Hierarchical situation modeling and reasoning for pervasive computing

Situation awareness is one of the most fundamental features of entities in pervasive computing environments to dynamically adapt their behavior to situation changes to satisfy user requirements, including security and privacy. In order to support situation-aware adaptation, it is necessary to model and specify context and situation in a way such that multiple entities can easily exchange, share and reuse their knowledge on context and situation. In this paper, an OWL-based situation ontology to model situation hierarchically to facilitate sharing and reusing of situation knowledge and logic inferences is presented. The conversion of OWL situation ontology specifications to the first-order logic (FOL) representations, and the performance of FOL rule-based reasoning in terms of problem size and time are discussed