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.
AI classification
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.