Fault Diagnosis in the Internet of Things Applications

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This Special Issue aims to collate original, unpublished and high-quality research articles focused on fault diagnosis solutions applied to the IoT and Industry 4.0.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

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. Journal of Sensor and Actuator Networks 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 2000 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.

• fault diagnosis
• anomaly detection
• Industry 4.0
• IoT
• edge computing
• cloud computing
• deep learning
• data fusion