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| 005 | 20250920172102.0 | ||
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_e _e _aBernadine Marie Bernal,Erica Eunice A. Bulaun, Christine Joy C. Del Mundo, Daniel V. Lagarto. _d _b4 _u _c0 _q16 |
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_a _aAdvancing aquaculture sustainability : IoT - Driven automation for precise water condition monitoring in ColoongI, Valenzuela fishpond. _d _b _n _c _h6 _p |
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_3 _30 _b _aunmediated _2rdamedia |
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_a _aUndergraduate Thesis: (Bachelor of Science in Electrical Engineering) - Pamantasan ng Lungsod ng Maynila. 2024. _d _b _c56 |
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_b _b _c _aABSTRACT: Pond agriculture plays a vital role in food recurity by providing an efficient means of food production. However, poor water quality and stressful conditions often leads to parasites and diseases in pond fish, causing unexpected deaths. Fish are sensitive to environmental changes, such as toxic substances, pH levels, temperature, and ammonia. Regular monitoring and management are essential to sustain productivity, ensure quality, and promote optimal fish health. This study aims to alleviate the labor burden on fish keepers and reduce mortality rates resulting toxic water conditions in fishponds that has been an issue in different part of the country, specifically where the researchers conducted their prototype testing. Water quality testing in fishponds with owners who seldom pay visits to their fishpond business and hiring fish farmers to be caretakers are the main target of this research. This research addresses the lack of precise water quality testing from traditional testing to using a senior-based prototype connected to IoT remote application for easier, precise, and more advanced testing in fishponds. The researchers focused on the following parameters-turbidity, ammonia, pH level, and temperature-that are considered important by many fish farmers based on previous studies. After thorough testing of the prototype on the chosen fishpond in Valenzuela, the researchers proved the study's objective and answered the problem's statement through the results acquired from following different types of statistical treatment namely, two-tail T-test and Mean formula that then proved the accuracy of the study's relation to the acquired data gathered by using IoT remote application and sensor-base protype. _u |
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