PlaceWalker: An energy-efficient place logging method that considers kinematics of normal human walking

Cited 4 time in webofscience Cited 7 time in scopus
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dc.contributor.authorCho, Dae-Kiko
dc.contributor.authorLee, Uichinko
dc.contributor.authorNoh, Youngtaeko
dc.contributor.authorPark, Taiwooko
dc.contributor.authorSong, June-Hwako
dc.date.accessioned2015-06-03T06:19:43Z-
dc.date.available2015-06-03T06:19:43Z-
dc.date.created2015-05-26-
dc.date.created2015-05-26-
dc.date.created2015-05-26-
dc.date.issued2015-05-
dc.identifier.citationPERVASIVE AND MOBILE COMPUTING, v.19, pp.24 - 36-
dc.identifier.issn1574-1192-
dc.identifier.urihttp://hdl.handle.net/10203/198693-
dc.description.abstractFine-grained place logging with Wi-Fi beacon signatures provides a useful tool for delivering various semantic location-aware services such as reminders and advertisements. Existing solutions however heavily rely on energy-hungry periodic Wi-Fi scanning for place detection in resource limited mobile devices. In this paper, we present PlaceWalker, a scheme that uses a low-power duty-cycled accelerometer in the background to continuously monitor user's significant physical activity changes (e.g., walking to resting) as it provides a useful clue to the change of place. Unlike existing schemes, PlaceWalker triggers Wi-Fi scanning only when such an activity shift is detected and then determines a change of place by comparing Wi-Fi signatures. Our experimental results verify that detecting significant activity intensity changes can precisely capture arrival/departure times, and PlaceWalker substantially lowers the energy consumption by as much as 60.9%, when compared with the state-of-the-art method. We also analyze the experimental results with a simple analytic model and validate its efficiency under varying parameter settings.-
dc.languageEnglish-
dc.publisherELSEVIER SCIENCE BV-
dc.titlePlaceWalker: An energy-efficient place logging method that considers kinematics of normal human walking-
dc.typeArticle-
dc.identifier.wosid000353830400002-
dc.identifier.scopusid2-s2.0-84929047178-
dc.type.rimsART-
dc.citation.volume19-
dc.citation.beginningpage24-
dc.citation.endingpage36-
dc.citation.publicationnamePERVASIVE AND MOBILE COMPUTING-
dc.identifier.doi10.1016/j.pmcj.2014.04.001-
dc.contributor.localauthorLee, Uichin-
dc.contributor.localauthorSong, June-Hwa-
dc.contributor.nonIdAuthorCho, Dae-Ki-
dc.contributor.nonIdAuthorNoh, Youngtae-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorEnergy-efficient place logging-
dc.subject.keywordAuthorSemantic location context-
dc.subject.keywordAuthorLocation-aware services-
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IE-Journal Papers(저널논문)CS-Journal Papers(저널논문)
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