Prosecution Insights
Last updated: October 27, 2026
Application No. 18/622,631

METHOD AND SYSTEM FOR INTELLIGENT TRANSPORT SYSTEM (ITS)

Non-Final OA §102§112
Filed
Mar 29, 2024
Examiner
GLASS, ERICK DAVID
Art Unit
Tech Center
Assignee
Lenovo (United States) Inc.
OA Round
1 (Non-Final)
90%
Grant Probability
Favorable
1-2
OA Rounds
0m
Est. Remaining
97%
With Interview

Examiner Intelligence

Grants 90% — above average
90%
Career Allowance Rate
650 granted / 725 resolved
+29.7% vs TC avg
Moderate +7% lift
Without
With
+7.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 4m
Avg Prosecution
18 currently pending
Career history
746
Total Applications
across all art units

Statute-Specific Performance

§101
1.5%
-38.5% vs TC avg
§103
41.4%
+1.4% vs TC avg
§102
43.0%
+3.0% vs TC avg
§112
12.7%
-27.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 725 resolved cases

Office Action

§102 §112
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 § 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. Claims 1-20 are 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. With respect to claim 1, 11, and 19, it is unclear of how “determining, via the AI model, a route for the elevator car based at least in part on the sensor data, wherein the determined route is a shortest route that satisfies the set of preset parameters”, AI determines shortest route in elevator trip, when floors are set distances apart and two elevator in same building would have the same set distances of travel between bottom and top floors. With respect to claims 2 and 12, it is also unclear of how, “wherein resolving the route planning conflict comprises determining, via the AI model, an updated shortest route having a minimal number of stops based on the set of preset parameters”. 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. Claim(s) 1, 11, and 19 are rejected under 35 U.S.C. 102(a1) as being taught by One (PGPUB 2022/0185625). With respect to claim 1, One teaches a method of an elevator system comprising: receiving, from one or more sensors (fig. 3, 325), sensor data associated with an elevator car (fig. 2, 210); training an artificial intelligence (“AI”) model (paragraph 0061; 322) with a set of preset parameters, archived data from the one or more sensors and corresponding archived data depicting a historical route traveled by the elevator car (paragraph 007-008; improve elevator efficiency and optimizing performance); determining, via the AI model, a route for the elevator car based at least in part on the sensor data (paragraph 0062), wherein the determined route is a shortest route that satisfies the set of preset parameters; and transporting the elevator car according to the determined route (paragraph 0064). With respect to claim 11, One teaches an elevator control system comprising: a processor (paragraph 0056; 3rd sentence); and a non-transitory computer readable storage (paragraph 0035) medium storing code, the code being executable by the processor to perform operations comprising: receiving, from one or more sensors (fig. 3, 325), sensor data associated with an elevator car (fig. 2, 210); training an artificial intelligence (“AI”) model (paragraph 0061; 322) with a set of preset parameters, the sensor data, archived data (paragraph 0064) from the one or more sensors and corresponding archived data depicting a historical route traveled by the elevator car (paragraph 007-008; improve elevator efficiency and optimizing performance); determining, via the AI model, a route for the elevator based at least in part on the sensor data (paragraph 0064), wherein the determined route is a shortest route that satisfies the set of preset parameters; and transporting the elevator car according to the determined route (paragraph 0064). With respect to claim 19, One teaches an elevator system comprising: at least one elevator car (fig. 2, 210); a set of sensors (fig. 3, 325) configured to acquire sensor data (paragraph 0064) associated with the at least one elevator car; and a controller (fig. 3, 321) operative to: train an artificial intelligence (“AI”) model (paragraph 0061; 322) with a set of preset parameters, archived data from the one or more sensors and corresponding archived data depicting a historical route traveled by the at least one elevator car; determine, via the AI model, a route for the elevator car based at least in part on the sensor data, wherein the determined route is a shortest route that satisfies the set of preset parameters (paragraph 007-008; improve elevator efficiency and optimizing performance); and transport the elevator car according to the determined route (paragraph 0064). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to ERICK DAVID GLASS whose telephone number is (571)272-8395. The examiner can normally be reached Mon-Fri_8-5pm. 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, Eduardo Colon-Santana can be reached at 571-272-2060. 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. /ERICK D GLASS/Primary Examiner, Art Unit 2837
Read full office action

Prosecution Timeline

Mar 29, 2024
Application Filed
Oct 05, 2026
Non-Final Rejection mailed — §102, §112 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12767483
GENERATION OF CONTROL SIGNALS
4y 2m to grant Granted Oct 20, 2026
Patent 12753042
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Patent 12753045
A SYSTEM AND A METHOD FOR CONTROLLING SWAY ANGLE OF AN ELEVATOR CABIN
2y 8m to grant Granted Oct 06, 2026
Patent 12753044
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Patent 12738874
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2y 0m to grant Granted Sep 15, 2026
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
90%
Grant Probability
97%
With Interview (+7.0%)
2y 4m (~0m remaining)
Median Time to Grant
Low
PTA Risk
Based on 725 resolved cases by this examiner. Grant probability derived from career allowance rate.

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