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Poster: SaveAlert: an efficient and scalable sensor-driven danger detection system

Published: 07 September 2014 Publication History

Abstract

SaveAlert is an adaptive framework for crowd-monitoring and danger-detection using off-the-shelf smartphones and other peripherals such as smartwatches. It is a system that provides users with an increased awareness of their surroundings by detecting and notifying them of impending danger, by relying only on sensor data collected from the users. Our framework's novelty is in how it performs efficient sensor data collection from potentially a large number of people by limiting the disturbance and stress on the existing Wi-Fi and cellular infrastructure. To the best of our knowledge, this is the first crowd-monitoring framework that takes advantage of peer-to-peer connections to perform local aggregation to alleviate the stress on existing infrastructures for better scalability and efficiency.

References

[1]
http://www.amberalert.gov/.
[2]
Robin Kravets, Hilfi Alkaff, Andrew Campbell, Karrie Karahalios, and Klara Nahrstedt. Crowdwatch: Enabling in-network crowd-sourcing. In Proceedings of the Second ACM SIGCOMM Workshop on Mobile Cloud Computing, MCC '13, 2013.
[3]
Ólafur Helgason and Sylvia T. Kouyoumdjieva. Enabling multiple controllable radios in omnet++ nodes. In Proceedings of the 4th International ICST Conference on Simulation Tools and Techniques, SIMUTools '11, 2011.
[4]
Guliz Seray Tuncay, Kirill Varshavskiy, and Robin Kravets. Demo: Savealert: Design for a sensor-driven crowdwatch danger detection system. In Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys '14, 2014.

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Published In

cover image ACM Conferences
MobiCom '14: Proceedings of the 20th annual international conference on Mobile computing and networking
September 2014
650 pages
ISBN:9781450327831
DOI:10.1145/2639108
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 September 2014

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Author Tags

  1. crowd dynamics
  2. crowd monitoring
  3. crowd sensing
  4. danger detection
  5. safety

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MobiCom'14
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MobiCom '14 Paper Acceptance Rate 36 of 220 submissions, 16%;
Overall Acceptance Rate 440 of 2,972 submissions, 15%

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