Ward, W.O.C. orcid.org/0000-0002-4904-7294, Li, X., Sun, Y. et al. (4 more authors) (2023) Estimating energy consumption of residential buildings at scale with drive-by image capture. Building and Environment, 234. 110188. ISSN 0360-1323
Abstract
Data-driven approaches to addressing climate change are increasingly becoming a necessary solution to deal with the scope and scale of interventions required to reach net zero. In the UK, housing contributes to over 30% of the national energy consumption, and a massive rollout of retrofit is needed to meet government targets for net zero by 2050. This paper introduces a modular framework for quantifying building features using drive-by image capture and utilising them to estimate energy consumption. The framework is demonstrated on a case study of houses in a UK neighbourhood, showing that it can perform comparatively with gold standard datasets. The paper reflects on the modularity of the proposed framework, potential extensions and applications, and highlights the need for robust data collection in the pursuit of efficient, large-scale interventions.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Building energy modelling; Residential buildings; Mobile sensing; Data-driven methods; Retrofit; Artificial Intelligence |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Funding Information: | Funder Grant number Department for Business, Energy and Industrial Strategy EP/V012053/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 16 Aug 2024 11:35 |
Last Modified: | 16 Aug 2024 11:35 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.buildenv.2023.110188 |
Related URLs: | |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:216186 |