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Constraint Satisfaction in Intelligent Context-Aware Systems

Context-aware systems provide an effective basis upon which the processing of captured and user-entered data (contextual information) with a direct relationship to an individuals current personal and environmental situation (termed ‘situated role’) can be achieved. Context-aware systems have significant potential benefits for the individual, academia, and industry alike, the use of context being evident in a broad and diverse range of domains and systems. The implementation of context however introduces the issue of constraint satisfaction and preference compliance. This paper considers this issue and presents an algorithm incorporating weighting applied to context properties in a quantitative approach to enable mitigation of violations of constraints and expressed preferences. The algorithm is presented with proof-of-concept. Implementation is considered with related issues and projected future research.