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RESEARCH ON DATA COLLECTION AND TRANSMISSION TECHNOLOGIES FOR AUTOMATIC CONTROL OF HIGH-FREQUENCY OZONATORS IN WATER DISINFECTION

Palvan KalandarovNational Research University "Tashkent Institute of Irrigation and Agricultural Mechanization Engineers". Kari Niyazov Street 39, Tashkent, Republic of UzbekistanDina ErmanovaDepartment of Radio Engineering, Electronics and Space Technologies, Satbayev University, 050013, Satpaev str., 22a, Almaty, Republic of KazakhstanNurzak DuisenovDepartment of Mathematics, Physics and Computer Science. Central Asian Innovation University. 160000, Baitursynova str., 80A, Shymkent, Republic of Kazakhstan;Madina KoshkinbayevaDepartment of Mathematics, Physics and Computer Science. Central Asian Innovation University. 160000, Baitursynova str., 80A, Shymkent, Republic of Kazakhstan;Bekmurat ShynzhigitDepartment of Mathematics, Physics and Computer Science. Central Asian Innovation University. 160000, Baitursynova str., 80A, Shymkent, Republic of Kazakhstan;Djamilya AbdullaevaNational Research University "Tashkent Institute of Irrigation and Agricultural Mechanization Engineers". Kari Niyazov Street 39, Tashkent, Republic of UzbekistanХ. А. АбдуллаевBukhara Institute of Natural Resources Management of the National Research University of the Tashkent Institute of Irrigation and Agricultural Mechanization Engineers. 200100, Bukhara region, Gazliyskoe highway, 32. Republic of Uzbekistan
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Abstract

This scientific work analyzes the research on data collection and transmission technologies for automatic control of high-frequency ozonators in water disinfection. The purpose of the study is to improve disinfection efficiency and optimize the system's operation by using IoT and artificial intelligence technologies in the control of ozonators. During the study, data collected by sensors were processed in real time through an IoT system and analyzed using artificial intelligence. Results showed that the efficiency of ozonator control increased by 25%, and ozone consumption was reduced by 20%. The use of a PID controller allowed for a 15% reduction in the duration of the disinfection process. The application of sensor networks reduced system downtime by 10%, ensuring continuous operation. Service costs were reduced by up to 30%, improving economic efficiency. These results proved the effectiveness of integrating IoT and artificial intelligence technologies. Furthermore, this method offers an environmentally friendly solution. In conclusion, improving the automatic control systems of ozonators is a significant step towards enhancing the water disinfection process.

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