Reference : Big Data beats engineering in residential energy performance assessment : a case study
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Business & economic sciences : Multidisciplinary, general & others
Security, Reliability and Trust; Sustainable Development
http://hdl.handle.net/10993/51164
Big Data beats engineering in residential energy performance assessment : a case study
English
Fridgen, Gilbert mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) >]
Guggenmos, Florian [> >]
Regal, Christian [> >]
Schmidt, Marco [> >]
2017
DACH + Energieinformatik 2017
Yes
DACH+ Energieinformatik 2017
5-10-2017 to 6-10-2017
[en] Energy-efficiency; Big Data Analytics; Energy prediction; Residential building
[en] Engineering-based energy performance assessments, e.g., required for the award of energy certificates, evoke significant effort and lack accuracy. This paper introduces the idea of building energy performance assessment on Big Data Analytics and information on buildings and occupants while respecting people’s privacy. Using a case study, we investigate whether the proposed method can outperform engineering-based methods in the field of residential buildings in terms of cost and accuracy.
http://hdl.handle.net/10993/51164
https://link.springer.com/article/10.1007/s00450-017-0365-4

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