Estimating residential building energy consumption using overhead imagery

Artem Streltsov, Jordan M. Malof, Bohao Huang and Kyle Bradbury

Applied Energy, 2020, vol. 280, issue C, No S0306261920314616

Abstract: Residential buildings account for a large proportion of global energy consumption in both low- and high- income countries. Efficient planning to meet building energy needs while increasing operational, economic, and environmental efficiency requires accurate, high spatial resolution information on energy consumption. Such information is difficult to acquire and most models for estimating residential building energy consumption require detailed knowledge of individual homes and communities which are unlikely to be available at a large scale.

Keywords: Buildings; Energy demand; Energy consumption; Convolutional neural network; Random forest (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (20)

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DOI: 10.1016/j.apenergy.2020.116018

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