Generative AI Applications in Sustainable and Resilient Architecture Design in the Face of Climate Change

The architecture, engineering, and construction (AEC) industry is increasingly leveraging generative artificial intelligence (AI) to automate design processes, enhance creativity, and optimize resource utilization. As climate change resilience becomes a critical priority, AI-driven generative models offer innovative solutions to improve energy efficiency, minimize material waste, and support climate-responsive architecture. This review examines the role of generative AI in sustainable architecture, focusing on its applications in energy-efficient building design, material optimization, and renewable energy integration. Using machine learning algorithms and computational design tools, AI enables architects and engineers to explore diverse design possibilities while considering sustainability. This study follows a systematic literature review approach, analyzing recent research articles, case studies, and industry reports related to generative AI in sustainable architecture. The study highlights AI's contributions to passive design strategies, natural lighting and ventilation optimization, and the use of low-carbon materials. Advanced simulations facilitate solar radiation, wind flow, and thermal behavior optimization, leading to resilient urban planning and adaptive structures. Despite its potential, challenges such as ethical concerns, data privacy, algorithmic bias, and workforce skill gaps hinder AI's broader implementation. Additionally, AI's high computational demands necessitate energy-efficient training strategies. Through an analysis of current research, case studies, and emerging trends, this review underscores AI's transformative impact on sustainable architecture and its role in fostering climate change resilience.

کلیدواژه ها:

Generative AI ، Sustainable Architecture Design ، Resilient Architecture Design ، Climate Change ، Energy Efficiency