Development of semantic sensor web for monitoring environment conditions

The semantic sensor web (SSW) is a combination of sensor networks, web services, database and semantic web technologies. The SSW describes sensor data with spatial, temporal, and thematic semantic metadata. One of the challenges for sensor web application is the integration and fusion of data coming from autonomously deployed sensor network. Gas Sensor technology is one of the wireless sensor network (WSN), which has a wide range of sensors that can be used to monitor the concentration of gas in a region. This paper implements SSW with existing gas sensor to perform readings from the environment, store it into a database and provide services application program interface (API) data. Sensor data used in this study are temperature, CO, CO
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and Humidity Sensor. The method we use is to build a Semantic Web to connect the sensor data that is spread by harnessing service API on the sensor semantic web servers interconnected. Furthermore, the data retrieved from the sensors will be represented in the form of ontology with RDF/OWL type and stored into RDF Repository (OPENRDF-SESAME) in order to be processed and published to the semantic web service. SPARQL library and curl serves to bridge the gap between service and Apache Tomcat. Existing data in the RDF Triple Store file will be displayed to the user to utilize the service using standard API RESTFUL. Then the existing data in the RDF database is displayed in a JSON data format.