KEYWORDS: Data modeling, Sensors, Artificial intelligence, Linear regression, Internet of things, Systems modeling, Industry, Machine learning, Temperature sensors, Evolutionary algorithms
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.
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