A framework is introduced that is aimed at integrating ontology- and logic-based approaches for context-awareness, suitable for use in Ambient Intelligence (AmI) scenarios. In particular, the context description language is described, which allows to easily specify patterns of events which occurrences must be monitored by actual systems. As long as systems evolve, symbolic data originating from heterogeneous sources are first aggregated and then classified according to formulas described in . Experimental results performed in a Smart Home environment are presented and discussed.
Designing a context-aware artificial system
MASTROGIOVANNI, FULVIO;SCALMATO, ANTONELLO;SGORBISSA, ANTONIO;ZACCARIA, RENATO UGO RAFFAELE
2008-01-01
Abstract
A framework is introduced that is aimed at integrating ontology- and logic-based approaches for context-awareness, suitable for use in Ambient Intelligence (AmI) scenarios. In particular, the context description language is described, which allows to easily specify patterns of events which occurrences must be monitored by actual systems. As long as systems evolve, symbolic data originating from heterogeneous sources are first aggregated and then classified according to formulas described in . Experimental results performed in a Smart Home environment are presented and discussed.
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