Real-Time Evolutionary Earthquake Location for Seismic Early Warning

2008 ◽  
Vol 98 (3) ◽  
pp. 1482-1494 ◽  
Author(s):  
C. Satriano ◽  
A. Lomax ◽  
A. Zollo
2012 ◽  
Vol 17 (2) ◽  
pp. 485-505 ◽  
Author(s):  
M. Picozzi ◽  
D. Bindi ◽  
M. Pittore ◽  
K. Kieling ◽  
S. Parolai

1998 ◽  
Vol 88 (5) ◽  
pp. 1254-1259
Author(s):  
Yih-Min Wu ◽  
Tzay-Chyn Shin ◽  
Yi-Ben Tsai

Abstract This article reports efforts toward using real-time earthquake monitoring by the Taiwan Central Weather Bureau to meet the needs of seismic early warning. Twenty-three sets of strong-motion data from moderate earthquakes (ML > 5.0) in the Taiwan area are used to demonstrate the feasibility of this goal. For earthquakes larger than ML 5, epicenters can be reliably determined in about 15 sec after the arrival of the P wave at the nearest station. The earthquake magnitude ML cannot be determined in the same time frame due to incomplete recording of shear waves at some stations. However, the magnitude based on the first 10 sec of signal (ML10) can be related to ML as follows: M L = 1.28 * M L 10 − 0.85 ± 0.13 . Our results show that the real-time strong-motion system routinely used by the Central Weather Bureau can be used to determine epicenters and magnitudes in about 30 sec after occurrence of earthquakes in Taiwan. Such information hopefully can be used to reduce damage to society.


Author(s):  
Claudio Satriano ◽  
Anthony Lomax ◽  
Aldo Zollo

Author(s):  
Krum Videnov ◽  
Vanya Stoykova

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.


2020 ◽  
Vol 14 (1) ◽  
pp. 113-119
Author(s):  
Zhang Su

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.


Author(s):  
Jun-hua Chen ◽  
Da-hu Wang ◽  
Cun-yuan Sun

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.


2020 ◽  
pp. 1-11
Author(s):  
Qiaoying Ding

The financial market is changing rapidly. Since joining the WTO, our country’s financial companies have faced pressure from dual competition at domestic and abroad. The complex internal and external environment has forced financial enterprise managers to improve risk prevention awareness, early warning and monitoring, so as to responding to emergencies and challenges in the financial market. However, traditional forecasting and analysis methods have problems such as large workload, low efficiency, and low accuracy. Therefore, this article applies intelligent computing to the forecast of financial markets, using related concepts of fuzzy theory and Internet intelligent technology, and proposes to establish a model system for financial enterprise risk early warning management and intelligent real-time monitoring based on fuzzy theory. This article first collected a large amount of data through the literature investigation method, and made a systematic and complete introduction to the related theoretical concepts of fuzzy theory and financial risk early-warning management, has laid a sufficient theoretical foundation for the subsequent exploration of the application of fuzzy theory in financial enterprise risk early warning management and intelligent real-time systems; Then a fuzzy comprehensive evaluation method that combines the analytic hierarchy process and fuzzy evaluation method is proposed, taking a listed company mainly engaged in automobile sales in our province as a case, the company’s financial risk management and modeling experiment of the intelligent real-time system; Finally quoted specific cases again, used the fuzzy comprehensive evaluation method to carry out risk warning and evaluation on the PPP projects of private enterprises in our province, and concluded that the project risk score is between 20-60, which is meet the severe-medium range in the risk level. Research shows that the use of fuzzy theory and modern network technology can make more accurate warnings and assessments of potential and apparent risks of financial enterprises, greatly improving the safety of financial enterprise management and reducing the losses caused by various risks.


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