Latency and geofence testing of wireless emergency alerts intended for the ShakeAlert® earthquake early warning system for the West Coast of the United States of America

McBride, Sara K.; Sumy, D. F.; Llenos, A. L.; Parker, Grace A.; McGuire, J. J.; Saunders, J. K.; Meier, Men‐Andrin; Schuback, Pascal; Given, Douglas D.; Groot, Robert D.

doi:10.1016/j.ssci.2022.105898

Cited by 18 publications

(6 citation statements)

References 52 publications

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“…The findings proved that facilitation conditions are positively moderated between trustworthiness and ITU5G argument supported by multiple studies 12 , 95 . A past study 96 discussed that information acquisition in the context of 5G technology refers to learning about and comprehending its characteristics, advantages, and potential drawbacks. Users can gain trustworthy information with the support of clear guidelines, regulations, and communication from regulatory organizations, which may favourably impact their decision to use 5G 53 .…”

Section: Discussion and Recommendationsmentioning

confidence: 99%

Effect of social influence, environmental awareness, and safety affordance on actual use of 5G technologies among Chinese students

Shahzad,

Xu,

Khan

et al. 2023

Sci Rep

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Abstract5G technology continues to evolve, and its potential to revolutionize various aspects of society is becoming increasingly evident. However, the successful adoption and utilization of 5G technology depends on various factors, particularly among consumers expected to be early adopters and critical drivers of technological advancements. This study investigates the effect of social influence, environmental awareness, and safety affordance on Chinese university students' actual use of 5G (AU5G) technologies. It also analyzed the mediating role of trustworthiness and intention to use 5G (ITU5G) between them and the moderating role of facilitation conditions between trustworthiness and ITU5G. Data was collected from university students (n = 364) in Beijing and was examined employing the structural equation modelling (SEM) approach. The outcomes confirm that trustworthiness and ITU5G significantly mediate the relationship between social influence, environmental awareness, and safety affordance on AU5G technologies among Chinese students. Further, the supportive facilitation conditions strengthen the relationship between trustworthiness and ITU5G. These findings are backed by UTAUT2 models that support the technology acceptance and adoption among the users. The study outcomes can help policymakers design strategies to address potential barriers and encourage greater uptake of 5G services among university students.

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Section: Discussion and Recommendationsmentioning

confidence: 99%

Effect of social influence, environmental awareness, and safety affordance on actual use of 5G technologies among Chinese students

Shahzad,

Xu,

Khan

et al. 2023

Sci Rep

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“…We calculate a maximum possible warning time for each station as the time between when GRAPES predicts shaking above the threshold and ground motion above that threshold occurs. We include 1 s of processing time in our warning time estimates but do not account for alert delivery times (McBride et al., 2023). We compare GRAPES's performance to the Propagation of Local Undamped Motion (PLUM) algorithm (Kodera et al., 2018), a ground motion‐based EEW algorithm currently in use in Japan (Kodera et al., 2020), and to a hypothetical and unrealistic (Minson et al., 2018) “perfect” algorithm, which exactly predicts shaking at all locations at the instant rupture begins (Figures 4a–4c).…”

Section: Resultsmentioning

confidence: 99%

GRAPES: Earthquake Early Warning by Passing Seismic Vectors Through the Grapevine

Clements,

Cochran,

Baltay

et al. 2024

Geophysical Research Letters

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Estimating an earthquake's magnitude and location may not be necessary to predict shaking in real time; instead, wavefield‐based approaches predict shaking with few assumptions about the seismic source. Here, we introduce GRAph Prediction of Earthquake Shaking (GRAPES), a deep learning model trained to characterize and propagate earthquake shaking across a seismic network. We show that GRAPES’ internal activations, which we call “seismic vectors”, correspond to the arrival of distinct seismic phases. GRAPES builds upon recent deep learning models applied to earthquake early warning by allowing for continuous ground motion prediction with seismic networks of all sizes. While trained on earthquakes recorded in Japan, we show that GRAPES, without modification, outperforms the ShakeAlert earthquake early warning system on the 2019 M7.1 Ridgecrest, CA earthquake.

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“…Instead, PLUM is designed considering a threshold‐based approach to alert performance, where the relative over‐ or underestimation of ground‐motion amplitudes does not matter as much as whether alerts are received before target‐level shaking is experienced. This binary alert quality approach is the way that many users perceive EEW system performance (Santos‐Reyes, 2019), and is reflected in ShakeAlert by the lack of predicted shaking intensity information in the alert message issued to the public (McBride et al., 2023).…”

Section: Discussionmentioning

confidence: 99%

“…An analysis of the moveout distributions for different MMI exceedances determined this velocity to be appropriate for estimating exceedance times for target thresholds of MMI 3.5 and higher and yields conservative warning time estimates for target thresholds of MMI 5.0 and higher (Cochran et al., 2022). While the ShakeAlert Testing Platform simulates real‐time data streams by sending station data to the EEW algorithms in one‐second packets, it does not include data telemetry latencies or additional latencies from alert delivery, both of which can range from <1 s to several seconds or more (McBride et al., 2023; Patel & Allen, 2022; Stubailo et al., 2021). Alert recipients will also take time to process the alert message and take protective actions, which will also vary depending on the recipient.…”

Section: Simulated Real‐time Tests and Cost‐reduction Analysismentioning

confidence: 99%

Incorporating Intensity Distance Attenuation Into PLUM Ground‐Motion‐Based Earthquake Early Warning in the United States: The APPLES Configuration

Saunders,

Cochran,

Bunn

et al. 2024

Earth's Future

Self Cite

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We develop Attenuated ProPagation of Local Earthquake Shaking (APPLES), a new configuration for the United States West Coast version of the Propagation of Local Undamped Motion (PLUM) earthquake early warning (EEW) algorithm that incorporates attenuation into its ground‐motion prediction procedures. Under APPLES, instead of using a fixed radius to forward‐predict observed peak ground shaking to the area surrounding a seismic station, the forward‐predicted intensity at a location depends on the distance from the station using an intensity prediction relationship. We conduct conceptual tests of maximum intensity distribution predictions in APPLES and PLUM using a catalog of ShakeMaps to confirm that the attenuation relationship in APPLES is appropriately modeling shaking distributions for West Coast earthquakes. Then, we run APPLES and PLUM in simulated real‐time tests to determine warning time performance. Finally, we compare real‐time alert behavior during the 2022 M6.4 Ferndale, California, earthquake and other recent events. We find that APPLES presents two potential improvements to PLUM by reducing over‐alerting during smaller magnitude earthquakes and by increasing warning times in some locations during larger earthquakes. APPLES can produce missed and late alerts in locations that experience shaking intensities close to the level used to issue alerts, so preferred alerting strategies with APPLES would use alert thresholds that are lower than the intensities targeted for EEW alerts. We find alerts using APPLES are also similar to those for the source‐based approaches currently used in the ShakeAlert EEW system, which will make APPLES easier to integrate into the system.

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Latency and geofence testing of wireless emergency alerts intended for the ShakeAlert® earthquake early warning system for the West Coast of the United States of America

Cited by 18 publications

References 52 publications

Effect of social influence, environmental awareness, and safety affordance on actual use of 5G technologies among Chinese students

Effect of social influence, environmental awareness, and safety affordance on actual use of 5G technologies among Chinese students

GRAPES: Earthquake Early Warning by Passing Seismic Vectors Through the Grapevine

Incorporating Intensity Distance Attenuation Into PLUM Ground‐Motion‐Based Earthquake Early Warning in the United States: The APPLES Configuration

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