Talhe Ghodousiyan, Abdolbasir Hosseinbor,
Volume 1, Issue 4 (Spesial Issue 1.4 2019)
Abstract
The comprehensive and remarkable expansion and progress of sciences, especially in the fields of natural, basic and engineering sciences, has caused a huge leap in scientific and methodological approaches in the fields of humanities, medicine, agriculture and art. This leap has created interdisciplinary knowledge or a common language between different sciences and specialties, and their integration has formed a compatible interaction. Among these, archaeometry is one of the interdisciplinary sciences that was often considered as a side specialty and an addition to archaeological analysis and restoration of historical monuments, but today, with the systematic use of natural, basic and technical and engineering approaches, archaeometry has become a common language of the aforementioned sciences with humanities and arts, especially in the field of cultural heritage studies, and has become more important as an independent specialty than ever before. In the present study, an applied and preliminary model of the position of archaeometric approaches and studies in the recognition and study of architectural heritage and its elements has been presented. The need and demand of conservation researchers for controlled and scientific information and data in recent years has doubled the importance of archaeological approaches, but the lack of data in the field of conservation of Iran's historical monuments, especially architectural heritage, is still clearly felt.
Talhe Ghodousiyan, Mehdi Razani, Amir Hossein Mehdikhani, Arash Keshtkar, Ali Kh Mirzaie, Alireza Mansouri, Ali Akbar Kiaei , Hossein Shirazi , Mustafa Dehpahlavan, Abdolbasir Hosseinbor,
Volume 7, Issue 3 (11-2024)
Abstract
Artificial intelligence (AI) and machine learning (ML) have emerged as transformative tools in preserving, analyzing, and representing cultural heritage and arts. This article provides a systematic and comprehensive review of AI applications in this domain, exploring their potential to address longstanding challenges such as natural degradation, limited accessibility, and complex documentation. By integrating classical and advanced ML algorithms, we examine case studies including the Time Machine Europe project, the Ithaca model for ancient Greek texts, and metaverse-based heritage digitization. These initiatives demonstrate AI’s capacity to enhance precision, speed, and interactivity in heritage tasks, from virtual reconstruction to multimodal data analysis. However, limitations such as data quality, ethical concerns, and computational complexity pose significant barriers to widespread adoption. Emerging technologies like non-fungible tokens (NFTs), prompt engineering, and quantum AI are highlighted as future directions that promise further innovation. This study underscores the need for interdisciplinary collaboration and ethical frameworks to ensure sustainable advancements, offering a roadmap for researchers and policymakers in the digital era.
