Abstract
Buildings significantly contribute to global energy consumption and greenhouse gas emissions. This systematic literature review explores the potential of artificial intelegence (AI) to enhance sustainability throughout a building’s lifecycle. The review identifies AI technologies applicable to sustainable building practices, examines their influence, and analyses implementation challenges. The findings reveal AI’s capabilities in optimising energy efficiency, enabling predictive maintenance, and aiding in design simulation. Advanced machine learning algorithms facilitate data-driven analysis, while digital twins provide real-time insights for decision-making. The review also identifies barriers to AI adoption, including cost concerns, data security risks, and implementation challenges. While AI offers innovative solutions for energy optimisation and environmentally conscious practices, addressing technical and practical challenges is crucial for its successful integration in sustainable building practices.
| Original language | English |
|---|---|
| Article number | 2137 |
| Journal | Buildings |
| Volume | 14 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - Jul 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 12 Responsible Consumption and Production
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SDG 13 Climate Action
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SDG 17 Partnerships for the Goals
Keywords
- Internet of Things
- artificial intelligence
- building lifecycle
- design optimization
- digital twins
- sustainability
ASJC Scopus subject areas
- Architecture
- Civil and Structural Engineering
- Building and Construction
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