1 / 15

VolcanoSRI: 4D Volcano Seismic Tomography in a Large-scale Sensor Network

VolcanoSRI: 4D Volcano Seismic Tomography in a Large-scale Sensor Network. WenZhan Song, Ph.D. Associate Professor Director of Sensorweb Research Lab Department of Computer Science Georgia State University. VolcanoSRI: Volcano Seismic Realtime Imaging.

amina
Download Presentation

VolcanoSRI: 4D Volcano Seismic Tomography in a Large-scale Sensor Network

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. VolcanoSRI: 4D Volcano Seismic Tomography in a Large-scale Sensor Network WenZhan Song, Ph.D. Associate Professor Director of Sensorweb Research Lab Department of Computer Science Georgia State University

  2. VolcanoSRI: Volcano Seismic Realtime Imaging • VolcanoSRI: Volcano Seismic Realtime Imaging • * make the fictional holographic projector “Virgil” in Supervolcano film a reality: http://www.youtube.com/watch?v=WF-RKzqNtz0 (3:49) NSF CDI($1.83M 2011-2015): VolcanoSRI: 4D Volcano Tomography in a Large-scale Sensor Networks (PI: Song (GSU), Co-PI: Lees (UNC), Xing (MSU)). http://sensorweb.cs.gsu.edu/research/VolcanoSRI.html

  3. VolcanoSRI: Vigil in Supervolcano Film

  4. VolcanoSRI: Volcano Seismic Realtime Imaging The tentative deployment map at Ecuador

  5. Instrumentation

  6. Tomographic Inversion • n – number of nodes in the network • m – dimension of tomography; thus the size of tomography model is m3 A nxm3 s m3x1 t nx1 In VolcanoSRI, n =500, m = 500, although each row Ai is very sparse. = node i Each node i only has Ai and ti, e.g., the i-th row info in A and t. All nodes together to find s such that ||As-t|| is minimized. s is the 3D velocity model and can be very big (e.g., 500x500x500, if m=500). Here, A is just illustrated as the matrix for one EQ event only. There will be many EQ events and EQ event is processed one after another.

  7. Multi-resolution Evolving Tomography

  8. Vertical Tomograph Partition

  9. Accuracy

  10. Robustness

  11. Communication Cost

  12. Oilfield Explorations http://www.forbes.com/2004/10/04/cx_af_1004oilimaging.html

  13. Thanks for listening! Thank you! Questions or Comments? Dr. WenZhan Song wsong@gsu.edu (404)413-5734 More information: http://sensorweb.cs.gsu.edu Sensorweb Service Portal Sensor Web: Connecting Dots for Intelligence

  14. Space In-situ Sensor Web NASA project ($1.6M 2007-2009): Optimized Autonomous Space In-situ Sensorweb. Collaborative project between WSU, USGS and JPL (PI: Song, Co-I: Shirazi, LaHusen, Kedar, Chien, Webb). NASA Video: http://sensorweb.cs.gsu.edu/news.html Project website: http://sensorweb.cs.gsu.edu/research/oasis.html

  15. omnidirectional antenna GPS antenna air-drop hook ash detector seismic sensor - iMote2 and accessories- infrasonic sensors- air-alkaline batteries

More Related