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Orientation-Aware Indoor Localization Path Loss Prediction Model for Wireless Sensor Networks
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Orientation-Aware Indoor Localization Path Loss Prediction Model for Wireless Sensor Networks
Marc Lihan1 , Takeshi Tsuchiya1 and Keiichi Koyanagi1 
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Graduate School of Information, Production, and Systems, Waseda University, 2-7 Hibikino, Wakamatsu-ku, Kitakyushu-shi, Fukuoka Japan, 808-0135 |
Abstract
There have been a large amount of research and interest in the area of ubiquitous and indoor location aware computing in the
past decade. Among several proposed algorithms, fingerprint algorithm stands as one of the most accurate systems for localization.
However, there is a lack of theoretical basis and understanding on the orientation of the user. This paper presents a model
for orientation-aware indoor location tracking system using a Zigbee based protocol wireless sensor called Sun’s SPOT (Small
Programmable Object Technology). Our experiment shows better accuracy in location tracking when orientation and attenuation
factors are considered for the path loss prediction model than the traditional path loss model. Orientation-aware fingerprint
algorithm is also examined in our experiment to have a basis of comparison on an empirical algorithm.
Keywords indoor localization - RSS - path loss model - WSN - fingerprint algorithm - ZigBee - tracking system
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