Enhancing semantic spaces with event-driven context interpretation

One important functionality provided by a context-aware infrastructure is to derive high-level contexts on behalf of context-aware applications. High-level contexts are summary descriptions about users' states and surroundings which are generally inferred from low-level, explicit contexts directly provided by hardware sensors and software programs. In Semantic Space, an ontology-based context-aware infrastructure, high-level contexts are derived using context reasoning. In this paper, we present another approach to deriving high-level contexts in Semantic Space, event-driven context interpretation. We show how event-driven context interpretation can leverage on the context model and dynamic context acquisition/representation in Semantic Space as well as easily integrate into Semantic Space. Differing from the context reasoning approach, our proposed event-driven context interpreter offers better performance in terms of flexibility, scalability and processing time. We also present a prototype of the event-driven context interpreter we are building within Semantic Space to validate the feasibility of the new approach.