The safety of pilots and passengers relies on runways being kept in good condition, but at remote airports in harsh environments, maintenance can be a challenge. A new study from Canada used drones and autonomous technology to demonstrate how this could change.
There are many ways that a runway can become dangerous. Damage to the surface of a runway can disrupt the stability of aircraft, as can foreign object debris such as loose hardware components, wildlife, rocks and broken pieces of concrete. This is why runway health is governed by strict regulations, and major airports have dedicated teams to inspect runways multiple times a day.
The runways at small airports need just as much maintenance, but finding the resources to do this can be a struggle. In Canada, a network of more than 100 small airports serve as delivery lifelines for isolated communities that range in population from tens to hundreds of people. Most of these airports have gravel runways which are susceptible to a number of unique problems, especially in the harsh weather of Canada.
Aside from the typical issue of foreign object debris, vegetation can quickly spread over the gravel surface due to buildup of organic soils over time. But the biggest problem is surface water. This collects within gaps and freezes, growing by 9% in size and causing breakages in the surface.
The problem is that runway inspections require labor-intensive work from specialized technicians who must physically travel to these locations. This is an expensive undertaking, and weather conditions can often prevent access to these places outside of small time windows.
Michal Aibin, visiting associate teaching professor of computer science at Northeastern University, in collaboration with Transport Canada, carried out an experiment to automate the identification of runway maintenance issues using drones and AI processing. Drones have been used to inspect runways many times before, but the automation of the process is a breakthrough development in Canada: it enables inspections to be done remotely, ensuring that small operational windows are never missed.
The experiment was carried out at six remote airports (Port McNeil, Kashechewan, Moosonee, Round Lake, Keewaywin and North Spirit Lake). Flying 40-70 meters AGL, drones gathered data and enabled identification of surface water, vegetation, and imperfections in runway smoothness. Thousands of images were taken, and the results displayed very high accuracy rates.
This study has laid the foundation for a new method of runway inspection that could improve safety and bring considerable cost savings to small communities around the world. The study notes that technology such as the DJI Dock 2 could make autonomous runway inspections available to communities in countries like the US, Australia and New Zealand, as well as developing nations with limited infrastructure. As Aibin pointed out: "Basically, what you do is you start the drone, you collect the data and — with coffee in your hand — you can inspect the entire runway."
This study is another demonstration of the power that autonomous drone systems have to improve our lives. High Lander's Orion DFM enables autonomous UAS operations for a wide range of commercial, industrial and public safety applications, and we're proud to offer the DJI Dock 2 to our clients for creating end-to-end autonomous systems. For more information about how our solutions can enhance your operations, get in touch.
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