基于模糊分类系统的探测区虾池水质水平分析

Fithrotul Irda Amaliah, A. I. Gunawan, T. Taufiqurrahman, Bima Sena Bayu Dewantara, Ferry Astika Saputra
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引用次数: 1

摘要

从几年前开始,凡纳滨对虾(Litopenaeus vannamei)在印度尼西亚被广泛养殖,因为它有很好的商业机会。在水产养殖活动中,水质是影响池塘对虾生存和品质的重要因素。因此,为了获得满意的收成,农民必须了解水质信息。本研究旨在开发一个基于温度、pH、盐度、溶解氧等信息的水质监测系统。传感器的数据利用物联网(IoT)技术发送到云端,然后通过模糊逻辑系统进行分类。为了方便养殖户了解自家虾池的水质情况,将包含模糊逻辑分类结果在内的4个传感器数据发送至手机。经过系统的试用,100%的数据成功发送到云端(谷歌电子表格)。该系统还成功地将水质水平分类为农民的期望。通过该系统,希望能帮助养殖户监测虾池水质,提高对虾的质量和数量。
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Water Quality Level for Shrimp Pond at Probolinggo Area Based on Fuzzy Classification System
Since several years ago, vaname shrimp (Litopenaeus vannamei) has been extensively cultivated in Indonesia because it has good business opportunities. In aquaculture activities, water quality is an important factor that dramatically impacts the survival and quality of shrimp in the pond. Therefore, information of water quality must be known by the farmer for obtaining a satisfactory harvest. This study aims to develop a water quality monitoring system based on information of temperature, pH, salinity, and dissolved oxygen. The data from sensors are sent to the cloud utilizing Internet of Things (IoT) technology and then classified by a fuzzy logic system. In order to help farmers easily know the water quality of their shrimp pond, four sensor data including the result of classification from fuzzy logic are sent to the phone. After a trial of the system, 100% of the data are successfully sent to the cloud (google spreadsheet). The system also successfully classified the level of water quality as the expectation of the farmer. With this system, it is hoped that it can assist farmers in monitoring the water quality of shrimp pond to improve the quality and quantity of shrimp.
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审稿时长
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