The intelligent aquaculture system utilizes the Internet of Things technology to constantly monitor water quality and weather changes, and then uses machine learning models to replicate traditional manual management experience. This not only reduces cost expenditure (personnel and resources), but also allows expert experience to be replicated on a large scale.

Moreover, the intelligent aquaculture system can be equipped with automated control technology and autonomous learning technology, allowing the farming equipment to adjust its operating state autonomously and learn how to handle different farming problems independently, thus better coping with various challenges. In addition, the system can also incorporate intelligent prediction technology to predict future changes in farming environment and demand, and make corresponding adjustments in advance to reduce losses and risks.

Traditional aquaculture management mainly relies on the experience and decisions of aquaculture experts, which are often based on intuitive management without data-driven guidance, making it difficult to replicate experiences on a large scale. With an intelligent aquaculture system, not only can expert experience be replicated on a large scale, but also a more intelligent and autonomous management approach can be achieved, further improving aquaculture productivity and quality, while reducing cost expenditure and achieving a more stable and sustainable aquaculture.