Abstract:
The paper focuses on Design and Modeling of an IOT-based Transformer Health Monitoring System designed to improve transformer reliability and lifespan byenabling real-time monitoring and predictive maintenance. Transformers, essential to power systems, are prone to failures that can cause costly repairs and service disruptions. Traditional manual or basic automated monitoring methods often fail to provide timely insights.This system integrates sensors to measure parameters like temperature, humidity, load current, oil level, and voltage, with data transmitted to a cloud-based platform. Using IOT technology, data analytics, and machine learning, it detects abnormalities and predicts faults, allowing operators to take preventive actions. Alerts and reports are accessible via web or mobile apps, enabling quick responses. The system reduces maintenance costs, extends transformer life, and enhances grid stability, making it vital for advancing smart grid infrastructure and energy management efficiency.
