DocumentCode :
609134
Title :
RSS-based localization considering topographical feature for pasturing
Author :
Yokoo, K. ; Nishidoi, T. ; Urabe, H. ; Ikenouchi, T. ; Ninomiya, Tamotsu ; Yoshida, Manabu ; Sugiyama, Junichi
Author_Institution :
Network Innovation Center, Fujitsu Ltd., Kawasaki, Japan
fYear :
2013
fDate :
20-21 March 2013
Firstpage :
1
Lastpage :
5
Abstract :
This paper describes a localization technique to be used for a pasturing management system. Issues to be addressed are low energy consumption for battery operation and radio propagation degradation due to undulating lands in pastures. We decided to use received signal strength- (RSS-) based trilateration for low power, and to consider the topographical effect using particle filters (PF). To evaluate the proposed algorithm, an experimental campaign was conducted in a pasture with an area of 2 km2. The results show that the proposed algorithm improves the localization accuracy by 28% when compared with the least square (LS) algorithm, whereas plain PF increased it by 14%. These results show that our technique meets the requirements for pasture management.
Keywords :
agriculture; energy consumption; least squares approximations; particle filtering (numerical methods); radiowave propagation; wireless sensor networks; RSS-based localization; battery operation; localization accuracy; localization technique; low energy consumption; particle filters; pasture management; pasturing management system; radio propagation degradation; received signal strength-based trilateration; square algorithm; topographical effect; topographical feature; wireless sensor networks; Accuracy; Cows; Particle filters; Radio propagation; Sensors; Shadow mapping; Wireless sensor networks; localization; pasturing; patricle filter; radio propagation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Positioning Navigation and Communication (WPNC), 2013 10th Workshop on
Conference_Location :
Dresden
Print_ISBN :
978-1-4673-6031-9
Type :
conf
DOI :
10.1109/WPNC.2013.6533277
Filename :
6533277
Link To Document :
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