Loss mitigation implementing unmanned aerial vehicles (UAVs)

• US 10,275,834 B1
• Filed: 07/26/2018
• Issued: 04/30/2019
• 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:
  US16/045,851
• Time in Patent Office: 278 Days
• Field of Search: 705 40
• 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: B64U 2201/102 adapted for flying in formations
• CPC Class Codes: B64U 2201/104 using satellite radio beacon positioning systems, e.g. GPS
• 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 insured asset and the area surrounding an insured asset, such as with the policyholder or insured'"'"'s permission and collect data related to the insured asset, such as images, video, audio, weather conditions, thermal signatures, wood and soil samples, etc., and transmit this data to a computing device. The computing device may be associated with and/or utilized by an insurance provider to perform insurance-related tasks, such as processing the data to determine an amount of risk associated with the insured asset. If the amount of risk has increased, the computing device may provide a recommendation to a mobile device of the policyholder on how to reduce the risk such that corrective action may be taken. Insurance discounts may be provided based upon following recommendations that mitigate risk.

Claims

1. A computer-implemented method of mitigating potential loss using drone data, the method comprising:

instructing, by one or more unmanned aerial vehicles, one or more sensors communicatively coupled to the one or more unmanned aerial vehicles to capture first drone data at a first date, including;

navigating to an area surrounding an insured asset;

collecting samples of data;

analyzing the sample data; and

storing the sample data as the first drone data;

wherein the one or more sensors include at least one of a soil sample extractor, a wood sample extractor, a spectrometer, or a volumetric moisture content sensor, and wherein the first drone data corresponds to an asset insured by an insurance provider via an insurance policy;

analyzing, by one or more processors, the first drone data corresponding to the insured asset to determine an amount of risk associated with the insured asset;

providing, by the one or more processors, a recommendation to a policyholder on how to reduce the amount of risk to the insured asset;

receiving, at the one or more processors, second drone data captured by the one or more sensors of the one or more unmanned aerial vehicles, wherein the second drone data corresponds to the insured asset and the second drone data is captured at a second date within a predetermined amount of time from the first date; and

updating, by the one or more processors, insurance policy data for the insurance policy based upon whether the policyholder complies with the provided recommendation according to the second drone data to facilitate providing insurance cost savings to risk averse policyholders.

2. The computer-implemented method of claim 1, wherein when the policyholder does not comply with the provided recommendation, updating insurance policy data for the insurance policy includes increasing, by the one or more processors, an insurance premium upon renewal of the insurance policy based upon the amount of risk associated with the insured asset.

3. The computer-implemented method of claim 1, wherein when the policyholder complies with the provided recommendation, updating insurance policy data for the insurance policy includes maintaining, by the one or more processors, a same insurance premium upon renewal of the insurance policy.

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

comparing, by the one or more processors, the second drone data to the first drone data; and

determining, by the one or more processors, whether the policyholder complies with the provided recommendation based upon the comparison.

5. The computer-implemented method of claim 4, wherein the insured asset is a home, the first drone data includes images of vegetation within a predetermined distance of the home, and the amount of risk corresponds to a risk of fire based upon the distance of the vegetation to the home;

wherein providing a recommendation to a policyholder on how to reduce the amount of risk includes providing a recommendation to remove at least a portion of the vegetation that is within the predetermined distance of the home;

wherein receiving second drone data includes directing the one or more unmanned aerial vehicles to capture images of the vegetation within the predetermined distance of the home at the second date; and

wherein the insurance policy data is updated based upon whether the portion of vegetation is removed as determined based upon the comparison of the second drone data to the first drone data.

6. The computer-implemented method of claim 4, wherein the insured asset is a home, the first drone data includes a soil sample of soil surrounding the home having a soil moisture content above a predetermined threshold moisture content level, and the amount of risk corresponds to a risk of sewer or drain backup based upon the soil moisture content level;

and

wherein providing a recommendation to a policyholder on how to reduce the amount of risk includes providing a recommendation to install a sump pump above a predetermined threshold size, type, capacity, or redundancy to mitigate the risk of sewer or drain backup.

7. The computer-implemented method of claim 4, wherein the insured asset is a home, the first drone data includes a wood and a soil sample of a tree surrounding the home, and the amount of risk corresponds to a risk of the tree falling based upon at least one of:

(i) a number and size of dead sections of the tree, (ii) a degree of root damage, (iii) a number of dead branches, or (iv) an age of the tree;

wherein providing a recommendation to a policyholder on how to reduce the amount of risk includes providing a recommendation to remove or repair the tree;

wherein receiving second drone data includes directing the one or more unmanned aerial vehicles to capture images of the tree at the second date; and

wherein the insurance policy data is updated based upon whether the tree has been removed or repaired by the second date.

8. The computer-implemented method of claim 1, wherein the policyholder complies with the provided recommendation when the risk is reduced by more than a predetermined threshold amount, wherein the recommendation indicates or recommends that (i) snow should be removed from a roof of an insured home, or (ii) a backup generator should be installed to mitigate risk and receive a discount.

9. The computer-implemented method of claim 1, wherein the recommendation includes one or more corrective actions to take and the policyholder complies with the provided recommendation when the policyholder carries out more than a predetermined threshold number of the one or more corrective actions.

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

transmitting, by the one or more processors, the insurance policy including the updated insurance policy data to a mobile computing device of the policyholder upon renewal of the insurance policy; and

receiving, at the one or more processors from the mobile computing device of the policyholder, an indication of whether the policyholder accepts the renewed insurance policy.

11. A system of mitigating potential loss using 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, or a volumetric moisture content sensor, the one or more unmanned aerial vehicles configured to capture first drone data at a first date by instructing the one or more sensors to collect the first drone data, including;

navigate to an area surrounding an insured asset;

collect samples of data;

analyze the sample data; and

store the sample data as the first drone data,

wherein the first drone data corresponds to the insured asset insured by an insurance provider via an insurance policy;

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;

analyze the first drone data corresponding to the insured asset to determine an amount of risk associated with the insured asset when compared to a previously determined amount of risk;

provide, via the communication network, a recommendation to a policyholder on how to reduce the amount of risk to the insured asset;

receive, via the communication network, second drone data captured by the one or more sensors for the one or more unmanned aerial vehicles, wherein the second drone data corresponds to the insured asset and the second drone data is captured at a second date within a predetermined amount of time from the first date; and

update insurance policy data for the insurance policy based upon whether the policyholder complies with the provided recommendation according to the second drone data to facilitate providing insurance cost savings to risk averse policyholders.

12. The system of claim 11, wherein when the policyholder does not comply with the provided recommendation, to update insurance policy data for the insurance policy the instructions cause the system to increase an insurance premium upon renewal of the insurance policy based upon the amount of risk associated with the insured asset.

13. The system of claim 11, wherein when the policyholder complies with the provided recommendation, to update insurance policy data for the insurance policy the instructions cause the system to maintain a same insurance premium upon renewal of the insurance policy.

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

compare the second drone data to the first drone data; and

determine whether the policyholder complies with the provided recommendation based upon the comparison.

15. The system of claim 14, wherein the insured asset is a home, the first drone data includes images of vegetation within a predetermined distance of the home, and the amount of risk corresponds to a risk of fire based upon the distance of the vegetation to the home;

wherein to provide a recommendation to a policyholder on how to reduce the amount of risk, the instructions cause the system to provide a recommendation to remove at least a portion of the vegetation that is within the predetermined distance of the home;

wherein to receive second drone data, the instructions cause the system to direct the one or more unmanned aerial vehicles to capture images of the vegetation within the predetermined distance of the home at the second date; and

wherein the insurance policy data is updated based upon whether the portion of vegetation is removed as determined based upon the comparison of the second drone data to the first drone data.

16. The system of claim 14, wherein the insured asset is a home, the first drone data includes a soil sample of soil surrounding the home having a soil moisture content above a predetermined threshold moisture content level, and the amount of risk corresponds to a risk of sewer or drain backup based upon the soil moisture content level;

and

wherein to provide a recommendation to a policyholder on how to reduce the amount of risk, the instructions cause the system to provide a recommendation to install a sump pump above a predetermined threshold size, type, capacity, or redundancy to mitigate the risk of sewer or drain backup.

17. The system of claim 14, wherein the insured asset is a home, the first drone data includes a wood and a soil sample of a tree surrounding the home, and the amount of risk corresponds to a risk of the tree falling based upon at least one of:

(i) a number and size of dead sections of the tree, (ii) a degree of root damage, (iii) a number of dead branches, or (iv) an age of the tree;

wherein to provide a recommendation to a policyholder on how to reduce the amount of risk, the instructions cause the system to provide a recommendation to remove or repair the tree;

wherein to receive second drone data, the instructions cause the system to direct the one or more unmanned aerial vehicles to capture images of the tree at the second date; and

wherein the insurance policy data is updated based upon whether the tree has been removed or repaired by the second date.

18. The system of claim 11, wherein the policyholder complies with the provided recommendation when the risk is reduced by more than a predetermined threshold amount.

19. The system of claim 11, wherein the recommendation includes one or more corrective actions to take and the policyholder complies with the provided recommendation when the policyholder carries out more than a predetermined threshold number of the one or more corrective actions.

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

transmit, via the communication network, the insurance policy including the updated insurance policy data to a mobile computing device of the policyholder upon renewal of the insurance policy; and

receive, via the communication network and from the mobile computing device of the policyholder, an indication of whether the policyholder accepts the renewed insurance policy.