AI Monitoring of Fishing on the Edge
Mobilizing AI and Edge Technologies to Advance Near Real-Time Electronic Monitoring Footage Review
The health of our oceans and the communities and economies that depend on them hinges on our ability to sustainably manage industrial fisheries. Yet for decades, fisheries managers have lacked timely and reliable data to keep pace with the complexity of modern fishing operations. This initiative marks a transformative leap forward, demonstrating how artificial intelligence (AI) can be harnessed not just to streamline data collection on catch activity, but to fundamentally reshape how we manage industrial fishing.
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By deploying an AI-powered system capable of analyzing electronic monitoring (EM) footage directly onboard longline vessels, this initiative brings near real-time visibility to one of the most opaque corners of the seafood supply chain.
The implications for conservation are profound. With species-level catch counts that rival expert human reviewers and risk profiles delivered within hours of fishing activity, managers are no longer forced to rely on delayed or inaccurate self-reported catch data. Instead, they can act swiftly to enforce quotas and deter illegal fishing. Beyond compliance, these rapid insights open the door to dynamic management strategies. In short, the system equips decision-makers with the timely, granular intelligence needed to move from data-poor management to proactive stewardship.
The system is built to work alongside human experts, not replace them. EM reviewers remain in the loop to validate AI predictions, ensuring that final catch assessments are grounded in professional judgment. By combining machine efficiency with expert oversight, the system delivers both scalability and accountability, reinforcing trust in the data that underpin fisheries management.
The AI-powered system is a transferable and publicly available solution that all stakeholders can adopt and iterate on. Its flexible, modular architecture and reliance on open-source tools enable it to be reconfigured for different target species and monitoring goals. All components, from the models to the reporting logic, were designed with reuse and scalability in mind to lower barriers to adoption and enable broad, equitable access.
By making the technology freely available, The Nature Conservancy is aiming to empower global longline fisheries operations to harness AI-enabled electronic monitoring for smarter, more sustainable management practices. To learn more about how the AI-powered system works and how you can access this publicly available solution to adopt and iterate on, see the report linked below titled Monitoring Fishing Activity on the Edge. To learn more about how the AI-powered system can be paired with simple traceability hardware to provide industry and regulators with valuable data on seafood product verification, risk, and quality, see the report linked below titled First-Mile Transparency & Traceability on the Edge
In an era of accelerating environmental change and growing demand for sustainable marine-based protein, this AI-powered system demonstrates meaningful advancement in fisheries monitoring and management. It’s a promising step toward a future where sustainable, global industrial fishing is not just an aspiration but a standard we achieve together.
This critical work is made possible through collaboration with the Patrick J. McGovern Foundation and the Bezos Earth Fund. See the news release.
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