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Emerging Paradigms and Architectures for Industry 5.0 Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (20 January 2022) | Viewed by 18685

Special Issue Editors


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Guest Editor
Department of Computer Engineering, University of A Coruña (UDC), 15071 A Coruña, Spain
Interests: blockchain; distributed ledger technology (DLT); fog computing; internet of things; IIoT; cyber-physical systems; industry 4.0; defense and public safety; cybersecurity; wearables; industrial augmented reality; traceability
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department Computer Engineering, Faculty of Computer Science, Universidade da Coruña, 15071 A Coruña, Spain
Interests: blockchain; intelligent transportation systems; wireless sensor networks; fog computing; edge computing; industrial internet of things (IIoT); RFID; wireless communications; cybersecurity; augmented reality; industry 4.0; traceability
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
ADiT-LAB, Applied Digital Transformation Laboratory, Polytechnic Institute of Viana do Castelo, Rua Escola Industrial e Comercial de Nun’Álvares, n.º 34, 4900-347 Viana do Castelo, Portugal
Interests: cyber-physical systems; IoT; wireless sensor networks; signal processing; smart sensing; data analytics; visual analytics; IAQ monitoring; radon risk management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Fifth Industrial Revolution (5IR), called “Industry 5.0” in Europe, complements the existing Industry 4.0 paradigm by driving the transition to a sustainable, human-centered and resilient industry.

5IR-enabling technologies such as the Industrial Internet of Things (IIoT), industrial cyber–physical systems (ICPSs), novel computing paradigms (fog, mist and edge computing), digital twin, augmented/mixed reality, and distributed ledger technologies (DLTs) like blockchain or advanced wireless sensor networks, can enable novel cyber-secure, resilient, collaborative and human-centric computing and communications architectures to improve manufacturing processes in diverse aspects related to data collection, data communications, storage, authentication, reliability, scalability, communications latency, energy efficiency, standardization, interoperability, mobility or security.

This Special Issue aims to report the latest advances in architectures, paradigms and applications in the ever-increasing complex ecosystem of green smart manufacturing. Potential topics include but are not limited to the following challenges, visions and concepts for Industry 5.0:

  • Novel architectures for the Green Industrial Internet of Things (GIIoT);
  • Industrial applications of the Green Internet of Things (GIoT) such as green manufacturing, agile manufacturing, predictive maintenance and zero-defect production;
  • Novel network infrastructures for IIoT;
  • IIoT data analytics, data aggregation, data abstraction and event detection;
  • Cybersecurity in IIoT environments;
  • Cognitive IIoT;
  • Cloud, fog, mist, edge and mobile edge computing architectures for industrial scenarios;
  • Industrial cyber–physical systems (ICPSs);
  • Advances in the application of distributed ledger technologies (DLTs) (e.g., Blockchain, IOTA) to industrial scenarios;
  • Industrial wireless sensor networks;
  • Low-power wide-area network (LPWAN) technologies (e.g., LoRa, SigFox, NB-IoT) for Industry 5.0 applications;
  • Localization and tracking technologies for Industry 5.0;
  • Energy-harvesting techniques for industrial scenarios;
  • Advanced sensors for Industry 5.0 applications;
  • Novel sensing strategies for process monitoring and product traceability;
  • Human–machine interfaces and interactions in human-centric smart industrial systems;
  • Green machine learning and artificial intelligence for Industry 5.0;
  • Digital twins.

Prof. Dr. Paula Fraga-Lamas
Prof. Dr. Tiago M. Fernández-Caramés
Prof. Dr. Sérgio Ivan Lopes
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. Applied Sciences 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

  • Industry 5.0
  • Green Industrial Internet of Things (GIIoT)
  • cloud, fog, mist, edge and mobile edge computing
  • industrial cyber-physical systems (ICPSs)
  • human–machine interfaces
  • human-centered technologies
  • traceability
  • sustainable supply chains
  • industrial wireless sensor networks
  • distributed ledger technologies (DLTs)
  • low-power wide-area network (LPWAN)
  • advanced sensors
  • cybersecurity in GIIoT
  • cognitive GIIoT
  • green AI

Published Papers (5 papers)

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Research

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10 pages, 13656 KiB  
Article
Challenges and Founding Pillars for a Manufacturing Platform to Support Value Networks Operating in a Circular Economy Framework
by Paolo Pedrazzoli, Marzio Sorlini, Diego Rovere, Oscar Lazaro, Pedro Malò and Michele Fiorello
Appl. Sci. 2022, 12(6), 2995; https://doi.org/10.3390/app12062995 - 15 Mar 2022
Cited by 4 | Viewed by 2197
Abstract
Circularity is clearly a competitive advantage and a market opportunity for European industries. From this perspective, while digitalization is largely recognized as an accelerator and an enabler of Circular Economy, the fact that European industry is strong but fragmented (highly specialized medium- and [...] Read more.
Circularity is clearly a competitive advantage and a market opportunity for European industries. From this perspective, while digitalization is largely recognized as an accelerator and an enabler of Circular Economy, the fact that European industry is strong but fragmented (highly specialized medium- and small-sized companies have different needs and different tools) naturally results in the proliferation of commercial platforms for digitalized manufacturing. If such fragmentation is not properly addressed, it will eventually become a threat to European competitiveness. Despite some examples, value networks still do not operate in a seamless, transparent, and effective way. This paper addresses the challenges and the resulting technical funding pillars for an IDS (International Data Space) manufacturing platform meant to empower a fully digital circular thread of products and services. Full article
(This article belongs to the Special Issue Emerging Paradigms and Architectures for Industry 5.0 Applications)
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17 pages, 3751 KiB  
Article
Blockchain-Based Network Concept Model for Reliable and Accessible Fine Dust Management System at Construction Sites
by Seungwon Cho, Muhammad Khan, Jaeho Pyeon and Chansik Park
Appl. Sci. 2021, 11(18), 8686; https://doi.org/10.3390/app11188686 - 17 Sep 2021
Cited by 16 | Viewed by 2456
Abstract
In total, 44.3% of particle matter 10 (PM10) is fugitive dust, and one of the main sources of fugitive dust generation in Korea is construction work (22%). Construction sites account for 84% of the total business places that have reported fugitive dust generation. [...] Read more.
In total, 44.3% of particle matter 10 (PM10) is fugitive dust, and one of the main sources of fugitive dust generation in Korea is construction work (22%). Construction sites account for 84% of the total business places that have reported fugitive dust generation. Currently, the concentration of fine dust at construction sites is being remotely monitored by government inspection agencies through IoT sensors, but it is difficult to trust that appropriate fine dust reduction measures are being taken, because contractors can avoid taking these measures by submitting false reports or photos. In addition, since the fine dust monitoring system under government management is not an open platform and centralized system, residents near construction sites encounter difficulties in accessing information about fine dust. Therefore, in this study, we designed and constructed a blockchain network model to transparently and reliably provide network participants with the information associated with IoT data and fine dust reduction measures. To operate the blockchain network, we designed the chaincode, DApp, and network architecture. In addition, information on fine dust concentration and reduction measure photos were shared with the participants via the blockchain search tool (Hyperledger Explorer). The proposed blockchain network is expected to form a trust protocol among contractors, government inspection agencies, and citizens. Full article
(This article belongs to the Special Issue Emerging Paradigms and Architectures for Industry 5.0 Applications)
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Review

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21 pages, 787 KiB  
Review
Internet of Things (IoT) Technologies for Managing Indoor Radon Risk Exposure: Applications, Opportunities, and Future Challenges
by Paulo Barros, António Curado and Sérgio Ivan Lopes
Appl. Sci. 2021, 11(22), 11064; https://doi.org/10.3390/app112211064 - 22 Nov 2021
Cited by 10 | Viewed by 3291
Abstract
Radon gas is a harmful pollutant with a well-documented adverse influence on public health. In poorly ventilated environments, that are often prone to significant radon levels, studies indicate a known relationship between human radon exposure and lung cancer. Recent technology advances, notably on [...] Read more.
Radon gas is a harmful pollutant with a well-documented adverse influence on public health. In poorly ventilated environments, that are often prone to significant radon levels, studies indicate a known relationship between human radon exposure and lung cancer. Recent technology advances, notably on the Internet of Things (IoT) ecosystem, allow the integration of sensors, computing, and communication capabilities into low-cost and small-scale devices that can be used for implementing specific cyber-physical systems (CPS) for online and real-time radon management. These technologies are crucial for improving the overall building indoor air quality (IAQ), contributing toward the so-called cognitive buildings, where human-based control is tending to decline, and building management systems (BMS) are focused on balancing critical factors, such as energy efficiency, human radon exposure management, and user experience, to achieve a more transparent and harmonious integration between technology and the built environment. This work surveys recent IoT technologies for indoor radon exposure management (monitoring, assessment and mitigation), and discusses its main challenges and opportunities, by focusing on methods, techniques, and technologies to answer the following questions: (i) What technologies have been recently in use for radon exposure management; (ii) how they operate; (iii) what type of radon detection mechanisms do they use; and (iv) what type of system architectures, components, and communication technologies have been used to assist the referred technologies. This contribution is relevant to pave the way for designing more intelligent and sustainable systems that rely on IoT and Information and Communications Technology (ICT), to achieve an optimal balance between these two critical factors: human radon exposure management and building energy efficiency. Full article
(This article belongs to the Special Issue Emerging Paradigms and Architectures for Industry 5.0 Applications)
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32 pages, 1824 KiB  
Review
GNSS-Free Outdoor Localization Techniques for Resource-Constrained IoT Architectures: A Literature Review
by Azin Moradbeikie, Ahmad Keshavarz, Habib Rostami, Sara Paiva and Sérgio Ivan Lopes
Appl. Sci. 2021, 11(22), 10793; https://doi.org/10.3390/app112210793 - 15 Nov 2021
Cited by 20 | Viewed by 3757
Abstract
Large-scale deployments of the Internet of Things (IoT) are adopted for performance improvement and cost reduction in several application domains. The four main IoT application domains covered throughout this article are smart cities, smart transportation, smart healthcare, and smart manufacturing. To increase IoT [...] Read more.
Large-scale deployments of the Internet of Things (IoT) are adopted for performance improvement and cost reduction in several application domains. The four main IoT application domains covered throughout this article are smart cities, smart transportation, smart healthcare, and smart manufacturing. To increase IoT applicability, data generated by the IoT devices need to be time-stamped and spatially contextualized. LPWANs have become an attractive solution for outdoor localization and received significant attention from the research community due to low-power, low-cost, and long-range communication. In addition, its signals can be used for communication and localization simultaneously. There are different proposed localization methods to obtain the IoT relative location. Each category of these proposed methods has pros and cons that make them useful for specific IoT systems. Nevertheless, there are some limitations in proposed localization methods that need to be eliminated to meet the IoT ecosystem needs completely. This has motivated this work and provided the following contributions: (1) definition of the main requirements and limitations of outdoor localization techniques for the IoT ecosystem, (2) description of the most relevant GNSS-free outdoor localization methods with a focus on LPWAN technologies, (3) survey the most relevant methods used within the IoT ecosystem for improving GNSS-free localization accuracy, and (4) discussion covering the open challenges and future directions within the field. Some of the important open issues that have different requirements in different IoT systems include energy consumption, security and privacy, accuracy, and scalability. This paper provides an overview of research works that have been published between 2018 to July 2021 and made available through the Google Scholar database. Full article
(This article belongs to the Special Issue Emerging Paradigms and Architectures for Industry 5.0 Applications)
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41 pages, 3122 KiB  
Review
A Conceptual and Systematics for Intelligent Power Management System-Based Cloud Computing: Prospects, and Challenges
by Ahmed Hadi Ali AL-Jumaili, Yousif I. Al Mashhadany, Rossilawati Sulaiman and Zaid Abdi Alkareem Alyasseri
Appl. Sci. 2021, 11(21), 9820; https://doi.org/10.3390/app11219820 - 20 Oct 2021
Cited by 24 | Viewed by 5699
Abstract
This review describes a cloud-based intelligent power management system that uses analytics as a control signal and processes balance achievement pointer, and describes operator acknowledgments that must be shared quickly, accurately, and safely. The current study aims to introduce a conceptual and systematic [...] Read more.
This review describes a cloud-based intelligent power management system that uses analytics as a control signal and processes balance achievement pointer, and describes operator acknowledgments that must be shared quickly, accurately, and safely. The current study aims to introduce a conceptual and systematic structure with three main components: demand power (direct current (DC)-device), power mix between renewable energy (RE) and other power sources, and a cloud-based power optimization intelligent system. These methods and techniques monitor demand power (DC-device), load, and power mix between RE and other power sources. Cloud-based power optimization intelligent systems lead to an optimal power distribution solution that reduces power consumption or costs. Data has been collected from reliable sources such as Science Direct, IEEE Xplore, Scopus, Web of Science, Google Scholar, and PubMed. The overall findings of these studies are visually explained in the proposed conceptual framework through the literature that are considered to be cloud computing based on storing and running the intelligent systems of power management and mixing. Full article
(This article belongs to the Special Issue Emerging Paradigms and Architectures for Industry 5.0 Applications)
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