ATNESH
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 9/11/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
Claim 5 is objected to because of the following informalities: MPEP 2173.05(s) Reference to Figures or Tables states that “Where possible, claims are to be complete in themselves. Incorporation by reference to a specific figure or table “is permitted only in exceptional circumstances where there is no practical way to define the invention in words and where it is more concise to incorporate by reference than duplicating a drawing or table into the claim. Incorporation by reference is a necessity doctrine, not for applicant’s convenience.” Ex parteFressola, 27 USPQ2d 1608, 1609 (Bd. Pat. App. & Inter. 1993)” . Appropriate correction is required.
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, 2, 4, 11, and 14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lee et al (Lee hereinafter (KR 20180124477 “A System And Method For Managing Parking”)
As per claim 1
Lee teaches A parking management system comprising (Description of embodiments: “Referring to FIG. 3, the parking management system according to the embodiment of the present invention includes a photographing module 10, a parking manager 20, and a control unit 30.”) a first image obtaining device configured to recognize a vehicle number at an entry of a parking lot or in the parking lot (Description of embodiments “The photographing module 10 photographs a vehicle entering and exiting a region of interest, and acquires first image information from the entering and exiting vehicle. The first image information may include the vehicle number of the entering and exiting vehicle and the first vehicle identification additional information.”) a second image obtaining device installed in the parking lot (Description of embodiments: “the parking controller 20 may include a camera 21 for acquiring second image information, and a sensing unit 23 for sensing whether the vehicle is parked or departed.”) a computing device configured to communicate with the first image obtaining device or the second image obtaining device (Description of embodiments “ The control unit 30 compares the first image information and the second image information with each other to extract matching information” “The controller 30 is communicably connected to the photographing module 10 and the parking controller 20 to control the photographing module 10 and the parking controller 20.”) wherein the computing device identifies a vehicle considering vehicle information detected by using a re-identification (RE-ID) technology ( Description of embodiments: “Here, the second image information includes the vehicle number of the vehicle parked in the parking area, and second vehicle identification sub information including the shape, shape, and / or color of the vehicle.” Parking controller 20 is in communication with controller 30. Furthermore “the controller 30 can determine the traveling direction of the vehicle based on the change of the image information value of at least one of the shape, the shape, and the hue of the vehicle over time. That is, whether or not the space occupied by the shape of the vehicle in the image information increases or decreases with the lapse of time from the first image information photographed by the photographing module 10, and if the space increases,”) and vehicle information obtained by analyzing an image obtained from at least one of the first and second image obtaining devices, (Description of embodiments “The first and second image information thus stored may be used by the controller 30 to recognize the vehicle number.”) and the RE-ID technology determines whether vehicles are the same by using appearance information of a vehicle included in an image obtained by the first image obtaining device and appearance information of a vehicle included in an image obtained by the second image obtaining device. (Description of embodiments: “ the first vehicle identification additional information includes information on the shape, shape, and / or color of the entering and exiting vehicle.” “ the second image information includes the vehicle number of the vehicle parked in the parking area, and second vehicle identification sub information including the shape, shape, and / or color of the vehicle.” “The control unit 30 compares the first image information and the second image information with each other to extract matching information when a part or all of the car number of the parked vehicle is not recognized from the second image information, Recognizes the vehicle number of the parked vehicle, and manages parking based on the recognized vehicle number.” )
As per claim 2
Lee teaches all claim limitations previously rejected in claim 1’s 102 rejection. See claim 1’s 102 rejection.
Lee teaches wherein the first image obtaining device is an entry camera (Description of embodiments: “the vehicle entering and exiting the predetermined region of interest 11 is photographed through the photographing module 10 (S21)”) and wherein the RE-ID technology detects a type of the vehicle by comparing a vehicle image included in the image obtained by the first image obtaining device with a vehicle image stored in a database (Description of embodiments: “The vehicle license plate 15 and the first vehicle identification additional information obtained as described above are stored in the storage unit 40 described later and utilized as matching information” “The storage unit 40 is connected to the photographing module 10, the controller 30 and the parking controller 20 and stores first and second image information and the like obtained by the photographing module 10 and the camera 21 . The first and second image information thus stored may be used by the controller 30 to recognize the vehicle number.” In regards to “type” Lee states that “the first vehicle identification sub information is matched with the second vehicle identification additional information of the vehicle number recognition target vehicle so that the number of the vehicle parked in the parking area can be identified.” This sub information is “ sub information such as shape, shape and / or color of the vehicle.” All images are stored in the storage unit 40. These stored images are compared with the first image) and determines whether the vehicles are the same by comparing a vehicle image included in the image obtained by the second image obtaining device with the vehicle image included in the image obtained by the first image obtaining device based on the detected type of the vehicle (Description of embodiment “second image information may include a vehicle number of the vehicle parked in the parking area, and second vehicle identification sub information such as shape, shape and / or color of the vehicle. In this case, when the vehicle number of the second image information is not recognized or is partially recognized, the first vehicle identification sub information and the second vehicle identification sub information are matched with each other, Can be identified.”) and the computing device links numbers of the vehicles when it is determined that the vehicles are the same through the RE-ID technology. (Description of embodiments “The control unit 30 compares the first image information and the second image information with each other to extract matching information when a part or all of the car number of the parked vehicle is not recognized from the second image information, Recognizes the vehicle number of the parked vehicle,” “The first and second image information thus stored may be used by the controller 30 to recognize the vehicle number.” “The control unit 30 compares the first image information with the second image information to be matched to extract matching information, and recognizes the vehicle number”)
As per claim 4
Lee teaches all claim limitations previously rejected in claim 1’s 102 rejection. See claim 1’s 102 rejection.
Lee teaches the computing device tracks a vehicle through a tracking function (Description of embodiments: “The first vehicle identification additional information thus obtained can be utilized for reading and tracking the traveling direction of the vehicle through the control unit 30, vehicle matching, and the like.”) wherein the tracking function determines whether a vehicle parks in a parking area or exits from the parking area by comparing location information of the vehicle in previous frame obtained from the second image obtaining device with location information of the vehicle in current frame. (Description of embodiments: “The second image information is set as the matching target only to the vehicle that is heading toward the parking area based on the information on the traveling direction of the vehicle when the vehicle number of the parked vehicle is not recognized from the second image information, The first image information and the second image information may be compared with each other to extract matching information. Based on this, the vehicle number of the parked vehicle can be recognized.”)
As per claim 11
Lee teaches all claim limitations previously rejected in claim 1’s 102 rejection. See claim 1’s 102 rejection.
Lee teaches A parking management system comprising (Description of embodiments: Referring to FIG. 3, the parking management system according to the embodiment of the present invention includes a photographing module 10, a parking manager 20, and a control unit 30.) a first image obtaining device configured to recognize a vehicle number (Description of embodiments “The photographing module 10 photographs a vehicle entering and exiting a region of interest, and acquires first image information from the entering and exiting vehicle. The first image information may include the vehicle number of the entering and exiting vehicle and the first vehicle identification additional information.”) a second image obtaining device (Description of embodiments: “the parking controller 20 may include a camera 21 for acquiring second image information) an identifier (Description of embodiments “the communication unit 25 communicates with a server that integrally manages a plurality of parking managers, a neighboring parking manager, a charge settlement terminal, and / or a user portable terminal” The user portable terminal can be seen as an identifier. Furthermore Lee states that “when the vehicle number of the parking vehicle is recognized from the second image information, parking is managed on the basis of the information of the parking manager…Accordingly, when the vehicle identification number is not recognized from the second image information acquired from the parking management device, the vehicle identification number is recognized by matching the first image information and the second image information” Therefore the parking manager as well can be seen as an identifier.) a computing device configured to communicate with the first image obtaining device or the second image obtaining device (Description of embodiments “ The control unit 30 compares the first image information and the second image information with each other to extract matching information” “The controller 30 is communicably connected to the photographing module 10 and the parking controller 20 to control the photographing module 10 and the parking controller 20.”) wherein the computing device identifies the vehicle by using one or more of vehicle information obtained by analyzing an image obtained by at least one of the image obtaining devices and vehicle information detected by using a re-identification (RE-ID) technology, (Description of embodiments: “ the first vehicle identification additional information includes information on the shape, shape, and / or color of the entering and exiting vehicle.” “ the second image information includes the vehicle number of the vehicle parked in the parking area, and second vehicle identification sub information including the shape, shape, and / or color of the vehicle.” “The control unit 30 compares the first image information and the second image information with each other to extract matching information when a part or all of the car number of the parked vehicle is not recognized from the second image information, Recognizes the vehicle number of the parked vehicle, and manages parking based on the recognized vehicle number.” Description of embodiments “The first and second image information thus stored may be used by the controller 30 to recognize the vehicle number” Description of embodiments: “Here, the second image information includes the vehicle number of the vehicle parked in the parking area, and second vehicle identification sub information including the shape, shape, and / or color of the vehicle.” Parking controller 20 is in communication with controller 30. Furthermore “the controller 30 can determine the traveling direction of the vehicle based on the change of the image information value of at least one of the shape, the shape, and the hue of the vehicle over time. That is, whether or not the space occupied by the shape of the vehicle in the image information increases or decreases with the lapse of time from the first image information photographed by the photographing module 10, and if the space increases, ) the computing device charges for or collects automatically parking fee based on an inputted user’s information when a user of the vehicle inputs the user’s information through recognition of the identifier (Description of embodiments “The parking controller 20 may further include a communication unit 25 for communicating with peripheral devices and a display unit 27 for indicating a parking situation or whether the parking controller 20 is abnormal. The communication unit 25 communicates with a server that integrally manages a plurality of parking managers, a neighboring parking manager, a charge settlement terminal, and / or a user portable terminal. The communication unit 25 is capable of both wired and wireless communication. The controller 30 may be incorporated…the control unit 30 determines whether the vehicle number of the parking vehicle is recognized from the second image information. If the vehicle number of the parked vehicle is recognized …controller 30 performs a parking management mode for parking based on the information of the parking controller 20 (S41). The parking management mode carries out parking and departure time management, billing, account receivable management, and delinquency management.” ) and the RE-ID technology determines whether vehicles are the same by using appearance information of a vehicle included in an image obtained by the first image obtaining device and appearance information of a vehicle included in an image obtained by the second image obtaining device. (Description of embodiments: “ the first vehicle identification additional information includes information on the shape, shape, and / or color of the entering and exiting vehicle.” “ the second image information includes the vehicle number of the vehicle parked in the parking area, and second vehicle identification sub information including the shape, shape, and / or color of the vehicle.” “The control unit 30 compares the first image information and the second image information with each other to extract matching information when a part or all of the car number of the parked vehicle is not recognized from the second image information, Recognizes the vehicle number of the parked vehicle, and manages parking based on the recognized vehicle number.” )
As per claim 14
Claim 14 is the device claim that parallels claim 1 and will be rejected under the same premise.
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 (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 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 3 and 15 is rejected under 35 U.S.C. 103 as being unpatentable over Lee et al (Lee hereinafter KR 20180124477 A) in view of Ratnesh (Ratnesh hereinafter CN 113056743 A “Training Neural Networks For Vehicle Reidentification”)
As per claim 3
Lee teaches all claim limitations previously rejected in claim 1’s 102 rejection. See claim 1’s 102 rejection.
Lee does not teach wherein the RE-ID technology is trained through a deep learning model using a triplet loss which is a loss function, and wherein the RE-ID technology locates close to each other images of the same vehicles in an N (an integer more than 2)-dimensional feature space and locates far apart images of different vehicles in the N-dimensional feature space through the triplet loss when the images including the vehicle are inputted.
Ratnesh teaches wherein the RE-ID technology is trained through a deep learning model using a triplet loss which is a loss function (Figure 3, Contents of the invention: “Embodiments of the present disclosure relate to training deep neural networks (DNN) for vehicle reidentification. The invention claims systems and methods for training DNN to re-identify vehicles or other objects captured at any number of different directions and locations and captured by any number of different cameras.”) wherein the RE-ID technology locates close to each other images of the same vehicles in an N (an integer more than 2)-dimensional feature space (Contents of the Invention: “The invention claims a system and a method for training a neural network for vehicle reidentification….in order to match the appearance of the object, can generate embedded (or referred to as feature vector or signature) of each object… For example, the same object across a plurality of frames may have been determined to be close to each other (e.g., in the threshold distance) of the embedding, and different objects can be further separated “ “128 units (or 256 units in the example or less) of the embedded dimension can be used for some embodiments of the present disclosure,”) locates far apart images of different vehicles in the N-dimensional feature space through the triplet loss when the images including the vehicle are inputted. (Contents of the invention “DNN can output the embedded object in each instance corresponding to the sensor data, and contrast loss can be used across two instances to train the distance between the same object as 0 (or the other value in the threshold distance) and across two instances the two different objects (e.g., The distance between the first object and the second object is trained to be higher than a predefined threshold or margin….three instances of the triplet loss at each training instance using sensor data…each instance describing …different objects, wherein each instance is applied to instantiation of DNN. For example, the first image Ia may be an anchor image representing the first object, the second image In may be a negative image representing the second object, and the third image Ip may be a positive image also representing the first object…Then, a triplet loss function can be used to train the DNN such that the distance between the same objects is less than the distance between different objects.)
Accordingly, a person of ordinary skill in the art, at the time this invention was effectively filed would have found it obvious to modify Lee’s pipeline with Ratnesh’s concept of training the RE-ID technology with a deep learning model that uses a triplet loss function. Lee states that “vehicle number can be unrecognized due to insufficient angle of view on the front surface of the vehicle 1a. Also, when the vehicle 1b stays at a position outside the parking space 5 for a predetermined time, it can be mistaken as a parking vehicle due to sensor recognition.” With that issue disclosed by Lee a person of ordinary skill in the art is aware that angles along with glare and shadow can drastically change between cameras sullying recognition and matching accuracy. A person of ordinary skill in the art is aware that triplet loss focuses on relative relationship of features rather than a pixel per pixel absolute match. Using the triplet loss function incorporated in the RE-ID enables the system to recognize the same cars in different conditions. The fact that the loss function adjusts its parameters until the positive distance is smaller than the negative distance allows for a reduced mismatch, something a person of ordinary skill in the art would see as advantageous in Lee’s pipeline which automates payment downstream.
As per claim 15
Lee teaches all claim limitations previously rejected in claim 14’s 102 rejection. See claim 14’s 102 rejection.
Claim 15 is the device claim that parallels claim 3 and will be rejected under the same premise.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Lee et al (Lee hereinafter KR 20180124477 “A System And Method For Managing Parking”) in view of Su et al (Su hereinafter CN 111009131 A “A High Video Intelligent Parking System Based On Image Identification”)
As per claim 5
Lee teaches all claim limitations previously rejected in claim 4’s 102 rejection. See claim 4’s 102 rejection.
Lee does not teach wherein the tracking function determines whether the vehicle parks in the parking area or exits from the parking area through an intersection over union (IoU) matching, and wherein the IoU matching detects a proportion of a vehicle area detected by an AI model in the sum of the parking area and the vehicle area, and the tracking function determines that the vehicle parks in the parking area when a result of the IoU matching is more than a predefined value and determines that the vehicle exits from the parking area when the result is smaller than the predefined value. [ IoU matching ]
Su teaches wherein the tracking function determines whether the vehicle parks in the parking area or exits from the parking area through an intersection over union (IoU) matching (Description: “detecting the parking state is according to the detection result (the position of the vehicle and the area information) and the virtual parking position information for overlap rate calculation (IOU)”) and wherein the IoU matching detects a proportion of a vehicle area detected by an AI model in the sum of the parking area and the vehicle area (Description: “based on the action target detection algorithm of the convolutional neural network, whether a vehicle is present in the image, detecting the rectangular location area of the vehicle…detecting the parking space state need to rely on vehicle detection result and the virtual space information”) the tracking function determines that the vehicle parks in the parking area when a result of the IoU matching is more than a predefined value (Description; “detecting the parking state is according to the detection result (the position of the vehicle and the area information) and the virtual parking position information for overlap rate calculation (IOU); if the overlap rate exceeds a certain threshold thresh-1, then the stall is occupied” An occupied parking space is a “parked” vehicle.) determines that the vehicle exits from the parking area when the result is smaller than the predefined value (Description: “ if the overlap rate is less than the threshold, it is considered that parking is idle state” If the system detects an idle space from one that was once occupied, the vehicle has effectively exited the parking space.”)
Accordingly, a person of ordinary skill in the art at the time this invention was effectively filed would have found it obvious to modify Lee’s pipeline with Su’s concept of using IoU matching attached to thresholding to determine if a car is parked or if a car has exited. Lee states that “There are various forms such as right angle parking, parallel parking, 60 degree opposite parking, 45 degree opposite parking and cross parking depending on the type of parking line” and that “..in the case of parallel parking, the camera angle of the unmanned parking management system cannot be secured or the car number is blocked by the parked vehicle adjacent to the car, so that the car number cannot be recognized frequently.” A person of ordinary skill in the art understands that Instead of solely relying on a singular point, which can fail if a car parks awkwardly (such as diagonally or bypassing a parking line), the IoU in Su’s methodology measures the degree of overlap between the detected car’s bounding box and the spaces bounding box. Evaluation of the respective bounding boxes along with a threshold allows flagging and classification of a car exiting or entering a parking spot as it fluctuates through the threshold and its limits. The thresholding through IoU circumvents Lee’s issue with odd parking situations that would obstruct car recognition and adds another layer to Lee’s vehicle recognition.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Lee et al (Lee hereinafter KR 20180124477 “A System And Method For Managing Parking”) in view of Yan et al (Yan hereinafter CN 110163107 A “A Video Frame Identification Based On Road Side Parking Behavior Of Method And Device”)
As per claim 6
Lee teaches all claim limitations previously rejected in claim 4’s 102 rejection. See claim 4’s 102 rejection.
Lee does not teach wherein the tracking function determines that the vehicle parks in the parking area or exits from the parking area through whether a center of a vehicle area detected by an AI model locates in the parking area. (Description: “by performing labeling and training to the plurality of vehicle image sample based on deep learning method of a convolutional neural network, to obtain the vehicle training model…said step the vehicle location based on the coordinate information of the parking space, by vehicle training model in the first video frame and the second video detection, comprises: the vehicle in the position detection result with the parking position coordinate comparison, calculating the centroid of vehicle rectangular area computing a centroid of the vehicle in the parking space, information record and the centroid of the vehicle in the parking space in the detection result.)
Yan teaches wherein the tracking function determines that the vehicle parks in the parking area or exits from the parking area through whether a center of a vehicle area detected by an AI model locates in the parking area. (Description: “by performing labeling and training to the plurality of vehicle image sample based on deep learning method of a convolutional neural network, to obtain the vehicle training model…said step the vehicle location based on the coordinate information of the parking space, by vehicle training model in the first video frame and the second video detection, comprises: the vehicle in the position detection result with the parking position coordinate comparison, calculating the centroid of vehicle rectangular area computing a centroid of the vehicle in the parking space, information record and the centroid of the vehicle in the parking space in the detection result.)
Accordingly, a person of ordinary skill in the art at the time this invention was effectively filed would have found it obvious to modify Lee’s pipeline with Yan’s concept of using the car’s centroid to in regards to the parking space to determine vehicle parking behavior i.e. if the vehicle is parked. Lee states that a variety of parking angles can obstruct vehicle recognition. Yan’s vehicle centroid detection and parking determination allows for single, mathematically stable anchor point to check against a specific space's boundaries. A person of ordinary skill in the art knows that this can be used as a backup or auxiliary with a bounding box logic. Using the bounding box to check occupancy can lead to false positives. Random moving car's bounding box might overlap with an empty parking space causing issues. Using a centroid of a vehicle can sidestep this possibility.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Lee et al (Lee hereinafter KR 20180124477 “A System And Method For Managing Parking”) in view of Yonezawa et al (Yonezawa hereinafter JP 2010108240 A “COMPUTER MANAGEMENT SYSTEM FOR PARKING LOT FACILITIES”)
As per claim 12
Lee teaches all claim limitations previously rejected in claim 11’s 102 rejection. See claim 11’s 102 rejection.
Lee teaches the RE-ID technology detects a type of the vehicle by comparing a vehicle image included in the image obtained by the first image obtaining device with a vehicle image stored in a database (Description of embodiments: “The vehicle license plate 15 and the first vehicle identification additional information obtained as described above are stored in the storage unit 40 described later and utilized as matching information” “The storage unit 40 is connected to the photographing module 10, the controller 30 and the parking controller 20 and stores first and second image information and the like obtained by the photographing module 10 and the camera 21 . The first and second image information thus stored may be used by the controller 30 to recognize the vehicle number.” In regards to “type” Lee states that “the first vehicle identification sub information is matched with the second vehicle identification additional information of the vehicle number recognition target vehicle so that the number of the vehicle parked in the parking area can be identified.” This sub information is “ sub information such as shape, shape and / or color of the vehicle.” All images are stored in the storage unit 40. These stored images are compared with the first image) determines whether the vehicles are the same by comparing a vehicle image included in the image obtained by the second image obtaining device with the vehicle image included in the image obtained by the first image obtaining device based on the detected type of the vehicle (Description of embodiment “second image information may include a vehicle number of the vehicle parked in the parking area, and second vehicle identification sub information such as shape, shape and / or color of the vehicle. In this case, when the vehicle number of the second image information is not recognized or is partially recognized, the first vehicle identification sub information and the second vehicle identification sub information are matched with each other, Can be identified.”)
Lee does not teach the identifier is a QR code and wherein the QR code is shown on a floor of a parking area or on a device he camera nor the user’s information includes one or more of a vehicle number, a phone number and account information
Yonezawa teaches the identifier is a QR code and wherein the QR code is shown on a floor of a parking area or on a device (Figure 1) the user’s information includes one or more of a vehicle number, a phone number and account information (Description: “ a two-dimensional barcode such as a QR code in which individual information of the parking space is encoded is printed on the floor or the wall surface of the place where the user parks, and the user carries it. By using a bar code reader such as a telephone, the fact that the space in the parking lot is currently being used is registered in the system according to the present invention, and the subsequent parking time notification service, theft prevention system, and the parking reservation system… or a user registered according to the fourth aspect of the invention, a predetermined WEB site is disclosed, information on the parking lot is provided, and parking is performed by registering in the mail delivery system. It is possible to provide a fee notification service over time, a member discount service, a service linked with a nearby store, and the like…you can also make payments from the member site for various discounts” This disclosure shows that after the QR code is submitted a user is taken to a website, registers an email (mail delivery system based login) . This constitutes “Account information” )
Accordingly, a person of ordinary skill in the art, at the time this invention was effectively filed would have found it obvious to modify Lee’s pipeline with Park’s concept of using a QR code as the identifier having the user information be account information. A person of ordinary skill in the art is aware that using a QR code in a parking lot and having the user submit account details streamlines the process by bypassing a traditional kiosk. It provides contactless payment, digital receipts supports remote time extension, instantly routes user to a web page, supports frictionless payment platforms like Apple pay or Google pay, eliminates hardware cost, and allows for remote management by user, All of this being well known in the art .
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Lee et al (Lee hereinafter KR 20180124477 “A System And Method For Managing Parking”) Balakrishnan in view of et al (Balakrishnan hereinafter US-20150178640-A1)
As per claim 13
Lee teaches all claim limitations previously rejected in claim 11’s 102 rejection. See claim 11’s 102 rejection.
Lee teaches wherein the computing device transmits information related to the parking fee to a server of a manager (Description of embodiments “The parking controller 20 may further include a communication unit 25 for communicating with peripheral devices and a display unit 27 for indicating a parking situation or whether the parking controller 20 is abnormal. The communication unit 25 communicates with a server that integrally manages a plurality of parking managers, a neighboring parking manager, a charge settlement terminal, and / or a user portable terminal…The controller 30 may be incorporated in the parking controller 20)
Lee does not teach wherein the parking fee is automatically paid based on the user’s information through the identifier,
Balakrishnan teaches wherein the parking fee is automatically paid based on the user’s information through the identifier (Paragraph [0065] “The charging can be done either through a pre-registered "Park-&-Leave" account or by fetching the registered owner's details by recognising the vehicle's registration plate from the buffer as described above” Paragraph [0073] “... the "Park-and-leave" embodiment described above, a user registers with a parking resource provider using their registration plate number and enters into contract with the provider for automatic payment of parking. In this case, when a "Park and Leave" registered registration plate is recognised by the citation module, the software in the citation module will automatically discard that transaction and charge that particular transaction to a pre-arranged method of payment”)
Accordingly, a person of ordinary skill in the art, at the time this invention was effectively filed would have found it obvious to modify Lee’s pipeline (which includes the computing device transmitting information related to the parking fee to a server of a manger) with Balakrishnan‘s concept of automatic payment based on the user’s information through the identifier. A person of ordinary skill in the art is aware that automatic payment through the user’s information via the identifier enables a frictionless, ticketless parking experience which gives the user a seamless experience. A person of ordinary skill in the art knows that bottlenecks are eliminated because vehicles are clocked in and out automatically. A person of ordinary skill in the art knows this because it is well known in the art.
Allowable Subject Matter
Claim 7-10 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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Brooks et al US 20200272837 A1. Tang et al CN 110910655 A.
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/SHANE WRENSFORD CODRINGTON/ Examiner, Art Unit 2667
/MATTHEW C BELLA/ Supervisory Patent Examiner, Art Unit 2667
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