Our goal is to build a system for air quality prediction in atmosphere and to investigate which supervised machine learning methods are best suited to solve it. The value is tested via program. If the output is abnormal, it shows abnormal UI otherwise normal UI using Tkinter library. Examining and protecting air quality has become one of the most essential activities for the government in many industrial and urban areas today. The meteorological and traffic factors, burning of fossil fuels, and industrial parameters play significant roles in air pollution.With this increasing air pollution,Weare in need of implementing models which will record information about concentrations of air pollutants(so2,no2,etc).The deposition of this harmful gases in the air is affecting the quality of people’s lives, especially in urban areas. Lately, many researchers began to use Big Data Analytics approach as there are environmental sensing networks and sensor data available.In this paper, machine learning techniques are used to predict the concentration of so2 in the environment. Sulphur dioxide irritates the skin and mucous membranes of the eyes, nose, throat, and lungs.Models in time series are employed to predict the so2 readings in nearing years or months.