Volunteer Drone: Search and Rescue of the Industrial Building Collapsed Worker

Drones are effective in search and rescue (SAR) operations due to their commercial availability and the way in which they access hard to reach areas. Specifically, a drone is compact enough to discover victims and gain access to accidents inside of a collapsed buildings. However, there are limitations when it comes to structure and control of the drone during such SAR operations. In practical applications, the condition of the disaster area is unpredictable. For academic purposes, this study assumes that the victim is pressed against a thick wall of cement in a low-light area, which is not reachable by GPS. The study proposes an overall architecture for a victim detection process, which aims to detect the victim in the shortest amount of time and with maximum accuracy. The drone model used is the DJI Mavic air 2 drone, with a Bluetooth Low Energy (BLE) detection application, a Beacon chipset, a Bluetooth enabled mobile phone, and the Hokuyo Lidar for detection and mapping. The study will implement a data mining approach and the results/analysis will show that using this approach can significantly improve the rescuers’ efforts to find and save victims of accidents.