dailyai.report

The framework models cultural assets with 3D scans and feeds data into physics‑informed neural networks (PINNs). By layering IoT sensors, 3D analysis, and PINNs, it simulates degradation and predicts maintenance needs. Researchers can now test preservation strategies in virtual environments before applying them on fragile artifacts. The approach offers a reproducible, data‑driven path for heritage managers to safeguard priceless collections.