An approach to data fusion for context awareness

Authors:
Amir Padovitz;Seng W. Loke;Arkady Zaslavsky;Bernard Burg;Claudio Bartolini
Affiliations:
Centre for Distributed Systems and Software Engineering, Caulfield-East, Victoria, Australia;Centre for Distributed Systems and Software Engineering, Caulfield-East, Victoria, Australia;Centre for Distributed Systems and Software Engineering, Caulfield-East, Victoria, Australia;HP Labs, Palo-Alto;HP Labs, Palo-Alto
Venue:
CONTEXT'05 Proceedings of the 5th international conference on Modeling and Using Context
Year:
2005

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Abstract

We propose and develop an approach modeled with multi-attribute utility theory for sensor fusion in context-aware environments. Our approach is distinguished from existing general purpose fusion techniques by a number of factors including a general underlying context model it is built upon and a set of heuristics it covers. The technique is developed for context-aware applications and we argue that it provides various advantages for data fusion in context-aware scenarios. We experimentally evaluate our approach with actual use cases using real sensors.