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Pinpointing users with location estimation techniques and Wi-Fi hotspot technology

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Curran, Kevin and Furey, E (2008) Pinpointing users with location estimation techniques and Wi-Fi hotspot technology. International Journal of Network Management, 18 (5). pp. 395-408. [Journal article]

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DOI: 10.1002/nem.683

Abstract

Location awareness is becoming an important capability for mobile computing; however, it has not been possible until now to provide cheap pervasive positioning systems. Wide area coverage is most famously achieved by using global positioning systems (GPS). A constellation of low-orbit satellites cover the earth’s surface. Unfortunately GPS does not work indoors and has limited success in big cities because of the ‘urban canyon’ effect. PlaceLab is a research project that attempts to solve the ubiquity issues surrounding 802.11-based location estimation. PlaceLab, like RADAR, uses a device’s 802.11 interface; however, it does not require the area to be pre-calibrated. It predicts location via the known positions of the access points detected by the device. Commonly used systems have a number of drawbacks, including cost, accuracy and the ability to work indoors. PlaceLab is a piece of open source software developed by Intel Research that can pinpoint a user within a Wi-Fi network. We set out here to investigate whether PlaceLab can be used as a means of establishing a user’s position. This type of investigation could, if successful, pave the way for the development of other location-based applications. This report documents the efforts to answer the above question. PlaceLab was found to work, but only in ideal locations where factors such as the number of floors and the lack of available APs did not affect its use. It was concluded that these factors prevent the system from being effective as a means of establishing a user’s position in most locations on campus.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:17432
Deposited By:Dr Kevin Curran
Deposited On:07 Mar 2011 13:03
Last Modified:05 May 2011 12:01

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