CTFR 18/917,324 CTFR 95474 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Response to Amendment The amendment filed on 04/24/2026 has been entered, claims 1-20 remain pending in the application. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1, 8, 15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. On January 7, 2019, the USPTO released new examination guidelines setting forth a two-step inquiry for determining whether a claim is directed to non-statutory subject matter. According to the guidelines, a claim is directed to non-statutory subject matter if: STEP 1 : the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or STEP 2 : the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis: STEP 2A (PRONG 1) : Does the claim recite an abstract idea, law of nature, or natural phenomenon? STEP 2A (PRONG 2) : Does the claim recite additional elements that integrate the judicial exception into a practical application? STEP 2B : Does the claim recite additional elements that amount to significantly more than the judicial exception? Using the two-step inquiry, it is clear that claim 1 is directed toward non-statutory subject matter, as shown below: STEP 1 : Do the claims fall within one of the statutory categories ? Yes claims 1, 8, 15 are directed towards a method, system, non transitory readable medium respectively. STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea ? Yes, the claims are directed to an abstract idea . With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas: Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations; Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion). The process in claims 1, 8, 15 is a mental process that can be practicably performed in the human mind, or with the aid of pen and paper and as such is directed toward and abstract idea. The claim consists of determining based on sensor data that a vehicle departs from a charging station within a predetermined time, this is similar to a human determining based on the camera image of a vehicle that left the station quickly that the station is not charging. Notably, the claim does not positively recite any limitations regarding actual determination of the attitude of the vehicle. STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application ? No, the claims do not recite additional elements that integrate the judicial exception into a practical application. With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application: an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field; an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition; an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim; an additional element effects a transformation or reduction of a particular article to a different state or thing; and an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application: an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea; an additional element adds insignificant extra-solution activity to the judicial exception; and An additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use. Claims 1, 8, 15 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. The monitoring and the sending of signal are is recited at a high level of generality and amounts to mere data gathering which is a form of insignificant extra-solution activity. The vehicle, computers, server are at the apply it level technology to apply the abstract idea. The sensors are considered generic linking. Thus, it is clear that the abstract idea is merely implemented on a computer at the “apply it level”, which is indicative of the abstract solution having not been integrated into a practical application. STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception ? No, the claims do not recite additional elements that amount to significantly more than the judicial exception. With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements: adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present. Claims 1,8 do not recite any specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field. The processor and communication device are considered at the apply it level technology. The monitoring and the sending of signal are is recited at a high level of generality and amounts to mere data gathering which is a form of insignificant extra-solution activity. The vehicle, computers, server are at the apply it level technology to apply the abstract idea. The sensors are considered generic linking.. See Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result ‐‐ a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added)). MPEP 2106.05(d)(II) CONCLUSION Thus, since claims 1, 8, : (a) directed toward an abstract idea, (b) does not recite additional elements that integrate the judicial exception into a practical application, and (c) does not recite additional elements that amount to significantly more than the judicial exception, it is clear that the claims are directed towards non-statutory subject matter. Claim 2, 9: the AI is recited with high level of generality such that it amounts to a computer to recite the outcome of the analysis without details of how the output is accomplished. The labeling of the first charging station as unavailable is considered data gathering. Claim 4, 11: determining a charging station is unavailable is part of the abstract idea of claim 1, the notification is post solution data gathering. Claims 5, 12: determining based on sensor data an attempt to charge is similar to a human analyzing camera data to determine a vehicle parked to charge at the charging station. The AI is recited with high level of generality and it amounts to a computer at the apply it level. Claims 6, the operation check is recited with high level of generality and is considered to be data gathering of signals. Claim Rejections - 35 USC § 103 07-20-aia AIA 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, 6, 8, 13, 15, are rejected under 35 U.S.C. 103 as being unpatentable by Raguse (US20250065768) in view of Kinomura (US20190322185) and Terada (US20250170920). Regarding claim 1, Raguse teaches a method comprising: Monitoring, by a server, a first attempt by a vehicle to charge at a first charging station based on first sensor data sensed by hardware sensors located at the first charging station ([0082]-[0101] disclosing the vehicle attempts charging at a first station based on sensor data indicative of an attempt, the sensors including a communication sensor such as Bluetooth sensors to receive the vehicle’s intention to charge at the station. [0096]-[0101] further disclosing the charging station side also detects position of vehicle and position of the charging station to determine relative parameters indicative of a charge processes. See also [0121] disclosing sensors to detect charging attempts) ; identifying, by the server, the first attempt as an unsuccessful attempt based on the vehicle departing the charging station within a threshold time ([0100]-[0102] disclosing a dwelling time less than a threshold indicative of a defective charging station, see at least [0112]-[0116] disclosing a remote server to determine the failure) ; in response to the unsuccessful attempt, triggering monitoring, by the server, of a second attempt by the vehicle to charge at a second charging station based on second sensor data from an additional sensor at the second charging station, wherein the second charging station is located within a threshold distance of the first charging station ([0102]-[0103] and [0126] disclosing testing charging at a second charging station in response to the failed attempt of the first station and that determines if indeed the first primary station is blocked, see the last three lines in [0103] disclosing which can be interpreted as a clear sign that the charging station that was controlled first (primary charging station) was defective, e.g. non-functional. At least [0077] disclosing the secondary charging station is within a radius region thus it is within a threshold distance of the first charging station) ; and while Raguse does not explicitly disclose the server determining the unsuccessful charging, Raguse discloses the use of a server to determine the failure to reduce load on the vehicle, thus it is obvious to one of ordinary skill in the art to substitute the server for determining the failure yielding predictable results in order to save resources on the vehicle as taught by Raguse. Terada and Kinmore further disclose the server to determine failures, thus that combination alternatively teaches the need for server monitoring with motivation given by Raguse to reduce resources of the vehicle computing system. Terada teaches sending a notification to the first charging station related to the successful charge ([0068]-[0069] disclosing the sending of the charging status to the charger management server, i.e., including failed and successful charging, and [0070]-[0100]). The combination of Terada’s method of notifying the charging management server is obvious yielding predictable result in order to stop the charging if the charging is not compatible as taught by Terada [0068]-[0100]. While Terada teaches notifying the management server in this case, it would have been obvious to try to notify the charging station when the charging station manages itself with reasonable expectation of success. Kinomura teaches responsive to a successful charge of the vehicle at the second charging station ([0122] disclosing when the abnormal overheat does not occur in different stations, i.e., the no overheating is indicative of a successful charge at a different charger, in order to confirm that the error is from the specific charging station. At least [0095] disclosing the server based on determining an action to the charging station based on the abnormality). Raguse teaches the verification of failure of the station based on the vehicle going to another station to charge, thus the combination of Kinomura of checking the failure is from the station based on successful charging at another station is obvious yielding predictable results in order to verify the result. Regarding claim 6, Raguse as modified by Kinomura and Terada teaches the method of claim 1, comprising causing the first charging station to perform an operability check of its components of the first charging station based on the first sensor data ([0038] disclosing the testing of the charging station based on the sensor data, see also [0121] disclosing selg testing of the station in response to the server detecting the deviation) . Claims 8 and 15 are rejected for similar reasons as claim 1, see above rejection. Claim 13 is rejected for similar reasons as claim 6. Claims 2, 9, 16 are rejected under 35 U.S.C. 103 as being unpatentable by Raguse (US20250065768) in view of Kinomura (US20190322185) and Terada (US20250170920) and Meroux (US20250346143) and Haupt (US20230158916) and Kim (US20240092210). Regarding claim 2, Raguse as modified by Terada and Kinomura teaches the method of claim 1, Raguse as modified by Terada and Kinomura does not teach comprising determining that the first charging station is unavailable based on an output of an artificial intelligence (AI) model executed on the first sensor data, and labelling the first charging station as unavailable on a map that includes a plurality of charging stations. Meroux teaches comprising determining that the first charging station is unavailable based on execution of an artificial intelligence (AI) model on the first sensor data, ([0027], [0064]-[0067] disclosing the AI model of sensor data that determines the unavailable stations on a map including a plurality of charging stations) . The combination of the teaching of Meroux of determining the first charging station is unavailable based on AI models is obvious yielding predictable results in order to improve and speed up and detect the abnormality more accurately using machine learning thus improving the detection processes. Haupt teaches and labelling the first charging station as unavailable on a map that includes a plurality of charging stations ([0081]-[0083] disclosing the labeling of the first charging station as not available and the selection of another station). The combination of Haupt is obvious yielding predictable results in order to navigate the vehicle to a working charging station thus avoiding further depleting the charge of the vehicle when driven to a non functional charging station. While Haupt does not explicitly state the labeling on the map, Kim teaches the labeling of the stations on the map (Figure 2 disclosing the labeling of errors in each charging station). The combination of Kim is obvious yielding predictable results in order to allow the driver to visually determine the best charging station. Claims 9, 16 are rejected for similar reasons as claim 2, see above rejection. Claims 3, 10, 17 are rejected under 35 U.S.C. 103 as being unpatentable by Raguse (US20250065768) in view of Kinomura (US20190322185) and Terada (US20250170920) and Haupt (US20230158916) Regarding claim 3, Raguse as modified by Kinomura and Terada teaches the method of claim 1, Raguse as modified by Kinomura and Terada does not teach comprises receiving a route from a second vehicle that includes the first charging station, and in response, automatically rerouting the second vehicle to a different charging station that is available. Haupt teaches receiving a route from a second vehicle which includes the first charging station, and in response, automatically rerouting the second vehicle to a different charging station that is available ([0080]-[0085] disclosing a second vehicle is rerouted to another station in response to the unavailable charging station) . The combination of Haupt is obvious yielding predictable results in order to navigate the vehicle to a working charging station thus avoiding further depleting the charge of the vehicle when driven to a non functional charging station. Claims 10, 17 are rejected for similar reasons as claim 3, see above rejection. Claims 4, 11, 18 are rejected under 35 U.S.C. 103 as being unpatentable by Raguse (US20250065768) in view of Kinomura (US20190322185) and Terada (US20250170920) and Meroux (US20250346143) and Solomon (US20150202975). Regarding claim 4, Raguse as modified by Kinomura and Terada teaches the method of claim 1. Raguse as modified by Kinomura and Terada does not teach comprising determining that the first charging station is not available based on the first sensor data, and notifying the second charging station that the vehicle attempted to obtain charge at the first charging station while it was not available, before the second attempt. Meroux teaches determining that the first charging station is not available based on the first sensor data ([0027], [0064]-[0067] disclosing the AI model of sensor data that determines the unavailable stations on a map including a plurality of charging stations) . The combination of the teaching of Meroux of determining the first charging station is unavailable based on AI models is obvious yielding predictable results in order to improve and speed up and detect the abnormality more accurately using machine learning thus improving the detection processes. Solomon teaches and notifying the second charging station that the vehicle attempted to obtain charge at the first charging station while it was not available, before to the second attempt ([0041] disclosing the other station that had a queue prioritizes the vehicle that was not able to charge at another charger, i.e., it is interpreted that the second station is notified since it knew that the vehicle experienced failure at a station). The combination of the teaching of Solomon teaching of obtaining information of a vehicle having failed charging attempt with the teaching of failed charging of Raguse is obvious yielding predictable results in order to prevent the vehicle from being discharged even more and compensating the driver for the long wait. Claims 11, 18 are rejected for similar reasons as claim 4, see above rejection. Claims 5, 12, 19 are rejected under 35 U.S.C. 103 as being unpatentable by Raguse (US20250065768) in view of Kinomura (US20190322185) and Terada (US20250170920) and Choi (US20210101502). Regarding claim 5, Raguse as modified by Kinomura and Terada teaches the method of claim 1, comprising receiving third sensor data from another sensor sensed by further hardware sensors located at a third charging station based on an attempt by an other vehicles to charge at the third charging station, and predicting that the third charging station will be unavailable at a future point in time based on output of an artificial intelligence AI model executed on the third sensor data. Choi teaches receiving third sensor data from an other sensor sensed by further hardware sensors located at a third charging station based on attempts by other vehicles to charge at the third charging station, and predicting that the third charging station will be unavailable at a future point in time based on output of an artificial intelligence AI model executed on the third sensor data ([0009], [0080] disclosing acquiring sensor data of the chargers based on charging of vehicles requested/attempts and using neural network to predict future failure of the charger). the combination of Choi’s teaching of predicting the charger would be unavailable via machine learning is obvious yielding predictable results in order to utilize machine learning to optimize the charging process of the plurality of vehicles and rerouting vehicles before they cause a backup due to a failed charger in the future, see [0009]. Claims 12, 19 are rejected for similar reasons as claim 5, see above rejection. Claims 7, 14, 20 are rejected under 35 U.S.C. 103 as being unpatentable by Raguse (US20250065768) in view of Kinomura (US20190322185) and Terada (US20250170920) and Haupt (US20230158916). Regarding claim 7, Raguse as modified by Kinomura and Terada teaches the method of claim 1, Raguse as modified by Kinomura and Terada does not teach comprising In response to the unsuccessful attempt controlling the vehicle to autonomously maneuver from the first charging station to the second charging station based on the first attempt by the vehicle to charge at the first charging station. In response to the unsuccessful attempt, controlling the vehicle to autonomously maneuver from the first charging station to the second charging station based on the first attempt by the vehicle to charge at the first charging station ([[0080]-[0085] disclosing autonomously rerouted to another station in response to the unavailable charging station) . Raguse teaches the driving of the vehicle to a second station to attempt charging, thus the combination of Haupt is obvious yielding predictable results in order to autonomously navigate the vehicle to a working charging station thus avoiding further depleting the charge of the vehicle when driven to a non functional charging station, the automation of the vehicle to follow the route is an improvement. Claims 14, 20 are rejected for similar reasons as claim 1, see above rejection. Response to Arguments 07-37 AIA Applicant’s arguments filed on 04/24/2026 have been fully considered but they are not persuasive. 101 rejection: with respect to applicant’s arguments regarding the 101 rejection, the monitoring of a second attempt in response to the unsuccessful attempt is considered a mental processes similar to a human determining to monitor the vehicle at another charger to determine if he vehicle charging capability or battery is compromised. The server is merely recited with high level of generality and is considered at the apply it level to apply the mental processes of monitoring the charger at a proximate location to determine if the vehicle is faulty or the charger is faulty. 103 rejection: with respect to applicant’s argument that Raguse does not disclose or suggest “in response to the unsuccessful attempt, triggering monitoring, by the server, of a second attempt by the vehicle to charge at a second charging station based on second sensor data from an additional sensor at the second charging station, wherein the second charging station is located within a threshold distance of the first charging station”, examiner respectfully disagrees for the following reasons: Raguse in at least [0077], [0102]-[0103] and specifically in [0103] disclosing “It can also be detected whether the vehicle to be charged (subsequently) controls an alternative charging station (secondary charging station) in order to test and/or initiate a charging process at this charging station, which can be interpreted as a clear sign that the charging station that was controlled first (primary charging station) was defective”, thus this is interpreted as the monitoring of the secondary is triggered to confirm that the first station was defective or the vehicle was defective, thus is response to the unsuccessful charging of the vehicle at the first station. Conclusion 07-40 AIA Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL . See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The prior art cited in PTO-892 and not mentioned above disclose related devices and methods. US20220144123 disclosing checking if a charger is blocked at location proximate to the first vehicle based on charging data from a second vehicle charging at the charger to reroute the first vehicle based on the second vehicle plugged but there is no charging or simply determining the charger is not available due to the second vehicle charging. US20210404838 disclosing an index value indicating charging failure. US20230158910 disclosing AI to predict charger failure. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMAD O EL SAYAH whose telephone number is (571)270-7734. The examiner can normally be reached on M-Th 6:30-4:30. 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, Ramon Mercado can be reached on (571) 270-5744. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see https://ppair-my.uspto.gov/pair/PrivatePair. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /MOHAMAD O EL SAYAH/Primary Examiner, Art Unit 3658B Application/Control Number: 18/917,324 Page 2 Art Unit: 3658 Application/Control Number: 18/917,324 Page 3 Art Unit: 3658 Application/Control Number: 18/917,324 Page 4 Art Unit: 3658 Application/Control Number: 18/917,324 Page 5 Art Unit: 3658 Application/Control Number: 18/917,324 Page 6 Art Unit: 3658 Application/Control Number: 18/917,324 Page 7 Art Unit: 3658 Application/Control Number: 18/917,324 Page 8 Art Unit: 3658 Application/Control Number: 18/917,324 Page 9 Art Unit: 3658 Application/Control Number: 18/917,324 Page 10 Art Unit: 3658 Application/Control Number: 18/917,324 Page 11 Art Unit: 3658 Application/Control Number: 18/917,324 Page 12 Art Unit: 3658 Application/Control Number: 18/917,324 Page 13 Art Unit: 3658 Application/Control Number: 18/917,324 Page 14 Art Unit: 3658 Application/Control Number: 18/917,324 Page 15 Art Unit: 3658 Application/Control Number: 18/917,324 Page 16 Art Unit: 3658 Application/Control Number: 18/917,324 Page 17 Art Unit: 3658 Application/Control Number: 18/917,324 Page 18 Art Unit: 3658 Application/Control Number: 18/917,324 Page 19 Art Unit: 3658 Application/Control Number: 18/917,324 Page 20 Art Unit: 3658 Application/Control Number: 18/917,324 Page 21 Art Unit: 3658
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