Fault Diagnosis in the Internet of Things Applications
A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708). This special issue belongs to the section "Network Services and Applications".
Deadline for manuscript submissions: 31 March 2025 | Viewed by 10217
Special Issue Editors
Interests: anomaly detection; fault diagnosis; IIoT; machine learning; deep Learning; edge computing; cloud computing; cyber physical systems; embedded systems
Interests: machine learning; deep learning; cyber physical systems; Internet of Things; anomaly detection; fault diagnosis; edge computing; cloud computing
Special Issue Information
Dear Colleagues,
Recent years have observed phenomenal market growth of Internet of Things (IoT) applications with strong economic potential. The advancements of technology, both in terms of hardware and software, and the spread of IoT, have acted as catalysts for the development of a wide array of systems, where hundreds of devices cooperatively interact with the cyber and physical worlds.
At present, aspects related to fault diagnosis are becoming an important requirement for modern IoT applications to prevent or avoid potentially harmful conditions. In this sense, efficient monitoring and regular maintenance are crucial for the timely detection of faults (or anomalies) that can have, in the worst cases, catastrophic consequences. This is even more evident in the industrial sector, where the pervasive use of sensors and actuators engendered the Industry 4.0 paradigm that leverages the IoT to provide an estimate on the “health” condition of an industrial plant. In such a context, technologies such as artificial intelligence (AI), cloud computing, and edge computing emerge as the key enabling technologies of novel infrastructures for efficient monitoring, data collection, and analysis, which play a proactive role during the diagnosis process.
This Special Issue aims to collate original, unpublished and high-quality research articles focused on fault diagnosis solutions applied to the IoT and Industry 4.0.
The topics of interest include, but are not limited to, the following:
- AI methods for industrial applications;
- Machine learning applications at the edge;
- Deep learning fault diagnosis models;
- Intelligent fault detection;
- Industrial IoT applications;
- IoT energy efficient algorithms;
- Data fusion;
- IoT privacy and security;
- Predictive maintenance;
- Anomaly detection;
- Edge/cloud monitoring frameworks;
- Digital twins for fault diagnosis;
- Fault tolerance models.
Dr. Fabrizio De Vita
Dr. Giovanni Cicceri
Guest Editors
Manuscript Submission Information
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Keywords
- fault diagnosis
- anomaly detection
- Industry 4.0
- IoT
- edge computing
- cloud computing
- deep learning
- data fusion
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