Abstract
Modern scientific applications of sensor networks are driving the development of technologies to make heterogeneous sensor networks easier to deploy, program and use in multiple application contexts. One key requirement, addressed by this work, is the need for methods to detect events in real time that arise from complex correlations of measurements made by independent sensing devices. Because the mapping of such complex events to direct sensor measurements may be poorly understood, such methods must support experimental and frequent specification of the events of interest. This means that the event specification method must be embedded in the problem domain of the end-user, must support the user to discover observable properties of interest, and must provide automatic and efficient enaction of the specification.
This paper proposes the use of ontologies to specify and recognise complex events that arise as selections and correlations (including temporal correlations) of structured digital messages, typically streamed from multiple sensor networks. Ontologies are used as a basis for the definition of contextualised complex events of interest which are translated to selections and temporal combinations of streamed messages. Supported by description logic reasoning, the event descriptions are translated to the native language of a commercial Complex Event Processor (CEP), and executed under the control of the CEP.
The software is currently deployed for micro-climate monitoring of experimental food crop plants, where precise knowledge and control of growing conditions is needed to map phenotypical traits to the plant genome.
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Abadi, D.J., Carney, D., Cetintemel, U., Cherniack, M., Convey, C., Lee, S., Stonebraker, M., Tatbul, N., Zdonik, S.B.: Aurora: a new model and architecture for data stream management. VLDB Journal 12(2), 120–139 (2003)
Arasu, A., Babu, S., Widom, J.: The CQL continuous query language: Semantic foundations and query execution. Very Large Database (VLDB) Journal 14 (2005)
Calbimonte, J.-P., Corcho, O., Gray, A.J.G.: Enabling ontology-based access to streaming data sources. In: Patel-Schneider, P.F., Pan, Y., Hitzler, P., Mika, P., Zhang, L., Pan, J.Z., Horrocks, I., Glimm, B. (eds.) ISWC 2010, Part I. LNCS, vol. 6496, pp. 96–111. Springer, Heidelberg (2010)
Esper–Complex Event Processing. Espertech event stream intelligence (December 2010), http://esper.codehaus.org/
Hinze, A., Sachs, K., Buchmann, A.: Event-based applications and enabling technologies. In: DEBS 2009: Proceedings of the Third ACM International Conference on Distributed Event-Based Systems, pp. 1–15. ACM, New York (2009)
Le-Phuoc, D., Hauswirth, M.: Linked open data in sensor data mashups. In: Taylor, K., Ayyagari, A., De Roure, D. (eds.) Proceedings of the 2nd International Workshop on Semantic Sensor Networks, SSN 2009, Washington DC, USA, October 2009, vol. 522, pp. 1–16 (2009) CEUR workshop proceedings
Li, L., Taylor, k.: Generating an efficient sensor network program by partial deduction. In: Zhang, B.-T., Orgun, M.A. (eds.) PRICAI 2010. LNCS, vol. 6230, pp. 134–145. Springer, Heidelberg (2010)
Li, L., Taylor, K.: A framework for semantic sensor network services. In: Bouguettaya, A., Krueger, I., Margaria, T. (eds.) ICSOC 2008. LNCS, vol. 5364, pp. 347–361. Springer, Heidelberg (2008)
Liu, Y., Vijayakumar, N., Plale, B.: Stream processing in data-driven computational science. In: Proc. 7th IEEE/ACM International Conference on Grid Computing, GRID 2006, pp. 160–167. IEEE, Washington, DC, USA (2006)
Madden, S.R., Franklin, M.J., Hellerstein, J.M., Hong, W.: TinyDB: an acquisitional query processing system for sensor networks. ACM Trans. Database Syst. 30, 122–173 (2005)
Sirin, E., Parsia, B., Hendler, J.: Filtering and selecting semantic web services with interactive composition techniques. IEEE Intelligent Systems 19, 42–49 (2004)
Taylor, K., Penkala, P.: Using explicit semantic representations for user programming of sensor devices. In: Advances in Ontologies: Proceedings of the Australasian Ontology Workshop Conferences in Research and Practice in Information Technology, Melbourne, Australia, December 1. CRPIT, vol. 112, Australasian Computer Society (2009)
W3C SSN-XG members. SSN: Semantic sensor network ontology (December 2010), http://purl.oclc.org/NET/ssnx/ssn
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Taylor, K., Leidinger, L. (2011). Ontology-Driven Complex Event Processing in Heterogeneous Sensor Networks. In: Antoniou, G., et al. The Semanic Web: Research and Applications. ESWC 2011. Lecture Notes in Computer Science, vol 6644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21064-8_20
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DOI: https://doi.org/10.1007/978-3-642-21064-8_20
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