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NASA Is Designing a Swarm of ‘Hive Mind’ Weather Satellites

The new machine learning software could revolutionize our understanding of weather patterns.

Swarms of satellites could be linked to form a "hive mind," allowing them to collect data on important weather patterns from different angles and different times, a report by NASA explains. These swarms have the potential to "revolutionize scientists’ understanding of weather and climate change," NASA says.

Sabrina Thompson, an engineer at NASA's Goddard Space Flight Center, is working on software that will allow SmallSats to communicate with each other and relay vital information down to Earth from different perspectives at the same time.

Machine learning-powered satellite configurations

Thompson's software would allow scientists to target specific weather events. The spacecraft swarm would then figure out how to move relative to the event in order to gather the most comprehensive data possible. Not only could this allow for image data collection of weather events from different angles at the same time, but it could also even quickly collect data from different times of says on vast cloud formations crossing the Atlantic, as an example.

Different swarm configurations could include one where "satellites will be in different orbits, which will allow them to view a cloud or other phenomenon at different angles," Thompson said. Another swarm could "view the same phenomena with similar view, but at different times of the day" and a third could be a combination of the two "with some satellites in the same orbit, following one another with some time offset, and other satellites which may be in orbits with different altitudes and/or inclinations."

Satellite networks do vital work despite growing concern over space debris

Though the individual SmallSats would largely remain on the same orbital trajectory, they could use a technique called differential drag control to speed them up and slow them down (and in so doing, slightly adjust their orbits up and down) in order to keep them in position relative to each other. Ultimately, Thompson's software would reduce the reliance on ground control and communications networks, allowing for fast real-time decisions to be made. This would be crucial for enabling high-speed data collection on quick-moving weather events.

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Though experts warn of the increasing space debris orbiting Earth as we continue to launch satellites into orbit, Thompson and NASA's "hive mind" swarms come at a crucial time for our planet. The IPCC's latest report on climate change paints a dire picture and has been described as "code red for humanity" by UN Secretary-General António Guterres. Machine learning-enabled satellite swarms may help us to collect the data we need to gain a greater understanding of the effects of climate change and how we can turn back the tide on its most adverse effects.

Editorial Note: This article has been updated to offer specific details about how differential drag control works, allowing the satellites to move both up and down. 

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