Context-Aware Sensor Search Framework in Semantic Web of Things
Heying Gong -, Yimin Shi, Guanyu Li · 2016
The problem that the current sensor search methods cannot use the important character of sensors and semantic information efficiently leads to the search result can not satisfy the user's actual demand, Context-aware Sensor Search Framework (CASSF) in Semantic Web of Things is proposed. In the framework, sensor information is stored as RDF graph to preserve the semantic information to the maximum extent, user requirements are transformed to structured query language in order to search sensor entity according to the pattern information of sensor related context ontology, an approximate query method called Threshold Algorithm for Sensor Information (TASI) is put forward to reduce query scope thus improves the overall search efficiency. By contrasting, CASSF is better satisfied with user requirement than other sensor search methods.