A Predictive Method for Site Selection in Aquaculture with a Robotic Platform

The aquaculture industry significantly impacts human life and social development since it provides excellent resources and continues to grow for our needs. To improve production efficiency and minimize risk, suitable site selection in aquaculture tends to be more desirable. This paper proposes a predictive method based on the environmental sampling information to justify the site condition for aquaculture. A robotic platform is designed to automatically patrol the water body with sensors sampling the environment information to achieve the above-mentioned accomplishment. Based on the obtained data, a machine learning model is trained and further used to assess the probability. Finally, potential sites could be selected for the future aquaculture industry. Both the predictive method and the robotic platform have been tested in an outdoor lake, and the results verified their feasibility. Both the platform and the prediction method could be applied to increase the site selection efficiency, thus promoting the aquaculture industry's development.