The increasing demand for reliable power distribution necessitates advanced monitoring solutions for distribution transformers. This paper presents an IoT-driven health monitoring system designed to enhance the reliability and efficiency of smart power grids. The system integrates sensors to measure voltage, current, oil temperature, and body temperature, ensuring real-time data acquisition and fault detection. An ESP32 microcontroller processes sensor data and transmits it to the Blynk IoT platform for remote monitoring and predictive maintenance. The system effectively identifies phase failures, earth faults, overheating, and other anomalies, allowing for timely intervention and reduced downtime. Unlike conventional manual inspection methods, this low-cost solution provides continuous monitoring, improving transformer lifespan and operational efficiency. The proposed approach offers a scalable and cost-effective strategy for smart power grid applications, promoting sustainable energy management through data-driven decision-making. Future enhancements may include AI-based fault prediction and expanded integration with smart grid infrastructures.