Advanced Fault and Error Detection Techniques Using Machine Learning and Artificial Intelligence
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 9
Special Issue Editors
Interests: machine learning; deep learning; data mining; parallel algorithms; data structures; information retrieval
Special Issues, Collections and Topics in MDPI journals
Interests: algorithms; data structures; data mining; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid development of research in the field of Artificial Intelligence (AI) has led to the implementation of revolutionary methods for detecting faults and errors in a wide range of systems. Today, a large number of researchers are working to improve the existing methods and invent new approaches with greater efficiency. Sophisticated AI and Machine Learning models are being constantly introduced with the aim of detecting faults in a wide range of industries, from manufacturing to energy production, by analyzing vibrations, temperature changes, pressure variations, and other operational metrics.
This Special Issue aims to explore the most recent advances in the area of fault, error, and defect detection with Machine Learning/Artificial Intelligence models and algorithms. We call the interested research groups to submit high-quality, original studies in the relevant areas. The Special Issue will also host comprehensive review articles on the involved research fields.
Indicative topics of interest include, but are not limited to, the following:
- Fault, error, and defect detection AI/ML models in a wide variety of application areas such as industrial robotics, rotating machinery, oil & gas industry, healthcare equipment, Heating/Ventilation/Air Conditioning (HVAC) Systems, fabrics industry, telecommunications networks, computer software, and others.
- Predictive Maintenance in Manufacturing
- Energy Grid & Power Systems Monitoring
- Automotive Diagnostics
- Aircraft Health Monitoring
- Smart Buildings
- Data mining and data augmentation techniques in fault detection systems
- Anomaly detection in fault detection systems.
Dr. Leonidas Akritidis
Prof. Dr. Panayiotis Bozanis
Guest Editors
Manuscript Submission Information
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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. Electronics 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 2400 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
- fault detection
- error detection
- defect detection
- health monitoring
- diagnostics
- machine learning
- artificial intelligence
- classification
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