Edge-Based Predictive Maintenance Framework for AC Motors Using Real-Time Power Quality and Temperature Monitoring"

This project presents an edge-based predictive maintenance framework for AC motors using an ESP32 microcontroller, PZEM energy monitoring module, and DS18B20 temperature sensor. The system continuously monitors critical electrical parameters such as voltage, current, power, energy consumption, frequency, and power factor, along with motor temperature. The collected data are processed locally and displayed on an OLED screen for real-time condition assessment. By identifying abnormal operating conditions such as overheating, overload, voltage fluctuations, and excessive power consumption, the proposed framework enables early fault detection, improves motor reliability, reduces downtime, and supports energy-efficient operation through intelligent predictive maintenance.