Abstract
The article presents the assessment methodology for anthropogenic water pollution in swimming pools, based on intelligent video monitoring of people physical activity, as well as a model for correlation data analysis and a regression model for the main parameters of chemical water contamination and doses of introduced reagents. The ultimate goal of the project is to create an intelligent water treatment management system for swimming pools. It is planned to use YOLOv4 neural networks to implement an intelligent pattern recognition module (swimmers in the pool) in the data stream coming from video cameras in real time. This innovative system will make it possible to automatically make managerial and technical decisions to determine the required amount of introduced reagents at various time intervals depending on the actual amount of organic contaminants, as well as other factors determined by the results of the correlation-regression analysis of the data. A review of information resources has shown that such a methodology does not exist both in Russia and abroad.
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