AI-Driven XR Situational Awareness Platform for Urban Crisis Management and Smart Mobility Operations
Urban environments are increasingly exposed to complex, dynamic, and interdependent risks, ranging from traffic incidents and infrastructure failures to large-scale crises such as extreme weather events and emergency response scenarios. In such conditions, decision-makers and operators are required to act under time-critical constraints while relying on fragmented, heterogeneous, and often incomplete information. The lack of unified situational awareness, combined with limited visibility and disconnected systems, significantly affects response time, coordination efficiency, and overall operational effectiveness. In parallel, modern cities have deployed extensive sensing infrastructures, including surveillance camera networks, IoT devices, connected vehicles, and satellite-based observation systems. Although these technologies generate vast amounts of data, their exploitation remains limited due to the absence of integrated platforms capable of real time data fusion, intelligent interpretation, and intuitive visualization. As a result, a substantial gap persists between data availability and actionable intelligence, particularly in safety-critical and crisis management applications. To address this challenge, this paper presents an AI-driven XR situational awareness and operational platform designed for urban crisis management and smart mobility operations. The proposed system integrates data from city infrastructure, connected vehicles, and VRUs, enabling a comprehensive and real-time understanding of the urban environment. Through a unified operational dashboard and AR interfaces, the platform supports both centralized monitoring and field-level interaction. By enhancing perception, enabling cooperative awareness, and delivering context-aware information, the proposed approach improves decision-making, coordination, and safety across diverse urban scenarios.