Applying Artificial Intelligence (AI) Techniques to Implement a Practical Smart Cage Aquaculture Management System
Chung‐Cheng Chang, Jung-Hua Wang, Jenq‐Lang Wu, Yi‐Zeng Hsieh, Tzong‐Dar Wu, Shyi-Chy Cheng, Chin-Chun Chang, Jih‐Gau Juang, Chyng‐Hwa Liou, Te‐Hua Hsu, Yii-Shing Huang, Cheng‐Ting Huang, Chen‐Chou Lin, Yan‐Tsung Peng, Renjie Huang, Jia‐Yao Jhang, Yen-Hsiang Liao, Chin-Yang Lin
Abstract
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.