skip to main content
research-article
Free Access

Community sense and response systems: your phone as quake detector

Published:01 July 2014Publication History
Skip Abstract Section

Abstract

The Caltech CSN project collects sensor data from thousands of personal devices for real-time response to dangerous earthquakes.

References

  1. Aberer, K., Sathe, S., Chakraborty, D., Martinoli, A., Barrenetxea, G., Faltings, B., and Thiele, L. Opensense: Open community driven sensing of environment. In Proceedings of the ACM SIGSPATIAL International Workshop on GeoStreaming (San Jose, CA, Nov. 2--5). ACM Press, New York, 2010, 39--42. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Aoki, P.M., Honicky, R.J., Mainwaring, A., Myers, C., Paulos, E., Subramanian, S., and Woodruff, A. A vehicle for research: Using street sweepers to explore the landscape of environmental community action. In Proceedings of the 27th International Conference on Human Factors in Computing Systems (Boston, Apr 4-9). ACM Press, New York, 2009, 375--384. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. J. Bilmes. A Gentle Tutorial on the EM Algorithm Including Gaussian Mixtures and Baum-Welch. International Computer Science Institute Technical Report TR-97-021, May 1997.Google ScholarGoogle Scholar
  4. Borokhov, P., Blandin, S., Samaranayake, S., Goldschmidt, O., and Bayen, A. An adaptive routing system for location-aware mobile devices on the road network. In Proceedings of the 14th International IEEE Conference on Intelligent Transportation Systems (Washington, D.C., Oct. 5--7). IEEE Computer Society Press, New York, 2011, 1839--1845.Google ScholarGoogle ScholarCross RefCross Ref
  5. Boulos, M.N.K, Resch, B., Crowley, D.N., Breslin, J.G., Sohn, G., Burtner, R., Pike, W.A., Jezierski, E., and Chuang, K.-Y.S. Crowdsourcing, citizen sensing and sensor Web technologies for public and environmental health surveillance and crisis management: Trends, OGC standards, and application examples. International Journal of Health Geographics 10, 1 (2011).Google ScholarGoogle ScholarCross RefCross Ref
  6. Burke, J., Estrin, D., Hansen, M., Parker, A., Ramanathan, N., Reddy, S., and Srivastava, M.B. Participatory sensing. In the Workshop on World Sensor Web Workshop (Boulder, CO, Oct. 31--Nov. 3, 2006), 1--5.Google ScholarGoogle Scholar
  7. Chen, X., Qi, Y., Bai, B., Lin, Q., and Carbonell, J.G. Sparse latent semantic analysis. In Proceedings of the SIAM International Conference on Data Mining (Mesa, AZ, Apr. 28--30). SIAM, Philadelphia, 2011, 474--485.Google ScholarGoogle Scholar
  8. Cochran, E.S., Lawrence, J.F., Christensen, C., and Jakka, R.S. The Quake-Catcher Network: Citizen science expanding seismic horizons. Seismological Research Letters 80, 1 (2009), 26--30.Google ScholarGoogle ScholarCross RefCross Ref
  9. Ervasti, M., Dashti, S., Reilly, J., Bray, J.D., Bayen, A., and Glaser, S. iShake: Mobile phones as seismic sensors, user study findings. In Proceedings of the 10th International Conference on Mobile and Ubiquitous Multimedia (Beijing, Dec. 7--9). ACM Press, New York, 2011, 43--52. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Faulkner, M., Liu, A., and Krause, A. A fresh perspective: Learning to sparsify for detection in massive noisy sensor networks. In Proceedings of the 12th ACM/IEEE International Conference on Information Processing in Sensor Networks (Philadelphia, Apr. 8--11). ACM Press, New York, 2013, 7--18. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Faulkner, M., Olson, M., Chandy, R., Krause, J., Chandy, K.M., and Krause, A. The next big one: Detecting earthquakes and other rare events from community-based sensors. In Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks (Chicago, Apr. 12--14). ACM Press, New York, 2011, 13--24.Google ScholarGoogle Scholar
  12. Feldman, D., Faulkner, M., and Krause, A. Scalable training of mixture models via coresets. In Proceedings of the Neural Information Processing Systems Annual Conference (Granada, Spain, Dec. 12--14, 2011).Google ScholarGoogle Scholar
  13. Har-Peled, S. and Mazumdar, S. On coresets for k-means and k-median clustering. In Proceedings of the 36th Annual ACM Symposium on Theory of Computing (Chicago, June 13--15). ACM Press, New York, 2004, 291--300. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Hoh, B., Gruteser, M., Herring, R., Ban, J., Work, D., Herrera, J.C., Bayen, A.M. Annavaram, M., and Jacobson, Q. Virtual trip lines for distributed privacy-preserving traffic monitoring. In Proceedings of the International Conference on Mobile Systems, Applications, and Services (Breckenridge, CO, June 17--20, 2008), 17--20. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Kapoor, A., Eagle, N., and Horvitz, E. People, quakes, and communications: Inferences from call dynamics about a seismic event and its influences on a population. In Proceedings of AAAI Symposium on Artificial Intelligence for Development (Atlanta, July 11--15). AAAI, Palo Alto, CA, 2010, 51--56.Google ScholarGoogle Scholar
  16. Krause, A., Horvitz, E., Kansal, A., and Zhao, F. Toward community sensing. In Proceedings of the ACM/IEEE International Conference on Information Processing in Sensor Networks (St. Louis, MO, Apr. 22--24). IEEE Computer Society Press, Washington, D.C., 2008, 481--492. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Liu, A., Olson, M., Bunn, J., and Chandy, K.M. Towards a discipline of geospatial distributed event-based systems. In Proceedings of the Sixth ACM International Conference on Distributed Event-Based Systems (Berlin, July 16--20). ACM Press, New York, 2012, 95--106. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Mun, M., Reddy, S., Shilton, K., Yau, N., Burke, J., Estrin, D., Hansen, M., Howard, E., West, R., and Boda, P. Peir: The personal environmental impact report as a platform for participatory sensing systems research. In Proceedings of the Seventh International Conference on Mobile Systems, Applications, and Services (Kraków, Poland, June 22--25). ACM Press, New York, 2009, 55--68. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Neill, D.B. Fast subset scan for spatial pattern detection. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 74 (2012), 337--360.Google ScholarGoogle Scholar
  20. Thiagarajan, A., Ravindranath, L., LaCurts, K., Madden, S., Balakrishnan, H., Toledo, S., and Eriksson, J. VTrack: Accurate, energy-aware road traffic delay estimation using mobile phones. In Proceedings of the Seventh ACM Conference on Embedded Networked Sensor Systems (Berkeley, CA, Nov. 4--6). ACM Press, New York, 2009, 85--98. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Tsitsiklis, J.N. Decentralized detection by a large number of sensors. Mathematics of Control, Signals, and Systems 1, 2 1988, 167--182.Google ScholarGoogle Scholar

Index Terms

  1. Community sense and response systems: your phone as quake detector

                                      Recommendations

                                      Comments

                                      Login options

                                      Check if you have access through your login credentials or your institution to get full access on this article.

                                      Sign in

                                      Full Access

                                      • Published in

                                        cover image Communications of the ACM
                                        Communications of the ACM  Volume 57, Issue 7
                                        July 2014
                                        98 pages
                                        ISSN:0001-0782
                                        EISSN:1557-7317
                                        DOI:10.1145/2622628
                                        • Editor:
                                        • Moshe Y. Vardi
                                        Issue’s Table of Contents

                                        Copyright © 2014 ACM

                                        Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

                                        Publisher

                                        Association for Computing Machinery

                                        New York, NY, United States

                                        Publication History

                                        • Published: 1 July 2014

                                        Permissions

                                        Request permissions about this article.

                                        Request Permissions

                                        Check for updates

                                        Qualifiers

                                        • research-article
                                        • Popular
                                        • Refereed

                                      PDF Format

                                      View or Download as a PDF file.

                                      PDFChinese translation

                                      eReader

                                      View online with eReader.

                                      eReader

                                      HTML Format

                                      View this article in HTML Format .

                                      View HTML Format