Systems and methods for analyzing structural damage images using machine learning

1 . A computing device for analyzing images using machine learning tools to identify and categorize changes in a state of a structure, the computing device comprising at least one memory and at least one processor in communication with the at least one memory, the at least one processor configured to:

train, via machine learning, a structure assessment model using historical records including (i) historical photographic data including a plurality of historical images of structures, and (ii) one or more historical values associated with each of the plurality of historical images of structures, the one or more historical values associated with one or more parametric trigger events, the trained structure assessment model configured to output one or more values associated with the one or more parametric trigger events based upon an input of photographic data;

receive photographic data including one or more images of a structure;

in response to receiving the photographic data, input the photographic data into the trained structure assessment model;

receive an output from the structure assessment model generated based upon the input of the photographic data, wherein the output comprises at least a first value associated with a parametric trigger event of the one or more parametric trigger events;

determine, based upon the first value, that the parametric trigger event has been satisfied; and

based upon the determination, transmit a message to a user computing device associated with the structure that causes display of an indicator that the parametric trigger event has been satisfied.

2 . The computing device of claim 1 , wherein the at least one processor is further programmed to receive the photographic data from the user computing device.

3 . The computing device of claim 2 , wherein the at least one processor is further configured to cause the user computing device to display a graphical user interface (GUI) prompting a user to submit the one or more images of the structure.

4 . The computing device of claim 3 , wherein the at least one processor is further configured to:

in response to receiving the photographic data, determine that one or more additional images are necessary for the structure assessment model to satisfy a threshold confidence score; and

cause the user computing device to prompt within the GUI the user to submit the one or more additional images of the structure.

5 . The computing device of claim 1 , wherein the at least one processor is further configured to:

update the historical records to updated historical records comprising a new historical record, the new historical record comprising the received photographic data and the determined first value associated with the structure; and

re-train the trained structure assessment model using the updated historical records.

6 . The computing device of claim 1 , wherein the historical records further include historical structural data associated with the plurality of historical images.

7 . The computing device of claim 6 , wherein the historical structural data includes at least one of the following: roof material, roof age, shingle type, roof slant angle, age of roof, total area of a roof, and roof occlusion.

8 . The computing device of claim 1 , wherein the processor is further configured to:

receive an acceptance of a payout amount associated with the parametric trigger event submitted at the user computing device; and

in response to the acceptance, transfer the payout amount to an account associated with the structure.

9 . The computing device of claim 1 , wherein the processor is further configured to generate a flight plan for a drone, the flight plan causing the drone to capture the one or more images of the structure.

10 . A computer-implemented method for analyzing images using machine learning tools to identify and categorize changes in a state of a structure, the computer-implemented method performed by a server computing device including at least one memory and at least one processor in communication with the at least one memory, the computer-implemented method comprising:

training, via machine learning by the server computing device, a structure assessment model using historical records including (i) historical photographic data including a plurality of historical images of structures, and (ii) one or more historical values associated with each of the plurality of historical images of structures, the one or more historical values associated with one or more parametric trigger events, the trained structure assessment model configured to output one or more values associated with the one or more parametric trigger events based upon an input of photographic data;

receiving, by the server computing device, photographic data including one or more images of a structure;

in response to receiving the photographic data, inputting, by the server computing device, the photographic data into the trained structure assessment model;

receiving, by the server computing device, an output from the structure assessment model generated based upon the input of the photographic data, wherein the output comprises at least a first value associated with a parametric trigger event of the one or more parametric trigger events;

determining, by the server computing device, based upon the first value, that the parametric trigger event has been satisfied; and

based upon the determination, transmitting, by the server computing device, a message to a user computing device associated with the structure that causes display of an indicator that the parametric trigger event has been satisfied.

11 . The computer-implemented method of claim 10 , further comprising receiving, by the server computing device, the photographic data from the user computing device.

12 . The computer-implemented method of claim 11 , further comprising causing, by the server computing device, the user computing device to display a graphical user interface (GUI) prompting a user to submit the one or more images of the structure.

13 . The computer-implemented method of claim 12 , further comprising:

in response to receiving the photographic data, determining, by the server computing device, that one or more additional images are necessary for the structure assessment model to satisfy a threshold confidence score; and

causing, by the server computing device, the user computing device to prompt within the GUI the user to submit the one or more additional images of the structure.

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

updating, by the server computing device the historical records to updated historical records comprising a new historical record, the new historical record comprising the received photographic data and the determined first value associated with the structure; and

re-training, by the server computing device, the structure assessment model using the updated historical records.

15 . The computer-implemented method of claim 10 , wherein the historical records further include historical structural data associated with the plurality of historical images.

16 . The computer-implemented method claim 15 , wherein the historical structural data includes at least one of the following: roof material, roof age, shingle type, roof slant angle, age of roof, total area of a roof, and roof occlusion.

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

receiving, by the server computing device, an acceptance of a payout amount associated with the parametric trigger event submitted at the user computing device; and

in response to the acceptance, transfer the payout amount to an account associated with the structure.

18 . The computer-implemented method of claim 10 , further comprising generating, by the server computing device, a flight plan for a drone, the flight plan causing the drone to capture the one or more images of the structure.

19 . At least one non-transitory computer-readable storage media having computer-executable instructions embodied thereon for analyzing images using machine learning tools to identify and categorize changes in a state of a structure, wherein when executed by a server computing device including at least one memory and at least one processor in communication with the at least one memory, the computer-executable instructions cause the at least one processor to:

train, via machine learning, a structure assessment model using historical records including (i) historical photographic data including a plurality of historical images of structures, and (ii) one or more historical values associated with each of the plurality of historical images of structures, the one or more historical values associated with one or more parametric trigger events, the trained structure assessment model configured to output one or more values associated with the one or more parametric trigger events based upon an input of photographic data;

receive photographic data including one or more images of a structure;

in response to receiving the photographic data, input the photographic data into the trained structure assessment model;

receive an output from the structure assessment model generated based upon the input of the photographic data, wherein the output comprises at least a first value associated with a parametric trigger event of the one or more parametric trigger events;

determine, based upon the first value, that the parametric trigger event has been satisfied; and

based upon the determination, transmit a message to a user computing device associated with the structure that causes display of an indicator that the parametric trigger event has been satisfied.