Project description
Automatic onboard sorting solution for sustainable fisheries
The digital revolution of the fisheries sector will one day equip fleets with cameras, sensors and other smart instruments to gather data. Currently, the vast majority of fisheries do not make use of real-time data. In this context, the EU-funded SEASCANN project will develop a game-changing system to automate the onboard grading process, which is currently handled manually by fishermen. Specifically, the SEASCANN process is fully automatic (one fish per second), increasing yields and reducing post harvesting loss. Prototypes have been tested successfully in vessels for North Atlantic species (cod, haddock, pollock, hake, mackerel, herring), with data being transferred in real time to standardised databases. The solution will ensure the sustainability of fisheries management, which is essential to preserve wild fish stocks.
Objective
Fishing fleets must handle great amounts of fish as fast as possible to prevent deterioration of quality, assess catch’s worth, prepare next processing and marketing steps, and report catch to the authorities. Today, this labour-intensive, time-consuming and subjective process is conducted by fishermen. By speeding up the onboard grading process and unleashing the potential of real-time data, SEASCANN is a game-changer for the fish value chain: fully automatic, it provides a high throughput (1 fish per second), saves 35% labour costs, and yields a high-quality product avoiding almost 100% of post-harvesting loss. With SEASCANN, Skaginn delivers an automated vision system that sorts large quantities of fish based on species, size and quality, increasing quality and value. SEASCANN also makes real-time catch information available for fishing companies, processors, researchers & authorities, assisting decision-making at several levels. SEASCANN enables fisheries turn from single- to more sustainable multi-specific businesses, and benefits society by collecting reliable fisheries-related data. While two prototypes have been already implemented in vessels, the objectives now are to achieve a completely-automatic solution with accuracy of 99% for seven North-Atlantic species (cod, haddock, pollock, hake, mackerel, herring), with data being transferred in real-time to standardised databases. The solution will be improved to meet the industry demands of compactness, scalability and suitability for vessels’ retrofits.
Fields of science
- natural sciencesbiological sciencesmarine biology
- agricultural sciencesagriculture, forestry, and fisheriesfisheries
- engineering and technologymaterials engineeringcolors
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencesbiological scienceszoologyichthyology
Programme(s)
Funding Scheme
SME-2 - SME instrument phase 2Coordinator
300 AKRANES
Iceland
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.