performance shows the CPU usage of the load-balancer below 15% while processing 5000 messages per second. This makes it possible to achieve up to a 7-fold improvement of performance resulting in processing up to 35,000 messages per second. Full article
(This article belongs to the Special Issue Selected Papers from the 12th International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT 2020))
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16 pages, 776 KiB  
Article
Enabling Next-Generation Public Safety Operations with Mission-Critical Networks and Wearable Applications
by Salwa Saafi, Jiri Hosek and Aneta Kolackova
Sensors 2021, 21(17), 5790; https://doi.org/10.3390/s21175790 - 28 Aug 2021
Cited by 4 | Viewed by 3128
Abstract
Public safety agencies have been working on the modernization of their communication networks and the enhancement of their mission-critical capabilities with novel technologies and applications. As part of these efforts, migrating from traditional land mobile radio (LMR) systems toward cellular-enabled, next-generation, mission-critical networks [...] Read more.
Public safety agencies have been working on the modernization of their communication networks and the enhancement of their mission-critical capabilities with novel technologies and applications. As part of these efforts, migrating from traditional land mobile radio (LMR) systems toward cellular-enabled, next-generation, mission-critical networks is at the top of these agencies’ agendas. In this paper, we provide an overview of cellular technologies ratified by the 3rd Generation Partnership Project (3GPP) to enable next-generation public safety networks. On top of using wireless communication technologies, emergency first responders need to be equipped with advanced devices to develop situational awareness. Therefore, we introduce the concept of the Internet of Life-Saving Things (IoLST) and focus on the role of wearable devices—more precisely, cellular-enabled wearables, in creating new solutions for enhanced public safety operations. Finally, we conduct a performance evaluation of wearable-based, mission-critical applications. So far, most of the mission-critical service evaluations target latency performance without taking into account reliability requirements. In our evaluation, we examine the impact of device- and application-related parameters on the latency and the reliability performance. We also identify major future considerations for better support of the studied requirements in next-generation public safety networks. Full article
(This article belongs to the Special Issue Selected Papers from the 12th International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT 2020))
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28 pages, 932 KiB  
Article
Generator of Slow Denial-of-Service Cyber Attacks
by Marek Sikora, Radek Fujdiak, Karel Kuchar, Eva Holasova and Jiri Misurec
Sensors 2021, 21(16), 5473; https://doi.org/10.3390/s21165473 - 13 Aug 2021
Cited by 10 | Viewed by 4092
Abstract
In today’s world, the volume of cyber attacks grows every year. These attacks can cause many people or companies high financial losses or loss of private data. One of the most common types of attack on the Internet is a DoS (denial-of-service) attack, [...] Read more.
In today’s world, the volume of cyber attacks grows every year. These attacks can cause many people or companies high financial losses or loss of private data. One of the most common types of attack on the Internet is a DoS (denial-of-service) attack, which, despite its simplicity, can cause catastrophic consequences. A slow DoS attack attempts to make the Internet service unavailable to users. Due to the small data flows, these attacks are very similar to legitimate users with a slow Internet connection. Accurate detection of these attacks is one of the biggest challenges in cybersecurity. In this paper, we implemented our proposal of eleven major and most dangerous slow DoS attacks and introduced an advanced attack generator for testing vulnerabilities of protocols, servers, and services. The main motivation for this research was the absence of a similarly comprehensive generator for testing slow DoS vulnerabilities in network systems. We built an experimental environment for testing our generator, and then we performed a security analysis of the five most used web servers. Based on the discovered vulnerabilities, we also discuss preventive and detection techniques to mitigate the attacks. In future research, our generator can be used for testing slow DoS security vulnerabilities and increasing the level of cyber security of various network systems. Full article
(This article belongs to the Special Issue Selected Papers from the 12th International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT 2020))
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20 pages, 7534 KiB  
Article
Skeleton Driven Action Recognition Using an Image-Based Spatial-Temporal Representation and Convolution Neural Network
by Vinícius Silva, Filomena Soares, Celina P. Leão, João Sena Esteves and Gianni Vercelli
Sensors 2021, 21(13), 4342; https://doi.org/10.3390/s21134342 - 25 Jun 2021
Cited by 17 | Viewed by 4252
Abstract
Individuals with Autism Spectrum Disorder (ASD) typically present difficulties in engaging and interacting with their peers. Thus, researchers have been developing different technological solutions as support tools for children with ASD. Social robots, one example of these technological solutions, are often unaware of [...] Read more.
Individuals with Autism Spectrum Disorder (ASD) typically present difficulties in engaging and interacting with their peers. Thus, researchers have been developing different technological solutions as support tools for children with ASD. Social robots, one example of these technological solutions, are often unaware of their game partners, preventing the automatic adaptation of their behavior to the user. Information that can be used to enrich this interaction and, consequently, adapt the system behavior is the recognition of different actions of the user by using RGB cameras or/and depth sensors. The present work proposes a method to automatically detect in real-time typical and stereotypical actions of children with ASD by using the Intel RealSense and the Nuitrack SDK to detect and extract the user joint coordinates. The pipeline starts by mapping the temporal and spatial joints dynamics onto a color image-based representation. Usually, the position of the joints in the final image is clustered into groups. In order to verify if the sequence of the joints in the final image representation can influence the model’s performance, two main experiments were conducted where in the first, the order of the grouped joints in the sequence was changed, and in the second, the joints were randomly ordered. In each experiment, statistical methods were used in the analysis. Based on the experiments conducted, it was found statistically significant differences concerning the joints sequence in the image, indicating that the order of the joints might impact the model’s performance. The final model, a Convolutional Neural Network (CNN), trained on the different actions (typical and stereotypical), was used to classify the different patterns of behavior, achieving a mean accuracy of 92.4% ± 0.0% on the test data. The entire pipeline ran on average at 31 FPS. Full article
(This article belongs to the Special Issue Selected Papers from the 12th International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT 2020))
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22 pages, 978 KiB  
Systematic Review
The Rise of Wearable Devices during the COVID-19 Pandemic: A Systematic Review
by Asma Channa, Nirvana Popescu, Justyna Skibinska and Radim Burget
Sensors 2021, 21(17), 5787; https://doi.org/10.3390/s21175787 - 28 Aug 2021
Cited by 115 | Viewed by 11064
Abstract
The COVID-19 pandemic has wreaked havoc globally and still persists even after a year of its initial outbreak. Several reasons can be considered: people are in close contact with each other, i.e., at a short range (1 m), and the healthcare system is [...] Read more.
The COVID-19 pandemic has wreaked havoc globally and still persists even after a year of its initial outbreak. Several reasons can be considered: people are in close contact with each other, i.e., at a short range (1 m), and the healthcare system is not sufficiently developed or does not have enough facilities to manage and fight the pandemic, even in developed countries such as the USA and the U.K. and countries in Europe. There is a great need in healthcare for remote monitoring of COVID-19 symptoms. In the past year, a number of IoT-based devices and wearables have been introduced by researchers, providing good results in terms of high accuracy in diagnosing patients in the prodromal phase and in monitoring the symptoms of patients, i.e., respiratory rate, heart rate, temperature, etc. In this systematic review, we analyzed these wearables and their need in the healthcare system. The research was conducted using three databases: IEEE Xplore®, Web of Science®, and PubMed Central®, between December 2019 and June 2021. This article was based on the PRISMA guidelines. Initially, 1100 articles were identified while searching the scientific literature regarding this topic. After screening, ultimately, 70 articles were fully evaluated and included in this review. These articles were divided into two categories. The first one belongs to the on-body sensors (wearables), their types and positions, and the use of AI technology with ehealth wearables in different scenarios from screening to contact tracing. In the second category, we discuss the problems and solutions with respect to utilizing these wearables globally. This systematic review provides an extensive overview of wearable systems for the remote management and automated assessment of COVID-19, taking into account the reliability and acceptability of the implemented technologies. Full article
(This article belongs to the Special Issue Selected Papers from the 12th International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT 2020))
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