Air Quality Prediction using Machine Learning Algorithms –A Review

Tanisha Madan, Shrddha Sagar, Deepali Virmani

20202020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN)113 citationsDOI

Abstract

Predicting air quality is necessary step to be taken by government as it is becoming the major concern among the health of human beings. Air quality Index measure the quality of air. Various air pollutants causing air pollution are Carbon dioxide, Nitrogen dioxide, carbon monoxide etc that are released from burning of natural gas, coal and wood, industries, vehicles etc. Air Pollution can cause severe disease like lungs cancer, brain disease and even lead to death. Machine learning algorithms helps in determining the air quality index. Various research is being done in this field but still results are still not accurate. Dataset are available from Kaggle, air quality monitoring sites and divided into two Training and Testing. Machine Learning algorithms employed for this are Linear Regression, Decision Tree, Random Forest, Artificial Neural Network, Support Vector Machine.

Topics & Concepts

Air quality indexDecision treeSupport vector machineMachine learningRandom forestAir pollutionComputer scienceArtificial neural networkArtificial intelligenceAlgorithmMeteorologyOrganic chemistryChemistryPhysicsAir Quality Monitoring and ForecastingAir Quality and Health ImpactsImpact of Light on Environment and Health