NDLI: Building energy management and data analytics

Content Provider	IEEE Xplore Digital Library
Author	Zucker, G. Habib, U. Blochle, M. Wendt, A. Schaat, S. Siafara, L.C.
Copyright Year	2015
Description	Author affiliation: Inst. of Comput. Technol., Vienna Univ. of Technol., Vienna, Austria (Wendt, A.; Schaat, S.; Siafara, L.C.) \|\| Energy Dept., AIT Austrian Inst. of Technol., Vienna, Austria (Zucker, G.; Habib, U.; Blochle, M.)
Abstract	Energy efficiency in buildings depends on the way the building is operated. Therefore energy management is the key component for efficient operation. Data analysis of operation data helps to better understand the systems and detect faults and inefficiencies. The facility manager benefits from smart analysis that makes use of machine learning algorithms and innovative visualizations. This analysis is part of a bigger review of the current structure of building automation as it is used in today's buildings. The operation targets in energy efficiency are complex, ambiguous and contradictory: indoor comfort, energy efficiency, high availability and low costs cannot be met at the same time. In order to improve building operation, a novel model of automation is discussed. The foundation of this model is in cognitive automation, since each building is unique in its selection of energy sources, architecture, usage and location, which implies that the building's control system has to be adapted individually. This paper connects the data-driven analysis of operation data with a cognitive concept to be used for operating the energy systems in a building and regarding goals on how to optimally operate while considering constraints about the limits of operation, using the complex, dynamic data from building automation.
Starting Page	462
Ending Page	467
File Size	282846
Page Count	6
File Format	PDF
e-ISBN	9781479977369
DOI	10.1109/SEDST.2015.7315253
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-08
Publisher Place	Austria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data analysis Architecture Bionics Energy-efficient systems Control systems Energy efficiency Data analytics Data mining Cognitive systems Artificial intelligence Building automation
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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