<![CDATA[Induction motors are critical components in industrial systems that require continuous condition monitoring to prevent damage and downtime. Previous research generally uses Local Area Network (LAN)-based monitoring systems, thus limiting monitoring access to the local network and not supporting real-time mobile notifications. This research aims to develop a cloud-based Internet of Things (IoT) induction motor monitoring system capable of monitoring motor parameters in real-time via the internet. The system was developed using an ESP32 microcontroller with integrated DS18B20 sensors for temperature measurement, MPU6050 for vibration detection, and SCT013-30A and ADS1115 for electric current measurement. Monitoring data is sent to the Firebase Realtime Database and displayed on a mobile web dashboard in real-time. In addition, the system is equipped with an automatic notification feature using Telegram Bot when motor parameters exceed predetermined safe limits. Test results show that the system is able to distinguish between normal and abnormal motor conditions based on changes in temperature, vibration, and current parameters. Under normal conditions, the average temperature was 39.38°C, vibration 1.65 mm/s, and current 0.40 A, while under abnormal conditions the average vibration increased to 5.15 mm/s and the current decreased to 0.15 A. The system also succeeded in performing stable remote monitoring, cloud-based historical data storage, and sending mobile notifications with a fast response. The development of this system provides increased monitoring flexibility compared to previous research which was still based on local LAN and supports the implementation of predictive maintenance on modern IoT-based induction motors.]]>
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