Abstract
In the process of Recirculating Aquaculture System (RAS), artificial feeding method has many problems, such as inappropriate feeding rhythm and waste of bait, which seriously affect the growth of fish. In order to tackle this problem, we designed an intelligent feeding algorithm applied to the RAS. First, the feeding frequency of fish in the culture pools and the amount of residual bait are acquired by processing the feeding image and video data captured by the camera on top of the culture pools by computer vision method. Then, the subsequent feeding amount are determined by the heuristic algorithm based on the amount of residual bait, the feeding frequency of fish and the other key parameters. The experimental results show that the intelligent feeding algorithm can save about 15% bait than the traditional manual feeding method without affecting the growth of fish.
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Acknowledgements
This research was supported by Chongqing Municipal Education Commission (KJCX2020035). Open project of Chongqing Technology and Business University (KFJJ2019053, 2156004). Teaching reform project of Chongqing Technology and Business University (212027, 212017). Thanks to Junfeng Zeng and Yufeng Zhang for their work in algorithm model construction and experiment.
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Yang, J., Wu, H., Yang, J., Zhou, Y., Shen, Y. (2022). Intelligent Feeding Algorithm for Recirculating Aquaculture System Based on Deep Learning. In: S. Shmaliy, Y., Abdelnaby Zekry, A. (eds) 6th International Technical Conference on Advances in Computing, Control and Industrial Engineering (CCIE 2021). CCIE 2021. Lecture Notes in Electrical Engineering, vol 920. Springer, Singapore. https://doi.org/10.1007/978-981-19-3927-3_39
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DOI: https://doi.org/10.1007/978-981-19-3927-3_39
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