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The Impact of Emerging Technologies on Sensor-Based Systems/Solutions
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The Impact of Emerging Technologies on Sensor-Based Systems/Solutions

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

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 32233

Special Issue Editors

Dr. Helen C. Leligou

E-Mail Website
Guest Editor
Department of Industrial Design and Production Engineering, University of West Attica, GR-122 44 Egaleo, Greece
Interests: information and communication technologies including: routing protocols and trust management in wireless sensor networks; control plane technologies in broadband networks including HFC, PON, WDM metro and core networks; industrial, embedded, and network system design and development; blockchain technologies
Special Issues, Collections and Topics in MDPI journals
Dr. Panagiotis Trakadas

E-Mail Website
Guest Editor
Department of Ports Management and Shipping, National and Kapodistrian University of Athens, 157 72 Athens, Greece
Interests: wireless communications; networking; machine learning; cloud computing; IoT
Special Issues, Collections and Topics in MDPI journals
Dr. Panagiotis A. Karkazis

E-Mail Website
Guest Editor
Department of Informatics and Computer Engineering, University of West Attica, GR12243 Athens, Greece
Interests: embedded systems; IoT; cloud computing; SDN/NFV
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Emerging technologies such as Artificial Intelligence, blockchain, software-defined networking (SDN), network function virtualization (NFV), and Big Data analytics have transformed the way sensors, actuators, and any connected device forming an Internet-of-Things system can serve diverse purposes. Devices specialized in one or more capabilities are intended to work together based on an infrastructure of intelligent systems, to provide a variety of services improving safety, security, and the quality of life in ordinary living, traveling, and working environments. The combination of the emerging technologies with IoT systems is anticipated to cause a multiplication effect on the potential applications of IoT systems, offering additional services on top of possibly existing infrastructures. However, this combination introduces specific challenges as, for example, IoT devices are not necessarily capable of supporting heavy processing. This Special Issue intends to bring to the audience results from both scientific research and practical implementations addressing issues raised when combining IoT and any type of emerging technology (including artificial intelligence, blockchain, software-defined networks/NFV, VR/AR, and others). The development of innovative applications/solutions targeting specific sectors (e.g., supply chain, industry 4.0, smart cities, smart grids or smart learning environments) are also welcome.

Dr. Nelly Leligou
Dr. Panagiotis Trakadas
Dr. Panagiotis A. Karkazis
Guest Editor

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

  • IoT and blockchain technologies
  • IoT and artificial intelligence
  • IoT and SDN/NFV
  • IoT and Big Data
  • IoT and VR/AR
  • Methods and techniques to enrich IoT systems with emerging technologies
  • Solutions and prototypes for IoT systems enriched with emerging technologies
  • Emerging Technology based IoT systems for different verticals including smart factories, supply chain, health, energy efficiency, smart cities, and smart infrastructures
  • IoT-based security solutions

Published Papers (4 papers)

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20 pages, 1414 KiB  
Review
Enhancing the Internet of Things with Knowledge-Driven Software-Defined Networking Technology: Future Perspectives
by Yuhong Li, Xiang Su, Aaron Yi Ding, Anders Lindgren, Xiaoli Liu, Christian Prehofer, Jukka Riekki, Rahim Rahmani, Sasu Tarkoma and Pan Hui
Sensors 2020, 20(12), 3459; https://doi.org/10.3390/s20123459 - 19 Jun 2020
Cited by 25 | Viewed by 5341
Abstract
The Internet of Things (IoT) connects smart devices to enable various intelligent services. The deployment of IoT encounters several challenges, such as difficulties in controlling and managing IoT applications and networks, problems in programming existing IoT devices, long service provisioning time, underused resources, [...] Read more.
The Internet of Things (IoT) connects smart devices to enable various intelligent services. The deployment of IoT encounters several challenges, such as difficulties in controlling and managing IoT applications and networks, problems in programming existing IoT devices, long service provisioning time, underused resources, as well as complexity, isolation and scalability, among others. One fundamental concern is that current IoT networks lack flexibility and intelligence. A network-wide flexible control and management are missing in IoT networks. In addition, huge numbers of devices and large amounts of data are involved in IoT, but none of them have been tuned for supporting network management and control. In this paper, we argue that Software-defined Networking (SDN) together with the data generated by IoT applications can enhance the control and management of IoT in terms of flexibility and intelligence. We present a review for the evolution of SDN and IoT and analyze the benefits and challenges brought by the integration of SDN and IoT with the help of IoT data. We discuss the perspectives of knowledge-driven SDN for IoT through a new IoT architecture and illustrate how to realize Industry IoT by using the architecture. We also highlight the challenges and future research works toward realizing IoT with the knowledge-driven SDN. Full article
(This article belongs to the Special Issue The Impact of Emerging Technologies on Sensor-Based Systems/Solutions)
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22 pages, 668 KiB  
Article
Efficient Traffic Engineering in an NFV Enabled IoT System
by Thi-Thuy-Lien Nguyen and Tuan-Minh Pham
Sensors 2020, 20(11), 3198; https://doi.org/10.3390/s20113198 - 4 Jun 2020
Cited by 2 | Viewed by 2976
Abstract
The Internet of Things (IoT) is increasingly creating new market possibilities in several industries’ sectors such as smart homes, smart manufacturing, and smart cities, to link the digital and physical worlds. A key challenge in an IoT system is to ensure network performance [...] Read more.
The Internet of Things (IoT) is increasingly creating new market possibilities in several industries’ sectors such as smart homes, smart manufacturing, and smart cities, to link the digital and physical worlds. A key challenge in an IoT system is to ensure network performance and cost-efficiency when a plethora of data is generated and proliferated. The adoption of Network Function Virtualization (NFV) technologies within an IoT environment enables a new approach of providing services in a more agile and cost-efficient way. We address the problem of traffic engineering with multiple paths for an NFV enabled IoT system (vIoT), taking into account the fluctuation of traffic volume in various time periods. We first formulate the problem as a mixed linear integer programming model for finding the optimal solution of link-weight configuration and traffic engineering. We then develop heuristic algorithms for a vIoT system with a large number of devices. Our solution enables a controller to adjust a link weight system and update a flow table at an NFV switch for directing IoT traffic through a service function chain in a vIoT system. The evaluation results under both synthetic and real-world datasets of network traffic and topologies show that our approach to traffic engineering with multiple paths remarkably improves several performance metrics for a vIoT system. Full article
(This article belongs to the Special Issue The Impact of Emerging Technologies on Sensor-Based Systems/Solutions)
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20 pages, 2354 KiB  
Article
An Artificial Intelligence-Based Collaboration Approach in Industrial IoT Manufacturing: Key Concepts, Architectural Extensions and Potential Applications
by Panagiotis Trakadas, Pieter Simoens, Panagiotis Gkonis, Lambros Sarakis, Angelos Angelopoulos, Alfonso P. Ramallo-González, Antonio Skarmeta, Christos Trochoutsos, Daniel Calvο, Tomas Pariente, Keshav Chintamani, Izaskun Fernandez, Aitor Arnaiz Irigaray, Josiane Xavier Parreira, Pierluigi Petrali, Nelly Leligou and Panagiotis Karkazis
Sensors 2020, 20(19), 5480; https://doi.org/10.3390/s20195480 - 24 Sep 2020
Cited by 56 | Viewed by 9665
Abstract
The digitization of manufacturing industry has led to leaner and more efficient production, under the Industry 4.0 concept. Nowadays, datasets collected from shop floor assets and information technology (IT) systems are used in data-driven analytics efforts to support more informed business intelligence decisions. [...] Read more.
The digitization of manufacturing industry has led to leaner and more efficient production, under the Industry 4.0 concept. Nowadays, datasets collected from shop floor assets and information technology (IT) systems are used in data-driven analytics efforts to support more informed business intelligence decisions. However, these results are currently only used in isolated and dispersed parts of the production process. At the same time, full integration of artificial intelligence (AI) in all parts of manufacturing systems is currently lacking. In this context, the goal of this manuscript is to present a more holistic integration of AI by promoting collaboration. To this end, collaboration is understood as a multi-dimensional conceptual term that covers all important enablers for AI adoption in manufacturing contexts and is promoted in terms of business intelligence optimization, human-in-the-loop and secure federation across manufacturing sites. To address these challenges, the proposed architectural approach builds on three technical pillars: (1) components that extend the functionality of the existing layers in the Reference Architectural Model for Industry 4.0; (2) definition of new layers for collaboration by means of human-in-the-loop and federation; (3) security concerns with AI-powered mechanisms. In addition, system implementation aspects are discussed and potential applications in industrial environments, as well as business impacts, are presented. Full article
(This article belongs to the Special Issue The Impact of Emerging Technologies on Sensor-Based Systems/Solutions)
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17 pages, 4050 KiB  
Article
A Smart Microcontroller Architecture for the Internet of Things
by Zhenyu Wu, Kai Qiu and Jianguo Zhang
Sensors 2020, 20(7), 1821; https://doi.org/10.3390/s20071821 - 25 Mar 2020
Cited by 14 | Viewed by 13272
Abstract
The interoperations of endpoint devices are generally achieved by gateways in Internet of Things (IoT) systems. However, the gateways mainly focus on networking communication, which is lack of data logic control capabilities. The microcontrollers with embedded intelligence could work as an intermediate device [...] Read more.
The interoperations of endpoint devices are generally achieved by gateways in Internet of Things (IoT) systems. However, the gateways mainly focus on networking communication, which is lack of data logic control capabilities. The microcontrollers with embedded intelligence could work as an intermediate device to help the interconnections of the endpoint devices. Moreover, they could help control the endpoint devices. In this paper, a microcontroller architecture with intelligent and scalable characteristics is proposed. The intelligence means that the microcontroller could control the target endpoint devices by its logical circuits, and the scalability means that the microcontroller architecture could be easily extended to deal with more complex problems. Two real world industrial implementations of the proposed architecture are introduced. The implementations show that the microcontroller is important to provide the intelligent services to users in IoT systems. Furthermore, a simulation experiment based on the cloud model is designed to evaluate the proposed method. The experimental results demonstrate the effectiveness of the proposed architecture. Full article
(This article belongs to the Special Issue The Impact of Emerging Technologies on Sensor-Based Systems/Solutions)
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