The article presents the study of Particulate Matter air pollution with PM₁, PM_2,5 and PM₁₀ by means of a low-cost sensors mounted on Unmanned Aerial Vehicles. The article is divided into two parts. In first part pollution measurement system is described. In second part expert system for optimization of flight parameters is described. The research was conducted over a municipal cemetery area in Poland. The obtained results were analyzed through an inductive knowledge management system (decision tree method) for classification analysis of air pollution. The decision tree mechanism would be used to optimize flight parameters taking into account the air pollution parameters. The analysis was made from the influence of PM concentration point of view, depending on the altitude. The decision tree method was used, which allowed to determine, among other aspects, which PM indicator should be measured and which altitude plays a greater role in the optimization of air pollution measurements by means of cheap sensors mounted on drones. As a result of the analysis, the optimum flight altitude of the measurement drone in the specified area was determined.

本文介绍了 PM ₁、PM _2,5和 PM ₁₀对颗粒物空气污染的研究通过安装在无人驾驶飞行器上的低成本传感器。文章分为两部分。第一部分描述了污染测量系统。第二部分描述了飞行参数优化专家系统。该研究是在波兰的一个市政公墓地区进行的。通过归纳知识管理系统（决策树方法）对所得结果进行分析，用于空气污染的分类分析。考虑到空气污染参数，决策树机制将用于优化飞行参数。分析是从 PM 浓度影响的角度进行的，取决于海拔高度。使用了决策树方法，它允许确定，除其他方面外，应该测量哪个 PM 指标以及哪个高度在通过安装在无人机上的廉价传感器优化空气污染测量方面发挥着更大的作用。根据分析结果，确定了测量无人机在指定区域内的最佳飞行高度。