US 12,293,667 B1
Facial recognition technology for improving driver safety
Evaline Shin-Tin Tsai, Cupertino, CA (US); Alan Guihong Liu, San Francisco, CA (US); Ijeoma Emeagwali, San Francisco, CA (US); Ishaan Kansal, San Francisco, CA (US); Saleh ElHattab, San Francisco, CA (US); Bodecker John DellaMaria, San Francisco, CA (US); Eliott Ray Chapuis, San Francisco, CA (US); Jason Noah Laska, San Francisco, CA (US); Jennifer Kao, San Francisco, CA (US); Sean Kyungmok Bae, San Francisco, CA (US); Sylvie Lee, Pittsburgh, PA (US); and Brian Tuan, Cupertino, CA (US)
Assigned to Samsara Inc., San Francisco, CA (US)
Filed by Samsara Inc., San Francisco, CA (US)
Filed on Apr. 29, 2024, as Appl. No. 18/649,115.
Application 18/649,115 is a continuation of application No. 18/130,756, filed on Apr. 4, 2023, granted, now 12,002,364.
Application 18/130,756 is a continuation of application No. 17/821,887, filed on Aug. 24, 2022, granted, now 11,749,117.
Application 17/821,887 is a continuation of application No. 16/929,722, filed on Jul. 15, 2020, granted, now 11,620,909.
Claims priority of provisional application 62/909,327, filed on Oct. 2, 2019.
Int. Cl. G08G 1/00 (2006.01); B60R 11/04 (2006.01); G06N 20/00 (2019.01); G06T 7/73 (2017.01); G06V 20/59 (2022.01); G06V 40/16 (2022.01)
CPC G08G 1/20 (2013.01) [B60R 11/04 (2013.01); G06N 20/00 (2019.01); G06T 7/74 (2017.01); G06V 20/59 (2022.01); G06V 40/173 (2022.01); B60R 2300/8006 (2013.01); G06T 2200/24 (2013.01); G06T 2207/30201 (2013.01); G06T 2207/30268 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A system comprising: one or more computer processors; one or more computer memories; a set of instructions stored in the one or more computer memories, the set of instructions configuring the one or more computer processors to perform operations, the operations comprising: detecting that a driver has been assigned a first safety event; identifying additional safety events associated with the driver; sorting the additional safety events based on severity levels; providing a notification to the driver to complete an online learning module pertaining to the additional safety events, the online learning module recommended through an application of machine-learning to a type of the first safety event or the additional safety events; and tracking progress of the driver toward completing the online learning module;
wherein the sorting of the additional safety events based on the severity levels is performed using a machine-learned model that prioritizes the additional safety events based on historical data regarding accident outcomes associated with similar events.