DocumentCode :
539255
Title :
Information fusion based on graph analysis during Urban Search and Rescue
Author :
Hamp, Q. ; Eitelberg, M. ; Lee, B. ; Becker, T. ; Wiebeck, D. ; Reindl, Leonhard
Author_Institution :
Lab. for Electr. Instrum., Albert-Ludwigs-Univ., Freiburg, Germany
fYear :
2010
fDate :
26-29 July 2010
Firstpage :
1
Lastpage :
7
Abstract :
Conventional practices in Urban Search and Rescue (USAR) operations have a great potential for improvement as regards information management. This paper presents a method for automated information processing of uncertain search results produced by multiple agents. Information association is based on graph analysis which considers georeferences, spatial precision and preexisting knowledge. The objective of the scoring fusion is to suggest as quickly and as precisely as possible the hypothetic positions of trapped persons by increasing the quality of uncertain information. The overall aim is to ameliorate the search efficiency by increasing the detection capabilities while reducing risks, false alarms and oversight.
Keywords :
graph theory; multi-agent systems; sensor fusion; automated information processing; detection capability; graph analysis; information association; information fusion; information management; multiple agents; scoring fusion; urban search and rescue; Atmospheric measurements; Data processing; Equations; Mathematical model; Particle measurements; Search methods; Systematics; GIS; association; graph; high-level information fusion; k-means; multi-agent; uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion (FUSION), 2010 13th Conference on
Conference_Location :
Edinburgh
Print_ISBN :
978-0-9824438-1-1
Type :
conf
DOI :
10.1109/ICIF.2010.5712115
Filename :
5712115
Link To Document :
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