Design of Disaster Collection and Analysis System Using Crowd Sensing and Beacon Based on Hadoop Framework

  • Eun-Su Mo
  • Jae-Pil Lee
  • Jae-Gwang Lee
  • Jun-Hyeon Lee
  • Young-Hyuk Kim
  • Jae-Kwang LeeEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9158)


Currently, disaster data is collected by using site-based, limited regional collection. In this study, a system that collects location information of users that have a mobile device is proposed. The proposed system collects real-time disaster data by using crowd sensing, a user-involved sensing technology. In order to quickly and accurately determine a large amount of unstructured data, among big data frameworks, the Hadoop framework is applied as it efficiently sorts a large amount of data. Also, to enable fast local evacuation alert for users, a beacon-based ad-hoc routing interface was designed As an integrated interface of the proposed systems, a hybrid app based on HTML5, which uses JSON syntax.


Crowd sensing Big data Beacon Disaster Calamity Warning system 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Eun-Su Mo
    • 1
  • Jae-Pil Lee
    • 1
  • Jae-Gwang Lee
    • 1
  • Jun-Hyeon Lee
    • 1
  • Young-Hyuk Kim
    • 2
  • Jae-Kwang Lee
    • 1
    Email author
  1. 1.Department of Computer EngineeringHannam UniversityDaejeonSouth Korea
  2. 2.Public Procurement Service, Information Management DivisionDaejeonKorea

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