This research examines the contributions that artificial intelligence (AI) can make to green building certification systems, with a particular focus on the evaluation and optimization of indoor environmental quality (IEQ) criteria within the Leadership in Energy and Environmental Design (LEED) framework. The study investigates the role of AI in the classification and analysis of core IEQ components, including indoor air quality, lighting efficiency, sustainable material selection, acoustic performance, and ergonomic design. The research adopts a hybrid methodological approach that combines qualitative content analysis of existing LEED-certified projects with a conceptual simulation model based on AI-supported decision-making algorithms. This model demonstrates how AI capabilities—such as real-time data processing, pattern recognition, and predictive analysis—can be integrated into the certification process. Data sources include LEED v4 documentation, AI-based environmental simulation software, and expert interviews with sustainability consultants and architects. The findings indicate that the integration of artificial intelligence can significantly enhance efficiency, objectivity, and accuracy in the assessment of IEQ criteria. AI-driven systems are shown to identify optimization opportunities within complex trade-offs between energy consumption and occupant comfort that are often overlooked by traditional manual evaluation methods. Furthermore, the study highlights AI’s potential to reduce subjective interpretations and to accelerate the overall certification process. This research contributes to the literature on AI-supported sustainable design by proposing a concrete methodological framework and demonstrating the transformative role of artificial intelligence in ecological interior architecture. The results suggest that AI-based evaluation frameworks have strong potential for standardization across green building certification systems worldwide, extending beyond LEED-specific applications.
]]>Attaianese, E., & Duca, G. (2012). Ergonomics and workplace design for user comfort. Journal of Environmental Design, 6(2), 45–58.
Arslan, N. C. (2015). LEED certification categories and evaluation criteria. International Journal of Sustainable Architecture, 10(3), 112–125.
Bajwa, S., Khan, M., & Ahmed, R. (2022). Optimization of indoor environments with smart building systems using artificial intelligence. Sustainable Built Environment Journal, 8(4), 77–92.
Bayrak, E. (2022). Applications of artificial intelligence in urban infrastructure management. Journal of Smart Cities, 5(1), 33–48.
Bluyssen, P. M. (2013). The indoor environment handbook: How to make buildings healthy and comfortable. Earthscan.
Celik, K. (2009). Sustainable buildings and indoor environmental quality. Building and Environment, 44(5), 1016–1023.
Celik, K. (2016). Comparative analysis of global green building certification systems. Journal of Green Architecture, 11(2), 34–49.
Doğan, M., Akten, M., & Selection, D. (2018). Green building evaluation systems and their effectiveness. Environmental Research and Design, 7(3), 56–70.
Ece, P. (2022). Text-to-image artificial intelligence: Current trends and applications. Journal of Artificial Creativity, 4(2), 15–28.
Ertuğrul, H., & Altın, S. (2022). LEED ID+C category and sustainable interior design. Sustainability in Architecture Journal, 9(1), 42–60.
Görgün, H. (2012). The global spread and impact of LEED certification. International Journal of Sustainable Development, 5(4), 88–102.
Liu, W., Chen, R., & Zhao, H. (2019). Sustainable material selection in interior design. Journal of Environmental Engineering, 12(3), 101–114.
Öktem, A. K. (2020). Indoor environmental quality and human health in green buildings. Springer.
OpenAI. (2025). ChatGPT: Optimizing language models for dialogue [Software].
https://openai.com/chatgpt
Reinhart, C. (2019). Daylighting handbook for sustainable building design. Routledge.
Reviriego, P., & Merino-Gómez, M. (2022). Text-to-image artificial intelligence systems: Principles and applications. Artificial Intelligence Review, 55(6), 4237–4261.
U.S. Green Building Council. (2021). LEED v4 rating system guidelines.
https://www.usgbc.org/leed
Yıldız, H. (2019). Human–environment interaction in sustainable architecture. Journal of Environmental Studies, 11(2), 15–27.
Zhang, L., Wang, Q., & Liu, S. (2023). Artificial intelligence applications in energy modeling for architecture. Sustainable Computing Journal, 7(1), 66–79.
Zhang, L., Wang, Q., Liu, S., & Chen, R. (2024). AI-based approaches for structural optimization in architecture. Journal of Computational Design, 9(2), 45–62.
Leonardo AI. (2025). Leonardo AI platform for text-to-image generation [Software].
https://www.leonardo.ai
Stability AI. (2024). Stable Diffusion: Open-source artificial intelligence for image generation [Software].
https://stability.ai