Development of an Integrated IoT-based Monitoring System for a Three-Phase Induction Motor Using ESP32 and Industrial Power Meter

Abstract

Three-phase induction motors are essential in industrial systems and require continuous condition monitoring to improve operational reliability and reduce unexpected downtime. However, many Internets of Things (IoT)-based monitoring systems focus on data acquisition without quantitatively validating communication performance and data integrity. This study develops and validates an IoT-based monitoring system for real-time acquisition, transmission, visualization, and storage of electrical parameters. The proposed system integrates an ESP32 microcontroller, an industrial multifunction power meter, Modbus RTU communication, a Flask web server, an SQLite database, and a Streamlit dashboard. Voltage, current, active power, power factor, and frequency were monitored under no-load and loaded conditions. System validation used 621 valid monitoring samples, while communication performance was evaluated through three independent trials comprising 300 transmission attempts. The system achieved an HTTP success rate of 99.33% with an average latency of 655.47 ms (minimum 100 ms, maximum 3952 ms). Database verification confirmed 100% sequence completeness, with no missing sequence IDs among the records validated in the database. These results demonstrate consistent near-real-time monitoring, high HTTP transmission success, and complete sequence integrity within the validated database records. This study introduces an IoT-based monitoring platform validated through quantitative evaluation of HTTP success rate, communication latency, and database sequence completeness using sequence IDs. The validated platform provides a foundation for future LSTM-based predictive-maintenance research on three-phase induction motors.