Implementation of Semantic Web on Wireless Sensor Application for Environment Monitoring

The Semantic makes the machine understand data automatically and able to process then infer new data information from existing ones. The quick development of the automotive industry and the decreasing number of trees due to the development of the residential caused environmental conditions less healthy. Continuous health monitor of the environment is an important step in order to maintain the environmental conditions. In this paper, the Semantic Web has been implemented to process gas sensor data using Wireless Sensor Networks (WSN) to monitor environmental health. The sensor of temperature, humidity, Carbon Monoxide (CO) and Carbon Dioxide (CO2) has been used. WSN system is developed using hardware Waspmote PRO v1.2 and Waspmote Gases Sensor Board v2.0. XBee devices used to communication between board sensor gases with the server. The data sensor consists of temperature, humidity, CO and CO2 from the sensor nodes will transmit to the semantic database with XBee communication through python programming include RDFLib to OpenRDF semantic Database. Ontology on Semantic Database will store and process data. A website has been developed with semantic technology to displayed data sensors in real-time from the semantic database through PHP Programming with SparqlLib.