Sustainability and Circular Economy
Research and Development under Contract
Computer Vision, Interaction and Graphics
Computer vision and image processing
Computer graphics, virtual, augmented and mixed reality
FRAMEWORK
Aquaculture plays an increasingly strategic role in food security, and the production of flatfish, such as turbot, has great potential for expansion in Portugal. However, this growth requires optimisation of the reproductive process, especially in the feeding and management of broodstock, which are currently monitored visually and manually, which is imprecise, labour-intensive and stressful for the fish
In order to overcome these limitations, the iCAMBreeder project proposes the development of an intelligent monitoring system for turbot broodstock, which will not only contribute to strengthening their competitiveness by improving the turbot reproduction process, but will also drive innovative precision practices, promoting productivity, reducing environmental impacts and optimising resources.
The iCAMBreeder project will be implemented through close and complementary collaboration between a cohesive consortium, composed by FLATLANTIC, with extensive experience in the technical aspects of turbot production, and ENESII (CCG/ZGDV), an entity that brings scientific excellence and state-of-the-art methodologies in the areas of AI and VC.
PROPOSED SOLUTIONS
The main objective of the iCAMBreeder project is to develop an intelligent system for monitoring turbot breeders based on advanced AI and VC technologies for the automation and control of processes that affect the success of reproduction in captivity (e.g. feeding, behaviour assessment and maturation status).
The technological solution to be developed aims to be validated under the farming conditions of FLATLANTIC, a leading turbot producer in Portugal. To this end, four strategic objectives have been defined:
- SO1: Individual detection of fish in the farming tank.
- SO2: Feeding monitoring.
- SO3: Trajectory analysis and tracking.
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SO4: Classification of the maturity status of females in the farming tanks.
CCG/ZGDV CONTRIBUTION
CCG/ZGDV plays a central role in developing an intelligent turbot broodstock monitoring system using advanced Computer Vision (CV) and Artificial Intelligence (AI) technologies.
CCG/ZGDV leads the project's technical component, ensuring the quality, consistency and efficiency of the system from its design through to validation in a real-world environment.
Its key responsibilities include developing advanced deep learning algorithms for real-time image processing and monitoring, providing the foundation for behavioural analysis of fish in a controlled environment. CCG/ZGDV also leads the prototyping of innovative technological solutions for the accurate capture and interpretation of behavioural data.
The project enables exploration of new applications of Computer Vision (CV), Artificial Intelligence (AI), and machine learning, positioning CCG/ZGDV as a key partner in precision aquaculture solutions within a growing sector that offers significant opportunities for market expansion and long-term sustainability.