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Industrial Internet of Things: Emerging Trends in the Domain of Manufacturing and Energy Management

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (20 April 2022) | Viewed by 17615

Special Issue Editor

Dr. Lorenzo Ricciardi Celsi

E-Mail Website1 Website2
Guest Editor
Elis Innovation Hub, via Sandro Sandri 81, 00159 Rome, Italy
Interests: IIoT; anomaly detection; predictive maintenance; output regulation; multiagent control

Special Issue Information

Dear Colleagues,

Over the last few years, several companies operating in the manufacturing and energy management domains have expressed relevant business needs that can be successfully addressed through Industrial Internet of Things (IIoT) technology. There has been a dramatic increase in the attention paid by the international scientific community to the research topic of the emerging applications of IIoT, especially those aimed at fostering the adoption of cloud- and edge-computing resources as well as of 5G/6G mobile networks. Ranging from data collection through data preparation and analytics to distributed control systems relying on smart sensors, IIoT is indeed expected to provide increased connectivity and a significantly higher degree of automation.

This Special Issue intends to provide a comprehensive overview of the most recent and promising advancements in IIoT. Submissions are expected to cover the current state of the art and highlight the remaining challenges and barriers to the development of intelligent IIoT solutions aimed at addressing the emerging needs of the manufacturing and energy management sector. Potential topics include but are not limited to the following: predictive or even prescriptive maintenance solutions based on AI and machine learning; intelligent and resilient approaches to preserving safety and security of the manufacturing/power plant considered as a critical infrastructure; intelligent IIoT solutions integrating measurements coming from additive sensors that are external to the Manufacturing Execution System (MES) of the considered plant; innovatively distributed control protocols applied to IIoT scenarios (e.g., drone swarms or teams of unmanned ground vehicles equipped with computer vision technologies for surveillance, control and inspection of critical infrastructures); promoting the digital twin of power and water infrastructures based on the IIoT paradigm.

Dr. Lorenzo Ricciardi Celsi
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. Energies 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
  • IIoT
  • 5G/6G
  • edge computing
  • predictive maintenance
  • prescriptive maintenance
  • distributed control systems
  • surveillance of critical infrastructures
  • digital twin

Published Papers (3 papers)

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Research

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13 pages, 6675 KiB  
Article
A Multi-Variable DTR Algorithm for the Estimation of Conductor Temperature and Ampacity on HV Overhead Lines by IoT Data Sensors
by Rossana Coccia, Veronica Tonti, Chiara Germanò, Francesco Palone, Lorenzo Papi and Lorenzo Ricciardi Celsi
Energies 2022, 15(7), 2581; https://0-doi-org.brum.beds.ac.uk/10.3390/en15072581 - 01 Apr 2022
Cited by 2 | Viewed by 1841
Abstract
The transfer capabilities of High-Voltage Overhead Lines (HV OHLs) are often limited by the critical power line temperature that depends on the magnitude of the transferred current and the ambient conditions, i.e., ambient temperature, wind, etc. To utilize existing power lines more effectively [...] Read more.
The transfer capabilities of High-Voltage Overhead Lines (HV OHLs) are often limited by the critical power line temperature that depends on the magnitude of the transferred current and the ambient conditions, i.e., ambient temperature, wind, etc. To utilize existing power lines more effectively (with a view to progressive decarbonization) and more safely with respect to the critical power line temperatures, this paper proposes a Dynamic Thermal Rating (DTR) approach using IoT sensors installed on some HV OHLs located in different Italian geographical locations. The goal is to estimate the OHL conductor temperature and ampacity, using a data-driven thermo-mechanical model with the Bayesian probability approach, in order to improve the confidence interval of the results. This work highlights that it could be possible to estimate a space-time distribution of temperature for each OHL and an increase in the actual current threshold values for optimizing OHL ampacity. The proposed model is validated using the Monte Carlo method. Full article
(This article belongs to the Special Issue Industrial Internet of Things: Emerging Trends in the Domain of Manufacturing and Energy Management)
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Review

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30 pages, 1830 KiB  
Review
Internet of Things Approaches for Monitoring and Control of Smart Greenhouses in Industry 4.0
by Chiara Bersani, Carmelina Ruggiero, Roberto Sacile, Abdellatif Soussi and Enrico Zero
Energies 2022, 15(10), 3834; https://0-doi-org.brum.beds.ac.uk/10.3390/en15103834 - 23 May 2022
Cited by 28 | Viewed by 9325
Abstract
In recent decades, climate change and a shortage of resources have brought about the need for technology in agriculture. Farmers have been forced to use information and innovation in communication in order to enhance production efficiency and crop resilience. Systems engineering and information [...] Read more.
In recent decades, climate change and a shortage of resources have brought about the need for technology in agriculture. Farmers have been forced to use information and innovation in communication in order to enhance production efficiency and crop resilience. Systems engineering and information infrastructure based on the Internet of Things (IoT) are the main novel approaches that have generated growing interest. In agriculture, IoT solutions according to the challenges for Industry 4.0 can be applied to greenhouses. Greenhouses are protected environments in which best plant growth can be achieved. IoT for smart greenhouses relates to sensors, devices, and information and communication infrastructure for real-time monitoring and data collection and processing, in order to efficiently control indoor parameters such as exposure to light, ventilation, humidity, temperature, and carbon dioxide level. This paper presents the current state of the art in the IoT-based applications to smart greenhouses, underlining benefits and opportunities of this technology in the agriculture environment. Full article
(This article belongs to the Special Issue Industrial Internet of Things: Emerging Trends in the Domain of Manufacturing and Energy Management)
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28 pages, 624 KiB  
Review
Edge-Oriented Computing: A Survey on Research and Use Cases
by Nour Alhuda Sulieman, Lorenzo Ricciardi Celsi, Wei Li, Albert Zomaya and Massimo Villari
Energies 2022, 15(2), 452; https://0-doi-org.brum.beds.ac.uk/10.3390/en15020452 - 10 Jan 2022
Cited by 28 | Viewed by 5759
Abstract
Edge computing is a distributed computing paradigm such that client data are processed at the periphery of the network, as close as possible to the originating source. Since the 21st century has come to be known as the century of data due to [...] Read more.
Edge computing is a distributed computing paradigm such that client data are processed at the periphery of the network, as close as possible to the originating source. Since the 21st century has come to be known as the century of data due to the rapid increase in the quantity of exchanged data worldwide (especially in smart city applications such as autonomous vehicles), collecting and processing such data from sensors and Internet of Things devices operating in real time from remote locations and inhospitable operating environments almost anywhere in the world is a relevant emerging need. Indeed, edge computing is reshaping information technology and business computing. In this respect, the paper is aimed at providing a comprehensive overview of what edge computing is as well as the most relevant edge use cases, tradeoffs, and implementation considerations. In particular, this review article is focused on highlighting (i) the most recent trends relative to edge computing emerging in the research field and (ii) the main businesses that are taking operations at the edge as well as the most used edge computing platforms (both proprietary and open source). First, the paper summarizes the concept of edge computing and compares it with cloud computing. After that, we discuss the challenges of optimal server placement, data security in edge networks, hybrid edge-cloud computing, simulation platforms for edge computing, and state-of-the-art improved edge networks. Finally, we explain the edge computing applications to 5G/6G networks and industrial internet of things. Several studies review a set of attractive edge features, system architectures, and edge application platforms that impact different industry sectors. The experimental results achieved in the cited works are reported in order to prove how edge computing improves the efficiency of Internet of Things networks. On the other hand, the work highlights possible vulnerabilities and open issues emerging in the context of edge computing architectures, thus proposing future directions to be investigated. Full article
(This article belongs to the Special Issue Industrial Internet of Things: Emerging Trends in the Domain of Manufacturing and Energy Management)
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