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@article{161991,
        author = {R.Sharanya Reddy and K.Satish kumar and A.Sathvika and P.Sejal and R.Shailaj and A.Shanthi Priya and Thayyaba Khatoon and Manikkannan},
        title = {AIR QUALITY PREDICTION USING MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {7},
        pages = {161-163},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=161991},
        abstract = {To predict the Air Quality Index (AQI) for different locations in India. This involves using historical data on major pollutants like NO2, SO2, RSPM, and SPM, collected from the Indian government database. The goal is to develop a forecasting model that can estimate future AQI values for a given region. To analyse the data and extract valuable information. The model will consider factors like pollutant concentrations, meteorological data, industrial activities, and geographical features. By employing machine learning algorithms such as regression or time series analysis, you aim to create a reliable model that can predict air quality levels. This information is crucial for targeted efforts to improve air quality in different regions of India.},
        keywords = {},
        month = {},
        }