An Integrated AI+FEM+AR System for Real-Time Structural Simulations and X-Ray Visualization of Heritage and Aging Buildings

Traditional and historical buildings, including heritage structures, existing aging buildings, and extended architectural systems, face increasing vulnerability due to natural deterioration, environmental stressors, and structural fatigue. Current assessment methods, such as embedded sensors or external instrumentation, often present challenges in accessibility, cost, and invasiveness. To overcome these limitations, this study proposes a novel integration of Augmented Reality (AR), Finite Element Method (FEM), and Artificial Intelligence (AI) to enable real-time, non-invasive structural health monitoring and predictive analysis for both historical and modern structures. AR technology will visualize full-scale digital twins of the buildings in situ, offering interactive and immersive “X-ray” views of the hidden structural systems. FEM will simulate stress, deformation, and dynamic responses under various loading scenarios. Leveraging Machine Learning (ML) models trained on FEM outputs, the framework will identify potential vulnerabilities, anomalies, and damage patterns in advance, accelerating assessment and maintenance planning. This integrated AR-AI system not only supports heritage conservation but also enhances the management and resilience of existing and retrofitted buildings. The framework serves as a powerful tool for structural engineers, conservationists, and educators, offering insights into structural behavior while minimizing physical intervention. Additionally, the system creates engaging opportunities for public learning and tourism by exposing the unseen structural logic of buildings through immersive AR experiences. This research contributes to the future of digitally supported sustainable architecture, blending advanced simulation, computational methods, and real-time visualization for holistic building analysis and conservation.