Study on Adapting the Auto Feeding System for Sillago Japonica to Actual Aquaculture Environment

Sillago japonica is a popular fish used in Japanese cuisine, and a stable aquaculture method for growing fish of more than 25 cm in length, which are traded at high prices, may help to revitalize the aquaculture industry. However, it is difficult to raise Sillago japonica in aquaculture using conventional simple automatic feeding systems. Recently, AI and IoT have been used in aquaculture. Thus, we have been developing a fish distribution recognition system using image recognition AI: preprocessing of an automatic feeding control AI to optimize feeding timing. In this study, both fish positional recognition and fish directional recognition were achieved by recognizing the position of the head to fine-tune feeding using AI. Moreover, to adapt the system to the actual aquaculture environment, we implemented a mechanism to operate the actual feeder according to the instructions of the AI developed on the simulator. We mainly studied the following two items for practical use. First, we studied the mechanical operation of an actual feeder. Second, we built a wireless communication system between the feeding control and the feeder action processes.