Air pollution is the major environmental and public health concern in the globe today. Air pollution leads to detrimental consequences on Human health, climate and ecology. Air is increasingly contaminated due to release of Toxic gases by businesses, vehicle emissions and increased concentration of dangerous gases and particulate matter in the environment. Particulate matter is one of the most important indicators having the considerable role to the growth in air pollution. This provides a requirement for measurement and analysis of real-time air quality monitoring so that suitable choices may be done in a timely timeframe. This work proposes a real-time independent air quality monitoring system which incorporates multiple parameters: PM 2.5, carbon monoxide, carbon dioxide, temperature, humidity and air pressure. Internet of Things is presently finding significant usage in each and every area, plays a major part in our air quality monitoring system too. Using empirical analysis, typical air automated monitoring system has excellent precision, but big bulk, high cost, and single datum class make it unfeasible for wide-scale installation. Based on incorporating Internet of Things (IOT) into the sphere of environmental protection, this study brings up a form of real-time air pollution monitoring and forecasting system. By adopting IOT, this system may lower the hardware cost into 1/10 as previously. The system may be set out in a big number in monitoring region to build monitoring sensor network. Besides the features of traditional air automated monitoring system, it also shows the function of predicting development trend of air pollution within a specified time range by evaluating the data collected by front-end perception system according to neural network technology. Targeted emergency disposal techniques may be made to reduce losses in practical use.