Technology Using Artificial Intelligence (AI) to Enhance Productivity and Sustainability in Atlantic Salmon Production and Challenges From Knowledge Management

Abstract Aquaculture fish proteins have considerably increased in volume and importance. High-tech artificial intelligence (AI)-based growth has enhanced the production productivity of Atlantic salmon; however, serious issues have arisen regarding sustainability, such as fish health and emissions. Surveillance of salmon in cages is crucial for conducting managerial tasks such as developing biomass and optimizing feed. In addition, fish health must be monitored, which is mainly achieved with underwater cameras as the main technological solution. Sonar equipment has recently been introduced at production sites, providing improved surveillance based on AI technologies. This led to the following research questions: (1) What characterizes the most recent solutions for analyzing the integration of sustainability and productivity needs using AI-based lasers for surveillance in salmon-based aquaculture? (2) How do these solutions challenge knowledge management? Our study is based on experience gained from installing sonar equipment on aquaculture sites through the high-tech company CageEye. Three key approaches play crucial roles in the development of AI-based sonars for use in aquaculture: (1) image processing, (2) machine learning, and (3) deep learning. Experience has demonstrated that operators and site managers must have a fundamental understanding of how AI is used. Therefore, companies must allocate resources to their employees to ensure the necessary knowledge level. Knowledge management challenges have changed as a result of modern management and human resource management (HRM) principles as well as substantial increases in education and knowledge levels.