Making Sense of Sensor Data Using Ontology: A Discussion for Residential Building Monitoring

Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 382)


We illustrate the application of automated representation of knowledge acquired from sensor network data to quality of life services. Specifically, for a sensor network used to monitor a residential building we acquire knowledge about events of interest to occupants and represent such knowledge in ontology. An event of particular interest to quality of life which we discuss is ‘unhealthy’ exposure to carbon monoxide. Hence, we aim at reducing the considerable gap between raw sensor data and abstract domain terminology. Our results support the claim that computational techniques in signal processing, machine learning, and ontology engineering are important elements to systems that make use of environmental sensing, including systems for quality of life information services.


Sensor data ontology knowledge representation residential building monitoring 


  1. 1.
    Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Patel-Schneider, P.: The Description Logic Handbook: Theory, Implementation and Applications, 2nd edn. Cambridge University Press (2007)Google Scholar
  2. 2.
    Barnaghi, P., Meissner, S., Presser, M., Moessner, K.: Sense and Sens’ability: Semantic Data Modelling for Sensor Networks. In: Proceedings of the ICT Mobile Summit 2009 (2009)Google Scholar
  3. 3.
    Berners-Lee, T.: Linked Data–Design Issues (2006),
  4. 4.
    Bizer, C., Auer, S., Kobilarov, G., Lehmann, J., Cyganiak, R.: DBpedia–Querying Wikipedia like a database. In: Developers Track Presentation at the 16th International Conference on World Wide Web, WWW, pp. 8–12 (2007)Google Scholar
  5. 5.
    Compton, M.: What Now and Where Next for the W3C Semantic Sensor Networks Incubator Group Sensor Ontology. In: Proceedings of the 4th International Workshop on Semantic Sensor Networks 2011 (SSN 2011), pp. 1–8. CEUR-WS (2011)Google Scholar
  6. 6.
    Compton, M., Henson, C., Neuhaus, H., Lefort, L., Sheth, A.: A Survey of the Semantic Specification of Sensors. In: 2nd International Workshop on Semantic Sensor Networks, at 8th International Semantic Web Conference (2009)Google Scholar
  7. 7.
    Conroy, K., May, G., Roantree, M., Warrington, G., Cullen, S.J., McGoldrick, A.: Knowledge Acquisition from Sensor Data in an Equine Environment. In: Cuzzocrea, A., Dayal, U. (eds.) DaWaK 2011. LNCS, vol. 6862, pp. 432–444. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  8. 8.
    Conroy, K., May, G., Roantree, M., Warrington, G.: Expanding Sensor Networks to Automate Knowledge Acquisition. In: Fernandes, A.A.A., Gray, A.J.G., Belhajjame, K. (eds.) BNCOD 2011. LNCS, vol. 7051, pp. 97–107. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  9. 9.
    Gaglio, S., Gatani, L., Lo Re, G., Ortolani, M.: Understanding the Environment Through Wireless Sensor Networks. In: Basili, R., Pazienza, M.T. (eds.) AI*IA 2007. LNCS (LNAI), vol. 4733, pp. 72–83. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  10. 10.
    Henson, C.A., Pschorr, J.K., Sheth, A.P., Thirunarayan, K.: SemSOS: Semantic Sensor Observation Service. In: Proceedings of the 2009 International Symposium on Collaborative Technologies and Systems (CTS 2009), Baltimore, MD (May 2009)Google Scholar
  11. 11.
    Liu, J., Zhao, F.: Towards semantic services for sensor-rich information systems. In: 2nd International Conference on Broadband Networks, BroadNets 2005, vol. 2, pp. 967–974 (October 2005)Google Scholar
  12. 12.
    Manola, F., Miller, E.: RDF Primer. Tech. Rep. W3C Recommendation, W3C (2004)Google Scholar
  13. 13.
    Prud’hommeaux, E., Seaborne, A.: SPARQL Query Language for RDF. Tech. Rep. W3C Recommendation, W3C (2008)Google Scholar
  14. 14.
    Sheth, A., Henson, C., Sahoo, S.: Semantic Sensor Web. IEEE Internet Computing 12(4), 78–83 (2008)CrossRefGoogle Scholar
  15. 15.
    Simmhan, Y., Aman, S., Cao, B., Giakkoupis, M., Kumbhare, A., Zhou, Q., Paul, D., Fern, C., Sharma, A., Prasanna, V.: An Informatics Approach to Demand Response Optimization in Smart Grids. Tech. Rep., University of Southern California (2011)Google Scholar
  16. 16.
    Stocker, M., Rönkkö, M., Kolehmainen, M.: Making sense of sensor data using ontology: A discussion for road vehicle classification. In: 2012 International Congress on Environmental Modelling and Software. International Environmental Modelling and Software Society, iEMSs (2012)Google Scholar
  17. 17.
    Stocker, M., Rönkkö, M., Villa, F., Kolehmainen, M.: The Relevance of Measurement Data in Environmental Ontology Learning. In: Hřebíček, J., Schimak, G., Denzer, R. (eds.) ISESS 2011. IFIP AICT, vol. 359, pp. 445–453. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  18. 18.
    W3C OWL Working Group: OWL 2 Web Ontology Language. Tech. Rep. W3C Recommendation, W3C (2009)Google Scholar
  19. 19.
    W3C Semantic Sensor Network Incubator Group: Semantic Sensor Network Ontology. Tech. Rep., W3C (2009)Google Scholar
  20. 20.
    Wanner, L., Vrochidis, S., Tonelli, S., Moßgraber, J., Bosch, H., Karppinen, A., Myllynen, M., Rospocher, M., Bouayad-Agha, N., Bügel, U., Casamayor, G., Ertl, T., Kompatsiaris, I., Koskentalo, T., Mille, S., Moumtzidou, A., Pianta, E., Saggion, H., Serafini, L., Tarvainen, V.: Building an Environmental Information System for Personalized Content Delivery. In: Hřebíček, J., Schimak, G., Denzer, R. (eds.) ISESS 2011. IFIP AICT, vol. 359, pp. 169–176. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  21. 21.
    Wei, W., Barnaghi, P.: Semantic Annotation and Reasoning for Sensor Data. In: Barnaghi, P., Moessner, K., Presser, M., Meissner, S. (eds.) EuroSSC 2009. LNCS, vol. 5741, pp. 66–76. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  22. 22.
    Whitehouse, K., Zhao, F., Liu, J.: Semantic Streams: A Framework for Composable Semantic Interpretation of Sensor Data. In: Römer, K., Karl, H., Mattern, F. (eds.) EWSN 2006. LNCS, vol. 3868, pp. 5–20. Springer, Heidelberg (2006)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2012

Authors and Affiliations

  1. 1.University of Eastern FinlandKuopioFinland

Personalised recommendations