HR: 0800h
AN: ED11C-0633    [Abstracts]
TI: The Quake Catcher Network: Cyberinfrastructure Bringing Seismology into Schools and Homes
AU: * Lawrence, J F
EM: jfl77@stanford.edu
AF: Stanford University, Department of Geophysics 397 Panama Mall Mitchell Building 360 Stanford University, Stanford, CA 94305-2215, United States
AU: Cochran, E S
EM: cochran@ucr.edu
AF: UC Riverside, Department of Earth Sciences Geology Building, Room 434 University of California, Riverside, Riverside, CA 92521-0423, United States
AB: We propose to implement a high density, low cost strong-motion network for rapid response and early warning by placing sensors in schools, homes, and offices. The Quake Catcher Network (QCN) will employ existing networked laptops and desktops to form the world's largest high-density, distributed computing seismic network. Costs for this network will be minimal because the QCN will use 1) strong motion sensors (accelerometers) already internal to many laptops and 2) nearly identical low-cost universal serial bus (USB) accelerometers for use with desktops. The Berkeley Open Infrastructure for Network Computing (BOINC!) provides a free, proven paradigm for involving the public in large-scale computational research projects. As evidenced by the SETI@home program and others, individuals are especially willing to donate their unused computing power to projects that they deem relevant, worthwhile, and educational. The client- and server-side software will rapidly monitor incoming seismic signals, detect the magnitudes and locations of significant earthquakes, and may even provide early warnings to other computers and users before they can feel the earthquake. The software will provide the client-user with a screen-saver displaying seismic data recorded on their laptop, recently detected earthquakes, and general information about earthquakes and the geosciences. Furthermore, this project will install USB sensors in K-12 classrooms as an educational tool for teaching science. Through a variety of interactive experiments students will learn about earthquakes and the hazards earthquakes pose. For example, students can learn how the vibrations of an earthquake decrease with distance by jumping up and down at increasing distances from the sensor and plotting the decreased amplitude of the seismic signal measured on their computer. We hope to include an audio component so that students can hear and better understand the difference between low and high frequency seismic signals. The QCN will provide a natural way to engage students and the public in earthquake detection and research.
UR: http://qcn.stanford.edu
DE: 0845 Instructional tools
DE: 7212 Earthquake ground motions and engineering seismology
DE: 7219 Seismic monitoring and test-ban treaty verification
DE: 7290 Computational seismology
DE: 7294 Seismic instruments and networks (0935, 3025)
SC: Education and Human Resources [ED]
MN: 2007 Fall Meeting