Knowledge Acquisition from Sensor Data in an Equine Environment

  • Kenneth Conroy
  • Gregory May
  • Mark Roantree
  • Giles Warrington
  • Sarah Jane Cullen
  • Adrian McGoldrick
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6862)


Recent advances in sensor technology have led to a rapid growth in the availability of accurate, portable and low-cost sensors. In the Sport and Health Science domains, this has been used to deploy multiple sensors in a variety of situations in order to monitor participant and environmental factors of an activity or sport. As these sensors often output their data in a raw, proprietary or unstructured format, it is difficult to identify periods of interest, such as events or actions of interest to the Sport and Exercise Physiologists. In our research, we deploy multiple sensors on horses and jockeys while they engage in horse-racing training exercises. The Exercise Physiologists aim to identify events which contribute most to energy expenditure, and classify both the horse and jockey movement using basic accelerometer sensors. We propose a metadata driven approach to enriching the raw sensor data using a series of Profiles. This data then forms the basis of user defined algorithms to detect events using an Event-Condition-Action approach. We provide an Event Definition interface which is used to construct algorithms based on sensor measurements both before and after integration. The result enables the end user to express high level queries to meet their information needs.


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  1. 1.
    Babitski, G., Bergweiler, S., Hoffmann, J., Schon, D., Stasch, C., Walkowski, A.: Ontology-Based Integration of Sensor Web Services in Disaster Management. In: Janowicz, K., Raubal, M., Levashkin, S. (eds.) GeoS 2009. LNCS, vol. 5892, pp. 103–121. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  2. 2.
    Bonnet, P., Gehrke, J., Seshadri, P.: Towards Sensor Database Systems. In: Tan, K.-L., Franklin, M.J., Lui, J.C.-S. (eds.) MDM 2001. LNCS, vol. 1987, pp. 3–14. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  3. 3.
    Conroy, K., May, G., Roantree, M., Warrington, G.: Expanding Sensor Networks to Automate Knowledge Acquisition. In: To Appear in British National Conference on Databases (BNCOD). LNCS. Springer, Heidelberg (2011)Google Scholar
  4. 4.
    Corrales, J.A., Candelas, F.A., Torres, F.: Sensor data integration for indoor human tracking. Robotics and Autonomous Systems 58(8), 931–939 (2010)CrossRefGoogle Scholar
  5. 5.
    Cosmed (2011),
  6. 6.
    Da Costa, R.A.G., Cugnasca, A.E.: Use of Data Warehouse to Manage Data from Wireless Sensors Networks That Monitor Pollinators. In: 11th International Conference on Mobile Data Management (MDM), pp. 402–406. IEEE Computer Society, Los Alamitos (2010)Google Scholar
  7. 7.
    Henson, C.A., Pschorr, J.K., Sheth, A.P., Thirunarayan, K.: SemSOS: Semantic sensor Observation Service. In: International Symposium on Collaborative Technologies and Systems (CTS), pp. 44–53 (2009)Google Scholar
  8. 8.
    Marks, G., Roantree, M., Smyth, D.: Optimizing Queries for Web Generated Sensor Data. In: Australasian Database Conference (ADC), pp. 151–159. Australian Computer Society, Inc. (2011)Google Scholar
  9. 9.
    Observations and Measurements (2011),
  10. 10.
    Resource Description Framework in attributes (RDFa) (2011),
  11. 11.
    Semantic Web Rule Language (2011),
  12. 12.
    SenseWear System (BodyMedia) (2011),
  13. 13.
    Sensor Observation Service (2011),
  14. 14.
  15. 15.
    Sheth, A.P., Henson, C.A., Sahoo, S.S.: Semantic Sensor Web. IEEE Internet Computing 12, 78–83 (2008)CrossRefGoogle Scholar
  16. 16.
    The Irish Turf Club (2011),
  17. 17.
    Web Ontology Language (2011),
  18. 18.
  19. 19.
    XQuery Update Facility (2011),
  20. 20.
    Yang, J., Zhang, C., Li, X., Huang, Y., Fu, S., Acevedo, M.F.: Integration of wireless sensor networks in environmental monitoring cyber infrastructure. Wireless Networks 16(4), 1091–1108 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Kenneth Conroy
    • 1
  • Gregory May
    • 1
  • Mark Roantree
    • 2
  • Giles Warrington
    • 1
  • Sarah Jane Cullen
    • 3
  • Adrian McGoldrick
    • 4
  1. 1.CLARITY: Centre for Sensor Web TechnologiesIreland
  2. 2.Interoperable Systems Group, School of ComputingIreland
  3. 3.School of Health & Human PerformanceDublin City UniversityDublin 9Ireland
  4. 4.The Turf Club, The Curragh, Co. KildareIreland

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