The use of artificial intelligence and automation in aquaculture to increase productivity and sustainability is a relatively new idea. Modern intelligent technology's widespread usage has benefited many sectors, including aquaculture, by greatly reducing labour requirements, improving aquaculture output, and having a negligible impact on the natural environment. Machine learning is a branch of artificial intelligence that employs pre-trained model algorithms to recognise and learn characteristics from the data it encounters. Water quality monitoring, farm management systems, turbidity sensors, pH metres, feeding control methods, a fish grader for assessing and controlling fish populations, and fish disease and health management are all examples of how machine learning has been applied in smart aquaculture. The research results in this article offer a synopsis of recent smart aquaculture and intelligent technology advancements. We analysed 75 studies from the last decade on the topic of machine learning's impact on smart aquaculture. The articles focus on the research process, the findings, and the most promising new technologies that could inform the field's future.

Artificial Intelligence, Machine Learning, Fisheries