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PERCOM
2011
ACM

Using prediction to conserve energy in recognition on mobile devices

10 years 12 months ago
Using prediction to conserve energy in recognition on mobile devices
—As devices are expected to be aware of their environment, the challenge becomes how to accommodate these abilities with the power constraints which plague modern mobile devices. We present a framework for an embedded approach to context recognition which reduces power consumption. This is accomplished by identifying class-sensor dependencies, and using prediction methods to identify likely future classes, thereby identifying sensors which can be temporarily turned off. Different methods for prediction, as well as integration with several classifiers is analyzed and the methods are evaluated in terms of computational load and loss in quality of context. The results indicate that the amount of energy which can be saved is dependent on two variables (the acceptable loss in quality of recognition, and the number of most likely classes which should be accounted for), and two scenario-dependent properties (predictability of the context sequences and size of the context-sensor dependency ...
Dawud Gordon, Stephan Sigg, Yong Ding, Michael Bei
Added 22 Aug 2011
Updated 22 Aug 2011
Type Journal
Year 2011
Where PERCOM
Authors Dawud Gordon, Stephan Sigg, Yong Ding, Michael Beigl
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