Fine grained analysis method for unmanned aerial vehicle measurement based on laser-based light scattering particle sensing

Abstract

As an effective particle measurement method, laser-based particle sensors combined with unmanned aerial vehicles (UAVs) can be used for measuring air quality in near ground space. The Sniffer4D Mini2 features portability and real-time acquisition of accurate spatial distribution information on air pollution. Additionally, a new fine-grained analysis method called Co-KNN-DNN has been proposed to assess air quality between flight trajectories, allowing for a more detailed presentation of the continuous distribution of air quality. Therefore, this article introduces an unmanned aerial vehicle measurement fine-grained analysis method based on laser light scattering particle sensors. Firstly, the overall scheme was designed, M30T UAV was selected to carry the portable air quality monitoring equipment, with laser-based laser particulate matter sensor and Mini2, to collect AQI and related attributes of the near-ground layer in the selected research area, to do the necessary processing of the collected data, to build a data set suitable for model input, etc., to train and optimize the model, and to carry out practical application of the model. This article is based on the Co-KNN-DNN model for fine-grained analysis of air quality in spatial dimensions. Three experiments were conducted at different altitudes in the study area to investigate the practical application of fine-grained analysis of near-surface air quality. The experimental results show that the average R-squared value can reach 0.99. Choose to conduct experiments using the M30T UAV equipped with Sniffer4D Mini2 and a laser-based particulate matter sensor. The application research validates the effectiveness and practicality of the Co-KNN-DNN model.