IoT and ML based AQI Estimation using Real time Traffic Data

Presentation by Nitin Nilesh at IEEE World Forum on IoT 2022

Written by Ayush Kumar Dwivedi on Dec 6, 2022

Abstract

This paper proposes an IoT and machine learning (ML)-based novel method to estimate the air quality index (AQI) using traffic data in real-time. With the help of particulate matter (PM) monitoring nodes deployed in fifteen locations with diverse traffic scenarios of Indian roads, and using digital map service providers, a rich traffic dataset with approximately 210,000 samples has been collected. Three different ML models, namely random forest (RF), support vector machine (SVM), and multi-layer perceptron (MLP), are trained on this dataset to predict the AQI category into five levels. The experimental results show an accuracy of 82.60% with the F1-score of 83.67% on the complete dataset. Apart from this, ML models were also trained on individual node datasets, and the behavior of AQI levels was observed.

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