Towards crowd-aware sensing platform for metropolitan environments

  • Authors:
  • Saumay Pushp;Chulhong Min;Youngki Lee;Chi Harold Liu;Junehwa Song

  • Affiliations:
  • KAIST, Daejeon, Republic of Korea;KAIST, Daejeon, Republic of Korea;KAIST, Daejeon, Republic of Korea;IBM Research, Beijing, China;KAIST, Daejeon, Republic of Korea

  • Venue:
  • Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
  • Year:
  • 2012

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Abstract

In this paper, we propose an in-situ Crowd-aware Sensing Platform, called "CrowdMon", which envisions the cooperation among mobile users in highly crowded urban areas such as metro and square. CrowdMon establishes a spontaneous connection from co-located users in a semantic proximity and enables them to share contextual information such as location, ambient music, and mood of places. To the best of our knowledge, CrowdMon is the first attempt to support crowd-aware services at a platform level. We show interesting use cases of CrowdMon and an initial system design to realize the crowd-based context sharing.