Situation Awareness Meets Ontologies: A Context Spaces Case Study
Abstract
Efficiency and appeal of pervasive computing systems strongly de-pends on how well and robustly they represent and reason about context and situations. Populating situation search space and inferring situations from con-text which, in turn, is computed from fusing sensor data and observations re-mains a major research challenge. This paper proposes to use ontologies as rep-resentation of domain knowledge to generate situation search space and then match context with already defined situations. To illustrate the feasibility, a context spaces approach is used to represent, generate and reason about situa-tions as abstractions in a multidimensional space. The proposed approach is evaluated and discussed.
Authors:
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Conference Paper
Year:
2015
Location:
The Ninth International and Interdisciplinary Conference on Modeling and Using Context (CONTEXT'15)