By Elaina Koros
A local collaborative initiative to which Stanford is a contributor is asking residents of homes and schools along the Hayward Fault to install earthquake-sensing devices that will create the “Quake-Catcher Network” (QCN) to monitor seismic activity.
Inspired by SeisMac, a program that effectively turns Macintosh computers into seismographs, and BOINC, open-source software that allows individuals to remotely donate their computers’ unused processing power to researchers, QCN attaches sensors to personal computers to create a low-cost yet dense seismic network.
“With 6,000 sensors, it’s amazing what one can do,” said geophysics assistant professor and QCN project leader Jesse Lawrence. “People are used to talking about tens or hundreds even, but not thousands.”
QCN has already installed 2,000 sensors and plans to install at least 6,000 more worldwide in the next couple of years, with the potential to grow to 60,000 or more. Lawrence and USGS researcher Elizabeth Cochran lead the study.
Last weekend, QCN volunteers traveled to areas along the Hayward fault to install the sensors in the floors of project participants and connect them to their computers with USB cables. Equipped with a micro-electro-mechanical systems (MEMS) chip, each sensor can measure acceleration in three directions, making it possible to ascertain the direction of the earth’s movement.
When a MEMS chip detects a strong new motion, it uploads small bits of data to QCN’s server to report a potential new event. If the motion proves isolated to one computer, it will appear as a blip and will not disrupt QCN’s system. However, if the server receives data from many chips, it detects a regional event, such as an earthquake.
“It’s a little bit like the nervous system,” Lawrence said. “If one nerve were to fire on your fingertip, you wouldn’t notice, but when a bunch of them fire all at once, you notice that maybe there’s an event there.”
“The sensor doesn’t interfere at all with your computer, so you don’t see it actually working, but you know it’s there and that it’s sending data to this big network,” said QCN administrator Claudia Baroni, who organizes volunteers and finances. “It’s a huge amount of people working toward the same goal.”
The low cost of each sensor makes building a dense seismic network possible. Although larger sensors can cost anywhere from $25,000 to $50,000 dollars and may cost an additional $10,000 a year to maintain, QCN’s highest-quality smaller sensors each cost only $150. An individual small sensor cannot measure ground motion as accurately as a larger sensor, but the sum of the small sensors creates a network, which can be better for monitoring strong motion.
“We’re not going to be observing earthquakes across the planet, but we’ll be able to detect them really rapidly and very well up close, and this project is really aimed at looking at how the earthquakes look up close,” Lawrence said.
QCN experimented with a similar program in New Zealand and plans to expand beyond the Hayward fault, covering the entire Bay Area and parts of Southern California, the Pacific Northwest, Anchorage, Salt Lake City and Memphis. Expanding internationally to Mexico, Taiwan, Peru and Chile is also a possibility, the researchers said.
QCN is funded by a National Science Foundation grant and small sums of money from agencies like the Southern California Earthquake Center, the Incorporated Research Institutions for Seismology and the United Parcel Service (UPS). This funding allows QCN to provide sensors to participants in certain regions for free. However, all individuals can buy sensors on QCN’s website for $49, and teachers in all regions can request up to three sensors at a subsidized rate of five dollars.
“I love that it gets the community involved, because I am very passionate about helping people, and I think this is a great way to educate people about earthquakes, because we’re installing seismometers in their homes and getting people involved in awareness,” said third-year geophysics graduate student Angela Chung.
QCN’s applied scientific objective is to determine whether or not the network can detect an earthquake’s magnitude and location rapidly enough to alert the affected community before the waves actually reach them, creating an earthquake early-warning system. Additionally, QCN sensors can detect earthquake magnitude, so they could help emergency services find those who were hit the hardest by an earthquake.
“[The goal of the project] from my perspective is to learn more about the Earth,” Lawrence said. “From the practical side, it’s to help us better understand earthquake hazards and how to better prepare and better respond to earthquake hazards.”