DETAILED ACTION
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 .
Notice to Applicants
This action is in response to the Restriction Election filed on 09/09/2025.
Claims 1-20 are pending.
Priority
The Application claims priority to Provisional Application 63/363,227 with filing date 04/19/2022, which is acknowledged.
Information Disclosure Statement
The Information Disclosure Statement (IDS) submitted on 07/26/2023 has been fully considered by the examiner.
Restriction/Election
The Examiner thanks Applicant for their careful consideration of the Restriction Requirement mailed on 07/09/2025.
Applicant’s election without traverse of Group I (Claims 1-8) in the reply filed on 09/09/2025 is acknowledged.
Claims 9-20 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 09/09/2025.
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 § 2146 et seq. 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 filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual 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/apply/applying-online/eterminal-disclaimer.
Claim 1 is rejected on the grounds of nonstatutory double patenting as being unpatentable over claim 20 of U.S. Patent no. US-11989787-B2 (hereinafter referred to as the ‘787 Patent).
Although the claims at issue are not identical, they are not patentably distinct from each other because of the following reasons.
Regarding claim 1, the claim language of present claim 1 is anticipated by claim 20 of the ‘787 patent, as described below:
Row #
Present Application 18/303,115
Claim 1
Reference Patent
US 11,989,787 B2
Claim 20
Analysis
1
A method, comprising:
A user device, comprising:
Claim 20 is a device claim instead of a method claim, but the method of claim 1 reads on the operations of claim 20 below.
2
capturing images of a vehicle;
a camera configured to capture a series of images of a vehicle;
Row 2 of claim 1 is broader than and reads on row 2 of claim 20, as both require capturing multiple images of a vehicle.
3
performing, by one or more machine learning models, a visual inspection of the vehicle based on the images;
and a processor configured to perform operations comprising: receiving a series of images of the vehicle from one or more viewpoints;
Row 3 of claim 1 is broader than and reads on rows 3-4 of claim 20, as claim 20 more narrowly recites a vehicle inspection based on the images.
4
determining, by the one or more machine learning models, inspection results based on the visual inspection;
classifying, for each of the images, one or more parts of the vehicle captured in the image using a web-based application comprising a first artificial intelligence (AI) model for identifying the parts of the vehicle,
Row 4 of claim 1 is broader than and reads on rows 6-7 of claim 20, as claim 20 more narrowly recites inspection results as damage extents and repair estimates.
5
and determining, by the one or more machine learning models, a confidence value for the inspection results.
wherein the first AI model generates confidence levels for identifying parts of the vehicle;
Row 5 of claim 1 is broader than and reads on row 8 of claim 20, which more narrowly recites a confidence level for the damage estimates.
6
classifying, for each of the images, an extent of damage of the classified one or more parts of the vehicle captured in the images using the web-based application comprising a second AI model for identifying the damage of the vehicle;
7
and generating an estimate to repair the damage of the one or more parts of the vehicle;
8
generating a confidence level for the damage estimate;
9
and prompting a user of the user device to capture additional images when the confidence level for the damage estimate is below a predetermined threshold.
Claim 7 is rejected on the grounds of nonstatutory double patenting as being unpatentable over claim 20 of U.S. Patent no. US-11989787-B2 (hereinafter referred to as the ‘787 Patent) in view of Haitao et al. (U.S. Publ. 2018/0293806 A1).
Regarding claim 7, claim 20 of the ‘787 Patent discloses wherein the inspection results include an identification of a damaged part (see row 6 of claim 20 above), a repair or replace determination for the damaged part (see row 7 of claim 20 above) and a confidence value for the inspection results related to the damaged part (see row 8 of claim 20 above).
Claim 20 of the ‘787 Patent fails to disclose displaying the inspection results determined by the one or more machine learning models.
Pertaining to the same field of endeavor, Haitao discloses displaying the inspection results determined by the one or more machine learning models (see paragraph 0120, where a maintenance plan is displayed to the user; paragraphs 0055-0057 specify that the maintenance plan can include damaged components, damage types, and repair/replace recommendations).
The ‘787 Patent and Haitao are considered analogous art, as they are both directed to automated vehicle inspection models. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Haitao into the ‘787 Patent because displaying the maintenance plan allows for the user to analyze and approve the proposed remedial actions (see Haitao paragraphs 0120-0123).
Claim Rejections – 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 4 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 4, the relative term “expert user” is not adequately defined in the specification. Paragraph 0075 provides an example of an expert user as an adjuster, but this is not a limiting definition. The specification does not provide a definitive standard for measuring who is or is not an “expert user”, and thus subjective judgement is required to determine what types of individuals or occupations would constitute an “expert” user.
The examiner suggests amending claim 4 to read either “routing the inspection results to a user interface of an insurance adjuster” or “routing the inspection results to a user interface of another user” (emphasis added).
Claim Rejections – 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract ideas without significantly more.
Analysis for claim 1 is provided in the following. Claim 1 is reproduced in the following (annotation added):
A method, comprising:
capturing images of a vehicle;
performing, by one or more machine learning models, a visual inspection of the vehicle based on the images;
determining, by the one or more machine learning models, inspection results based on the visual inspection;
and determining, by the one or more machine learning models, a confidence value for the inspection results.
Step 1: Does the claim belong to one of the statutory categories? Claim 1 is directed to a process, which is a statutory category of invention (YES).
Step 2A Prong One: Does the claim recite a judicial exception? Part c recites performing a visual inspection of the vehicle based on images. Part d recites determining inspection results based on the visual inspection. Part e recites determining a confidence value for the inspection results. Each of parts c, d, and e are directed to mental processes including observations, evaluations, judgments, or opinions that can be practically performed in the human mind. Other than “by the one or more machine learning models”, the claim places no limitations on how the visual inspections, inspection results, and confidence values are determined, thus a human performing these mentally in any way would sufficiently anticipate the claim. Note that the courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (see MPEP 2106.04(a)(2).III) (YES).
Step 2A Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? Part a is merely a preamble reciting a method. Part b recites mere data gathering (NO).
Step 2B: Does the claim as a whole amount to significantly more than the recited exception? The claim as a whole recites data gathering, followed by using a computer to broadly perform three mental processes that can be practically performed in the human mind (NO). Claim 1 is not eligible.
Claims 2 and 6 recite outputting data obtained from performing mental processes on a computer. Claims 2 and 6 are not eligible.
Claim 3 recites performing at least one additional evaluation, when the confidence value is less than a predetermined threshold, both of which are mental processes that can be practically performed in the human mind. Claim 3 is not eligible.
Claim 4 recites routing the inspection results to a user interface of an expert user, which as recited is regarded as mere data output. Claim 4 is not eligible.
Claim 5 recites that the at least one further evaluation comprises a statistical correlation for damaged parts of the vehicle that is not based on the images, which is directed to mathematical calculations. Claim 5 is not eligible.
Claim 7 recites displaying the inspection results, including identifications of damaged parts, repair/replace determinations, and confidence values, which is regarded as mere data output of the results of performing a mental process on a computer. Claim 7 is not eligible.
Claim 8 recites receiving instructions for capturing the images from one or more machine learning models, which as claimed is regarded as instructions for mere data gathering and is not indicative of integration into a practical application. Claim 8 is not eligible.
Claim Rejections – 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim 1 is rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Haitao et al. (U.S. Publ. US-2018/0293806-A1).
Regarding claim 1, Haitao discloses a method (see figure 1) comprising:
capturing images of a vehicle (see figure 1, step S1 and paragraphs 0028-0029, which specify that multiple photos can be input);
performing, by one or more machine learning models, a visual inspection of the vehicle based on the images (see figure 1, steps S2-S3 and paragraphs 0031 and 0038, where identification models analyze the images to identify vehicle parts and damage);
determining, by the one or more machine learning models, inspection results based on the visual inspection (see figure 1, step S4 and paragraphs 0049-0050, where damage locations and types are concluded);
and determining, by the one or more machine learning models, a confidence value for the inspection results (see paragraphs 0044 and 0047, where confidence levels representing the degree of authenticity of damage types are also output).
Claim Rejections – 35 USC § 103
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.
Claims 2-3 are rejected under 35 U.S.C. 103 as being unpatentable over Haitao et al. (U.S. Publ. US-2018/0293806-A1) in view of Price et al. (U.S. Patent US-10332245-B1).
Regarding claim 2, Haitao fails to disclose the limitations of claim 2.
Pertaining to the same field of endeavor, Price discloses when the confidence value exceeds a predetermined threshold, outputting the inspection results (see figure 7 and column 14, line 58 to column 15, line 5, where the identity of an object/vehicle is only concluded when at least one confidence value is above a threshold).
Haitao and Price are considered analogous art, as they are both directed to vehicle inspection models. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Price into Haitao because doing so allows for determining a more accurate object identification (see Price column 8, lines 33-53).
Regarding claim 3, Haitao fails to disclose the limitations of claim 3.
Pertaining to the same field of endeavor, Price discloses when the confidence value is less than a predetermined threshold, performing at least one additional evaluation of the vehicle (see figure 7 and column 14, line 58 to column 15, line 5, where if no assigned confidence value is above a threshold, the method of figure 7 is used to perform additional inspections 724, 734, 744, 754 until at least one confidence value is above the threshold).
Haitao and Price are considered analogous art, as they are both directed to vehicle inspection models. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Price into Haitao because doing so allows for determining a more accurate object identification (see Price column 8, lines 33-53).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Haitao et al. (U.S. Publ. US-2018/0293806-A1) in view of Price et al. (U.S. Patent US-10332245-B1), and further in view of Behrens et al. (U.S. Patent US-11928737-B1).
Regarding claim 4, Haitao in view of Price fails to disclose the limitations of claim 4.
Pertaining to the same field of endeavor, Behrens discloses wherein the at least one additional evaluation comprises routing the inspection results to a user interface of an expert user (see column 7, lines 16-23 and claim 3, where if claim evaluation confidence is below a threshold, the claim report is routed to a claim adjuster for review).
Haitao and Behrens are considered analogous art, as they are both directed to vehicle inspection models. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Behrens into Haitao and Price because doing so enables claim adjusters to focus on more difficult decision making (see Behrens column 2, lines 30-35).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Haitao et al. (U.S. Publ. US-2018/0293806-A1) in view of Price et al. (U.S. Patent US-10332245-B1), and further in view of Lambert et al. (U.S. Publ. US-2020/0349370-A1).
Regarding claim 5, Haitao in view of Price fails to disclose the limitations of claim 5.
Pertaining to the same field of endeavor, Lambert discloses wherein the at least one further evaluation comprises a statistical correlation for damaged parts of the vehicle, wherein the statistical correlation is not based on the images (see paragraphs 0044 and 0137, where statistical analysis is used to infer internal damage in the vehicle based on the identified external damage types).
Haitao and Lambert are considered analogous art, as they are both directed to vehicle inspection models. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Lambert into Haitao and Price because doing so allows for predicting damage not directly observable in the images, based on large quantities of statistical data (see Lambert paragraph 0137).
Claims 6-7 are rejected under 35 U.S.C. 103 as being unpatentable over Haitao et al. (U.S. Publ. US-2018/0293806-A1) in view of Wei et al. (U.S. Patent US-10783643-B1).
Regarding claim 6, Haitao fails to disclose the limitations of claim 6.
Pertaining to the same field of endeavor, Wei discloses displaying representations of damage or potential damage of the vehicle keyed to the images (see figure 7 and column 16, lines 59-67, where prediction boxes for damage areas are displayed with damage types and confidence levels in the upper-left corners).
Haitao and Wei are considered analogous art, as they are both directed to vehicle inspection models. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Wei into Haitao because one of ordinary skill in the art would recognize that displaying the model's confidence level would inform the user of how much weight to give the model's prediction of the corresponding damage type.
Regarding claim 7, Haitao discloses displaying the inspection results determined by the one or more machine learning models (see paragraph 0120, where a maintenance plan is displayed to the user), wherein the inspection results include an identification of a damaged part (paragraphs 0055-0056 specify that the maintenance plan includes damaged components and their damage types), a repair or replace determination for the damaged part (paragraph 0057 specifies that the maintenance plan includes damage levels that correspond to replace or repair recommendations)
Haitao fails to disclose and a confidence value for the inspection results related to the damaged part. More specifically, although Zhang calculates confidence values, they do not disclose displaying the confidence values to the user.
Pertaining to the same field of endeavor, Wei discloses and a confidence value for the inspection results related to the damaged part (see figure 7 and column 16, lines 59-67, where prediction boxes for damage areas are displayed with damage types and confidence levels in the upper-left corners).
Haitao and Wei are considered analogous art, as they are both directed to vehicle inspection models. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Wei into Haitao because one of ordinary skill in the art would recognize that displaying the model's confidence level would inform the user of how much weight to give the model's prediction of the corresponding damage type.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Haitao et al. (U.S. Publ. US-2018/0293806-A1) in view of Lambert et al. (U.S. Publ. US-2020/0349370-A1).
Regarding claim 8, Haitao fails to disclose the limitations of claim 8.
Pertaining to the same field of endeavor, Lambert discloses wherein the capturing the images of the vehicle comprises: receiving, from one or more machine learning models, instructions for capturing the images (see figures 5-7 and paragraphs 0057-0058, where a model uses a live view to guide the user to capture the vehicle from certain angles and automatically capture sufficient images).
Haitao and Lambert are considered analogous art, as they are both directed to vehicle inspection models. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have integrated the teachings of Lambert into Haitao because doing so allows for the model to determine if the captured images are suitable for damage assessment or not (see Lambert paragraph 0074).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NICHOLAS JOHN HELCO whose telephone number is (703)756-5539. The examiner can normally be reached on Monday-Friday from 9:00 AM to 5:00 PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella, can be reached at telephone number 571-272-7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NICHOLAS JOHN HELCO/Examiner, Art Unit 2667
/MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667