Artificial Intelligence Tools in the Management of Reinforced Concrete Structures: Potential, Critical Issues, and Preliminary Results on Structural Degradation

The durability and management of reinforced concrete structures and infrastructures are a central issue in contemporary civil engineering. Efficient structural maintenance has become strategically critical to sustainable land and community management due to aging infrastructure, increasing operational stress, and limited financial resources. This study focuses specifically on reinforced concrete bridge piers, whose fundamental structural role influences road infrastructure management strategies. The objective of this study is to develop and use a system based on convolutional neural networks to visually, rapidly, and automatically identify degraded portions of the reinforcement, based on images acquired on-site or from visual inspections, and classify their level of degradation. The topic addressed is highly innovative. The need to define and calibrate reliable degradation classification criteria, and the difficulty of obtaining images and classifying them correctly for database construction, have influenced the development of the study and make the results interesting and promising, but absolutely preliminary.