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Expanding sensor networks to automate knowledge acquisition

Conroy, Kenneth and May, Gregory and Roantree, Mark and Warrington, Giles (2011) Expanding sensor networks to automate knowledge acquisition. In: British National Conference on Databases, 12-14th July 2011, Manchester, UK.

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Abstract

The availability of accurate, low-cost sensors to scientists has resulted in widespread deployment in a variety of sporting and health environments. The sensor data output is often in a raw, proprietary or unstructured format. As a result, it is often difficult to query multiple sensors for complex properties or actions. In our research, we deploy a heterogeneous sensor network to detect the various biological and physiological properties in athletes during training activities. The goal for exercise physiologists is to quickly identify key intervals in exercise such as moments of stress or fatigue. This is not currently possible because of low level sensors and a lack of query language support. Thus, our motivation is to expand the sensor network with a contextual layer that enriches raw sensor data, so that it can be exploited by a high level query language. To achieve this, the domain expert specifies events in a tradiational event-condition-action format to deliver the required contextual enrichment.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:sensors; exercise
Subjects:Computer Science > Information technology
Computer Science > Computer software
Computer Science > Information storage and retrieval systems
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Published in:Proceedings of 28th British National Conference on Databases. Lecture Notes in Computer Science . Springer-Verlag.
Publisher:Springer-Verlag
Copyright Information:© 2011 Springer-Verlag. The original publication is available at www.springerlink.com
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland (SFI)
ID Code:16581
Deposited On:10 Oct 2011 14:18 by Kenneth Conroy. Last Modified 10 Oct 2011 14:18

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