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. 18, 2025

Filed:

Jan. 11, 2023
Applicants:

University of Florida Research Foundation, Inc., Gainesville, FL (US);

Clarkson University, Potsdam, NY (US);

Woods Hole Oceanographic Institution, Woods Hole, MA (US);

Inventors:

Forrest J. Masters, Gainesville, FL (US);

Pedro L. Fernandez-Caban, Potsdam, NY (US);

Brian M. Phillips, Gainesville, FL (US);

Christopher C. Ferraro, Gainesville, FL (US);

Britt Raubenheimer, Woods Hole, MA (US);

Wei-Ting Lu, Gainesville, FL (US);

Assignees:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01W 1/04 (2006.01); E02D 5/56 (2006.01); E02D 27/16 (2006.01); E04H 12/18 (2006.01); G01W 1/00 (2006.01); G01W 1/10 (2006.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01); H04L 67/12 (2022.01); H04N 7/18 (2006.01); H04Q 9/00 (2006.01);
U.S. Cl.
CPC ...
G01W 1/04 (2013.01); E04H 12/18 (2013.01); G01W 1/10 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); H04L 67/12 (2013.01); E02D 5/56 (2013.01); E02D 27/16 (2013.01); G01W 2001/006 (2013.01); H04N 7/183 (2013.01); H04Q 9/00 (2013.01); H04Q 2209/40 (2013.01);
Abstract

The present disclosure describes various embodiments of systems, apparatuses, and methods for large-scale processing of weather-related data. For one such system, the system comprises a database of weather-related data providing from at least one weather monitoring station and at least one processor for coordinating a data processing job for processing a set of input weather-related data from the database. Accordingly, the input data comprises sensor data from the at least one weather monitoring station positioned on an open shoreline during a hydrodynamic event, weather model data for the hydrodynamic event, and at least one of air-craft reconnaissance data or satellite reconnaissance data regarding the hydrodynamic event, wherein the at least one processor is configured to assimilate the input data and generate, using machine learning, an improved weather prediction model for the hydrodynamic event. Other systems, apparatuses, and methods are also provided.


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