Earthquake early warning systems based on low-cost ground motion sensors: A systematic literature review

Abstract

Earthquake early warning system (EEWS) plays an important role in detecting ground shaking during an earthquake and alerting the public and authorities to take appropriate safety measures, reducing possible damages to lives and property. However, the cost of high-end ground motion sensors makes most earthquake-prone countries unable to afford an EEWS. Low-cost Microelectromechanical systems (MEMS)-based ground motion sensors are becoming a promising solution for constructing an affordable yet reliable and robust EEWS. This paper contributes to advancing Earthquake early warning (EEW) research by conducting a literature review investigating different methods and approaches to building a low-cost EEWS using MEMS-based sensors in different territories. The review of 59 articles found that low-cost MEMS-based EEWSs can become a feasible solution for generating reliable and accurate EEW, especially for developing countries and can serve as a support system for high-end EEWS in terms of increasing the density of the sensors. Also, this paper proposes a classification for EEWSs based on the warning type and the EEW algorithm adopted. Further, with the support of the proposed EEWS classification, it summarises the different approaches researchers attempted in developing an EEWS. Following that, this paper discusses the challenges and complexities in implementing and maintaining a low-cost MEMS-based EEWS and proposes future research areas to improve the performance of EEWSs mainly in 1) exploring node-level processing, 2) introducing multi-sensor support capability, and 3) adopting ground motion-based EEW algorithms for generating EEW.

Potential of Advanced Technologies for Environmental Management Systems

“…This not only results in cost savings but also serves to minimize the environmental impact. The utilization of Internet of Things (IoT) devices and the application of big data analytics can facilitate the development of early warning systems aimed at identifying and predicting environmental risks [105,106]. Through the continuous monitoring of sensor data and its integration with historical data, algorithms have the potential to identify abnormalities or deviations that could serve as indicators of potential environmental hazards.…”

Urban Seismic Networks: A Worldwide Review

“…It does not require an extended network, and the alert time is reduced compared to the regional approach, which need not necessarily include the accurate location of the event. For this reason, unlike the regional approach, low-cost sensors can be employed and transmission can even be neglected [146]. In particular, on-site early warning systems are based on the detection of P-wave arrivals and estimation of the intensity of the incoming ground shaking in a few fractions of second, which is done by taking advantage of the difference in velocity between the P and S waves [147][148][149].…”

Seismic Response of a Tall Reinforced Concrete Frame Structure Subjected to both Horizontal and Vertical Strong Motions

“…Another advantage consists in the continuous updating of the seismic scenarios based on the recorded data from recent severe earthquakes from around the world: Japan (Tohoku, 2011), Nepal (2015), Puerto Rico (2020), Croatia (Zagreb, 2020), Haiti (2021), Turkey (Gaziantep, 2023). The results obtained from realistic numerical simulations may serve as entries in data-bases designed to train and calibrate early warning systems (EWS) [9,10]. Their continuous development are of paramount importance taking into account their potential to save lives and prevent economic loses in case of a severe seismic event.…”