Development Status of Crowdsourced Ground Vibration Data Collection System Based on Micro-Electro-Mechanical Systems (MEMS) Sensor

Sangho Lee; Jihoe Kwon; Dong-Woo Ryu

doi:10.7474/TUS.2018.28.6.547

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2018 Vol.28, Issue 6 Preview Page Next Page

Technical Note

Development Status of Crowdsourced Ground Vibration Data Collection System Based on Micro-Electro-Mechanical Systems (MEMS) Sensor MEMS 센서 기반 지반진동 정보 크라우드소싱 수집시스템 개발 현황

31 December 2018. pp. 547-554

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Abstract

Using crowdsourced sensor data collection technique, it is possible to collect high-density ground vibration data which is difficult to obtain by conventional methods. In this study, we have developed a crowdsourced ground vibration data collection system using MEMS sensors mounted on small electronic devices including smartphones, and implemented client and server based on the proposed infrastructure system design. The system is designed to gather vibration data quickly through Android-based smartphones or fixed devices based on Android Things, minimizing the usage of resource like power usage and data transmission traffic of the hardware.

Keywords

Ground vibration

MEMS

Accelerometer

Crowdsourcing

Smartphone

크라우드소싱을 활용한 센서 자료 수집은 기존의 방식으로 얻기 어려운 고밀도 지반 진동 정보의 수집이 가능하다. 본 연구에서는 스마트폰과 같은 소형 전자기기에 탑재된 MEMS 센서를 활용한 크라우드소싱 방식 지반 진동 수집 시스템을 개발하였으며, 이를 위한 기반 체계 설계 및 클라이언트와 서버에 대한 구현을 수행하였다. 해당 시스템은 Android 기반의 스마트폰이나 Android Things 기반의 고정식 장비를 통해 진동 데이터를 신속히 수집하면서 하드웨어의 전력 및 데이터 사용량을 최소화할 수 있도록 설계되었다.

키워드

지반 진동

MEMS

가속도계

크라우드소싱

스마트폰

References

Cartwright, J., 2016, Technology: smartphone science, Nature 531.7596, 669-671.

10.1038/nj7596-669a27035011

Clayton, R. W., T. Heaton, M. Chandy, A. K. Krause, M. Kohler, J. Bunn, R. Guy, M. Olson, M. Faulkner, M. Cheng, L. Strand, R. Chandy, D. Obenshain, A. Liu and M. Aivazis, 2011, Community Seismic Network, Ann. Geophys. 54, 738-747.

Cochran, E., J. Lawrence, C. Christensen and A. Chung, 2009, A novel strong-motion seismic network for community participation in earthquake monitoring, IEEE Instrum. Meas. Mag. 12, 8-15.

10.1109/MIM.2009.5338255

D'Alessandro, A., D. Luzio and G. D'Anna, 2014, Urban MEMS based seismic network for post-earthquakes rapid disaster assessment, Adv. Geosci. 40.40, 1-9.

10.5194/adgeo-40-1-2014

Dunn, P. T., A. Y. Ahn, A. Bostrom and J. E. Vidale, 2016, Perceptions of earthquake early warnings on the US West Coast, Int. J. Disast. Risk Re. 20, 112-122.

10.1016/j.ijdrr.2016.10.019

Feng, M., Y. Fukuda, M. Mizuta and E. Ozer, 2015, Citizen sensors for SHM: Use of accelerometer data from smartphones, Sensors 15.2, 2980-2998.

10.3390/s15020298025643056PMC4367344

Finazzi, F. and Fasso, A., 2017, A statistical approach to crowdsourced smartphone-based earthquake early warning systems, Stoch. Env. Res. Risk A. 31.7, 1649-1658.

10.1007/s00477-016-1240-8

Finazzi, F., 2016, The earthquake network project: Toward a crowdsourced smartphone-based earthquake early warning system, B. Seismol. Soc. Am. 106.3, 1088-1099.

10.1785/0120150354

Haddadi, H., A. Shakal, M. Huang, J. Parrish, C. Stephens, W. Savage and W. Leith, 2012, Report on progress at the center for engineering strong motion data (CESMD), In Proc. World Conf. Earthq. Eng., Lisbon, 1-7.

Hsieh, C. Y., Y. M. Wu, T. L. Chin, K. H. Kuo, D. Y. Chen, K, S, Wang, Y. T. Chan, W. Y. Chang, W. S. Li and S. H. Ker, 2014, Low Cost Seismic Network Practical Applications for Producing Quick Shaking Maps in Taiwan. Terr. Atmos. Ocean. Sci. 25.5, 617-624.

10.3319/TAO.2014.03.27.01(T)

InvenSense, 2014, MPU-6500 Product Specification Revision 1.1.

Kim, Y., T. S. Kang and J. Rhie, 2017, Development and Application of a Real-Time Warning System Based on a MEMS Seismic Network and Response Procedure for the Day of the National College Entrance Examination in South Korea, Seismol. Res. Lett. 88.5, 1322-1326.

10.1785/0220160208

Kong, Q., Allen, R. M., Schreier, L. and Y. W. Kwon, 2016a, MyShake: A smartphone seismic network for earthquake early warning and beyond, Science Adv. 2.2, e1501055.

Kong, Q., R. M. Allen and L. Schreier, 2016b, MyShake: Initial observations from a global smartphone seismic network, Geophys. Res. Lett. 43.18, 9588-9594.

10.1002/2016GL070955

Krizhevsky, A., I. Sutskever and G. E. Hinton, 2012, Imagenet classification with deep convolutional neural networks, In Adv. Neur. In. 1097-1105.

Pierleoni, P., S. Marzorati, C. Ladina, S. Raggiunto, A. Belli, L. Palma, M. Cattaneo and S. Valenti, 2018, Performance Evaluation of a Low-Cost Sensing Unit for Seismic Applications: Field Testing During Seismic Events of 2016-2017 in Central Italy, IEEE Sens. J. 18.16, 6644-6659.

10.1109/JSEN.2018.2850065

Qiuping, W., Z. Shunbing and D. Chunquan, 2011, Study on key technologies of Internet of Things perceiving mine, Procedia Engineer. 26, 2326-2333.

10.1016/j.proeng.2011.11.2442

Shrestha, A., J. Dang and X. Wang, 2018, Development of a smart-device-based vibration-measurement system: Effectiveness examination and application cases to existing structure. Struct. Control Health Monit. 25.3, e2120.

Yang, D., G. Xue, X. Fang and J. Tang, 2012, Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing. In Proc. Int. Conf. Mob. Comp. Networking, Istanbul, 173-184.

10.1145/2348543.2348567

Zambrano, A. M., I. Perez, C. Palau and M. Esteve, 2017, Technologies of internet of things applied to an earthquake early warning system, Future Gener. Comp. Sy. 75, 206-215.

10.1016/j.future.2016.10.009

Information

Publisher :Korean Society for Rock Mechanics and Rock Engineering
Publisher(Ko) :한국암반공학회
Journal Title :Tunnel and Underground Space
Journal Title(Ko) :터널과 지하공간
Volume : 28
No :6
Pages :547-554
Received Date : 2018-12-04
Revised Date : 2018-12-18
Accepted Date : 2018-12-18
DOI :https://doi.org/10.7474/TUS.2018.28.6.547

Tunnel and Underground Space ISSN:1225-1275(Print) 2287-1748(Online) 터널과 지하공간

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