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Accelerometers equipped smartphones can detect seismic events in the same way as specialized seismological stations. However, the false alarm of the low-end sensors cannot meet the stringent requirement of earthquake detection applications. While a lot of work has been done to reduce the white noise, little of them focus on eliminating the adulteration caused by human motion. To that end, we first analyze the features of the sampling data for daily purpose, and employ a noise reduction strategy to extract the event features in data pre-processing to stick the p-waves out. Secondly, a new STA/LTA+DWT P-wave pickup algorithm is proposed to recognize the false alarms from the mixed events. The simulation results show that the proposed scheme can maintain the precision of positive decision to 90%, while significantly lowering the false alarm by about a third.

False Alarm Reduction from Anomalous Seismic Events Detected by Smart Phones