A Systematic Review of the Applications of AI in a Sustainable Building's Lifecycle

被引：14
作者：
Adewale, Bukola Adejoke [1 ,2 ,3 ]
Ene, Vincent Onyedikachi [1 ]
Ogunbayo, Babatunde Fatai [2 ,3 ]
Aigbavboa, Clinton Ohis [2 ,3 ]
机构：
[1] Covenant Univ, Coll Sci & Technol, Dept Architecture, Ota 112104, Ogun State, Nigeria
[2] Univ Johannesburg, Cidb Ctr Excellence & Sustainable Human Settlement, ZA-2006 Johannesburg, South Africa
[3] Univ Johannesburg, Fac Engn & Built Environm, Construct Res Ctr, ZA-2006 Johannesburg, South Africa
来源：
BUILDINGS | 2024年 / 14卷 / 07期
关键词：
artificial intelligence; sustainability; building lifecycle; design optimization; digital twins; Internet of Things; CONSTRUCTION-INDUSTRY; ARTIFICIAL-INTELLIGENCE; TECHNOLOGIES; OPTIMIZATION; CONSUMPTION; SIMULATION;
D O I：
10.3390/buildings14072137
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
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.
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页数：28
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