Abstract
The EMA (Energy Management Adviser) aims to produce personalised energy saving advice for EDF's customers. The advice takes the form of one or more 'tips', and personalisation is achieved using semantic technologies: customers are described using RDF, an OWL ontology provides a conceptual model of the relevant domain (housing, environment, and so on) and the different kinds of tips, and SPARQL query answering is used to identify relevant tips. The current prototype provides tips to more than 300,000 EDF customers in France at least twice a year. The main challenges for our future work include providing a timely service for all of the 35 million EDF customers in France, simplifying the system's maintenance, and providing new ways for interacting with customers such as via a Web site. © 2013 Springer-Verlag.
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CITATION STYLE
Chaussecourte, P., Glimm, B., Horrocks, I., Motik, B., & Pierre, L. (2013). The energy management adviser at EDF. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8219 LNCS, pp. 49–64). https://doi.org/10.1007/978-3-642-41338-4_4
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