• Anagha G.Patil
• Shrikant M. Bhosale
• Rashmi J. Deshamukh
• Sheetal Gaikwad

As cities grow both financially and technologically, pollution problems such as noise,water and air pollution become more prevalent. Particularly poor air quality has an effect on people's health. Fossil energy usage, rapidly expanding industrialisation, automobile exhaust, etc. are the main sources of air pollution. Waste generation represents one of the most significant contributors to air pollution. Carbon Monoxide, nitrogen Dioxide (No2) and Sulfur Dioxide (So2) are the major components of pollution of air. Various air quality surveillance devices keep an eye on various pollutants. Because the amount of contaminants in the air changes throughout the day, forecasting the air quality is challenging. Various Machine learning algorithms can be used to solve this issue. With the help of machine learning (ML) techniques and IoT sensors are installed at different stations of Shiroli located in Maharashtra Industrial Development Corporation District Kolhapur, Maharashtra. Data is collected hourly and preprocessed. The data obtained by industrial area are preprocessed and relevant features are extracted using different ML algorithm. Results of the algorithms are compared and performance is evaluated with different measures like R, R2 MAE, RMSE, etc.

machine learning, IoT Sensors, Air Pollution, AQI

"PREDICTION AND ANALYZING AIR QUALITY OF SHIROLI MIDC USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 4, page no.k635-k641, April-2023, Available :http://www.jetir.org/papers/JETIR2304A91.pdf

"PREDICTION AND ANALYZING AIR QUALITY OF SHIROLI MIDC USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 4, page no. ppk635-k641, April-2023, Available at : http://www.jetir.org/papers/JETIR2304A91.pdf