Automated Extraction of Information from 2D Bridge Drawings using Computer Vision

Bridge maintenance and demolition planning is an important task that requires a thorough understanding of several critical factors, including structural elements, material properties, and dimensions. 2D bridge drawings serve as a crucial information source for this process. However, these technical drawings are usually quite large and complicated, so manually obtaining relevant information from these drawings can be a cumbersome, error-prone, and expensive process. My research goal is to develop an automated system that utilizes computer vision technology to extract key information from 2D bridge drawings with utmost accuracy and efficiency. By automating this process, my solution will significantly reduce errors and save valuable time for engineers and planners.