Journal of Robotics, Networking and Artificial Life
Online ISSN : 2352-6386
Print ISSN : 2405-9021
Digital Transformation of Feeding Control Knowledge in Marine Aquaculture using Current Sensors
Dominic B. Solpico Yuya NishidaKazuo Ishii
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ジャーナル オープンアクセス

2022 年 9 巻 2 号 p. 143-153

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Improving the efficiency of fish feeding contributes to achieving sustainable expansion of the aquaculture industry. However, expert knowledge on feeding remains reliant on experience. This paper presents a new approach of applying digital transformation (DX) on such knowledge by measuring underwater currents induced by fishes as indicator of their hunger. A prototype sensor suite consisting of current sensors, cameras, and an inertial measurement unit (IMU) was constructed to measure the currents around the fish cage, measure the motion of the suite, and record fish activity, particularly during feeding. An initial experiment was performed in two fish cages during feeding activity. Current measurements were collected and analyzed together with the recorded videos to relate the changes in current to the feeding activities. Results suggest that the currents increase around when feeding was started continuously and decline to zero around when it was stopped. However, more data needs to be collected and analyzed for a better understanding of the relationship between the changes in current and fish activities so it can be used to optimize the feeding decisions of fish farmers.

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© 2022 ALife Robotics Corporation Ltd.

この記事はクリエイティブ・コモンズ [表示 - 非営利 4.0 国際]ライセンスの下に提供されています。
https://creativecommons.org/licenses/by-nc/4.0/deed.ja
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