Using Dempster-Shafer Theory of Evidence for Situation Inference

In the domain of ubiquitous computing, the ability to identify the occurrence of situations is a core function of being 'contextaware'. 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.