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This paper describes the implementation of a digital twin for buildings to enhance the emergency response capabilities of first responder teams, including firefighters, police, and emergency medical services. The proposed platform improves the planning of preventive evacuation strategies and supports real-time operational decisions during emergencies. It integrates wireless monitoring beacons, specifically designed for hostile environments, a cloud-based data management system, and a predictive model to monitor environmental air quality parameters, which are critical during emergency scenarios. The platform uses a digital twin to simulate the building’s behavior, incorporating multimedia content and time series graphs to enhance situational awareness and decision-making. Real-time building data are seamlessly integrated with predictive models generated from smart building sensors, offering a comprehensive visualization on a web-based monitoring interface. This approach provides critical insights to decision-makers, improving the safety and efficiency of both rescue operations and preventive measures. • Digital Twin system: GUIDE2FR fuses sensor data for better emergency awareness. • Real-time monitoring: IoT + AI predict hazards like CO 2 and TVOC for safety. • Scalable architecture: GUIDE2FR adapts to sensors, assets, and smart city needs. • Synced data: Grafana plugin merges video and sensors for faster emergency response. • Open-source cloud: GUIDE2FR ensures accessible, low-cost, and extensible solutions.
Delgado-Álvaro et al. (Wed,) studied this question.