How Drones Are Changing How We Repair Roads
Drones give their users a bird's eye view. While they've grown in popularity among hobbyists, they're also becoming commonplace on job sites. When it comes to asphalt and paving jobs, these flying robots are changing the way we handle repair jobs.
You can't overestimate the importance of good planning. Long before a paving job starts, drones can provide crucial site data. Getting an aerial shot of a damaged stretch of pavement or the area surrounding a road gives contractors more information to work with. Here are just a few of the ways that drones can do that:
Drones can also help with a concept called "digital twinning." Digital twin technology creates scale models of real-world assets. That means that you can work with a digital model of a road and the surrounding area, run traffic and weather simulations, and see how the finished project is likely to hold up over time. You can also simulate different materials, thicknesses, and other variables.
All of that aside, your model is only going to be as useful as the information you put into the modeling software. To make a decent model of a paving project, you need as much data about the surrounding area as possible. Drone photography can capture that, in much less time than it takes to digitally stitch multiple conventional photographs together.
Machine learning dovetails with digital twinning. The information captured by drones can provide valuable data to an algorithm, which can then make predictions. This can guide you to weak points in a given project and help you make more informed decisions when it comes to choosing tools and materials for a given paving job.
Paving is almost as much an art as it is a science. No matter how much you've been taught, there's no substitute for experience when you're dealing with asphalt and concrete. Machine learning algorithms seek to take that kind of experience and make it more accessible. Instead of needing 25 years of experience to make informed decisions, machine learning compiles as much information as possible, crunches the data, and provides predictions in a fraction of the time. Drone images can be a very valuable part of that dataset.
For big jobs, there's virtually no substitute for an aerial view. This is especially true when you have to move a lot of soil or cover a large area. Not only do you need to get the lay of the land before you start, but you'll also need to keep an eye on how it's progressing to spot any potential complications.
Even if you aren't working on a big earth-moving job, drones can be a lifesaver. A lot of road repairs involve breaking up and moving massive quantities of asphalt. A drone can give you a zoomed-out view of the project in its entirety, so you can monitor how much is done, how much is left to do, and how things are going. It's a tool that makes it much easier to manage big, multi-stage jobs efficiently, and respond to problems as they crop up.
Even small jobs like pothole repairs can benefit from drone photography. Potholes and cracks can show up in groups — water seeps in, freezes, expands, and cracks begin to stretch outward from the initial site of infiltration. They also generally show up long after the initial damage to the road surface has already been done. Drones give you the opportunity to see things that you might not be able to spot at ground level, including the connections between multiple potholes and signs of minor damage that could turn into bigger problems in the future.
Potholes can also be unpredictable. Some of them appear and stay roughly the same size for a long time, while others show up suddenly and worsen just as quickly. While an aerial shot can give you a lot of information, it doesn't tell the whole story. For that, you need to turn to machine learning again.
By supplying an artificial intelligence with a bank of images of potholes and data on which ones subsequently got worse and which didn't, it's possible to train the AI to pick out which potholes need to be imminently repaired. It's a useful tool for prioritizing jobs — low-priority holes can get patched, while higher-priority, expanding holes may need to be cut out and repaved to keep them from steadily worsening. Using drone images and AI to prioritize can save you a lot of time, labor, materials, and wear and tear on your machinery.
In the past, paving professionals had to rely on their experience and what they could see in front of them. Drone technology expands that. Now, it's possible to capture an aerial view of a project, create a 3d model, use artificial intelligence to prioritize the damage, and run weather and traffic simulations. The end result is lower costs, less wasted time, and pavement repairs that last longer.
POSTED: October 19, 2022
TAGS: Asphalt Repair