Airlines generally aren’t soaring with fans, but AI could shorten delays to get people flying high again.
Zurich-based Assaia is developing AI that aims to compress the time between landing and liftoff.
The self-funded startup, founded earlier this year, is using image recognition algorithms sped by NVIDIA GPUs to process video feeds and deliver insights for management of airplane turnarounds.
Airport ground crews today don’t rely on sophisticated systems. Airports lack the digital tools to manage all the activities of an aircraft turnaround in real time, said Max Diez, founder and CEO of Assaia.
“We saw that turnarounds in the aviation industry are really a black box. Sometimes the catering truck will hit the plane and cause a dent,” Diez said.
Air carrier delays caused by crews servicing planes accounted for 5.8 percent of all airplanes running late, according to an October report from the U.S. Department of Transportation. That’s roughly six times the delays to flights caused by extreme weather.
Minimizing delays promises to boost airline profits. Delays can cost an airline about $70 per minute, according to the Bureau for Transportation Statistics.
AI Airport Operations
AI can help get a grip on this. That’s because airports capture a ton of video that can be fed into Assaia’s software and used to help manage turnarounds. That monitored video helps airlines track vendors servicing planes before takeoff to ensure timely turnarounds.
Airlines can hold their vendors accountable to quickly carrying out services. Catering trucks, cleaners and other service providers all have what’s known as service-level agreements with airlines to abide by in order to help keep the planes running on time. Those spell out how long a provider is given to perform a service before receiving a financial penalty.
Assaia’s software is helping record instances of service that run afoul of agreements.
“We provide a real-time dashboard that can help them understand whether they (airlines) need to intervene or not — like did the gasoline arrive or not,” said Diez.
GPUs at Gates
Assaia is working with more than a dozen airports in the U.S., Europe, the Middle East and Asia. Among its customers are some of the largest US carriers. At London Heathrow, Assaia just completed an extensive pilot in collaboration with British Airways.
It has arrangements in place with some to put its GPU-driven system in or near the airline terminals, and its units are already processing hundreds of video streams. A single system can process up to six video feeds at once. It can then push out the information for its customers. It’s planning to use Jetson AGX Xavier for the next iteration of its systems.
The startup trained its neural networks on several years’ worth of video from airfields around the world. The neural nets understand how different objects on the airfield look, move and interact, said Nikolay Kobyshev, CTO at Assaia.
“If we can make airplane turnarounds only a little bit efficient, it’s already a significant addition to the airlines’ revenue — which in turn will translate at almost 100 percent to incremental profit,” said Diez.
And passengers will get to their destinations that much sooner.
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