Digital Twin and AI for Real-Time Environmental Simulation

The project involves building a high-fidelity digital twin of complex urban or environmental systems by integrating GIS data, IoT sensor measurements, and domain-specific information. AI models will be developed to predict dynamic behaviors and key risk zones, and these models will be embedded into the digital twin to enable real-time simulation and visualization. The system’s performance will be evaluated in terms of prediction accuracy, computational efficiency, and usability to ensure it provides actionable insights for decision-making and planning.