SukonyaPhukan92/Image_Based_Air_Pollution_detection_using_InceptionV3_Model

In this project work, the main motive is to build a deep learning model to detect air pollution from real-time images. In order to achieve that goal, we have collected data from different sources and then enhanced the low-quality images using the Image enhancement technique. Our next step was to train a CNN (Convolutional Neural Network) on the images in order to detect air pollution by analyzing the clearness of the sky in the image. In this work, we have used the Inception V3 model. After the successful testing of the CNN model, we have deployed the model on an Android Application.

28
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Experimental

This tool helps environmental monitoring teams and public health organizations assess air quality by analyzing everyday images. You provide photos, and it tells you if air pollution is present by evaluating the clarity of the sky. This is ideal for those who need a quick visual assessment of air quality without specialized equipment.

No commits in the last 6 months.

Use this if you need a quick, image-based assessment of air pollution in a given location.

Not ideal if you require precise air pollutant concentrations or detailed scientific measurements.

environmental-monitoring air-quality-assessment public-health visual-inspection community-monitoring
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 15 / 25

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Jupyter Notebook

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Last pushed

Oct 24, 2021

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