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

Bukola Adejoke Adewale, Vincent Onyedikachi Ene, B. Ogunbayo, C. Aigbavboa
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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.
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人工智能在可持续建筑生命周期中的应用系统回顾
建筑是全球能源消耗和温室气体排放的主要来源。本系统性文献综述探讨了人工智能(AI)在整个建筑生命周期内提高可持续性的潜力。该综述确定了适用于可持续建筑实践的人工智能技术,研究了这些技术的影响,并分析了实施方面的挑战。研究结果揭示了人工智能在优化能源效率、实现预测性维护和协助设计模拟方面的能力。先进的机器学习算法促进了数据驱动分析,而数字双胞胎则为决策提供了实时见解。审查还指出了采用人工智能的障碍,包括成本问题、数据安全风险和实施挑战。虽然人工智能为能源优化和环保实践提供了创新解决方案,但要将其成功融入可持续建筑实践,解决技术和实际挑战至关重要。
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