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Prototyping of Industrial IoT Solutions
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Prototyping of Industrial IoT Solutions

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

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 13786

Special Issue Editors

Dr. Daniele Mazzei

E-Mail Website
Guest Editor
Computer Science Department, University of Pisa, 56126 Pisa, PI, Italy
Interests: industrial IoT; embedded programming; industrial innovation; AI on the edge for industrial applications; human–machine and human–robot interaction
Special Issues, Collections and Topics in MDPI journals
Dr. Dorota Stadnicka

E-Mail Website
Guest Editor
Faculty of Mechanical Engineering and Aeronautics, Rzeszów University of Technology, 35-959 Rzeszów, Poland
Interests: production engineering; lean production; intelligent manufacturing systems; human–robot collaboration; sustainable development; human-centric manufacturing systems.
Special Issues, Collections and Topics in MDPI journals
Dr. Joan Navarro

E-Mail Website
Guest Editor
Engineering Department of the La Salle, Universitat Ramon Llull, 08022 Barcelona, Spain
Interests: big data; cloud computing; edge computing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Chrysostomos Stylios

E-Mail Website
Guest Editor
Department of Informatics and Telecommunications, University of Ioannina, GR-47100 Arta, Greece
Interests: Industry 4.0; artificial intelligence computational intelligence, fuzzy cognitive maps; fuzzy logic, neural networks; support vector machines; knowledge-based systems; modeling complex systems; intelligent systems; medical decision support systems; biosignal processing and analysis; hierarchical systems and supervisory control; intelligent manufacturing systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Giuseppe Iannaccone

E-Mail Website
Guest Editor
Department of Information Engineering, University of Pisa, 56122 Pisa, Italy
Interests: quantum transport; materials/device engineering for electronics; design of analog and mixed-signal integrated circuits for artificial intelligence; analog circuit design; systems for the Internet of Things
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

The Industrial Internet of Things (I-IoT) is widely considered a key enabling technology of the fourth industrial revolution (I-4.0). The bridging of industrial assets with cloud infrastructures will allow the generation of many digital twins. I-IoT will fuel a multitude of innovation processes aimed at optimizing industrial processes and methods. However, the introduction of industrial IoT technologies into factories is a complex and cumbersome activity. Researchers, technicians, and entrepreneurs interested in bringing IoT into shop floors need to deal with reliability, scalability, compatibility, and security issues that are more complex in industrial environments than in consumer and domestic scenarios. Evolution from IoT to Industrial IoT requires a dedicated design process where the prototyping phase becomes crucial. Companies need to reduce the investment required for testing I-4.0 and I-IoT solutions, thus increasing the Return of Investment (ROI) while minimizing the impact on production and organization. Moreover, Industry 4.0 pushes companies and factories toward lean production strategies where fast prototyping in R&D processes is mandatory. For this reason, there is a strong need for reliable and secure fast prototyping solutions for Industrial IoT that, while guaranteeing a fast and cost-effective implementation of proof of concept, also guarantee future scalability toward extended, secure, stable and professional industrial setups.

Prof. Dr. Daniele Mazzei
Prof. Dr. Dorota Stadnicka
Dr. Joan Navarro
Prof. Dr. Chrysostomos Stylios
Prof. Dr. Giuseppe Lannaccone
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

  • Industrial IoT
  • IoT hardware
  • IoT software stack
  • Digital twin
  • Industry 4.0
  • Cybersecurity for IoT and Industrial IoT
  • Industrial IoT training

Published Papers (3 papers)

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Research

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34 pages, 656 KiB  
Article
Role of Academics in Transferring Knowledge and Skills on Artificial Intelligence, Internet of Things and Edge Computing
by Grzegorz Dec, Dorota Stadnicka, Łukasz Paśko, Maksymilian Mądziel, Roberto Figliè, Daniele Mazzei, Marios Tyrovolas, Chrysostomos Stylios, Joan Navarro and Xavier Solé-Beteta
Sensors 2022, 22(7), 2496; https://0-doi-org.brum.beds.ac.uk/10.3390/s22072496 - 24 Mar 2022
Cited by 17 | Viewed by 4402
Abstract
Universities play an essential role in preparing human resources for the industry of the future. By providing the proper knowledge, they can ensure that graduates will be able to adapt to the ever-changing industrial sector. However, to achieve this, the courses provided by [...] Read more.
Universities play an essential role in preparing human resources for the industry of the future. By providing the proper knowledge, they can ensure that graduates will be able to adapt to the ever-changing industrial sector. However, to achieve this, the courses provided by academia must cover the current and future industrial needs by considering the trends in scientific research and emerging technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and Edge Computing (EC). This work presents the survey results conducted among academics to assess the current state of university courses, regarding the level of knowledge and skills provided to students about the Internet of Things, Artificial Intelligence, and Edge Computing. The novelty of the work is that (a) the research was carried out in several European countries, (b) the current curricula of universities from different countries were analyzed, and (c) the results present the teachers’ perspective. To conduct the research, the analysis of the relevant literature took place initially to explore the issues of the presented subject, which will increasingly concern the industry in the near future. Based on the literature review results and analysis of the universities’ curricula involved in this study, a questionnaire was prepared and shared with academics. The outcomes of the analysis reveal the areas that require more attention from scholars and possibly modernization of curricula. Full article
(This article belongs to the Special Issue Prototyping of Industrial IoT Solutions)
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24 pages, 1627 KiB  
Article
Possible Applications of Edge Computing in the Manufacturing Industry—Systematic Literature Review
by Kacper Kubiak, Grzegorz Dec and Dorota Stadnicka
Sensors 2022, 22(7), 2445; https://0-doi-org.brum.beds.ac.uk/10.3390/s22072445 - 22 Mar 2022
Cited by 15 | Viewed by 3566
Abstract
This article presents the results of research with the main goal of identifying possible applications of edge computing (EC) in industry. This study used the methodology of systematic literature review and text mining analysis. The main findings showed that the primary goal of [...] Read more.
This article presents the results of research with the main goal of identifying possible applications of edge computing (EC) in industry. This study used the methodology of systematic literature review and text mining analysis. The main findings showed that the primary goal of EC is to reduce the time required to transfer large amounts of data. With the ability to analyze data at the edge, it is possible to obtain immediate feedback and use it in the decision-making process. However, the implementation of EC requires investments not only in infrastructure, but also in the development of employee knowledge related to modern computing methods based on artificial intelligence. As the results of the analyses showed, great importance is also attached to energy consumption, both in ongoing production processes and for the purposes of data transmission and analysis. This paper also highlights problems related to quality management. Based on the analyses, we indicate further research directions for the application of edge computing and associated technologies that are required in the area of intelligent resource scheduling (for flexible production systems and autonomous systems), anomaly detection and resulting decision making, data analysis and transfer, knowledge management (for smart designing), and simulations (for autonomous systems). Full article
(This article belongs to the Special Issue Prototyping of Industrial IoT Solutions)
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Review

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47 pages, 9741 KiB  
Review
Industrial Needs in the Fields of Artificial Intelligence, Internet of Things and Edge Computing
by Dorota Stadnicka, Jarosław Sęp, Riccardo Amadio, Daniele Mazzei, Marios Tyrovolas, Chrysostomos Stylios, Anna Carreras-Coch, Juan Alfonso Merino, Tomasz Żabiński and Joan Navarro
Sensors 2022, 22(12), 4501; https://0-doi-org.brum.beds.ac.uk/10.3390/s22124501 - 14 Jun 2022
Cited by 9 | Viewed by 4148
Abstract
Industry 4.0 corresponds to the Fourth Industrial Revolution, resulting from technological innovation and research multidisciplinary advances. Researchers aim to contribute to the digital transformation of the manufacturing ecosystem both in theory and mainly in practice by identifying the real problems that the industry [...] Read more.
Industry 4.0 corresponds to the Fourth Industrial Revolution, resulting from technological innovation and research multidisciplinary advances. Researchers aim to contribute to the digital transformation of the manufacturing ecosystem both in theory and mainly in practice by identifying the real problems that the industry faces. Researchers focus on providing practical solutions using technologies such as the Industrial Internet of Things (IoT), Artificial Intelligence (AI), and Edge Computing (EC). On the other hand, universities educate young engineers and researchers by formulating a curriculum that prepares graduates for the industrial market. This research aimed to investigate and identify the industry’s current problems and needs from an educational perspective. The research methodology is based on preparing a focused questionnaire resulting from an extensive recent literature review used to interview representatives from 70 enterprises operating in 25 countries. The produced empirical data revealed (1) the kind of data and business management systems that companies have implemented to advance the digitalization of their processes, (2) the industries’ main problems and what technologies (could be) implemented to address them, and (3) what are the primary industrial needs and how they can be met to facilitate their digitization. The main conclusion is that there is a need to develop a taxonomy that shall include industrial problems and their technological solutions. Moreover, the educational needs of engineers and researchers with current knowledge and advanced skills were underlined. Full article
(This article belongs to the Special Issue Prototyping of Industrial IoT Solutions)
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