REAL TIME EFFICIENCY MONITORING OF INDUCTION MOTOR

Because of their ease of use, dependability, and little maintenance needs, induction motors are frequently utilized in commercial and industrial settings. However, their efficiency and performance can be greatly impacted by changes in supply, voltage, and load circumstances. To guarantee the best possible use of energy, avoid malfunctions, and save operating expenses, motor efficiency must be continuously monitored. This project offers an Internet of Things-based real-time efficiency monitoring solution for induction motors. The system uses sensors (ZMPT101B and ACS712) to detect electrical characteristics like voltage, current, and power factor, and a tachometer or infrared sensor to assess mechanical parameters like speed. Real-time calculations of the inp ut and output power are used to determine the motor's efficiency. The sensor data is processed by an Arduino/ESP32 microcontroller, which then shows the results on an LCD and sends the data to an Internet of Things platform like Blynk or Thing Speak for re mote monitoring and analysis. The suggested method allows users to plan predictive maintenance, identify performance decline, and enhance energy management by offering precise and ongoing efficiency data. The implementation shows an efficient, affordable, and scalable method for sustainable power use in electrical motor systems and intelligent industrial monitoring.