US 12,762,631 B2Granted

Geographical risk heatmap based on variable risk factors

AssigneeAllstate Insurance Company

InventorsMarvin Lu, Sarah K. Webster, Leah M. Birch, Andrew Young

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Abstract

Implementations described herein provide systems and methods for generating a geographical heatmap based on variable factors. One implementation can include aggregating a plurality of data associated with a geographical location, generating a respective asset for a respective region within the geographical location, associating a respective subset of the plurality of data with the respective asset, determining a respective first type score for a respective first type data, determining a respective second type score for a respective second type data, generating a respective overall score based on the respective first type score and the respective second type score, constructing a map including each of the respective assets, and displaying, as a heatmap, the map with each respective asset.

Claims17

Dependent claims

A method for generating a geographical heatmap based on variable factors, the method comprising:

aggregating a plurality of data associated with a geographical location, wherein the plurality of data includes a first type of data associated with a first factor, the first factor associated with climate conditions, and a second type of data associated with a second factor, wherein the first type of data is different from the second type of data, wherein aggregating the plurality of data includes receiving climate prediction data from a non-hydrostatic climate model configured to simulate atmospheric conditions using physical parameterizations of atmospheric processes;
generating, for each respective region within the geographical location, a respective asset for a respective region within the geographical location;
determining, based on the first type of data, a granularity for each of the respective regions based on climate risk characterizations, wherein determining the granularity for each of the respective regions includes determining a bounding box for the geographical location based on geographic features affecting climate conditions;
determining, based on the granularity, a size for each of the respective regions, wherein each of the respective regions are generated based on the size, and wherein the granularity is dynamically determined based on a type of climate risk;
associating, for each of the respective assets, a respective subset of the plurality of data with the respective asset, wherein the respective subset of the plurality of data is associated with the respective region of the geographical location;
determining, for each of the respective assets, a respective first type score for a respective first type data in the respective subset of the plurality of data that is of the first type of data;
determining, for each of the respective assets, a respective second type score for a respective second type data in the respective subset of the plurality of data in the plurality of data that is of the second type of data;
generating, for each of the respective assets, a respective overall score based on the respective first type score and the respective second type score, wherein generating the respective overall score includes processing the respective subset of the plurality of data along with climate prediction data from the climate model to determine risk for the respective asset;
and
constructing, based on each of the respective regions and each of the respective overall scores, a map including each of the respective assets, and wherein each of the respective assets is associated with the respective region of the map;
and
displaying, as a heatmap, the map with each respective asset, wherein each respective asset is displayed based on the respective overall score.

9 more elements

A computing apparatus comprising:

a processor;
and
a memory storing instructions that, when executed by the processor, configure the apparatus to:
aggregate a plurality of data associated with a geographical location, wherein the plurality of data includes a first type of data associated with a first factor, the first factor associated with climate conditions, and a second type of data associated with a second factor, wherein the first type of data is different from the second type of data;
generate, for each respective region within a geographical location, a respective asset for a respective region within the geographical location;
determine, based on the first type of data, a granularity for each of the respective regions based on climate risk characterizations, wherein determining the granularity for each of the respective regions includes determining a bounding box for the geographical location based on geographic features affecting climate conditions;
determine, based on the granularity, a size for each of the respective regions, wherein each of the respective regions are generated based on the size and wherein the granularity is dynamically determined based on a type of climate risk;
associate, for each of the respective assets, a respective subset of the plurality of data with the respective asset, wherein the respective subset of the plurality of data is associated with the respective region of the geographical location;
determine, for each of the respective assets, a respective first type score for a respective first type data in the respective subset of the plurality of data that is of the first type of data;
determine, for each of the respective assets, a respective second type score for a respective second type data in the respective subset of the plurality of data in the plurality of data that is of the second type of data;
generate, for each of the respective assets, a respective overall score based on the respective first type score and the respective second type score, wherein generating the respective overall score includes processing the respective subset of the plurality of data along with climate prediction data from a climate model to determine risk for the respective asset;
and
construct, based on each of the respective regions and each of the respective overall scores, a map including each of the respective assets, and wherein each of the respective assets is associated with the respective region of the map;
and
render for display, as a heatmap, the map with each respective asset, wherein each respective asset is displayed based on the respective overall score.

12 more elements

A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a computer, cause the computer to:

aggregate a plurality of data associated with a geographical location, wherein the plurality of data includes a first type of data associated with a first factor, the first factor associated with climate conditions, and a second type of data associated with a second factor, wherein the first type of data is different from the second type of data, wherein aggregating the plurality of data includes receiving climate prediction data from a climate model;
generate, for each respective region within a geographical location, a respective asset for a respective region within the geographical location;
determine, based on the first type of data, a granularity for each of the respective regions based on climate risk characterizations, wherein determining the granularity for each of the respective regions includes determining a bounding box for the geographical location based on geographic features affecting climate conditions;
determine, based on the granularity, a size for each of the respective regions, wherein each of the respective regions are generated based on the size and wherein the granularity is dynamically determined based on a type of climate risk;
associate, for each of the respective assets, a respective subset of the plurality of data with the respective asset, wherein the respective subset of the plurality of data is associated with the respective region of the geographical location;
determine, for each of the respective assets, a respective first type score for a respective first type data in the respective subset of the plurality of data that is of the first type of data;
determine, for each of the respective assets, a respective second type score for a respective second type data in the respective subset of the plurality of data in the plurality of data that is of the second type of data;
generate, for each of the respective assets, a respective overall score based on the respective first type score and the respective second type score, wherein generating the respective overall score includes processing the respective subset of the plurality of data along with climate prediction data from the climate model to determine risk for the respective asset;
and
construct, based on each of the respective regions and each of the respective overall scores, a map including each of the respective assets, and wherein each of the respective assets is associated with the respective region of the map;
and
display, as a heatmap, the map with each respective asset, wherein each respective asset is displayed based on the respective overall score.

9 more elements

Dependencies are inferred from the claim text.