AI Based Air Pollution Monitoring and Controlling System

B Praveen kumar; V saketha; R Karthik kumar; T Sai shivankar; P Nirath kumar

doi:10.36948/ijfmr.2026.v08i02.74058

AI Based Air Pollution Monitoring and Controlling System

Author(s)	Mr. B Praveen kumar, Ms. V saketha, Mr. R Karthik kumar, Mr. T Sai shivankar, Mr. P Nirath kumar
Country	India
Abstract	Air pollution has emerged as one of the most critical environmental and public health challenges worldwide, particularly in rapidly urbanizing regions. Traditional monitoring systems often rely on sparse, high-cost infrastructure that provides limited spatial and temporal coverage, making real-time decision-making difficult. This study presents an Artificial Intelligence (AI)-based air pollution monitoring and control system designed to provide continuous, accurate, and intelligent environmental assessment along with automated mitigation strategies. The proposed system integrates low-cost sensors to measure key air quality parameters such as particulate matter (PM2.5 and PM10), carbon monoxide (CO), nitrogen dioxide (NO₂), sulphur dioxide (SO₂), temperature, and humidity. These sensors are connected to IoT-enabled devices that transmit real-time data to a centralized cloud platform. AI techniques, including machine learning algorithms such as regression models, decision trees, and neural networks, are employed to analyse historical and real-time data for pollution prediction, anomaly detection, and trend analysis. The system not only monitors air quality but also provides intelligent control mechanisms. Based on predicted pollution levels, automated actions such as activating air purifiers, controlling ventilation systems, and issuing alerts to users and authorities are triggered. In addition, the system can recommend preventive measures, such as reducing industrial emissions or limiting vehicular movement during high pollution periods. A user-friendly interface, accessible via mobile or web applications, allows users to visualize air quality indices and receive personalized health advisories. The AI-based approach enhances accuracy, scalability, and responsiveness compared to conventional methods. It enables proactive pollution management by predicting hazardous conditions before they occur, thereby minimizing health risks and environmental damage. Furthermore, the system supports sustainable development goals by promoting cleaner air and healthier living environments, particularly in closed or semi-closed spaces such as smart homes and urban buildings.
Keywords	Electrical Engineering, Air Pollution, Artificial Intelligence, IoT
Field	Engineering
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-04-10
DOI	https://doi.org/10.36948/ijfmr.2026.v08i02.74058

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AI Based Air Pollution Monitoring and Controlling System

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