AI-Powered Saildrones Monitor Alaska's Krill

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Scientists deployed three robot boats to track krill in Alaska's Bering Sea when COVID-19 halted regular ocean research missions in 2020.

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These autonomous saildrones carried special sonar equipment to monitor tiny shrimp-like krill, which feed fish, seabirds, and marine mammals in the ocean ecosystem.

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Regular research ships used five different sonar frequencies to track krill, but the robot boats operated with just two frequencies - creating a technical challenge for scientists.

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NOAA scientists solved this limitation by teaching computers to recognize krill patterns using historical data from previous ship surveys since 2004.

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The machine learning system, called random forest algorithm, successfully matched the accuracy of traditional four-frequency krill detection methods.

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Recent studies revealed krill populations in the North Atlantic dropped by 50%, making this new tracking technology crucial for monitoring ocean health.

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This breakthrough keeps tabs on America's largest volume fishery - the Bering Sea's walleye pollock - which depends on krill for survival.

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Scientists can now use robot boats and smart algorithms to continue vital ocean research even when traditional survey ships cannot sail.

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