Journal of Aquaculture Engineering and Fisheries Research received 336 citations as per google scholar report
Faizan Hasan MUSTAFA, Awangku Hassanal Bahar Pengiran BAGUL, Shigeharu SENOO, Rossita SHAPAWI
This paper reviews smart fish farming systems that demonstrate how complex science and technology can be made easy for application in seafood production systems. In this context, the focus of this paper is on the use of artificial intelligence (AI) in fish culture. AI mimics some of the capabilities of human brain via its Artificial Neural Network (ANN) in performing certain tasks in a fish hatchery that are crucial for aquaculture systems. Water quality is of utmost importance for survival, growth and all other living activities of captive stocks of fish. The AI-based systems can be designed for controlling the main parameters of water quality such as salinity, dissolved oxygen, pH and temperature. This systems approach uses software application that runs on an application server connected to multi-parameter water quality meters such as those offered by YSI. The software captures these parameter values from YSI device and checks if they are within the optimum range. If not, then an alarm system is triggered for immediate remedial action that can be executed by personnel handling the hatchery management roles. This improves accuracy, saves cost and action time to ensure sustainability life-supporting system in the hatchery. Despite complexity in evolving this system, the application is simple enough to be operated by an organized fish farming community. Because this study introduces a rather new approach to aquaculture management, presentation of a detailed background scenario was deemed necessary to put the pertinent issues in the right perspective.
Select your language of interest to view the total content in your interested language