This article analyzes the issue of atmospheric pollution caused by particulate matter (PM2.5, PM10) in cotton processing enterprises. The efficiency of conventional dust collection devices—cyclones, cartridge filters, and HEPA filters—is scientifically compared, and their limitations in ensuring environmental safety are identified. Furthermore, the theoretical and practical integration of IoT (Internet of Things)-based smart sensors and GIS (Geographic Information Systems) platforms into industrial monitoring is substantiated. The study develops a block-diagram approach for real-time data acquisition, network-based transmission, and spatial visualization to determine pollution dynamics. Based on the analysis of local and international practices, it has been demonstrated that smart-filter systems can reduce atmospheric pollution by up to 90%. The findings provide a solid foundation for formulating scientifically grounded recommendations on the implementation of digital technologies in the field of industrial ecology.
| Mualliflar | Tursunov, Ahror, Sharibaev, Nosir |
|---|---|
| Jurnal | Наманган муҳандисликтехнология институти илмийтехника журнали |
| Nashr sanasi | 2025-09-30 |
| Jild | 10 |
| Son | 3 |
| Betlar | 36-42 |
| Til | Ingliz |
| DOI | 10.61151/stjniet.v10i3.853 |
DOI: 10.61151/stjniet.v10i3.853 · Maqolaning asl sahifasi
cotton industry enterprises, atmospheric particulate pollution, IoT technologies, GIS systems, smart filters, environmental monitoring, particulate matter (PM2.5, PM10), industrial ecology, real-time control, smart sensors
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