Prosecution Insights
Last updated: July 17, 2026
Application No. 18/816,151

COMPUTER VISION METHODS FOR LOSS PREDICTION AND ASSET EVALUATION BASED ON AERIAL IMAGES

Non-Final OA §DP
Filed
Aug 27, 2024
Priority
Apr 01, 2021 — continuation of 12/106,462
Examiner
CHU, RANDOLPH I
Art Unit
Tech Center
Assignee
Allstate Insurance Company
OA Round
1 (Non-Final)
80%
Grant Probability
Favorable
1-2
OA Rounds
1y 1m
Est. Remaining
86%
With Interview

Examiner Intelligence

Grants 80% — above average
80%
Career Allowance Rate
649 granted / 806 resolved
+20.5% vs TC avg
Moderate +6% lift
Without
With
+5.8%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
27 currently pending
Career history
833
Total Applications
across all art units

Statute-Specific Performance

§101
6.7%
-33.3% vs TC avg
§103
68.4%
+28.4% vs TC avg
§102
14.5%
-25.5% vs TC avg
§112
3.8%
-36.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 806 resolved cases

Office Action

§DP
Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . DETAILED ACTION Double Patenting The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp. Claim 1 is are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 12,106,462. Although the claims at issue are not identical, they are not patentably distinct from each other because they are obvious variant. Instant application 1. A computing platform comprising: at least one processor; a communication interface communicatively coupled to the at least one processor; and memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to: receive, from a first data source, historical images comprising aerial images of a plurality of residential properties; receive, from a second data source, historical inspection data indicating historical inspection results corresponding to one or more of the plurality of residential properties; train, using the historical images and the historical inspection data, a roof waiver model, wherein training the roof waiver model configures the roof waiver model to output inspection prediction information directly from an image, and wherein the roof waiver model is a computer vision model; receive, from the first data source, a new image corresponding to a particular residential property; analyze, using the roof waiver model, the new image, wherein analyzing the new image directly results in output of a likelihood of passing inspection; and send, to an enterprise user device, inspection information, based on the likelihood of passing inspection, and one or more commands directing the enterprise user device to display the inspection information, wherein the inspection information indicates whether or not a physical inspection should be performed, and wherein sending the one or more commands directing the enterprise user device to display the inspection information causes the enterprise user device to display the inspection information. 1. A computing platform comprising: at least one processor; a communication interface communicatively coupled to the at least one processor; and memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to: receive, from a first data source, historical images comprising aerial images of a plurality of residential properties; receive, from a second data source, historical inspection data indicating historical inspection results corresponding to one or more of the plurality of residential properties; train a roof waiver model of a neural network computer vision model, using a machine learning engine, the historical images, and the historical inspection data, wherein training the roof waiver model configures the roof waiver model to output inspection prediction information directly from an image using a set of rules, and wherein the neural network computer vision model correlates the historical inspection data with the corresponding historical images and generates a labelled set of training data for training the roof waiver model, and wherein the machine learning engine iteratively refines the roof waiver model in response to new images; receive, from the first data source, a new image corresponding to a particular residential property; analyze, using the roof waiver model, the new image, wherein analyzing the new image directly results in output of a likelihood of passing inspection; update the roof waiver model in response to the new image; and send, to an enterprise user device, inspection information, based on the likelihood of passing inspection, and one or more commands directing the enterprise user device to display the inspection information, wherein the inspection information indicates whether or not a physical inspection should be performed, and wherein sending the one or more commands directing the enterprise user device to display the inspection information causes the enterprise user device to display the inspection information. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to Randolph Chu whose telephone number is 571-270-1145. The examiner can normally be reached on Monday to Thursday from 7:30 am - 5 pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella can be reached on (571) 272-7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). /RANDOLPH I CHU/ Primary Examiner, Art Unit 2667
Read full office action

Prosecution Timeline

Aug 27, 2024
Application Filed
Jun 17, 2026
Non-Final Rejection mailed — §DP (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
80%
Grant Probability
86%
With Interview (+5.8%)
2y 11m (~1y 1m remaining)
Median Time to Grant
Low
PTA Risk
Based on 806 resolved cases by this examiner. Grant probability derived from career allowance rate.

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