Event Detection Techniques and Optimization for Earthquake Early Warning Application

Abstract

An efficient, robust, reliable Earthquake Early Warning (EEW) can play a vital role in hazard mitigation by reducing false and missed alarms. This study represents a comparative analysis of state-of-the-art real-time event detection techniques for the EEW. In real-time event detection, a trade-off between detection reliability and delay in detection exists dominantly. This trade-off is the motivation behind the implementation and performance optimization of event detection techniques, namely Short-time-average over Long-time-average (STA/LTA), Multi-window Algorithm (MWA), and Modified Energy Ratio (MER) for EEW applicability. Earthquake data from the Kyoshin Network (K-NET), Japan along with noise events recorded by the Seismic Sensing Nodes (SSN) at the NCR, India is used for analysis and validation of detection techniques for the EEW system. The critical parameters such as signal window duration and threshold for event declaration are optimized for the detection techniques. An introspection of their performance measures in terms of delay in detection and detection accuracy for optimized parameters is presented. The median delay in detection is best for STA/LTA (0.53[Formula: see text]s) followed by MER (0.55[Formula: see text]s) and MWA (3.23[Formula: see text]s). The comparative analysis shows that MER provides the best results among the candidate techniques with a normalized balanced accuracy of 0.98 followed by STA/LTA (0.97) and MWA (0.82).