AI in Marine Monitoring and Biodiversity Assessment

CatchCam Technologies looks back on SeaFrame, a project demonstrating how AI transforms the processing of underwater data, solving a broad range of marine challenges Subsea Imaging Systems / Feature Article by CatchCam Technologies

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AI in Marine Monitoring and Biodiversity Assessment
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CatchCam Technologies understands that turning vast underwater datasets into actionable insights has long been a challenge for marine industries.

SeaFrame, an innovative AI-powered computer vision software, is transforming this landscape by enabling the rapid analysis of hours of underwater footage. From enhancing sustainable fishing practices to advancing biodiversity assessments, SeaFrame represents a major leap forward in how humans manage and understand ocean ecosystems.

Bridging Technology and Marine Challenges

Developed through a five-month project funded by Innovate UK, SeaFrame is the product of collaboration between technology developers and marine professionals. Its mission: to simplify underwater monitoring by automating the detection of critical events such as species movement, gear performance, and biodiversity shifts.

For fishers, this means identifying gear behaviour and bycatch events with ease. For scientists, it accelerates biodiversity assessments that would otherwise take months of manual analysis.

Transforming Video into Actionable Ocean Data

Underwater cameras, like the CatchCam developed by CatchCam Technologies, are indispensable tools for fishing and marine research. They provide a window into underwater environments, but the sheer volume of footage can overwhelm operators.

For fishing vessels, CatchCam captures insights into gear behaviour, helping to mitigate bycatch and assess seabed impact. These vessels often record upwards of 40 hours of footage per trip, with only a fraction yielding actionable data. Similarly, marine researchers collect massive datasets, with less than 1% typically capturing significant activity.

SeaFrame addresses this challenge by automating video analysis, significantly reducing review time. By identifying moments of interest with pinpoint accuracy, the software ensures that critical information is not lost in the flood of data.

The AI Behind SeaFrame

At the core of SeaFrame lies a robust library of training footage sourced from CatchCam deployments worldwide. This diverse dataset encompasses real-world ocean conditions, enabling the software to adapt to complex environments.

SeaFrame’s algorithm uses machine learning and deep learning techniques to analyze underwater video and detect significant events such as fish movement, gear interactions, and lighting changes. The software generates an “interestingness” graph, which scores video segments based on activity levels. This approach streamlines the review process, allowing operators to focus on decision-making rather than laborious video analysis.

Even in challenging conditions, such as murky waters or chaotic environments, SeaFrame delivers reliable results. Its ability to function with low frame rates and suboptimal video quality underscores its practical utility.

 

Enhancing Sustainability Through Precision

SeaFrame’s standout feature is its capability to detect trawl contact with the seabed, a critical insight for minimizing environmental impact. By analyzing footage captured by fishers deploying CatchCam on trawl gear, the software has been fine-tuned to address this industry-specific need.

Whether it’s identifying moving fish, monitoring gear performance, or detecting changes in underwater lighting, SeaFrame provides an adaptable solution for sustainable fishing and ecosystem monitoring. Its high accuracy and reliability position it as a valuable tool for promoting responsible marine practices.

Collaborative Innovation: A Model for the Future

The success of SeaFrame is a testament to the power of collaboration. CatchCam Technologies worked closely with a dedicated team — including Aran Dasan, Tom Rossiter, Chris Lewis, Dylan Van Bramer, Pranali Dhane, Lachlan Stibbard Hawkes, Sarah Ready, and Darren McClements — to bring this project to life.

While the initial project has concluded, CatchCam Technologies continues to develop tailored tools for the fishing and marine research sectors. SeaFrame’s success highlights the potential of targeted, AI-driven solutions to address real-world challenges in marine monitoring and sustainability.

A New Era of Marine Monitoring

SeaFrame exemplifies how technology can reshape ocean science. By reducing environmental impact, improving data accessibility, and enhancing operational efficiency, it offers a glimpse into the future of marine monitoring.

In an era where remote sensing and sustainable practices are paramount, SeaFrame sets a new standard for underwater data analysis. As AI technologies continue to evolve, innovations like SeaFrame will play a vital role in protecting marine ecosystems and advancing ocean research.

Read the original article on the CatchCam Technologies website.

Posted by Abi Wylie Edited by Abigail Wylie, Editor and Copywriter experienced in digital media with a keen interest in ocean science technology. Connect & Contact

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