The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 25, 2025

Filed:

Aug. 09, 2022
Applicants:

Korea Meteorological Administration, Seoul, KR;

Kyungpook National University Industry-academic Cooperation Foundation, Daegu, KR;

Inventors:

Jae-Kwang Ahn, Seoul, KR;

Young-Woo Kwon, Daegu, KR;

Jangsoo Lee, Daegu, KR;

Euna Park, Seoul, KR;

Eui-hong Hwang, Daejeon, KR;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
B81B 7/04 (2006.01); G01V 1/01 (2024.01); G01V 1/28 (2006.01); G01V 1/30 (2006.01); G01V 1/38 (2006.01);
U.S. Cl.
CPC ...
B81B 7/04 (2013.01); G01V 1/01 (2024.01); G01V 1/282 (2013.01); G01V 1/288 (2013.01); G01V 1/307 (2013.01); G01V 1/3808 (2013.01); B81B 2201/0285 (2013.01); B81B 2207/05 (2013.01);
Abstract

Provided are a device, method, and computer-readable recording medium for detecting an earthquake in a microelectromechanical system (MEMS)-based auxiliary seismic observation network. The method includes performing detrending of removing a moving average from original acceleration data received from single sensors of an MEMS-based auxiliary seismic observation network to preprocess the acceleration data, calculating a short-term average/long-term average (STA/LTA) value using a filter parameter value specified on the basis of the preprocessed acceleration data, generating an event occurrence message or event end message on the basis of the calculated STA/LTA value and transmitting the event occurrence message or event end message, when the event occurrence message is generated, calculating an earthquake probability through an earthquake detection deep learning model using the preprocessed acceleration data as an input, and analyzing noise by calculating a power spectral density (PSD) from the original acceleration data which is merged at certain intervals.


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