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基于智能手机的高效测量水中的

Haiping Ai¹, Kai Zhang¹, Huichun Zhang¹

¹Department of Civil and Environmental Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA.

Water research X

|June 4, 2024

概括

本研究介绍了一种新的,无需设备的智能手机方法,用于使用色度分析测量水 (P) 水平. 这种简单的技术使得公众广泛参与到监测水质和防止缩的过程中.

科学领域:

环境科学环境科学
分析化学分析化学
水质监测水质监测

背景情况:

农业排水是 (P) 污染的主要来源,导致肥胖化和有害藻类繁殖.
有效监测P水平需要可访问的工具和公众参与,以便广泛采样.
现有的基于智能手机的P测量方法通常需要特定的照明和设备,限制了大规模应用.

研究的目的:

为 (P) 分析开发一种简单,无设备,基于智能手机的色度测量方法.
克服现有方法的局限性,例如严格的光线条件和初始设备投资.
促进公众广泛参与定期水质监测.

主要方法:

一个智能手机摄像头从标准的 Askorbic 酸 P 测量方法中捕获了色度反应.
红绿蓝 (RGB) 值是使用Python代码进行定量建模的.
开发和测试了回归和分类模型,在各种条件下进行了测试 (光线,手机类型,水样).

主要成果:

一个随机森林回归模型实现了高精度 (R2 = 0.97,RMSE = 0.051) 的P度从0.01到1.0毫克P/L.
一个分类模型准确估计了P水平低于0.1毫克P/L,准确率为95.2%.
这些模型在不同的室内照明,手机类型和水样中展示了强度.

结论:

开发的基于智能手机的方法为频繁的P测量提供了一个简单,有效和无设备的工具.
这种方法可以显著提高公众参与水质监测.
自由可用的在线模型支持P分析的可访问和广泛应用.

关键词:

颜值测量分析的颜色分析机器学习是机器学习.的监测的监测一个智能手机的智能手机.

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