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 .
Status of Claims
This action is in reply to non-provisional patent application filed on 3/10/25. Claims 1-20 are pending and examined.
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.
Claims 1, 5-6, 9, 11, 15-16 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over US 20240326633 A1 (Nakanis) in view of US 20240193998 A1 (Elkhoury).
As to claims 1 and 11,
Nakanis teaches,
receive a second image of the vehicle from the charging station (FIG. 1, items 20, 27, para. 17 “The camera 27 is installed in the housing 20 or in the vicinity of the housing 20 and is capable of capturing images of at least a license plate of the electric vehicle”);
identify the vehicle based on the second image (para. 32 “the management module 35 acquires the vehicle number of the electric vehicle V from the image data captured by the camera 27 as vehicle identification information”);
instruct the charging station to initiate a charging session with the vehicle (FIG. 4, item S220, para. 30 “In response to the command signal from the management server 3, the ECU 25 starts the charging of the battery B of the electric vehicle V with the electric power from the electric power converter ”);
process a payment for the charging session based on the payment method (FIG. 4, item S230, para. 30 “settles the charging fee based on the amount of electric power spent on the charging of the battery B”);
notify the user of a status of the charging session (para. 17 “The ECU 25 displays information on the display device 26 to a user of the electric vehicle V parked in a parking space of the quick charging station 10. The information displayed on the display device 26 includes information on use of the charging device 2 and information on payment of a charging fee by a charging authentication card or cashless payment”);
wherein the charging station is configured (para. 14-16 “ECU”) to:
automatically capture the second image, via the one or more cameras, of the vehicle approaching the charging station (para. 17 “The camera 27 … capturing images …”);
communicate the second image to at least one of the one or more servers (para. 23 “the ECU 25 sends the image data captured by camera 27 or the like to the management server 3”);
charge a battery of the vehicle, during the charging session (FIG. 4, item S220, para. 30), in response to instructions received from the server (FIG. 4, item S220, para. 30);
communicate to the server that the charging session has stopped (FIG. 1, items 25, 35, para. 30 “he ECU 25 … stops the charging of the battery B when the SOC of the battery B reaches the predetermined target value (step S220). After the charging of battery B is completed, the management module 35 settles the charging fee based”).
Nakanis does not teach,
extract one or more identifiers from the first image, wherein the identifiers include at least one of the vehicle's make, model, color, and license plate;
associate the extracted one or more identifiers with a payment method.
however, Elkhoury teaches,
extract one or more identifiers from the first image, wherein the identifiers include at least one of the vehicle's make, model, color, and license plate (FIG. 2, items 206, 208, para. 36 “the user aims the imaging device or camera of the device on a vehicle license plate to capture image of the license plate (Step 206). The front-face showing the plate number is scanned or captured by the application using the camera of the electronic device”, para. 39 “Using a conventional technique such as optical character recognition (OCR), the server extracts the license plate number from the received image”);
associate the extracted one or more identifiers with a payment method (FIG. 2, item 210, para. 37 “the user includes payment information (i.e., payor account) in the form of a credit card or any other financial card to link the payment information or payor account with the license plate”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine vehicle identifier based charging session of Nakanis with user device based vehicle identifier verification of Elkhoury because user device based vehicle identifier verification improves vehicle identifier based charging session by enhancing security charging session security through user device aided vehicle identity verification.
Additionally, with respect to claim 1,
Nakanis teaches,
A system for managing electric vehicle charging sessions, the system (FIG. 1, item 1, para. 13 “a vehicle charging system”) comprising:
one or more server computers (FIG. 1, item 3, para. 13 “a management server);
a charging station (FIG. 1, item 2, para. 13 “a charging device”) comprising or in communication with at least one camera (FIG. 1, item 27, para. 17 “a camera”); wherein the one or more server computers are configured (para. 18) to
As to claims 5 and 15, combination of Nanakis and Elkhoury teach all limitations of claims 1 and 10.
Nanakis does not teach,
wherein the mobile application on the user device provides a user interface for capturing the first image and associating the vehicle with a payment method.
however, Elkhoury teaches,
wherein the mobile application on the user device provides a user interface for capturing the first image and associating the vehicle with a payment method (para. 36-37, 39).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine vehicle identifier based charging session of Nakanis with user device based vehicle identifier verification of Elkhoury because user device based vehicle identifier verification improves vehicle identifier based charging session by enhancing security charging session security through user device aided vehicle identity verification.
As to claims 6 and 16, combination of Nanakis and Elkhoury teach all limitations of claims 1, 5 and 10, 15.
Nanakis teaches,
wherein [the mobile application] notifies the user upon conclusion of the charging session, the notification including information about the cost of the charging session and the payment method used (para. 17 “The information displayed on the display device 26 includes information on use of the charging device 2 and information on payment of a charging fee by a charging authentication card or cashless payment.”).
Nanakis does not teach,
the mobile application [notifies …].
however, Elkhoury teaches,
the mobile application (para. 36 “the vehicle license plate payment application in the electronic device”, para. 10 “providing a notification to the user for the deducted amount”) [notifies …].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine vehicle identifier based charging session of Nakanis with user device based vehicle identifier verification of Elkhoury because user device based vehicle identifier verification improves vehicle identifier based charging session by enhancing security charging session security through user device aided vehicle identity verification.
As to claims 9 and 19, combination of Nanakis and Elkhoury teach all limitations of claims 1 and 11.
Nanankis teaches,
wherein the charging station is further configured (para. 14-16) to
monitor activity around the vehicle while it is parked at the charging station using the at least one camera (para. 17 “The camera 27 … capturing images …”),
communicate data related to the monitored activity to the one or more server computers (para. 23 “the ECU 25 sends the image data captured by camera 27 or the like to the management server 3”).
Claims 2-3 and 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Nakanis in view of Elkhoury in further view of US 20190378347 A1 (Gallaway).
As to claims 2 and 12, combination of Nakanis and Elkhoury teach all limitations of claims 1 and 11.
combination of Nakanis and Elkhoury do not teach,
wherein the one or more servers use a machine learning algorithm to identify the vehicle associated with the second image.
however, Gallaway teaches,
wherein the one or more servers use a machine learning algorithm to identify the vehicle associated with the second image (para. 36 “The license plate detection circuitry 210 can execute a neural network (NN) configured to determine whether the license plate 106 is present in the image data”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine vehicle identifier based charging session of Nakanis with user device based vehicle identifier verification of Elkhoury with machine learning based license plate number detection from an image of Gallaway because machine learning based license plate detection from an image improves vehicle identifier based charging session by enhancing license plate number detection from the provided image of the vehicle.
As to claims 3 and 13, combination of Nakanis, Elkhoury and Gallaway teach all limitations of claims 1-2 and 11-12.
combination of Nakanis and Elkhoury do not teach,
wherein the machine learning algorithm is trained to recognize at least one of the make, model, color, and license plate of the vehicle.
however, Gallaway teaches,
wherein the machine learning algorithm is trained to recognize at least one of the make, model, color, and license plate of the vehicle (para. 36 “The license plate detection circuitry 210 can execute a neural network (NN) configured to determine whether the license plate 106 is present in the image data”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine vehicle identifier based charging session of Nakanis with user device based vehicle identifier verification of Elkhoury with machine learning based license plate number detection from an image of Gallaway because machine learning based license plate detection from an image improves vehicle identifier based charging session by enhancing license plate number detection from the provided image of the vehicle.
Claims 4 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Nakanis in view of Elkhoury in view of Gallaway in further view of US 20170237944 A1 (Haas).
As to claims 4 and 14, combination of Nakanis, Elkhoury and Gallaway teach all limitations of claims 1-3 and 11-13.
combination of Nakanis, Elkhoury and Gallaway do not teach,
wherein the machine learning algorithm is further configured to detect at least one of a queue, blockage, or security issue at the charging station.
however, Haas teaches,
wherein the machine learning algorithm is further configured to detect at least one of a queue, blockage, or security issue at the charging station (para. 9 “an electric vehicle charging station including built-in-cameras to allow video and pictures taken by the camera to be transmitted to a server or a mobile phone and stored on the electric vehicle charging station and processed locally as camera or image data for performing various camera functions such as authentication, security monitoring”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine vehicle identifier based charging session of Nakanis with user device based vehicle identifier verification of Elkhoury with machine learning based license plate number detection from an image of Gallaway with security monitoring of Haas because security monitoring improves vehicle identifier based charging session by enhancing security during a charging session.
Claims 7-8 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Nakanis in view of Elkhoury in further view of US 20210129703 A1 (Annampedu).
As to claims 7 and 17, combination of Nanakis and Elkhoury teach all limitations of claims 1 and 11.
combination of Nanakis and Elkhoury do not teach,
the server is further configured to automatically notify an operator of the charging station when a non-electric vehicle is identified at the charging station.
however, Annampedu teaches,
the server is further configured to automatically notify an operator of the charging station when a non-electric vehicle is identified at the charging station (FIG. 11, item 1104, 1110, para. 34 “If decision A from block 1104 is 1 and decision B from block 1106 is 0, then it means that some vehicle (… non-electric) is parked in the said parking space and electric current is not flowing through the charging cable… changes the status light to red (indicating that the parking space is occupied by an ineligible vehicle) and/or sounds an audible alarm and/or alerts parking authority, towing companies and/or law enforcement authority”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine vehicle identifier based charging session of Nakanis with user device based vehicle identifier verification of Elkhoury with ineligible vehicle management of Annampedu because ineligible vehicle management improves vehicle identifier based charging session by freeing up a charging spot for an eligible vehicle.
As to claims 8 and 18, , combination of Nanakis and Elkhoury teach all limitations of claims 1 and 11.
combination of Nanakis and Elkhoury do not teach,
wherein the one or more server computers are further configured to: calculate an idle fee for the vehicle based on a duration of time the vehicle remains parked at the charging station without engaging in the charging process;
communicate the calculated idle fee to the user.
however, Annampedu teaches,
wherein the one or more server computers are further configured to: calculate an idle fee for the vehicle based on a duration of time the vehicle remains parked at the charging station without engaging in the charging process (para. 2 “Some charging stations, like the superchargers established by Tesla Inc., charges a penalty fee if a vehicle manufactured by Tesla is parked for an extended period after the charging is complete”);
communicate the calculated idle fee to the user (para. 2 “Some charging stations, like the superchargers established by Tesla Inc., charges a penalty fee if a vehicle manufactured by Tesla is parked for an extended period after the charging is complete”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine vehicle identifier based charging session of Nakanis with user device based vehicle identifier verification of Elkhoury with ineligible vehicle management of Annampedu because ineligible vehicle management improves vehicle identifier based charging session by freeing up a charging spot for an eligible vehicle.
Claims 10 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Nakanis in view of Elkhoury in further view of US 20250267343 A1 (George).
As to claims 10 and 20, combination of Nakanis and Elkhoury teach all limitations of claims 1, 9 and 11, 19.
Nanakis teaches,
wherein the one or more server computers are further configured (para. 16-17) to
combination of Nanakis and Elkhoury do not teach,
analyze the data related to the monitored activity using artificial intelligence algorithms to detect suspicious activities or incidents involving the vehicle;
generate and send an alert to the user's mobile device when suspicious activities or incidents are detected.
however, George teaches,
analyze the data related to the monitored activity using artificial intelligence algorithms (para. 87 “the system leverages artificial intelligence (AI) algorithms to personalize the method and intensity of alerts ”) to detect suspicious activities or incidents involving the vehicle (para. 50 “a security and alert system for an EV 102 while charging at a charging station… This system utilizes a range of external sensors 116 and internal sensors 118, such as cameras… These sensors detect the presence of persons or objects in proximity to the vehicle”);
generate and send an alert to the user's mobile device when suspicious activities or incidents are detected (para. 50 “the external sensors 116 and internal sensors 118 may actively monitor the surroundings and notify the vehicle processor 120 about potential threats or unusual activities near the vehicle. The haptic feedback 124, audible alerts 126, and visible alerts 128 can provide visual, audible, and haptic warnings inside the cabin”, para. 64 “An alert may also be sent 188 to the personal devices”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine vehicle identifier based charging session of Nakanis with user device based vehicle identifier verification of Elkhoury with proximate suspicious activity warning of George because proximate suspicious activity warning improves vehicle identifier based charging session by increasing security during the charging session.
Conclusion
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/BROCK E TURK/Examiner, Art Unit 3692
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