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http://dx.doi.org/10.14775/ksmpe.2020.19.07.106

Big Data Analysis on Oyster Growth and FLUPSY Environment  

Yoo, Hyun-Joo (Institute of Industrial Technology Development, Dong-Eui University)
Zhang, Sung-Uk (Automotive Engineering, Dong-Eui University)
Jung, Sun-Jin (SEABANK CO., LTD.)
Publication Information
Journal of the Korean Society of Manufacturing Process Engineers / v.19, no.7, 2020 , pp. 106-111 More about this Journal
Abstract
In the era of the fourth industrial revolution, the application of big data analysis technology is crucial in various industries. In this regard, considerable research is necessary to improve aquafarming productivity, particularly in fish culture, which is one of the primary industries in the world. In this study, a sample experiment using a flop was conducted to improve oyster productivity in fish farms, and a flush was installed in an environment similar to aquaculture farms. Thereafter, the temperature data of the water environment where the formation of burrows considerably improved were collected; the growth rate of burrow seeds was also measured. The gathered experimental data were examined by time series data analysis. Finally, a system that visualizes the analysis results based on big data is proposed. In accord with the results of this study, it is expected that more advanced research on the productivity improvement of oyster aquafarming will be performed.
Keywords
Oyster Aqua-farming; Big Data; Visualization Data;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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