By Dronelife Features Editor Jim Magill
As artificial intelligence (AI) tools are rapidly driving the pace of technological innovation across a wide swath of industries, a controversy is brewing over which AI tools the commercial drone industry should embrace and how quickly that adoption should take place.
Currently, military drone applications, which are increasingly focused on guiding multiple drones toward targets in GPS-denied environments, are driving the pace of adoption of AI-enabled navigation and control systems. But commercial drone operators are not far behind in finding new uses for AI technology.
Shaun Passley, founder and CEO of Zenatech, a company specializing in AI-related drone and software-as-a-service solutions, said AI will play an oversized role in the development of UAS traffic control systems and wildfire mitigation, among a myriad of other applications.
The FAA and private companies, such as drone delivery company, Zipline, and Alphabet Inc., Google’s parent company, all are working to develop the AI-enabled traffic management systems that will be needed to manage the large number of UAVs flying within the U.S. airspace in the not-too-distant future, Passley said.
“It is going to be a very important because of the volume of drone aircraft. You may have 5,000 large aircraft in the sky (today), but you could potentially have millions of drones in the sky one day. Human beings can’t manage that many drones,” he said.
Passley added that because drones typically fly at lower altitudes than manned aircraft, the UAS traffic management (UTM) systems of the future will have to deal with many more variables regarding noise abatement and aerial vehicle separation than the existing air traffic management system. UTM systems will likely rely on AI tools in the development of object-avoidance technology and in locating where each drone is located in the airspace and where it’s going.
Zenatech and other technology companies are also employing AI-enabled technology to change the face of wildlife firefighting, developing early-detection systems to spot fires in their early stages, and dispatching swarms of autonomous drones to extinguish the blazes before they have a chance to grow into massively destructive infernos.
When implemented, this technology likely will save federal and state firefighting agencies tens of millions of dollars annually and help preserve thousands of acres of wild land as well as protect adjacent communities. Such early-detection systems could supplant the decades-old techniques of relying on humans to spot and report wildfires
“With AI technology and using drone swarms, you have a hundred drones in the air scanning the forest. And if any fire happens, the drone immediately goes to the fire and extinguishes the fire,” he said. “We’re talking about fires that may even be less than 10 square feet, and the drone extinguishes it immediately, so it doesn’t spread.”
Drone swarms could also revolutionize the way airborne assets are used to fight wildfires, techniques that have remained largely unchanged since the 1950s.
“Right now, they’re using these $30-million aerial tankers that go into the lake and grab about 150,000 gallons of water,” he said. Once the tanker aircraft fills up with water, it flies to the fire site to dump its cargo.
“The pilot looks down on the ground and he eyeballs it, to drop that huge payload,” Passley said. “So, many times he misses and I believe 25% to 75% of the water doesn’t hit the target and it’s evaporated before it even hits the ground.”
This is where AI plays a critical role in the firefighting systems envisioned by Zenatech. Using drone collected-data from land surveys, LIDAR and other sensors, the AI tool can determine the location of a fire, and then signal other drones on patrol in the sky to concentrate together in the hot zone to fight the fire.
“So, in our approach, there’ll always be drones in the sky 24 hours a day looking for fire. And then when the fire is detected, they’ll call other drones to act as a drone swarm to go after the fire and extinguish it,” Passley said.
Limits to AI
But while AI tools hold great promise to advance technological developments in the commercial drone industry, there is a potential for drone operators to become too dependent on the technology, especially for those who are just beginning to develop their piloting skills, said industry veteran Gene Robinson.
Robinson, a drone pilot instructor who teaches at Austin Community College, said some UAV control systems, such as those designed by Skydio, could make it more difficult for the novice pilot to get the feel of flying their drone unaided by AI.
“I call it a nanny engine,” he said. “So, if you’re flying Skydio and you give control input to the stick, the nanny engine has to bless it before it gets out. Right now, it happens in microseconds, obviously, but I can tell there’s a minuscule lag there and it just doesn’t seem as crisp and responsive to me.”
He said even without AI-tools, most drone missions currently can be accomplished with a minimum of human operator input.
“We’ve got sufficient automation right now to where if you plan your mission, literally, all you have to do is push a button and it goes. It flies the mission for you, right? It’s a robot,” he said.
Robinson agreed that AI could one day be used to aid in the development of UTM systems, as Passley suggested, but he thought that the technology hasn’t advanced to that point yet.
“Could AI be used to handle any unforeseen circumstances? Maybe, but I’m not sure it’s ready for that at the moment,” Robinson said. He added that today’s drones don’t yet have the onboard sensor capability that would be needed to develop such an advanced detect-and-avoid system.
“And it doesn’t matter how much AI you’ve got on board, if you can’t see it or sense it, it doesn’t make any difference. You still could have a potential for a collision,” he said.
Robinson said one area in which AI tools could prove useful to most drone operators is in assisting them in mission planning.
“If you look at the process of filing a mission, if you want to fly a mission in a controlled airspace, you could use AI,” he said. “I can ask ChatGPT, ‘Hey, I’m going to fly a mission in Bravo airspace. What do I need to do?” And if it becomes familiar enough with your operation and knows what your equipment is, it can literally, from start to finish, give you everything that you need: waivers, language to put the waivers in, what your sensor is.”
Meanwhile, the use of AI tools in the development of military drone-related technology represents a whole different set of considerations compared with civilian use of the technology, Robinson said.
“Military use is a completely different situation because you get to take some of the controls off; you’re not worried about causing mayhem and destruction,” he said. “You take off the controls or the restrictions and let AI do its thing, and you’re not worried about running into something that could kill somebody. And that’s really quite unsettling.”
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Jim Magill is a Houston-based writer with almost a quarter-century of experience covering technical and economic developments in the oil and gas industry. After retiring in December 2019 as a senior editor with S&P Global Platts, Jim began writing about emerging technologies, such as artificial intelligence, robots and drones, and the ways in which they’re contributing to our society. In addition to DroneLife, Jim is a contributor to Forbes.com and his work has appeared in the Houston Chronicle, U.S. News & World Report, and Unmanned Systems, a publication of the Association for Unmanned Vehicle Systems International.
Ian McNabb is a journalist focusing on drone technology and lifestyle content at Dronelife. He is based between Boston and NH and, when not writing, enjoys hiking and Boston area sports.