Digital transition of catch monitoring in European fisheries

Project Information

EveryFish

Grant agreement ID: 101059892

DOI

10.3030/101059892

EC signature date 3 June 2022

Start date 1 January 2023

End date 31 December 2026

Funded under

• Food, Bioeconomy Natural Resources, Agriculture and Environment

Total cost

€ 4 369 882,50

EU contribution

€ 3 880 352,00

Coordinated by

SINTEF OCEAN AS
Norway

Periodic Reporting for period 2 - EveryFish (Digital transition of catch monitoring in European fisheries)

Reporting period: 2024-07-01 to 2025-12-31

Summary of the context and overall objectives of the project

European fisheries face increasing demands for transparency, sustainability and accountability. Reliable information about what is caught, where and how is essential for managing fish stocks, protecting marine ecosystems and ensuring fair competition. At the same time, monitoring systems must be practical and cost-efficient for fishers operating in demanding conditions at sea.

EVERYFISH addresses these challenges by developing and testing digital technologies for automatic catch registration in different European fisheries. The project supports the modernised EU fisheries control framework, which strengthens electronic reporting, traceability and digital monitoring requirements. It also contributes to broader EU sustainability objectives, including the EU Biodiversity Strategy for 2030 and international commitments to sustainable fisheries management.

The overall objective is to develop and validate interoperable technologies that improve monitoring, control and sustainability of fisheries. These include artificial intelligence (AI) systems for automatic species identification, size and weight estimation, detection of unusual fishing patterns, and secure data sharing.

Ten technologies are being developed and tested in tropical tuna, pelagic, demersal, small- and mid-scale, recreational and artisinal fisheries. The project combines engineering, natural- and social sciences to ensure that solutions are technically robust, economically realistic and socially acceptable. Stakeholder workshops and field trials are used to assess operational feasibility, regulatory implications and incentives for uptake.

By improving data quality and transparency, EVERYFISH aims to strengthen stock assessments, support more efficient inspections and build trust between fishers, authorities and markets.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The EVERYFISH project has progressed from development to large-scale testing and refinement.

Smart camera systems and mobile applications have been installed and are in operation already on commercial fishing vessels in several fisheries. These systems automatically identify species, estimate size and weight, count fish and record catch data. Testing under real working conditions has generated large volumes of operational data.

AI models have been retrained using new datasets, improving performance under challenging conditions such as variable lighting, overlapping fish and vessel movement. A common digital annotation format has been finalised to ensure interoperability across systems.

Analytical tools have been developed to combine catch data with vessel tracking information in order to identify unusual fishing patterns and early results show that such tools can support more targeted monitoring approaches.

Several technologies have demonstrated high accuracy under specific conditions. For example, some onboard systems now achieve very high species recognition rates for selected fisheries, and portable scanning equipment for shellfish has shown performance comparable to or faster than manual measurements.

At the same time, challenges remain. Performance can vary depending on environmental conditions, species similarity, catch composition and equipment setup. Further optimisation is needed to reduce error margins, improve long-term operational stability and integrate systems into existing regulatory frameworks.

The project has demonstrated technical feasibility in real fisheries, but most systems are at an advanced validation stage rather than ready for full deployment. The final phase will focus on optimisation, extended trials and preparation for long-term implementation.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

EVERYFISH moves beyond existing electronic logbooks and camera systems on fishing vessels by integrating sensors and cameras for automated species recognition, size estimation, anomaly detection and secure data exchange into a coherent digital framework tested under real operational conditions.

Key advances include:

*Harmonised data standards for fish image annotation and exchange.
*AI models trained on diverse real-world fisheries data.
*Methods for detecting unusual fishing behaviour using combined catch and tracking data.
*Portable automated measurement tools for shellfish.
*A prototype distributed ledger system for traceability along the supply chain.

The project also advances knowledge on implementation conditions. It identifies economic, regulatory, technical and social factors that influence adoption of digital monitoring systems.

For further uptake, several needs have been identified:

*Continued testing and optimisation in diverse fisheries.
*Clear regulatory frameworks and interoperability standards.
*Support for standardisation and international alignment.
*Ongoing stakeholder engagement to ensure trust and usability.

The results provide a foundation for scaling digital monitoring solutions in Europe and potentially internationally.