SWANS: Semantic Web Architecture for Sensor Networks
2007 (English)Student thesis (Other (popular science, discussion, etc.))
The advancements in science and technology have improved our standards of living, yet unlocked countless problems. Today, when there is a rapid growth in creation of new systems; at the same time, the scientists are struggling with associated challenges which have been brought in front of us. One of the foremost challenge researchers have to confront is data integration from heterogeneous sources. The computing capacity becomes exponentially smaller and cheaper which led to a tremendous growth in the development of various sensor network. These sensor networks are present all around us measuring different physical and environmental phenomenas like location, temperature and so on. Unfortunately, the data from these sensor networks possess natural heterogeneity. Thus, integration of sensor data and its availability to different applications is an extremely tedious task. At the same time, the data provided by sensor networks is raw in nature and does not provide any meaningful information. The recent developments in semantic web technologies have brought hope to resolve this issue. Semantic web technologies geared towards integration, sharing and reusability of information in a machine-processable way. We carried out this research to propose architecture for heterogeneous sensor networks based on semantic web technologies. We call this Semantic Web Architecture for Sensor Networks (SWANS). This architecture provides a flexible and scalable infrastructure for sensor networks to integrate and share their raw data among different applications. Moreover, semantic web support for carrying out inferencing allowed us to extract more useful knowledge from the raw sensor data which otherwise would not have been possible. We followed the design science in information system research methodology to carry out this work. The problem has been explicitly defined and a case study was carried out with location and physiological sensor networks. The entire process was based on our proposed architecture to examine its effectiveness.
Place, publisher, year, edition, pages
context, aware, computing., sensor, networks,, ontology
IdentifiersURN: urn:nbn:se:su:diva-12090OAI: oai:DiVA.org:su-12090DiVA: diva2:178610