Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/105671
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Computing | - |
dc.creator | Chen, Y | - |
dc.creator | Guo, M | - |
dc.creator | Shen, J | - |
dc.creator | Cao, J | - |
dc.date.accessioned | 2024-04-15T07:35:49Z | - |
dc.date.available | 2024-04-15T07:35:49Z | - |
dc.identifier.issn | 1617-4909 | - |
dc.identifier.uri | http://hdl.handle.net/10397/105671 | - |
dc.language.iso | en | en_US |
dc.publisher | Springer UK | en_US |
dc.rights | © Springer-Verlag London 2017 | en_US |
dc.rights | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use(https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s00779-017-1011-7. | en_US |
dc.subject | Graph-based matching | en_US |
dc.subject | Subarea localization | en_US |
dc.subject | WiFi radio signal strength | en_US |
dc.subject | Zero-configuration | en_US |
dc.title | GraphLoc : a graph-based method for indoor subarea localization with zero-configuration | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 489 | - |
dc.identifier.epage | 505 | - |
dc.identifier.volume | 21 | - |
dc.identifier.issue | 3 | - |
dc.identifier.doi | 10.1007/s00779-017-1011-7 | - |
dcterms.abstract | Indoor subarea localization can facilitate numerous location-based services, such as indoor navigation, indoor POI recommendation and mobile advertising. Most existing subarea localization approaches suffer from two bottlenecks, one is fingerprint-based methods require time-consuming site survey and another is triangulation-based methods are lack of scalability. In this paper, we propose a graph-based method for indoor subarea localization with zero-configuration. Zero-configuration means the proposed method can be directly employed in indoor environment without time-consuming site survey or pre-installing additional infrastructure. To accomplish this, we first utilize two unexploited characteristics of WiFi radio signal strength to generate logical floor graph and then formulate the problem of constructing fingerprint map as a graph isomorphism problem between logical floor graph and physical floor graph. In online localization phase, a Bayesian-based approach is utilized to estimate the unknown subarea. The proposed method has been implemented in a real-world shopping mall, and extensive experimental results show that the proposed method can achieve competitive performance comparing with existing methods. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Personal and ubiquitous computing, June 2017, v. 21, no. 3, p. 489-505 | - |
dcterms.isPartOf | Personal and ubiquitous computing | - |
dcterms.issued | 2017-06 | - |
dc.identifier.scopus | 2-s2.0-85013223253 | - |
dc.identifier.eissn | 1617-4917 | - |
dc.description.validate | 202402 bcch | - |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | COMP-1236 | en_US |
dc.description.fundingSource | RGC | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | National Basic Research 973 Program of China; National Natural Science Foundation of China; Program for National Natural Science Foundation of China / Research Grants Council (NSFC/RGC); Program for Changjiang Scholars and Innovative Research Team in University; Scientific In-novation Act of STCSM; EU FP7 CLIMBER project | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 6724144 | en_US |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Cao_Graphloc_Graph-Based_Method.pdf | Pre-Published version | 1.37 MB | Adobe PDF | View/Open |
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