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AMI
2009
Springer

Increased Robustness in Context Detection and Reasoning Using Uncertainty Measures: Concept and Application

11 years 6 months ago
Increased Robustness in Context Detection and Reasoning Using Uncertainty Measures: Concept and Application
This paper reports on a novel recurrent fuzzy classification method for robust detection of context activities in an environment using either single or distributed sensors. It also introduces a classification of system architectures for uncertainty calculation in general. Our proposed novel method utilizes uncertainty measures for improvement of detection, fusion and aggregation of context knowledge. Uncertainty measurement calculations are based on our novel recurrent fuzzy system. We applied the method in a real application to recognize various applause (and non applause) situations, e.g. during a conference. Measurements were taken from mobile phone sensors (microphone, accel. if available) and acceleration sensory attached to a board marker. We show that we are able to improve robustness of detection using our novel recurrent fuzzy classifier in combination with uncertainty measures by ∼30% on average. We also show that the use of multiple phones and distributed recognition in...
Martin Berchtold, Michael Beigl
Added 25 May 2010
Updated 25 May 2010
Type Conference
Year 2009
Where AMI
Authors Martin Berchtold, Michael Beigl
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