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Title	Predicting Air Quality In Smart City Using Novel Transfer Learning Based Framework
ID_Doc	42673
Authors	Sonawani S.; Patil K.
Year	2023
Published	Indonesian Journal of Electrical Engineering and Computer Science, 32, 2
DOI	http://dx.doi.org/10.11591/ijeecs.v32.i2.pp1014-1021
Abstract	Air quality is a matter of concern these days due to its adverse effect on human health. Multiple new air pollution monitoring and prediction stations are being developed in smart cities to tackle the issue. Recent advanced deep learning techniques show excellent performance for air quality predictions but need sufficient training data for model performance. The data insufficiency issue at a new station can be resolved using the proposed novel transfer learning-based framework to predict pollution concentration at the new station. The prediction ability at a new station can be significantly enhanced by this effective technology. The performance of the model is assessed on various stations in Delhi, India. © 2023 Institute of Advanced Engineering and Science. All rights reserved.
Author Keywords	Air quality Chaining approach Deep learning Multi-headed CNN-GRU Smart city and safety Transfer learning

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