DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cho, Dae-Ki | ko |
dc.contributor.author | Lee, Uichin | ko |
dc.contributor.author | Noh, Youngtae | ko |
dc.contributor.author | Park, Taiwoo | ko |
dc.contributor.author | Song, June-Hwa | ko |
dc.date.accessioned | 2015-06-03T06:19:43Z | - |
dc.date.available | 2015-06-03T06:19:43Z | - |
dc.date.created | 2015-05-26 | - |
dc.date.created | 2015-05-26 | - |
dc.date.created | 2015-05-26 | - |
dc.date.issued | 2015-05 | - |
dc.identifier.citation | PERVASIVE AND MOBILE COMPUTING, v.19, pp.24 - 36 | - |
dc.identifier.issn | 1574-1192 | - |
dc.identifier.uri | http://hdl.handle.net/10203/198693 | - |
dc.description.abstract | Fine-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.language | English | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.title | PlaceWalker: An energy-efficient place logging method that considers kinematics of normal human walking | - |
dc.type | Article | - |
dc.identifier.wosid | 000353830400002 | - |
dc.identifier.scopusid | 2-s2.0-84929047178 | - |
dc.type.rims | ART | - |
dc.citation.volume | 19 | - |
dc.citation.beginningpage | 24 | - |
dc.citation.endingpage | 36 | - |
dc.citation.publicationname | PERVASIVE AND MOBILE COMPUTING | - |
dc.identifier.doi | 10.1016/j.pmcj.2014.04.001 | - |
dc.contributor.localauthor | Lee, Uichin | - |
dc.contributor.localauthor | Song, June-Hwa | - |
dc.contributor.nonIdAuthor | Cho, Dae-Ki | - |
dc.contributor.nonIdAuthor | Noh, Youngtae | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Energy-efficient place logging | - |
dc.subject.keywordAuthor | Semantic location context | - |
dc.subject.keywordAuthor | Location-aware services | - |
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