Measurement of Air Pollution by Measurement of Traffic Density
Leon Rothkrantz (Czech Technical University, TU Delft - Electrical Engineering, Mathematics and Computer Science)
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Abstract
The areas of many cities in the Netherlands are covered by a network of stationary sensors, measuring special components of air pollution such as CO2, NO2, PM2.5 and PM10. The pollution with fine dust along roads, surrounding and crossing the city is primarily related to traffic density. To measure traffic density, we used a license plate recognizer based on a special Neural Network Neocognitron, analyzing the video footage of surveillance cameras along the roads. We also studied the onset and offset of traffic density to predict traffic density, using the first recorded sparse traffic data. In cooperation with MIT Senseable City Lab the Technical University of Delft has developed special mobile, low cost sensors to measure air pollution. These mobile sensors are integrated with stationary sensors to a heterogeneous sensor network and enable measurement of air pollution out of the reach of the stationary sensor network..