Artificial Intelligence in Industrial Systems: From Data Acquisition to Intelligent Decision-Making

A special issue of AI (ISSN 2673-2688). This special issue belongs to the section "AI in Autonomous Systems".

Deadline for manuscript submissions: 31 January 2026

Special Issue Editors


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Guest Editor
Faculty of Engineering, University of Deusto, Bilbao (48940), Spain
Interests: communication protocols; edge-AI; PLCs; RFID
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Faculty of Engineering, University of Deusto, 48007, Bilbao, Spain
Interests: embedded systems; remote laboratories; edge-AI

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Guest Editor
Department of eTourism and Cultural Heritage, Vicomtech, Paseo Mikeletegi 57, E-20009 Donostia, San Sebastian, Spain
Interests: cyber physical systems; embedded systems; Industry 4.0

Special Issue Information

The primary aim of this Special Issue is to explore the transformative role of Artificial Intelligence (AI) in solving practical industrial problems across the full data lifecycle—from acquisition to actionable insights. While AI has traditionally been associated with prediction and automation, its integration with sensor systems, edge devices, and industrial networks opens new avenues for intelligent decision-making, real-time optimization, and adaptive control in complex industrial environments.

 

The scope of this Special Issue encompasses the application of AI methods in diverse industrial domains such as manufacturing, energy, logistics, transportation, and smart infrastructure. Topics include AI-driven approaches for sensor data acquisition, fusion, real-time processing, anomaly detection, fault diagnosis, process optimization, and predictive maintenance. We aim to gather interdisciplinary research that not only showcases successful implementations but also addresses technical challenges such as data sparsity, model robustness, and the integration of AI into legacy systems.

 

This Special Issue seeks to supplement the existing literature by bridging the gap between the theory of AI and its deployment in industrial practice. While numerous studies have advanced AI methods in controlled or simulated settings, this Special Issue emphasizes applied research that demonstrates tangible improvements in industrial performance. In doing so, it contributes to the evolving discourse on Industry 4.0 and AI-driven digital transformation, offering both methodological insights and practical case studies.

Dr. Hugo Landaluce
Dr. Ignacio Angulo Martínez
Dr. Ander Garcia
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. AI 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 1600 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

  • artificial intelligence
  • industrial applications
  • sensor systems
  • predictive maintenance
  • smart manufacturing
  • intelligent decision-making
  • data acquisition and analysis

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Published Papers

This special issue is now open for submission.
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