BC Earthquake Early Warning System, a Program for Seismic Structural Health Monitoring of Infrastructure

Ventura, Carlos E.; Kaya, Yavuz; Taale, Alireza

doi:10.1007/978-3-319-93157-9_4

Cited by 2 publications

(1 citation statement)

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“…This method only requires the P-wave first motion information from a single seismic station; therefore, the lead time is reduced more than that of network-based EEW. In addition, on-site EEW can be used for buildings (Ventura et al, 2019), structures (Bindi et al, 2016), schools, and specific areas (Wu and Mittal, 2021) because the system alone operates without a network. However, the on-site EEW can produce false and missed alarms due to its lower accuracy compared to the network-based EEW, making it difficult to use for public service in smart cities.…”

Section: Introductionmentioning

confidence: 99%

Stable operation process of earthquake early warning system based on machine learning: trial test and management perspective

et al. 2023

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Earthquake Early Warning (EEW) is an alert system, based on seismic wave propagation theory, to reduce human casualties. EEW systems mainly utilize technologies through both network-based and on-site methods. The network-based method estimates the hypocenter and magnitude of an earthquake using data from multiple seismic stations, while the on-site method predicts the intensity measures from a single seismic station. Therefore, the on-site method reduces the lead time compared to the network-based method but is less accurate. To increase the accuracy of on-site EEW, our system was designed with a hybrid method, which included machine learning algorithms. At this time, machine learning was used to increase the accuracy of the initial P-wave identification rate. Additionally, a new approach using a nearby seismic station, called the 1+ α method, was proposed to reduce false alarms. In this study, an on-site EEW trial operation was performed to evaluate its performance. The warning cases for small and large events were reviewed and the possibility of stable alert decisions was confirmed.

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Section: Introductionmentioning

confidence: 99%