Immersive Simulations and AI-Enhanced Approaches for Enhancing Post-Disaster Response

Effective and timely disaster response is critical for minimizing damage and saving lives following catastrophic events. This paper presents a novel framework that integrates immersive simulations, synthetic data generation, and AI-enhanced robotic training to support post-disaster operations. The framework comprises three main components. First, immersive virtual environments are developed to train first responders by simulating complex disaster scenarios, aiming to enhance decision-making and reduce response time. Second, synthetic datasets derived from these simulations are used to train artificial intelligence models for damage assessment and resource allocation. Third, Unity-based environments are employed to train autonomous robots to navigate debris-filled areas, facilitating improved human–robot collaboration during search and rescue missions. Together, these components form a scalable and cost-effective solution to strengthen emergency preparedness and operational efficiency in high-risk environments.