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Bangkok
Jan. 28, 2013 to Jan. 30, 2013
ISBN: 978-1-4673-5740-1
pp: 412-416
Kamol Kaemarungsi , Embedded System Technology Laboratory (EST) National Electronics and Computer Technology Center (NECTEC) Pathumthani, Thailand
ABSTRACT
In location fingerprinting based indoor positioning system, received signal strength (RSS) indications from a set of Wi-Fi access points are used as a unique fingerprint to identify a specific location. However these RSS fingerprints may become outdated when there are unanticipated environmental changes. Re-measuring RSS fingerprints for all locations to maintain an up-to-date RSS database incurs high operational cost, which is impractical in dynamically changed environment. In this paper, we propose a method to estimate the RSS fingerprint of a specific location from a set of neighboring re-measured RSS fingerprints, called “feedbacks”. The proposed method searches for new feedbacks and some necessary old RSS fingerprints in the cut-off area and then applies plane-interpolation to calculate the new RSS fingerprint for a specific location. Based on simulation results, about 5% of re-measured RSS feedbacks are required to satisfy 80% of positioning correctness in the simulated 30×30 m2 area.
INDEX TERMS
feedback, Location estimation, Wi-Fi fingerprint, adaptive RSS fingerprint, plane-interpolation
CITATION
Kamol Kaemarungsi, "Indoor localization improvement via adaptive RSS fingerprinting database", ICOIN, 2013, 2013 International Conference on Information Networking (ICOIN), 2013 International Conference on Information Networking (ICOIN) 2013, pp. 412-416, doi:10.1109/ICOIN.2013.6496414
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