Case-Based Reasoning in a System Architecture for Intelligent Fish Farming

Fish farmers manage assets of considerable value on a daily basis. Many aspects of the daily operation are automated in some way, such as the feeding sys- tem. Sensory equipment steadily becomes cheaper and more ubiquitous, yielding data that can be used by automated systems and for post-processing (i.e. data min- ing) to discover hidden trends in the data. However, a lot of information is only known informally by the fish farmers themselves, through years of experience. Companies that can store this information and reuse it will have an advantage; even more so if high-level human expertise can be linked to low-level sensor data. This paper presents early developments of a system that stores this informal knowledge using case based-reasoning, combined with corresponding sensor data.