A Context-Aware Model for Smart Space

With mobile and pervasive computing prevails increasingly today, applications and services in smart spaces should quickly sense the context and adapt to context changing in highly dynamic environment. Personized services are also needed. Now many context models were build according to specific smart space, lacking of common structure to different fields. We propose a common ontology context model to enable the reusing and sharing of ontology. Then we propose a forward chaining reasoning method based on Rete algorithm to optimize the rule matching process. Finally we show a context model of Smart Home which was built on the common model. A rule-based reasoning test is conducted to prove the usability of the model.