Processing and visualizing traffic pollution data in Hanoi City from a wireless sensor network

Abstract

Hanoi city is currently dealing with rapidly increasing air pollution that result from variety of sources. The main cause of pollution is exhaust gas from traffic system with a very large number of private vehicles. In order to help the city's environment authorities monitor the level of air pollution, a wireless sensor network is currently under development to collect traffic pollution data measured by a number of gas sensors. This paper focuses on how to process pollution data and visualize level of pollution relying on available datasets collected from sensor network. The volume of data collected from each area of the city can be very large and dynamic due to the number of mobile sensors deployed in the same area at the same time and their measurement frequency. First, we present a method for processing raw data using calibration and data clustering techniques. Second, we describe how measurement datasets are visually represented on the city's online map on the basis of mathematical interpolation method that corresponding to characteristics of environmental data. And then we also use computer graphic technique to improve the visualization quality. Finally, this paper show the result of those methods with sample data collected from an urban district of Hanoi City on a website by which we do not only provide to viewer the actual level of pollution by position but also by time.