Abstract
Globalization and contemporary development have threatened indigenous sustainable construction techniques, which were naturally environmentally friendly and material conserving. The building sector has adopted modern construction techniques that are ecologically harmful, and there is a need to rediscover conventional construction techniques that are sustainable. This study discusses how Artificial Intelligence (AI) can learn, record, and improve indigenous construction techniq Add Contributor ues to meet contemporary architecture standards. With the unification of human hand labor and AI-driven techniques like computer vision and machine learning, modern studies integrate new technology and traditional craftsmanship. Using sprint ethnographic methods in conjunction with AI-computation locates and measures local practices in intimate detail with high-tech photography, material sensing for analysis, and mechanical recording sensors of textual and intangible knowledge. This advanced AI algorithm employs structural predictions, optimizes the design, inputs constraint, and provides customized solutions. Case studies demonstrate the potential of AI in reviving ancient construction using the integration of sustainable practices in contemporary architecture. AI simulations maximize local material mixtures, unveil concealed structure patterns, and maximize thermal performance—such as earth architecture enhanced by the algorithmic selection of materials. The study raises ethical concerns, including cultural appropriation and AI copyright, and demands responsible AI deployment. Rather than replacing traditional practices, AI can assist in their preservation and transformation. This study invites AI experts, designers, and policymakers to adopt AI as a tool to preserve traditional knowledge. It demands an open-source approach to AI-based construction, where new technologies archive and refresh previous practices into new, sustainable design solutions.

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