Analytics for Smarter Buildings

Young M. Lee, Lianjun An, Fei Liu, Raya Horesh, Young Tae Chae and Rui Zhang
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Young M. Lee: IBM Thomas J. Watson Research Center, Yorktown, NY, USA
Lianjun An: IBM Thomas J. Watson Research Center, Yorktown, NY, USA
Fei Liu: IBM Thomas J. Watson Research Center, Yorktown, NY, USA
Raya Horesh: IBM Thomas J. Watson Research Center, Yorktown, NY, USA
Young Tae Chae: IBM Thomas J. Watson Research Center, Yorktown, NY, USA
Rui Zhang: IBM Thomas J. Watson Research Center, Yorktown, NY, USA

International Journal of Business Analytics (IJBAN), 2014, vol. 1, issue 1, 1-15

Abstract: Buildings consume about 40% of the total energy in most countries contributing to a significant amount of greenhouse gas (GHG) emissions and global warming. Therefore, reducing energy consumption in buildings, making buildings more energy efficient and operating buildings in more energy efficient manner are important tasks in today's world. Analytics can play an important role in identifying energy saving opportunities in buildings by modeling and analyzing how energy is consumed in buildings. In this paper, a set of analytics which can assist building owners, facility managers, operators and tenants of buildings in assessing, benchmarking, diagnosing, tracking, forecasting, simulating and optimizing energy consumption is presented.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jban00:v:1:y:2014:i:1:p:1-15

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