S22C-01:
Large-N in Volcano Settings: Volcanosri
Tuesday, 16 December 2014: 10:20 AM
Jonathan M Lees1, WenZhan Song2, Guoliang Xing3, Steve Vick4 and Dennis Phillips3, (1)University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, (2)Georgia State University, Computer Sciences, Atlanta, GA, United States, (3)Michigan State University, Department of Computer Science & Engineering, East Lansing, MI, United States, (4)Prime Audio Inc., Atlanta, GA, United States
Abstract:
We seek a paradigm shift in the approach we take on volcano monitoring where the compromise from high fidelity to large numbers of sensors is used to increase coverage and resolution. Accessibility, danger and the risk of equipment loss requires that we develop systems that are independent and inexpensive. Furthermore, rather than simply record data on hard disk for later analysis we desire a system that will work autonomously, capitalizing on wireless technology and in field network analysis. To this end we are currently producing a low cost seismic array which will incorporate, at the very basic level, seismological tools for first cut analysis of a volcano in crises mode. At the advanced end we expect to perform tomographic inversions in the network in near real time. Geophone (4 Hz) sensors connected to a low cost recording system will be installed on an active volcano where triggering earthquake location and velocity analysis will take place independent of human interaction. Stations are designed to be inexpensive and possibly disposable. In one of the first implementations the seismic nodes consist of an Arduino Due processor board with an attached Seismic Shield. The Arduino Due processor board contains an Atmel SAM3X8E ARM Cortex-M3 CPU. This 32 bit 84 MHz processor can filter and perform coarse seismic event detection on a 1600 sample signal in fewer than 200 milliseconds. The Seismic Shield contains a GPS module, 900 MHz high power mesh network radio, SD card, seismic amplifier, and 24 bit ADC. External sensors can be attached to either this 24-bit ADC or to the internal multichannel 12 bit ADC contained on the Arduino Due processor board. This allows the node to support attachment of multiple sensors. By utilizing a high-speed 32 bit processor complex signal processing tasks can be performed simultaneously on multiple sensors. Using a 10 W solar panel, second system being developed can run autonomously and collect data on 3 channels at 100Hz for 6 months with the installed 16Gb SD card. Initial designs and test results will be presented and discussed.