论文标题
卢旺达的趋势分析和预测空气污染
Trend analysis and forecasting air pollution in Rwanda
论文作者
论文摘要
尽管缺乏数据是大多数低收入国家和中等收入国家的全球问题，但空气污染是全球主要的公共卫生问题。以细颗粒物（PM2.5）形式的环境空气污染超过了卢旺达的世界卫生组织指南，每天平均每米的平均值约为42.6微克。监测和缓解策略需要对设备收集污染数据进行昂贵的投资。低成本的传感器技术和机器学习方法已成为替代解决方案，以获取可靠的决策信息。本文分析了卢旺达的空气污染趋势，并提出了适用于由卢旺达部署的低成本传感器网络收集的数据的预测模型。
Air pollution is a major public health problem worldwide although the lack of data is a global issue for most low and middle income countries. Ambient air pollution in the form of fine particulate matter (PM2.5) exceeds the World Health Organization guidelines in Rwanda with a daily average of around 42.6 microgram per meter cube. Monitoring and mitigation strategies require an expensive investment in equipment to collect pollution data. Low-cost sensor technology and machine learning methods have appeared as an alternative solution to get reliable information for decision making. This paper analyzes the trend of air pollution in Rwanda and proposes forecasting models suitable to data collected by a network of low-cost sensors deployed in Rwanda.
