IoT-Enabled Transformer Health Monitoring System Using Embedded Sensors and Cloud Analytics

This research focuses on developing an Internet of Things (IoT)-based smart monitoring system for electrical power transformers, which are crucial assets in any power distribution network. Traditional transformer maintenance relies on manual inspections and scheduled servicing, which often fail to detect sudden faults and lead to costly downtimes. The proposed system integrates embedded sensors to monitor vital transformer parameters such as: Oil level Winding temperature Vibration Load current These sensors are connected to a microcontroller (ESP32) that collects data and transmits it in real-time to a cloud analytics dashboard using Wi-Fi and MQTT protocol. The dashboard provides live alerts and visualizations for maintenance teams to act promptly. This solution enables predictive maintenance, reduces operational costs, prevents unexpected failures, and significantly improves transformer reliability, especially in rural and remote substations. The entire system is cost-effective, scalable, and suitable for deployment in smart grid infrastructure.