4 Fisheries Monitoring System

Author

Lancelot Blondeel

Building a Digital Twin of the Ocean begins with data. In the fisheries sector, large volumes of information are collected onboard vessels, yet much of it is fragmented, inconsistent, or underutilized. To unlock its full value, this data must be standardized, integrated, and continuously updated.

This section provides a practical roadmap for setting up a real-time monitoring system for active fisheries—the first and most essential step toward a Digital Twin.

Why Start with Monitoring?

A Digital Twin is a dynamic, data-driven representation of a physical system. In fisheries, it can help simulate fishing behavior, predict catch outcomes, optimize fuel use, and even assess ecological impacts.

But a twin is only as good as the data that feeds it. The foundation is real-time, high-resolution monitoring data—capturing what truly happens on the vessel, in the water, and at the gear level. Without this, advanced modeling or simulation has little value.

This section focuses on that foundation: how to design and implement a monitoring system onboard mobile (active gear) fisheries. It draws from the Belgian VISTools project—a multi-year collaboration between ILVO, technology partners, and the fishing sector—and reflects best practices in scientific monitoring and fisheries management.

For more on how to extend monitoring into a full digital twin, see the later chapters.

Who This Section Is For?

This section is designed for fisheries scientists, managers, policymakers, and technology partners involved in modernizing data collection in active fisheries.

It is particularly relevant to operations using mobile (active) gears, such as:

  • Beam trawls
  • Otter trawls
  • Dredges
  • Seines

It does not cover passive or static gear fisheries (e.g., gillnets, traps), which require different monitoring logic and data flows.

What This Section Covers?

  • The role of monitoring in building a digital twin
  • Core system components: sensors, data transfer, and visualization (Power BI)
  • Lessons learned from VISTools across 37 operational beam trawl vessels
  • Best practices for data governance and integration