篇名 |
Big Data Analysis on Water Quality Condition in a White Shrimp Farming Environment
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並列篇名 | Big Data Analysis on Water Quality Condition in a White Shrimp Farming Environment |
作者 | Wu-Chih Hu、Hsin-Te Wu、Jun-We Zhan、Jing-Mi Zhang |
英文摘要 | In order to prevent food shortage in the future, human kind must rely on aquafarming to compensate for shortage in marine resources. Our proposed scheme monitors water quality via the Internet of Things (IoT). Given that the survival rate of white shrimp is highly dependent on water quality, this study collects water quality-related data through the IoT sensors, including data on temperature, oxygen content, and more. The main goals of the proposed big data analysis include the following: (1) to analyze a variety of environmental factors of a culture pond and determine whether it is a suitable environment for culturing white shrimp, and (2) to analyze the correlation between a single environmental factor against other environmental factors. The above analysis should help aquafarmers examine whether a culture pond is suitable for culturing white shrimp; moreover, aquafarmers will also learn how to, when water quality deteriorates, adjust a single factor to improve the overall water quality. Experimental results indicate that the analysis performed can indeed effectively help us better understand the living environment of the white shrimp as well as how to adjust one single environmental factor in order to elevate the overall water quality. The results of this study will aid aquafarmers in obtaining a better grasp of the overall culture environment. With the water quality analysis and monitoring system to initiate relevant equipment, the livability of white shrimp has reached 37%, which is higher than that of general breeding approaches. The approach developed in this article can effectively reduce the waste of water resources and enhance the livability of white shrimp. |
起訖頁 | 1563-1573 |
關鍵詞 | Big data、White shrimp、Aquaculture、IoT |
刊名 | 網際網路技術學刊 |
期數 | 202112 (22:7期) |
出版單位 | 台灣學術網路管理委員會 |
DOI |
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