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Norwegian

Rydoo Accounts Payable AI invoice automation at Norwegian

MidAmerica St. Louis

GoodMaps indoor navigation at MidAmerica St. Louis Airport

Lyon Saint-Exupéry Airport

Stan robotic valet parking at Lyon Saint-Exupéry

London Heathrow

Facial-recognition eGates at Heathrow

Almaty International Airport

Q-Gate biometric passport-control terminals at Almaty

Pittsburgh International Airport

Arrow Analytics EZ-Board computer-vision carry-on analytics test at PIT Gate A7

Federal Aviation Administration

FAA SMART airspace and trajectory management platform

Dubai International

Dubai Police AI systems for passenger screening, unattended baggage and camera analysis at Dubai airports

Airport intelligence / Minneapolis–Saint Paul

Minneapolis tests whether AI can help passengers sort waste

Oscar AI appeared as a waste-sorting pilot in MSP Terminal 1. The environmental task is precise, but the source does not establish a sustained reduction in contamination.

Aerial view of Minneapolis–Saint Paul International Airport, May 2012
Aerial view of Minneapolis–Saint Paul International Airport, May 2012. Photograph: Michael Adams / CC BY-SA 3.0 (cropped to fit). Shows the airport, not an AI implementation.
The picture at Minneapolis–Saint Paul

What is happening on the ground

A food court produces mixed waste, and even a willing passenger may not know which bin is correct.

MSP's airport blog described a March 2026 Oscar AI pilot offering sorting guidance near the Terminal 1 food court.

Unlike many broad sustainability claims, this programme has a specific observable interaction, though the final trial result is not known.

Selected implementations

The application under review

01 / Pilot

Minneapolis tests whether AI can help passengers sort waste

The operational problem

Passengers need to identify the appropriate waste stream without slowing down or creating contaminated recycling.

What the sources report

The Metropolitan Airports Commission reported the Oscar AI trial at the Terminal 1 food court on 29 March 2026.

Why it matters

The technology could be assessed through bin contamination, number of prompts and correct disposal.

What remains unproven

No controlled waste audit, permanent deployment decision or cost benefit has been published.

Sources and verification (1)

MSP Airport blog · Evidence grade A

Evidence supports a reported claim; it does not automatically establish a measured operating benefit.

The wider register

What else is happening at Minneapolis–Saint Paul?

Related airport systems stay in the wider evidence register. Their maturity and AI involvement should be checked separately from the feature above.

No additional publicly listed deployment records.

Editorial judgement

The useful outcome would be a measured improvement in sorting behaviour, with a clear comparison period.

Source attribution and status limits remain attached to the implementation record.

Live data from the Aerostack register. Status reflects published evidence only. See Our approach for how records are graded.

Aerostack tracks AI deployments across airports and airlines, with the published evidence behind each record. Photography is real aviation imagery. Record thumbnails may show the named airport or airline; other photographs do not.