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

dc.contributor.authorAdewale, Bukola
dc.contributor.authorEne, Vincent Onyedikach
dc.contributor.authorOgunbayo, Babatunde Fatal
dc.contributor.authorAigbavboa, Clinton Ohis
dc.date.accessioned2026-06-22T19:44:25Z
dc.date.issued2024
dc.description.abstractBuildings significantly contribute to global energy consumption and greenhouse gas emis sions. 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 anal ysis, 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.
dc.identifier.otherhttps://doi.org/10.3390/buildings14072137
dc.identifier.urihttps://repository.covenantuniversity.edu.ng/handle/123456789/51028
dc.language.isoen
dc.publisherBuildings
dc.subjectartificial intelligence
dc.subjectsustainability
dc.subjectbuilding lifecycle
dc.subjectdesign optimization
dc.subjectdigital twins
dc.subjectInternet of Things
dc.titleA Systematic Review of the Applications of AI in a Sustainable Building’s Lifecycle
dc.typeArticle

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