reviewEnergy and AIAug 8, 2022GOLD OA

Machine Learning and Deep Learning Methods for Enhancing Building Energy Efficiency and Indoor Environmental Quality – A Review

University of Nottingham

Indexed incrossrefdoaj

Abstract

The built environment sector is responsible for almost one-third of the world's final energy consumption. Hence, seeking plausible solutions to minimise building energy demands and mitigate adverse environmental impacts is necessary. Artificial intelligence (AI) techniques such as machine and deep learning have been increasingly and successfully applied to develop solutions for the built environment. This review provided a critical summary of the existing literature on the machine and deep learning methods for the built environment over the past decade, with special reference to holistic approaches. Different AI-based techniques employed to resolve interconnected problems related to heating, ventilation and…

Citation impact

264
total citations
FWCI
24.83
Percentile
100%
References
164
Citations per year

Authors

5

Topics & keywords

Keywords
  • HVAC
  • Artificial intelligence
  • Computer science
  • Machine learning
  • Deep learning
  • Energy consumption
  • Thermal comfort
  • Quality (philosophy)
UN Sustainable Development Goals
  • Affordable and clean energy
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Funding