Feasibility Study of Inexpensive Thermal Sensors and Small Uas Deployment for Living Human Detection in Rescue Missions Application Scenarios

Abstract

ABSTRACT:Significant efforts are invested by rescue agencies worldwide to save human lives during natural and man-made emergency situations including those that happen in wilderness locations. These emergency situations include but not limited to: accidents with alpinists, mountainous skiers, people hiking and lost in remote areas. Sometimes in a rescue operation hundreds of first responders are involved to save a single human life. There are two critical issues where geospatial imaging can be a very useful asset in rescue operations support: 1) human detection and 2) confirming a fact that detected a human being is alive. International group of researchers from the Unites States and Poland collaborated on a pilot research project devoted to identify a feasibility of use for the human detection and alive-human state confirmation small unmanned aerial vehicles (SUAVs) and inexpensive forward looking infrared (FLIR) sensors. Equipment price for both research teams was below $8,000 including 3DR quadrotor UAV and Lepton longwave infrared (LWIR) imager which costs around $250 (for the US team); DJI Inspire 1 UAS with commercial Tamarisc-320 thermal camera (for the Polish team). Specifically both collaborating groups performed independent experiments in the USA and Poland and shared imaging data of on the ground and airborne electro-optical and FLIR sensor imaging collected. In these experiments dead bodies were emulated by use of medical training dummies. Real humans were placed nearby as live human subjects. Electro-optical imagery was used for the research in optimal human detection algorithms. Furthermore, given the fact that a dead human body after several hours has a temperature of the surrounding environment our experiments were challenged by the SUAS data optimization, i.e., distance from SUAV to object so that the FLIR sensor is still capable to distinguish temperature differences between a dummy and a real human. Our experiments indicated feasibility of use SUAVs and small thermal sensors for the human detection scenarios described above. Differences in temperatures were collected by deployed imaging acquisition platform are interpretable on FLIR images visually. Moreover, we applied ENVI image processing functions for calibration and numerical estimations of such a temperature differences. There are more potential system functionalities such as voice messages from rescue teams and even distant medication delivery for the victims of described emergencies. This paper describes experiments, processing results, and future research in more details.

Unmanned Aerial Vehicles in the protection of the elements of a country’s critical infrastructure – selected directions of development

“…Th is type of UAV can also be used to search for traffi c accident victims using thermal images obtained from infrared cameras. Th anks to thermal imaging cameras mounted on an airframe, a person in a diffi cult terrain may be immediately located (Levin et al 2016).…”

Conception of UAV use in the road rescue

“…Istnieją już drony, które wyszukują ludzi na podstawie obrazu termicznego uzyskanego z kamer w podczerwieni. Zamontowana na dronie kamera termowizyjna w zaledwie kilka chwil może zlokalizować osobę, przebywającą w trudno dostępnym terenie [6]. Termowizja jest pasmem promieniowania znajdującego się znacznie poniżej zakresu promieniowania widzialnego.…”

Thermal Image Tracking for Search and Rescue Missions with a Drone

“…The technology has been also applied to wildlife monitoring and agricultural and industrial inspection [7,8]. People detection with thermal images captured by drones has been studied in [9][10][11][12][13][14][15]. Persons and animals were detected using the YOLO detection model [9].…”

“…The YOLO detection model was adopted to build a human detection system using drones [11]. The spatial gray level co-occurrence matrix estimates temperature differences [12]. In [13], a person is recognized with a two-stage hot-spot detection approach.…”