Pervasive monitoring of carbon monoxide and methane using air quality prediction

The first step towards pollution control is monitoring pollution. In this paper we present an innovative way of pollution monitoring in which any person can see the pollution content of a specific area where the sensors are installed and take measures to control the same. A prototype for monitoring few major gas pollutants like CO, CH4 along with the temperature variations in the surroundings has been implemented. The semiconductor gas sensors (MQ7, MQ4) were calibrated according to standard methods and interfaced with Raspberry Pi Model B+ using Python 2.7. The readings are displayed in real time and also recorded using an online analytics and data visualization tool, Plotly. This model can further be improved by adding more number of sensors to create a low cost and portable system for pollution monitoring.