GNSS for Quasi-Real-Time Earthquake Source Determination in Eastern Tibet: A Prototype System toward Early Warning Applications

2021 ◽  
Author(s):  
Xinjian Shan ◽  
Yanchuan Li ◽  
Zhenjie Wang ◽  
Hao Yin ◽  
Xiaodong Liu ◽  
...  
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Crustal Deformation ◽  
Processing System ◽  
Earthquake Source ◽  
High Rate ◽  
Prototype System ◽  
The Tibetan Plateau ◽  
Source Determination ◽  
Eastern Tibet

Abstract Active crustal deformation of the Tibetan plateau results in destructive continental earthquakes and is therefore the focus of intense research interest. Increases in the numbers of Global Navigation Satellite System (GNSS) networks and stations deployed in Tibet are allowing for the characterization of crustal deformation during different phases of the earthquake cycle. Here, we present the status of a “seismic + high-rate GNSS” network deployed in eastern Tibet, including its data streams and data processing system, with the goal of supporting quasi-real-time earthquake source determination. Furthermore, we use this network to test a prototype earthquake early warning (EEW) system using data from the 2008 Mw 7.9 Wenchuan earthquake, the 2011 Mw 9.0 Tohoku earthquake, and 2200 synthetic earthquakes with moment magnitudes ranging from 6.5 to 7.5 on the southern Longmen Shan fault and Anninghe fault. The results show that our current methodology could respond to moderate-to-large earthquakes (magnitude 7+) within tens of seconds after the origin time, with implications for EEW applications in China.

Rapid Earthquake Source Description Using Variometric-Derived GPS Displacements toward Application to the 2019 Mw 7.1 Ridgecrest Earthquake

2021 ◽  
Author(s):  
Jianfei Zang ◽  
Caijun Xu ◽  
Yangmao Wen ◽  
Xiaohang Wang ◽  
Kefeng He
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Moment Tensor ◽  
Continuous Phase ◽  
Earthquake Source ◽  
High Rate ◽  
Convergence Time ◽  
Centroid Moment Tensor ◽  
Origin Time ◽  
Broadcast Ephemeris

Abstract Using near-field high-rate Global Positioning System (GPS) displacements to invert for earthquake fault slips in real time has the potential to improve the accuracy of earthquake early warning or tsunami early warning. For such applications, real-time retrieval of high-accuracy GPS displacements is essential. Here, we report on rapid modeling of the 2019 Mw 7.1 Ridgecrest earthquake with real-time GPS displacements derived from a variometric approach with readily available broadcast ephemeris. This method calculates station variations in real time by differencing continuous phase observations and does not rely on precise orbit and clock information. The phase ambiguity is also removed, and thus the method does not suffer from a relatively long convergence time. To improve the accuracy of variometric displacements, we use a local spatial filter to decrease the influence of residual errors that cannot be removed completely by the time difference. We invert for the centroid moment tensor, static fault slips, and fault rupture process from the derived displacements. Our results show that all inverted models are available within about 65 s after the origin time of the earthquake and are comparable with models inverted by real-time precise point positioning displacements. This study highlights the great value of variometric displacements for the rapid earthquake source description with only broadcast ephemeris.

scholarly journals Real-time high-rate co-seismic displacement from ambiguity-fixed precise point positioning: Application to earthquake early warning

2013 ◽  
Vol 40 (2) ◽  
pp. 295-300 ◽  
Author(s):  
Xingxing Li ◽  
Maorong Ge ◽  
Xiaohong Zhang ◽  
Yong Zhang ◽  
Bofeng Guo ◽  
...  
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Precise Point Positioning ◽  
Earthquake Early Warning ◽  
High Rate ◽  
Seismic Displacement ◽  
Point Positioning

GPS for real-time earthquake source determination and tsunami warning systems

2009 ◽  
Vol 83 (3-4) ◽  
pp. 335-343 ◽  
Author(s):  
Geoffrey Blewitt ◽  
William C. Hammond ◽  
Corné Kreemer ◽  
Hans-Peter Plag ◽  
Seth Stein ◽  
...  
Keyword(s):  
Real Time ◽  
Earthquake Source ◽  
Tsunami Warning ◽  
Warning Systems ◽  
Source Determination

scholarly journals Predicting approximate seismic responses in multistory buildings from real-time earthquake source information, for earthquake early warning applications

2021 ◽  
Author(s):  
Gemma Cremen ◽  
Omar Velazquez ◽  
Benazir Orihuela ◽  
Carmine Galasso
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Source Parameters ◽  
Earthquake Source ◽  
Earthquake Early Warning ◽  
Multistory Buildings ◽  
Building Model ◽  
Beam Combination ◽  
Earthquake Source Parameters ◽  
Wide Range

AbstractRegional earthquake early warning (EEW) alerts and related risk-mitigation actions are often triggered when the expected value of a ground-motion intensity measure (IM), computed from real-time magnitude and source location estimates, exceeds a predefined critical IM threshold. However, the shaking experienced in mid- to high-rise buildings may be significantly different from that on the ground, which could lead to sub-optimal decision-making (i.e., increased occurrences of false and missed EEW alarms) with the aforementioned strategy. This study facilitates an important advancement in EEW decision-support, by developing empirical models that directly relate earthquake source parameters to resulting approximate responses in multistory buildings. The proposed models can leverage real-time earthquake information provided by a regional EEW system, to provide rapid predictions of structure-specific engineering demand parameters that can be used to more accurately determine whether or not an alert is triggered. We use a simplified continuum building model consisting of a flexural/shear beam combination and vary its parameters to capture a wide range of deformation modes in different building types. We analyse the approximate responses for the building model variations, using Italian accelerometric data and corresponding source parameter information from 54 earthquakes. The resulting empirical prediction equations are incorporated in a real-time Bayesian framework that can be used for building-specific EEW applications, such as (1) early warning of floor-shaking sensed by occupants; and (2) elevator control. Finally, we demonstrate the improvement in EEW alert accuracy that can be achieved using the proposed models.

scholarly journals Resolving dynamic ground motions with high-rate GNSS and implications for data fusion in broadband seismology and Earthquake Early Warning

2020 ◽  
Author(s):  
Roland Hohensinn ◽  
Nikolaj Dahmen ◽  
John Clinton ◽  
Alain Geiger ◽  
Markus Rothacher
Keyword(s):  
Data Fusion ◽  
Real Time ◽  
Early Warning ◽  
Ground Motions ◽  
Real Data ◽  
Satellite System ◽  
Earthquake Early Warning ◽  
High Rate ◽  
Velocity Waveform ◽  
Global Navigation Satellite

<p>In this paper we highlight the potential of geodetic high-precision and high-rate GNSS <em>(Global Navigation Satellite System)</em> sampling (1 to 100 Hz) for resolving seismic ground motions, of both the near and the far field of an earthquake. The analysis of the budget and characteristics of the error of high-rate GNSS displacement time series yields results, discussion, and conclusions on the sensitivity and waveform resolvability as well as on the derivation of a minimum detectable displacement (in the statistical sense).</p><p>Based on these analyses, we show how GNSS can contribute to optimal broadband displacement and velocity waveform products by means of data fusion by combining measurements taken from co-located sensors – e.g. accelerometers or gyroscopes – in real-time, near real-time and postprocessing mode. Concerning the inclusion of GNSS for such an analysis, we also briefly explore the ability of GNSS to record signals from different earthquake magnitudes and epicentral distances. We show that high-rate GNSS is sensitive to displacements down to the level of a few millimeters, and even below – an example also comes from the detection of very small vibrations from 100 Hz GNSS data.</p><p>We analyze measurements of synthetized signals obtained from experiments with a shake table, as well as from real data from strong earthquakes, namely the 6.5 M<sub>w</sub> event of 2016 near the city of Norcia (Italy) and the 7.0 M<sub>w</sub> Kumamoto earthquake of 2016 (Japan). Based on these data and our main findings, we finally discuss the role of GNSS in Earthquake Early Warning in terms of a fast hypocenter localization and reliable magnitude estimation.</p>

scholarly journals Vital Signs Prediction and Early Warning Score Calculation Based on Continuous Monitoring of Hospitalised Patients Using Wearable Technology

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6593
Author(s):  
Ahmed Youssef Ali Amer ◽  
Femke Wouters ◽  
Julie Vranken ◽  
Dianne de Korte-de Boer ◽  
Valérie Smit-Fun ◽  
...  
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Real Time ◽  
Early Warning ◽  
Continuous Monitoring ◽  
Time Series Prediction ◽  
Vital Signs ◽  
Wearable Technology ◽  
High Rate ◽  
Hospitalised Patients

In this prospective, interventional, international study, we investigate continuous monitoring of hospitalised patients’ vital signs using wearable technology as a basis for real-time early warning scores (EWS) estimation and vital signs time-series prediction. The collected continuous monitored vital signs are heart rate, blood pressure, respiration rate, and oxygen saturation of a heterogeneous patient population hospitalised in cardiology, postsurgical, and dialysis wards. Two aspects are elaborated in this study. The first is the high-rate (every minute) estimation of the statistical values (e.g., minimum and mean) of the vital signs components of the EWS for one-minute segments in contrast with the conventional routine of 2 to 3 times per day. The second aspect explores the use of a hybrid machine learning algorithm of kNN-LS-SVM for predicting future values of monitored vital signs. It is demonstrated that a real-time implementation of EWS in clinical practice is possible. Furthermore, we showed a promising prediction performance of vital signs compared to the most recent state of the art of a boosted approach of LSTM. The reported mean absolute percentage errors of predicting one-hour averaged heart rate are 4.1, 4.5, and 5% for the upcoming one, two, and three hours respectively for cardiology patients. The obtained results in this study show the potential of using wearable technology to continuously monitor the vital signs of hospitalised patients as the real-time estimation of EWS in addition to a reliable prediction of the future values of these vital signs is presented. Ultimately, both approaches of high-rate EWS computation and vital signs time-series prediction is promising to provide efficient cost-utility, ease of mobility and portability, streaming analytics, and early warning for vital signs deterioration.

AUTOMATIC WATER LEVEL MONITORING WITH IOT AND LPWAN

2019 ◽  
pp. 95-103
Author(s):  
Krum Videnov ◽  
Vanya Stoykova
Keyword(s):  
Water Level ◽  
Real Time ◽  
Early Warning ◽  
Water Sources ◽  
Water Levels ◽  
Water Level Fluctuations ◽  
Level Monitoring ◽  
Water Level Monitoring

Monitoring water levels of lakes, streams, rivers and other water basins is of essential importance and is a popular measurement for a number of different industries and organisations. Remote water level monitoring helps to provide an early warning feature by sending advance alerts when the water level is increased (reaches a certain threshold). The purpose of this report is to present an affordable solution for measuring water levels in water sources using IoT and LPWAN. The assembled system enables recording of water level fluctuations in real time and storing the collected data on a remote database through LoRaWAN for further processing and analysis.

A real-time processing system for determination of metabolic rates of a suited astronaut

1969 ◽  
Author(s):  
D. BILLINGSLEY ◽  
G. HUMBERT ◽  
R. KELLY
Keyword(s):  
Real Time ◽  
Processing System ◽  
Metabolic Rates ◽  
Real Time Processing ◽  
Time Processing

A Multi-parameter Joint Warning Mechanism for Physical Condition Monitoring System in Physical Education

2020 ◽  
Vol 14 (1) ◽  
pp. 113-119
Author(s):  
Zhang Su
Keyword(s):  
Physical Education ◽  
False Alarm ◽  
Real Time ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Early Warning ◽  
Physical Condition ◽  
School Students ◽  
Early Warning Mechanism ◽  
Number Of Segments

Background: In recent years, sudden deaths of primary and secondary school students caused by sports activities have drawn great attention in education and medical circles. It is necessary for schools to monitor the physical condition of the students in order to reasonably set the duration of their physical activity. At present, the physical condition monitoring instruments used in various hospitals are expensive, bulky, and difficult to operate, and the detection process is complicated. Therefore, existing approaches cannot meet the needs of physical education teachers on campus for detecting the physical condition of students. Methods: This study designs a portable human-physiological-state monitoring and analysis system. Real-time communication between a wearable measurement device and a monitoring device can be ensured by real-time detection of the environment and power control of the transmitted signal. Results: From a theoretical point of view, the larger the number of segments M, the more significantly the reduction of false alarm probability. The simulation results also show this fact. Compared with the conventional early warning mechanism, the probability of a false alarm for the proposed system is lower, and the greater the number of segments, the faster its reaction speed. Conclusion: The portable monitoring system of student physical condition for use in physical education of primary and middle school students proposed in this paper ensures real-time monitoring of the members within the system in an open environment, and further proposes an early warning mechanism for combining multiple vital sign parameters. In addition, the proposed system functions faster; the average early warning time required is only one-quarter of that of the conventional system.

Safety Monitoring and Warning System for Subway Construction Workers using Wearable Technology

2019 ◽  
Vol 13 ◽  
Author(s):  
Jun-hua Chen ◽  
Da-hu Wang ◽  
Cun-yuan Sun
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Early Warning ◽  
Warning System ◽  
Safety Monitoring ◽  
Wearable Technology ◽  
Construction Workers ◽  
Great Success ◽  
Subway Construction ◽  
Monitoring And Early Warning

Objective: This study focused on the application of wearable technology in the safety monitoring and early warning for subway construction workers. Methods: With the help of real-time video surveillance and RFID positioning which was applied in the construction has realized the real-time monitoring and early warning of on-site construction to a certain extent, but there are still some problems. Real-time video surveillance technology relies on monitoring equipment, while the location of the equipment is fixed, so it is difficult to meet the full coverage of the construction site. However, wearable technologies can solve this problem, they have outstanding performance in collecting workers’ information, especially physiological state data and positioning data. Meanwhile, wearable technology has no impact on work and is not subject to the inference of dynamic environment. Results and conclusion: The first time the system applied to subway construction was a great success. During the construction of the station, the number of occurrences of safety warnings was 43 times, but the number of occurrences of safety accidents was 0, which showed that the safety monitoring and early warning system played a significant role and worked out perfectly.

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