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A UAV BASED 3-D POSITIONING FRAMEWORK FOR DETECTING LOCATIONS OF BURIED PERSONS IN COLLAPSED DISASTER AREA

Authors :
H. Moon
C. Kim
W. Lee
Source :
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B8, Pp 121-124 (2016)
Publication Year :
2016
Publisher :
Copernicus Publications, 2016.

Abstract

Regarding spatial location positioning, indoor location positioning theories based on wireless communication techniques such as Wi-Fi, beacon, UWB and Bluetooth has widely been developing across the world. These techniques are mainly focusing on spatial location detection of customers using fixed wireless APs and unique Tags in the indoor environment. Besides, since existing detection equipment and techniques using ultrasound or sound etc. to detect buried persons and identify survival status for them cause 2nd damages on the collapsed debris for rescuers. In addition, it might take time to check the buried persons. However, the collapsed disaster sites should consider both outdoor and indoor environments because empty spaces under collapsed debris exists. In order to detect buried persons from the empty spaces, we should collect wireless signals with Wi-Fi from their mobile phone. Basically, the Wi-Fi signal measure 2-D location. However, since the buried persons have Z value with burial depth, we also should collect barometer sensor data from their mobile phones in order to measure Z values according to weather conditions. Specially, for quick accessibility to the disaster area, a drone (UAV; Unmanned Arial Vehicle) system, which is equipped with a wireless detection module, was introduced. Using these framework, this study aims to provide the rescuers with effective rescue information by calculating 3-D location for buried persons based on the wireless and barometer sensor fusion.

Details

Language :
English
ISSN :
16821750 and 21949034
Volume :
XLI-B8
Database :
Directory of Open Access Journals
Journal :
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.bbac326c5748c3bdf48f1e4d8a855b
Document Type :
article
Full Text :
https://doi.org/10.5194/isprs-archives-XLI-B8-121-2016