Advanced air quality prediction using multimodal data and dynamic modeling techniques

Advanced air quality prediction using multimodal data and dynamic modeling techniques

Abstract Accurate air quality forecasting is critical for human health and sustainable atmospheric management. To address this challenge, we propose a novel hybrid deep learning model that combines cutting-edge techniques, including CNNs, BiLSTM, attention mechanisms, GNNs, and Neural ODEs, to enhan...

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Bibliographic Details
Main Authors: Umesh Kumar Lilhore, Sarita Simaiya, Rajesh Kumar Singh, Abdullah M. Baqasah, Roobaea Alroobaea, Majed Alsafyani, Afnan Alhazmi, M. D. Monish Khan
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Multimodal
Air quality
Sensor data
Meteorological data
Satellite imagery
Pollutant distribution
Online Access:https://doi.org/10.1038/s41598-025-11039-1
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https://doi.org/10.1038/s41598-025-11039-1

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