Prosecution Insights
Last updated: April 19, 2026
Application No. 19/014,575

CAMERA OPERATION VERIFICATION SYSTEM AND METHOD

Non-Final OA §102§103
Filed
Jan 09, 2025
Examiner
TRAN, TRANG U
Art Unit
2422
Tech Center
2400 — Computer Networks
Assignee
Tyco Fire & Security GmbH
OA Round
1 (Non-Final)
79%
Grant Probability
Favorable
1-2
OA Rounds
2y 10m
To Grant
94%
With Interview

Examiner Intelligence

Grants 79% — above average
79%
Career Allow Rate
719 granted / 915 resolved
+20.6% vs TC avg
Strong +16% interview lift
Without
With
+15.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
20 currently pending
Career history
935
Total Applications
across all art units

Statute-Specific Performance

§101
6.2%
-33.8% vs TC avg
§103
45.9%
+5.9% vs TC avg
§102
35.2%
-4.8% vs TC avg
§112
2.7%
-37.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 915 resolved cases

Office Action

§102 §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 § 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. Claims 1-5 and 11-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipate by Yang Laixin et al. (CN 114286082 A). In considering claim 1, Laixin et al. discloses all the claimed subject matter, note 1) the claimed acquiring security data from one or more security devices is met by the acquired image of the camera to the data layer (Figs. 1-3, page 7, lines 1-24), 2) the claimed assessing security data quality by conducting one or more tests that compare the security data to one or more predetermined thresholds is met by the image matching algorithm of the camera, and the similarity between the current image of the camera and the template image is compared to the preset threshold (Figs. 1-3, page 7, line 1 to page 8, line 26), 3) the claimed and assigning one or more anomaly indicators to security devices if the security data quality fails to meet the one or more predetermined thresholds is met by if the similarity between the current image of the camera and the template image is less than the preset threshold, then Output alarm information, and update the template image after the camera is adjusted correctly (Figs. 1-3, page 7, line 1 to page 8, line 26), and 4) the claimed generating an automated maintenance report for the one or more security devices including the one or more anomaly indicators is met by using the camera anomaly detection system based on visual AI (Artificial Intelligence) technology, it can automatically detect camera anomalies in real time 7*24, output alarm information and statistical data are transmitted to the presentation layer (Figs. 1-3, page 7, line 1 to page 8, line 26). In considering claim 2, the claimed wherein acquiring security data from one or more security devices further comprises integrating a security maintenance system with one or more security systems comprising the one or more security devices is met by using the camera anomaly detection system based on visual AI (Artificial Intelligence) technology (Figs. 1-3, page 7, line 1 to page 8, line 26). In considering claim 3, the claimed wherein the security devices comprise one or more video cameras and the security data comprises one or more video recordings captured by the one or more video cameras is met by the video cameras (page 9, lines 4-27). In considering claim 4, the claimed wherein the one or more predetermined thresholds are predetermined based on video recordings stored in one or more databases is met by the preset threshold (Figs. 1-3, page 7, line 1 to page 8, line 26). In considering claim 5, the claimed wherein conducting one or more tests comprises conducting one or more tests that detect one or more of tampering, lens obstruction, frame clarity, brightness levels, and blur levels is met by detect the camera anomalies includes steering, occlusion and stains (Figs. 1-3, page 7, line 25 to page 8, line 26). Claim 11 is rejected for the same reason as discussed in claim 1 above and further the claimed comprising one or more computer readable memories, and one or more processors is met by the processor and the memory of the electronic device (Fig. 4, page 9, line 28 to page 10, line 7). Claims 12-15 are rejected for the same reason as discussed in claims 2-5, respectively. 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 6-10 and 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over Yang Laixin et al. (CN 114286082 A) in view of NIIKURA et al. (US 2019/0369031 A1). In considering claim 6, Yang Laixin et al. discloses all the claimed subject matter, note 1) the claimed utilizing an artificial intelligence (Al) model to detect one or more anomalies is met by using the camera anomaly detection system based on visual AI (Artificial Intelligence) technology (Figs. 1-3, page 7, line 1 to page 8, line 26). However, Yang Laixin et al. explicitly do not disclose the claimed further comprising: periodically retrieving one or more security data sets from the one or more security devices, and generating one or more predictive maintenance suggestions. NIIKURA et al. teach that the contamination degree determination unit 42 transmits information related to the contamination degree to the cleaning timing prediction unit 43 in order to calculate a cleaning timing to be performed in the future when the contamination degree is equal to or smaller than the threshold (step S12: NO), in step S14, the cleaning timing prediction unit 43 calculates the cleaning timing (that is, a predicted cleaning timing) to be performed in the future and the display device 23 notifies of the content thereof, after that, the flow returns to step S11, this process is repeated automatically every arbitrary period determined in advance by the operator or at a timing based on a manual operation of the operator (Fig. 8, page 6, paragraph #0078- #0082). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the predictive maintenance as taught by NIIKURA et al. into Yang Laixin et al.’s system in order to notify the user to perform maintenance in an appropriate timing. In considering claim 7, the claimed wherein utilizing an AI model to detect anomalies further comprises: training the Al model based on the periodically retrieved security data; classifying the periodically retrieved data; and based on the classifying, detecting the one or more anomalies is met by using the camera anomaly detection system based on visual AI (Artificial Intelligence) technology to detect the camera anomalies includes steering, occlusion and stains (Figs. 1-3, page 7, line 1 to page 8, line 26 of Yang Laixin et al.). The motivation to combine the references has been discussed in claim 6 above. In considering claim 8, the claimed further comprising: triggering one or more notifications if one or more anomalies are detected is met by outputting alarm information and statistical data are transmitted to the presentation layer (Figs. 1-3, page 7, line 1 to page 8, line 26 of Yang Laixin et al.). The motivation to combine the references has been discussed in claim 6 above. In considering claim 9, the claimed wherein the one or more notifications comprise an alarm is met by outputting alarm information and statistical data are transmitted to the presentation layer (Figs. 1-3, page 7, line 1 to page 8, line 26 of Yang Laixin et al.). The motivation to combine the references has been discussed in claim 6 above. In considering claim 10, the claimed further comprising one or more of providing the one or more predictive maintenance suggestions to an authorized user; and performing one or more predictive maintenance actions automatically is met by the cleaning timing prediction unit 43 calculates the cleaning timing (that is, a predicted cleaning timing) to be performed in the future and the display device 23 notifies of the content thereof (Fig. 8, page 6, paragraph #0078- #0082 of NIIKURA et al.). The motivation to combine the references has been discussed in claim 6 above. Claims 16-20 are rejected for the same reason as discussed in claims 6-10, respectively. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Kulshreshtha et al. (US Patent No. 12,316,666 B2) disclose systems and methods for deriving application security signals from application performance data. McLean (US Patent No. 11,522,877 B2) discloses systems and methods for identifying malicious actors or activities. Muddu et al. (US Patent No. 9,516,053 B1) disclose network security threat detection by user/user-entity behavioral analysis. Any inquiry concerning this communication or earlier communications from the examiner should be directed to TRANG U TRAN whose telephone number is (571)272-7358. The examiner can normally be reached M-F 10:00AM- 6:00PM. 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, JOHN W. MILLER can be reached at 571-272-7353. 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. March 11, 2026 /TRANG U TRAN/Primary Examiner, Art Unit 2422
Read full office action

Prosecution Timeline

Jan 09, 2025
Application Filed
Mar 13, 2026
Non-Final Rejection — §102, §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

1-2
Expected OA Rounds
79%
Grant Probability
94%
With Interview (+15.9%)
2y 10m
Median Time to Grant
Low
PTA Risk
Based on 915 resolved cases by this examiner. Grant probability derived from career allow rate.

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