Enabling knowledge extraction from low level sensor data

Authors:
Paolo Cappellari;Jie Shi;Mark Roantree;Crionna Tobin;Niall Moyna
Affiliations:
Interoperable Systems Group, Dublin City University;Interoperable Systems Group, Dublin City University;Interoperable Systems Group, Dublin City University;School of Health and Human Performance, Dublin City University;School of Health and Human Performance, Dublin City University
Venue:
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
Year:
2011

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Abstract

While sensor networks play a significant role in the modern information society, they output data in proprietary format and with little or no associated semantics. As a consequence, sensed data must be managed on a case by case basis, requiring significant human efforts. In this paper, we present an approach that: seamlessly supports any kind of network by exposing sensed data in a standard format; enables users to specify at a high level how to enrich sensed data with the semantics in which data is generate; facilitates end users in transforming data to meet their analytical requirements.