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.
Patent No.:
Date of Patent:
Jan. 11, 2022
Filed:
Jun. 10, 2020
Applicant:
Arccos Golf Llc, Stamford, CT (US);
Inventors:
Salman Hussain Syed, Stamford, CT (US);
Colin David Phillips, Lee's Summit, MO (US);
Assignee:
Arccos Golf LLC, Stamford, CT (US);
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A63B 71/06 (2006.01); A63B 60/46 (2015.01); A63B 24/00 (2006.01); G06N 3/08 (2006.01); G16H 20/30 (2018.01); A63B 102/32 (2015.01); A63B 69/36 (2006.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
A63B 71/0622 (2013.01); A63B 24/0003 (2013.01); A63B 60/46 (2015.10); A63B 71/0669 (2013.01); G06N 3/08 (2013.01); G16H 20/30 (2018.01); A63B 69/36 (2013.01); A63B 2071/0691 (2013.01); A63B 2102/32 (2015.10); A63B 2220/12 (2013.01); A63B 2220/51 (2013.01); A63B 2220/56 (2013.01); A63B 2220/72 (2013.01); A63B 2220/74 (2013.01); A63B 2220/75 (2013.01); A63B 2220/76 (2013.01); A63B 2220/803 (2013.01); A63B 2220/807 (2013.01); A63B 2220/808 (2013.01); A63B 2220/833 (2013.01); A63B 2220/836 (2013.01); A63B 2225/50 (2013.01); A63B 2230/06 (2013.01); A63B 2230/202 (2013.01); A63B 2230/207 (2013.01); A63B 2230/30 (2013.01); A63B 2230/50 (2013.01); G06N 20/00 (2019.01);
Abstract
Exemplary embodiments of the present disclosure are directed to systems, methods, and computer-readable media configured to autonomously generate personalized recommendations for a user before, during, or after a round of golf. The systems and methods can utilize course data, environmental data, user data, and/or equipment data in conjunctions with one or more machine learning algorithms to autonomously generate the personalized recommendations.