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.

Highlights

  • INTRODUCTION1.1 State-of-the-art geospatial data acquisition and processing for rescue operations

  • 1.1 State-of-the-art geospatial data acquisition and processing for rescue operationsRescue operations for natural and man-made disasters response take significant amount of various organizations and humans effort and financial expenses

  • TheUS National Parks System rescue operations have a budget of 12+ million dollars USD annually (Heggie et al, 2009)

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Summary

INTRODUCTION

1.1 State-of-the-art geospatial data acquisition and processing for rescue operations. McKie & Richardson (2003) described the human-factor analysis of a rescue and indicated the conspicuous feature of a human tendency to disregard opportunity costs when the life of identifiable individuals are visibly threatened Due to this fact, we may observe operations when hundreds of people and multiple sets of equipment are deployed to save only one human life. Sensors-suite combining video and still visible spectrum cameras is described (Ahmed et al, 2008), which deploys RPH2 (RPH2, 2016) helicopter UAV that allows to care up to 100 kilograms of payload. This system functioned efficiently during disaster response and provided efficient data fusion from its sensor suite. The research described in this paper is a proof of concept for using small UAVs equipped with infrared and visible diapason sensors for detection of living humans in outdoor settings

Why SUAV?
Why Thermal Sensors?
Experimental Scenarios
Experimental Data
EXPERIMENT RESULTS
CONCLUSIONS AND FUTURE RESEARCH
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