Monitoring earthquakes is tricky business. They occur very sporadically in both space and time, so to record them you need a continuously operating measurement network. Such networks are traditionally very expensive both to install, and to operate. What if there was a better way? It turns out there might be. The brainchild of University of California-Riverside professor Elizabeth Cochran, the Quake-Catcher Network wants to do for seismic monitoring what SETI@home did for the search for extra-terrestrial life.
The Quake-Catcher Network is based on the idea that there are already thousands of seismic monitoring devices out there, we just need to harness them: namely, most Apple laptops made since 2005, most IBM laptops made since 2003, and a number of laptops made by HP, Acer, and others. These laptops include an accelerometer that is designed to park the hard drive heads in the event of a sudden shock to the computer. In addition to falls, this accelerometer can also measure any other vibrations, such as those of an earthquake.
If history has taught the computer industry nothing else, it is that if you give a geek a tool to do one thing, he or she will find a way to use it for five others. So when Apple introduced the Sudden Motion Sensor in all of its laptops, it should be no surprise that geeks everywhere drooled at the possibilities.
Perhaps the first use was for a computer game. Like the Wii controller, the ability to detect the movement, and thus orientation, of a laptop provides infinite possibilities for controlling a computer game. One innovating soul took it upon himself to find a way to control Marble Madness by moving his laptop around. Between the smackbook, pong, iAlertu, and others, geeks everywhere proved how useful and how much fun having an accelerometer could be.
In the midst of all that, another application came out. Arguably the simplest of the bunch, SeisMac did not actually do anything with the data, it just showed it to you. But now you could tap your laptop and watch the raw data go flying by, or hit the desk and watch the vibrations that occur in multiple directions. While it can be an interesting teaching tool, SeisMac has not been used for actual research.
Putting this tool to good use
When Cochran saw the Seismac program in 2006, she saw that the natural evolution of the idea was to network a group of laptops together. The idea of a low-cost, high-density seismic network was intriguing, and she and Dr. Jesse Lawrence, a colleague at Stanford University, began working on what will ultimately become the Quake Catcher Network.
Much like other distributed computing projects, most of this network will be made up of volunteer computers. Volunteers will download a program which will run in the background and as a screensaver. This program will record data anytime the user is not using the computer. It will also display a screensaver that will show recent earthquakes on a globe, as well as the data that the laptop is recording.
In the future, they hope to get funding to install accelerometers in schools around the Bay Area in California. This network will be a combination research and educational outreach tool. They hope to install USB accelerometers on desktops in hundreds of schools. Teachers can then use these accelerometers to show students simple seismic effects. For example, by bouncing a heavy ball on the ground at increasing distance from the accelerometer, they can show the decrease in magnitude as a function of distance from an earthquake epicenter. In addition, by making the public an active part of the network, they hope to increase awareness of seismic hazards.
Combining the volunteer and school-based systems they hope to have 1,000 to 100,000 systems in California. Eventually this could be scaled up to a global network. This project has the potential to have large benefits to smaller countries that cannot afford a standard seismic network. The cost of this network may be around $50 per USB stick, or effectively free for each additional node for the volunteer portion. Unfortunately, this seismic network has many potential problems.
Most seismic monitoring networks go to great pains to avoid spurious shakes. One does not generally install a monitoring station under a freeway, on a train, or on the third floor of a building, and one never, ever, installs a permanent monitoring station in one's lap. But these are all scenarios that could not be avoided for Cochran and Lawrence.
To avoid the problems inherent in noisy environments, the Quake-Catcher Network will only record data during times when the screensaver is active, and it will use two statistical filters on that data as well. First, it will filter noise on each individual computer. The local software will keep a running measure of the variance of the signal and only pass on signals that exceed some threshold (e.g., 99.999 percent of the normal noise). These top 0.001 percent of signals will be passed on to a server, but even most of these will be due to local vibrations.
The server can run another statistical check to verify that this is an earthquake, not just a large truck, your sister slamming the bathroom door, or a herd of wild school children running down the hall. All of the typical noise in the system will be highly localized. While it is likely that more than one laptop may be knocked at the same time, it is unlikely that all of the laptops in the network will (or even a reasonably large number of them). Again, using a 99 percent-plus confidence interval, they are able to pick out earthquakes with a high degree of confidence in their test simulations.
Time and place
In addition to dealing with noisy environments, there are other problems that must be taken care of before these data become useful. First of all, they need to know the location of the computer. The strength of an earthquake varies depending on how far one is from the epicenter, thus it is important to get the laptop location as close as possible.
The QCN plan to use three techniques to determine a laptop's locations. The best method is to have users enter their locations through a built-in Google Maps interface. Users can enter several locations and tie them to IP addresses. Because IP addresses can change each time one connects to the network, they only look at the three most significant bytes of the IP address. If a user does not specify a location, then they approximate the location based on the IP address. This is not as accurate, but it gives them a rough location. Finally, they can ask users where they were at the time of an earthquake after the quake has been recorded.
Second, they need to know the exact time that the signal was recorded. Time is an easier problem. The QCN will use the network time protocol to keep the clocks in sync with a local server that they will keep in sync with an atomic clock.
What do the researchers hope to get out of this network? There are already seismic networks spread out across the world. Indeed, California has thousands of stations. Cochran and Laurence hope that by using 100,000 sensors in a very small geographic region, they can gain a better measure of the spatial pattern of earthquake movement as well as potentially create a robust earthquake early warning system... and, of course, teach people a thing or two about earthquakes.
A better early warning system
QCN hopes to create a more robust early warning system by having a larger number of sensors. When you have a denser seismic network, you are more likely to have a station close to the epicenter, and thus you will receive an earlier warning. If this system works out, they may be able to give 10 to 15 seconds' warning before an earthquake hits.
This system is based on the fact that there are two major types of seismic waves, P-waves and S-waves. P-waves, or primary/parallel waves, shake the earth parallel to the direction the wave traveling and travel faster than S-waves. S-waves, or secondary/shear waves, shake the earth perpendicular to the direction of travel. They hope to be able to detect the P-waves which may reach a location 15-20 seconds before the more destructive S-waves.
The developers estimate that it will take up to five seconds to conclude that an earthquake is occurring, leaving them 10 to 15 seconds to act. This estimate includes over three seconds for the P-wave to be detected, 0.1 seconds for the local computer to set off a trigger, 1.5 seconds to notify the server, and 6ms for the server to determine if this is real or a false positive. In contrast, the current seismic network in California takes 10-15 seconds to detect an earthquake.
While this may not sound like much time to enact any meaningful safety measures, there are a number of things that can be done in this time. For example, gas lines can be shut down, trains can be slowed down, elevators can be told to stop on the next floor, students can crawl under desks, and manufacturing plants, power plants, and hospitals can take a number of safety measures... all in 10 seconds, given the proper infrastructure.
This is not something that will be happening soon. There is simply too much potential for false positives (and most of the above safety measures cost a lot of money). However, the team hopes to initially use the network for research into supplementing existing seismic hazard systems. If this network is ever used as a warning system, it will be to inform existing seismic hazard organizations which can then make a decision to issue a warning or not.
The research aspect of this study will be more useful in the short term. The larger number of stations will provide better data for comparison to models. This will improve back-projections of the actual earthquake center, and a better understanding of wave propagation dynamics.
Additionally, QCN will record data that most seismic monitoring stations avoid. Most stations are carefully located on the ground to measure the ground movement directly. The new network will provide more insight into the shaking that occurs in locations where people are working and living on a regular basis. For example, the network will monitor laptops that are sitting on desks, or on the fifth floor of buildings.
A magnitude 3.7 earthquake recorded by a laptop sitting in a closet
In preliminary data collection, the developers have identified relatively small earthquakes. The first earthquake they recorded was a magnitude 3.7 that was 100km away from the laptop that recorded it. This was with a laptop sitting quietly on its own, but as you can see from the image above, the signal is very clear. QCN is expecting to be able to reliably detect earthquakes with magnitude 4.5 or larger; the team is being cautious about predicting how small an earthquake they will be able to reliably detect, but from the clarity of the signal in the 3.7 earthquake, it does not seem unreasonable for them to be able to detect even smaller earthquakes.
In the future they would like to expand the network even further. Eventually they would like to include smart phones like the iPhone that have simple accelerometers in them. There is even someone working on creating seismic monitoring software that will run on the Wii using its controller's accelerometer.
In the near term, they expect to have beta software available to download sometime in June. Now they just need a metric to get that competitive, "I've folded more proteins, found more aliens, detected more earthquakes than you" thing going.