Journal of Applied Science and Engineering

Published by Tamkang University Press


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Chi-Fu Hung This email address is being protected from spambots. You need JavaScript enabled to view it.1, Chiu-Ching Tuan1 and Fong-Mao Jhuang1

1Department of Electronic Engineering, National Taipei University of Technology, Taipei, Taiwan 106, R.O.C.


Received: November 27, 2015
Accepted: July 10, 2016
Publication Date: September 1, 2016

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This study proposes a method based on access point (AP) selection and adaptive pattern-matching for Wi-Fi indoor positioning (ASAPM). In the proposed ASAPM, a box plot algorithm is used to remove received signal strength (RSS) outliers in samples received from APs in order to smooth the RSS. Subsequently, we analyzed the RSS variations for selecting the top-N APs with the least interference. Moreover, we analyzed the history of the positioning results to estimate the direction and distance of users in subsequent positions in order to reduce the pattern-matching time and computational overhead of the positioning system. The simulation results revealed that the average positioning error, average maximum positioning error, and average pattern-matching times of ASAPM were 36%, 51%, and 57% lower than the three compared strategies, respectively. These findings show that ASAPM could reduce the computational overhead; moreover, it is suitable as an indoor-positioning service for mobile devices.

Keywords: Access Point Selection, Adaptive Pattern-matching, Indoor Positioning, Received Signal Strength, Box Plot


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