Efficient utilization of marine resources is becoming increasingly important as sustainability requirements tighten and fish quotas become more restrictive. While modern fish processing equipment has significantly improved productivity, current gutting machines often damage internal organs, reducing the value of by-products and limiting how much of the fish can be utilized for human consumption.
SmartCut addresses this challenge by developing a fully automated gutting line that combines machine vision, artificial intelligence, and robotics. The system will analyse each fish, adapt its cutting path accordingly, and gently extract the offal while preserving high-value fractions such as liver and roe. It will also automate the process of feeding fish into the processing line.
The long-term goal is to improve resource utilization, reduce waste, increase profitability for the fishing industry, and create safer,less physically demanding working environments.
Why SmartCut matters
A significant share of seafood by-products remains underutilized, despite containing valuable resources that could be used for food production and other high-value applications. In whitefish processing, valuable materials such as roe and liver are often damaged during automated processing and are therefore downgraded to lower-value products or discarded altogether.
By enabling precise cutting and gentle extraction of internal organs, SmartCut can help transform these by-products into products suitable for human consumption, creating additional value from existing fish catches. This contributes to a more sustainable seafood industry, reduces food waste, and improves economic returns for fishers and processors.
The project also supports the transition toward increased automation in the fishing industry, reducing repetitive manual labour and improving workplace safety.
What the project will deliver
SmartCut will:
- Design a robust, digitalized gutting machine capable of withstanding the demanding maritime environment on board fishing vessels.
- Develop an adaptive cutting method that uses machine vision to adjust the cutting path and protect the offal during cutting.
- Develop an automated and gentle method for extracting and separating offal whilekeeping organs such as liver and roe intact.
- Develop a robotic feeding solution that picks fish from a pile and places them in the correct orientation for processing.
- Test the resulting system at laboratory scale, at an onshore processing plant, and on board a commercial fishing vessel.
SINTEF's role
SINTEF Digital and SINTEF Ocean contribute expertise in machine vision, artificial intelligence, robotics, automation, industrial control systems, and cybernetics. The research teams are responsible for developing and testing key technologies related to adaptive cutting, robotic fish handling, machine vision, and digital automation systems.
