This whitepaper presents a digital twin-based approach to improving wind turbine operations through predictive maintenance and real-time monitoring. It explains how digital twins replicate physical assets using sensor data, AI, and IoT to detect anomalies early, optimize performance, and reduce downtime. The solution architecture leverages Azure IoT Hub, Digital Twins, time-series databases, and AI/ML services to process and analyze turbine data. Key capabilities include vibration analysis, component inspection, damage prediction, and performance optimization. By enabling proactive diagnostics and continuous monitoring, the solution enhances operational efficiency, reduces maintenance costs, and extends asset lifespan in wind energy systems.

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