Semantic annotation of summarized sensor data stream for effective query processing

摘要: In the big data era, volume of streaming produced by sensor networks is staggeringly large that enables business intelligence to make well-informed decisions on emerging modern applications. Performing analytics and query processing over fast arriving streams a tedious process. The semantic annotation stream provides high-level description, context supports intelligent querying analytics. This paper presents framework called SEmantic Annotation Summarized sensOr Data stReam (SEASOR) includes summarization, annotation, facilitates summarization merges these types values increase performance decrease memory space. scripted with help application-dependent base ontology extends Semantic Sensor Network (SSN) ontology. detailed descriptions for observation sensors using ontology, it divides into several subsets according sensing features. domain model processor access relevant results via an annotated Resource Description Framework (RDF). uses extended SPARQL (Cs-SPARQL) only relatively small subset RDF file allows extending support windows parallel streams. experimental prove proposed SEASOR timely answers user queries achieves better in terms result accuracy 95%.