New sensor technologies and computer algorithms that allow us to predict earthquakes, floods and famines before they happen. So now we're safe, right? Wrong. The big question is how we'll use this information, and whether we can warn people in time.
Photo by Robert A. Eplett/CAL EMA.
Over at Wired, I've got an article about this issue, and the creation of a California earthquake warning network. Here's how it starts:
California is studded with a network of sensors that can perceive almost any motion in the ground, including the slightest perturbation of the Earth’s crust. The network began as a seismology research project, to track earthquakes in this fault-ridden part of the world. But as technologies developed, the network became more sophisticated, gathering far more data than ever before. Eventually, the science of earthquake observation reached a tipping point, and became the science of earthquake prediction.
Richard Allen, director of the UC Berkeley Seismology Laboratory, now has a prototype app on his computer called ShakeAlert that emits an annoying clanging noise up to a minute before an earthquake hits his office. Most of these quakes are so small you can barely perceive them, but ShakeAlert has successfully issued warnings in advance of all three of the quakes that hit the Bay Area in the past year. And, though a minute warning may not seem like much, it’s enough time to stop a train, pull over on the freeway, initiate shutdown at a power station, or stabilize a patient in surgery. It’s the kind of warning that could be a gamechanger for people in earthquake country.
ShakeAlert is just one of a new generation of disaster prediction technologies that are changing the odds of survival in the event of earthquakes, floods, mudslides, and even famines. Using sensor networks and algorithms that model the behavior of complex systems, we’re now able to predict the future more accurately than ever before. The question now is what we’ll do with our newfound power to look five minutes into the future.
You can read the rest of the article over at Wired