Autor/Autorin: Mekuria Birhanu
Birhanu Mekuria,a graduate of Addis Ababa University,holds B.Sc. and M.Sc. in Computer Science.His is interested in Mobile Computing, Pervasive Systems, Context-Aware Systems and Semantic Web. He worked as a Programmer in Ethiopian Telecom and thought at Addis Ababa University.He is an Independent Software Developer specializing in Web Development.
Context information refinement is aimed at deriving context information to assist applications in making decisions on what to deliver to users.We identified the limitations of existing works regarding context information refinement in pervasive medical systems. Lack of consideration for quality parameters of context information,relevance of context information and requirements of the pervasive health care domain are the major ones. The proposed architecture is composed of client mobile device and context refinement server. The client mobile device consists of components for tracking device context, listening to incoming events,interface for specifying service constraints and local caching services. On the context refinement server are the reasoning and decision engine, the service parameters manager, the context ontology and the context acquisition component that collects and aggregates context data from context sources. To demonstrate the validity of the proposed architecture, we developed a prototype that implements components of the architecture. The prototype was tested with a real-life pervasive health care scenario and encouraging initial results were obtained.
Context information refinement is aimed at deriving context information to assist applications in making decisions on what to deliver to users.We identified the limitations of existing works regarding context information refinement in pervasive medical systems. Lack of consideration for quality parameters of context information,relevance of context information and requirements of the pervasive health care domain are the major ones. The proposed architecture is composed of client mobile device and context refinement server. The client mobile device consists of components for tracking device context, listening to incoming events,interface for specifying service constraints and local caching services. On the context refinement server are the reasoning and decision engine, the service parameters manager, the context ontology and the context acquisition component that collects and aggregates context data from context sources. To demonstrate the validity of the proposed architecture, we developed a prototype that implements components of the architecture. The prototype was tested with a real-life pervasive health care scenario and encouraging initial results were obtained.
Über den Autor
Birhanu Mekuria,a graduate of Addis Ababa University,holds B.Sc. and M.Sc. in Computer Science.His is interested in Mobile Computing, Pervasive Systems, Context-Aware Systems and Semantic Web. He worked as a Programmer in Ethiopian Telecom and thought at Addis Ababa University.He is an Independent Software Developer specializing in Web Development.
Klappentext
Context information refinement is aimed at deriving context information to assist applications in making decisions on what to deliver to users.We identified the limitations of existing works regarding context information refinement in pervasive medical systems. Lack of consideration for quality parameters of context information,relevance of context information and requirements of the pervasive health care domain are the major ones. The proposed architecture is composed of client mobile device and context refinement server. The client mobile device consists of components for tracking device context, listening to incoming events,interface for specifying service constraints and local caching services. On the context refinement server are the reasoning and decision engine, the service parameters manager, the context ontology and the context acquisition component that collects and aggregates context data from context sources. To demonstrate the validity of the proposed architecture, we developed a prototype that implements components of the architecture. The prototype was tested with a real-life pervasive health care scenario and encouraging initial results were obtained.
