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. 03, 2026

Filed:

Aug. 28, 2024
Applicant:

Nota, Inc., Daejeon, KR;

Inventors:

Sangtae Kim, Hwaseong-si, KR;

Eunsik Jung, Seoul, KR;

Wheemyung Shin, Seoul, KR;

Assignee:

NOTA, INC., Daejeon, KR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
B60W 50/14 (2020.01); B60W 40/09 (2012.01); G06V 10/82 (2022.01); G06V 20/59 (2022.01); B60W 40/08 (2012.01);
U.S. Cl.
CPC ...
B60W 50/14 (2013.01); B60W 40/09 (2013.01); G06V 10/82 (2022.01); G06V 20/597 (2022.01); B60W 2040/0827 (2013.01); B60W 2050/143 (2013.01); B60W 2420/403 (2013.01); B60W 2540/229 (2020.02); B60W 2556/10 (2020.02);
Abstract

Disclosed is a method for providing an alarm based on a behavior of a driver in a driver monitoring system. The method includes receiving a first image corresponding to the driver within a vehicle, generating first model output information which indicates possibility that an anomaly which compromises safety of the driver exists in the first image, from the first image, by using an artificial intelligence model. The method includes generating a first anomaly primary prediction result indicating whether the anomaly exists in the first image by comparing the first model output information with a first threshold, generating a first anomaly secondary prediction result by performing a first voting using the first anomaly primary prediction result and determining an anomaly alarm corresponding to the first image by performing a second voting using the first anomaly secondary prediction result.


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