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

2022 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2022-12-05 DOI:10.1109/ROBIO55434.2022.10011913

Tong Shen, Tianqi Zhang, Kai Yuan, Kaiwen Xue, Huihuan Qian

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Abstract

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.

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基于机器人平台的水产养殖选址预测方法

水产养殖业对人类生活和社会发展产生了重大影响，因为它提供了优良的资源，并不断满足我们的需求。为了提高生产效率和降低风险，在水产养殖中更需要选择合适的场地。本文提出了一种基于环境采样信息的预测方法来确定养殖场地条件。设计了一个机器人平台，通过传感器采集环境信息，实现对水体的自动巡逻。基于获得的数据，训练机器学习模型并进一步用于评估概率。最后，可以为未来的水产养殖业选择潜在的地点。该预测方法和机器人平台已在室外湖泊中进行了测试，结果验证了其可行性。该平台和预测方法均可提高选址效率，从而促进水产养殖业的发展。

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2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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