Air Visio: Air Quality Monitoring and Analysis Based Predictive System

Abstract

Sri Lanka is facing a serious air pollution problem that severely impacts the daily life of every Sri Lankan. The main source of ambient air pollution in Sri Lanka is vehicular emissions. A methodology to monitor the air quality in real-time with an overall coverage of Sri Lanka, and automatically process these huge data to identify air quality levels in a specific area is now becoming a timely research topic. An air quality monitoring and analysis based predictive system is proposed to monitor the ambient air quality, provides the best route with minimum polluted air, maps the heatmaps to identify the current air quality of an area easily and predict the future air quality of each area. The prototype was implemented by hierarchically deploying two different gas sensors, an Arduino Uno board and a wifi module, to implement in open spaces between smart buildings, and transfers the sensor data back to the information processing center by using IoT technology for real-time display. The information processing center stores real-time information which is collected from the sensors to the database. By reading sensor data stored in the database, the front-end system draws real-time, accurate air quality levels included maps and predicts the less polluted routes and the air quality level over an area. Further, an energy harvesting system is also presented for the power consumption of the device. A route is suggested in an accuracy of 70% from this system. The final product provides a low cost, highly portable and easily maintainable system for the users.