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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 08/28/2026 has been entered.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-15 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.
The examiner notes that Applicant has neither challenged nor mentioned the subject matter of the OFFICIAL NOTICE in Claims 5, 12. Due to the applicants’ inadequate traversal of the examiner OFFICIAL NOTICE, the subject matter of the OFFICIAL NOTICE is taken to be applicants admitted prior art. See MPEP 2144.03(C) which recites “To adequately traverse such a finding, an applicant must specifically point out the supposed errors in the examiner’s action, which would include stating why the noticed fact is not considered to be common knowledge or well-known in the art” and “If applicant does not traverse the examiner’s assertion of official notice or applicant’s traverse is not adequate, the examiner should clearly indicate in the next Office action that the common knowledge or well-known in the art statement is taken to be admitted prior art because applicant either failed to traverse the examiner’s assertion of official notice or that the traverse was inadequate”. Clearly, Applicant did not state why the subject matter of the OFFICIAL NOTICE was not common knowledge or well known in the art.
The rejections for Claims 5, 12 will be updated to reflect applicants admitted prior art.
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) 1-3, 6-10, 12-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bartschat et al. (US2020/0191122) in view of Wen et al. (CN111232023) and Huh (US2020/0242799).
To claim 1, Bartschat teach a system for monitoring technical installations (paragraphs 0009, 0014), comprising:
symbols (1) that are provided on parts of technical installations to be monitored in a surrounding area (paragraphs 0018-0019, 0022-0023, position markers);
at least one camera (2) that acquires image data of the surrounding area and applies spatial coordinates and a recording point in time thereto (paragraphs 0026, 0028, the times of the acquisition of optical images can thus be coordinated with specific operating parameters of the installation and/or with the occurrence of specific framework conditions… as a result of such a coordination in the capturing of images, images and parameters that are currently captured can be compared with reference data recorded under similar framework conditions);
an image database (4) in which the image data are archived (paragraph 0016, images and parameters detected in previous measurements are stored in a storage device and are retained for comparison);
a symbol library (5) in which a plurality of symbols (1) and rules assigned thereto are stored (paragraphs 0011-0013); and
an object recognition unit (3), which is designed to recognize symbols (1) in the image data and compare these to the symbols (1) stored in the symbol library (4), wherein a spatial coordinate is assigned to a symbol (1) when the symbol (1) is recognized in the image data (Figs. 3-6, object recognition would be an obvious implementation in identifying markers and respective positions for comparison with stored reference),
a comparison of recognized symbols (1) to earlier image data of the surrounding area is carried out (paragraphs 0028, symbol is under broadest reasonable interpretation, as any recognizable framework condition), and
an alarm is triggered when the comparison reveals a change in the rotational state or the visibility of the recognized symbol (1) that violates the rule assigned to the recognized symbol (1) (paragraphs 0017-0018, compare the position, in particular the rotary angle, of the screw in the image with the position in the reference image… If a screw comes loose, it can thus be rotated in the thread for example, which can be easily determined on the basis of the marked position. The rotary angle of the screw can be monitored in the longer term even in the event of small changes, so as to identify trends; paragraph 0052, at the time of comparison, the difference between the captured data and the reference data exceeds a specified threshold, a notification is sent to an operator of the installation; which would be obvious to one of ordinary skill in the art to recognize such change detection as a violation of rule).
But, Bartschat do not expressly disclose wherein the rules pertain the rotational state or the visibility of the symbol (1) and provide information about a state of the technical installation.
In furthering said obviousness, Wen teach a comprehensive intelligent control system for tracking engineering construction and traffic safety management (abstract), wherein monitoring camera can be installed on vehicle (paragraph 0022), which generate reports of production violation and misconduct information caused by incomplete information recording in the production operation process through the statistical analysis module for violations and the statistical module for production task completion (paragraphs 0027, 0040), which corresponds to Bartchat’s screwing state as incomplete production task.
Huh teach a system for monitoring installation of prefabricated parts at a construction site includes retrieving an installation plan for a room which a plurality of parts are installed (abstract, Fig. 2, Figs. 3A-B), wherein symbols that are provided on parts of technical installations to be monitored in a surrounding area (paragraphs 0019, 0032, 0042-0043, 0058-0062, visual indicators); at least one camera that acquires image data of the surrounding area and applies spatial coordinates and a recording point in time thereto (104 of Fig. 1A, paragraphs 0020-0021, 0046, 0050-0051); an image database in which the image data are archived (paragraphs 0042, 0091); a symbol library in which a plurality of symbols and rules assigned thereto are stored, wherein the rules pertain the rotational state or the visibility of the symbol and provide information about a state of the technical installation (214 of Fig. 2, track and analyze installation process; paragraphs 0049-0054, installation graphics operate as an installation guide for a user to install a prefab part, allows a user to align the actual prefab part at the installation location to ensure proper installation of the prefab part; Figs. 3A-B); and an object recognition unit, which is designed to recognize symbols in the image data and compare these to the symbols stored in the symbol library, wherein a spatial coordinate is assigned to a symbol when the symbol is recognized in the image data, a comparison of recognized symbols to earlier image data of the surrounding area is carried out (paragraphs 0042-0043, entire part or a portion of the part is scanned such as by a camera, and the part is recognized based on object recognition, may be performed by a machine learning algorithm by comparison of the image of the part to a stored database of parts or by a machine learning classifier… record and track the prefab parts that have been installed and the current position in the installation order).
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 teaching of Huh into the system of Bartschat and Wen, in order to implement object recognition and analysis.
To claim 10, Bartschat, Wen and Huh teach a method for monitoring technical installations (as explained in response to claim 1 above, wherein both Bartschat and Huh teach saving captured character/symbol in earlier captured images for referencing).
To claim 2, Bartschat, Wen and Huh teach claim 1.
Bartschat teach characterized in that the at least one camera (2) is fixedly installed (paragraph 0022, imaging device can be fixedly mounted).
To claim 3, Bartschat, Wen and Huh teach claim 1.
Bartschat, Wen and Huh teach characterized in that the at least one camera (2) is mobile (Wen, paragraph 0022, monitoring camera can be installed on vehicle).
To claims 6 and 13, Bartschat, Wen and Huh teach claims 1 and 10.
Bartschat, Wen and Huh teach characterized in that the symbols (1) can be distinguished well from the surrounding area as a result of the coloring and reflective properties thereof (Bartschat, paragraphs 0019, 0049, shape markers, colour markers, fluorescent).
To claims 8 and 15, Bartschat, Wen and Huh teach claims 1 and 10.
Bartschat, Wen and Huh teach characterized in that the object recognition unit (3) utilizes a machine learning-based model for recognizing the symbols (1) in the image data (Huh, paragraph 0158).
To claim 9, Bartschat, Wen and Huh teach claim 1.
Bartschat, Wen and Huh teach characterized in that the image database (4), the symbol library (5) and the object recognition unit (3) are parts of a processor (9) that is connected via a network to the at least one camera (2) (Huh, Fig. 8).
To claim 12, Bartschat, Wen and Huh teach claim 10.
Bartschat, Wen and Huh teach characterized in that the step of preparing the image data (S2) additionally comprises a preprocessing and a filtering of the image data (despite lack of disclosure, but preprocessing and filtering are well-known techniques in preprocessing and manipulating raw image data into a usable, consistent format to enhance computer vision model performance, as applicant admitted prior art).
Claim(s) 4-5, 7, 11, 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bartschat et al. (US2020/0191122) in view of Wen et al. (CN111232023), Huh (US2020/0242799) and Glaser et al. (US2018/0014382).
To claims 4 and 11, Bartschat, Wen and Huh teach claims 1 and 10.
Bartschat, Wen and Huh teach characterized in that the at least one camera (2) comprises a device for position determination (6), a device for determining the recording angle (7), and a device for distance measurement (8) so as to determine the spatial coordinates of the image data (obvious in Huh, paragraphs 0028, 0040-0041).
Glaser teach at least one camera comprises a device for position determination, a device for determining the recording angle, and a device for distance measurement so as to determine the spatial coordinates of the image data (paragraphs 0072, 0087, 0113, 0115, 0139), which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Bartschat, Wen and Huh, in order to further implementation of spatial analysis.
To claim 5, Bartschat, Wen, Huh and Glaser teach claim 4.
Bartschat, Wen, Huh and Glaser teach characterized in that the distance measurement (8) is carried out by a laser range finder or by setting a focus of the at least one camera (Glaser, paragraph 0139, distance estimation; measuring distance by laser range finder or by setting a focus of the camera is well-known technique in the art, which would have been obvious to one of ordinary skill in the art to incorporate for distance estimation, as applicant admitted prior art).
To claims 7 and 14, Bartschat, Wen and Huh teach claims 1 and 10.
Bartschat, Wen, Huh and Glaser teach characterized in that the symbol library assigns rules to symbols (1) which relate a plurality of symbols (1) to one another (Glaser, paragraphs 0089-0093, 0196, 0203, association).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZHIYU LU whose telephone number is (571)272-2837. The examiner can normally be reached Weekdays: 8:30AM - 5:00PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Stephen R Koziol can be reached at (408) 918-7630. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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ZHIYU . LU
Primary Examiner
Art Unit 2669
/ZHIYU LU/Primary Examiner, Art Unit 2665 September 4, 2026
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