Enhancing semantic spaces with event-driven context interpretation

  • Authors:

  • Joo Geok Tan;Daqing Zhang;Xiaohang Wang;Heng Seng Cheng

  • Affiliations:

  • Institute for Infocomm Research, Singapore;Institute for Infocomm Research, Singapore;National University of Singapore, Singapore;Institute for Infocomm Research, Singapore

  • Venue:
  • PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
  • Year:
  • 2005

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Abstract

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.