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Electronics
Special Issues
Emerging Technologies for the Next Generation Smart Systems
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Emerging Technologies for the Next Generation Smart Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 9821

Special Issue Editors

Dr. Nenad Gligoric

E-Mail Website
Guest Editor
Zentrix Lab, 26000 Pancevo, Serbia
Interests: iot; circular economy; product passport; printed sensors; functional ink; ontology; mobile computing
Special Issues, Collections and Topics in MDPI journals
Dr. Eryk Schiller

E-Mail Website
Guest Editor
Department of Informatics, University of Zurich, 14 CH-8050 Zurich, Switzerland
Interests: Mobile Networks; IoT; Network Security; Future Internet; P2P Systems; 5G; Blockchain

Special Issue Information

Dear Colleagues,

The key factors for the proliferation of next generation systems (NGS) are scientific and industrial advances in the multidisciplinary areas. These new systems will be driven by artificial intelligence (AI) and interaction will be via advanced HCI and interfaces based on augmented and virtual reality (AR/VR), different types of sensors and the new generation of displays. Potentially, NGS will require high-data rates, large bandwidth with low latency and high throughput, meaning that fifth generation (5G) networks will play an important role. The prevelance of Internet of Things (IoT) concept that provides seamless connectivity between heterogeneus networks will surely be of great interest together with the edge computing for these new environments, with unlimited usage of big data in the various domains close to the edge, to ensure low latency.

The main aim of this Special Issue is to demonstrate both theoretical and experimental studies and novel approaches, protocols, applications and frameworks focusing on future technologies and emerging trends in the multidisciplinary area of the next generation systems. High-quality review papers and surveys are welcomed.

The topics of interest include, but are not limited to:

  • Algorithms, protocols and interfaces for next generation systems, e.g. brain machine and human–machine interfaces, haptic software and hardware interfaces, displays, gesture recognition and other HCIs;
  • Emerging 5G–IoT driven use cases, advances and performance analyses in artificial intelligence, machine and deep learning, ongoing 5G initiatives, quality of service (QoS) requirements in 5G, standardization issues;
  • Ubiquitous deployment of the IoT technology, edge, MEC, sensor networking (SD-WSN), network function virtualization (NFV) and cognitive radios (CRs);
  • Research in the horizontal domain of the next generation systems, covering different layers from low-level protocols, edge computing for IoT, to application layer and user interaction;
  • AI-enabled edge computing architectures, frameworks, platforms, and protocols for IoT in (but not mandatory) 5G networks;
  • Energy monitoring and energy-efficient edge network operations and services for the 5G;
  • Protocols, services, and application for vehicular V2V and V2I scenarios;
  • Robots and interfaces: cross-domain robots for streamlining and executing operations in various environments;
  • Distributed computing, edge network architecture and optimizations for next generation smart systems;
  • AI algorithms for dynamic and large-scale topology discovery in 5G;
  • The applications of concepts such augmented reality, virtual reality, high-resolution video streaming in different domains, e.g., self-driven cars, drones, smart environment, health care, etc.;
  • Wearables: active and passive orthotics, prosthetics, exoskeletons, and wearables.

Dr. Nenad Gligoric
Dr. Eryk Schiller
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

  • HCI
  • IoT
  • AI
  • 5G
  • V2V
  • AR/VR

Published Papers (4 papers)

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Research

19 pages, 883 KiB  
Article
IoT-Based Access Management Supported by AI and Blockchains
by Eryk Schiller, Elfat Esati and Burkhard Stiller
Electronics 2022, 11(18), 2971; https://doi.org/10.3390/electronics11182971 - 19 Sep 2022
Cited by 2 | Viewed by 1590
Abstract
Internet-of-Things (IoT), Artificial Intelligence (AI), and Blockchains (BCs) are essential techniques that are heavily researched and investigated today. This work here specifies, implements, and evaluates an IoT architecture with integrated BC and AI functionality to manage access control based on facial detection and [...] Read more.
Internet-of-Things (IoT), Artificial Intelligence (AI), and Blockchains (BCs) are essential techniques that are heavily researched and investigated today. This work here specifies, implements, and evaluates an IoT architecture with integrated BC and AI functionality to manage access control based on facial detection and recognition by incorporating the most recent state-of-the-art techniques. The system developed uses IoT devices for video surveillance, AI for face recognition, and BCs for immutable permanent storage to provide excellent properties in terms of image quality, end-to-end delay, and energy efficiency. Full article
(This article belongs to the Special Issue Emerging Technologies for the Next Generation Smart Systems)
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20 pages, 1174 KiB  
Article
Python-Based TinyIPFIX in Wireless Sensor Networks
by Eryk Schiller, Ramon Huber and Burkhard Stiller
Electronics 2022, 11(3), 472; https://doi.org/10.3390/electronics11030472 - 5 Feb 2022
Viewed by 2137
Abstract
While wireless sensor networks (WSN) offer potential, their limited programmability and energy limitations determine operational challenges. Thus, a TinyIPFIX-based system was designed such that this application layer protocol is now used to exchange data in WSNs efficiently. The new prototype is based on [...] Read more.
While wireless sensor networks (WSN) offer potential, their limited programmability and energy limitations determine operational challenges. Thus, a TinyIPFIX-based system was designed such that this application layer protocol is now used to exchange data in WSNs efficiently. The new prototype is based on the Espressif ESP32-WROOM-32D Internet-of-Things (IoT) platform, which is becoming famous, as it is inexpensive but powerful compared to older generations of IoT devices. The system implementation is provided in the programming language MicroPython, which provides a simple and efficient implementation, compared to a lower-level programming language. Therefore, this approach focuses on value creation rather than platform-specific implementation difficulties. The system is evaluated in smart home use cases and displays valuable overhead, reliability, and power efficiency. TinyIPFIX outperforms the data overhead of the type–length–value (TLV) paradigm by a factor of 7% when a TinyIPFIX data message carries only two records, and one TinyIPFIX template message is sent per three TinyIPFIX data messages. A further decrease in overhead is observed when the number of data records per message and the number of TinyIPFIX data messages sent per one TinyIPFIX template message increase to larger values. The message delivery between end devices and the application server resides at a very high level, close to 100%, when the transmission reliability is secured with acknowledgments and retransmissions. The energy efficiency resides at the limited level, as the experienced deep sleep power consumption of the ESP32 device resides at the milliwatt level. Full article
(This article belongs to the Special Issue Emerging Technologies for the Next Generation Smart Systems)
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27 pages, 4314 KiB  
Article
PEDTARA: Priority-Based Energy Efficient, Delay and Temperature Aware Routing Algorithm Using Multi-Objective Genetic Chaotic Spider Monkey Optimization for Critical Data Transmission in WBANs
by Omar Ahmed, Min Hu and Fuji Ren
Electronics 2022, 11(1), 68; https://doi.org/10.3390/electronics11010068 - 27 Dec 2021
Cited by 7 | Viewed by 2628
Abstract
Software-Defined Wireless Body Area Network (WBAN)s have gained significance in emergency healthcare applications for remote patients. Prioritization of healthcare data traffic has a high influence on the congestion and delay in the WBAN routing process. Currently, the energy constraints, packet loss, retransmission delay [...] Read more.
Software-Defined Wireless Body Area Network (WBAN)s have gained significance in emergency healthcare applications for remote patients. Prioritization of healthcare data traffic has a high influence on the congestion and delay in the WBAN routing process. Currently, the energy constraints, packet loss, retransmission delay and increased sensor heat are pivotal research challenges in WBAN. These challenges also degrade the network lifetime and create serious issues for critical health data transmission. In this context, a Priority-based Energy-efficient, Delay and Temperature Aware Routing Algorithm (PEDTARA) is presented in this paper using a hybrid optimization algorithm of Multi-objective Genetic Chaotic Spider Monkey Optimization (MGCSMO). This proposed optimized routing algorithm is designed by incorporating the benefits of chaotic and genetic operators to the position updating function of enhanced Spider Monkey Optimization. For the prioritized routing process, initially, the patient data transmission in the WBAN is categorized into normal, on-demand and emergency data transmissions. Each category is ensured with efficient routing using the three different strategies of the suggested PEDTARA. PEDTARA performs optimal shortest path routing for normal data, energy-efficient emergency routing for high priority critical data and faster but priority verified routing for on-demand data. Thus, the proposed PEDTARA ensures energy-efficient, congestion-controlled and delay and temperature aware routing at any given period of health monitoring. Experiments were performed over a high-performance simulation scenario and the evaluation results showed that the proposed PEDTARA performs efficient routing better than the traditional approaches in terms of energy, temperature, delay, congestion and network lifetime. Full article
(This article belongs to the Special Issue Emerging Technologies for the Next Generation Smart Systems)
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16 pages, 816 KiB  
Article
Reinforcement Learning Aided UAV Base Station Location Optimization for Rate Maximization
by Sudheesh Puthenveettil Gopi and Maurizio Magarini
Electronics 2021, 10(23), 2953; https://doi.org/10.3390/electronics10232953 - 27 Nov 2021
Cited by 8 | Viewed by 2152
Abstract
The application of unmanned aerial vehicles (UAV) as base station (BS) is gaining popularity. In this paper, we consider maximization of the overall data rate by intelligent deployment of UAV BS in the downlink of a cellular system. We investigate a reinforcement learning [...] Read more.
The application of unmanned aerial vehicles (UAV) as base station (BS) is gaining popularity. In this paper, we consider maximization of the overall data rate by intelligent deployment of UAV BS in the downlink of a cellular system. We investigate a reinforcement learning (RL)-aided approach to optimize the position of flying BSs mounted on board UAVs to support a macro BS (MBS). We propose an algorithm to avoid collision between multiple UAVs undergoing exploratory movements and to restrict UAV BSs movement within a predefined area. Q-learning technique is used to optimize UAV BS position, where the reward is equal to sum of user equipment (UE) data rates. We consider a framework where the UAV BSs carry out exploratory movements in the beginning and exploitary movements in later stages to maximize the overall data rate. Our results show that a cellular system with three UAV BSs and one MBS serving 72 UE reaches 69.2% of the best possible data rate, which is identified by brute force search. Finally, the RL algorithm is compared with a K-means algorithm to study the need of accurate UE locations. Our results show that the RL algorithm outperforms the K-means clustering algorithm when the measure of imperfection is higher. The proposed algorithm can be made use of by a practical MBS–UAV BSs–UEs system to provide protection to UAV BSs while maximizing data rate. Full article
(This article belongs to the Special Issue Emerging Technologies for the Next Generation Smart Systems)
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