Ontology-based context-aware middleware for smart spaces

Weijun Qin, Yuanchun Shi, Yue Suo
<span title="">2007</span> <i title="Tsinghua University Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/w77vm44enzh4tgk44gtrsw7f64" style="color: black;">Tsinghua Science and Technology</a> </i> &nbsp;
Context-awareness enhances human-centric, intelligent behavior in a smart environment; however, context-awareness is not widely used due to the lack of effective infrastructure to support context-aware applications. This paper presents an agent-based middleware for providing context-aware services for smart spaces to afford effective support for context acquisition, representation, interpretation, and utilization to applications. The middleware uses a formal context model, which combines first
more &raquo; ... rder probabilistic logic (FOPL) and web ontology language (OWL) ontologies, to provide a common understanding of contextual information to facilitate context modeling and reasoning about imperfect and ambiguous contextual information and to enable context knowledge sharing and reuse. A context inference mechanism based on an extended Bayesian network approach is used to enable automated reactive and deductive reasoning. The middleware is used in a case study in a smart classroom, and performance evaluation result shows that the context reasoning algorithm is good for non-time-critical applications and that the complexity is highly sensitive to the size of the context dataset.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/s1007-0214(07)70179-7">doi:10.1016/s1007-0214(07)70179-7</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qkjtwps2trex7picyfva6glh3u">fatcat:qkjtwps2trex7picyfva6glh3u</a> </span>
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