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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on April 14, 2026 has been entered.
Response to Arguments
Applicant’s arguments with respect to claims 1-21 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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 1-21 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang Laixin et al. (CN 114286082 A) in view of NIIKURA et al. (US 2019/0369031 A1).
In considering claim 1, Zhang Laixin et al. discloses all the claimed subject matter, note 1) the claimed one or more memories configured to store program code, wherein the program code is for performing an automated verification test of elements of the video camera recording system using at least one artificial intelligence (Al) model to identify potential issues with the elements of the video camera recording system is met by the nonvolatile storage medium which stores computer program codes and/or operating system to be executed by the processor to detect abnormality of a video camera (Figs. 1 and 4, page 1, lines 7-21 and page 3, line 22 to page 4, line 5), 2) the claimed one or more processors, operatively coupled to the one or more memories and configured to run the program code is met by the main processor 250 (Figs. 1 and 4, page 3, line 22 to page 4, line 5 and page 7, line 1 to page 8, line 12), and 3) the claimed a transceiver configured to transmit instructions to the video camera recording system the at least one element of the video camera recording system is met by the detection result which transmits to the display layer (Figs. 1 and 4, page 5, lines 1-27).
However, Zhang Laixin et al. explicitly do not disclose the newly added limitations wherein the at least one Al model is configured to compare input images captured by a video camera to reference images to generate a prediction of a possible issue and a confidence value associated with the prediction and the instructions configured to cause the video camera recording system the at least one element to autonomously perform a corrective action for at least one of the potential issues.
NIIKURA et al. teach that various methods of calculating the contamination degree of the lens on the basis of comparison between information based on an initial image and information based on a post-operation image may be used (Figs. 4A-4B, page 5, paragraph #0064 to paragraph #0065)…. Next, a process of calculating a cleaning timing (that is, a predicted cleaning timing) of the lens of the camera 6, to be performed in the future on the basis of the contamination degree calculated by the contamination degree calculation unit 41… and A configuration in which a confirmation screen for asking the operator whether cleaning is to be performed when the contamination index is decreased remarkably is displayed may be employed, for example, a configuration in which when the contamination index is decreased by a predetermined value or more, a message that “Please press “Restart” when lens cleaning is performed (Figs. 5-7, page 5, paragraph #0067 to page 6, paragraph #0077).
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 comparing, the prediction and an instruction for correction as taught by NIIKURA et al. into Zhang Laixin et al.’s system in order to accurately detecting and correcting the abnormalities in lenses or lens cover of a visual sensor.
In considering claim 2, the claimed wherein the at least one element of the video camera recording system subjected to the automated verification test comprise video cameras, video recorders, and networks connecting the video cameras to the video recorders is met by the automatic detection, real-time alarm and data aggregation of camera anomalies (Fig. 1, page 1, lines 7-21 of Zhang Laixin et al.).
The motivation to combine the references has been discussed in claim 1 above.
In considering claim 3, the claimed wherein the potential issues comprise video camera issues, video recorder issues, and network issues is met by the automatic detection, real-time alarm and data aggregation of camera anomalies (Fig. 2, page 1, lines 7-21 of Zhang Laixin et al.).
The motivation to combine the references has been discussed in claim 1 above.
In considering claim 4, the claimed wherein the video camera issues comprise unintended camera movement, distortion, and blurriness is met by the camera anomalies such as steering, stains, and occlusion (Figs. 2-3, page 1, lines 7-21 and page 6, lines 1-23 of Zhang Laixin et al.).
The motivation to combine the references has been discussed in claim 1 above.
In considering claim 5, the combination of Zhang Laixin et al. and NIIKURA et al. disclose all the limitations of the instant invention as discussed in claims 1-3 above, except for providing the claimed wherein the video recorder issues comprise an incorrect video duration. The capability using of the video recording issues comprise an incorrect video duration is old and well known in the art. Therefore, the Official Notice is taken. It was notoriously well-known in the art before the effective filing date of the claimed invention to incorporate the video recorder issues comprise an incorrect video duration into the combination of Zhang Laixin et al. and NIIKURA et al.’s system in order to detect the duration of camera’s abnormally.
In considering claim 6, the claimed further comprising a graphical user interface having display elements configured to display a video camera health status, a video recorder health status, and a network health status is met by the display layer which displays the result of the camera detection (Figs. 1 and 4, page 5, lines 1-27 and page 7, line 1 to page 8, line 12 of Zhang Laixin et al.).
The motivation to combine the references has been discussed in claim 1 above.
In considering claim 7, the claimed wherein the graphical user interface further has display elements configured to display a confidence value for each of the video camera health status, the video recorder health status, and the network health status is met by the display layer which displays the result of the camera detection (Figs. 1 and 4, page 5, lines 1-27 and page 7, line 1 to page 8, line 12 of Zhang Laixin et al.).
The motivation to combine the references has been discussed in claim 1 above.
In considering claim 8, the claimed wherein the verification test is repeated on a random basis is met by the automatic detection, real-time alarm and data aggregation of camera anomalies in real time 7*24 (Fig. 2, page 1, lines 7-21 of Zhang Laixin et al.).
The motivation to combine the references has been discussed in claim 1 above.
In considering claim 9, the claimed wherein the verification test is repeated on a scheduled basis is met by the automatic detection, real-time alarm and data aggregation of camera anomalies in real time 7*24 (Fig. 2, page 1, lines 7-21 of Zhang Laixin et al.).
The motivation to combine the references has been discussed in claim 1 above.
In considering claim 10, the claimed wherein the AI model comprises pattern-matching between input images and reference images is met by the image matching algorithm of the camera between the current image and the template image (Figs. 2-3, page 2, lines 1-27 and page 6, lines 1-23 of Zhang Laixin et al.).
The motivation to combine the references has been discussed in claim 1 above.
Claims 11-15 are rejected for the same reason as discussed in claims 1-5, respectively.
Claims 16-20 are rejected for the same reason as discussed in claims 6-10, respectively.
In considering claim 21, the claimed wherein the instructions cause the video camera recording system to perform at least one of holding a camera still, resetting a camera position, cleaning a lens of the camera using a self- cleaning operation, re-focusing the camera to overcome blurriness, or replacing a broken camera, a broken recorder, and/or a broken network element is met by the lens abnormality detection system 1 is activated to guide the lens holder 7 of the camera 6 fixed to the robot 5 to the vicinity of the cap-shaped member 11 (Figs. 3-4, page 4, paragraph #0056 to page 5, paragraph #0062 of NIIKURA et al.).
The motivation to combine the references has been discussed in claim 1 above.
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.
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April 29, 2026
/TRANG U TRAN/Primary Examiner, Art Unit 2422
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