Life Signs Detector Using a Drone in Disaster Zones

• Published in: Remote sensing (Basel, Switzerland) Vol. 11; no. 20; p. 2441
• Main Authors: Al-Naji, Ali, Perera, Asanka G., Mohammed, Saleem Latteef, Chahl, Javaan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 21.10.2019
• Subjects: Cameras; cardiopulmonary motion; Computer vision; Data analysis; Data collection; denoising; Disasters; drone; Earthquakes; Ethics; Evacuations & rescues; Human motion; Human subjects; humans; landscapes; Mannequins; Motion detection; Motion perception; openpose; Remote sensing; Seismic activity; Sensors; Sequences; Survival; uav; Unmanned aerial vehicles; Vision systems; wavelet; United States > US
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs11202441

In the aftermath of a disaster, such as earthquake, flood, or avalanche, ground search for survivors is usually hampered by unstable surfaces and difficult terrain. Drones now play an important role in these situations, allowing rescuers to locate survivors and allocate resources to saving those who can be helped. The aim of this study was to explore the utility of a drone equipped for human life detection with a novel computer vision system. The proposed system uses image sequences captured by a drone camera to remotely detect the cardiopulmonary motion caused by periodic chest movement of survivors. The results of eight human subjects and one mannequin in different poses shows that motion detection on the body surface of the survivors is likely to be useful to detect life signs without any physical contact. The results presented in this study may lead to a new approach to life detection and remote life sensing assessment of survivors.