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A land demonstration of a low cost ocean sensor, Maka Niu

Access to data collection is one of the primary barriers to deep-sea exploration. We are creating low-cost, easy-to-use deep-sea systems that gather the most critical data to inform environmental decision-making.

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Deep-sea fish surrounded by eggs

The 2022 Global Deep-Sea Capacity Assessment, conducted by the Ocean Discovery League, is a baseline assessment of the technical and human capacity for deep-sea exploration and research in every coastal area with deep ocean worldwide.

A web of connected light blue dots against a dark blue diagram.

Enormous amounts of ocean video have been collected in the last few decades, but little has been viewed or analyzed. We are developing AI-driven tools to dramatically accelerate analysis of existing and newly acquired ocean video and imagery.

Deep sea creature.

The current expense of studying the deep seas stymies many research initiatives, so scientists have developed a low-cost imaging and sensor device to make access to the deep sea more equal. Katy explains the how the idea was developed and what the future of Maka Niu looks like. 

 

Deep sea fish and egg sack

The 2022 Global Deep-Sea Capacity Assessment includes online survey and manual research data for 186 geographical areas divided into six global regions: Europe, Asia, Northern America, Africa, Oceania, and Latin America & the Caribbean. 

Students developing a deployment stucture for a low cost ocean sensor.

In partnership with Sharks Pacific, ODL is currently co-hosting a workshop for Cook Islanders ages 16-24 in ocean exploration, technology, and research using our Maka Niu camera and other technology.

Scuba diver with a low cost ocean sensor on the surface of the water.

Hakai Magazine profiles Ocean Discovery League's work on Maka Niu and other low-cost, deep ocean sensors to broaden access to deep-sea exploration by removing the barrier of affordability.

An example of machine learning detection of deep-sea footage

ODL is part of a multi-disciplinary team recently awarded a $5M NSF Convergence Accelerator Grant to develop Ocean Vision AI (OVAI). OVAI uses the power of artificial intelligence to process ocean imagery.

A screenshot of the FathomNet webpage

The new paper in Nature Scientific Reports, "FathomNet: A global image database for enabling artificial intelligence in the ocean," documents our work on FathomNet, the open image database for training machine learning algorithms to help analyze ocean images and video. 

A schematic diagram of a low cost ocean sensor, Maka Niu

In this paper, we detail and provide open source access to the mechanical, electrical, and digital control design for the Maka Niu system, including the internal 3D-printed dry chassis; the battery management and sealed inductive charging system; and the Raspberry Pi camera and control subsystems.

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Ocean Discovery League recently participated in the fourth Young Explorers Program with OceanX aboard OceanXplorer providing hands-on research and mentorship opportunities to 15 university students in the fields of storytelling, marine biology, and ocean exploration.

Opportunities

Ocean Discovery League highlights opportunities throughout the ocean exploration community. If you have an opportunity or event you'd like us to feature, please submit it here!

We are proud to partner with Experiment on the Ocean Solutions Fund. This fund provides a fundraising platform for local ocean projects worldwide. 

​The Nautilus Science and Engineering Internship Program (SEIP) aims to train and provide real-world experience for community college, undergraduate, and graduate students studying ocean sciences, technology, engineering, and video in the at-sea environment.

Deadline: January 3, 2025

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