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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/109071


    Title: Improving Wi-Fi Indoor-Positioning Accuracy by Using AP Selection and Adaptive Pattern Matching
    Authors: Hung, Chi-Fu, Tuan, Chiu-Ching;Jhuang, Fong-Mao
    Keywords: Access Point Selection;Adaptive Pattern-matching;Indoor Positioning;Received Signal Strength;Box Plot
    Date: 2016-09
    Issue Date: 2017-01-03 09:39:46 (UTC+8)
    Publisher: 淡江大學出版中心
    Abstract: 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.
    Relation: Journal of Applied Science and Engineering 19(3), pp.337-346
    DOI: 10.6180/jase.2016.19.3.12
    Appears in Collections:[淡江理工學刊] 第19卷第3期

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