{U}sing {S}emantic {A}nnotation for {K}nowledge {E}xtraction from {G}eographically {D}istributed and {H}eterogeneous {S}ensor {D}ata

Abstract

Using semantic technologies for enriching sensor data descriptionin scalable and heterogeneous sensor network are intended as a solutionfor better interoperability and easier maintainability. Through semanticannotations it is possible to provide context for sensor networks,which will improve knowledge extractions from sensor data streamsand will facilitate reasoning capabilities. We propose an architecturefor a system able to automatically annotate sensors descriptions,as provided by the publishers, with semantic concepts. The annotatedsensor data become more meaningful and machine understandable, enablingbetter analysis and processing from heterogeneous streams of data.Based on the system proposed, we provide illustrative examples fordemonstrating the improvements that semantic context brings and wediscuss a real-world scenario of Participatory Sensing.