Intelligent Systems for Predictive Maintenance in Engineering Infrastructures
Keywords:
Predictive maintenance, intelligent systems, engineering infrastructures, machine learning, Internet of Things (IoT), fault detection, big data analytics, maintenance optimizationAbstract
Creating predictive maintenance models is crucial to enhancing efficiency, reducing risks and maximizing the output of engineering systems. Using integrated intelligent systems, machine learning, Internet of Things (IoT) sensors and big data analytics enables continuous monitoring and advanced prediction of equipment failures before they occur. The study investigates the latest advancements in predictive maintenance technology and introduces a novel methodology that exploits IoT sensor data and machine learning algorithms to enhance fault prediction accuracy in engineering systems. The research demonstrates that employing intelligent systems significantly enhances the accuracy of identifying faults and scheduling timely maintenance.
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