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Abstract:
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The Earthquake Network project (www.earthquakenetwork.it) implements an earthquake early warning system based on a smartphone network at the global level. Thanks to the accelerometer mounted in each smartphone, the network is exploited to detect quakes in real time. When a quake is detected, a warning is issued and the population who lives at a given distance from the epicentre can be alerted in advance. In this work we describe the statistical method which is used to detect the quake from the signals collected from the smartphones and to estimate the location of the epicentre. Smartphone with the Earthquake Network app installed are part of the network and they send a signal to a server every time an acceleration is detected. Since smartphones are not professional seismometers, the number of false signals is very high. In order to filter out signals related to anthropic noise, we adopt a statistical method based on the likelihood approach. The method allows to detect real quakes while controlling the probability of false alarm and to estimate the location of the epicentre. During the last 4 years, the network was able to detect more than 370 earthquakes in real time.
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