浊度
环境科学
水质
计算机科学
均方误差
RGB颜色模型
米
遥感
数学
统计
人工智能
生态学
物理
天文
生物
地质学
作者
Bayu Taruna Widjaja Putra,Levana Angela Rocelline,Wahyu Nurkholis Hadi Syahputra
标识
DOI:10.1016/j.micpro.2022.104603
摘要
The periodical assessment of water quality in response to increased pollution has become increasingly crucial. Water turbidity, which indicates the growth of pathogenic microorganisms in water, is a well-known water quality indicator. In fish farming, water turbidity affects fish health. Commercially available tools for estimating water turbidity are expensive, which is an obstacle for small-scale farmers. In this study, a low-cost (<20 USD) embedded meter that allows near real-time assessment of water turbidity was developed. The developed tool was integrated into an Android-based mobile application and comprised a turbidity sensor, RGB sensor, LED as the light source, and electronic components. Light source uniformity is essential for obtaining reliable measurement results and instrument replication. Uniformity is performed by calculating the luminance index from the RGB sensor value and then determining the light intensity. Moreover, two developed tools were tested by comparing their results against those of a commercial turbidimeter (Eutech TN-100). The comparison indicated a strong coefficient of determination (0.96 and 0.98), with root-mean-square error (RMSE) values of 30.48 and 22.08, in the turbidity evaluation range of 300–500 NTU. However, upon measuring samples with turbidity levels of 0–300 NTU, the developed tools showed better performance based on the RMSE results of 20.63 and 11.87. Thus, the developed meter is proven useful for smallholders to manage water resources and fish farming activities.
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