Using AI in the Restoration of Historic Buildings: Digital Diagnostics, Predictive Modelling and Ethical Challenges

Historic buildings, symbols of cultural heritage, represent unique architectural and cultural values. Historic buildings face the gradual erosion of materials and structures caused by time, climate change and the impact of human activity. Today, artificial intelligence (AI) technologies, including computer vision and deep learning, are opening up new possibilities in diagnosing, monitoring and planning the restoration of these historic monuments. This publication analyses existing AI applications in the restoration of historic buildings that allow detailed records and predictions of the condition of monuments, reducing the need for interventions that could compromise their historic integrity. Main focuses include automated damage detection, structural degradation analysis, and the creation of predictive models to support long-term maintenance. The article includes and/or analyses case studies that demonstrate the practical application of AI in architectural heritage conservation and discusses the benefits of implementing these technologies, including improved diagnostic accuracy and efficiency. The ethical and technical challenges associated with the application of AI are also analyzed, including costs, dependence on technology, and potential impact on authenticity. The results of this research contribute to the understanding of how AI can effectively support sustainable heritage conservation practices while respecting the historical value and aesthetics of the objects being restored.