Predictive Urban Air Quality Monitoring for Healthier Cities

Abstract

The research work proposal outlines an innovative and crucial project for addressing urban air quality issues using advanced technological solutions. Establishing a real-time air quality monitoring system with integrated big data and machine learning will enable precise tracking and analysis of pollution levels. The research paper begins with the key aspects of air quality. It further focuses upon the need for utilizing advanced techniques to curb the issues due to poor air quality. A system is proposed to determine the air quality utilizing machine learning techniques, predicting the quality of air index. Evaluation measures are then undertaken for predicting the same using Random forest, Support vector and Catboost regression techniques.