An early warning system for seismic events based on the multi-agent model

When a disastrous earthquake is about to occur in a specific territory, there are a series of anomalies that alter the pre-existing natural balances. Seismic swarms, ground deformation, bright flashes, emissions of various gas types (radon, CO2,..), changes in the composition and flow rate groundwater are just some physical-chemical perturbations induced by the growing stress condition borne by the crustal masses. Dilatancy theory and asperity model allow us to interpret the dynamic mechanisms to which the seismic precursors are due: the development of a network of cracks and the sliding of areas with less mechanical resistance are in agreement with seismic, mechanical and geochemical anomalies that occur before to high magnitude earthquakes. In areas with high seismic risk, constant monitoring of geophysical parameters is frequent, carried out using different types of sensors. The MAS (Multi-Agent System) model is one of the most suitable choices for efficiently implementing a seismic alert system, based on the interpretation of experimental data obtained from the sensor network. Using this type of approach, a Seismic Early Warning (SEW) has been created that according to the data acquired by the sensors and through the activities carried out by agent clusters, define the risk of seismic events having magnitude at least six. The SEW system aims to interpret, in real-time, the variations of an adequate number of seismic precursors for specific threshold values, calculated statistically. The integrated and complementary analysis of them, using several specific Boolean expressions, assesses the contribution provided by each parameter for computing the level of risk, divided into soft, medium and hard. The model has been tested with data gathered in New Zealand, a nation with a high seismic and volcanic risk which offers free access to some seismic precursors.