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Victim Localization and Assessment System for Emergency Responders

Author(s)
Yoon, HyungchulShiftehfar, RezaCho, SoojinSpencer, Billie F., Jr.Nelson, Mark E.Agha, Gul
Issued Date
2016-03
DOI
10.1061/(ASCE)CP.1943-5487.0000483
URI
https://scholarworks.unist.ac.kr/handle/201301/18917
Fulltext
http://ascelibrary.org/doi/10.1061/%28ASCE%29CP.1943-5487.0000483
Citation
JOURNAL OF COMPUTING IN CIVIL ENGINEERING, v.30, no.2, pp.04015011
Abstract
In minor to moderate natural and man-made disasters, such as earthquakes and fires, people may be trapped inside buildings and hurt by the disaster. Considering that trapped victims may be unconscious, there is a high demand by emergency responders to get information on the locations and physical statuses of trapped victims inside a building during a disaster. In this paper, a smartphone-based, in-building emergency response assistance system, named iRescue, is presented. The system is comprised of two subsystems: a Victim Positioning System (VPS) and a Victim Assessment System (VAS). The VPS uses the received signal strength indicator of Wi-Fi signals from multiple wireless access points with referencing a pre-established Wi-Fi fingerprinting map of a building. The VAS uses patterns obtained from measured 3D acceleration changes by status of a victim. A Naive Bayes classifier is employed for both VPS and VAS: for localization in between the fingerprinting map and for recognition of activities to be used for status assessment. The performance of the VPS has been validated by a localization test on a complex building. The VAS has been validated by activity simulation test with five people and real-time monitoring of a person equipped with an activity recording device. (C) 2015 American Society of Civil Engineers
Publisher
ASCE-AMER SOC CIVIL ENGINEERS
ISSN
0887-3801
Keyword (Author)
Disaster rescueEmergency responseIndoor localizationActivity recognitionNaive Bayes classifierSmartphone
Keyword
INDOOR LOCALIZATIONRECOGNITIONSMARTPHONE

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