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Analysis on Seismic Observation Data through Operation of MEMS Acceleration Sensor Based CrowdQuake

Research output: Contribution to journalArticlepeer-review

Abstract

CrowdQuake is a seismic observation network based on MEMS acceleration sensors. Starting with 300 smartphone-based seismic sensors in 2019, more than 5,200 sensors have been installed and operated nationwide in September 2021. In this paper, we analyze the seismic detection performance of CrowdQuake through two weeks of records in September 2021. First, we monitor changes in the number of sensors connected to the seismic network according to the time change. Then, we classify the recording quality of each sensor using K-means clustering. By classifying the data quality of a sensor, we can see how sensor data quality affects the overall performance of earthquake detection thereby analyzing the detection performance of CrowdQuake. In addition, to understand changes in data quality due to the weather, we collected sensor data when typhoon Omais was passed across the country in September 2021. Finally, we report two detected earthquake cases of magnitude 2.2 in Taean on September 17, 2021, and magnitude 2.2 in Boseong on September 20, 2021.

Original languageEnglish
Pages (from-to)206-213
Number of pages8
JournalJournal of Korean Institute of Communications and Information Sciences
Volume47
Issue number1
DOIs
StatePublished - 1 Jan 2022

Keywords

  • Earthquake
  • Machine Learning
  • MEMS Accelerometer
  • Noise Analysis

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