SYSTEMS AND METHODS FOR FORECASTING AND ASSESSING HAZARD-RESULTANT EFFECTS

Patent №

US 11,200,788

Granted

2021-12-14

Filed 2021

Owner

1ST STREET FOUNDATION, INC.

Lab

AI components

4

ml · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

17361290

Hazard-resultant effects to land and buildings are predicted based on various inputs. Hazards may include any appropriate type of hazard (e.g., flood, wildfire, climate-related hazards, or the like). Inputs may include the likelihood that that a specific type of hazard may occur for various scenarios, terrestrial boundaries, property boundaries, census geographies, or the like. Relationships between the inputs are determined and used to quantify parameters pertaining to a specific type of hazard. For example, the depth of flood water may be predicted for a particular terrestrial boundary, a city or town, or a building, for specific climate scenarios. A risk likelihood of the quantified parameter may be determined for a particular period of time and environment. For example, flooding to a building may be determined, broken down by depth threshold and year of annual risk for specific climate scenarios. Economic loss also may be predicted.

Machine learningKnowledge representationPlanningAI hardwareG08B 21/10G08B 31/00G06N 7/01G06T 7/70G08B 29/26G06T 2207/20076G06T 2207/30184

AI classification

Planning1.00
Knowledge representation0.97
AI hardware0.97
Machine learning0.67
Vision0.44
Evolutionary computation0.00
Speech0.00
Natural language0.00

Ownership

1ST STREET FOUNDATION, INC.

assignment · 579800353

Assignors

AMODEO, MICHAEL, EBY, MATTHEW, FREEMAN, NEIL, KEARNS, EDWARD, MCALPINE, STEVEN, PORTER, JEREMY

On an employer assignment, the assignors are typically the inventors.

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