Predictive maintenance in industrial IoT (IIoT)

Fawaz S. Al-Anzi; Abdullah F. Al-Anzi; Sumi Sarath

doi:10.1117/12.3030667

26 June 2024 Predictive maintenance in industrial IoT (IIoT)

Fawaz S. Al-Anzi, Abdullah F. Al-Anzi, Sumi Sarath

Proceedings Volume 13188, International Conference on Medical Imaging, Electronic Imaging, Information Technologies, and Sensors (MIEITS 2024); 131880C (2024) https://doi.org/10.1117/12.3030667
Event: International Conference on Medical Imaging, Electronic Imaging, Information Technologies, and Sensors (MIEITS 2024), 2024, Kuala Lumpur, Malaysia

Abstract

Industrial maintenance practices have been transformed by the integration of the Industrial Internet of Things (IIoT) and AI. In the context of the IIoT, this research article seeks to examine the efficacy of AI-driven predictive maintenance. This study investigates how AI can forecast machinery and equipment breakdowns, enabling prompt maintenance measures, and drastically lowering downtimes. It does this by utilizing cutting-edge machine learning techniques. The methodology, data sources, model building, and real-world consequences of AI-based predictive maintenance in IIoT are all thoroughly examined in this study.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Fawaz S. Al-Anzi, Abdullah F. Al-Anzi, and Sumi Sarath "Predictive maintenance in industrial IoT (IIoT)", Proc. SPIE 13188, International Conference on Medical Imaging, Electronic Imaging, Information Technologies, and Sensors (MIEITS 2024), 131880C (26 June 2024); https://doi.org/10.1117/12.3030667

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