Computer Vision and IoT-Enabled Robotic Platform for Automated Crack Detection in Road and Bridges

摘要

Structural health monitoring (SHM) plays a critical role in preserving and maintaining civil structures such as bridges, roads, and monuments. However, the current approach to SHM relies on costly sensors and manual inspection, posing challenges in terms of efficiency and accuracy. In light of advancements in Artificial Intelligence (AI) and robotics, we propose an innovative solution for autonomous structural health monitoring. Our approach utilizes a specially designed robotic chassis and robotic arm equipped with an infrared (IR) camera to assess the quality of structures and detect cracks and defects. By leveraging these cutting-edge technologies, we aim to significantly enhance the SHM process, making it more efficient and error-free. The key element of our solution is an entirely in-house manufactured robot that integrates a camera onto its robotic arm to improve crack detection. By implementing computer vision techniques like YOLO (You Only Look Once), we achieve precise and real-time crack detection, enabling prompt notifications to relevant authorities regarding any identified defects. This autonomous robotic system optimizes the monitoring process and reduces human intervention, making it a cost-effective and reliable solution for ensuring the structural integrity of critical infrastructure.