articleAug 11, 2013Closed access

U-Air

Microsoft Research Asia (China) · Zhejiang University · +1 more institution

Indexed incrossref

Abstract

Information about urban air quality, e.g., the concentration of PM2.5, is of great importance to protect human health and control air pollution. While there are limited air-quality-monitor-stations in a city, air quality varies in urban spaces non-linearly and depends on multiple factors, such as meteorology, traffic volume, and land uses. In this paper, we infer the real-time and fine-grained air quality information throughout a city, based on the (historical and real-time) air quality data reported by existing monitor stations and a variety of data sources we observed in the city, such as meteorology, traffic flow, human mobility, structure of road networks, and point of interests (POIs). We propose a…

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Authors

3

Topics & keywords

Keywords
  • Air quality index
  • Beijing
  • Computer science
  • Classifier (UML)
  • Artificial neural network
  • Decision tree
  • Air pollution
  • Random forest
UN Sustainable Development Goals
  • Sustainable cities and communities
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