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Smart Sensors in the Industrial Internet of Things (IIoT)
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Smart Sensors in the Industrial Internet of Things (IIoT)

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

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 25691

Special Issue Editors

Prof. Dr. Jorn Mehnen

E-Mail Website
Guest Editor
Design, Manufacturing and Engineering Management Department, The University of Strathclyde, Glasgow G1 1XJ, UK
Interests: Industry 4.0; IoT; AI/CI; big data analysis; cloud manufacturing
Special Issues, Collections and Topics in MDPI journals
Prof. Weidong Li

E-Mail Website
Guest Editor
Manufacturing, Coventry University, Priory St, Coventry CV1 5FB, UK
Interests: cloud manufacturing; advanced manufacturing
Prof. Dr. Xifan Yao

E-Mail Website
Guest Editor
School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China
Interests: smart production; cyber-physical production system; industry 4.0/5.0
Special Issues, Collections and Topics in MDPI journals
Dr. Hongmei He

E-Mail Website
Guest Editor
School of Computer Science and Informatics, De Montfort University, Leicester, UK
Interests: machine learning; security; sensor data fusion; robotics

Special Issue Information

Dear Colleagues,

The Industrial Internet of Things (IIoT) is not a matter of hype anymore—it has matured into a highly successful technology that many modern digital-based companies utilize to rapidly expand their businesses. The IIoT provides instant real-time data that are crucial for agile decision making. It supports the whole lifecycle of a product, from its design and make to its use, service, and remanufacture. IIoT connects the user with the product and the business through technical and financial information. It also establishes emotional as well as immersive links between user and product. Advanced meshed networks of smart sensors and tailored cloud services are the means that deliver the right data at the right time to allow for rapid decision making for more adaptive, agile, and scalable services that make the difference for companies that address the needs of their customers.

This Special Issue is dedicated to interdisciplinary research that makes IIoT the powerful tool it is today. It is calling for cutting-edge contributions to fundamental research that enables IIoT as well as groundbreaking applications of research of industrial smart sensors in industry. This Special Issue covers but is not limited to the following topics:

  • Smart Sensors with Edge AI
  • IIoT networks and meshes
  • Wearables for IIoT
  • Robotics and IIoT
  • Smart IIoT services
  • New business models based on IIoT
  • Industrial applications of IIoT
  • Security and trust in IIoT
  • Mixed realities and IIoT
  • Digital manufacturing
  • Device-to-cloud IIoT solutions
  • Intelligent sensing for IIoT

Both review articles and original research papers are solicited.

Prof. Jorn Mehnen
Prof. Weidong Li
Prof. Xifan Yao
Dr. Hongmei He
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

  • smart sensors
  • Industrial Internet of Things (IIoT)
  • edge AI
  • Robotics and automation
  • security
  • cloud technologies
  • advanced manufacturing and services

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Published Papers (4 papers)

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Research

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17 pages, 400 KiB  
Article
Cost-Effective Vibration Analysis through Data-Backed Pipeline Optimisation
by Artur Sokolovsky, David Hare and Jorn Mehnen
Sensors 2021, 21(19), 6678; https://doi.org/10.3390/s21196678 - 8 Oct 2021
Cited by 2 | Viewed by 2462
Abstract
Vibration analysis is an active area of research, aimed, among other targets, at an accurate classification of machinery failure modes. The analysis often leads to complex and convoluted signal processing pipeline designs, which are computationally demanding and often cannot be deployed in IoT [...] Read more.
Vibration analysis is an active area of research, aimed, among other targets, at an accurate classification of machinery failure modes. The analysis often leads to complex and convoluted signal processing pipeline designs, which are computationally demanding and often cannot be deployed in IoT devices. In the current work, we address this issue by proposing a data-driven methodology that allows optimising and justifying the complexity of the signal processing pipelines. Additionally, aiming to make IoT vibration analysis systems more cost- and computationally efficient, on the example of MAFAULDA vibration dataset, we assess the changes in the failure classification performance at low sampling rates as well as short observation time windows. We find out that a decrease of the sampling rate from 50 kHz to 1 kHz leads to a statistically significant classification performance drop. A statistically significant decrease is also observed for the 0.1 s time window compared to the 5 s one. However, the effect sizes are small to medium, suggesting that in certain settings lower sampling rates and shorter observation windows might be worth using, consequently making the use of the more cost-efficient sensors feasible. The proposed optimisation approach, as well as the statistically supported findings of the study, allow for an efficient design of IoT vibration analysis systems, both in terms of complexity and costs, bringing us one step closer to the widely accessible IoT/Edge-based vibration analysis. Full article
(This article belongs to the Special Issue Smart Sensors in the Industrial Internet of Things (IIoT))
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20 pages, 1301 KiB  
Article
A Complete Key Management Scheme for LoRaWAN v1.1
by Xingda Chen, Margaret Lech and Liuping Wang
Sensors 2021, 21(9), 2962; https://doi.org/10.3390/s21092962 - 23 Apr 2021
Cited by 14 | Viewed by 3984
Abstract
Security is one of the major concerns of the Internet of Things (IoT) wireless technologies. LoRaWAN is one of the emerging Low Power Wide Area Networks being developed for IoT applications. The latest LoRaWAN release v.1.1 has provided a security framework that includes [...] Read more.
Security is one of the major concerns of the Internet of Things (IoT) wireless technologies. LoRaWAN is one of the emerging Low Power Wide Area Networks being developed for IoT applications. The latest LoRaWAN release v.1.1 has provided a security framework that includes data confidentiality protection, data integrity check, device authentication and key management. However, its key management part is only ambiguously defined. In this paper, a complete key management scheme is proposed for LoRaWAN. The scheme addresses key updating, key generation, key backup, and key backward compatibility. The proposed scheme was shown not only to enhance the current LoRaWAN standard, but also to meet the primary design consideration of LoRaWAN, i.e., low power consumption. Full article
(This article belongs to the Special Issue Smart Sensors in the Industrial Internet of Things (IIoT))
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Review

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45 pages, 13461 KiB  
Review
Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions
by Shahid Latif, Maha Driss, Wadii Boulila, Zil e Huma, Sajjad Shaukat Jamal, Zeba Idrees and Jawad Ahmad
Sensors 2021, 21(22), 7518; https://doi.org/10.3390/s21227518 - 12 Nov 2021
Cited by 76 | Viewed by 9882
Abstract
The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast communication protocols, and efficient cybersecurity mechanisms to improve industrial processes and applications. In large industrial networks, smart devices generate large amounts of data, and thus IIoT frameworks require [...] Read more.
The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast communication protocols, and efficient cybersecurity mechanisms to improve industrial processes and applications. In large industrial networks, smart devices generate large amounts of data, and thus IIoT frameworks require intelligent, robust techniques for big data analysis. Artificial intelligence (AI) and deep learning (DL) techniques produce promising results in IIoT networks due to their intelligent learning and processing capabilities. This survey article assesses the potential of DL in IIoT applications and presents a brief architecture of IIoT with key enabling technologies. Several well-known DL algorithms are then discussed along with their theoretical backgrounds and several software and hardware frameworks for DL implementations. Potential deployments of DL techniques in IIoT applications are briefly discussed. Finally, this survey highlights significant challenges and future directions for future research endeavors. Full article
(This article belongs to the Special Issue Smart Sensors in the Industrial Internet of Things (IIoT))
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30 pages, 1225 KiB  
Review
Recent Technologies, Security Countermeasure and Ongoing Challenges of Industrial Internet of Things (IIoT): A Survey
by Soo Fun Tan and Azman Samsudin
Sensors 2021, 21(19), 6647; https://doi.org/10.3390/s21196647 - 6 Oct 2021
Cited by 49 | Viewed by 7247
Abstract
The inherent complexities of Industrial Internet of Things (IIoT) architecture make its security and privacy issues becoming critically challenging. Numerous surveys have been published to review IoT security issues and challenges. The studies gave a general overview of IIoT security threats or a [...] Read more.
The inherent complexities of Industrial Internet of Things (IIoT) architecture make its security and privacy issues becoming critically challenging. Numerous surveys have been published to review IoT security issues and challenges. The studies gave a general overview of IIoT security threats or a detailed analysis that explicitly focuses on specific technologies. However, recent studies fail to analyze the gap between security requirements of these technologies and their deployed countermeasure in the industry recently. Whether recent industry countermeasure is still adequate to address the security challenges of IIoT environment are questionable. This article presents a comprehensive survey of IIoT security and provides insight into today’s industry countermeasure, current research proposals and ongoing challenges. We classify IIoT technologies into the four-layer security architecture, examine the deployed countermeasure based on CIA+ security requirements, report the deficiencies of today’s countermeasure, and highlight the remaining open issues and challenges. As no single solution can fix the entire IIoT ecosystem, IIoT security architecture with a higher abstraction level using the bottom-up approach is needed. Moving towards a data-centric approach that assures data protection whenever and wherever it goes could potentially solve the challenges of industry deployment. Full article
(This article belongs to the Special Issue Smart Sensors in the Industrial Internet of Things (IIoT))
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