Aquaculture with Artificial Intelligence: Emerging Technologies for Sustainable Industry Development will play in aquaculture and aquaculture-adjacent sectors in the coming years. The aquaculture industry faces various challenges, including environmental concerns, disease management, and resource optimization, and integrating AI into aquaculture practices can improve industry efficiency, sustainability, and overall productivity. This book explores how AI technologies such as machine learning for predictive analytics, computer vision for monitoring aquatic environments, and robotics for automated tasks can streamline various aspects of aquaculture requiring monitoring, management, and decision-making. Aquaculture with Artificial Intelligence: Smart Aquaculture is co-authored by a diverse team of experts bridging disciplines in aquaculture, aquatic immunology, biotechnology, and artificial intelligence. Early chapters provide a thorough introduction to the aquaculture industry to provide critical context for all audiences. Central chapters explore machine learning, bioimaging, drone technology, bioengineering, OMICs technologies, big data, and other AI technologies emerging in aquaculture. Global case studies highlight the practical applications of AI to various aspects of aquaculture operations, including automated feeding, water quality monitoring, disease protection, and precision aquaculture. The book concludes with a look to the future of the industry, research gaps, and opportunities for continued research. This is an essential read for aquaculturists, environmental scientists, data scientists, and roboticists interested in the intersection of aquaculture and AI.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Foreword I - p. xiii 7. Foreword II - p. xv 8. Foreword III - p. xvii 9. 1. Aquaculture—An introductory text - p. 1 10. 2. Technological update in aquaculture - p. 19 11. 3. Smart and digitalizing the aquaculture - p. 37 12. 4. Introducing artificial intelligence toward aquaculture - p. 51 13. 5. Learning algorithms of AI and ML for aquaculture - p. 63 14. 6. Bioimaging and AI integration for aquaculture disease control and monitoring - p. 81 15. 7. AI integrating drone technologies for feeding technology - p. 95 16. 8. Enhancing aquatic animal health with AI-integrated bioengineering - p. 109 17. 9. Handling IoT toward the aquaculture - p. 125 18. 10. OMICS technologies for aquaculture - p. 141 19. 11. Aquaculture drug design using AI and ML methods - p. 159 20. 12. Blockchain, cloud computing, and big data for aquaculture - p. 175 21. 13. Aquaculture and AI integration in industrial aspects - p. 193 22. 14. Future directions - p. 209 23. Index - p. 225
Aquaculture with Artificial Intelligence: Emerging Technologies for Sustainable Industry Development will play in aquaculture and aquaculture-adjacent sectors in the coming years. The aquaculture industry faces various challenges, including environmental concerns, disease management, and resource optimization, and integrating AI into aquaculture practices can improve industry efficiency, sustainability, and overall productivity. This book explores how AI technologies such as machine learning for predictive analytics, computer vision for monitoring aquatic environments, and robotics for automated tasks can streamline various aspects of aquaculture requiring monitoring, management, and decision-making. Aquaculture with Artificial Intelligence: Smart Aquaculture is co-authored by a diverse team of experts bridging disciplines in aquaculture, aquatic immunology, biotechnology, and artificial intelligence. Early chapters provide a thorough introduction to the aquaculture industry to provide critical context for all audiences. Central chapters explore machine learning, bioimaging, drone technology, bioengineering, OMICs technologies, big data, and other AI technologies emerging in aquaculture. Global case studies highlight the practical applications of AI to various aspects of aquaculture operations, including automated feeding, water quality monitoring, disease protection, and precision aquaculture. The book concludes with a look to the future of the industry, research gaps, and opportunities for continued research. This is an essential read for aquaculturists, environmental scientists, data scientists, and roboticists interested in the intersection of aquaculture and AI.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Foreword I - p. xiii 7. Foreword II - p. xv 8. Foreword III - p. xvii 9. 1. Aquaculture—An introductory text - p. 1 10. 2. Technological update in aquaculture - p. 19 11. 3. Smart and digitalizing the aquaculture - p. 37 12. 4. Introducing artificial intelligence toward aquaculture - p. 51 13. 5. Learning algorithms of AI and ML for aquaculture - p. 63 14. 6. Bioimaging and AI integration for aquaculture disease control and monitoring - p. 81 15. 7. AI integrating drone technologies for feeding technology - p. 95 16. 8. Enhancing aquatic animal health with AI-integrated bioengineering - p. 109 17. 9. Handling IoT toward the aquaculture - p. 125 18. 10. OMICS technologies for aquaculture - p. 141 19. 11. Aquaculture drug design using AI and ML methods - p. 159 20. 12. Blockchain, cloud computing, and big data for aquaculture - p. 175 21. 13. Aquaculture and AI integration in industrial aspects - p. 193 22. 14. Future directions - p. 209 23. Index - p. 225
