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AI Tool Will Help Automate Ocean Data Analysis

The use of AI (artificial intelligence) technologies is transforming industries from manufacturing to healthcare, retail, agriculture, transportation, and beyond. Precedence Research estimates the global market for AI will reach nearly $1.6 trillion by 2030, up from about $87 billion in 2021. A new AI and machine learning-powered project funded by the NSF (National Science Foundation) will leverage these powerful technologies to transform the way scientists analyze ocean imagery, adding yet one more way AI is changing the way humans interact with everything—from other humans to machines and even data from the depths of the sea.

Every day, new information from Earth’s oceans is being collected by research crews and ROVs (remotely operated vehicles) equipped with cameras, video cameras, and instruments that measure parameters from the ROV’s surroundings, such as water temperature. This equipment allows research vehicles to collect massive amounts of imagery and other data about the ocean. However, just a fraction of the images and video captured during scientific dives is typically viewed, analyzed, and shared, which means the full value of this data is locked up and unavailable.

Ocean Vision AI, a new program that leverages AI and machine learning to accelerate the way scientists access and process ocean video and ocean imagery, aims to change this. Katy Croff Bell, founder and president of the Ocean Discovery League and a co-principal investigator for Ocean Vision AI, says: “In a single dive, thousands of species could have been recorded in new locations at new depths and new environmental conditions. A wealth of untapped biodiversity information is trapped in these existing recordings, with new data acquired daily.” NOAA says Ocean Vision AI will accelerate the automated analysis of underwater visual data to allow scientists, policymakers, and the general public to better understand and care about the ocean and its inhabitants.

The NSF recently awarded MBARI (Monterey Bay Aquarium Research Institute) $5 million for the project, which will accomplish goals like providing a central hub for research groups using underwater imaging, AI, and open data; creating data pipelines from existing image and video data repositories; providing project tools for coordination; leveraging public participation and engagement via game development; and generating data products shared with researchers and other open-data repositories.

MBARI says the current process of analyzing visual data gathered in the ocean often requires expert classifications, which the institute describes as “a resource-intensive process that is not scalable in its current form.” However, AI can help solve this painpoint. With Ocean Vision AI, anyone interested in what happens below the ocean’s surface will be able to access the data via open-source platforms like FathomNet, an image database that uses data-processing algorithms to help process the backlog of visual data.

In the future, this new technology could usher in an era of realtime ocean imagery processing. In doing so, the AI-powered solution could indirectly help promote effective marine stewardship and conservation. In fact, a long-term goal of Ocean Vision AI is to not only accelerate discoveries through the automatic analysis of videos and images but also to make this analysis available to a broad community of interested parties.

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