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- Publisher Website: 10.1109/TMC.2014.2320254
- Scopus: eid_2-s2.0-84919934995
- WOS: WOS:000347098100016
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Article: Smartphones based crowdsourcing for indoor localization
Title | Smartphones based crowdsourcing for indoor localization |
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Authors | |
Keywords | smartphones Indoor localization floor plan RSS fingerprint site survey |
Issue Date | 2015 |
Citation | IEEE Transactions on Mobile Computing, 2015, v. 14, n. 2, p. 444-457 How to Cite? |
Abstract | Indoor localization is of great importance for a range of pervasive applications, attracting many research efforts in the past decades. Most radio-based solutions require a process of site survey, in which radio signatures of an interested area are annotated with their real recorded locations. Site survey involves intensive costs on manpower and time, limiting the applicable buildings of wireless localization worldwide. In this study, we investigate novel sensors integrated in modern mobile phones and leverage user motions to construct the radio map of a floor plan, which is previously obtained only by site survey. Considering user movements in a building, originally separated RSS fingerprints are geographically connected by user moving paths of locations where they are recorded, and they consequently form a high dimension fingerprint space, in which the distances among fingerprints are preserved. The fingerprint space is then automatically mapped to the floor plan in a stress-free form, which results in fingerprints labeled with physical locations. On this basis, we design LiFS, an indoor localization system based on off-the-shelf WiFi infrastructure and mobile phones. LiFS is deployed in an office building covering over 1,600 m2 , and its deployment is easy and rapid since little human intervention is needed. In LiFS, the calibration of fingerprints is crowdsourced and automatic. Experiment results show that LiFS achieves comparable location accuracy to previous approaches even without site survey. |
Persistent Identifier | http://hdl.handle.net/10722/303437 |
ISSN | 2023 Impact Factor: 7.7 2023 SCImago Journal Rankings: 2.755 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Wu, Chenshu | - |
dc.contributor.author | Yang, Zheng | - |
dc.contributor.author | Liu, Yunhao | - |
dc.date.accessioned | 2021-09-15T08:25:18Z | - |
dc.date.available | 2021-09-15T08:25:18Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | IEEE Transactions on Mobile Computing, 2015, v. 14, n. 2, p. 444-457 | - |
dc.identifier.issn | 1536-1233 | - |
dc.identifier.uri | http://hdl.handle.net/10722/303437 | - |
dc.description.abstract | Indoor localization is of great importance for a range of pervasive applications, attracting many research efforts in the past decades. Most radio-based solutions require a process of site survey, in which radio signatures of an interested area are annotated with their real recorded locations. Site survey involves intensive costs on manpower and time, limiting the applicable buildings of wireless localization worldwide. In this study, we investigate novel sensors integrated in modern mobile phones and leverage user motions to construct the radio map of a floor plan, which is previously obtained only by site survey. Considering user movements in a building, originally separated RSS fingerprints are geographically connected by user moving paths of locations where they are recorded, and they consequently form a high dimension fingerprint space, in which the distances among fingerprints are preserved. The fingerprint space is then automatically mapped to the floor plan in a stress-free form, which results in fingerprints labeled with physical locations. On this basis, we design LiFS, an indoor localization system based on off-the-shelf WiFi infrastructure and mobile phones. LiFS is deployed in an office building covering over 1,600 m2 , and its deployment is easy and rapid since little human intervention is needed. In LiFS, the calibration of fingerprints is crowdsourced and automatic. Experiment results show that LiFS achieves comparable location accuracy to previous approaches even without site survey. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Transactions on Mobile Computing | - |
dc.subject | smartphones | - |
dc.subject | Indoor localization | - |
dc.subject | floor plan | - |
dc.subject | RSS fingerprint | - |
dc.subject | site survey | - |
dc.title | Smartphones based crowdsourcing for indoor localization | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TMC.2014.2320254 | - |
dc.identifier.scopus | eid_2-s2.0-84919934995 | - |
dc.identifier.volume | 14 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 444 | - |
dc.identifier.epage | 457 | - |
dc.identifier.isi | WOS:000347098100016 | - |