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D. Schachinger, L. Krammer:
"Building Profiling for Energy Management";
Talk: Blickpunkt Forschung: Smart Communities + Technologies @ TU Wien, Wien (invited); 2016-10-17.

The heterogeneity of building automation technologies and the amount of sensor data created are still an inhibitor for the successful deployment of home or building energy management systems. BProfEM aims at defining a generic semantic integration layer amongst the heterogeneous technologies using Semantic Web technologies in order to exploit the enriched semantics to support data mining and (privacy-aware) profiling algorithms to be used within energy management systems. The goal is to improve the local energy optimization and smart grid interaction within automated demand response programs. Real world test data samples are used to identify interesting patterns of human behavior and building energy consumption and to further create a simulation model to be used within a building simulation environment that shall evaluate the benefits of a semantic-aware energy optimization and demand response system. A feasibility study accompanied with a cost/benefit analysis will evaluate the potential of the project results.

Energy efficiency, semantic technologies, data analytics, optimization

Project Head Wolfgang Kastner:
Building Profiling for Energy Management