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

• US 10,410,289 B1
• Filed: 09/18/2015
• Issued: 09/10/2019
• Est. Priority Date: 09/22/2014
• Status: Active Grant

• Current Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Original Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Inventors: Tofte, Nathan L., Ryan, Timothy W., Baumann, Nathan W., Jacob, Michael Shawn, Lillie, Joshua David, Harvey, Brian N., Lyons, Roxane, Grant, Rosemarie Geier
• Primary Examiner(s): Nguyen, Tien C
• Application Number:
  US14/858,075
• Time in Patent Office: 1,453 Days
• Field of Search: 705 4, 705 5, 705 2, 705 35, 705 38, 705 39, 705 40, 340961, 342 30, 342 36, 342 29, 701 3, 701 2, 701301, 701120, 244 751, 244175, 244 63, 715738, 715719, 182145, 367116, 348117, 702186, 709224
• CPC Class Codes: B64C 39/024 of the remote controlled vehicle type, i.e. RPV
• CPC Class Codes: B64D 47/08 Arrangements of cameras
• CPC Class Codes: B64U 10/00 Type of UAV
• CPC Class Codes: B64U 10/14 with four distinct rotor axes, e.g. quadcopters
• CPC Class Codes: B64U 2101/00 UAVs specially adapted for particular uses or applications
• CPC Class Codes: B64U 2101/30 for imaging, photography or videography
• CPC Class Codes: G01C 11/02 Picture taking arrangements specially adapted for photogrammetry or photographic surveying, e.g. controlling overlapping of pictures
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G06T 11/60 Editing figures and text; Combining figures or text
• CPC Class Codes: G06T 17/05 Geographic models
• CPC Class Codes: G06T 2207/10032 Satellite or aerial image; Remote sensing
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 2207/30236 Traffic on road, railway or crossing
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 2215/16 Using real world measurements to influence rendering
• CPC Class Codes: G06T 7/00 Image analysis
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/75 : involving models
• CPC Class Codes: G06V 10/42 : Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation
• CPC Class Codes: G06V 20/10 : Terrestrial scenes scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59
• CPC Class Codes: G06V 20/41 : Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items segmenting video sequences G06V20/49
• CPC Class Codes: G06V 20/44 : Event detection
• CPC Class Codes: H04N 5/44 : Receiver circuitry for the reception of television signals according to analogue transmission standards H04N5/14 takes precedence
• CPC Class Codes: H04N 7/185 : from a mobile camera, e.g. for remote control

Abstract

Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an area surrounding an insured or potentially insured asset, such as with the insurance customer'"'"'s permission, and collect data related to the insured or potentially insured asset, such as size, height, roof shape, materials (siding, roofing), etc. which may form a basis of the underwriting detail used to evaluate a property. The drone data may reveal site characteristics, such as slope or grade of a parcel; the proximity to other structures (and their uses); trees; rivers; coastlines; and earthquake faults. The drone data may be used by an insurance provider remote server to assess the risk associated with an insured asset, generate or modify an insurance premium or discount, etc. The drone data may also be used to mitigate risk and prevent loss by alerting policyholders of the risk such that corrective action may be taken.

Claims

1. A computer-implemented method of underwriting insurance based upon drone data, the method comprising:

capturing drone data, by one or more unmanned aerial vehicles communicatively coupled to one or more sensors configured to capture the drone data, including;

navigating to an area surrounding an asset insured or potentially insured by an insurance provider via an insurance policy;

collecting samples of data;

analyzing the samples of data; and

storing the samples of data as the drone data,

wherein the one or more sensors include at least one of a soil sample extractor, a wood sample extractor, a spectrometer, a heat sensor, an ultrasonic sensor, an image sensor, or a volumetric moisture content sensor, and wherein the drone data corresponds to the insured asset;

receiving, at one or more processors, the drone data captured by the one or more sensors communicatively coupled to the one or more unmanned aerial vehicles, wherein the drone data corresponds to the insured or potentially insured asset;

analyzing, by the one or more processors, the drone data corresponding to the insured or potentially insured asset to identify one or more risk elements associated with the insured or potentially insured asset;

determining, by the one or more processors, an amount of risk associated with each of the one or more risk elements; and

generating, by the one or more processors, insurance policy data for the insurance policy corresponding to the insured or potentially insured asset based upon the amount of risk associated with each of the one or more risk elements to facilitate performing an accurate and efficient underwriting or re-underwriting process using data collected by the one or more unmanned aerial vehicles.

2. The computer-implemented method of claim 1, wherein the drone data further corresponds to the area which surrounds the insured or potentially insured asset, 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 insured or potentially insured asset with a second amount of risk associated with each of the one or more risk elements corresponding to the area which surrounds the insured or potentially insured asset; and

determining, by the one or more processors, a total amount of risk associated with the insured or potentially insured asset based upon the combined amounts of risk.

3. The computer-implemented method of claim 1, 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 insured or potentially insured asset 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 insured or potentially insured asset has increased or decreased from a time in which the previous drone data was captured.

4. The computer-implemented method of claim 1, wherein when the amount of risk associated with the insured or potentially insured asset has increased or decreased from the time in which the previous drone data was captured based upon the comparison, adjusting, by the one or more processors, an insurance premium upon renewal of the insurance policy.

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

directing, by the one or more processors, the one or more unmanned aerial vehicles to an area defined by a geofenced geographic location surrounding the insured or potentially insured asset; and

directing, by the one or more processors, the one or more unmanned aerial vehicles to capture the drone data at a plurality of positions within the geofenced geographic location.

6. The computer-implemented method of claim 1, wherein the insured or potentially insured asset 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 the analysis of the thermal signature, the method further comprising:

providing, by the one or more processors, an alert to emergency personnel that the home is at an increased risk of fire; and

adjusting, by the one or more processors, an insurance premium upon renewal of the insurance policy based upon the increased risk of fire.

7. The computer-implemented method of claim 1, wherein the insured or potentially insured asset 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 the analysis of the soil sample, the method further comprising:

determining, by the one or more processors, a risk of sewer or drain backup associated with the home based upon the soil moisture content;

adjusting, by the one or more processors, an insurance premium upon renewal of the insurance policy based upon the risk of sewer or drain backup; and

determining, 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 1, wherein the insured or potentially insured asset is a home, the drone data includes a wood and a soil sample of a tree surrounding the home and further comprising:

analyzing, by the one or more unmanned aerial vehicles, 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 insured or potentially insured asset;

(ii) chemical and biological data;

(ii) image data;

(iii) audio data;

(iv) location data;

or (v) size data and material characteristics for the insured or potentially insured asset.

10. The computer-implemented method of claim 1, 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 insured or potentially insured asset;

(ii) a natural disaster risk associated with the insured or potentially insured asset;

(iii) a risk of pests associated with the insured or potentially insured asset;

(iv) a risk based upon a hazardous object or activity associated with the insured or potentially insured asset;

or (v) a risk based upon a current condition of vegetation or other organic matter at or around the insured or potentially insured asset.

11. A system for underwriting insurance based upon drone data comprising:

one or more unmanned aerial vehicles communicatively coupled to one or more sensors including at least one of a soil sample extractor, a wood sample extractor, a spectrometer, a heat sensor, an ultrasonic sensor, an image sensor, or a volumetric moisture content sensor, the one or more unmanned aerial vehicles configured to capture drone data including;

navigate to an area surrounding an asset insured or potentially insured by an insurance provider via an insurance policy;

collect samples of data;

analyze the samples of data; and

store the samples of data as the drone data,

wherein the drone data corresponds to the insured or potentially insured asset;

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, the drone data captured by the one or more sensors communicatively coupled to the one or more unmanned aerial vehicles;

analyze the drone data corresponding to the insured or potentially insured asset to determine one or more risk elements associated with the insured or potentially insured asset;

determine an amount of risk associated with each of the one or more risk elements; and

generate insurance policy data for the insurance policy corresponding to the insured or potentially insured asset based upon the amount of risk associated with each of the one or more risk elements to facilitate performing an accurate and efficient underwriting or re-underwriting process using data collected by the one or more unmanned aerial vehicles.

12. The system of claim 11, wherein the drone data further corresponds to the area which surrounds the insured or potentially insured asset, 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 insured or potentially insured asset with a second amount of risk associated with each of the one or more risk elements corresponding to the area which surrounds the insured or potentially insured asset; and

determine a total amount of risk associated with the insured or potentially insured asset based upon the combined amounts of risk.

13. The system of claim 11, 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 insured or potentially insured asset 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 insured or potentially insured asset has increased or decreased from a time in which the previous drone data was captured.

14. The system of claim 11, wherein when the amount of risk associated with the insured or potentially insured asset has increased or decreased from the time in which the previous drone data was captured based upon the comparison, the instructions cause the system to adjust an insurance premium upon renewal of the insurance policy.

15. The system of claim 11, wherein the instructions further cause the system to:

direct, via the communication network, the one or more unmanned aerial vehicles to an area defined by a geofenced geographic location surrounding the insured or potentially insured asset; and

direct, via the communication network, the one or more unmanned aerial vehicles to capture the drone data at a plurality of positions within the geofenced geographic location.

16. The system of claim 11, wherein the insured or potentially insured asset 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 the analysis of the thermal signature, the instructions further cause the system to:

provide, via the communication network, an alert to emergency personnel that the home is at an increased risk of fire; and

adjust an insurance premium upon renewal of the insurance policy based upon the increased risk of fire.

17. The system of claim 11, wherein the insured or potentially insured asset 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 the analysis of the soil sample, the instructions further cause the system to:

determine a risk of sewer or drain backup associated with the home based upon the soil moisture content;

adjust an insurance premium upon renewal of the insurance policy based upon the risk of sewer or drain backup; and

determine 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.

18. The system of claim 11, wherein the insured or potentially insured asset is a home, the drone data includes a wood and a soil sample of a tree surrounding the home and the instructions further cause the system to:

receiving, via the communication network, an analysis of the wood and soil sample by the one or more unmanned aerial vehicles, wherein the analysis includes 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; and

determine a risk of the tree falling based upon the received analysis.

19. The system of claim 11, 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 insured or potentially insured asset;

(ii) a natural disaster risk associated the insured or potentially insured asset;

(iii) a risk of pests associated with the insured or potentially insured asset;

(iv) a risk based upon a hazardous object or activity associated with the insured or potentially insured asset;

or (v) a risk based upon a current condition of vegetation or other organic matter at or around the insured or potentially insured asset.