If you commute over bridges and overpasses each day, there’s a fairly good chance that some of them might need repair (more than 54,000 U.S. bridges are rated “structurally deficient”). As the country’s infrastructure ages, bridge inspections get even more important, but the work is expensive, time-consuming, and dangerous, requiring engineers to rappel down the side of a bridge hundreds of feet above a river. It’s a task that might be better suited for drones.
In two recent bridge inspections–one at the Stone Arch Bridge in Minneapolis, and the other at the Daniel Carter Beard Bridge at the Ohio-Kentucky border–Intel partnered with transportation officials to use drones to capture detailed high-res images of each structure.
“It’s collecting a series of images, and the second part is actually stitching these images to gather and recreate what you call a digital twin,” says Anil Nanduri, general manager of Intel’s drone group. “Imagine you have a bridge over a river, but then you have an exact replica of it–you can zoom into the finest details, including a sub-centimeter level of detail, on your computer screen.”
Current inspections are often done with pen and paper, so the data is difficult to share. A drone’s data is both easier for a group of people to analyze and can be tracked over time. As more and more data is collected, AI and machine learning can begin to automatically highlight cracks, corrosion, or other defects.
While a manual inspection might take weeks, and can force traffic lanes to shut down, a drone can cover a bridge in just a matter of days, Nanduri says. In the case of the Stone Arch Bridge, the shift could save taxpayers around $160,000 in the cost of inspections over 10 years. Despite the advantages, though, it may take a little more time before the tech scales up widely. The FAA is still working on regulations for unmanned drones, and it takes experience for a pilot to fly a drone now. As the technology improves, the drones will become simpler to operate. Software also still needs to be developed that can quickly go through the thousands of images that the drones can collect. “My team’s focus is to make it as simple as possible by leveraging automation,” says Nanduri.