TRACE envisions a scalable, AI-driven, multimodal, human-centered testbed that strengthens disaster resilience and accelerates emergency response and recovery. We integrate robotics (UAVs, UGVs, USVs), IoT sensing (RGB, LiDAR, mmWave, audio), and social signals with trustworthy AI to detect life signs, assess damage, and coordinate teams in rugged, network-denied settings. TRACE advances navigation, multi-agent communication, and virtual-physical co-simulation for realistic training and evaluation. With human-in-the-loop feedback and ethical safeguards, TRACE turns streaming spatio-temporal data into actionable awareness, measurable resilience, and faster, safer decisions.

Core Research Pillars