4.3 Data Transfer

Author

Lancelot Blondeel

The ILIAD North Sea Fisheries case showcases how modern sensor technology and cloud-based infrastructure can enable effective data centralization and transmission directly from fishing vessels. This section uses the case as a practical example to illustrate how such a monitoring system can be designed and implemented.


Data Centralization on the Vessel

Data centralization starts onboard fishing vessels through a network of specialized fisheries equipment and additional sensors, including GPS, towing force meters, fuel consumption meters, catch scales, weather stations, and environmental sensors like CTD (conductivity-temperature-depth) and TD (temperature-depth).

These sensors are connected to a central onboard data hub, the DB Matic Pro data concentrator. This device collects data from all sensors in real time and temporarily stores it before processing. This ensures continuous data capture even when connectivity is limited.

To maintain consistency and interoperability, the data is standardized into the PoseiDat format, allowing easy integration with cloud services. The system uses pre-processing algorithms to organize data based on timestamps, linking specific sensor readings to fishing activities such as towing, hauling, or navigation phases. More information on PoseiDAT can be found here.

Operational Considerations:

  • Ensure all onboard sensors are compatible with the central concentrator.
  • Use timestamp-matching algorithms to ensure data reliability.
  • Implement regular maintenance checks to avoid data interruptions.

Data Transmission to the Cloud Environment

In the North Sea Fisheries case, the data collected onboard is securely transmitted to ILVO’s Azure-based cloud environment using a dual communication network.

  1. Primary Communication Network:

    • VSAT Satellite Connection: Provides reliable global coverage, ensuring uninterrupted data transmission even in remote ocean regions.

  2. Secondary Communication Network:

    • 4G Cellular Network: Used for faster and cost-effective data uploads when vessels operate nearshore.

Upon arrival at the cloud environment, the data is processed using Azure SQL servers and Azure Virtual Machines, enabling real-time data ingestion. This setup supports long-term data storage and secure access through encrypted cloud accounts.

Access and Visualization:

  • Vessel owners and researchers access data through interactive dashboards built on PowerBI, offering real-time insights into fishing operations, including catch prediction, fuel consumption, and environmental monitoring.
  • ILVO’s cloud platform uses strict access control and security protocols, ensuring data confidentiality while supporting data-sharing agreements for research and policy development.

Operational Considerations:

  • Ensure secure satellite and cellular network redundancy to minimize data loss.
  • Use a reliable cloud platform with encryption and multi-factor authentication.
  • Implement dashboards that provide actionable insights for both vessel operators and researchers.

Conclusion

The North Sea Fisheries case provides a clear example of how fishing fleets can implement a robust data centralization and transmission system. By combining onboard data collection with cloud-based processing and visualization, fisheries operations can improve efficiency, sustainability, and regulatory compliance. This model can serve as a scalable solution for fisheries and marine monitoring projects globally.