Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/20323
Title: Using fuzzy color maps to increase the positioning accuracy in poor Wi-Fi coverage regions
Authors: Chan, ECL
Baciu, G 
Mak, SC
Keywords: Fuzzy Logic
Indoor positioning
Location Awareness
Location Fingerprinting
Newton Trust Region
Social Networks
Wi-Fi Localization
Issue Date: 2011
Publisher: IEEE
Source: 2011 IEEE 7th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 10-12 October 2011, Wuhan, p. 165-171 How to cite?
Abstract: Recently, in the context of IEEE 802.11b/g network protocols, Wi-Fi radio channels been proposed to estimate the location of a smart mobile device. We can locate Wi-Fi-enabled devices by applying location-sensing techniques. However, the positioning accuracy depends greatly on the Wi-Fi signal coverage. The positioning accuracy due to poor Wi-Fi signal coverage has not been investigated systematically in the current research on Wi-Fi location awareness. Our previous work provide a location threshold of 1.82m on average. However, when a person enters in a poor Wi-Fi coverage region, the positioning accuracy drops dramatically. In this paper, we extend our previous work and create a fuzzy color map to visualize the distribution of Wi-Fi signal: red represents strong signals and blue represents weak signals. Then we make use of the proposed map by selecting the best candidates of AP to increase the positioning accuracy in the poor Wi-Fi coverage region. Our experiment result shows that we can reduce the distance error significantly by 25% in a poor Wi-Fi coverage environment and locate a person within 1.75m in average. The proposed method leads to substantially more accurate and robust localization system.
URI: http://hdl.handle.net/10397/20323
ISBN: 978-1-4577-2013-0
ISSN: 2160-4886
DOI: 10.1109/WiMOB.2011.6085409
Appears in Collections:Conference Paper

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