Abstract
In the populated and developing countries, governments consider the regulation and protection of environment as a major task and should take into consideration the concept of Smart Environment Monitoring. The main motive of these systems is to enhance the environment with various technology including sensors, processors, data sets and other devices connected across the globe through a network. This system can basically help in monitoring air quality which is necessary in the field of meteorological studies and movement factors. Also, these factors contribute a lot in air pollution. The values of major pollutants like SO2, PM2.5, CO, PM10, NO2, and O3. In recent years, machine learning in most emerging technology for predicting on historical data with 99.99% of accuracy. To prognosticating air quality index of NCR, India in different aspects like stubble farming, motor vehicle emission, and open construction practices which result in polluting the air quality of NCR. The manuscript is helping to frame a structured view of air quality prediction methods in reader's mind.
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