AI-Powered Predictive Maintenance for IOT Systems

Abstract

The advent of Industry 4.0 has transformed industrial maintenance methods via the integration of Artificial Intelligence (AI) and Internet of Things (IoT) technology. This study offers a thorough evaluation and analysis of AI-driven predictive maintenance in IoT-enabled industrial systems. We investigate the interplay between AI algorithms and IoT sensor networks in forecasting equipment malfunctions, refining maintenance plans, and improving overall system dependability. The research encompasses many AI methodologies, such as machine learning, deep learning, and reinforcement learning, used for predictive maintenance. We examine the problems and possibilities associated with the implementation of these technologies across several industrial sectors. Our research demonstrates that AI-driven predictive maintenance substantially decreases downtime, lowers maintenance expenses, and enhances the durability of industrial equipment. The report finishes with prospective research avenues and possible ramifications for industry professionals.