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 .
DETAILED ACTION
This Office Action is in response to the application 18/830,983 filed on 09/11/2024.
Claims 1 have been examined and are pending in this application.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/03/2025. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Double Patenting
A rejection based on double patenting of the “same invention” type finds its support in the language of 35 U.S.C. 101 which states that “whoever invents or discovers any new and useful process... may obtain a patent therefor...” (Emphasis added). Thus, the term “same invention,” in this context, means an invention drawn to identical subject matter. See Miller v. Eagle Mfg. Co., 151 U.S. 186 (1894); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Ockert, 245 F.2d 467, 114 USPQ 330 (CCPA 1957).
A statutory type (35 U.S.C. 101) double patenting rejection can be overcome by canceling or amending the claims that are directed to the same invention so they are no longer coextensive in scope. The filing of a terminal disclaimer cannot overcome a double patenting rejection based upon 35 U.S.C. 101.
Claim 1 is/are rejected under 35 U.S.C. 101 as claiming the same invention as that of claim 1 of prior U.S. Patent No. 11,674,839 B1. This is a statutory double patenting rejection.
Claim Rejections - 35 USC § 103
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 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 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 1 are rejected under 35 U.S.C. 103 as being unpatentable over Shapiro et al. (US 2021/0407121 A1) in view of Meads et al. (US 2015/0030304 A1).
Regarding claim 1, Shapiro discloses: “a system comprising:
at least one processor [see para: 0017; one or more processors]; and
memory, the memory containing instructions to control any number of the at least one processor [see para: 0090; a processor will receive instructions and data from a read-only memory or a random-access memory or both] to:
receive, from a first infrared image capture device with a first field of view [see para: 0060; The camera can be configured to acquire infrared images, visible images (e.g., grayscale, color, etc.), or combination thereof], a first image including a first fluid storage tank storing a first fluid [see para: 0065; Schematic diagrams representing baseline 2D images of sites 200, 204 including respective containers 204 (e.g., cylindrical containers) are shown in FIG. 2A and FIG. 2B], the image including a plurality of image intensities [see para: 0072; In an embodiment, the occluded portion 506 can have a visually different appearance (e.g., color, intensity, etc.) than the non-occluded portion 510], a first image intensity associated with a first temperature of a first portion of the first fluid storage tank with a first internal surface that is in contact with the first fluid stored therein and a second image intensity associated with a second temperature of a second portion of the first fluid storage tank with a second internal surface that is not in contact with the first fluid [see para: 0005; the temperature of the container material not in contact with the liquid (e.g., approximately above the level of the liquid) can be different from the temperature of the container material in contact with the liquid (e.g., approximately at or below the level of the liquid). Such temperature differences can be distinguished as brightness differences (e.g., lighter/darker) by infrared cameras. The relative lightness and darkness of the outer surface of the container above and below the level of the liquid can depend upon the specific conditions under which the 2D image is acquired (e.g., the composition of the container material, the composition of the liquid, the time of day of 2D image acquisition, ambient temperature, weather conditions, etc.)];
generate feature maps from the first image by applying at least a first convolutional neural network [see para: 0064; an annotation technique can be employed to characterize respective containers. In general, image annotation, also referred to as tagging, is a process that can be employed in machine learning or deep learning (e.g., artificial neural networks) to label or classify features of interest within the baseline 2D images];
slide a first window across the feature maps to obtain a plurality of anchor shapes using a region proposal network [see para: 0065; In operation 110, a total volume of respective containers can be determined. As an example, assuming that the containers are cylindrical, cylindrical contours can be fit to respective containers. With knowledge of the position of the containers and the position at which the baseline 2D images are acquired, the height and diameter of the containers can be determined. From these dimensions, total volume of respective containers can be calculated. In another example, the total volume can be directly input (e.g., from manufacturer specifications, other independent measurements, etc.) Schematic diagrams representing baseline 2D images of sites 200, 204 including respective containers 204 (e.g., cylindrical containers) are shown in FIG. 2A and FIG. 2B. Further illustrated on respective containers 204 is a line indicating the level of the liquid and dividing the containers between a liquid holding portion 205 and an empty or non-liquid holding portion 207. It can be appreciated that, while determining the volume of cylindrically shaped containers is discussed above, the volume of containers having other geometric shapes can be similarly determined];
determine if each anchor shape of the plurality of anchor shapes contains an object to generate a plurality of regions of interest [see para: 0014; Additional image processing techniques can be used in IR domain to determine “darker” portion of the containers indicating the colder liquid in the container. However, it can be understood that, in alternative embodiments, the “brighter” portion of the containers can indicate the wanner liquid within the container. The height of this dark region along the container's vertical boundary in the 2D image can give the ratio of liquid height to total height of the container (fullness in vertical (Z) direction). Knowing the total container volume (e.g., from any one or more of the site/container data, calculating the total container volume from an on-boarded 3D model and container fitting, obtaining the total container volume from prior knowledge such as a manufacturer specification, etc.), and the geometry of the container, the measured liquid volume can be calculated from the vertical boundary in the 2D image];
extract feature maps from each region of interest [see para: 0012; Data from sensor kit can be a plurality of images, e.g., a video or a collection of individual images, viewing the containers from different viewpoints. The containers can be on-boarded and a more extensive visual data collection can be run to extract a 3D baseline representation (model) from the plurality of images using photogrammetry techniques (e.g., at least one of visible and IR modality). Images acquired at human-visible light wavelengths can be represented in a variety of ways];
classify objects in each region of interest [see para: 0017; The method can additionally include classifying, by the one or more processors, a portion of the selected container containing the liquid. The method can further include determining, by the one or more processors, the volume of liquid held within the container based upon the classified portion];
identify first stored fluid using the objects based on classifications [see para: 0017; The method can additionally include classifying, by the one or more processors, a portion of the selected container containing the liquid. The method can further include determining, by the one or more processors, the volume of liquid held within the container based upon the classified portion] and segmentation masks [see para: 0011; By analyzing 2D monitoring images of the containers acquired after generation of the 3D model from baseline 2D images, intensity differences can be characterized and used to determine the level of liquid within the container];
determine first volume of stored fluid based on the first stored fluid [see para: 0011; By analyzing 2D monitoring images of the containers acquired after generation of the 3D model from baseline 2D images, intensity differences can be characterized and used to determine the level of liquid within the container]; and
Shapiro does not explicitly disclose: “provide first volume to a digital device for display”.
However, Meads, from the same or similar field of endeavor teaches: “provide first volume to a digital device for display [see para: 0042; As shown in FIG. 7, the user interface displays information 230 associated with the particular indicia that the system found during the scan. In this case, the system scanned the QR code of Tank 1 and retrieved relevant data about the tank from a remote database that was being continuously populated with data from a computer associated with Tank 1 (and/or various measurement instruments associated with Tank 1). Such data includes the tank's pressure, fill level, and pH. The display may also include one or more graphical representations of information, such as the graph shown in FIG. 7. The system displays the data on the user interface for the user to see].
It would have been obvious to the person of ordinary skill in the art before the effective filing date of the claimed invention to modify determining the level (e.g., volume) of liquid within containers system disclosed by Shapiro to add the teachings of Meads as above, in order to provide a means for displaying liquid level of the containers, the captured images can be analyzed using image processing technique and determine the level of the containers and output to the handheld display or computer system to inform the users [Meads see para: 0042].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Fauveau et al (US 7,334,451 A1).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Masum Billah whose telephone number is (571)270-0701. The examiner can normally be reached Mon - Friday 9 - 5 PM ET.
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/MASUM BILLAH/Primary Patent Examiner, Art Unit 2486