| Abstract [eng] |
This paper presents an overview of how Artificial Intelligence (AI) supports the sustainability assessment of buildings, structured around the main phases of the building lifecycle. The review focuses on four core stages: design and planning, operation and monitoring, assessment and optimization, and compliance and certification support. Within this structure, the study highlights the growing role of AI in enhancing decision-making, improving building performance, and supporting sustainable outcomes across each phase. AI tools are categorized into four main groups: general-purpose platforms, data analytics environments, building-specific tools, and specialized applications. These are then mapped to key application domains such as prediction, simulation, decision support, and system optimization. The study emphasizes the connection between AI functionalities and specific needs in building sustainability, offering a structured approach for understanding the current landscape of tools and methods. By combining a lifecycle-based perspective with a classification of AI technologies and use cases, the paper aims to support researchers and practitioners in navigating the evolving intersection of AI and sustainable built environments. The findings serve as a foundation for further research and tool development, fostering more effective integration of AI in future sustainability assessments. |
