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VayuAnukulani: Adaptive memory networks for air pollution forecasting

Abstract: 

Air pollution is the leading environmental health hazard globally due to various sources which include factory emissions, car exhaust and cooking stoves. As a precautionary measure, air pollution forecast serves as the basis for taking effective pollution control measures, and accurate air pollution forecasting has become an important task. In this paper, we forecast fine-grained ambient air quality information for 5 prominent locations in Delhi based on the historical and realtime ambient air quality and meteorological data reported by Central Pollution Control board. We present VayuAnukulani system, a novel end-to-end solution 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. Extensive experiments on data sources obtained in Delhi demonstrate that the proposed adaptive attention based Bidirectional LSTM Network outperforms several baselines for classification and regression models. The accuracy of the proposed adaptive system is ∼ 15 − 20% better than the same offline trained model. We compare the proposed methodology on several competing baselines, and show that the network outperforms conventional methods by ∼ 7 − 18%.

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Paper Details

Authors:
Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall
Submitted On:
6 November 2019 - 4:11pm
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Prerana Mukherjee
Paper Code:
1570567905
Document Year:
2019
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[1] Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall, "VayuAnukulani: Adaptive memory networks for air pollution forecasting", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4917. Accessed: Nov. 11, 2019.
@article{4917-19,
url = {http://sigport.org/4917},
author = {Divyam Madaan; Radhika Dua; Prerana Mukherjee; Brejesh Lall },
publisher = {IEEE SigPort},
title = {VayuAnukulani: Adaptive memory networks for air pollution forecasting},
year = {2019} }
TY - EJOUR
T1 - VayuAnukulani: Adaptive memory networks for air pollution forecasting
AU - Divyam Madaan; Radhika Dua; Prerana Mukherjee; Brejesh Lall
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4917
ER -
Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall. (2019). VayuAnukulani: Adaptive memory networks for air pollution forecasting. IEEE SigPort. http://sigport.org/4917
Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall, 2019. VayuAnukulani: Adaptive memory networks for air pollution forecasting. Available at: http://sigport.org/4917.
Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall. (2019). "VayuAnukulani: Adaptive memory networks for air pollution forecasting." Web.
1. Divyam Madaan, Radhika Dua, Prerana Mukherjee, Brejesh Lall. VayuAnukulani: Adaptive memory networks for air pollution forecasting [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4917