@article{MAKHILLJEAS201712514232,
    title = {An Improvement of Indoor Navigation System Based on
Fingerprinting Technique Using K-Means Clustering Algorithm},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {12},
    number = {5},
    pages = {1192-1199},
    year = {2017},
    issn = {1816-949x},
    doi = {jeasci.2017.1192.1199},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2017.1192.1199},
    author = {Jirapat and},
    keywords = {Indoor navigation system,fingerprinting technique,K-Means (KM),clustering algorithm,Least Square (LS),K-Nearest Neighbor (KNN)},
    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.}
    }