The Integration of Artificial Intelligence in Architectural Surveying and Cultural Heritage: Developments, Methodologies, and Perspectives of the Digital Twin

Advancements in artificial intelligence (AI) and digital twin technology are transforming architectural surveying and heritage conservation, offering precise, predictive, and prescriptive models for preserving built heritage. This research highlights the effectiveness of Machine Learning and Deep Learning algorithms—such as PointNet++ and DGCNN—in automatically recognizing architectural elements across diverse datasets, enabling semantic segmentation of point clouds and Heritage Building Information Modeling (HBIM). Case studies, including the In-Heritage platform for microclimate monitoring in Genoa’s Palazzi dei Rolli and the Aïoli platform for Notre-Dame de Paris’s post-disaster reconstruction, demonstrate AI’s potential to enhance conservation efforts. The study also addresses ethical challenges, algorithm interpretability, and the integration of immersive technologies (VR/AR), advocating for a transparent, data-driven approach to heritage protection.

Paduano, I. (2026). The Integration of Artificial Intelligence in Architectural Surveying and Cultural Heritage: Developments, Methodologies, and Perspectives of the Digital Twin. Journal of Architectural and Engineering Research, 10, 98–109. https://doi.org/10.54338/27382656-2026.10-08