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Calgary International Airport turns to AI to streamline freighter operations

Calgary Airports is equipping a dedicated cargo apron with Assaia’s AI-powered ApronAI system to provide real-time visibility into freighter turnarounds, improve operational coordination and identify opportunities to make cargo handling more predictable and efficient.

The Logistic News by The Logistic News
October 29, 2026
in Air, Cargo, Logistic, Tech
Reading Time: 3 mins read
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Calgary International AI

Calgary International AI

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Calgary International Airport (YYC) is bringing artificial intelligence to its freighter operations, providing cargo operators and ground handlers with real-time visibility of aircraft turnaround activities from arrival to departure.

Calgary Airports has installed AI-enabled cameras on one of the airport’s dedicated cargo aprons to monitor each freighter turnaround and record the start and end times of key activities such as unloading, loading and fueling. The system is designed to provide a common operational picture that will allow the airport, cargo operators and ground handling teams to operate from the same timely information.

The platform, developed by technology firm Assaia, will go live on 10 November. Following deployment at YYC’s passenger gates last year, the system is being rolled out and will now also be used for the airport’s cargo operations.

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The timing of the launch was intentional, with the system set to go live just ahead of the airport’s busiest cargo period of the year, said Megan Gupton, chief information officer at Calgary Airports.

“We’re going live just before our busiest period of the year for cargo, and that’s on purpose,” Gupton said.

“Peak season will be an opportunity to see how well operations are running, see where processes are working well and to highlight areas that need improving,” she said. The results will help Calgary Airports and its partners plan for 2027 and beyond.

For Assaia, the initiative also provides an opportunity to better understand the factors affecting cargo aircraft turnaround times. Chief executive Christiaan Hen said that freighter operations present unique challenges compared to handling passenger aircraft, particularly as turnaround procedures can vary considerably depending on the type of cargo and its particular handling needs.

Because of this variation, it is more difficult to have reliable expectations of what individual turnarounds should be. With Assaia’s ApronAI platform, which gathers detailed operational data from activities directly on the apron, Calgary Airports and its partners will be able to analyze these differences and identify ways to improve predictability and efficiency.

The project has received financial support from the Government of Canada through the National Trade Corridors Fund, which supports investments to strengthen Canada’s transportation infrastructure and supply chains.

“This initiative demonstrates the role of technology and infrastructure investment in supporting economic growth,” said Steven MacKinnon, Canada’s minister of transport and leader of the government in the House of Commons.

“Building a stronger economy means smart investments in the infrastructure and technology that keeps Canada moving,” said MacKinnon.

“The National Trade Corridors Fund supports transportation hubs like YYC Calgary International Airport to bring forward innovative solutions to improve efficiency, strengthen supply chains and support businesses across the country,” he added.

The airport’s cargo activity demonstrates the significance of the project. Last year YYC had more than 5,200 cargo landings and handles more than 70% of Alberta’s air cargo tonnage.

Calgary Airports has also invested more than $100 million on cargo infrastructure. Its facilities support a wide range of freight needs including e-commerce shipments, perishables, pharmaceuticals, oversized industrial equipment and live animals.

Calgary International Airport is expanding its use of AI-powered monitoring to its freighter apron to boost operational visibility during a busy time for cargo traffic and build a larger data foundation for future improvements.

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