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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) was submitted on 04/24/2026. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Status of the Claims
This Office Action is in response to the claims filed on 04/24/2026.
Claims 1-6 have been presented for examination.
Claims 1-6 are currently rejected.
Claim 6 is rejected under 35 U.S.C. 112.
Claims 1-4 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Ekkizogloy et al. (U.S. Patent Publication Number 2018/0350167) in view of Lee (U.S. Patent Publication Number 2024/0290144).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Ekkizogloy et al. (U.S. Patent Publication Number 2018/0350167) in view of Lee (U.S. Patent Publication Number 2024/0290144), further in view of Cella (U.S. Patent Publication Number 2021/0272394).
Response to Argument
Objection to the Specification
The title of the invention submitted on 04/24/2026 overcomes the objection. The objection to the specification is withdrawn.
35 U.S.C. 101
Applicant’s arguments, see Applicant Remarks, filed 04/24/2026, with respect to 35 U.S.C. 101 have been fully considered and are persuasive. The 35 U.S.C. 101 rejection has been withdrawn.
35 U.S.C. 102
The Applicant’s arguments, see Applicant Remarks filed on 04/24/2026 appear to be primarily directed to the amended claim language. The Applicant’s arguments with respect to claim(s) 1-5 have been considered but are moot because amendments shift the scope of claims and necessitate a new ground of rejection, which is made in view of Lee (U.S. Patent Publication Number 2024/0290144).
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 6 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. As written, claim 6 recites an “information processing apparatus according to claim 6,” rendering claim 6 to be dependent on itself. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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 1-4 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Ekkizogloy et al. (U.S. Patent Publication Number 2018/0350167) in view of Lee (U.S. Patent Publication Number 2024/0290144).
Regarding claim 1, Ekkizogloy discloses an information processing apparatus including a controller (Ekkizogloy ¶ 40 disclosing that processor 440 includes “one or more microcontrollers (MCUs)”) configured to perform:
acquiring, from sensors installed in a vehicle and connected to an electronic control unit (ECU) (Ekkizogloy ¶ 40 dislcoses that processor 440 may include one or more microprocessors or microcontrollers for controlling the execution of software), and accumulating a plurality of types of data collected in the vehicle, the plurality of types of data being detected by the sensors and correlated with deterioration of the vehicle; (Ekkizogloy ¶ 7 discloses “inputting, by the processor, sensor data into the analysis module [i.e., accumulating a plurality of types of data] having a trained model, the sensor data from at least one sensor disposed on the vehicle [i.e., acquiring a plurality of types of data collected in a vehicle], where the trained model further associates various sensor data, along with the various audio sounds, and the corresponding vehicular malfunction conditions [i.e., deterioration of the vehicle],” wherein “sensor data (from non-audio sources) [i.e., a plurality of types of data] can be input into the analysis module, which may further associate the sensor data with the various audio sounds and corresponding vehicular malfunction conditions,” see 64)
Ekkizogloy does not expressly disclose:
wherein accumulating the plurality of types of data comprises, for each type of data, calculating an incremental change in a sensor measurement and adding the incremental change to a cumulative total stored in a memory, such that the accumulated plurality of types of data represents cumulative totals of sensor measurements from an initial state of the vehicle to a current state of the vehicle;
generating a relationship between an accumulated plurality of types of data and a result of an actual assessment of the vehicle corresponding to the plurality of types of data;
outputting information on an assessment of a first vehicle according to the plurality of types of data accumulated for the first vehicle and the relationship,
the information including a numerical value or a rank indicating a condition of the first vehicle.
However, Lee discloses:
wherein accumulating the plurality of types of data comprises, for each type of data, calculating an incremental change in a sensor measurement and adding the incremental change to a cumulative total stored in a memory, such that the accumulated plurality of types of data represents cumulative totals of sensor measurements from an initial state of the vehicle to a current state of the vehicle; (Lee ¶ 20 discloses “inputting the sensing data accumulated in time series and the condition feature data for each device or component accumulated in time series into the life prediction model and the complex condition diagnosis mode” wherein a control signal generation unit 160 may “adjust the gain [i.e., “calculate an incremental change”] of a braking force for a brake pedal signal based on the values of brake pad condition feature data,” and “Based on the data that is cumulatively collected data and saved as big data [i.e., “adding the incremental change to a cumulative total stored in a memory”], the machine learning guidance unit 202 may generate learning guidance data for training the condition diagnosis model of the VHM device 100 through guidance (S221),” see ¶ 73. The Examiner further notes that the limitation “such that” indicates an intended use and is not expressly required under the broadest reasonable interpretation of the claim.)
generating a relationship between an accumulated plurality of types of data and a result of an actual assessment of the vehicle corresponding to the plurality of types of data; (Lee ¶ 66 discloses that “the VHM device 100 may send relevant data to the VHM cloud 200 in accordance with the values of condition feature data derived from a particular device or component or generate a control signal for controlling a device/component related to the condition feature data,” and the necessity [i.e., a generated relationship] of feature data for control may be determined (S153) to control the relevant device/component, and the control signal generation unit 160 may generate a control signal for controlling the operation of the device/component.)
outputting information on an assessment of a first vehicle according to the plurality of types of data accumulated for the first vehicle and the relationship, (Lee ¶ 66 discloses sending, thereby outputting, “relevant data [i.e., according to a relationship] to the VHM cloud 200 in accordance with the values of condition feature data derived from a particular device or component or generate a control signal for controlling a device/component related to the condition feature data,” wherein the VHM cloud may “generate a vehicle management report based on the life prediction data and the complex condition feature data and then send the same to the VHM device.”)
the information including a numerical value or a rank indicating a condition of the first vehicle. (Lee ¶ 77 discloses “the VHM cloud 200 may send to each vehicle's VHM device 100 a management report for each vehicle, which is generated based on ... component life prediction data,” wherein the “condition feature data is derived as a numerical value (e.g., a remaining pad life of 55%),” see ¶ 67)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the model of Ekkizogloy with calculating an incremental change in a sensor measurement and adding the incremental change to a cumulative total stored in a memory, such that the accumulated plurality of types of data represents cumulative totals of sensor measurements from an initial state of the vehicle to a current state of the vehicle, as disclosed by Lee, with reasonable expectation of success, because the in-depth vehicle diagnosis model performs in-depth vehicle diagnosis by giving comprehensive consideration into data associated with different frames, thereby enabling more precise vehicle condition monitoring for each vehicle and driver (Lee ¶ 104), rendering the limitation to be an obvious modification.
Regarding claim 2, Ekkizogloy in view of Lee discloses the information processing apparatus according to claim 1, wherein:
the controller is further configured to generate the model (Ekkizogloy in at least ¶ 62 “a trained model”) in which the accumulated plurality of types of data are used as input data, and information on the assessment of the vehicle is used as output data, and the accumulated plurality of types of data and data on the result of the actual assessment of the vehicle corresponding to the plurality of types of data are used as teacher data. (Ekkizogloy ¶ 62 discloses “inputting the audio data into an analysis module having a trained model. The trained model can associate various audio data and corresponding vehicular malfunction conditions,” such that “the trained model can be trained by machine learning. For example, as more input data is obtained and hypothesis are made, the analysis module can modify analyses based on previous outcomes (e.g., verified diagnoses)” and “reinforcing data (e.g., other non-audio sensors corroborate hypothesized malfunction condition) [i.e., teacher data],” see ¶ 63)
Regarding claim 3, Ekkizogloy in view of Lee discloses the information processing apparatus according to claim 1, wherein:
the plurality of types of data includes at least two of data on an operating angle of a steering wheel, data on a travel distance of a accelerator pedal, data on a travel distance of a brake pedal, and data on an operating time of an engine. (Lee ¶ 50 discloses that the sensor data includes “a pedal position sensor” and “a steering angle sensor”)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the sensor data of Ekkizogloy with the data being at least two of an operating angle of a steering wheel and a travel distance of an accelerator pedal and brake pedal, as disclosed by Lee, with reasonable expectation of success, for accurately diagnosing the condition of a vehicle through assessment of the conditions of components and the overall performance of the vehicle (Lee ¶ 23), rendering the limitation to be an obvious modification.
Regarding claim 4, Ekkizogloy in view of Lee discloses the information processing apparatus according to claim 1, wherein:
the controller is further configured to transmit a command to cause a terminal of a user of the first vehicle to display the information on the assessment of the first vehicle when outputting the information on the assessment of the first vehicle. (Ekkizogloy ¶ 41 discloses that “when an anomalous audio signature is detected, cross-referenced with database 460, and identified (as further discussed below), a message can be sent to display 470 to alert the driver that a failure mode has occurred or is likely to occur.”)
Regarding claim 6, Ekkizogloy in view of Lee discloses the information processing apparatus according to claim 6, wherein:
the plurality of types of data represents physical quantities corresponding to forces applied to components of the vehicle that contribute to mechanical deterioration of the vehicle. (Lee ¶¶ 108-109 discloses that “a vehicle's braking system ... may generate a braking force based on brake pedal signal data (e.g., pedal stroke),” wherein the control signal for the braking force is generated “depending on the condition of the brake system (typically, the pad wear condition)”)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the data of Ekkizogloy with the data representing physical quantities corresponding to forces applied to components of the vehicle that contribute to mechanical deterioration of the vehicle, as disclosed by Lee, with reasonable expectation of success, so that consistent braking performance can be achieved despite a degradation in the condition of a brake consumable (Lee ¶ 109), and allowing the condition of each component or device in a vehicle can be efficiently diagnosed, thus sparing the driver the trouble of having to remember when to replace each automotive consumable (Lee ¶ 24), rendering the limitation to be an obvious modification.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Ekkizogloy et al. (U.S. Patent Publication Number 2018/0350167) in view of Lee (U.S. Patent Publication Number 2024/0290144), further in view of Cella (U.S. Patent Publication Number 2021/0272394).
Regarding claim 5, Ekkizogloy in view of Lee discloses the information processing apparatus according to claim 1, wherein:
the controller is further configured to: generate and store, in the memory, the model in which the accumulated plurality of types of data is used as input data, and information on the assessment of the vehicle is used as output data, (Ekkizogloy Fig. 9 depicts using the received audio data, in 910 [i.e., accumulated plurality of types of data], as input into an analysis module, in 920, to then obtain a hypothesized vehicular malfunction condition 930. See corresponding ¶¶ 60 and 63-64)
wherein the accumulated plurality of types of data and data on the result of the actual assessment of the vehicle corresponding to the plurality of types of data are used as teacher data; (Ekkizogloy ¶ 63 discloses that “the trained model can be trained by machine learning” so that “as more input data is obtained and hypothesis are made, the analysis module can modify analyses based on previous outcomes (e.g., verified diagnoses)” and “reinforcing data (e.g., other non-audio sensors corroborate hypothesized malfunction condition) [i.e., previous data used as teacher data]”)
The combination of Ekkizogloy and Lee does not expressly disclose:
acquire information on the assessment of the first vehicle by inputting the plurality of types of data corresponding to the first vehicle to the model in response to a request for information on the assessment of the first vehicle from a terminal of a user;
transmit the acquired information on the assessment of the vehicle to the terminal of the user.
However, Cella discloses:
acquire information on the assessment of the first vehicle by inputting the plurality of types of data corresponding to the first vehicle to the model in response to a request for information on the assessment of the first vehicle from a terminal of a user; (Cella ¶ 22 discloses “a computer-implemented method for generating a digital twin of a vehicle includes receiving, through an interface, a request from a user of the vehicle to display state information of the vehicle,” wherein the “vehicle operating state is a vehicle maintenance state,” see ¶ 8, including “showing wear and failure of components of the vehicle and predicting a need for service, repairs or replacement based on a condition of the vehicle condition”)
transmit the acquired information on the assessment of the vehicle to the terminal of the user. (Cella ¶ 22 discloses displaying, thereby transmitting, via the interface, “the state information of the vehicle using the digital twin representation of the vehicle”)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the acquisition of information of the assessment of the vehicle of Ekkizogloy, of the combination of Ekkizogloy and Lee, with acquiring information on the assessment of the first vehicle in response to a request for information on the assessment of the first vehicle from a terminal of a user, by inputting the plurality of types of data corresponding to the first vehicle to the model, as disclosed in Cella, with reasonable expectation of success, to provide a navigation view to the driver for improved situational awareness through real-time information exchange (Cella ¶ 25) and to further improve user experience (Cella ¶ 125), rendering the limitation to be an obvious modification.
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to STEPHANIE T SU whose telephone number is (571)272-5326. The examiner can normally be reached Monday to Friday, 9:30AM - 5:00PM EST.
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, ANISS CHAD can be reached at (571)270-3832. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/STEPHANIE T SU/Primary Examiner, Art Unit 3662
Prosecution Insights