Situation modeling and identifying under uncertainty

Situation modeling and identifying are key issues for situation-aware applications. Uncertainty modeling and reasoning are big challenges in these processes: the semantic of situation may be fuzzy; context usually comes with imperfection such as imprecision and incompleteness. To overcome this problem, this paper proposes an innovative model for situation modeling and identifying under uncertainty. In this model, fuzzy ontology based on our new fuzzy language, F -OWL, is used to model context and situation, which can make the structure and semantic of context and situation easily understood, reused and shared by users, devices and services. Then a situation approximate identifying algorithm is proposed to identify situations considering uncertainty, which is a robust and reliable one.