DogOnt - Ontology modeling for intelligent domotic environments

Abstract

Home automation has recently gained a new momentum thanks to the ever-increasing commercial availability of domotic components. In this context, researchers are working to provide interoperation mechanisms and to add intelligence on top of them. For supporting intelligent behaviors, house modeling is an essential requirement to understand current and future house states and to possibly drive more complex actions. In this paper we propose a new house modeling ontology designed to fit real world domotic system capabilities and to support interoperation between currently available and future solutions. Taking advantage of technologies developed in the context of the Semantic Web, the DogOnt ontology supports device/network independent description of houses, including both "controllable" and architectural elements. States and functionalities are automatically associated to the modeled elements through proper inheritance mechanisms and by means of properly defined SWRL auto-completion rules which ease the modeling process, while automatic device recognition is achieved through classification reasoning. © 2008 Springer Berlin Heidelberg.