Research on data collection and transmission technologies for automatic control of high-frequency ozonators in water disinfection

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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Publication Details

Journal
IOP Conference Series Earth and Environmental Science
Published
2025-04-01
DOI
https://doi.org/10.1088/1755-1315/1491/1/012052
Citations
1
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
6.00
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article

Research on data collection and transmission technologies for automatic control of high-frequency ozonators in water disinfection

Madina Koshkinbayeva, Palvan Kalandarov, Daria Riumina, Dina Ermanova et al.
1 citations
IOP Conference Series Earth and Environmental Science
Water Quality Monitoring Technologies
6.00
article

Research on data collection and transmission technologies for automatic control of high-frequency ozonators in water disinfection

Madina Koshkinbayeva, Palvan Kalandarov, Daria Riumina, Dina Ermanova, Nurzak Duisenov, Bekmurat Shynzhigit
article en
1 citations

Abstract

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.

IOP Conference Series Earth and Environmental ScienceVol. 1491(1)
National Academy of Sciences of Ukraine (UA), Satbayev University (KZ), Tashkent Institute of Irrigation and Agricultural Mechanization Engineers (UZ), M.S. Poliakov Institute of Geotechnical Mechanics of the National Academy of Sciences of Ukraine (UA), Global Health Research Center of Central Asia (KZ)
Openalex Percentile: Top 7%
Water Quality Monitoring Technologies
6.00
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Research on data collection and transmission technologies for automatic control of high-frequency ozonators in water disinfection — Madina Koshkinbayeva, Palvan Kalandarov, et al. · IOP Conference Series Earth and Environmental Science (2025) | TGRS Research Map | TGRS