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Supporting semantic Web of things functionality in the cloud

Tzavaras Aimilios

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Summary

The world is moving towards machine-type communication, where anything (from smart sensors to everyday products in supermarkets) will be connected to the Internet. The Semantic Web of Things (SWoT) concept suggests the design of interoperable services or Web of Things applications using Semantic Web technologies. SWoT is a semantic extension of the Web of Things that allows applications to share content and services beyond their limits or, even more significant, to develop new applications as a composition of existing ones (e.g. using mashups). The main idea is to succeed the accomplishment of these tasks automatically or with minimum human intervention. Tools that are capable of understanding the meaning of IoT applications (i.e. data and services) and reason over their content must be applied, in order to enable the SWoT vision. Just as in the Semantic Web, formal definitions of concepts and their properties form ontologies, which are defined using the RDF, RDFS and the OWL language. In particular, IoT ontologies comprise definitions of IoT concepts (e.g. sensors, services) along with their properties (e.g. sensor observations) by means of binary relations. Query languages such as SPARQL can be used for querying information in ontologies and reasoners such as Pellet can be applied for locating inconsistencies or for inferring new information from information represented in ontologies. In this thesis, a Semantic Web of Things architecture is designed and implemented, using the above technologies and adopting a service-oriented architecture. What’s more, the experimental results demonstrate the effectiveness of the above architecture and it is proved that the implementation of the SWoT vision is possible by combining the advantages of the classic and the new technologies as much as possible.

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