Work

Artificial intelligence-based preservation of architectural cultural heritage: a review, current trends and new perspective

Year: 2026

Type: article

Abstract: Architectural cultural heritage faces persistent threats from natural weathering and human activities. While artificial intelligence (AI) has seen growing adoption and research in this field, a systematic review integrating quantitative and qualitative perspectives remains lacking. This study conducts a comprehensive review of AI-based preservation of architectural cultural heritage to examine current research, key technologies, and emerging trends. Through bibliometric and content analysis of 238 relevant publications, this paper traced the evolution of the field, identified research hotspots, and mapped its developmental trajectory. The results highlight that AI plays a critical role in six key phases: preventive monitoring, restoration, digital archiving, public engagement, generative digital preservation, and ethics and authenticity. Furthermore, an integrated framework is proposed to illustrate the synergistic operation of core technologies, such as 3D point cloud analysis, deep learning, and generative artificial intelligence within these phases. Based on observed research gaps, six forward-looking directions are outlined to encourage theoretical refinement and practical innovation in this interdisciplinary domain.

Source: Journal of Asian Architecture and Building Engineering

DOI: 10.1080/13467581.2026.2721852

Authors: Jiaolan Zhu, Xinru Hao, Md Morshed Alam, Guanghan Song

Institutions: Lanzhou University of Technology, Swinburne University of Technology

Language: English

Topic: 3D Surveying and Cultural Heritage

Subfield: Geology

Field: Earth and Planetary Sciences

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,165

Funders: Lanzhou University, National Natural Science Foundation of China, Lanzhou University of Technology