Prosecution Insights
Last updated: April 19, 2026
Application No. 18/592,570

SYSTEMS AND METHODS FOR GENERATING A CUSTOMIZED BADGE

Final Rejection §103
Filed
Mar 01, 2024
Examiner
LAM, ELIZA ANNE
Art Unit
3681
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Kpn Innovations LLC
OA Round
4 (Final)
38%
Grant Probability
At Risk
5-6
OA Rounds
4y 6m
To Grant
68%
With Interview

Examiner Intelligence

Grants only 38% of cases
38%
Career Allow Rate
207 granted / 547 resolved
-14.2% vs TC avg
Strong +30% interview lift
Without
With
+30.3%
Interview Lift
resolved cases with interview
Typical timeline
4y 6m
Avg Prosecution
36 currently pending
Career history
583
Total Applications
across all art units

Statute-Specific Performance

§101
27.6%
-12.4% vs TC avg
§103
37.8%
-2.2% vs TC avg
§102
17.6%
-22.4% vs TC avg
§112
14.1%
-25.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 547 resolved cases

Office Action

§103
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 . 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. Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent 9,646,511 to Jerauld in view of U.S. Patent Application Publication 2019/0006040 to Fleming et al. in further view of U.S. Patent 9,378,657 to Nusbaum in further view of U.S. Patent Application Publication 2021/0134434 to Riley et al. As to claims 1 and 11, Jerauld discloses a system for generating a customized badge, wherein the system comprises: at least a processor; and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the processor to: receive cohort data (Jerauld column 3 lines 17-25) ; receive alimentary array data, wherein the alimentary array data comprises food quality standards (Jerauld column 17 lines 23-51 and column 25 lines 4-16 see “social feedback”); generate a cohort digital badge for the alimentary item of at least alimentary array data as a function of the cohort data (Jerauld column 17 lines 23-51); update the cohort digital badge to a user digital badge as a function of the additional data (Jerauld column 25 lines 17-24); display the updated user digital badge (Jerauld column 25 lines 17-24). However, Jerauld does not explicitly teach receive user data, wherein the user data comprises biological extraction data. Fleming discloses receive user data, wherein the user data comprises biological extraction data (Fleming [0047], [0055], and [0008]). It would have been obvious to one of ordinary skill in the art at the time of the effective filing of the invention by applicant to utilize biological extraction data to generate a digital badge as in Fleming in the system of Jerauld to improve the accuracy of the recommendation. However, Fleming and Jerauld do not explicitly teach “wherein the updated user digital badge incorporates color-coded indicators that display adherence of the user to specific dietary guidelines”. Nusbaum discloses wherein the updated user digital badge incorporates color-coded indicators that display adherence of the user to specific dietary guidelines (Nusbaum column 4 lines 45-60). It would have been obvious to one of ordinary skill in the art at the time of the effective filing of the invention by applicant to incorporate adherence characteristics into the display of the digital badge as in Nusbaum into the system of Fleming and Jerauld to better apprise the user of the healthiness of their choices. However, Nusbaum, Fleming and Jerauld do not explicitly teach generating an alimentary display data structure comprising the alimentary array data and an alimentary array event handler, wherein: the alimentary display data structure is configured to cause a display device to display an alimentary array and the user digital badge; and displaying, the alimentary display data structure and the user digital badge through a smartphone touchscreen interface wherein the alimentary array event handler, through a touch input received through the smartphone touchscreen interface, is configured to detect a user interaction on an item of the at least an alimentary array and, as a function of the detection, display a user score associated with the item. Riley discloses generating an alimentary display data structure comprising the alimentary array data and an alimentary array event handler, wherein: the alimentary display data structure is configured to cause a display device to display an alimentary array and the user digital badge (Riley [0008] see display of a food score for the selected food item and displaying of alternate food suggestions); and displaying, the alimentary display data structure and the user digital badge through a smartphone touchscreen interface wherein the alimentary array event handler, through a touch input received through the smartphone touchscreen interface, is configured to detect a user interaction on an item of the at least an alimentary array and, as a function of the detection, display a user score associated with the item (Riley [0013] see smart phone, user selections and functions, and food items with scores). It would have been obvious to one of ordinary skill in the art at the time of the invention to incorporate the smart phone display and interactions of Riley in the system of Nusbaum, Fleming and Jerauld to make the user better apprised of the consequences of their food consumption. As to claims 2 and 12, see the discussion of claim 1, additionally, Jerauld discloses the system wherein displaying the updated user digital badge further comprises: generating a digital menu as a function of the alimentary array; and displaying the updated user digital badge on the digital menu at a display corresponding to the alimentary item (Jerauld column 19 lines 25-62). As to claims 3 and 13, see the discussion of claim 1, additionally, Jerauld discloses the system wherein displaying the updated user digital badge further comprises: scanning a physical menu; identifying a listing on the physical menu corresponding to the alimentary item; generating a combined display of the physical menu and the updated user digital badge, wherein the combined display displays the updated user digital badge at the listing; and displaying the combined display (Jerauld column 19 lines 25-62). As to claims 5 and 15, see the discussion of claim 1, additionally, Jerauld discloses the system wherein updating the cohort digital badge to a user digital badge comprises generating the user digital badge, which comprises selecting a preferred alimentary item as a function of user score data, wherein the preferred alimentary item is selected for having higher user score data compared to another alimentary item (Jerauld column 25 lines 17-24). As to claims 6 and 16, see the discussion of claim 1, additionally, Jerauld discloses the system wherein generating a customized badge further comprises updating the cohort digital badge to the user digital badge as a function of user feedback (Jerauld column 19 lines 25-62). As to claim 7 and 17, see the discussion of claim 1, additionally, Fleming discloses the system wherein the memory comprises instructions further configuring at least a processor to: adjust the user digital badge, wherein adjusting the user digital badge comprises: receiving a digital badge machine-learning model (Fleming [0008] and [0057]-[0059]); training the digital badge machine-learning model using user-specific training data (Fleming [0008] and [0057]-[0059]); and generating the updated user digital badge using the trained digital badge machine- learning model (Fleming [0008] and [0057]-[0059]). As to claim 8 and 18, see the discussion of claim 1, additionally, Fleming discloses the system the system is configured to use a webcrawler to: collect validation data as a function of the at least alimentary array data; and generating the cohort badge as a function of the validation data (Fleming [0061-[0063]). As to claim 9 and 19, see the discussion of claim 1, additionally, Fleming discloses the system wherein the system is further configured to determine cohort nutrient data using a phenotype, wherein generating the cohort digital badge comprises generating the cohort digital badge as a function of the cohort nutrient data (Fleming [0055]). As to claim 10 and 20, see the discussion of claim 1, additionally Riley discloses generating a digital menu as a function of the alimentary array, wherein the digital menu comprises a plurality of food items including names and descriptions; and displaying the user digital badge on the digital menu, located corresponding to the alimentary item using a display device the alimentary array event handler is further configured to detect a user interaction on an item of the at least an alimentary array and, as a function of the detection, display a user score associated with the item (Riley user selections and functions, and food items with scores [0013] see also menu items [0076]). Claim(s) 4 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent 9,646,511 to Jerauld in view of U.S. Patent Application Publication 2019/0006040 to Fleming et al. in further view of U.S. Patent 9,378,657 to Nusbaum in further view of U.S. Patent Application Publication 2021/0134434 to Riley et al. in further view of U.S. Patent Application Publication 2018/0233223 to Solari. As to claims 4 and 14, see the discussion of claim 1, however, Jerauld, Fleming, and Nusbaum do not explicitly teach the system wherein the system is further configured to integrate environmental data into the user digital badge, wherein integrating the environmental data into the user digital badge comprises: training an environmental score machine-learning model using environmental score training data, wherein the environmental score training data comprises a plurality of environmental data correlated to environmental scores; receiving environmental data for the alimentary item; generating an environmental score using the environmental data and the environmental score machine-learning model; and incorporating the environmental score into the cohort digital badge. Solari discloses integrate environmental data into the user digital badge, wherein integrating the environmental data into the user digital badge comprises: training an environmental score machine-learning model using environmental score training data, wherein the environmental score training data comprises a plurality of environmental data correlated to environmental scores (Solari [0261]); receiving environmental data for the alimentary item (Solari [0261]); generating an environmental score using the environmental data and the environmental score machine-learning model (Solari [0261]); and incorporating the environmental score into the cohort digital badge (Solari [0261]). It would have been obvious to one of ordinary skill in the art at the time of the effective filing of the invention by applicant to include an environmental score into nutritional recommendations as in Solari in the system of Jerauld, Fleming, Nusbaum, and Riley to better address a user’s nutritional preferences and needs. Response to Arguments Applicant’s arguments are moot in view of new grounds of rejection. Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 Eliza Lam whose telephone number is (571)270-7052. The examiner can normally be reached Monday-Friday 8-4:30PST. 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. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Peter Choi can be reached on 469-295-9171. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. 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. /ELIZA A LAM/ Primary Examiner, Art Unit 3686
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Prosecution Timeline

Mar 01, 2024
Application Filed
Jun 01, 2024
Non-Final Rejection — §103
Jun 17, 2024
Interview Requested
Jul 01, 2024
Examiner Interview Summary
Jul 01, 2024
Applicant Interview (Telephonic)
Sep 05, 2024
Response Filed
Nov 02, 2024
Final Rejection — §103
Mar 07, 2025
Request for Continued Examination
Mar 12, 2025
Response after Non-Final Action
Mar 13, 2025
Non-Final Rejection — §103
Sep 10, 2025
Interview Requested
Sep 16, 2025
Applicant Interview (Telephonic)
Sep 17, 2025
Response Filed
Sep 18, 2025
Examiner Interview Summary
Jan 05, 2026
Final Rejection — §103 (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

5-6
Expected OA Rounds
38%
Grant Probability
68%
With Interview (+30.3%)
4y 6m
Median Time to Grant
High
PTA Risk
Based on 547 resolved cases by this examiner. Grant probability derived from career allow rate.

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