Fuzzy Semantic Web Architecture for Activity Detection in Wireless Multimedia Sensor Network Applications

Abstract

This study aims to increase the reliability of activity detection in Wireless Multimedia Sensor Networks (WMSNs) by using Semantic Web technologies extended with fuzzy logic. The proposed approach consists of three layers: the sensor layer, the data layer, and the Semantic Web layer. The sensor layer comprises a WMSN comprising sensor nodes with multimedia and scalar sensors. The data layer retrieves and stores data from the sink of WMSN. At the top of the architecture, there is a semantic web layer that includes a semantic web application server, a fuzzy reasoning engine, and a semantic knowledge base. When a new entity is detected at the sensor layer, the associated data produced by the sensors and the sink are collected in the data layer and transmitted to the semantic web application server where the data is converted into subjects, predicates, and objects, according to the ontology conceived and recorded in RDF format. Then, the fuzzy reasoning engine is automatically activated and fuzzy rules are executed to determine if there is an activity in the monitored area. Our implementation confirms that extended semantic Web technologies with fuzzy logic can have a significant impact on the detection of activities in WMSNs.