IP Library Granted Patent US 10,445,662
Granted Patent B2
US 10,445,662 · App. 16/160,332 · Granted Oct 15, 2019

Data processing system with machine learning engine to provide output generating functions

Inventors: John Rugel (Hawthorn Woods, IL); Brian Stricker (Northbrook, IL); Howard Hayes (Glencoe, IL)
Assignee: Allstate Insurance Company
G06N20/00G06F11/321G06F11/3438G06Q30/0271G06Q30/0627G06K9/66G16H10/60
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Quick Facts
Patent No.
US 10,445,662
App. No.
16/160,332
Granted
Oct 15, 2019
Kind
B2
Abstract

Systems, methods, computer-readable media, and apparatuses for identifying and executing one or more interactive condition evaluation tests to generate an output are provided. In some examples, user information may be received by a system and one or more interactive condition evaluation tests may be identified. An instruction may be transmitted to a computing device of a user and executed on the computing device to enable functionality of one or more sensors that may be used in the identified tests. A user interface may be generated including instructions for executing the identified tests. Upon initiating a test, data may be collected from one or more sensors in the computing device. The data collected may be transmitted to the system and may be processed using one or more machine learning datasets to generate an output.

Claims (63)

1. An interactive test generation and control computing platform, comprising:

a processing unit comprising a processor; and

a memory unit storing computer-executable instructions, which when executed by the processing unit, cause the interactive test generation and control computing platform to:

identify a first interactive condition evaluation test to be executed on a user computing device;

transmit a signal to the user computing device enabling functionality of one or more sensors in the user computing device and associated with the first interactive condition evaluation test;

generate a first user interface providing instructions for performing the first interactive condition evaluation test;

transmit the generated first user interface to the user computing device;

initiate the first interactive condition evaluation test on the user computing device;

after initiating the first interactive condition evaluation test, collect data from the enabled one or more sensors;

process, based on one or more machine learning datasets, the collected data to determine an output for the user; and

transmit the output to the user computing device.

2. The interactive test generation and control computing platform of claim 1 , further including instructions that, when executed, cause the interactive test generation and control computing platform to:

determine whether a second interactive condition evaluation test has been identified for execution; and

responsive to determining that the second interactive condition evaluation test has been identified for execution, initiating the second interactive condition evaluation test on the user computing device.

3. The interactive test generation and control computing platform of claim 1 , further including instructions that, when executed, cause the interactive test generation and control computing platform to:

receive user input requesting a product or service, and

identify one or more products for evaluation in response to receiving user input requesting the product or service.

4. The interactive test generation and control computing platform of claim 1 , wherein the processing, based on one or more machine learning datasets, the collected data to determine an output for the user further includes determining eligibility of the user for one or more products.

5. The interactive test generation and control computing platform of claim 4 , further including instructions that, when executed, cause the interactive test generation and control computing platform to:

receive data from an internal computing device;

receive data from an external computing device;

aggregate the data received from the internal computing device and the external computing device; and

process, based on the one or more machine learning datasets, the received data from the internal computing device and the received data from the external computing device to determine the eligibility of the user for the one or more products.

6. The interactive test generation and control computing platform of claim 5 , wherein the data from the external computing device includes data associated with at least one of: health information of the user and behavior information of the user.

7. The interactive test generation and control computing platform of claim 1 , wherein the first interactive condition evaluation test includes an instruction to walk for a predetermined distance.

8. The interactive test generation and control computing platform of claim 1 , wherein the first interactive condition evaluation test includes instructions to respond to a plurality of cognitive skills questions via the user computing device.

9. A method, comprising:

at a computing platform comprising at least one processor, memory, and a communication interface:

identifying, by the at least one processor, a first interactive condition evaluation test to be executed on a user computing device;

transmitting, by the at least one processor, a signal to the user computing device enabling functionality of one or more sensors in the user computing device and associated with the first interactive condition evaluation test;

generating, by the at least one processor, a first user interface providing instructions for performing the first interactive condition evaluation test;

transmitting, by the at least one processor, the generated first user interface to the user computing device;

initiating the first interactive condition evaluation test on the user computing device;

after initiating the first interactive condition evaluation test, collecting data from the enabled one or more sensors;

processing, by the at least one processor and based on one or more machine learning datasets, the collected data to determine an output for the user; and

transmitting the output to the user computing device.

10. The method of claim 9 , further including:

determining, by the at least one processor, whether a second interactive condition evaluation test has been identified for execution; and

responsive to determining that the second interactive condition evaluation test has been identified for execution, initiating, by the at least one processor, the second interactive condition evaluation test on the user computing device.

11. The method of claim 9 , further including:

receiving user input requesting a product or service, and

identifying one or more products for evaluation in response to receiving user input requesting the product or service.

12. The method of claim 9 , wherein the processing, based on one or more machine learning datasets, the collected data to determine an output for the user further includes determining eligibility of the user for one or more products.

13. The method of claim 9 , wherein the first interactive condition evaluation test includes an instruction to walk for a predetermined distance.

14. The method of claim 9 , wherein the first interactive condition evaluation test includes instructions to respond to a plurality of cognitive skills questions via the user computing device.

15. One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, memory, and a communication interface, cause the computing platform to:

identify a first interactive condition evaluation test to be executed on a user computing device;

transmit a signal to the user computing device enabling functionality of one or more sensors in the user computing device and associated with the first interactive condition evaluation test;

generate a first user interface providing instructions for performing the first interactive condition evaluation test;

transmit the generated first user interface to the user computing device;

initiate the first interactive condition evaluation test on the user computing device;

after initiating the first interactive condition evaluation test, collect data from the enabled one or more sensors;

process, based on one or more machine learning datasets, the collected data to determine an output for the user; and

transmit the output to the user computing device.

16. The one or more non-transitory computer-readable media of claim 15 , further including instructions that, when executed, cause the computing platform to:

determine whether a second interactive condition evaluation test has been identified for execution; and

responsive to determining that the second interactive condition evaluation test has been identified for execution, initiating the second interactive condition evaluation test on the user computing device.

17. The one or more non-transitory computer-readable media of claim 15 , further including instructions that, when executed, cause the computing platform to:

receive user input requesting a product or service, and

identify one or more products for evaluation in response to receiving user input requesting the product or service.

18. The one or more non-transitory computer-readable media of claim 15 , wherein the processing, based on one or more machine learning datasets, the collected data to determine an output for the user further includes determining eligibility of the user for one or more products.

19. The one or more non-transitory computer-readable media of claim 15 , wherein the first interactive condition evaluation test includes an instruction to walk for a predetermined distance.

20. The one or more non-transitory computer-readable media of claim 15 , wherein the first interactive condition evaluation test includes instructions to respond to a plurality of cognitive skills questions via the user computing device.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 15, 2018
From: RUGEL, JOHN; STRICKER, BRIAN; HAYES, HOWARD
To: ALLSTATE INSURANCE COMPANY
Reel/Frame 047167/0449 →
Continuity (3)
Continuation 15727226 · Oct 6, 2017
Continuation 15716983 · Sep 27, 2017
Related Publication 20190095307A1 · Mar 28, 2019