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.
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Padovitz, A., Loke, S.W., Zaslavsky, A., Burg, B., Bartolini, C. (2005). An Approach to Data Fusion for Context Awareness. In: Dey, A., Kokinov, B., Leake, D., Turner, R. (eds) Modeling and Using Context. CONTEXT 2005. Lecture Notes in Computer Science(), vol 3554. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11508373_27
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DOI: https://doi.org/10.1007/11508373_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26924-3
Online ISBN: 978-3-540-31890-3
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