A High-Density Seismic Network for Earthquake Early Warning in Taiwan Based on Low Cost Sensors

Wu, Yih‐Min; Chen, Da Yi; Lin, Tzu-Chiao; Hsieh, Chih Yih; Chin, Tai Lin; Chang, Wei-Ju; Li, Wei Sen; Ker, Shaw Hsung

doi:10.1785/0220130085

Cited by 119 publications

(63 citation statements)

References 31 publications

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“…Similar to Japan, the financial considerations (Horiuchi et al 2009) involved in traditional force-balanced accelerometers are not appropriate for Taiwan. Instead, a seismic network with MEMS accelerators is a better solution for EEW in Taiwan (Wu et al 2013a;Wu and Lin 2014).…”

Section: Low Cost Seismic Networkmentioning

confidence: 99%

“…The miniature devices provide an ideal, cost-saving solution for recording strong ground motion signals. Therefore, MEMS devices have been widely used in developing large-scale, dense seismic networks (Wu et al 2013a).…”

Section: Introductionmentioning

confidence: 99%

“…Currently, 401 stations were installed by first quarter of 2013 ( Fig. 1; Wu et al 2013a). Most of the stations are located in elementary schools where power and Internet connections are provided.…”

Section: Introductionmentioning

confidence: 99%

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Low Cost Seismic Network Practical Applications for Producing Quick Shaking Maps in Taiwan

Hsieh¹,

Wu²,

Chin³

et al. 2014

Terr. Atmos. Ocean. Sci.

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Two major earthquakes of M L greater than 6.0 occurred in Taiwan in the first half of 2013. The vibrant shaking brought landslides, falling rocks and casualties. This paper presents a seismic network developed by National Taiwan University (NTU) with 401 Micro-Electro Mechanical System (MEMS) accelerators. The network recorded high quality strong motion signals from the two events and produced delicate shaking maps within one minute after the earthquake occurrence. The high shaking regions of the intensity map produced by the NTU system suggest damage and casualty locations. Equipped with a dense array of MEMS accelerometers, the NTU system is able to accommodate 10% signals loss from part of the seismic stations and maintain its normal functions for producing shaking maps. The system also has the potential to identify the rupture direction which is one of the key indices used to estimate possible damage. The low cost MEMS accelerator array shows its potential in real-time earthquake shaking map generation and damage avoidance.

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Section: Low Cost Seismic Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Low Cost Seismic Network Practical Applications for Producing Quick Shaking Maps in Taiwan

Hsieh¹,

Wu²,

Chin³

et al. 2014

Terr. Atmos. Ocean. Sci.

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show abstract

“…In addition to detecting anomalous noise data generated by human or accidental factors, anomaly data detection can also be performed by analyzing the semantics implied by outlier, since anomaly data often reflect some evolution and variation of the physical world. As in the field of seismology, anomalous data mining and precursor data observation can be used to detect outliers in earthquake precursor data and provide the basis for earthquake prediction [27]. In the field of Internet security, real-time anomaly data detection and analysis of network packets can be used for intrusion detection [28].…”

Section: Application Of Outlier Detectionmentioning

confidence: 99%

Outlier Detection and Processing Technology and Its Application

Wang¹,

Cui²,

Zhang³

et al. 2016

Proceedings of the 2016 7th International Conference on Mechatronics, Control and Materials (ICMCM 2016)

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Abstract. Faced with the development of information technology and the arrival of the era of big data, data has become the advanced productive forces and strategic resources. However, the existence of outliers often has a negative impact on the storageand analysis of the data, andeven causes disastrous consequences. This paper starts with the definition, concept and classification of outliers, and then compares and analyzes various methods of outlier detection and cleaning technology based on attribute anomaly and the duplicate or similarrecords.Finally, the research and application of outliers are prospected.

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“…in the testing phase, in Europe (Italy, Romania), the USA, Japan, Mexico, Turkey, and Taiwan (e.g., Espinosa-Aranda et al, 1995;Böse et al, 2007;Hoshiba et al, 2008;Alcik et al, 2009;Allen et al, 2009;Hsiao et al, 2009;Satriano et al, 2011;Wu et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Assessing Earthquake Early Warning Using Sparse Networks in Developing Countries: Case Study of the Kyrgyz Republic

et al. 2017

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The first real-time digital strong-motion network in Central Asia has been installed in the Kyrgyz Republic since 2014. Although this network consists of only 19 strong-motion stations, they are located in near-optimal locations for earthquake early warning and rapid response purposes. In fact, it is expected that this network, which utilizes the GFZ-Sentry software, allowing decentralized event assessment calculations, not only will provide useful strong motion data useful for improving future seismic hazard and risk assessment, but will serve as the backbone for regional and on-site earthquake early warning operations. Based on the location of these stations, and travel-time estimates for P-and S-waves, we have determined potential lead times for several major urban areas in Kyrgyzstan (i.e., Bishkek, Osh, and Karakol) and Kazakhstan (Almaty), where we find the implementation of an efficient earthquake early warning system would provide lead times outside the blind zone ranging from several seconds up to several tens of seconds. This was confirmed by the simulation of the possible shaking (and intensity) that would arise considering a series of scenarios based on historical and expected events, and how they affect the major urban centers. Such lead times would allow the instigation of automatic mitigation procedures, while the system as a whole would support prompt and efficient actions to be undertaken over large areas.

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A High-Density Seismic Network for Earthquake Early Warning in Taiwan Based on Low Cost Sensors

Cited by 119 publications

References 31 publications

Low Cost Seismic Network Practical Applications for Producing Quick Shaking Maps in Taiwan

Low Cost Seismic Network Practical Applications for Producing Quick Shaking Maps in Taiwan

Outlier Detection and Processing Technology and Its Application

Assessing Earthquake Early Warning Using Sparse Networks in Developing Countries: Case Study of the Kyrgyz Republic

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