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
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Whiting et al. (US20220398684A1, hereinafter referred to as “Whiting”).
Regarding claim 1, Whiting teaches a gas analysis system comprising: at least one gas detection sensor and a controller component, wherein the controller component is configured to: obtain image data of a target area, wherein the image data comprises a series of image frames, wherein a first portion of the series of image frames are indicative of a gas plume (met by IR camera (105); further met by visible-light camera; further met by IR or visible-light camera configured to observe a plume of gas; further met by transmit image data as streaming data, such as streaming video data collected and transmitted in real-time or near real-time). This is read in (Paragraph [0029]).
PNG
media_image1.png
258
509
media_image1.png
Greyscale
PNG
media_image2.png
126
506
media_image2.png
Greyscale
Whiting further teaches to generate, by applying the image data to a gas plume impact model, gas plume impact data (met by frame sequence prediction model generating plume analysis data based on processing multiple sequential image frames). This is read in (Paragraph [0033]).
PNG
media_image3.png
117
507
media_image3.png
Greyscale
PNG
media_image4.png
536
510
media_image4.png
Greyscale
Whiting further teaches to generate refined gas quantity data based at least in part on the gas plume impact data (met by based on predicting the plume analysis data, determining the presence of a leak as well as estimating the size of the leak; further met by segmenting out gas leak plumes with different leak sizing). This is read in (Paragraph [0073]).
PNG
media_image5.png
722
513
media_image5.png
Greyscale
Whiting further teaches to initiate performance of one or more responsive actions based at least in part on the refined gas quantity data (met by plume analysis can be used to generate alerts or notifications). This is read in (Paragraph [0059]).
PNG
media_image6.png
623
511
media_image6.png
Greyscale
Regarding claim 2, Whiting further teaches wherein the target area is associated with an asset (met by the image data can be associated with a plume of gas that may be emitted from an industrial asset in an oil and gas production environment, or any other gas processing and distribution environment). This is read in (Paragraph [0064]).
PNG
media_image7.png
536
505
media_image7.png
Greyscale
Regarding claim 3, Whiting as read in the analysis of claim 2, incorporated herein, also meets wherein the asset is a processing plant by teaching the asset being an industrial asset in an oil and gas production environment.
Regarding claim 4, Whiting as read in the analysis of claim 1, incorporated herein, at (Paragraph [0033]) meets wherein the controller component is further configured to: perform a moving average operation on the refined gas quantity data by teaching generating plume analysis data based on processing multiple sequential image frames. See also (Paragraph [0059]) in the same analysis of claim 1 which recites delineating the observed and predicted spatial characteristics of the plume for a sequence of image frames as a function of time.
Regarding claim 5, Whiting further teaches wherein a second portion of the series of image frames are not indicative of the gas plume (met by image data which may or may not be observing an actual plume of gas is received; further met by plume analysis data is generated if a plume indeed exists in the data). This is read in (Paragraph [0026]).
PNG
media_image8.png
649
512
media_image8.png
Greyscale
Regarding claim 6, Whiting as previously read in the analysis of claim 1, incorporated herein, enables one to identify a first image frame in the second portion of the series of image frames, wherein the first image frame is immediately preceded in the series of image frames by a second image frame in the first portion of the series of image frames by virtue of the prior art’s ability to analyze an image frame sequence (also referred to as streaming video data). Further, to generate zero hit count data based at least in part on the first image frame being immediately preceded by the second image frame in the series of image frames is enabled by the analysis of claim 5, incorporated herein, since the prior art is shown to be capable of generating data in response to the occurrence of a gas plume if a plume indeed exists and therefore would not generate data in the absence of a gas plume.
Regarding claim 7, the claim is substantially identical to claim 6, the analysis of which is incorporated herein, except that a first image frame of the sequence is now followed by a second image frame as opposed to being preceded by a second image frame. The order of the two image frames in the sequence does not affect the prior art’s ability to still function appropriately based on the presence or lack of a plume of gas, regardless of whether the second frame precedes or follows the first frame.
Regarding claim 8, Whiting as read in the analysis of claim 1, incorporated herein, in (Paragraph [0033]) meets wherein generating the refined gas quantity data comprises: generating, by applying the gas plume impact data to raw gas quantity data, a first portion of the refined gas quantity data (met by the frame sequence prediction data (125) can include plume prediction masks generated for a sequence of image frames).
Regarding claim 9, Whiting as read in the analysis of claim 1, incorporated herein, in (Paragraph [0033]) meets wherein the raw gas quantity data is generated by applying the image data to a gas quantity determination machine learning model (met by the frame sequence prediction model (120) can include a network or algorithm that has been generated as a result of the model training).
Regarding claim 10, the limitation of the claim is enabled by the prior art’s ability to delineate the observed and predicted spatial characteristics of the plume for a sequence of image frames as a function of time, as read in the analysis of claim 4, incorporated herein (Paragraph [0059]). This enables the prior art to generate data as a function of time, or in other words, interpolate the data pertaining to the plume for a sequence of images over the course of multiple frames (which may span a first portion and a second portion of the refined gas quantity data).
Regarding claim 11, the claim is substantially identical to claim 1, the analysis of which is incorporated herein.
Regarding claim 12, the claim is substantially identical to claims 2 and 3, the analyses of which are incorporated herein.
Regarding claim 13, the claim is substantially identical to claim 4, the analysis of which is incorporated herein.
Regarding claim 14, the claim is substantially identical to claim 5, the analysis of which is incorporated herein.
Regarding claim 15, the claim is substantially identical to claim 6, the analysis of which is incorporated herein.
Regarding claim 16, the claim is substantially identical to claim 7, the analysis of which is incorporated herein.
Regarding claim 17, the claim is substantially identical to claim 8, the analysis of which is incorporated herein.
Regarding claim 18, the claim is substantially identical to claim 9, the analysis of which is incorporated herein.
Regarding claim 19, the claim is substantially identical to claim 10, the analysis of which is incorporated herein.
Regarding claim 20, the claim is substantially identical to claim 1, the analysis of which is incorporated herein.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW JAMES BODNARK whose telephone number is (703)756-5378. The examiner can normally be reached 8a-5p.
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, Vu Le can be reached at (571) 272-7332. 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.
/MATTHEW JAMES BODNARK/Examiner, Art Unit 2668
/VU LE/Supervisory Patent Examiner, Art Unit 2668
Prosecution Insights