IoT-Based Real-Time Condition Monitoring and Predictive Maintenance of Induction Motors

This paper presented the design and implementation of an IoT-based condition monitoring system for induction motors, aimed at improving reliability, reducing downtime, and enabling predictive maintenance. The proposed system integrates multiple sensors to monitor key parameters such as temperature, vibration, voltage, current, and speed in real time. An ESP32 microcontroller is used for data acquisition and wireless communication, while a cloud-based platform facilitates data storage, visualization, and analysis. The experimental results demonstrate that the system can effectively detect abnormal operating conditions and generate timely alerts when parameters exceed predefined thresholds. The real-time monitoring capability, combined with remote accessibility, significantly reduces the need for manual inspection and minimizes the chances of unexpected motor failures. The system also proves to be cost-effective, scalable, and suitable for deployment in modern industrial environments aligned with Industry 4.0 principles. Overall, the proposed framework successfully achieves its objective of providing a reliable and efficient solution for induction motor health monitoring and lays the foundation for intelligent maintenance strategies.

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