City Radio Map Construction for Wi-Fi-Based Citywide Indoor Positioning

Cited 28 time in webofscience Cited 3 time in scopus
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dc.contributor.authorHan, Dongsooko
dc.contributor.authorSahar, Ayeshako
dc.contributor.authorBerkner, Josephko
dc.contributor.authorLee, Gunwooko
dc.date.accessioned2019-08-29T02:20:10Z-
dc.date.available2019-08-29T02:20:10Z-
dc.date.created2019-08-26-
dc.date.created2019-08-26-
dc.date.created2019-08-26-
dc.date.created2019-08-26-
dc.date.created2019-08-26-
dc.date.issued2019-07-
dc.identifier.citationIEEE ACCESS, v.7, pp.99867 - 99877-
dc.identifier.issn2169-3536-
dc.identifier.urihttp://hdl.handle.net/10203/266066-
dc.description.abstractA Wi-Fi fingerprint consists of received signal strength values at a particular location along with the location information. A Wi-Fi radio map is constructed by maintaining a database of Wi-Fi fingerprints at various points in a building. A city radio map is a collection of radio maps for most buildings in a city. A highly precise citywide indoor positioning service is possible, if an accurate city radio map is available. However, tremendous time and effort are required to construct a city radio map through manual calibration. This paper proposes a method for constructing a city radio map through the crowdsourcing of Wi-Fi fingerprints from numerous smartphones. The proposed method classifies the buildings in a city into three categories: buildings in residential areas, commercial areas, and public areas. Then, it develops location-labeling techniques appropriate for the collected fingerprints from buildings in each category. Experiments conducted in the cities of Daejeon and Seoul revealed that the proposed method can construct a precise city radio map with minimal cost in a short period of time. Once city radio maps are constructed for most cities around the world, the global indoor positioning system will be completed.-
dc.languageEnglish-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.titleCity Radio Map Construction for Wi-Fi-Based Citywide Indoor Positioning-
dc.typeArticle-
dc.identifier.wosid000480340700002-
dc.identifier.scopusid2-s2.0-85087349412-
dc.type.rimsART-
dc.citation.volume7-
dc.citation.beginningpage99867-
dc.citation.endingpage99877-
dc.citation.publicationnameIEEE ACCESS-
dc.identifier.doi10.1109/ACCESS.2019.2929779-
dc.contributor.localauthorHan, Dongsoo-
dc.contributor.nonIdAuthorSahar, Ayesha-
dc.description.isOpenAccessY-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorCity radio map-
dc.subject.keywordAuthorcrowdsourcing-
dc.subject.keywordAuthorindoor positioning-
dc.subject.keywordAuthorsemi-supervised machine learning-
dc.subject.keywordAuthorsimultaneous calibration and address mapping (SCAM)-
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