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IoT
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Industrial IoT as IT and OT Convergence: Challenges and Opportunities
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Industrial IoT as IT and OT Convergence: Challenges and Opportunities

A special issue of IoT (ISSN 2624-831X).

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 62481

Special Issue Editors

Dr. Carlo Giannelli

E-Mail Website
Guest Editor
Department of Mathematics and Computer Science (DMI), University of Ferrara, Via Giuseppe Saragat, 1, 44122 Ferrara, Italy
Interests: IIoT; blockchain; software-defined networking; location/context awareness
Special Issues, Collections and Topics in MDPI journals
Dr. Marco Picone

E-Mail Website
Guest Editor
Department of Sciences and Methods for Engineering (DISMI), University of Modena and Reggio Emilia, Via Amendola 2, Pad. Morselli, 42121 Reggio Emilia, Italy
Interests: distributed systems; Internet of Things; edge computing; digital twins; pervasive and mobile ccomputing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

During the last decade, the advent of the Internet of Things (IoT) and its quick and pervasive evolution has significantly revolutionized the information technology ecosystem. The IoT will consist of billions of interconnected smart objects generating and consuming a huge amount of heterogeneous data. This massive amount of information has the power to revolutionize how applications and services are designed and deployed, allowing them to work more efficiently and profitably. In this context, the Industrial Internet of Things (IIoT) represents the fourth industrial revolution (also denoted as Industry 4.0) and is disrupting existing approaches and creating opportunities for growth in terms of innovations, developments, and disruptive business models.

Historically, on the one hand, operation technology (OT) has the role to support physical value creation and manufacturing processes involving devices, sensors, and software required to control and monitor plants and equipment. On the other hand, information technology (IT) combines all necessary information processing and technologies. Traditionally, industries have seen and handled OT and IT as two different specific domains, keeping separate technology stacks, protocols, standards, management, and organizational units. The advent of the IoT is changing this vision and, progressively, these two domains have gradually started to share common approaches and technologies. The convergence of IT and OT together with the IoT represents an appealing challenge for both the academic and the industrial research communities, with the aim of bringing enhanced performance and gains in terms of flexibility and interoperability.

This Special Issue focuses on the innovative developments, technologies, and challenges related to the convergence of IT and OT in IoT application scenarios. This Special Issue seeks the latest findings from research and ongoing projects, also including practical use cases and detailed real-world deployment toward gaining new insights. Additionally, review articles that provide readers with current research trends and solutions are also welcome. The potential topics include, but are not limited to:

  • Industrial Internet of Things use cases
  • Architectural and networking innovation for OT/IT interoperability
  • Cybersecurity for OT/IT convergence
  • IoT security protocols and IoT networking and communication security
  • Adoption of edge and fog computing for the shop floor
  • Cloud and edge/fog synchronization, interoperability, and hybrid architectures
  • Multiple access network technologies management, e.g., 5G/fiber/ethernet
  • Management of protocol heterogeneity and translation
  • Digital twin as a technological enabler for new IIoT architectures and deployments

Dr. Carlo Giannelli
Dr. Marco Picone
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. IoT is an international peer-reviewed open access quarterly 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 1200 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.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (8 papers)

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Editorial

Jump to: Research, Review

3 pages, 170 KiB  
Editorial
Editorial “Industrial IoT as IT and OT Convergence: Challenges and Opportunities”
by Carlo Giannelli and Marco Picone
IoT 2022, 3(1), 259-261; https://doi.org/10.3390/iot3010014 - 15 Mar 2022
Cited by 10 | Viewed by 4021
Abstract
During the last decade, the advent of the Internet of Things (IoT) and its quick and pervasive evolution have significantly revolutionized the Information Technology ecosystem [...] Full article
(This article belongs to the Special Issue Industrial IoT as IT and OT Convergence: Challenges and Opportunities)

Research

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24 pages, 9114 KiB  
Article
Methodology and Tools for Digital Twin Management—The FA3ST Approach
by Ljiljana Stojanovic, Thomas Usländer, Friedrich Volz, Christian Weißenbacher, Jens Müller, Michael Jacoby and Tino Bischoff
IoT 2021, 2(4), 717-740; https://doi.org/10.3390/iot2040036 - 26 Nov 2021
Cited by 29 | Viewed by 7955
Abstract
The concept of digital twins (DT) has already been discussed some decades ago. Digital representations of physical assets are key components in industrial applications as they are the basis for decision making. What is new is the conceptual approach to consider DT as [...] Read more.
The concept of digital twins (DT) has already been discussed some decades ago. Digital representations of physical assets are key components in industrial applications as they are the basis for decision making. What is new is the conceptual approach to consider DT as well-defined software entities themselves that follow the whole lifecycle of their physical counterparts from the engineering, operation up to the discharge, and hence, have their own type description, identity, and lifecycle. This paper elaborates on this idea and argues the need for systematic DT engineering and management. After a conceptual description of DT, the paper proposes a DT lifecycle model and presents methodologies and tools for DT management, also in the context of Industrie 4.0 concepts, such as the asset administration shell (AAS), the international data spaces (IDS), and IEC standards (such as OPC UA and AML). As a tool example for the support of DT engineering and management, the Fraunhofer-advanced AAS tools for digital twins (FA3ST) are presented in more detail. Full article
(This article belongs to the Special Issue Industrial IoT as IT and OT Convergence: Challenges and Opportunities)
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20 pages, 4992 KiB  
Article
Anomaly Detection and Classification in Predictive Maintenance Tasks with Zero Initial Training
by Filippo Morselli, Luca Bedogni, Umberto Mirani, Michele Fantoni and Simone Galasso
IoT 2021, 2(4), 590-609; https://doi.org/10.3390/iot2040030 - 9 Oct 2021
Cited by 5 | Viewed by 5192
Abstract
The Fourth Industrial Revolution has led to the adoption of novel technologies and methodologies in factories, making these more efficient and productive. Among the new services which are changing industry, there are those based on machine learning algorithms, which enable machines to learn [...] Read more.
The Fourth Industrial Revolution has led to the adoption of novel technologies and methodologies in factories, making these more efficient and productive. Among the new services which are changing industry, there are those based on machine learning algorithms, which enable machines to learn from their past observations and hence possibly forecast future states. Specifically, predictive maintenance represents the opportunity to understand in advance possible machine outages due to broken parts and schedule the necessary maintenance operations. However, in real scenarios predictive maintenance struggles to be adopted due to a multitude of variables and the heavy customization it requires. In this work, we propose a novel framework for predictive maintenance, which is trained online to recognize new issues reported by the operators. Our framework, tested on different scenarios and with a varying number and several kinds of sensors, shows recall levels above 0.85, demonstrating its effectiveness and adaptability. Full article
(This article belongs to the Special Issue Industrial IoT as IT and OT Convergence: Challenges and Opportunities)
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26 pages, 14140 KiB  
Article
CultivData: Application of IoT to the Cultivation of Agricultural Data
by Felipe Lemus-Prieto, Juan Francisco Bermejo Martín, José-Luis Gónzalez-Sánchez and Enrique Moreno Sánchez
IoT 2021, 2(4), 564-589; https://doi.org/10.3390/iot2040029 - 23 Sep 2021
Cited by 4 | Viewed by 3885
Abstract
CultivData proposes the convergence of technologies, such as IoT, big data, HPC, open data and artificial intelligence, to apply HPDA (High Performance Data Analytics) to the cultivation of agricultural data and improve the efficiency and effectiveness of farms. An information system has been [...] Read more.
CultivData proposes the convergence of technologies, such as IoT, big data, HPC, open data and artificial intelligence, to apply HPDA (High Performance Data Analytics) to the cultivation of agricultural data and improve the efficiency and effectiveness of farms. An information system has been developed as an IT platform for the cultivation of open data to extract knowledge and to support the decision making of stakeholders in the agricultural sector, so that it is possible to improve product quality and farm productivity. The resulting system integrates access to data provided by IoT devices that sensorize farms and public and open data sources (Open Data). The platform was designed to make precision agriculture a reality and to be useful not only to farmers, but also to agricultural decision-makers who plan species and crops based on data such as available water; expected weather; prices and market demands, and so forth. In addition, the platform provides to agricultural producers access to historical climate data; climate forecasts to anticipate times of drought or disasters; pest situations or monitoring of their plantations with sensorization and orthophotographs. Full article
(This article belongs to the Special Issue Industrial IoT as IT and OT Convergence: Challenges and Opportunities)
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21 pages, 1302 KiB  
Article
Towards a Hybrid Deep Learning Model for Anomalous Activities Detection in Internet of Things Networks
by Imtiaz Ullah, Ayaz Ullah and Mazhar Sajjad
IoT 2021, 2(3), 428-448; https://doi.org/10.3390/iot2030022 - 27 Jul 2021
Cited by 33 | Viewed by 6534
Abstract
The tremendous number of Internet of Things (IoT) applications, with their ubiquity, has provided us with unprecedented productivity and simplified our daily life. At the same time, the insecurity of these technologies ensures that our daily lives are surrounded by vulnerable computers, allowing [...] Read more.
The tremendous number of Internet of Things (IoT) applications, with their ubiquity, has provided us with unprecedented productivity and simplified our daily life. At the same time, the insecurity of these technologies ensures that our daily lives are surrounded by vulnerable computers, allowing for the launch of multiple attacks via large-scale botnets through the IoT. These attacks have been successful in achieving their heinous objectives. A strong identification strategy is essential to keep devices secured. This paper proposes and implements a model for anomaly-based intrusion detection in IoT networks that uses a convolutional neural network (CNN) and gated recurrent unit (GRU) to detect and classify binary and multiclass IoT network data. The proposed model is validated using the BoT-IoT, IoT Network Intrusion, MQTT-IoT-IDS2020, and IoT-23 intrusion detection datasets. Our proposed binary and multiclass classification model achieved an exceptionally high level of accuracy, precision, recall, and F1 score. Full article
(This article belongs to the Special Issue Industrial IoT as IT and OT Convergence: Challenges and Opportunities)
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17 pages, 3038 KiB  
Article
A Conceptual Architecture in Decentralizing Computing, Storage, and Networking Aspect of IoT Infrastructure
by Yustus Eko Oktian, Elizabeth Nathania Witanto and Sang-Gon Lee
IoT 2021, 2(2), 205-221; https://doi.org/10.3390/iot2020011 - 28 Mar 2021
Cited by 19 | Viewed by 7139
Abstract
Since the inception of the Internet of Things (IoT), we have adopted centralized architecture for decades. With the vastly growing number of IoT devices and gateways, this architecture struggles to cope with the high demands of state-of-the-art IoT services, which require scalable and [...] Read more.
Since the inception of the Internet of Things (IoT), we have adopted centralized architecture for decades. With the vastly growing number of IoT devices and gateways, this architecture struggles to cope with the high demands of state-of-the-art IoT services, which require scalable and responsive infrastructure. In response, decentralization becomes a considerable interest among IoT adopters. Following a similar trajectory, this paper introduces an IoT architecture re-work that enables three spheres of IoT workflows (i.e., computing, storage, and networking) to be run in a distributed manner. In particular, we employ the blockchain and smart contract to provide a secure computing platform. The distributed storage network maintains the saving of IoT raw data and application data. The software-defined networking (SDN) controllers and SDN switches exist in the architecture to provide connectivity across multiple IoT domains. We envision all of those services in the form of separate yet integrated peer-to-peer (P2P) overlay networks, which IoT actors such as IoT domain owners, IoT users, Internet Service Provider (ISP), and government can cultivate. We also present several IoT workflow examples showing how IoT developers can adapt to this new proposed architecture. Based on the presented workflows, the IoT computing can be performed in a trusted and privacy-preserving manner, the IoT storage can be made robust and verifiable, and finally, we can react to the network events automatically and quickly. Our discussions in this paper can be beneficial for many people ranging from academia, industries, and investors that are interested in the future of IoT in general. Full article
(This article belongs to the Special Issue Industrial IoT as IT and OT Convergence: Challenges and Opportunities)
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16 pages, 3281 KiB  
Article
Supervisory Control and Data Acquisition Approach in Node-RED: Application and Discussions
by Ioana-Victoria Nițulescu and Adrian Korodi
IoT 2020, 1(1), 76-91; https://doi.org/10.3390/iot1010005 - 10 Aug 2020
Cited by 27 | Viewed by 11892
Abstract
The Internet of Things (IoT) represents the binder of two worlds, specifically the real one and the digital one: tangible objects become recognizable in the virtual world, having digital matches, thus creating a network that enables the connection in-between the components. With the [...] Read more.
The Internet of Things (IoT) represents the binder of two worlds, specifically the real one and the digital one: tangible objects become recognizable in the virtual world, having digital matches, thus creating a network that enables the connection in-between the components. With the contemporary evolution of this domain, interconnectivity has become a primary fraction of new research and development directions. The Industrial Internet of Things (IIoT) is a concept that covers the more industrial level of the physical and digital connection and stays behind the Industry 4.0 concept. Supervisory control and data acquisition (SCADA) applications are important in the industry, their core being very present as complex products of big companies, at high prices. The Node-RED environment quickly evolved as one of the most important perspectives in IIoT, able to replace, up to a certain level, classic SCADA applications, bringing benefits to the industry. In this paper, the main focus is to evidence this aspect and to develop an application that will demonstrate the functionality of the concept, making use of protocols such as Modbus TCP (Transmission Control Protocol) for interacting with industrial devices and Message Queuing Telemetry Transport (MQTT) to interact with higher-levels, which provides a publish-subscribe structuring and a low band-width usage. The application uses logging and archiving modules based on InfluxDB database and is conceived to achieve the visual supervisory structure as close as possible to well-known SCADA solutions. The presented work results prove the efficiency of the solution. Full article
(This article belongs to the Special Issue Industrial IoT as IT and OT Convergence: Challenges and Opportunities)
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Review

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22 pages, 2298 KiB  
Review
A Study on Industrial IoT for the Mining Industry: Synthesized Architecture and Open Research Directions
by Abdullah Aziz, Olov Schelén and Ulf Bodin
IoT 2020, 1(2), 529-550; https://doi.org/10.3390/iot1020029 - 10 Dec 2020
Cited by 49 | Viewed by 12260
Abstract
The Industrial Internet of Things (IIoT) has the potential to improve the production and business processes by enabling the extraction of valuable information from industrial processes. The mining industry, however, is rather traditional and somewhat slow to change due to infrastructural limitations in [...] Read more.
The Industrial Internet of Things (IIoT) has the potential to improve the production and business processes by enabling the extraction of valuable information from industrial processes. The mining industry, however, is rather traditional and somewhat slow to change due to infrastructural limitations in communication, data management, storage, and exchange of information. Most research efforts so far on applying IIoT in the mining industry focus on specific concerns such as ventilation monitoring, accident analysis, fleet and personnel management, tailing dam monitoring, and pre-alarm system while an overall IIoT architecture suitable for the general conditions in the mining industry is still missing. This article analyzes the current state of Information Technology in the mining sector and identifies a major challenge of vertical fragmentation due to the technological variety of various systems and devices offered by different vendors, preventing interoperability, data distribution, and the exchange of information securely between devices and systems. Based on guidelines and practices from the major IIoT standards, a high-level IIoT architecture suitable for the mining industry is then synthesized and presented, addressing the identified challenges and enabling smart mines by automation, interoperable systems, data distribution, and real-time visibility of the mining status. Remote controlling, data processing, and interoperability techniques of the architecture evolve all stages of mining from prospecting to reclamation. The adoption of such IIoT architecture in the mining industry offers safer mine site for workers, predictable mining operations, interoperable environment for both traditional and modern systems and devices, automation to reduce human intervention, and enables underground surveillance by converging operational technology (OT) and information technology (IT). Significant open research challenges and directions are also studied and identified in this paper, such as mobility management, scalability, virtualization at the IIoT edge, and digital twins. Full article
(This article belongs to the Special Issue Industrial IoT as IT and OT Convergence: Challenges and Opportunities)
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