ArtDiff: Integrating IoT and AI to enhance precision in ancient mural restoration

Abstract

Ancient murals, as invaluable cultural artifacts, have profound historical and cultural significance. However, these murals often face degradation phenomena such as peeling, fading, and cracking, which compromises their preservation. Conventional methodologies for protection and restoration exhibit limitations and do not adequately address multifaceted damage conditions, thus necessitating the integration of advanced technological interventions to enhance restoration effectiveness.This paper delineates a framework for the preservation and restoration of cultural heritage buildings that uses Internet of Things (IoT) technology and Artificial Intelligence (AI). Using real-time environmental and structural health surveillance, in conjunction with security mechanisms, this framework markedly improves precision and efficiency in forecasting and identifying potential risks.Furthermore, in the context of mural restoration, this paper introduces the ArtDiff model. This model amalgamates a modified U-Net for initial crack detection with an edge-guided restoration technique, employing a diffusion model for meticulous restoration. Empirical results substantiate the superiority of the ArtDiff model in crack detection and mural restoration, delivering a greater precision and efficacy relative to existing approaches. Through the implementation of multilevel supervision strategies and an avant-garde model architecture, this study offers a sophisticated mural restoration solution, furnishing novel technological support for the preservation of cultural heritage.