The IntelliRAS project seeks to improve the sustainability, efficiency, and resilience of land-based Recirculating Aquaculture Systems (RAS) by transitioning from experience-based management to data-driven decision-making. Through the integration of diverse real-time and historical data streams, including environmental, operational, and biological parameters, the project employs artificial intelligence and advanced statistical modeling to support predictive and adaptive management strategies.
A core focus of IntelliRAS is monitoring and interpreting fish behavior using sensor data and machine learning techniques. This enables early detection of potential health issues and disease outbreaks, as well as optimized feeding regimes that reduce feed waste and improve feed conversion ratios. The project aims to enhance fish welfare, minimize environmental impact, and improve production performance by leveraging behavioral insights and system-level data analytics.
Ultimately, IntelliRAS empowers aquaculture operators with evidence-based tools and decision support systems to support a transition toward more intelligent, sustainable, and welfare-oriented aquaculture production.