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@article{182467,
        author = {Raj Prakashchandra Chauhan and Shubhangi Tidke and Prashant Kulkarni},
        title = {Predicting Air Quality Index (Aqi) Using Machine Learning In Urban Indian Cities},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {2},
        pages = {2043-2047},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=182467},
        abstract = {This study investigates the use of machine learning models like Random Forest and XGBoost to predict Air Quality Index (AQI) in Indian urban cities. By analyzing major pollutants such as PM2.5, PM10, NO2, and CO, the research aims to support early warning systems and data-driven environmental policy decisions.},
        keywords = {AQI, Machine Learning, Random Forest, XGBoost, Pollution Prediction.},
        month = {July},
        }