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VayuAnukulani: Adaptive Memory Networks for Air Pollution Forecasting

VayuAnukulani is a direct Hindi translation for the two key words Air and Adaptatability - Air, translated as Vayu and Adaptatability, translated as Anukulani. We proposed an end-to-end solution to predict air quality for next 24 hours.

Contributor: Divyam Madaan, Radhika Dua

Cite our work

@article{madaan2019vayuanukulani, title={VayuAnukulani: Adaptive Memory Networks for Air Pollution Forecasting}, author={Madaan, Divyam and Dua, Radhika and Mukherjee, Prerana and Lall, Brejesh}, journal={arXiv preprint arXiv:1904.03977}, year={2019} }

@article{mukherjee2019vayuanukulani, title={VayuAnukulani: Adaptive memory networks for air pollution forecasting}, author={MUKHERJEE, PRERANA and Madaan, Divyam and Dua, Radhika and Mukherjee, Prerana and Lall, Brejesh}, year={2019} }

Idea

We present a system to predict air quality for next 24 hours by estimating the concentration and level of different air pollutants including nitrogen dioxide (NO2), particulate matter (PM2.5 and PM10) for Delhi.

Project video can be found here

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Contributing

We'd love to accept your contributions to this project. Please feel free to open an issue, or submit a pull request as necessary. If you have implementations of this repository in other ML frameworks, please reach out so we may highlight them here.

Acknowledgment

We would like to thank our mentors, Dr. Aakanksha Chowdhery, Prerana Mukherjee, and Prof. Brejesh Lall for the inspiring guidance and constant encouragement during the course of this project. We owe our heartfelt gratitude to them for providing us an opportunity to pursue projectwith excellent laboratory facilities at IIT Delhi. We would also like to thank Marconi Society for sponsoring Celestini Project India. We would also like to thank Central pollution control board for the dataset which has played a very important role towards in the completion of this work

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End to end system to predict air quality

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