Protecting Our Oceans

Protecting our wild fisheries through digital surveillance of our precious oceans.

Project Overview

Updated March 31, 2023.

The Problem

Humanity has long relied on the world’s five oceans to sustain life as well as support marine transportation, tourism, fishing and energy generation.

Together, these oceans generate goods and services worth $2.5 trillion every year, enough to make them the seventh largest economy on the planet.

However, the fisheries and aquaculture sectors that provide food across the globe and livelihoods for almost 12 per cent of the world’s population are under threat from illegal, unreported and unregulated fishing. This activity costs the ocean economy more than $23 billion a year and endangers the sustainability of marine wildlife and the fishing industry.

Illegal fishing is typically done by ‘dark vessels’, which do not broadcast their location or appear in public monitoring systems. The threat to fish stocks is real and it is growing. Currently about 30 per cent of all fish stocks are overfished, and about 60 per cent are fully fished. Unreported and undetected ocean traffic also pose human rights, human trafficking and maritime border security issues.

Protection of our oceans relies on self-reporting by vessels – where they are from, what they are catching and whether they have the right to fish in their location. Dark vessels avoid detection to commit their crimes and are aided by a lack of a comprehensive detection system to locate them.

How We Are Solving It

This project applies satellite monitoring, artificial intelligence, big data analytics and data visualization techniques such as virtual reality to recognize these vessels, blacklist them, and ultimately prosecute the owners to protect our global fisheries and marine ecosystems.

The Result

PODS was focused on creating prototype software which may either be integrated with, or connected to, the Dark Vessel Detection (DVD) system developed by MDA for the Government of Canada. Key PODS developments were designed to add to this, and included:

  • Machine learning and other methods to fuse multi-sensor information so as to determine the identity of “dark” vessels which try to avoid detection by not reporting their position and activities.
  • Machine learning methods to reveal temporal vessel operating behaviours, which can be used to determine if these behaviours are inconsistent with reported activities.
  • A new 3D immersive interface which helps Analysts better view, understand and interpret the vast range of data and analytic outputs produced by the DVD system.

The PODS project successfully demonstrated these new capabilities in a closed demonstration setting. Through this work, PODS has also built the foundation for a much more valuable and longer term collaboration among the team members, and includes proposed plans to implement and operate the PODS elements commercially in conjunction with DVD.

Project Lead

  • mdaupdatelogo e1632702369570

Project Partners

  • VizworX Logo e1632702569140
  • sfu@2x e1632697382895

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