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An improvement of indoor navigation system based on fingerprinting technique using K-Means clustering algorithm
Author(s)
Sangthong, Jirapat
Date Issued
January 1, 2017
Type
Article
Abstract
Indoor navigation system is the one of interesting application among the researchers in an indoor environment due to the meter-level accuracy requirement in complex structure. This research proposed an improvement of the indoor navigation system based on fingerprinting technique by using K-Means (KM) clustering algorithm. The unknown positions are estimated by using Least Square (LS) and K-Nearest Neighbor (KNN) algorithms. The experimental results show the performance comparison between no-clustering case and KM-clustering case. Finally, we found that the KM clustering algorithm can be improved the accuracy of indoor navigation system both LS and KNN algorithm.
Citation
Journal of Engineering and Applied Sciences, 12(5), 1192-1199, 2017