Published Paper Details:

Problem with the automobile engines continues to increase in a very large scale. Every vehicle has its own emission but problem arises when the emission occurs beyond standard values. Even though lot of changes has been made in the consumption of fuel, increasing urbanization and industrialization contribute for the poor air quality. With the technical advancements in machine learning, it's been possible to build predictive models for monitoring and controlling pollution based on the real-time data. With this, we are using IoT techniques for monitoring the emission rates of vehicles. A predictive model is built on the real- time data available, predicting the values of carbon monoxide. Sensors are embedded in the vehicles to measure the pollutants levels. By using the monitoring techniques, vehicle details such as location, owner is notified with the current situation of pollution in his location and his vehicle emission rate contributing to environment. Machine learning model is used for the prediction of pollution level in the vehicle location based on the previous data and the current data obtained by the sensors. Here the pollutants level can be controlled using smart emission surveillance