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Chung-Cheng Chang



Project Name

Applying artificial intelligence (AI) techniques to implement a practical Smart Cage Aquaculture Management System


Project Intro

    The present research project aims to apply state-of-the-art artificial intelligence (AI) techniques to implement a practical Smart Cage Aquaculture Management System (SCAMS) useful for minimizing the cost of farming and maximizing the harvesting, and to further facilitate our country establishing a near-shore aquaculture industry of world-class competitiveness. Economic benefits of SCAMS include: to trigger the transformation of Taiwan's fishery, enabling fishermen to obtain real-time information for achieving the best aquaculture performance, as well as promoting Taiwan's current saturated fishing production. In addition, an AI farming services company will be established upon the completion of this project to provide fishermen with various technical services. R&D personnel concerning this project includes: an AI team, an automation team and an aquaculture team, all members of which are experienced scholars associated with NTOU (National Taiwan Ocean University), the aforesaid three teams will be joined by related enterprises such as the Taiwan-headquartered shrimp feed and farming giant Grobest group. NTOU also owns the oldest farming department in Taiwan and the various advanced research centers, Grobest group has both near-shore and offshore aquaculture experiences and skilled professional team, all these advantages make us superior over other competitors in completing the proposed research project.

    This four-year project is planned to accomplish the following two tasks: (1) to apply state-of-the-art AI techniques to the construction of an optimal aquaculture model, which is characterized by five sub-systems: Smart Feeding, Smart Image Behavior Monitoring and Analysis, Smart ROV, Smart Drone, and Big Data Analysis, the first four sub-systems collect data in real-time through various types of sensing components, these data will be uploaded to NTOU Cloud center and selectively labeled by the aquaculture team for the subsequent AI training at NCHC (National center for High-performance Computing) using state-of-the-art machine learning methods (e.g. deep learning) (2) enabling users to use mobile devices for monitoring the status of cages in real-time, herein an IoT architecture will be employed to integrate the Big Data for realizing the abovementioned practical benefits of intelligent cage aquaculture.


Project Host


Principal Investigator 

Chung-Cheng Chang,  Professor



Co-Principal Investigator 

Jung-Hua Wang, Professor



Jenq-Lang Wu, Professor



Tzong-Dar Wu, Assistant professor



Yi-Zeng Hsieh, Assistant professor



Shyi-Chy Cheng, Professor

Computer Eng. Dept, NTOU


Chin-Chun Chang, Associate Professor

Computer Eng. Dept, NTOU


Jih-Gau Juang, Professor



Yii-Shing Huang, Associate Professor

Aquaculture Dept, NTOU


 Chyng-Hwa Liou, Associate Professor

Aquaculture Dept, NTOU


Cheng-Ting Huang, Assistant Professor

Aquaculture Dept, NTOU


Te-Hua Hsu Ph.D, Research Assistant

Center of Excellence for the Oceans, NTOU 


Website To Link



Host's Public Contact Method


E-mail:This email address is being protected from spambots. You need JavaScript enabled to view it.


Representative Pictures Of The Research




70101 台南市東區大學路1號 成功校區 資訊工程系 舊館1樓4220辦公室
No.4220, CSIE Dept (old building), No.1, University Road, Tainan City 701, Taiwan (R.O.C)

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