The overall objective of R-Control is to conduct research that will enable ground-breaking generic methods and technologies to facilitate practical, effective, and widespread automatic catch registration to enable eff ective and risk-based resource control and sustainable resource management applicable across a wide range of fisheries.
The secondary objectives of the project are to:
• O1. Develop a 3D scanner to create "digital twins" of fish and crustaceans (i.e. shrimps, crabs).
• O2. Develop deep learning algorithms for species recognition, and weight and length estimation, whichsupport standardized automatic catch analysis systems enabled by large data sets of "digital twins" of fishand crustaceans.
• O3. Introduce generic methods for developing customized scanners that can be easily adapted to different fisheries.
• O4. Test and demonstrate automatic catch registration in specific fisheries.
• O5. Discuss institutional challenges and potential efficiency gains implications for implementing an automatic catch registration system in the fisheries.