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Monitoring Urban Waterlogging Disaster Using Social Sensors

  • Ningyu Zhang
  • Guozhou ZhengEmail author
  • Huajun Chen
  • Xi Chen
  • Jiaoyan Chen
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 480)

Abstract

Nowadays, urban waterlogging has been one of the most serious global urban hazards in some big cities in the world especially in Chinese cities. While, existing methods fail to cover all locations and forecast the waterlogging trend. Meanwhile, the past one decade has witnessed an astounding outburst in the number of online social media services. For example, when a rainstorm occurs, people make a large number of tweets related to the rainstorm, which enables detection of urban waterlogging promptly, simply by analyzing the tweets. In this paper, we present a semantic method that can monitor urban waterlogging using social sensors. Currently, we use ontology and fuzzy reasoning to analyze waterlogging locations and its severity and build Apps to monitor and forecast waterlogging in more than ten cities in China. With this method, people can easily monitor all the possible urban waterlogging locations with severity and trend, which may reduce the possibility of traffic congestion in a rainstorm.

Keywords

Urban Waterlogging Social Sense Waterlogging Locations Tweets Online Social Media Services 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgement

This work is funded by LY13F020005 of NSF of Zhejiang, NSFC61070156, YB2013120143 of Huawei and Fundamental Research Funds for the Central Universities.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Ningyu Zhang
    • 1
  • Guozhou Zheng
    • 1
    Email author
  • Huajun Chen
    • 1
  • Xi Chen
    • 1
  • Jiaoyan Chen
    • 1
  1. 1.Department of Computer ScienceZhejiang UniversityHangzhouChina

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