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Researchers have created an app that uses hundreds of mobile phones to predict earthquakes.

The U.S. Geological Survey hopes to create new types of crowdsourced early warning systems using the technology.

The team tested the system using data from previous earthquakes, and found that it only took a few thousand people in a major city running the app to give accurate predictions.

Myanmar residents gather as they inspect large cracks on a road two days after an earthquake struck the area: Now researchers say mobile phones could create a network of sensors to monitor and act as an early warning system.

Using crowdsourced observations from participating users' smartphones, earthquakes could be detected and analyzed, and customized earthquake warnings could be transmitted back to users. 

'Crowdsourced alerting means that the community will benefit by data generated from the community,' said Sarah Minson, USGS geophysicist and lead author of the study. 

Researchers tested the feasibility of crowdsourced EEW with a simulation of a hypothetical magnitude 7 earthquake, and with real data from the 2011 magnitude 9 Tohoku- oki , Japan earthquake. 

The study, led by scientists at the U.S. Geological Survey and published April 10 in the inaugural volume of the new AAAS journal Science Advances, found that the sensors in smartphones and similar devices could be used to build earthquake warning systems. 

Despite being less accurate than scientific-grade equipment, the GPS (Global Positioning System) receivers in a smartphone can detect the permanent ground movement (displacement) caused by fault motion in a large earthquake.

The results show that crowdsourced EEW could be achieved with only a tiny percentage of people in a given area contributing information from their smartphones. 

For example, if phones from fewer than 5000 people in a large metropolitan area responded, the earthquake could be detected and analyzed fast enough to issue a warning to areas farther away before the onset of strong shaking. 

'The speed of an electronic warning travels faster than the earthquake shaking does,' explained Craig Glennie, a report author and professor at the University of Houston.

The authors found that the sensors in smartphones and similar devices could be used to issue earthquake warnings for earthquakes of approximately magnitude 7 or larger, but not for smaller, yet potentially damaging earthquakes. 

Scientific-grade EEW, such as the U.S. Geological Survey's ShakeAlert system that is currently being implemented on the west coast of the United States, will be able to help minimize the impact of earthquakes over a wide range of magnitudes. 

The GPS (Global Positioning System) receivers in a smartphone can detect the permanent ground movement (displacement) caused by fault motion in a large earthquake.

However, in many parts of the world where there are insufficient resources to build and maintain scientific networks, but consumer electronics are increasingly common, crowdsourced EEW has significant potential.

'The U.S. earthquake early warning system is being built on our high-quality scientific earthquake networks, but crowdsourced approaches can augment our system and have real potential to make warnings possible in places that don't have high-quality networks,' said Douglas Given, USGS coordinator of the ShakeAlert Earthquake Early Warning System. 

The U.S. Agency for International Development has already agreed to fund a pilot project, in collaboration with the Chilean Centro Sismológico Nacional, to test a pilot hybrid earthquake warning system comprising stand-alone smartphone sensors and scientific-grade sensors along the Chilean coast.

'The use of mobile phone fleets as a distributed sensor network — and the statistical insight that many imprecise instruments can contribute to the creation of more precise measurements — has broad applicability including great potential to benefit communities where there isn't an existing network of scientific instruments,' said Bob Iannucci of Carnegie Mellon University, Silicon Valley.