dc.date.accessioned | 2008-12-30T21:45:11Z | |
dc.date.accessioned | 2018-11-26T22:25:50Z | |
dc.date.available | 2008-12-30T21:45:11Z | |
dc.date.available | 2018-11-26T22:25:50Z | |
dc.date.issued | 2008-12-30 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/43951 | |
dc.identifier.uri | http://repository.aust.edu.ng/xmlui/handle/1721.1/43951 | |
dc.description.abstract | We 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.extent | 14 p. | en_US |
dc.subject | Shared Sensing | en_US |
dc.subject | Computer Communication Networks | en_US |
dc.subject | Localization | en_US |
dc.subject | Location-Based Services | en_US |
dc.subject | Geo-Tagging | en_US |
dc.subject | Collaborative Computing | en_US |
dc.subject | Distributed Systems | en_US |
dc.subject | Distributed Applications | en_US |
dc.subject | Pervasive Computing | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Experiments | en_US |
dc.subject | Groups and Organization Interfaces | en_US |
dc.subject | Measurement | en_US |
dc.subject | Crowd-Sourcing | en_US |
dc.subject | Information Interfaces and Presentation | en_US |
dc.subject | Human Factors | en_US |
dc.title | Organic Indoor Location Discovery | en_US |