Analysis of Crowdsensed WiFi Fingerprints for Indoor Localization

Zhe Peng, Philipp Richter, Helena Leppäkoski, Elena-Simona Lohan

    Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

    3 Sitaatiot (Scopus)
    256 Lataukset (Pure)

    Abstrakti

    Crowdsensing is more and more used nowadays for indoor localization based on Received Signal Strength (RSS) fingerprinting. It is a fast and efficient solution to maintain fingerprinting databases and to keep them up-to-date. There are however several challenges involved in crowdsensing RSS fingerprinting data, and these have been little investigated so far in the current literature. Our goal is to analyse the impact of various error sources in the crowdsensing process for the purpose of indoor localization. We rely our findings on a heavy measurement campaign involving 21 measurement devices and more than 6800 fingerprints. We show that crowdsensed databases are more robust to erroneous RSS reports than to malicious fingerprint position reports. We also evaluate the positioning accuracy achievable with crowdsensed databases in the absence of any available calibration.
    AlkuperäiskieliEnglanti
    OtsikkoProceedings of the 21st Conference of Open Innovations Association FRUCT
    JulkaisupaikkaHelsinki, Finland
    KustantajaFRUCT
    Sivut268-277
    Sivumäärä10
    ISBN (elektroninen)978-952-68653-2-4
    TilaJulkaistu - marrask. 2017
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
    TapahtumaProceedings of Conference of Open Innovations Association FRUCT -
    Kesto: 1 tammik. 2000 → …

    Julkaisusarja

    Nimi
    ISSN (elektroninen)2305-7254

    Conference

    ConferenceProceedings of Conference of Open Innovations Association FRUCT
    Ajanjakso1/01/00 → …

    Julkaisufoorumi-taso

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