Scalable AI-driven air quality forecasting and classification for public health applications

Scalable AI-driven air quality forecasting and classification for public health applications

Abstract Background Air pollution remains one of the most pressing public health and environmental issues, particularly in developing countries like Afghanistan, where reliable air quality monitoring infrastructure is lacking. Traditional systems often rely on static data and limited sensors, which...

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Bibliographic Details
Main Authors: Mohammad Wasil Jalali, Bahir Saidi, Habibullah Farahmand, Mohammad Aref Rezvan Panah, Eda Nur Saruhan
Format: Article
Language:English
Published: Springer 2025-08-01
Series:Discover Atmosphere
Subjects:
Air quality prediction
Machine learning
Deep learning
Explainable AI
Time-series forecasting
Environmental monitoring
Online Access:https://doi.org/10.1007/s44292-025-00052-8
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https://doi.org/10.1007/s44292-025-00052-8

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