Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, China
Abstract :
This paper describes a context aware system that shall be able to effectively classify and store context information, and to reason out user behavior according to context information, in order to provide appropriate service. This study uses ontology to build a context model, as ontology has the ability to express abundant information. In addition, case-based reasoning is used for context reasoning, and refers to the user´s historical information, the reasoning ability of the system increases and approaches the user as the number of cases increases. When the behavior of the user is known, this study uses personal ontology to express the user´s habit and preferences for services, and uses personal ontology to select appropriate services, and finally, the OSGi platform provides services to meet user requirements. The field of this study is the development of an intelligent space system for common families by providing home services, such as lighting, music, air conditioning, IP-Cam, alarms, etc., the system can integrate service information and provide appropriate services for the user at the appropriate time. Fuzzy ontology is based on the concept that each index term or object is related to every other term in the ontology, via sensors of degrees, for all home devices of membership assigned to that relationship and based on fuzzy signature, as introduced by L.T. Koczy (1999).
Keywords :
case-based reasoning; fuzzy set theory; home computing; knowledge based systems; ontologies (artificial intelligence); open systems; ubiquitous computing; OSGi platform; abundant information; appropriate services; appropriate time; auto-plug in; case-based reasoning; context aware system; context information; context reasoning; context-models; fuzzy ontology; fuzzy signature; home devices; home services; intelligent home information system; intelligent space system; personal ontology; reasoning ability; service information; user behavior; user historical information; user requirements; Cognition; Context; Context modeling; Databases; Lighting; Ontologies; Sensors; Fuzzy rough set; OSGi; Ontology model; UPnP; auto-plug in; context-models;