A technique developed by an international research team could potentially improve the accuracy of determining the position of mobile devices. The protocol simultaneously predicts the location of the mobile device user and the data access points, or hotspots.
Sinno Jialin Pan at the A*STAR Institute for Infocomm Research and colleagues trained a learning-based system with the signal-strength values received from access points at selected places in the area of interest, then used the information to calibrate a probabilistic location-estimation system. They approximated the location from the learned model using signal strength samples received in real time from the access points. During testing, the approach required less calibration and was more accurate than state-of-the-art systems.
The technique could lead to the development of a new class of mobile apps that react to small changes in position. "We . . . want to find ways to make use of the estimated locations to provide more useful information, such as location-based advertising," Pan says. Robots also could use the approach to navigate on their own, he says.
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Abstracts Copyright © 2012 Information Inc., Bethesda, Maryland, USA
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