WindSight AI – AI-Based Real-Time Monitoring and Predictive Maintenance of Wind Turbines

Real-time monitoring and predictive analytics of wind turbines are essential for improving efficiency and reliability in the renewable energy sector. WindSight AI presents a hybrid, AI-driven framework combining Internet of Things (IoT) sensor data with machine learning algorithms to predict turbine health and performance. The system architecture integrates React.js for frontend visualization, Java Spring Boot for backend processing, MongoDB for time-series data storage, and Python-based machine learning models for predictive analytics. Real-time data is collected from turbine sensors—measuring wind speed, vibration, temperature, and rotational speed—and processed to detect anomalies and forecast failures. Predictive models such as Random Forest, Long Short-Term Memory (LSTM), and Anomaly Detection techniques are used for fault prediction. The system aims to minimize downtime, optimize maintenance schedules, and enhance operational performance, providing a sustainable solution for intelligent wind energy management.