Air Quality Monitoring and Prediction System

  • Tejal Sable, SmitaBodkhe, HarshalBhamare, Pratik Bhangare


In current years, Internet of Things(IoT) has been used in many areas like commerce, education and industry. Smart cities uses this concept and applications for smooth urban life. IoT uses information and technologies to aware people and make them more synergistic. IoT is the most important thing for future predication and make people aware. Most of the machine learning techniques have been used in future prediction for big data. Hence , in this paper we are using machine learning techniques for the future prediction of air quality. The air pollution contain so many toxic gases  such as carbon dioxide, nitrogen dioxide, chlorine and phosgene. This gases produces bad impact on human life. The developing and populated countries, air pollution  is the major  issue because of regular traffic and gases emmited from industries. This contain major harmful  particulate matter like PM 2.5 and PM 10. The  particulate matter PM 2.5 is more harmful when its level is high in air so precautions needs to be taken. When particulate matter (PM2.5) highly present in air it reduce visibility and causes the air to appear hazy. In smart cities, traffic factors, burning fossil fuels and emission of gases from industries causes this particulate matter highly present in air and it causes health issues to nearby residing  and working people.Hence, we have to control it by simultaneously checking the level of this particulate matter in air. In this paper we are using regression for statistic analysis of gases present in air. Auto regression is used to predict the future values  toxic gases present in air. It also predict the humidity and temperature values. For that it uses past data and real time data of gases  present in air  to predict the future values.