Abstract

Traditional methods for evaluating water quality have a number of drawbacks. They need expensive, specialized equipment as well as knowledgeable employees first. Second, data loss may result from human error. Thirdly, because people rather than algorithms will be analyzing the obtained data, these schemes cannot foresee future patterns. Additionally, changes in the characteristics of water may result from the sample transit process. Therefore, it is challenging to consistently check water quality using outdated monitoring techniques. The disadvantages of traditional environmental monitoring techniques have been covered in this study.

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