Yoruba Architectural Design Generative System: A Machine Learning Approach Using Shape Grammar and Teachable Machine Models
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Keywords:
Yoruba Architectural Design, Generative System, Machine Learning, Shape Grammar, Teachable MachineAbstract
This study presents an architectural language for Yoruba-Agboile (courtyard type) traditional
architecture, addressing the need for a comprehensive understanding of its plan layouts within physical and
socio-cultural contexts. The aim is to define and categorize architectural elements using an analytical shape
grammar approach, drawing from the recent compilations. Utilizing a mixed-methods strategy, the research
involved field surveys, archival research, shape grammar and machine learning techniques, specifically a
shapegraphic AI model, to analyze existing designs.
Key findings indicate that Yoruba-Agboile architecture features a distinct courtyard organization,
enhancing social interaction and cultural practices. The model successfully classified various plan types,
highlighting a coherent vocabulary of architectural elements such as the hypo-courtyard (Agbala) and
corridor (C). The study concludes that traditional Yoruba-Agboile architecture can inform contemporary
designs while maintaining cultural significance.
Recommendations include further research into the spatial structures of Yoruba architecture and the
application of generative shape grammar systems to foster deeper academic and practical insights into this
architectural heritage. This approach could bridge traditional design principles with modern architectural
practices, enhancing the appreciation and preservation of Yoruba cultural identity in contemporary
contexts.
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