Analyzing Makkah’s architectural vocabularies (MAV): a method for building a digital library for machine learning applications
This paper provides a comprehensive analysis of Makkah’s architectural vocabulary by examining the characteristics and design principles that shape the composition of its heritage buildings. It focuses on defining Makkah’s architectural compositions concerning design principles such as retheme, unity, emphasis, balance, contrast, transformation, and repetition within selected heritage buildings. The analysis highlights that the most emphasized design principles for the entrance include emphasis, balance, contrast, and transformation, while for the shoback, unity, balance, and reflection are predominant. The Roushan predominantly features unity, emphasis, and contrast, and the Shawabirs focus on harmony and balance. This study also addresses the application of these findings in creating a digital repository, which serves as a basis for machine learning applications to regenerate Makkah’s architectural vocabulary (MAV). This paper establishes a referential digital repository that underpins machine learning applications and the future regeneration of Makkah’s architectural vocabulary. Previous studies on Makkah’s architecture often focused on individual elements without considering how they collectively contribute to the city’s unique architectural style, limiting their usefulness for further development. By investigating Makkah’s architectural vocabulary as an integrated whole, this paper elucidates how various elements come together to form its distinctive aesthetic.
Authors
- Saeed Ali Alburgawi (ORCID: https://orcid.org/0000-0002-4244-2902)
- Wadia Albarqawi (ORCID: https://orcid.org/0000-0002-4021-2556)
Institutions
- Umm al-Qura University (SA)
Publication Details
- Journal
- Journal of Asian Architecture and Building Engineering
- Published
- 2024-12-24
- DOI
- https://doi.org/10.1080/13467581.2024.2431309
- Citations
- 1
- Primary Topic
- Architecture and Cultural Influences
- Type
- article
- Field-Weighted Citation Impact
- 2.92