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JCSIS

Air Quality Prediction Using Deep Learning and IoT Systems

Nizar M. SoufianSofia ArkhstanNajaad OubeBlika
Volume 4

Abstract

Predicting air quality is essential for public health and environmental sustainability. This paper combines deep learning models with IoT systems to monitor and forecast air quality in real-time. Techniques such as Convolutional Neural Networks (CNNs) are employed to analyze environmental data, providing actionable insights for pollution control. Results demonstrate that the integration of IoT and deep learning enhances prediction accuracy and responsiveness.

Keywords

Air Quality Prediction, Deep Learning, IoT, Environmental Monitoring, Pollution Control

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