A Systematic Review of the Applications of AI in a Sustainable Building’s Lifecycle
Систематический обзор применения искусственного интеллекта на протяжении жизненного цикла устойчивого здания
2024-07-11
SCID: 54.1/r6ackjgr
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artificial intelligencedigital twinsenergy efficiency optimizationpredictive maintenancesustainable building lifecycle
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Abstract (AI)
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.
Key Findings
1
AI can enhance sustainability across a building’s lifecycle, particularly through energy-efficiency optimization, predictive maintenance, and design simulation.
2
Advanced machine-learning algorithms support data-driven analysis for sustainable building practices.
3
Digital twins provide real-time insights that can improve decision-making throughout building lifecycle management.
4
Major barriers to AI adoption include implementation difficulties, high costs, and data-security risks.
5
Successful integration of AI into sustainable buildings requires addressing both technical and practical challenges.
Research Object
sustainable buildings throughout their lifecycle
Research Subject
applications of artificial intelligence for energy optimization, predictive maintenance, design simulation, and sustainable decision-making, including adoption barriers
Publication Details
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2024-07-11
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References available in scid.ai5
Exploring the impact of artificial intelligence on teaching and learning in higher education2017
Towards a semantic Construction Digital Twin: Directions for future research2020
Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges2021
Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications2022
Integration of IoT-Enabled Technologies and Artificial Intelligence (AI) for Smart City Scenario: Recent Advancements and Future Trends2023