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IAG Cargo’s accelerator finalist to test machine learning for ULD management

usscmc by usscmc
December 3, 2019
IAG Cargo’s accelerator finalist to test machine learning for ULD management
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IAG Cargo, the cargo arm of International Airlines Group, this week concludes its 2019 accelerator program, Hangar 51. For the past 10-weeks, IAG Cargo has been working with its chosen finalist, Spain-based startup Allread MLT to explore the use of machine learning to improve ULD container management.

With the goal of optimizing stock-taking process for ULDs, Allread intends to train its machine-learning software to recognize ULD containers, and read container numbers. “These past 10 weeks have been jam packed researching the problem statement and understanding how the [ULD management] process works today, “said Carly Morris, head of innovation, IAG Cargo. Training the algorithm has entailed extracting data from thousands of ULD images

Following the 10-week accelerator, Allread, along with the 12 other finalists selected by IAG companies at a pitch event earlier this fall, will participate in a demo day next month in Barcelona. Until then, Allread will continue working an app that will help IAG Cargo create efficiencies and improve the accuracy of data it collects about its assets.

In its fourth year, IAG’s Hangar 51 accelerator received 474 applications from across fifty different countries in 2019. This year marked IAG Cargo’s second year participating in the program, during which it was fielding startups in the “future cargo logistics” category.

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