http://scholars.ntou.edu.tw/handle/123456789/17796
Title: | Applying Artificial Intelligence (AI) Techniques to Implement a Practical Smart Cage Aquaculture Management System | Authors: | Chang, Chung-Cheng Wang, Jung-Hua Wu, Jenq-Lang Hsieh, Yi-Zeng Wu, Tzong-Dar Cheng, Shyi-Chy Chang, Chin-Chun Juang, Jih-Gau Liou, Chyng-Hwa Hsu, Te-Hua Huang, Yii-Shing Huang, Cheng-Ting Lin, Chen-Chou Peng, Yan-Tsung Huang, Ren-Jie Jhang, Jia-Yao Liao, Yen-Hsiang Lin, Chin-Yang |
Keywords: | Cageculture;Aquaculture;AI;IoT;Cloud system;ROV | Issue Date: | Oct-2021 | Publisher: | SPRINGER HEIDELBERG | Journal Volume: | 41 | Journal Issue: | 5 | Start page/Pages: | 652-658 | Source: | J MED BIOL ENG | Abstract: | Purpose This paper presents our team's results to establish an AIoT smart cage culture management system. Methods According to the built system, the farmed field information is transmitted to the data platform of Ocean Cloud, and all collected data and analysis results can be applied to the cage culture field after the bigdata analysis. Results This management system successfully integrates AI and IoT technologies and is applied in cage culture. Using underwater biological analysis images and AI feeding as examples, this paper explains how the system integrates AI and IoT into a feasible framework that can constantly acquire information about the health status of fish, survival rate of fish, as well as the feed residuals. Conclusion The results of our research enable the aquaculture operators or owners to efficiently reduce the feed residual, monitor the growth of fish, and increase fish survival rate, thereby increasing the feed conversion rate. |
URI: | http://scholars.ntou.edu.tw/handle/123456789/17796 | ISSN: | 1609-0985 | DOI: | 10.1007/s40846-021-00621-3 |
Appears in Collections: | 水產養殖學系 機械與機電工程學系 資訊工程學系 通訊與導航工程學系 電機工程學系 14 LIFE BELOW WATER |
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