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:
Apr. 23, 2024

Filed:

Feb. 21, 2021
Applicant:

Terrafuse, Inc., San Francisco, CA (US);

Inventors:

Brian White, San Francisco, CA (US);

Jing Li, Concord, CA (US);

Adrian Albert, San Francisco, CA (US);

Assignee:

Terrafuse, Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 18/2415 (2023.01); G06F 18/2113 (2023.01); G06F 18/214 (2023.01); G06F 30/20 (2020.01); G06N 3/08 (2023.01); G06V 10/25 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 20/13 (2022.01);
U.S. Cl.
CPC ...
G06F 30/20 (2020.01); G06F 18/2113 (2023.01); G06F 18/214 (2023.01); G06F 18/2415 (2023.01); G06N 3/08 (2013.01); G06V 10/25 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 20/13 (2022.01);
Abstract

Apparatuses, methods, and systems for generating gridded predictions of a probability of wildfire spread for geographies are disclosed. One method includes sensing observational climate and earth surface data, obtaining historical data on wildfire spread events, obtaining gridded climate data, creating a set of input features, creating a gridded wildfire data set, training a model that learns one or more probabilistic mapping function emulators between the set of input features and the gridded wildfire data set, which predicts a first probability of wildfire occurrence and a rate and extent of wildfire spread within a geographical region and at a specified period of time, and generating gridded wildfire prediction data including a second probability of wildfire occurrence and spread within the geographical region, using the model and a new set of input features over the geographical region but for a different time period.


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