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Title	Automated Detection Of Water Quality In Smart Cities Using Various Sampling Techniques
ID_Doc	11192
Authors	Mishra S.; Anithakumari T.; Jain O.
Year	2024
Published	Sustainable Farming through Machine Learning Enhancing: Productivity and Efficiency
DOI	http://dx.doi.org/10.1201/9781003484608-18
Abstract	Water quality monitoring is an essential requirement in a smart city. It is crucial to use cutting-edge technologies such as the Internet of Things (IoT) and Artificial Intelligence (AI) to plan urban areas that can address a variety of social issues, given the growing population in cities and the issue of the lack of appropriate and suitable resources for comfortable living. In this work, we identified the problem of water quality classification and created ML approaches on binary classification datasets. We identified the performance in Random Forest as superior in upsampling data with different splitting criteria that performed best with 99.7%. © (Publisher name) (publishing year) all right reserved.
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