Digital Twin for Marine Fish Farming

Fearghal O'Donncha: Fearghal is a Research Scientist and Technical Lead at IBM Research Europe – Ireland. His work focuses on applying AI, hybrid cloud, accelerated discovery, and quantum computing to real-world challenges. A core research interest is the development of human-centred digital twin technologies for environmental systems such as ships, ports, and fish farms. These virtual models allow rapid exploration of different management and environmental scenarios, helping to identify optimal strategies.He is a Chartered Engineer and holds a PhD from the National University of Ireland, Galway. Fearghal has published over 80 scientific articles and he holds more than 50 patents. He leads global patenting in AI Engineering at IBM.Martin Føre: Martin is an associate Professor at the Norwegian University of Science and Technology (NTNU), Department of Engineering Cybernetics. He holds an MSc (2006) and a PhD (2011) within Engineering Cybernetics from NTNU and before rejoining NTNU in 2019, he worked as a Research Scientist/Senior Research Scientist at SINTEF Ocean. Throughout his research career, he has specialised towards the application of cybernetic methods and control systems components in aquaculture situations, and he had a central role in the development of the Precision Fish Farming (PFF) concept for finfish aquaculture.Jon Grant: Jon was a Professor of Oceanography at Dalhousie University (Canada). He earned his BSc in Zoology from Duke University in 1976 and his PhD in Biology from the University of South Carolina in 1981. Grant joined Dalhousie as a NATO Postdoctoral Fellow in 1981, became a Full Professor of Oceanography in 1997, and held multiple positions that reflected his international leadership in aquaculture research. He was an outstanding scientist, publishing over 200 scientific papers and supervising more than 50 Master's and PhD students.

• Part I. On the Farm.- Chapter 1. Fish Health and Welfare Monitoring for Potential Digital Twins.- Chapter 2. Aquaculture Robotics – Challenges, Opportunities and Future Prospects and the Role of Digital Twin Technology and Autonomous Solutions.- Part II. In the Cloud.- Chapter 3. Machine Learning in Fish Farming.- Chapter 4. Simulation Modelling and Analysis for Aquaculture.- Chapter 5. Hybrid Analysis and Modeling for Aquaculture.- Part III. Precision Fish Farming.- Chapter 6. Digital Twin for Aquaculture.- Chapter 7. Climate Change, Marine Aquaculture, and the Digital Twin.- Chapter 8. Supply Chain for Aquaculture.- Chapter 9. Future of Intensive Pen Aquaculture.