A platform for matching context in real time

Abstract

Context-awareness is a key feature of Ambient Intelligence and future intelligent systems. In order to achieve context-aware behavior, applications must be able to detect context information, recognize situations and correctly decide on context-aware action. The representation of context information and the manner in which context is detected are central issues. Based on our previous work in which we used graphs to represent context and graph matching to detect situations, in this paper we present a platform that completely handles context matching, and does so in real time, in the background, by deferring matching to a component that acts incrementally, relying on previous matching results. The platform has been implemented and tested on an AAL-inspired scenario.