Document Type
Conference Paper
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
1.2 COMPUTER AND INFORMATION SCIENCE
Abstract
In the domain of ubiquitous computing, the ability to identify the occurrence of situations is a core function of being 'context- aware'. Given the uncertain nature of sensor information and inference rules, reasoning techniques that cater for uncertainty hold promise for enabling the inference process. In our work, we apply the Dempster Shafer theory of evidence to determine situation occurrence based on uncertain sensor data and inference rules. We also describe a set of evidential operations for sensor mass functions using context quality and evidence accumulation for temporal situation detection. We demonstrate how our approach enables situation inference with uncertain information using a case study based on a published smart home activity data set.
DOI
https://doi.org/10.1007/978-3-642-04471-7_12
Recommended Citation
McKeever S, Ye, J, & Coyle, L. (2009). Using Dempster Shafer Theory of Evidence for Situation Inference, Proceedings of EuroSSC 2009, Sept., London, UK. doi:10.1007/978-3-642-04471-7_12
Publication Details
Proceedings of EuroSSC 2009, Sept 2009, London, UK