Mario J. Kofler
Vienna University of Technology, Automation Systems Group, Vienna, Austria
Christian Reinisch
Vienna University of Technology, Automation Systems Group, Vienna, Austria
Wolfgang Kastner
Vienna University of Technology, Automation Systems Group, Vienna, Austria
Ladda ner artikel
http://dx.doi.org/10.3384/ecp11057921Ingår i: World Renewable Energy Congress - Sweden; 8-13 May; 2011; Linköping; Sweden
Linköping Electronic Conference Proceedings 57:23, s. 921-928
Publicerad: 2011-11-03
ISBN: 978-91-7393-070-3
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
Homes in today’s world tend to include more and more electrically powered devices. Much effort is put on improving these facilities; but their integration towards a smart home often remains unconsidered. While there are some promising approaches to integrate devices with the help of knowledge bases; they are still not fully convincing. In all cases they fail to cover the energy behavior of installed devices which is a severe shortcoming with respect to the increasing energy demand of a home. As most residents are still unaware where the energy is consumed and which actions eventually lead to a lower demand; an energy related knowledge representation is of importance. This paper proposes such an energy knowledge base modeled as ontology. This artifact comprises a comprehensive collection of miscellaneous energy related information and allows home automation systems to make intelligent decisions upon this knowledge. Using the ontology; energy consumption in the home itself can now be optimized by executing intelligent control strategies that incorporate and exploit the additional knowledge in their algorithms. Likewise; also renewable energy suppliers are represented and may be considered by a smart home system in order to reduce the overall ecological footprint of the residents and provide additional services for home control.
[1] P. Jazayeri; A. Schellenberg; W.D. Rosenhart; J. Doudna; S. Widergren D. Lawrence; J. Mickey; S. Jones; A Survey of Load Control Programs for Price and System Stability; IEEE Transactions on Power Systems; Vol. 20; No. 3; 2005; pp 1504 – 1509.
doi: 10.1109/TPWRS.2005.852147.
[2] W. Kastner; G. Neugschwandtner; S. Soucek; H. M. Newman; Communication Systems for Building Automation and Control; Proc. of the IEEE 93(6); 2005; pp 1178 – 1203.
doi: 10.1109/JPROC.2005.849726.
[3] W3C Recommendation; OWL 2 Web Ontology Language Document Overview; http://www.w3.org/TR/owl2-overview/; 2009; (online).
[4] F. Baader; D. Calvanese; D. L. McGuinness; D. Nardi; and P. F. Patel-Schneider (Eds.); The Description Logic Handbook: Theory; Implementation; and Applications; Cambridge University Press; 2003.
[5] L. Sommaruga; A. Perri; F. Furfari; DomoML-env: An ontology for Human Home Interaction; Proc. of the 2nd Italian Semantic Web Workshop; 2005.
[6] D. Bonino; F. Corno; DogOnt – Ontology Modeling for Intelligent Domotic Environments; Proc. of the 7th International Conference on The Semantic Web; 2008.
[7] E. Paslaru Bontas; M. Mochol; R. Tolksdorf; Case Studies on Ontology Reuse; Proc. of the 5th International Conference on Knowledge Management ; 2005.
[8] M. J. Kofler; W. Kastner; A Knowledge Base for Energy-Efficient Smart Homes; Proc. of the International Energy Conference ENERGYCON; 2010.
[9] A. L. Rector; Modularisation of Domain Ontologies Implemented in Description Logics and related formalisms including OWL. Proc. of the International Conference on Knowledge Capture; 2003; pp. 121-128.
doi: 10.1145/945645.945664.
[10] E. Sirin; B. Parsia; B. Cuenca Grau; A. Kalyanpur; Y. Katz; Pellet: A practical OWL-DL reasoner; Journal of Web Semantics; Volume 5; Issue 2; 2007; pp 51 – 53.
doi: 10.1016/j.websem.2007.03.004.
[11] F. Pan; A Temporal Aggregates Ontology in OWL for the Semantic Web; Proc. of the AAAI Fall Symposium on Agents and the Semantic Web; 2005.
[12] D. Allemang; J. Hendler; Semantic Web for the Working Ontologist; Morgan Kaufmann Publishing/Elsevier; 2008; pp. 251 – 253.
