Granted Patent B2

US 12,737,817 · App. 18/200,181 · Granted Sep 15, 2026

Inventors: Sharon Gibson (Carlock, IL); Bryan R. Nussbaum (Bloomington, IL); Arsh Singh (Frisco, TX); Alexander Cardona (Gilbert, AZ); Daniel Wilson (Glendale, AZ); Phillip Michael Wilkowski (Phoenix, AZ)

Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY

G06Q40/08

Abstract

Claims (66)

1 . A computer-implemented method for generating a home health indicator, the computer-implemented method comprising:

receiving, by one or more processors, home telematics data associated with a property for a user;

analyzing, by the one or more processors and according to a machine learning model, the home telematics data to determine age data for one or more components of the property, wherein:

the one or more components of the property are associated with a structural integrity of the property,

the age data is based upon at least a portion of the home telematics data identified as statistically significant, and

determining the age data includes weighting, using the at least the portion of the home telematics data identified as statistically significant, an original age of the property and an age of one or more modifications to the property;

training, by the one or more processors and responsive to an indication to train the machine learning model including a condition that the determined age data is accurately representative of the property, the machine learning model using at least the determined age data;

determining, by the one or more processors and based upon at least the determined age data, a home health indicator for the property, wherein the home health indicator for the property is associated with a determined age for the property; and

generating, by the one or more processors and based upon at least the determined home health indicator, a home score for the property.

2 . The computer-implemented method of claim 1 , further comprising:

receiving, by the one or more processors and from the user, user-reported data regarding the one or more components of the property.

3 . The computer-implemented method of claim 2 , further comprising:

retrieving, by the one or more processors, verification data from a third party database; and

verifying, by the one or more processors, the user-reported data by comparing the user-reported data to the verification data.

4 . The computer-implemented method of claim 2 , further comprising:

modifying, by the one or more processors, the generated home score for the property based upon at least the user-reported data.

5 . The computer-implemented method of claim 1 , further comprising:

transmitting, by the one or more processors, at least some of the home telematics data to the user; and

verifying, by the one or more processors, the at least some of the home telematics data before analyzing the home telematics data.

6 . The computer-implemented method of claim 1 , wherein the weighting is further based upon at least a percentage of the property that has been modified over time.

7 . The computer-implemented method of claim 1 , further comprising:

determining, by the one or more processors and based upon the home telematics data, one or more recommendations for modifications to the property;

generating, by the one or more processors, a range of home score modifications for at least some of the one or more recommendations, wherein the range of home score modifications are based upon at least a range of times for performing the at least some of the one or more recommendations; and

calculating, by the one or more processors and based upon the home score modifications, a modified home score.

8 . A computing device configured to generate a home health indicator, the computing device comprising:

one or more processors;

a communication unit; and

a non-transitory computer-readable medium coupled to the one or more processors and the communication unit and storing instructions thereon that, when executed by the one or more processors, cause the computing device to:

receive home telematics data associated with a property for a user;

analyze, according to a machine learning model, the home telematics data to determine age data for one or more components of the property, wherein:

the one or more components of the property are associated with a structural integrity of the property,

the age data is based upon at least a portion of the home telematics data identified as statistically significant, and

determining the age data includes weighting, using the at least the portion of the home telematics data identified as statistically significant, an original age of the property and an age of one or more modifications to the property;

train, responsive to an indication to train the machine learning model including a condition that the determined age data is accurately representative of the property, the machine learning model using at least the determined age data;

determine, based upon at least the determined age data, a home health indicator for the property, wherein the home health indicator for the property is associated with a determined age for the property; and

generate, based upon at least the determined home health indicator, a home score for the property.

9 . The computing device of claim 8 , wherein the non-transitory computer-readable medium further stores instructions that, when executed by the one or more processors, cause the computing device to:

receive, from the user, user-reported data regarding the one or more components of the property.

10 . The computing device of claim 9 , wherein the non-transitory computer-readable medium further stores instructions that, when executed by the one or more processors, cause the computing device to:

retrieve verification data from a third-party database; and

verify the user-reported data by comparing the user-reported data to the verification data.

11 . The computing device of claim 9 , wherein the non-transitory computer-readable medium further stores instructions that, when executed by the one or more processors, cause the computing device to:

modify the generated home score for the property based upon at least the user-reported data.

12 . The computing device of claim 8 , wherein the non-transitory computer-readable medium further stores instructions that, when executed by the one or more processors, cause the computing device to:

transmit at least some of the home telematics data to the user; and

verify the at least some of the home telematics data before analyzing the home telematics data.

13 . The computing device of claim 8 , wherein weighting the original age of the property and the age of the one or more modifications to the property is further based upon at least a percentage of the property that has been modified over time.

14 . The computing device of claim 8 , wherein the non-transitory computer-readable medium further stores instructions that, when executed by the one or more processors, cause the computing device to:

determine, based upon the home telematics data, one or more recommendations for modifications to the property;

generate a range of home score modifications for at least some of the one or more recommendations, wherein the range of home score modifications are based upon at least a range of times for performing the at least some of the one or more recommendations; and

calculate, based upon the home score modifications, a modified home score.

15 . A non-transitory computer-readable medium storing instructions to generate a home health indicator that, when executed, cause a computing device to:

receive home telematics data associated with a property for a user;

analyze, according to a machine learning model, the home telematics data to determine age data for one or more components of the property, wherein:

the one or more components of the property are associated with a structural integrity of the property,

the age data is based upon at least a portion of the home telematics data identified as statistically significant, and

determining the age data includes weighting, using the at least the portion of the home telematics data identified as statistically significant, an original age of the property and an age of one or more modifications to the property;

train, responsive to an indication to train the machine learning model including a condition that the determined age data is accurately representative of the property, the machine learning model using at least the determined age data;

determine, based upon at least the determined age data, a home health indicator for the property, wherein the home health indicator for the property is associated with a determined age for the property; and

generate, based upon at least the determined home health indicator, a home score for the property.

16 . The non-transitory computer-readable medium of claim 15 , the instructions further including instructions that, when executed, cause the computing device to:

receive, from the user, user-reported data regarding the one or more components of the property.

17 . The non-transitory computer-readable medium of claim 15 , the instructions further including instructions that, when executed, cause the computing device to:

determine, based upon the home telematics data, one or more recommendations for modifications to the property;

generate a range of home score modifications for at least some of the one or more recommendations, wherein the range of home score modifications are based upon at least a range of times for performing the at least some of the one or more recommendations; and

calculate, based upon the home score modifications, a modified home score.

Assignments (1)

Continuity (7)

References Cited (400)