INNOVATIVE METHOD FOR STUDYING THE DYNAMICS OF POLLUTION AND HUMIDITY CHANGES IN SPORTS FACILITIES: FITNESS ROOMS AND SWIMMING POOLS

Abstract

It is necessary to take into account the reaction time of the system to changes and provide for changes in parameters when using modern automation systems and indoor microclimate control with a dynamic change in the intake of harmful substances. The change in carbon dioxide (CO2) pollution and air humidity in sports facilities, such as fitness rooms and swimming pools, is a non-stationary random process with a complex type of non-stationarity and can be described by statistical characteristics. Obtaining these statistical characteristics is complicated by the probabilistic nature of the whole process and the presence of random systematic errors in measuring pollution (CO2) and air humidity of a particular sports facility, the specifics of the functioning of heat and mass transfer processes, moisture exchange in the premises of sports facilities (swimming pools, fitness halls, gyms, etc.). etc.) and has not been studied in modern scientific literature. Therefore, this study was carried out precisely in order to improve the situation and bring it out of the impasse (uncertainty) regarding sports facilities and premises for mass physical culture, recreation, and leisure. The paper proposes a comprehensive method for studying the dynamics of changes in pollution (CO2) and air humidity in a sports facility (fitness rooms, swimming pools, etc.). It allows you to determine the statistical characteristics of the process and identify it with an accuracy that is satisfactory for practical purposes (the error is no more than 10%). In the process of research, it is necessary to use daily diagrams of the operation of CO2 air pollution meters and moisture meters in fitness rooms and swimming pools for a long period of time (70 days). An optimal flow meter of air pollution with carbon dioxide (CO2) or a moisture meter should be built according to a discrete circuit with digital processing of information that comes from a sensor (an artificial intelligence system for controlling air gas exchange processes in a sports facility), according to an algorithm for determining a moving average over a period of 10 ... 20 minutes averaging of the signal and the interval for issuing results 2 ... 5 min. This is what will make it possible to reduce random measurement errors and ensure accurate reproduction of the dynamics of the processes of changing Ac(t) or Wp(t) (which, by the way, can be quite fleeting).