Authors : Jirapat Sangthong and Sathaporn Promwong
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.
Jirapat Sangthong and Sathaporn Promwong, 2017. An Improvement of Indoor Navigation System Based on Fingerprinting Technique Using K-Means Clustering Algorithm. Journal of Engineering and Applied Sciences, 12: 1192-1199.