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:
Sep. 20, 2022

Filed:

Dec. 01, 2020
Applicant:

Verizon Patent and Licensing Inc., Basking Ridge, NJ (US);

Inventors:

John A. Turato, Garden City South, NY (US);

Stephane Chaysinh, Basking Ridge, NJ (US);

Brian Peebles, Cranford, NJ (US);

Neha Yadav, Waltham, MA (US);

Matthew W. Turlington, Richardson, TX (US);

Assignee:

Verizon Patent and Licensing Inc., Basking Ridge, NJ (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G08G 1/056 (2006.01); G08G 1/04 (2006.01); G08G 1/017 (2006.01); G06K 9/62 (2022.01); G06N 20/00 (2019.01); G07C 5/00 (2006.01); G06Q 50/26 (2012.01); G06Q 10/10 (2012.01); G06Q 50/20 (2012.01); G06Q 40/08 (2012.01); G01H 9/00 (2006.01); G01V 8/24 (2006.01); G09B 19/16 (2006.01); H04B 10/073 (2013.01); G06V 20/54 (2022.01); B60K 28/00 (2006.01);
U.S. Cl.
CPC ...
G08G 1/056 (2013.01); G01H 9/004 (2013.01); G01V 8/24 (2013.01); G06K 9/6257 (2013.01); G06N 20/00 (2019.01); G06Q 10/1093 (2013.01); G06Q 40/08 (2013.01); G06Q 50/205 (2013.01); G06Q 50/265 (2013.01); G06V 20/54 (2022.01); G07C 5/008 (2013.01); G08G 1/017 (2013.01); G08G 1/04 (2013.01); G09B 19/167 (2013.01); H04B 10/073 (2013.01); B60K 28/00 (2013.01);
Abstract

A device may receive fiber sensing data identifying vehicles traveling on a roadway associated with a fiber optic network and location data identifying geographical locations of the vehicles traveling on the roadway. The device may process the fiber sensing data, with a machine learning model, to identify a particular vehicle, of the vehicles, that is traveling in a wrong direction on the roadway. The device may process the location data, with the machine learning model, to identify locations of the roadway, a cellular network associated with the roadway, and vehicle devices of the vehicles traveling on the roadway, other than the particular vehicle, and a nearest camera device to the particular vehicle. The device may perform one or more actions based on the locations of the roadway, the cellular network associated with the roadway, and the vehicle devices of the vehicles traveling on the roadway, other than the particular vehicle.


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