Prosecution Insights
Last updated: July 17, 2026
Application No. 18/597,562

SYSTEMS AND METHODS FOR ANALYZING STRUCTURAL DAMAGE IMAGES USING MACHINE LEARNING

Final Rejection §101§103
Filed
Mar 06, 2024
Priority
Mar 06, 2023 — provisional 63/488,578
Examiner
SAINI, AMANDEEP SINGH
Art Unit
2662
Tech Center
2600 — Communications
Assignee
State Farm Mutual Automobile Insurance Company
OA Round
2 (Final)
90%
Grant Probability
Favorable
3-4
OA Rounds
0m
Est. Remaining
98%
With Interview

Examiner Intelligence

Grants 90% — above average
90%
Career Allowance Rate
541 granted / 603 resolved
+27.7% vs TC avg
Moderate +8% lift
Without
With
+8.4%
Interview Lift
resolved cases with interview
Fast prosecutor
2y 1m
Avg Prosecution
10 currently pending
Career history
614
Total Applications
across all art units

Statute-Specific Performance

§101
5.6%
-34.4% vs TC avg
§103
79.0%
+39.0% vs TC avg
§102
4.7%
-35.3% vs TC avg
§112
6.8%
-33.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 603 resolved cases

Office Action

§101 §103
DETAILED ACTION Response to Arguments 35 USC § 101 With regards to the 35 USC § 101 abstract idea rejection of claim(s) 1-20, applicant argues the claims should not be rejected under 35 USC § 101 because the claims as amended are significantly more than an abstract idea. Applicant’s remarks and amendments have been fully considered and are found convincing. The rejection under 35 USC § 101 with regards to claim(s) 1-20 is withdrawn. 35 USC § 103 With regards to the 35 USC § 103 rejection of claim(s) 1-20, applicant argues the claims as amended are not taught by the immediate prior art and the claim(s) should not be rejected under 35 USC § 103. Applicant’s remarks and amendments have been fully considered and are found convincing, however, upon further search and consideration, the newly discovered prior art document(s), referenced in the updated rejection below, teaches the limitations as claimed. Please see below for full rejection. Accordingly, applicant’s amendments have necessitated the new grounds of rejection set forth and this action is made final. < Remainder of Page Left Intentionally Blank > Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. Claim(s) 1, 2, 7-8, 11-12, 17-18, and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over D3 [US 2022/0318980] Claim 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: [D3, Figure 1-2 and [0014] and [0072]] D3 teaches the trained platform using previously known data (structure and cost information). 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 costs of repair associated with each of the plurality of historical images of structures, the trained structure assessment model configured to output one or more estimated costs of repair based upon an input of photographic data; [D3, Figure 1-2 and [0014] and [0072]] D3 teaches the training of the model using previously known image data (structure and cost information). The computer vision platform trains a model that may directly identify roof repair costs based on historical photographic data.. receive photographic data including one or more images of a structure; [D3, Figure 2C and [0077] D3 receives the image of the roof. in response to receiving the photographic data, input the photographic data to the structure assessment model; [D3, Figure 2C and [0077] D3 input he current image into the trained model. receive an output from the structure assessment model generated based upon the input of the photographic data, wherein the output comprises at least an estimated cost of repairing damage having occurred to the structure; and [D3, Figure 2C and [0059] D3 input he current image into the trained model. Using the analysis for each image, the trained model may identify a likelihood of damage and pricing information directly from the current images. based upon the output, transmit a message to a user computing device associated with the structure that causes display of the estimated cost. [D3, Figure 2C and [0065] D3 teaches sending the damage information to the enterprise user device and/or the client device. D3 provides various example embodiments and it would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to combine the various example embodiment in which the training is complete and then utilized to determine a damage information related to a structure. One skilled in the art would have been motivated to modify the invention to use multiple example embodiments provided in this manner in order to efficiently provide a desired process to analyze structures to determine damage and cost of repair. Therefore one of ordinary skill in the art, would be capable to have combined the elements as claimed by known methods, and that in combination, each element merely performs the same function as it does separately. It is for at least the aforementioned reasons that the Examiner has reached a conclusion of obviousness with respect to claim 1. Claim 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. [D3, [0057-0059]] D3 teaches the computer vision platform is configured to receive the current images. Claim 7. The computing device of claim 1, wherein the historical records further include historical structural data associated with the plurality of historical images. [D3, Figure 1-2 and [0014] and [0072]] D3 teaches the trained platform using previously known data (structure and cost information). Claim 8. The computing device of claim 7, 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. [D3, Abstract] The roof is being analyzed. Claim 11 is rejected for similar reasons as to those described in claim 1. Claim 12 is rejected for similar reasons as to those described in claim 2. Claim 17 is rejected for similar reasons as to those described in claim 7. Claim 18 is rejected for similar reasons as to those described in claim 8. Claim 21 is rejected for similar reasons as to those described in claim 1. < Remainder of Page Left Intentionally Blank > Claim(s) 3-4, 9, 13-14, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over D3 [US 2022/0318980] in view of D1 [US 10580075 B1]. Claim 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. [D1, Fig. 4 and 5(all)] D1 teaches the graphical user interface with instruction on how to submit photos. It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to combine the teachings of D3 in view of D1 wherein D1 provides the submitted images were those that were prompted to be submitted by a user via a GUI. One skilled in the art would have been motivated to modify the device being used in D3 in this manner in order to provide a prompt to the user as done in D1 to provide the images of the structure. Therefore one of ordinary skill in the art, would be capable to have combined the elements as claimed by known methods, and that in combination, each element merely performs the same function as it does separately. It is for at least the aforementioned reasons that the Examiner has reached a conclusion of obviousness with respect to claim 3. Claim 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. [D1, Fig. 3] D1 teaches the determination of photos being acceptable or not and based upon that providing instructions to the user to submit photos. Claim 9. The computing device of claim 1, wherein the processor is further configured to: receive an acceptance of the estimated cost submitted at the user computing device; and in response to the acceptance, transfer a settlement amount determined based upon the estimated cost to an account associated with the structure. [D1, Fig. 3] See determination of estimate, sending of proposal, acceptance, and payout. Claim 13 is rejected for similar reasons as to those described in claim 3. Claim 14 is rejected for similar reasons as to those described in claim 4. Claim 19 is rejected for similar reasons as to those described in claim 9. < Remainder of Page Left Intentionally Blank > Claim(s) 6, 10, 16, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over D3 [US 2022/0318980] in view of D2 [US 11080838 B1]. Claim 6. 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 estimated cost of repairing damage having occurred to the structure; and re-train the trained structure assessment model using the updated historical records. [D2, Column 6, Lines 1-14] D2 teaches the updating of the model’s parameters in a dynamic process. It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to combine the teachings of D3 in view of D2 wherein D2 provides images being analyzed updating the model parameters dynamically. One skilled in the art would have been motivated to modify the device being used in D3 in this manner in order to provide additional training data of D2 to retrain the model. Therefore one of ordinary skill in the art, would be capable to have combined the elements as claimed by known methods, and that in combination, each element merely performs the same function as it does separately. It is for at least the aforementioned reasons that the Examiner has reached a conclusion of obviousness with respect to claim 6. Claim 10. 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. [D2, Column 4, Lines 36-55 and Column 11, Line 25-43] D1 teaches the drone is deployed to fly through the area to obtain data associated with the damage of the property which is in communication of the server. The drone is a automated device receiving instructions. Claim 16 is rejected for similar reasons as to those described in claim 6. Claim 20 is rejected for similar reasons as to those described in claim 10. < Remainder of Page Left Intentionally Blank > Conclusion THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Amandeep Saini whose telephone number is (571)272-3382. The examiner can normally be reached M-F (8AM-4PM). Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /AMANDEEP SAINI/Supervisory Patent Examiner, Art Unit 2662
Read full office action

Prosecution Timeline

Mar 06, 2024
Application Filed
Feb 05, 2026
Non-Final Rejection mailed — §101, §103
May 05, 2026
Response Filed
Jul 07, 2026
Final Rejection mailed — §101, §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12670723
APPARATUS AND METHOD FOR RECOGNIZING AN OBJECT
3y 2m to grant Granted Jun 30, 2026
Patent 12573055
IMAGE PROCESSING APPARATUS
2y 10m to grant Granted Mar 10, 2026
Patent 12499595
METHOD AND SYSTEM OF FLUORESCENCE MOLECULAR TOMOGRAPHY BASED ON WAVELET AND SCHUR DECOMPOSITION
2y 7m to grant Granted Dec 16, 2025
Patent 12462522
IMAGE ANALYSIS MODEL ADJUSTMENT METHOD AND IMAGE ANALYSIS APPARATUS
2y 0m to grant Granted Nov 04, 2025
Patent 12444038
Industrial Defect Recognition Method and System, Computing Device, and Storage Medium
2y 5m to grant Granted Oct 14, 2025
Study what changed to get past this examiner. Based on 5 most recent grants.

Strategy Recommendation AI-generated — please review before filing

Get a prosecution strategy drawn from examiner precedents, rejection analysis, and claim mapping.
Typically takes 5-10 seconds — AI-generated, attorney review required before filing

Prosecution Projections

3-4
Expected OA Rounds
90%
Grant Probability
98%
With Interview (+8.4%)
2y 1m (~0m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 603 resolved cases by this examiner. Grant probability derived from career allowance rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month