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Analytics for Smarter Buildings

Analytics for Smarter Buildings

Young M. Lee, Lianjun An, Fei Liu, Raya Horesh, Young Tae Chae, Rui Zhang
Copyright: © 2014 |Volume: 1 |Issue: 1 |Pages: 15
ISSN: 2334-4547|EISSN: 2334-4555|EISBN13: 9781466661868|DOI: 10.4018/ijban.2014010101
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MLA

Lee, Young M., et al. "Analytics for Smarter Buildings." IJBAN vol.1, no.1 2014: pp.1-15. http://doi.org/10.4018/ijban.2014010101

APA

Lee, Y. M., An, L., Liu, F., Horesh, R., Chae, Y. T., & Zhang, R. (2014). Analytics for Smarter Buildings. International Journal of Business Analytics (IJBAN), 1(1), 1-15. http://doi.org/10.4018/ijban.2014010101

Chicago

Lee, Young M., et al. "Analytics for Smarter Buildings," International Journal of Business Analytics (IJBAN) 1, no.1: 1-15. http://doi.org/10.4018/ijban.2014010101

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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.

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