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International Advanced Research Journal in Science, Engineering and Technology
International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal
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← Back to VOLUME 11, ISSUE 3, MARCH 2024

AIR POLLUTION DETECTION USING DEEP LEARNING

D. Tejaswi, V. Manjusha, M. Yamini Parvathi, S. Chandana Lakshmi Priya

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Abstract: As the world's population gets more urbanised, many of the fastest-growing cities are experiencing worsening air quality. According to a study, ambient air pollution concentrations are at a level where significant health consequences have been observed in 20 out of the 24 global megacities. Although it is commonly known that air pollution can have a substantial negative impact on agriculture, urban growth, and public health, there are evident gaps in the methods used by existing approaches to collect reliable data on air pollution.

Keywords: Convolutional Neural Network, AQI, ResNet-50, and air pollution levels

How to Cite:

[1] D. Tejaswi, V. Manjusha, M. Yamini Parvathi, S. Chandana Lakshmi Priya, “AIR POLLUTION DETECTION USING DEEP LEARNING,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2024.11327

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