IP Library Granted Patent US 10,304,313
Granted Patent B1
US 10,304,313 · App. 16/211,525 · Granted May 28, 2019

Sensor data to identify catastrophe areas

Inventors: Phillip Moon (Bloomington, IL); Sunish Menon (Normal, IL); Jeffrey Kinsey (Bloomington, IL); Jeffrey W. Stoiber (Atlanta, GA)
Assignee: State Farm Mutual Automobile Insurance Company
G08B21/10G08B27/001
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Quick Facts
Patent No.
US 10,304,313
App. No.
16/211,525
Granted
May 28, 2019
Kind
B1
Abstract

A computer-implemented method for generating an automated response to a catastrophic event, that includes (1) analyzing a sample set of data generated in association with a catastrophic event to determine a threshold pattern; (2) receiving, with customer permission or affirmative consent, home sensor data from a smart home controller via wireless communication or data transmission, the home sensor data including data regarding at least one of (i) structural status; (ii) wind speed; (iii) availability of electricity; (iv) presence of water; (v) temperature; (vi) pressure; and/or (vii) presence of pollutants in the air and/or water; (3) determining, based upon or from computer analysis of the home sensor data, whether the home sensor data indicates a match to the threshold pattern; and (4) automatically generating a response if the home sensor data indicates a match to the threshold pattern. As a result, catastrophic events and responses thereto may be improved through usage of a remote network of home sensors.

Claims (21)

1. A computer-implemented method of generating proposed corrective actions to insurance-related events, the method comprising:

receiving, at one or more processors, a set of sensor data associated with a catastrophic event,

inputting, at the one or more processors, the set of data into a machine learning program to identify the catastrophic event,

generating, at the one or more processors, a geographic boundary of an area associated with the catastrophic event, the geographic boundary being associated with an actual or forecast extent of the catastrophic event;

receiving, at the one or more processors, a set of sensor data associated with a customer;

determining, at the one or more processors, whether a GPS location of the customer is within, or may be in proximity, to the geographic boundary' of the catastrophic event, the GPS location being determined from GPS coordinates within the set of sensor data associated with the customer, and

if so, generating a response or corrective action, at the one or more processors to alleviate impact of the catastrophic event on insureds and insured assets;

wherein the response or corrective action is determining or estimating, at the one or more processors, an extent of damage to an insured asset caused by the catastrophic event by inputting the set of sensor data associated with the customer into a machine learning program that is trained using historical images to identify damage and the extent thereof;

wherein the one or more processors is further configured to generate a proposed virtual insurance claim for the customer using the extent of damage estimated and transmit the proposed virtual insurance claim to the customer's mobile device for their review.

2. The computer-implemented method of claim 1 , wherein the response or corrective action is an electronic message that is transmitted to the customer's mobile device warning them of a path of the catastrophic event, and an estimated intensity thereof at their current GPS location.

3. The computer-implemented method of claim 1 , wherein the response or corrective action includes—

generating, at the one or more processors, a request that emergency or EMS personnel be sent to the GPS location of the customer; and

transmitting, from the one or more processors, over one or more radio links via wireless communication or data transmission, the request to a computing device or remote server associated with a police or fire department, or hospital.

4. The computer-implemented method of claim 1 , wherein the response or corrective action includes (i) determining a GPS location of a customer based upon vehicle or mobile device GPS location; (ii) determining that the GPS location of the customer is within the geographic boundary of the catastrophic event; and (iii) if so, generating an alternate route for the vehicle of the customer to take, and transmitting the alternate route to their vehicle to alleviate impact of the event on the customer and their vehicle.

5. The computer-implemented method of claim 1 , wherein the vehicle is an autonomous vehicle.

6. The computer-implemented method of claim 1 , wherein the response or corrective action includes generating an alternate route for a vehicle of the customer to take, and transmitting the alternate route to their vehicle to alleviate impact of the event on the customer and their vehicle.

7. The computer-implemented method of claim 1 , wherein the vehicle is an autonomous vehicle.

8. The computer-implemented method of claim 1 , the method further comprising;

transmitting, from the one or more processors, the response or corrective action to a smart home controller, vehicle controller, or mobile device of the customer using wireless communication and over one or more radio links.

9. The computer-implemented method of claim 1 , wherein the response or corrective action includes, at an external computing device: (i) determining that a customer vehicle is moving from analysis of sensor data received via wireless communication over a radio link; (ii) determining a GPS location of a customer from the sensor data received; (iii) determining that the GPS location of the customer vehicle is within the geographic boundary for the area associated with the catastrophic event; (iv) if so, generating an alternate route for the customer vehicle to take to minimize impact of the event on the customer and customer vehicle; and (v) transmitting the alternate route to the customer vehicle.

10. The computer-implemented method of claim 9 , wherein the customer is an autonomous vehicle.

Continuity (4)
Continuation 15904769 · Feb 26, 2018
Continuation 15397277 · Jan 3, 2017
Provisional Application 62307101 · Mar 11, 2016
Provisional Application 62275566 · Jan 6, 2016
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