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:
Nov. 01, 2022

Filed:

Nov. 25, 2019
Applicant:

Strong Force Intellectual Capital, Llc, Santa Monica, CA (US);

Inventor:

Charles Howard Cella, Pembroke, MA (US);

Assignee:

Strong Force Intellectual Capital, LLC, Fort Lauderdale, FL (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01C 21/34 (2006.01); G07C 5/08 (2006.01); G06N 3/08 (2006.01); B60W 40/08 (2012.01); G06F 40/40 (2020.01); G05D 1/02 (2020.01); G07C 5/00 (2006.01); G05B 13/02 (2006.01); G05D 1/00 (2006.01); G06N 3/04 (2006.01); G07C 5/02 (2006.01); G06N 20/00 (2019.01); G06Q 50/18 (2012.01); G06Q 50/30 (2012.01); G06V 20/64 (2022.01); G06N 3/02 (2006.01); G06Q 30/02 (2012.01); G06Q 50/00 (2012.01);
U.S. Cl.
CPC ...
G01C 21/3469 (2013.01); B60W 40/08 (2013.01); G01C 21/3438 (2013.01); G05B 13/027 (2013.01); G05D 1/0088 (2013.01); G05D 1/0212 (2013.01); G05D 1/0287 (2013.01); G06F 40/40 (2020.01); G06N 3/0418 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06Q 50/188 (2013.01); G06Q 50/30 (2013.01); G06V 20/64 (2022.01); G07C 5/006 (2013.01); G07C 5/008 (2013.01); G07C 5/02 (2013.01); G07C 5/08 (2013.01); G07C 5/0816 (2013.01); B60W 2040/0881 (2013.01); G05D 2201/0213 (2013.01); G06N 3/02 (2013.01); G06Q 30/0281 (2013.01); G06Q 50/01 (2013.01);
Abstract

Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.


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