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

Title data

Fridgen, Gilbert ; Guggenmos, Florian ; Regal, Christian ; Schmidt, Marco:
Big Data beats engineering in residential energy performance assessment : a case study.
2017
Event: DACH+ Energieinformatik 2017 , 5.-6.10.2017 , Lugano, Switzerland.
(Conference item: Conference , Poster )
DOI: https://doi.org/10.1007/s00450-017-0365-4

Official URL: Volltext

Project information

Project title:
Project's official titleProject's id
BigDapesiNo information

Abstract in another language

Engineering-based energy performance assessments,
e.g., required for the award of energy certificates,
evoke significant effort and lack accuracy. This paper introducesthe idea of building energy performance assessment onBig 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.

Further data

Item Type: Conference item (Poster)
Refereed: Yes
Keywords: Energy-efficiency; Big Data Analytics; Energy prediction; Residential building
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Professorship Business Informations Systems and sustainable IT management
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Professorship Business Informations Systems and sustainable IT management > Professorship Business Informations Systems and sustainable IT management- Univ.-Prof. Dr. Gilbert Fridgen
Profile Fields > Emerging Fields > Energy Research and Energy Technology
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering
Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Faculties
Faculties > Faculty of Law, Business and Economics
Profile Fields
Profile Fields > Emerging Fields
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 28 Sep 2017 08:15
Last Modified: 28 Sep 2017 08:15
URI: https://eref.uni-bayreuth.de/id/eprint/39761