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Analysis of Crowdsensed WiFi Fingerprints for Indoor Localization

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

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 - marraskuuta 2017
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaProceedings of Conference of Open Innovations Association FRUCT -
Kesto: 1 tammikuuta 2000 → …

Julkaisusarja

Nimi
ISSN (elektroninen)2305-7254

Conference

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

Tiivistelmä

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.

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