Bioinspired Early Prediction of Earthquakes inferred by an Evolving Fuzzy Neural Network Paradigm

Earthquakes could be early predicted as demonstrated by animal’s behavior that are able to detect the leading wave part of the seismic wave (the P-wave). P-waves travel faster than S-wave wave (the shaking wave), so they reach the seismic sensors early (tens of seconds to minutes in advance) compared to the P-wave. A bioinspired framework could be implemented mimicking the animal’s behaviour related to the event of an incoming earthquake. Training a Fuzzy Neural Network to recognize the P-waves, early prediction of earthquakes is feasible and an adequate recovery strategy could be implemented. A technological motivation is the availability of OTS (off-the-shelf) vibration sensors and the fast development of IoT (Internet of Things) toward the new paradigm IoE (Internet of Everything).