Insurance underwriting and re-underwriting implementing unmanned aerial vehicles (UAVs)

Patent metadata

Field	Value
Publication number	US-12033221-B2
Application number	US-202318206889-A
Country	US
Kind code	B2
Filing date	Jun 7, 2023
Priority date	Sep 22, 2014
Publication date	Jul 9, 2024
Grant date	Jul 9, 2024

Abstract

Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an area surrounding a property, and collect data related to property. A location for an inspection of a property to be conducted by a UAV may be received, and one or more images depicting a view of the location may be displayed via a user interface. Additionally, a geofence boundary may be determined based on an area corresponding to a property boundary, where the geofence boundary represents a geospatial boundary in which to limit flight of the UAV. Furthermore, a navigation route may be determined which corresponds to the geofence boundary for inspection of the property by the UAV, the navigation route having waypoints, each waypoint indicating a location for the UAV to obtain drone data. The UAV may be directed around the property using the determined navigation route.

First claim

What is claimed is:

1. A computer-implemented method of directing an unmanned aerial vehicle for inspecting a property, the method comprising:
receiving, by one or more processors, a location for an inspection of a property to be conducted by an unmanned aerial vehicle (UAV);
determining, by the one or more processors, a geofence boundary based on an area corresponding to a property boundary;
determining, by the one or more processors, a navigation route corresponding to the geofence boundary for inspection of the property by the UAV;
sending control signals, by the one or more processors to the UAV, to direct the UAV to capture drone data along the navigation route.

2. The computer-implemented method of claim 1 , further comprising:
receiving, at the one or more processors, the drone data captured by one or more sensors communicatively coupled to the UAV, wherein the drone data corresponds to the property.

3. The computer-implemented method of claim 2 , further comprising:
analyzing, by the one or more processors, the drone data corresponding to the property to identify one or more risk elements associated with the property; and
determining, by the one or more processors, an amount of risk associated with each of the one or more risk elements.

4. The computer-implemented method of claim 3 , wherein the drone data further corresponds to an area which surrounds the property, and further comprising:
combining, by the one or more processors, a first amount of risk associated with each of the one or more risk elements corresponding to the property with a second amount of risk associated with each of the one or more risk elements corresponding to the area which surrounds the property; and
determining, by the one or more processors, a total amount of risk associated with the property based upon the combined amounts of risk.

5. The computer-implemented method of claim 3 , wherein the drone data is current drone data and analyzing the drone data to determine one or more risk elements includes:
obtaining, at the one or more processors, previous drone data corresponding to the property and which was captured before the current drone data; and
comparing, by the one or more processors, the previous drone data to the current drone data to determine whether the amount of risk associated with the property has increased or decreased from a time in which the previous drone data was captured.

6. The computer-implemented method of claim 2 , wherein the property is a home, the drone data includes a thermal signature for the home, and when the thermal signature exceeds a predetermined threshold temperature based upon an analysis of the thermal signature, the method further comprises:
providing, by the one or more processors, an alert to emergency personnel that the home is at an increased risk of fire.

7. The computer-implemented method of claim 2 , wherein the property is a home, the drone data includes a soil sample of soil surrounding the home, and when soil moisture content exceeds a predetermined threshold moisture content level based upon an analysis of the soil sample, the method further comprises:
determining, by the one or more processors, a risk of sewer or drain backup associated with the home based upon the soil moisture content; and
identifying, by the one or more processors, a sump pump above a predetermined threshold size, type, capacity, or redundancy recommended for the house to mitigate the risk of sewer or drain backup based upon the soil moisture content.

8. The computer-implemented method of claim 2 , wherein the property is a home, the drone data includes a wood and a soil sample of a tree surrounding the home and the method further comprises:
analyzing, by the UAV, the wood and soil sample to determine a number and size of dead sections of the tree, a degree of root damage, a number of dead branches, or an age of the tree;
receiving, at the one or more processors, the analysis of the wood and soil sample; and
determining, by the one or more processors, a risk of the tree falling based upon the received analysis.

9. The computer-implemented method of claim 1 , wherein the drone data includes at least one of: (i) temperature data indicative of a current temperature associated with the property; (ii) chemical and biological data; (ii) image data; (iii) audio data; (iv) location data; or (v) size data and material characteristics for the property.

10. The computer-implemented method of claim 3 , wherein the one or more risk elements include at least one of: (i) a risk based upon a current condition of a component of the property; (ii) a natural disaster risk associated with the property; (iii) a risk of pests associated with the property; (iv) a risk based upon a hazardous object or activity associated with the property; or (v) a risk based upon a current condition of vegetation or other organic matter at or around the property.

11. A system of directing an unmanned aerial vehicle for inspecting a property, the system comprising:
one or more processors;
a communication network;
a non-transitory computer-readable memory coupled to the one or more processors, and the communication network, and storing thereon instructions that, when executed by the one or more processors, cause the system to:
receive, via the communication network, a location for an inspection of a property to be conducted by an unmanned aerial vehicle (UAV);
determine a geofence boundary based on an area corresponding to a property boundary;
determine a navigation route corresponding to the geofence boundary for inspection of the property by the UAV; and
send control signals to the UAV to direct the UAV to capture drone data along the navigation route.

12. The system of claim 11 , wherein the instructions further cause the system to:
receive, via the communication network, the drone data captured by one or more sensors communicatively coupled to the UAV at each waypoint on the navigating route, wherein the drone data corresponds to the property.

13. The system of claim 12 , wherein the instructions further cause the system to:
analyze the drone data corresponding to the property to identify one or more risk elements associated with the property; and
determine an amount of risk associated with each of the one or more risk elements.

14. The system of claim 13 , wherein the drone data further corresponds to an area which surrounds the property, and the instructions further cause the system to:
combine a first amount of risk associated with each of the one or more risk elements corresponding to the property with a second amount of risk associated with each of the one or more risk elements corresponding to the area which surrounds property; and
determine a total amount of risk associated with the property based upon the combined amounts of risk.

15. The system of claim 13 , wherein the drone data is current drone data and to analyze the drone data to determine one or more risk elements, the instructions cause the system to:
obtain previous drone data corresponding to the property and which was captured before the current drone data; and
compare the previous drone data to the current drone data to determine whether the amount of risk associated with the property has increased or decreased from a time in which the previous drone data was captured.

16. The system of claim 12 , wherein the property is a home, the drone data includes a thermal signature for the home, and when the thermal signature exceeds a predetermined threshold temperature based upon an analysis of the thermal signature, the ins

Assignees

• State Farm Mutual Automobile Insurance Co

Inventors

• Tofte Nathan L
• Ryan Timothy W
• Baumann Nathan W
• Lillie Joshua David
• Harvey Brian N
• Lyons Roxane
• Grant Rosemarie Geier
• Jacob Michael Shawn

Classifications

• G06T2215/16

  Using real world measurements to influence rendering · CPC title

• G06T2207/30232

  Surveillance · CPC title

• G06T2207/10032

  Satellite or aerial image; Remote sensing · CPC title

• G06T17/05

  Geographic models · CPC title

• G06T11/60

  Creating or editing images; Combining images with text · CPC title