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Organic Indoor Location Discovery

dc.date.accessioned2008-12-30T21:45:11Z
dc.date.accessioned2018-11-26T22:25:50Z
dc.date.available2008-12-30T21:45:11Z
dc.date.available2018-11-26T22:25:50Z
dc.date.issued2008-12-30
dc.identifier.urihttp://hdl.handle.net/1721.1/43951
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/43951
dc.description.abstractWe describe an indoor, room-level location discovery method based on spatial variations in "wifi signatures," i.e., MAC addresses and signal strengths of existing wireless access points. The principal novelty of our system is its organic nature; it builds signal strength maps from the natural mobility and lightweight contributions of ordinary users, rather than dedicated effort by a team of site surveyors. Whenever a user's personal device observes an unrecognized signature, a GUI solicits the user's location. The resulting location-tagged signature or "bind" is then shared with other clients through a common database, enabling devices subsequently arriving there to discover location with no further user contribution. Realizing a working system deployment required three novel elements: (1) a human-computer interface for indicating location over intervals of varying duration; (2) a client-server protocol for pre-fetching signature data for use in localization; and (3) a location-estimation algorithm incorporating highly variable signature data. We describe an experimental deployment of our method in a nine-story building with more than 1,400 distinct spaces served by more than 200 wireless access points. At the conclusion of the deployment, users could correctly localize to within 10 meters 92 percent of the time.en_US
dc.format.extent14 p.en_US
dc.subjectShared Sensingen_US
dc.subjectComputer Communication Networksen_US
dc.subjectLocalizationen_US
dc.subjectLocation-Based Servicesen_US
dc.subjectGeo-Taggingen_US
dc.subjectCollaborative Computingen_US
dc.subjectDistributed Systemsen_US
dc.subjectDistributed Applicationsen_US
dc.subjectPervasive Computingen_US
dc.subjectAlgorithmsen_US
dc.subjectExperimentsen_US
dc.subjectGroups and Organization Interfacesen_US
dc.subjectMeasurementen_US
dc.subjectCrowd-Sourcingen_US
dc.subjectInformation Interfaces and Presentationen_US
dc.subjectHuman Factorsen_US
dc.titleOrganic Indoor Location Discoveryen_US


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