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Computers
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Artificial Intelligence in Industrial IoT Applications
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Artificial Intelligence in Industrial IoT Applications

A special issue of Computers (ISSN 2073-431X). This special issue belongs to the section "Internet of Things (IoT) and Industrial IoT".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 4539

Special Issue Editor

Prof. Dr. Isidro Calvo

E-Mail Website
Guest Editor
Department of Systems Engineering and Automatic Control, Faculty of Engineering of Vitoria-Gasteiz, University of the Basque Country (UPV/EHU), 48940 Leioa, Spain
Interests: smart sensors; IIoT; cyber physical systems; artificial intelligence in industry

Special Issue Information

Dear Colleagues,

At present, the introduction of artificial intelligence techniques into manufacturing processes has enabled significant advances in production operations. Typically, these improvements aim to refine the quality and efficiency of processes and reduce the use of resources, such as energy, raw materials, or production time and labour.

Modern industrial applications are becoming complex cyber physical systems (CPSs) that improve the performance of the manufacturing processes, leading them to achieve higher efficiency, improve quality, and reduce the use of resources. For these purposes, modern industrial applications are introducing artificial intelligence techniques which are combined with communication technologies for integrating the data acquired from diverse nodes scattered among factories.

The introduction of new concepts into production processes, such as wireless sensor networks and the Industrial Internet of Things (IIoT), is supporting the collection of updated information in production operations. In general, the use of wireless communications introduces higher flexibility and allows mobile devices to be involved. These are important benefits in industrial environments.

However, the modern industrial processes found in Industry 4.0 applications produce large amounts of data, which must be managed efficiently. This is a key issue which can be addressed through the successful introduction of artificial intelligence techniques. In this scenario, new paradigms such as the so-called edge, fog, and cloud paradigms are being introduced to create complex application architectures.

These issues are of the outmost importance in modern industrial applications; therefore, the scientific community may benefit from the presentation of use cases that show the application of both modern processing techniques and communication techniques. For that reason, we invite colleagues in the research community to disseminate their novel contributions in these fields.

Prof. Dr. Isidro Calvo
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. Computers is an international peer-reviewed open access monthly 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 1800 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 Internet of Things (IIoT)
  • communication architectures for industrial processes
  • artificial intelligence in industry
  • cyber physical systems (CPS)
  • smart sensors and actuators
  • information architectures for CPSs
  • Industry 4.0
  • industrial communications
  • wireless communications
  • fuzzy logic
  • machine learning
  • edge computing
  • fog computing
  • cloud computing

Published Papers (3 papers)

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Research

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38 pages, 10287 KiB  
Article
Proposed Fuzzy-Stranded-Neural Network Model That Utilizes IoT Plant-Level Sensory Monitoring and Distributed Services for the Early Detection of Downy Mildew in Viticulture
by Sotirios Kontogiannis, Stefanos Koundouras and Christos Pikridas
Computers 2024, 13(3), 63; https://doi.org/10.3390/computers13030063 - 28 Feb 2024
Cited by 1 | Viewed by 874
Abstract
Novel monitoring architecture approaches are required to detect viticulture diseases early. Existing micro-climate decision support systems can only cope with late detection from empirical and semi-empirical models that provide less accurate results. Such models cannot alleviate precision viticulture planning and pesticide control actions, [...] Read more.
Novel monitoring architecture approaches are required to detect viticulture diseases early. Existing micro-climate decision support systems can only cope with late detection from empirical and semi-empirical models that provide less accurate results. Such models cannot alleviate precision viticulture planning and pesticide control actions, providing early reconnaissances that may trigger interventions. This paper presents a new plant-level monitoring architecture called thingsAI. The proposed system utilizes low-cost, autonomous, easy-to-install IoT sensors for vine-level monitoring, utilizing the low-power LoRaWAN protocol for sensory measurement acquisition. Facilitated by a distributed cloud architecture and open-source user interfaces, it provides state-of-the-art deep learning inference services and decision support interfaces. This paper also presents a new deep learning detection algorithm based on supervised fuzzy annotation processes, targeting downy mildew disease detection and, therefore, planning early interventions. The authors tested their proposed system and deep learning model on the grape variety of protected designation of origin called debina, cultivated in Zitsa, Greece. From their experimental results, the authors show that their proposed model can detect vine locations and timely breakpoints of mildew occurrences, which farmers can use as input for targeted intervention efforts. Full article
(This article belongs to the Special Issue Artificial Intelligence in Industrial IoT Applications)
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29 pages, 2949 KiB  
Article
Exploring the Potential of Distributed Computing Continuum Systems
by Praveen Kumar Donta, Ilir Murturi, Victor Casamayor Pujol, Boris Sedlak and Schahram Dustdar
Computers 2023, 12(10), 198; https://doi.org/10.3390/computers12100198 - 02 Oct 2023
Cited by 2 | Viewed by 2597
Abstract
Computing paradigms have evolved significantly in recent decades, moving from large room-sized resources (processors and memory) to incredibly small computing nodes. Recently, the power of computing has attracted almost all current application fields. Currently, distributed computing continuum systems (DCCSs) are unleashing the era [...] Read more.
Computing paradigms have evolved significantly in recent decades, moving from large room-sized resources (processors and memory) to incredibly small computing nodes. Recently, the power of computing has attracted almost all current application fields. Currently, distributed computing continuum systems (DCCSs) are unleashing the era of a computing paradigm that unifies various computing resources, including cloud, fog/edge computing, the Internet of Things (IoT), and mobile devices into a seamless and integrated continuum. Its seamless infrastructure efficiently manages diverse processing loads and ensures a consistent user experience. Furthermore, it provides a holistic solution to meet modern computing needs. In this context, this paper presents a deeper understanding of DCCSs’ potential in today’s computing environment. First, we discuss the evolution of computing paradigms up to DCCS. The general architectures, components, and various computing devices are discussed, and the benefits and limitations of each computing paradigm are analyzed. After that, our discussion continues into various computing devices that constitute part of DCCS to achieve computational goals in current and futuristic applications. In addition, we delve into the key features and benefits of DCCS from the perspective of current computing needs. Furthermore, we provide a comprehensive overview of emerging applications (with a case study analysis) that desperately need DCCS architectures to perform their tasks. Finally, we describe the open challenges and possible developments that need to be made to DCCS to unleash its widespread potential for the majority of applications. Full article
(This article belongs to the Special Issue Artificial Intelligence in Industrial IoT Applications)
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Review

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26 pages, 4964 KiB  
Review
Digital Twin and 3D Digital Twin: Concepts, Applications, and Challenges in Industry 4.0 for Digital Twin
by April Lia Hananto, Andy Tirta, Safarudin Gazali Herawan, Muhammad Idris, Manzoore Elahi M. Soudagar, Djati Wibowo Djamari and Ibham Veza
Computers 2024, 13(4), 100; https://doi.org/10.3390/computers13040100 - 16 Apr 2024
Viewed by 528
Abstract
The rapid development of digitalization, the Internet of Things (IoT), and Industry 4.0 has led to the emergence of the digital twin concept. IoT is an important pillar of the digital twin. The digital twin serves as a crucial link, merging the physical [...] Read more.
The rapid development of digitalization, the Internet of Things (IoT), and Industry 4.0 has led to the emergence of the digital twin concept. IoT is an important pillar of the digital twin. The digital twin serves as a crucial link, merging the physical and digital territories of Industry 4.0. Digital twins are beneficial to numerous industries, providing the capability to perform advanced analytics, create detailed simulations, and facilitate informed decision-making that IoT supports. This paper presents a review of the literature on digital twins, discussing its concepts, definitions, frameworks, application methods, and challenges. The review spans various domains, including manufacturing, energy, agriculture, maintenance, construction, transportation, and smart cities in Industry 4.0. The present study suggests that the terminology “3 dimensional (3D) digital twin” is a more fitting descriptor for digital twin technology assisted by IoT. The aforementioned statement serves as the central argument of the study. This article advocates for a shift in terminology, replacing “digital twin” with “3D digital twin” to more accurately depict the technology’s innate potential and capabilities in Industry 4.0. We aim to establish that “3D digital twin” offers a more precise and holistic representation of the technology. By doing so, we underline the digital twin’s analytical ability and capacity to offer an intuitive understanding of systems, which can significantly streamline decision-making processes using the digital twin. Full article
(This article belongs to the Special Issue Artificial Intelligence in Industrial IoT Applications)
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