Paradigm Shift in Infrastructure Inspection Technology: Leveraging High-performance Imaging and Advanced AI Analytics to Inspect Road Infrastructure
Journal:
arXiv
Published Date:
May 20, 2025
Abstract
Effective road infrastructure management is crucial for modern society.
Traditional manual inspection techniques remain constrained by cost,
efficiency, and scalability, while camera and laser imaging methods fail to
capture subsurface defects critical for long-term structural integrity. This
paper introduces ROVAI, an end-to-end framework that integrates high-resolution
X-ray computed tomography imaging and advanced AI-driven analytics, aiming to
transform road infrastructure inspection technologies. By leveraging the
computational power of world-leading supercomputers, Fugaku and Frontier, and
SoTA synchrotron facility (Spring-8), ROVAI enables scalable and
high-throughput processing of massive 3D tomographic datasets. Our approach
overcomes key challenges, such as the high memory requirements of vision
models, the lack of labeled training data, and storage I/O bottlenecks. This
seamless integration of imaging and AI analytics facilitates automated defect
detection, material composition analysis, and lifespan prediction. Experimental
results demonstrate the effectiveness of ROVAI in real-world scenarios, setting
a new standard for intelligent, data-driven infrastructure management.
