Computer Science - Research and Development

, Volume 33, Issue 1–2, pp 235–236 | Cite as

Poster abstract: Big Data beats engineering in residential energy performance assessment—a case study

  • Gilbert FridgenEmail author
  • Florian Guggenmos
  • Christian Regal
  • Marco Schmidt
Special Issue Paper


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.


Energy-efficiency Big Data Analytics Energy prediction Residential building 



Grateful acknowledgement is due to the Bavarian Ministry of Economic Affairs and Media, Energy and Technology for their support of the project BigDAPESI (IUK-1606-0002, IUK491/001) making this paper possible.


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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Gilbert Fridgen
    • 1
    Email author
  • Florian Guggenmos
    • 1
  • Christian Regal
    • 2
  • Marco Schmidt
    • 2
  1. 1.Project Group Business & Information Systems Engineering, Fraunhofer FITUniversity of BayreuthBayreuthGermany
  2. 2.Project Group Business & Information Systems Engineering, Fraunhofer FITUniversity of AugsburgAugsburgGermany

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