# Proposal for a System Model for Offline Seismic Event Detection in Colombia
## 3 Earthquake Detection Methodologies
### Traditional Approaches  
Detection algorithms for earthquake detection assume that seismic signals correspond to ground vibrations isolated from human activity. Only stationary background noise is registered prior to earthquake waves' arrival. To automate the process of identifying the arrival of earthquake waves, specialized detection algorithms are required. These algorithms deal with the task of effectively discriminating background noise from seismic events, to avoid the recording of unnecessary data or the loss of actual seismic signals. Then, detection algorithms require having a high rate of positive event identification, which is easily achieved when strong motions occur (e.g., triggers such as signal's threshold can discriminate noise from strong seismic signals). However, if a seismic event is detected far from the causative fault, a decrease in the signal's amplitude can be expected, making it harder for the algorithm to perform a positive event detection. The simplest approach for an earthquake detection system is a front detection system, which consists of the direct monitoring of a given seismic source. Monitoring the signal's amplitude allows a central managing system to perform pre-defined tasks such as shutting down the power on certain areas or generating alerts of populated areas far enough from the strong ground motion epicenter. Mexico's earthquake monitoring system (SASMEX) implements front detection for this purpose. The front detection approach requires the analysis of most of the seismic signal to validate the trigger, dismissing valuable time that can be used to alert a wider area in case of a strong ground motion event. To deal with this, further approaches attempt to wider the alert time window by analyzing a shorter segment of the seismic signal, requiring more elaborated metrics that can be positively correlated to a significant earthquake event. Some of those metrics include the average noise level, predominant signal period,or cumulative energy [22]. However, these algorithms have a high rate of false alarms when dealing with weak-motion earthquake events [23]. Detection triggers are also specialized to work with frequency-domain data. In this case, signal energy metrics are used as thresholds (e.g., average power). Transform methods such as Fourier or Walsh and signal filtering have been used to provide faster and more reliable detection algorithms [5]. Time-frequency domain techniques such as the wavelet transform have been used to track the initiation of ground motion [24; 25]. A technique found more reliable and widely used is based on the short-time average through the long-time average ratio (STA/LTA). The technique is based on the fact that when seismic events occur, the current signal average (STA) is different from the long-term signal average (LTA) where no events occurred [5; 26]. Figure 1 shows the implementation of the STA/LTA algorithm over a strong-motion record. The seismic record (top figure) shows the arrival of P-waves in the interval 5-10 s. P-waves (P for primary) travel across the earth's mantle in tension-compression mode. Rocks have their highest stiffness (force to deformation ratio) for compression forces, and thus, compression waves can travel the fastest across the earth's mantle, arriving at the surface prior to secondary waves. After 10 s, the seismogram on the top figure shows the strongest acceleration recorded by the seismic station for the event. Secondary and surface waves arrive at the seismic station seconds later than P-waves. Cities with poor seismic resilient infrastructure usually take the highest toll on human and economic losses when they experiment strong ground accelerations. Figure 1 (middle) shows the STA and LTA parameters. It can be seen that the short-time average is useful to indicate the arrival of the seismic event as it suddenly arises from a very low value (assumed to be noise). The long-time average is less sensitive to the arrival of the seismic signal but keeps track of the signal's duration.