Rogue Drone Pilots Face A New Foe: Deep Learning AI (Communications of the ACM)

Rogue Drone Pilots Face A New Foe: Deep Learning AI In the wake of airspace-invading drones causing the precautionary shutdowns of three major airports--London's Gatwick in December and Heathrow in early January, along with Newark Liberty International, NJ last week--aviation authorities the world over are now considering the acquisition of commercial drone detection, tracking, and capture systems, in a bid to keep airliners and passengers safe. However, they could be jumping the gun. Experts are warning that today's counter-drone systems are no cure-all, as they cannot defend against some types of criminal drone threat--especially the most determined airspace saboteurs using home-built, customized drones that may not respond to conventional countermeasures. However, a number of ingenious ideas are now being investigated to shore up some of the gaps in functionality, and some of them are even based on the technology of the moment: deep learning. Aviation safety authorities worry about drones because they can penetrate cockpit windscreens, injuring the pilots, or risk starting inflight fires by breaching the fuel tanks in aircraft wings, or causing sudden engine failure during a critical part of flight like takeoff or landing, perhaps leading to a crash.