Intel Powers First Satellite with AI on Board

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As ubiquitous as artificial intelligence has become in modern life — from boosting our understanding of the cosmos to surfacing entertaining videos on your phone — AI hasn’t yet found its way into orbit. That is until Sept. 2, when an experimental satellite about the size of a cereal box was ejected from a rocket’s dispenser along with 45 other similarly small satellites. The satellite, named PhiSat-1, is now soaring at over 17,000 mph (27,500 kmh) in sun-synchronous orbit about 329 miles (530 km) overhead.

PhiSat-1 contains a new hyperspectral-thermal camera and onboard AI processing thanks to an Intel Movidius Myriad 2 Vision Processing Unit (VPU) — the same chip inside many smart cameras and even a $99 selfie drone here on Earth. PhiSat-1 is actually one of a pair of satellites on a mission to monitor polar ice and soil moisture, while also testing intersatellite communication systems in order to create a future network of federated satellites.

The first problem the Myriad 2 is helping to solve? How to handle the large amount of data generated by high-fidelity cameras like the one on PhiSat-1. “The capability that sensors have to produce data increases by a factor of 100 every generation, while our capabilities to download data are increasing, but only by a factor of three, four, five per generation,” says Gianluca Furano, data systems and onboard computing lead at the European Space Agency, which led the collaborative effort behind PhiSat-1.

At the same time, about two-thirds of our planet’s surface is covered in clouds at any given time. That means a whole lot of useless images of clouds are typically captured, saved, sent over precious down-link bandwidth to Earth, saved again, reviewed by a scientist (or an algorithm) on a computer hours or days later — only to be deleted.

“And artificial intelligence at the edge came to rescue us, the cavalry in the Western movie,” says Furano. The idea the team rallied around was to use onboard processing to identify and discard cloudy images — thus saving about 30% of bandwidth.