论文标题
使用车辆跟踪系统的PM2.5集中预测框架：从原因到效果
A PM2.5 concentration prediction framework with vehicle tracking system: From cause to effect
论文作者
论文摘要
空气污染是一个新兴的问题，尤其是在发达国家和发展中国家中需要解决的问题。在越南，在河内和胡志明市等大城市中，空气污染也是一个有关问题的问题，那里的空气污染主要来自汽车和摩托车等车辆。为了解决该问题，本文着重于开发一个解决方案，该解决方案可以通过计算交通中的车辆数量来估计发射的PM2.5污染物。我们首先研究了最近的对象检测模型，并开发了自己的交通监视系统。观察到的交通密度与测量的PM2.5相似，随着时间的推移滞后，这表明交通密度与PM2.5之间存在关系。我们与数学模型进一步表达了这种关系，该数学模型可以根据观察到的交通密度估算PM2.5值。估计的结果显示与城市地区环境中测得的PM2.5图有很大的相关性。
Air pollution is an emerging problem that needs to be solved especially in developed and developing countries. In Vietnam, air pollution is also a concerning issue in big cities such as Hanoi and Ho Chi Minh cities where air pollution comes mostly from vehicles such as cars and motorbikes. In order to tackle the problem, the paper focuses on developing a solution that can estimate the emitted PM2.5 pollutants by counting the number of vehicles in the traffic. We first investigated among the recent object detection models and developed our own traffic surveillance system. The observed traffic density showed a similar trend to the measured PM2.5 with a certain lagging in time, suggesting a relation between traffic density and PM2.5. We further express this relationship with a mathematical model which can estimate the PM2.5 value based on the observed traffic density. The estimated result showed a great correlation with the measured PM2.5 plots in the urban area context.
