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Rapid earthquake detection statistics for 116 earthquakes between 25 September 2010 and 1 April 2011. (a) Time between estimated earthquake origin to initial earthquake detection. (b) Latency from host signal detection to trigger registry on the QCN server. Histograms comparing QCN rapid earthquake characterization and GNS catalog of: (c) magnitude; (d) epicentral location; (e) depth; and (f) origin time (s). Histograms are shown for the first iteration; lines indicate median values for each iteration. The magnitudes are within 0.5 and 1.0 magnitude units for 63% and 90% of all earthquakes, respectively.
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We test the feasibility of rapidly detecting and characterizing earthquakes with the Quake-Catcher Network (QCN) that connects low-cost microelectromechanical systems accelerometers to a network of volunteer-owned, Internet-connected computers. Following the 3 September 2010 M 7.2 Darfield, New Zealand, earthquake we installed over 180 QCN sensors...
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... 25 September 2011 and 1 April 2011 the QCN sensors detected 116 earthquakes ranging in size from M 3.6 to M 6.3 ( Figs. 1 and 5). The minimum and median detection times were 3.1 and 9.8 s after the estimated earthquake origin time, respectively (Fig. 5a). This time includes: (1) source-to- sensor propagation (variable), (2) trigger detection (< 1 s), (3) transfer of trigger information to the QCN server (2-5 s), (4) trigger association and event declaration (requires at least five associated triggers, variable), (5) event detection (< 0:1 s), earthquake location (< 0:02 s), magnitude ...
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... compare the origin time, hypocenter, and magnitude for the QCN detected events to the GeoNet catalog (Fig. 5). On average, we find that the median error in earthquake lo- cation is ∼7 km, the QCN earthquake origin times are biased 1.5 s early, and the magnitude estimates are ∼0:5 magnitude units too high. These differences can be attributed primarily to different station distributions, velocity models, and attenu- ation relationships. Because ...
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... limited distribution of available hosts, QCN sensors are clustered in a small region (10 × 10 km 2 ) with the majority of the earthquakes occur- ring outside of the network (Fig. 1). This tends to increase the location error, biasing earthquake locations farther from the network, and leading to overestimation of magnitude and earlier origin times (Fig. 5). However, given these limita- tions, the QCN rapid earthquake detections compare favor- ably to the GNS Science ...
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Citations
... Chen et al., 2017) or serve as a pedometer to measure the number of steps taken on a jog (Bassett and John, 2010). Other fields of application include geology (Lawrence et al., 2014), biology (Shepard et al., 2008) and machinery health monitoring (Ron and Renard, 2008). ...
Clinical research seeks a voice monitoring device for everyday situations. This thesis investigates the extraction of vocal tract information (VTI) from a portable, lightweight, and wireless voice accelerometer (ACC). An experiment recorded participants' speech using two ACCs placed on the neck and cheek, comparing them to an acoustic microphone. The analysis focused on formant frequencies (FFs), inter-annotator agreement (IAA) for voice onset time (VOT), resistance to environmental noise, and accuracy of transcriptions using automatic speech recognition (ASR). FF extraction yielded unreliable and non-canonical vowel distributions. IAA showed agreement in voice onset between ACC and acoustic signal, but less for VOT start time and duration. Both placements resisted noise up to 85 dBA. However, ACC signals had a high Word error rate (WER), indicating poor recognition. These findings suggest limited VTI extraction from ACC signals, requiring further improvements before reliable VTI recording devices can be developed.
... P-Alert uses accelerometers of microelectromechanical systems (MEMS). MEMS accelerometers have been tested and applied in detecting vibrations of infrastructure, buildings, and the ground [29][30][31][32][33][34][35]. They are also installed in smartphones. ...
For measuring the structural health of buildings, high-performance vibration detection devices are used in a structural health monitoring (SHM) system, which consists of a sensor and a data logger. Those devices are seismographs or devices with high-performance sensors which are expensive. Recently, smartphones are being used as seismographs to accumulate big data of earthquake wave detection because they have accelerometers of microelectromechanical systems. Since a smartphone has the functions of a detection sensor and a data logger, a low-cost SHM system can be developed by using a low-cost smartphone. In this paper, smartphones were used to confirm the possibility of the development of a low-cost SHM system. To evaluate the vibration detection performance from small displacement and large displacement, smartphones were installed in a specimen of a large shaking table test. The specimen is a scale model of a two-story non-reinforced masonry-filled reinforce concrete (RC) frame building. The natural period and interstory drift ratio were used as the evaluation criteria. The natural period estimated by the smartphone data agreed with that found by the piezoelectric accelerometer data. For estimating the building deformation, which is related to building stability, the measurement performance for large deformation using smartphones was evaluated. The smartphones have 90% or higher accuracies for the estimation of the maximum acceleration and displacement.
... Many researchers have conducted studies on strong-motion networks, such as methods for the optimal layout of seismic measurement networks [6][7][8][9], and methods for the optimal layout of networks oriented toward early earthquake warning [10]. In recent years, related studies have also shown that densely distributed low-cost sensors have great potential in the field of earthquake engineering, including early earthquake warning [11,12] and rapid detection and characterization of earthquakes [13], quick shaking maps [14,15], and rapid post-earthquake disaster assessment [16][17][18]. However, research on methods to quantitatively evaluate the influence of strong-motion sensor quality and spatial density on seismic damage assessments is still limited. ...
A quantitative evaluation of the influence of sensor quality and spatial density on the results of rapid regional seismic damage evaluations of buildings can provide an important reference for the deployment of a strong-motion network. However, the influence of sensor quality and spatial density on seismic damage assessment is still unclear. Therefore, a cost-benefit analysis framework of sensor quality and spatial density for rapid regional post-event seismic damage assessment is proposed. In this framework, a simulation method for sensor-recorded ground motions and an interpolation-based ground motion field refinement method are used to consider the influence of the quality and density of the sensor network. The accuracies of seismic damage assessments with different sensor layout schemes were compared using the time-history analysis-based regional seismic damage assessment method, through which the influence of sensor quality and spatial density on the seismic damage assessment can be quantitatively evaluated. Finally, the Zeytinburnu district of Istanbul was selected as an example for illustrating the proposed framework. The main conclusions are as follows: (1) the spatial density of the sensors used is more significant for improving the accuracy of a seismic damage assessment than the quality of the sensors used; (2) the influence of population density can be considered using the proposed framework; and (3) the proposed framework can quantitatively consider the influence of sensor quality and spatial density on the rapid regional seismic damage assessment of buildings, which provides an important reference for the deployment of a strong-motion network for a given budget.
... The instrumentation of the school buildings comprises both classical accelerographs, i.e. ΕΤΝΑ2 (Kinemetrics Inc.) and low-cost triaxial digital accelerometers (Micro-Electro-Mechanical Systems -MEMS) specially designed and implemented in the framework of the project by the Electronics Laboratory of the Department of Physics in AUTH (Lawrence et al. 2014, Nof,Ran et al. 2019, Hu et al. 2021, Konstantakos et al. 2021). ...
Civil protection against earthquakes and other natural hazards is a subject of first priority, especially in Greece. We briefly describe herein the main components of an innovative system for earthquake early warning and real-time risk assessment of school buildings against earthquakes, which has an open architecture to be directly extended for other critical infrastructures and natural disasters. This work is implemented in the framework of SAFESCHOOLS project, (https: www.safeschools.gr/), funded by the General Secretary of Research in Greece. The system combines data from the national broadband strong and weak motion network and on-site classical and new-designed accelerometric sensors installed at selected school buildings, supported by appropriate software, to provide: (a) early detection of the incoming earthquake in terms of magnitude and location (early warning), (b) automatic estimation of the seismic motion characteristics in target sites, (c) real time assessment of expected damage in school buildings, and (d) warning send immediately to selected end-users for the incoming event and the intensity of the expected damage. These estimations provide a timeline of few seconds in order to take critical safety measures for the humans (pupils, employees) and the infrastructure affected. At the same time, the system allows health monitoring of the school building structures to check their safety margin and improve their vulnerability model. This innovative system is already installed and operable, at selected schools, in the city of Thessaloniki.
... Several dense low-cost MEMS networks have been recently tested for the monitoring of strong earthquakes and ground shaking, with promising results [11][12][13][14][15][16][17]. However, in these works, the epicentral distances of the seismic events, concerning the sensors, do not exceed 100 km. ...
... Figure 1b shows the internal circuit batch. Several dense low-cost MEMS networks have been recently tested for the monitoring of strong earthquakes and ground shaking, with promising results [11][12][13][14][15][16][17]. However, in these works, the epicentral distances of the seismic events, concerning the sensors, do not exceed 100 km. ...
In this work, we evaluate the suitability of a new MEMS sensor prototype, called ASX1000, for the monitoring of distant and moderate seismic events. This device is an inexpensive capacitive accelerometer with a relatively low level of instrumental noise; it can record both local and far seismic events. An experimental network built with ASX1000 MEMS, located in northern Italy, was able to record the Mw 6.3 29 Petrinja earthquake that occurred in December 2020; it had an epicentral distance of more than 350 km. We retrieved the strong motion parameters (PGA, pseudo-absolute velocity, and pseudo-absolute spectral acceleration) from the acceleration time histories recorded by the MEMS sensors. The obtained parameters were compared with the ones obtained by the closer high-quality seismometers, belonging to the INGV National Seismic Network. The comparison to the highest-quality sensors confirms a reasonable agreement of the inferred parameters. This work suggests that—in the near future—MEMS sensors could be adopted to integrate the existing seismic network. A denser coverage of sensors can sample more accurately the seismic wavefield, taking into account the large spatial variability of local geology and the relative differences in seismic response.
... The effectiveness and reliability of seismic urban networks, partially or entirely consisting of MEMS sensors, have been evaluated in numerous works together with the ability to record strong regional earthquakes [28][29][30][31] or even low to moderate (M ≥ 3) local earthquakes [32]. Other networks using MEMS sensors have mainly been designed for the seismic warning system (SWS) and many of these have already been implemented or are being set up in different countries [33][34][35]. ...
We describe the first dense real-time urban seismic–accelerometric network in Italy, named OSU-CT, located in the historic center of Catania. The city lies in the region with the greatest danger, vulnerability, and earthquake exposure in the entire Italian territory. OSU-CT was planned and realized within the project called EWAS “an Early WArning System for cultural heritage”, aimed at the rapid assessment of earthquake-induced damage and the testing of an on-site earthquake early warning system. OSU-CT is mainly based on low-cost instrumentation realized ad hoc by using cutting-edge technologies and digital MEMS (micro-electro-mechanical systems) triaxial accelerometers with excellent resolution and low noise. Twenty of the forty scheduled stations have already been set up on the ground floor of significant historic public buildings. In order to assess the performance of an earthquake early warning (EEW) on-site system, we also installed wide-band velocimeters (ETL3D/5s) in three edifices chosen as test sites, which will be instrumented for a structural health monitoring (SHM). In addition to several laboratory and field validation tests on the developed instruments, an effective operational test of OSU-CT was the Mw 4.3 earthquake occurring on 23 December 2021, 16 km west, south-west of Catania. Peak ground accelerations (4.956 gal to 39.360 gal) recorded by the network allowed obtaining a first urban shakemap and determining a reliable distribution of ground motion in the historical center of the city, useful for the vulnerability studies of the historical edifices.
... A study from Netherlands found previous flood experience was associated with both increased risk perceptions and increased preparedness and that people who had experienced flooding showed stronger emotions about future flooding and stronger intentions to take adaptive actions than those who had not [8]. Similarly, a survey from New Zealand found previous flood experience was associated with increased risk preparedness [9]. However, the findings on the relationship between past experience and risk perceptions are inconsistent, with some authors even suggesting that past experience can lower the perceived risk of future disaster through "gambler's fallacy" reasoning (i.e., the belief that the likelihood of an event occurring is lower after it has occurred [10]). ...
Flooding, already the most damaging type of natural disaster in China, is expected to become increasingly costly around the world. However, few studies have examined residents’ flood-preparedness intentions and the effect of flood experience and other variables on general financial risk-taking. This study explored the effects of Chinese residents’ previous flood experiences, trust in public flood protection, and flood-risk perception on flood-preparedness intentions and attitudes towards financial risk-taking in general. Study 1 surveyed residents in a flooded area (n = 241) and a non-flooded area (n = 248); Study 2 surveyed a non-flooded area (n = 1599). The relations between the variables were tested through structural-equation modelling (SEM). Overall, the two studies found that residents’ flood experiences, trust in public protection, and flood-risk perception not only predicted their flood preparedness but also their financial risk aversion. This study highlights the importance of residents’ trust in public flood protection for flood risk management and communication, especially for those who have not yet experienced flooding.
... They are widely adopted in many industrial applications such as telecommunication, automotive, game controllers, and so on (Shi et al., 2009). As a consequence of such widespread use, MEMS sensors are the most economic motion detector (Fleming et al., 2009;Cochran et al., 2012;D'Alessandro and D'Anna, 2013;Evans et al., 2014;Lawrence et al., 2014;Nof et al., 2019). Moreover, the performance of MEMS sensors is rapidly growing, being already comparable to high-quality accelerometers (Kong et al., 2016). ...
... This can lead to spatial aliasing of the wavefield and consequently an underestimation of the effective peak ground acceleration (PGA) as well as uncertainties in the estimation of local effects on the resulting shake maps (Wald et al., 2008). These are the reasons why several dense low-cost MEMS networks have been recently tested for the monitoring of strong earthquakes ground shaking (Cochran et al., 2009;Lawrence et al., 2014). The question remains whether such technology is suitable for low-magnitude seismicity detecting. ...
This study evaluates the seismicity detection efficiency of a new low-cost triaxial accelerometer prototype based on microelectromechanical systems (MEMS) technology. Networks of MEMS sensors were installed in telecommunication infrastructures to build two small arrays in northern and central Italy. The sensor prototypes recorded major earthquakes as well as nine small seismic events with 2.0<ML<3.0. Where possible, MEMS were compared to the closest high-quality seismic stations belonging to the national accelerometric network. The comparison, in terms of peak ground accelerations and spectral responses, confirms that the signals are in good agreement. The tested inexpensive MEMS sensors were able to detect small local events with epicentral distances as large as 50 km and provided an efficient characterization of the main motion parameters. This confirms that the proposed accelerometer prototypes are promising tools to integrate into traditional networks for local seismicity monitoring.
... The applicability and usefulness of these MEMS-based instruments in different applications including EEW and recording aftershock activity are reported by various researchers [6][7][8][9][10][11][12][13][14][15]. With the advancement in MEMS-based technology, many countries and companies have developed their sensors and are using them widely for EEW [16][17][18][19]. ...
Using low-cost sensors to build a seismic network for earthquake early warning (EEW) and to generate shakemaps is a cost-effective way in the field of seismology. National Taiwan University (NTU) network employing 748 P-Alert sensors based on micro-electro-mechanical systems (MEMS) technology is operational for almost the last 10 years. This instrumentation is capable of recording the strong ground motions of up to ± 2g and is dense enough to record the near-field ground motion. It has proven effective in generating EEW warnings and delivering real-time shake-maps to the concerned disaster relief agencies to mitigate the earthquake-affected regions. Before 2020, this instrumentation was used to plot peak ground acceleration (PGA) shakemaps only; however , recently it has been upgraded to generate the peak ground velocity (PGV), Central Weather Bureau (CWB) Intensity scale, and spectral acceleration (Sa) shakemaps at different periods as value-added products. After upgradation, the performance of the network was observed using the latest recorded earthquakes in the country. The experimental results in the present work demonstrate that the new parameters shakemaps added in the current work provide promising outputs, and are comparable with the shakemaps given by the official agency CWB. These shakemaps are helpful to delineate the earthquake-hit regions which in turn is required to assist the needy well in time to mitigate the seismic risk.
... A large number of institutions (either scientific and for civil protection) around the world have gained interest in this promising technology over the past decade by designing and implementing urban or regional seismic networks based on the MEMS technology (see [18] and [31] for a complete review). [14] The application and reliability of these devices have been evaluated [16,17] and they are able to record strong regional earthquakes or even moderate local earthquakes (M∼3) [7,13,15,24,26,38]. The main tasks of an urban seismic network can be summarized with a continuous chain of actions, before, during, and after that the strong ground motion reach the nodes of the network. ...
In the last years, monitoring systems based on low-cost and miniaturized sensors (MEMS) revealed as a very successful compromise between the availability of data and their quality. Also applications in the field of seismic and structural monitoring have been constantly increasing in term of number and variety of functions. Among these applications, the implementation of systems for earthquake early warning is a cutting-edge topic, mainly for its relevance for the society as millions of peoples in various regions of the world are exposed to high seismic hazard. This paper introduces the optimization of an already established seismic (and structural) monitoring system, that would make it suitable for the implementation of the earthquake early warning. In particular, the sampling code has been improved and a new triggering algorithm able to automatically detect the ground shaking due to the propagation of the seismic waves has been developed. The preliminary results indicate that the system is very flexible and easy to implement, and encourage to perform further developing steps.
