Data-Driven Framework for Understanding and Predicting Air Quality in Urban Areas

Monitoring, predicting, and controlling the air quality in urban areas is one of the effective solutions for tackling the climate change problem. Leveraging the availability of big data in different domains like pollutant concentration, urban traffic, aerial imagery of terrains and vegetation, and w...

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Veröffentlicht in:	Frontiers in big data Jg. 5; S. 822573
Hauptverfasser:	Babu Saheer, Lakshmi, Bhasy, Ajay, Maktabdar, Mahdi, Zarrin, Javad
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Media S.A 25.03.2022
Schlagworte:	aerial view image recognition Big Data climate change mitigation machine learning and deep learning algorithms regression based prediction algorithms urban air quality urban vegetation detection urban vegetation detection climate change mitigation machine learning and deep learning algorithms aerial view image recognition regression based prediction algorithms urban air quality cost effective modeling
ISSN:	2624-909X, 2624-909X
Online-Zugang:	Volltext
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