Indoor Navigation and Tracking Using WLAN-Fingerprinting Technique and K-Inverse Harmonic Means Clustering on Mobile Device

Jirapat Sangthong; Pichaya Supanakoon; Sathaporn Promwong

doi:10.4028/www.scientific.net/AMM.781.77

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 781Indoor Navigation and Tracking Using...

Indoor Navigation and Tracking Using WLAN-Fingerprinting Technique and K-Inverse Harmonic Means Clustering on Mobile Device

Abstract:

This work evaluated the indoor navigation with the WLAN-fingerprinting technique and k-inverse harmonic mean clustering. During offline phase, the RSS of references node are grouped by KIHM clustering algorithm. In addition, the flag parameter that means the member of each cluster will be added to database. Then, the KIHM membership values will be used to find the cluster and using fingerprinting technique to estimate the target node positions. The best result derived from the KIHM clustering techniques with 3 clusters. The average distance error is approximate 3.73 meters with the 18.41% no error estimated position.

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Periodical:

Applied Mechanics and Materials (Volume 781)

Pages:

77-80

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.781.77

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Online since:

August 2015

Authors:

Jirapat Sangthong*, Pichaya Supanakoon, Sathaporn Promwong

Keywords:

Fingerprinting Technique, Indoor Navigation, Indoor Positioning, Indoor Tracking, K-Inverse Harmonic Means, K-Mean, Mobile Devices, RSS

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References

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