Table 2.

Non-line-of-sight detection technologies and information about the system used.

Detection type	Environmental robustness	Sensor fusion effectiveness	Vital sign sensitivity	Operational feasibility
High accuracy through CNN + LSTM fusion with radar and infrared data30	Robust in post-earthquake rescue scenarios with congestion	Effective decision-level fusion improves detection reliability	Focuses on signs of life under debris	Moderate complexity; suitable for rescue environments
UAV-borne radar detects vital signs through obstacles31	Operates in low-visibility and congested environments	Radar fusion with other UAV sensors	Remotely detects breathing and heartbeat	Mobile, adaptable UAV deployment
UAV system combines radar and lidar for SAR support32	Effective in complex urban environments	Radar and lidar fusion with Artificial Intelligence (AI)	Detects breathing and pulse movement	UAV-based; real-time mapping
Low-cost thermopile sensor detects survivors under debris33	High detection accuracy with low false alarms	Single sensor; no fusion	Detects presence via thermal signals	Lightweight, low-power, robotic deployable
Testing millimeter-wave radars for vital signs extraction 34	Range resolution across frequencies	Radar only; no fusion	Detects breathing and heartbeat	Laboratory and field testing
Critical review of emerging human sensing Technologies35	Evaluates radar, AI, drones, gas, acoustics, and optics	Discuss fusion and its limitations	Detects human presence in disaster areas	Focus on SAR mission impact and future trends