PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Exposing real world information for the web of things
Alexandra Moraru, Dunja Mladenić, Matevž Vučnik, Maria Porcius, Carolina Fortuna and Mihael Mohorčič
In: IIWeb 2011, 28 Mar 2011, Hyderabad, India.


In this paper, we propose SemSense architecture for collecting real world data from a physical system of sensors and publishing it on the Web, thus contributing to the Web of Things. SemSense comprises of four components: (1) the data collection component, (2) the storage component (3) the semantic enrichment component and (4) the publishing component, which are described and implemented for an existing deployment of a sensor network. Through these components, the real world data is collected from the physical devices, processed, equipped with semantic information and published on the Web. The paper addresses challenges of efficiently collecting data and meta-data from sensors and publishing it following the linked data principles.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Information Retrieval & Textual Information Access
ID Code:8715
Deposited By:Jan Rupnik
Deposited On:21 February 2012