An Outdoor Air Quality Estimation System Based On Dual Camera And Environmental Sensor

In general,outdoor air quality estimation system relies on the urban ground environmental monitoring station.However,due to the lack of the monitoring sites and exorbitant cost of the devices,it is difficult to meet the needs of air quality evaluation in local areas.Using inexpensive and lightweight equipment to estimate the air quality is a reliable and cost-effective method.Nowadays,with the rapid development of computer vision,image processing and embedded technology,and the improvement of high-speed microcontroller and all kinds of sensors,using these technologies and hardware devices will become one of the latest and effective means.In this paper,by integrating the techniques of estimating the concentration of PM2.5 and other atmospheric pollutants and combining the computer vision theory,image haze removal and sensor control technology,an novel outdoor air quality estimation system has been introduced and tested,which uses the dual cameras and environmental sensors as the signal collection equipment.It has been proved that the system is feasible and applicable in terms of air quality estimation.The relative work and studies on this system include three aspects:(1)Using Dark Channel Prior algorithm for image haze removal to obtain the atmospheric transmission map and atmospheric light and combining the image depth map,this paper proposes an estimation method of PM2.5 concentration.(2)The binocular vision technique together with Raspberry Pi are used to measure the distance and of target object in the image,which provides effective data for PM2.5 concentration measurement.(3)With environmental sensor and gas sensor,Adafruit Feather M0 Bluefruit LE development board are used to get and transfer the data of air temperature,relative humidity,pressure and harmful gas.