Development of Qube: A Low-Cost Internet of Things Device for On-Site and Regional Earthquake Warning

Author(s):  
Vivien He

Abstract Earthquakes are a major global risk. The current earthquake early warning systems based on public seismic stations face challenges such as high cost, low density, high latency, no alert zone, and difficulty in predicting ground motions at the location of the user. This article pursues an alternative consumer-based approach. An Internet of Things consumer device, called a “Qube,” was built for a cost below $100 and is about the size of a Rubik’s cube. The Qube successfully detected earthquakes and issued earthquake warnings through sounding the onboard alarm for on-site warning and sending text messages to local subscribers for regional warning. The Qube is highly sensitive. During nine months of testing from September 2020 to May 2021, it detected all earthquakes over M 3.0 magnitude around Los Angeles, as well as nearby earthquakes down to M 2.3. The Qube uses a geophone for ground-motion velocity sensing and captures earthquake waveforms consistent with a nearby broadband seismometer in the Southern California Seismic Network. By analyzing data of the earthquakes detected by the Qube, an empirical logarithmic formula that is used to estimate local earthquake magnitude based on detected ground-motion amplitude in digital counts was developed. Although the Qube’s response in digital counts to ground-motion velocity in μm/s has not been determined, the empirical formula between Qube’s output and local earthquake magnitude suggests the Qube’s consistency in ground-motion measurement. The Qube has Wi-Fi connectivity and is controllable via a smartphone or computer. The combination of low cost, high sensitivity, and integrated alarm function of the Qube is intended to enable a consumer-based approach with the potential for mass adoption and use in dense networks, creating new opportunities for seismic network, earthquake warning, and educational applications.

1993 ◽  
Vol 217 (3-4) ◽  
pp. 243-253 ◽  
Author(s):  
P. Hatzidimitriou ◽  
C. Papazachos ◽  
A. Kiratzi ◽  
N. Theodulidis

2014 ◽  
Vol 8 (4) ◽  
pp. 1921-1930 ◽  
Author(s):  
H. E. Abdel Hafiez ◽  
I. El-Hussain ◽  
A. E. Khalil ◽  
A. Deif

2017 ◽  
Vol 107 (2) ◽  
pp. 521-531 ◽  
Author(s):  
Finnigan Illsley‐Kemp ◽  
Derek Keir ◽  
Jonathan M. Bull ◽  
Atalay Ayele ◽  
James O. S. Hammond ◽  
...  

2021 ◽  
Vol 906 (1) ◽  
pp. 012107
Author(s):  
Jakub Nosek ◽  
Pavel Václavovic

Abstract An accurate estimation of an earthquake magnitude plays an important role in targeting emergency services towards affected areas. Along with the traditional methods using seismometers, site displacements caused by an earthquake can be monitored by the Global Navigation Satellite Systems (GNSS). GNSS can be used either in real-time for early warning systems or in offline mode for precise monitoring of ground motion. The Precise Point Positioning (PPP) offers an optimal method for such purposes, because data from only one receiver are considered and thus not affected by other potentially not stable stations. Precise external products and empirical models have to be applied, and the initial convergence can be reduced or eliminated by the backward smoothing strategy or integer ambiguity resolution. The product for the magnitude estimation is a peak ground displacement (PGD). PGDs observed at many GNSS stations can be utilized for a robust estimate of an earthquake magnitude. We tested the accuracy of estimated magnitude scaling when using displacement waveforms collected from six selected earthquakes between the years 2016 and 2020 with magnitudes in a range of 7.5–8.2 Moment magnitude MW. We processed GNSS 1Hz and 5Hz data from 182 stations by the PPP method implemented in the G-Nut/Geb software. The precise satellites orbits and clocks corrections were provided by the Center for Orbit Determination in Europe (CODE). PGDs derived on individual GNSS sites formed the basis for ground motion parameters estimation. We processed the GNSS observations by the combination of the Kalman filter (FLT) and the backward smoother (SMT), which significantly enhanced the kinematic solution. The estimated magnitudes of all the included earthquakes were compared to the reference values released by the U. S. Geological Survey (USGS). The moment magnitude based on SMT was improved by 20% compared to the FLT-only solution. An average difference from the comparison was 0.07 MW and 0.09 MW for SMT and FLT solutions, respectively. The corresponding standard deviations were 0.18 MW and 0.22 MW for SMT and FLT solutions, which shows a good consistency of our and the reference estimates.


1975 ◽  
Vol 65 (2) ◽  
pp. 307-321
Author(s):  
M. D. Trifunac ◽  
A. G. Brady

abstract A quantitative measure of the Modified Mercalli Intensity Scale for earthquakes in the western United States has been developed by correlating the peak seismoscope relative displacement response, Sd, with the reported site intensity, IMM. This correlation can be approximated by S ̄ d ( cm ) ≈ 1 49.2 10 0.288 I MM for IMM ≦ VIII and is characterized by one standard deviation of about 0.7 S̄d. The data used in this study do not indicate an obvious type of dependence of Sd on local site conditions. A method for computing the analog of the local earthquake magnitude, Mseismoscope, has been presented for possible use in strong-motion seismology and for scaling earthquakes by close-in measuremients, when other seismological instruments may go off scale.


2018 ◽  
Vol 45 (15) ◽  
pp. 7496-7503 ◽  
Author(s):  
Jyh Cherng Jan ◽  
Hsin-Hua Huang ◽  
Yih-Min Wu ◽  
Chien-Chih Chen ◽  
Cheng-Horng Lin

2019 ◽  
Author(s):  
Megan Partch ◽  
Cass Dykeman

Mental health treatment providers seek high-impact and low-cost means of engaging clients in care. As such, text messaging is becoming more frequently utilized as a means of communication between provider and client. Research demonstrates that text message interventions increase treatment session attendance, decrease symptomology, and improve overall functioning. However, research is lacking related to the linguistic make up of provider communications. Text messages were collected from previously published articles related to the treatment of mental health disorders. A corpus of 39 mental health treatment text message interventions was composed totaling 286 words. Using Linguistic Inquiry and Word Count (LIWC) software, messages were analyzed for prevalence of terminology thought to enhance client engagement. Clout, demonstrating the writer’s confidence and expertise, and positive Emotional Tone were found to be at a high level within the corpus. Results demonstrated statistical significance for five linguistic variables. When compared with national blog norms derived from Twitter, Clout, Emotional Tone, and use of Biological terminology were found to be at higher rates than expected. Authenticity and Informal terminology were found at significantly lesser rates.


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