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 § 112
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 7-9 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 7 appears creating confusion as recites “perform the edge computation or a smart detection” meaning the first computing component needs only to perform either the edge computation or a smart detection, not both; but later recites “the result of the edge computation and the smart detection” meaning the first computing component requires to perform both the edge computation and the smart detection.
Claims 8-9 are also rejected as depended on claim 7.
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1 and 6 is/are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Pub, No.: US 20220277366 (hereinafter as Shih).
Regarding claim 1, Shih discloses an electric vehicle smart charging system (fig. 1), comprising:
at least one smart charging pile (fig. 2, 200 and [0028]), each comprising:
a charging gun (fig. 2, 216);
a power supply circuit electrically connected to the charging gun and configured
to provide electric power to the charging gun (“output the power to at least one electric vehicle through the charging gun 216” see [0029]);
a camera module configured to capture at least one image associated with a vehicle ([0043]);
and
a signal processing circuit (fig. 2, 218 and [0029]) having at least one recognition model (“control the operations of related software and hardware” see [0029]), the signal processing circuit electrically connected to the power supply circuit and the camera module, configured to use the at least one recognition model to perform an edge computation on the at least one image (“to provide functions of data analysis, processing and calculation” see [0029]) and control the power supply circuit according to a result of the edge computation (fig. 8, S810-S840 and [0043]), and
a cloud management center (fig. 1, 130 and [0029]; fig. 8, S810-S840 and [0043]) in signal connection with the signal processing circuit and configured to update the at least one recognition model (“update various parameters and information required for charging management calculations” see [0028]) of the signal processing circuit according to the result from the signal processing circuit (“the processing unit 218 can obtain the power parameter of a charging operation from the server 130” see [0029] and [0030]).
Regarding claim 6, Shih discloses the electric vehicle smart charging system of claim 1, wherein one of the at least one smart charging pile further comprises a communication unit (fig. 2, 214) electrically connected to the signal processing circuit and in communication connection the cloud management center and configured to transmit the result of the edge computation to the cloud management center (“server receives a first charging request from an electric vehicle charging station “ see [0043]).
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 2-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shih in view of Pub. No.: US 20240020947 (hereinafter as Darade).
Regarding claim 2, Shih discloses the electric vehicle smart charging system of claim 1, but silent wherein the cloud management center has a deep learning model, and the cloud management center is configured to use the deep learning model to train the at least one recognition model of the signal processing circuit according to the result of the edge computation. However, Darade teaches wherein the cloud management center (fig. 1, 26) has a deep learning model (fig. 1, 30), and the cloud management center is configured to use the deep learning model to train the at least one recognition model (fig. 1, 32 or 34) of the signal processing circuit ([0004]) according to the result of the edge computation ([0007). Before the effective filing date of the invention, it would be obvious to a person of ordinary skill in the art to use the system of Shih with the teaching of Darade as known as the machine learning drives innovation by automating repetitive tasks, uncovering hidden patterns in massive datasets, and improving decision-making through predictive analytics, and also scales operations, optimizes business processes, and enable hyper-personalization while operating 24/7 without fatigue.
Regarding claim 3, Shih discloses the electric vehicle smart charging system of claim 1, but silent wherein the camera module is configured to obtain a plurality of images in a continuous process of vehicle movement, the signal processing circuit has a license plate recognition model and a text recognition model, and the signal processing circuit is configured to:
analyze the plurality of images in the continuous process of vehicle movement through the license plate recognition model, and capture a plurality of license plate images;
analyze the plurality of license plate images through the text recognition model to
obtain a plurality of pieces of license plate number information corresponding to the
plurality of license plate images;
obtain a confidence license plate number based on the plurality of pieces of license plate number information; and
determine whether to activate the power supply circuit according to the confidence license plate number.
However, Darade teaches wherein the camera module is configured to obtain a plurality of images in a continuous process of vehicle movement (fig. 2, 51 and [0023]), the signal processing circuit has a license plate recognition model (fig. 1, 32) and a text recognition model (fig. 1, 34), and the signal processing circuit is configured to:
analyze the plurality of images in the continuous process of vehicle movement through the license plate recognition model, and capture a plurality of license plate images (fig. 2, 52 and [0023]);
analyze the plurality of license plate images through the text recognition model to
obtain a plurality of pieces of license plate number information corresponding to the
plurality of license plate images (fig. 2, 54);
obtain a confidence license plate number based on the plurality of pieces of license plate number information (fig. 2, 54 and [0023]); and
determine whether to activate the power supply circuit according to the confidence license plate number (fig. 2, 56 and [0023]). Before the effective filing date of the invention, it would be obvious to a person of ordinary skill in the art to use the system of Shih with the teaching of Darade as known as the machine learning drives innovation by automating repetitive tasks, uncovering hidden patterns in massive datasets, and improving decision-making through predictive analytics, and also scales operations, optimizes business processes, and enable hyper-personalization while operating 24/7 without fatigue.
Regarding claim 4, Shih and Darade disclose the electric vehicle smart charging system of claim 3, Shih further discloses wherein signal processing circuit is further configured to:
obtain an incorrect license plate number based on the plurality of pieces of license plate number information (see [0034] or fig. 8, S810), and
the cloud management center is configured to:
train the at least one recognition model of the signal processing circuit according
to the incorrect license plate number (“server determines whether the vehicle identification data corresponds to the user identification code or the corresponding contract situation… the flow is ended” see [0043] or fig. 8, S830 to No).
Claim 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shih in view of Pub. No.: US 20230202338 (hereinafter as Harris).
Regarding claim 10, Shih discloses the electric vehicle smart charging system of claim 1, but silent wherein the power supply circuit comprises a power expansion unit (Applicant’s specification describes as “power expansion unit may use, but is not limited to, a proprietary or standard connector such as Power over Ethernet (POE) to provide electric power to an external device” see [0029]), and the power expansion unit is configured to provide electric power to an external device. However, Harris teaches wherein the power supply circuit comprises a power expansion unit (fig. 19, CAT PoE), and the power expansion unit is configured to provide electric power to an external device (fig. 19). Before the effective filing date of the invention, it would be obvious to a person of ordinary skill in the art to use the system of Shih with the teaching of Harris as known as Power over Ethernet (PoE) transmits both electrical power and data over a single standard network cable, such as Cat5e or Cat6, to devices like security cameras, VoIP phones, and access points. This eliminates the need for separate power outlets and cabling, lowering infrastructure, labor, and maintenance costs.
Allowable Subject Matter
Claim 5 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Regarding claim 5, the combination or each of the cited references does not disclose nor fairly suggest each and every claimed limitation as the electric vehicle smart charging system of claim 1, wherein the camera module is configured to obtain a plurality of images in a continuous process of vehicle movement, the signal processing circuit has a license plate recognition model, and the signal processing circuit is configured to:
analyze the plurality of images in the continuous process of vehicle movement through the license plate recognition model, and capturing a plurality of license plate images;
acquire a plurality of endpoint coordinates for each of the plurality of license plate
images;
obtain a license plate size from the plurality of endpoint coordinates, and determining a movement status of the vehicle based on changes in the plurality of endpoint coordinates and the license plate size in the continuous process; and
determine whether to activate the power supply circuit according to the movement status.
Interview
Examiner invites the applicant for an interview to clarify/resolve all the issues and discuss the potential allowable subject matter to place the case in condition for allowance.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20220063432 disclsoes “the spotlight source 201 illuminates the area 203 in response to a determination that a user is approaching the EV charging station. For example, using one or more sensors (e.g., sensor(s) 601), such as an optical sensor (e.g., a camera, proximity sensor, ambient light sensor, or the like), of the EV charging station, the charging station determines that a user is within a predefined geographic proximity to the EV charging station. In response to determining that the user is within the predefined geographic proximity, the spotlight source 201 turns on” (fig. 2B and [0027].)
US 20230137349 suggests “the processor 4200 may recognize the license plate and the vehicle number (vehicle identification information) through a license plate recognition module and a text recognition module. The license plate recognition module may recognize a license plate area of a specific vehicle from an image photographed by the camera sensor 4100, and the text recognition module may recognize a text positioned in the license plate area and extract it as data. The license plate and text recognition process may improve recognition accuracy through data learning using machine learning or deep learning Artificial Intelligence (AI) algorithms” (see [0075].)
US 20230343113 teaches “The light sensor can operate at varying frame rates that vary based on the speed of the moving object whose license plate needs to be detected. To adjust the frame rate of the light sensor, the processor can detect, by the detector, a velocity of the moving object. Upon detecting the motion, the processor can activate the light sensor, which can be configured to record the video at an adjustable frame rate. Based on the velocity, the processor can adjust the frame rate associated with the light sensor, where a high velocity causes a first frame rate associated with a camera, where a low velocity causes a second frame rate associated with the camera, and where the first frame rate is higher than the second frame rate. Low velocity can be a velocity up to and including 10 mph. The first frame rate can be 2 frames per second. As the velocity increases, the frame rate can increase in proportion to the velocity. For example, if the velocity reaches 20 mph, the frame rate can be 4 frames per second. The processor can record a video of the moving object at the adjusted frame rate” (see [0080].)
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUY Q PHAN whose telephone number is (571)272-7924. The examiner can normally be reached M-F 9am-5pm.
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, Kiesha Bryant can be reached at (571)272-3606. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HUY Q PHAN/Supervisory Patent Examiner, Art Unit 2858
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