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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 06/10/2025 has been entered.
Response to Arguments
Applicant's arguments filed 06/10/2025, with respect to claims 1-20 rejections under 35 USC 101, see pages 10-14, have been fully considered but they are not persuasive.
Applicant's arguments with respect to claims 1-20 rejections under 35 USC 102(a)(1) and 35 USC 103 rejections have been fully considered but they are not persuasive.
Applicant Argues:
In summary, the Applicant argues that the claimed invention is not directed to an abstract idea and is integrated into a practical application that cannot be practically performed in the human mind. Additionally, Applicant argues that the claims add significantly more than an abstract idea.
Examiner’s Response:
The Examiner respectfully disagrees. The claimed invention recites receiving, selecting, identifying, collecting, calculating, comparing, determining, and outputting, which as currently recited is an abstract idea that can be performed within the human mind or with pen and paper. For example, selecting data from a dataset based on a signal, identifying, selecting, and collecting information from the selected data and the signal, then calculating, comparing, and determining a result from the selected data and the signal. In regards to the newly amended receiving, via a wireless communication interface, the claimed limitation is extra-solution activity (pre-solution in this case) data gathering, wherein the recited hardware merely applies the exception using a generic computing component. Next, the outputting step is recited at a high level of generality without respect to any specific system which pertains to extra-solution activity (post-solution in this case) data output using a generic computing component.
In regards to Applicant’s arguments pertaining newly amended limitations of a trigger signal of autonomous driving control of the vehicle, the signals of the autonomous driving control (or the autonomous vehicle thereof) is recited at a high level of generality and aim to encompass nearly any function of the vehicle. Merely directing the abstract idea to particular field of use or technological environment still produces an abstract idea and cannot integrate a judicial exception into a practical application. With respect to Applicant’s arguments that humans are incapable to understand the logic of autonomous driving, the processes disclosed in the claimed invention merely occur during autonomous driving control of the vehicle and does not recite any limitations in regards to generating and outputting to an autonomous driving control system of the vehicle or to control the vehicle behavior in any way. Therefore, the claimed invention is directed to an abstract idea.
In regards to Applicant’s arguments pertaining to claims 1-20 rejections under 35 USC 102(a)(1) and 35 USC 103, the arguments pertain to newly amended limitations that were not addressed in the prior Office Action of record. A detailed rejection follows below.
Claim Rejections - 35 USC § 101
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claims are directed to an abstract idea without significantly more.
Step 1 of the Subject Matter Eligibility Test entails considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: process, machine, manufacture, or composition of matter.
Claims 1-20 are directed to an apparatus and a method. Therefore, claims 1-20 are within at least one of the statutory categories , i.e., process, machine, manufacture, or composition of matter.
If the claims recite at least one statutory category of invention, the claims require further analysis in Step 2A. Step 2A of the Subject Matter Eligibility Test is a two-prong inquiry. In Prong One, examiners evaluate whether the claims recite a judicial exception of invention.
Claim 1, 11 and 20, recite the following (bolded) abstract limitations (or abstract limitations analogous to):
“An apparatus of a vehicle, the apparatus comprising:
a sensor device configured to collect real-time driving information of the vehicle and real- time state information of the vehicle, wherein the sensor device comprises at least one sensor, and wherein the real-time state information of the vehicle comprises real-time state information of a plurality of parts of the vehicle;
a storage to store the real-time state information of the vehicle and the real-time driving information; and
a controller configured to:
receive, via a wireless communication interface, a dataset associated with the vehicle from an electronic device;
select, based on at least a portion of the dataset, a signal for collecting pieces of information of the plurality of parts of the vehicle;
identify at least one policy associated with the selected signal;
select, based on the at least a portion of the dataset, a first policy associated with the signal among the at least one policy;
collect, based on the selected first policy and based on a trigger signal of autonomous driving control of the vehicle, the signal;
calculate, based on pieces of part information about the plurality of parts of the vehicle and based on the at least a portion of the dataset, a reference prediction value corresponding to at least one of a plurality of pieces of information comprised in the dataset;
compare the calculated reference prediction value with an updated accumulation value associated with at least one of:
the real-time driving information; or
the real-time state information of the vehicle comprising the real-time state information of the plurality of parts of the vehicle, wherein the updated accumulation value is associated with use of a first part of the vehicle and associated with a failure prediction indicator of at least one second part of the plurality of parts; and
determine, using a comparison result associated with the calculated reference prediction value and the updated accumulation value, states of the plurality of parts comprising the failure prediction indicator of the at least one second part of the plurality of parts,
wherein the controller is further configured to output, during autonomous driving control of the vehicle, a signal indicating at least one of the states of the plurality of parts comprising the failure prediction indicator of the at least one second part of the plurality of parts”
With respect to claims 1, 11, 20 the method steps can be performed entirely manually and are a process and/or math that, that under its broadest reasonable interpretation, cover performance of the limitations in the mind, or by a human using pen and paper. Therefore the claimed limitations recite a mental processes. For example, calculating and predicting values from data and real-time observations. The mere recitation of a generic computing component would not take the claim out of the mental process grouping. Thus, the claim recites an abstract idea.
If the claim recites a judicial exception in step 2A Prong One, then the claim requires further analysis in step 2A Prong Two. In step 2A Prong Two, examiners evaluate whether the claim recites additional elements that integrate the exception into a practical application.
Claim 1 further recites the (underlined) additional limitations (or limitations analogous to):
“An apparatus of a vehicle, the apparatus comprising:
a sensor device configured to collect real-time driving information of the vehicle and real- time state information of the vehicle, wherein the sensor device comprises at least one sensor, and wherein the real-time state information of the vehicle comprises real-time state information of a plurality of parts of the vehicle;
a storage to store the real-time state information of the vehicle and the real-time driving information; and
a controller configured to:
receive, via a wireless communication interface, a dataset associated with the vehicle from an electronic device;
select, based on at least a portion of the dataset, a signal for collecting pieces of information of the plurality of parts of the vehicle;
identify at least one policy associated with the selected signal;
select, based on the at least a portion of the dataset, a first policy associated with the signal among the at least one policy;
collect, based on the selected first policy and based on a trigger signal of autonomous driving control of the vehicle, the signal;
calculate, based on pieces of part information about the plurality of parts of the vehicle and based on the at least a portion of the dataset, a reference prediction value corresponding to at least one of a plurality of pieces of information comprised in the dataset;
compare the calculated reference prediction value with an updated accumulation value associated with at least one of:
the real-time driving information; or
the real-time state information of the vehicle comprising the real-time state information of the plurality of parts of the vehicle, wherein the updated accumulation value is associated with use of a first part of the vehicle and associated with a failure prediction indicator of at least one second part of the plurality of parts; and
determine, using a comparison result associated with the calculated reference prediction value and the updated accumulation value, states of the plurality of parts comprising the failure prediction indicator of the at least one second part of the plurality of parts,
wherein the controller is further configured to output, during autonomous driving control of the vehicle, a signal indicating at least one of the states of the plurality of parts comprising the failure prediction indicator of the at least one second part of the plurality of parts”
Where the claimed limitations recite a sensor device, at least one sensor, a storage, a wireless communication interface, and a controller, the functions of which are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component. The elements of receiving data, storing data and collecting signals amounts to extra-solution activity (pre-solution data gathering). The element of outputting signals amounts to extra-solution activity (post-solution data output) (see MPEP 2105.05(g)). Next, the element of during autonomous driving control of the vehicle, is merely a field of use or technological environment in which to apply a judicial exception and cannot integrate the judicial exception into a practical application (see MPEP 2106.05(h)). Accordingly, in combination, these additional elements do not impose any meaningful limits on practicing the abstract idea.
If the additional elements do not integrate the exception into a practical application in step 2A Prong Two, then the claim is directed to the recited judicial exception, and requires further analysis under Step 2B to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself).
Claim 1 additionally recites a sensor device, a sensor, a storage, a wireless communication interface, and a controller, which are recited at such a high level of generality that it amounts to no more than additional elements of instructions to apply an exception. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Thus, even when viewed as an ordered combination, nothing in the claims add significantly more (i.e. an inventive concept) to the abstract idea.
Additionally, with respect to the previously identified extra-solution activity, the Symantec, TLI, OIP Techs. and buySAFE court decisions cited in MPEP 2106.05(d)(II) indicate that mere receiving or transmitting data over a network is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here). In addition, the Versata and OIP Techs court decisions cited in MPEP 2106.05(d)(II) indicate that storing and retrieving data in memory is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here).
Next, “a trigger signal of autonomous driving control” and “during autonomous driving vehicle control of the vehicle”, of claims 1, 11, and 15, are directed to a judicial exception and cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use" Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application. See Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016).
Even when viewed as an ordered combination, nothing in the claims add significantly more (i.e. an inventive concept) to the abstract idea.
Claim 7 and 17 additionally recite the additional limitations (or limitations analogous to):
“wherein the controller is configured to transmit, to the electronic device” which is recited at such a high level of generality that it amounts to no more than additional elements of instructions to apply an exception. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Additionally and/or alternatively, transmitting function represents a form of extra-solution activity and the Symantec, TLI, OIP Techs. and buySAFE court decisions cited in MPEP 2106.05(d)(II) indicate that mere receiving or transmitting data over a network is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here). Claim 7 and 17 additionally recite “failure prediction information comprising the reference prediction value and the comparison result” which covers performance of the limitations in the mind, or by a human using pen and paper, such as analyzing results and predicting an outcome, which merely amounts to a mental process. Thus, even when viewed as an ordered combination, nothing in the claims add significantly more (i.e. an inventive concept) to the abstract idea.
Claims 9, 10, and 19 additionally recites “based on the brake pedal ON time accumulation value being greater than the reference prediction value, the comparison result comprising information indicating that it is necessary to replace the brake pad” which amounts to a mental process, and the additional limitations (or limitations analogous to): “display, on a display device” which is recited at such a high level of generality that it amounts to no more than additional elements of instructions to apply an exception. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Additionally and/or alternatively, a display function represents a form of extra-solution activity and the Symantec, Internet Patent Corp. court decision cited in MPEP 2106.05(d)(II) indicate that a display functionality is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here). Thus, even when viewed as an ordered combination, nothing in the claims add significantly more (i.e. an inventive concept) to the abstract idea.
The various metrics/limitations of claims 2-6, 8, 12-16, and 18 merely narrow the previously recited abstract idea limitations (e.g. further characterizing the data within the system). For the reasons described above with respect to claims 1, 11, and 20, this judicial exception is not meaningfully integrated into a practical application, or significantly more than the abstract idea.
Therefore, claim(s) 1-20 are ineligible under 35 USC § 101.
Claim Rejections - 35 USC § 102
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1-8 and 11-18 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Claessens et al. (20210335061; hereinafter Claessens, already of record).
Regarding claim 1, Claessens teaches An apparatus of a vehicle, the apparatus comprising:
a sensor device configured to collect real-time driving information of the vehicle and real- time state information of the vehicle, wherein the sensor device comprises at least one sensor (Claessens: “a vehicle may comprise one or more sensors ... that continuously or periodically gather sensor data associated with one or more components of the vehicle throughout the life of the vehicle” ¶ 11, “a second (e.g., progressive, real-time, current, etc.) sensor signature may be determined for the component of the vehicle” ¶ 12), and wherein the real-time state information of the vehicle comprises real-time state information of a plurality of parts of the vehicle (Claessens: “vehicle health and/or vehicle component health may be more accurately monitored throughout the lifespan of the vehicle” ¶ 11, “component and/or vehicle health may be determined in real-time” ¶ 12, see also ¶ 55, 66);
a storage to store the real-time state information of the vehicle and the real-time driving information (Claessens: “The vehicle computing device 404 can, in some examples, include one or more processors 416 and memory 418” ¶ 50); and
a controller configured to (Claessens: “a monitoring component 430” ¶ 50):
receive, via a wireless communication interface (Claessens: “... the communications connection(s) 410 can enable Wi-Fi-based communication such as via frequencies defined by the IEEE 702.11 standards, short range wireless frequencies such as Bluetooth®, cellular communication (e.g., 2G, 3G, 4G, 4G LTE, 5G, etc.) or any suitable wired or wireless communications ” ¶ 69), a dataset associated with the vehicle from an electronic device (Claessens: “The monitoring component 430 receives sensor data from the one or more sensor systems 406” ¶ 58, “receiving, from a sensor of the vehicle, data associated with the component of the vehicle” ¶ 87, “the first data may comprise raw sensor data” ¶ 88);
select, based on at least a portion of the dataset, a signal for collecting pieces of information of the plurality of parts of the vehicle (Claessens: “the sensor data may be processed to generate processed sensor data” ¶ 88, “monitoring of virtually any component of a vehicle by using live sensor data” ¶ 15);
identify at least one policy associated with the selected signal (Claessens: Fig. 6 Element 602, “the method 600 may include determining that the sensor data comprises audio data” ¶ 94, see also ¶ 88);
select, based on the at least a portion of the dataset, a first policy associated with the signal among the at least one policy (Claessens: “processing the sensor data may include removing and/or reducing portions of data (e.g., background noise) from the sensor data and/or isolating portions of sensor data associated with a particular component” ¶ 88);
collect, based on the selected first policy and based on a trigger signal of autonomous driving control of the vehicle, the signal (Claessens: “the vehicle 402 may perform one or more operations associated with causing a component to activate under one or more conditions so that sensor data associated with the component may be captured by the one or more sensors systems 406” ¶ 55);
calculate (Claessens: Fig. 5 Elements 510, 512, “the sensor signature may comprise information derived from the raw sensor data such as, but not limited to, Fourier transforms, Laplace transforms, principle component analysis, harmonic decomposition, and/or any other method of determining features associated therewith” ¶ 13), based on pieces of part information about the plurality of parts of the vehicle and based on the at least a portion of the dataset (Claessens: “receiving, from a sensor of the vehicle, first data associated with the component of the vehicle at the first time. In this way, a first sensor signature that is associated with the component” ¶ 16), a reference prediction value corresponding to at least one of a plurality of pieces of information comprised in the dataset (Claessens: “a first (e.g., baseline, initial, original, etc.) sensor signature may be determined for a component of a vehicle ... The sensor data may then be used to determine the first sensor signature of the component” ¶ 12, “a baseline (e.g., first) sensor signature” ¶ 44);
compare the calculated reference prediction value with an updated accumulation value associated with at least one of (Claessens: Fig. 5 Element 514 “the method 500 includes determining an association between the first sensor signature and the second sensor signature” ¶ 90, “The second sensor signature may then be compared to the first sensor signature in order to determine an operating status associated with the component” ¶ 12):
the real-time driving information; or
the real-time state information of the vehicle comprising the real-time state information of the plurality of parts of the vehicle (Claessens: “a second (e.g., progressive, real-time, current, etc.) sensor signature may be determined for the component of the vehicle ... component and/or vehicle health may be determined in real-time and before components fail” ¶ 12), wherein the updated accumulation value is associated with use of a first part of the vehicle and associated with a failure prediction indicator of at least one second part of the plurality of parts (Claessens: “the method may include determining an estimated time-to-failure associated with the component (e.g., an estimated number of miles, in-service hours, etc. until the component may fail) of the vehicle based at least in part on the first sensor signature, the second sensor signature, and/or the variation and/or association between the first sensor signature and the second sensor signature ...” ¶ 19 see also ¶ 32); and
determine, using a comparison result associated with the calculated reference prediction value and the updated accumulation value, states of the plurality of parts comprising the failure prediction indicator of the at least one second part of the plurality of parts (Claessens: Fig. 5 Element 518, “the second action may include determining and/or outputting an operating status associated with the component of the vehicle” ¶ 92, “the method may include determining an estimated time-to-failure associated with the component (e.g., an estimated number of miles, in-service hours, etc. until the component may fail) of the vehicle based at least in part on the first sensor signature, the second sensor signature, and/or the variation and/or association between the first sensor signature and the second sensor signature ...” ¶ 19, see also ¶ 12, 44),
wherein the controller is further configured to output, during autonomous driving control of the vehicle, a signal indicating at least one of the states of the plurality of parts comprising the failure prediction indicator of the at least one second part of the plurality of parts (Claessens: “the second action may include determining and/or outputting an operating status associated with the component of the vehicle ... the operating status may include an indication of wear associated with a component of a vehicle, such as a percentage of life used and/or remaining of the component (e.g., 50% life used, 75% life remaining, etc.), a time-to-failure associated with the component, such as an amount of time and/or a distance the vehicle may travel until the component will likely fail (e.g., 10 hours until component failure, 100 miles until component failure, etc.), or an indication of an anomaly associated with the component, such as one or more fault conditions” ¶ 92, “while activating the component of the vehicle at the first time and at the second time to receive the first data and the second data as described above ... while controlling operation of other components according to the operating parameter (e.g., while the vehicle is moving at different rates of speed, while the vehicle is stopped, with one or more doors or windows open and closed, etc.)” ¶ 21, see also ¶ 15).
Regarding claim 2, Claessens teaches the apparatus of claim 1, wherein the controller is configured to select the first policy among the at least one policy, based on vehicle information and driving information of the vehicle, wherein the vehicle information and the driving information are comprised in the dataset (Claessens: “the first sensor signature may be associated with an engine speed, operating status of other components (e.g., HVAC temperature and/or fan speed), brake pressure, and the like” ¶ 16, see also ¶ 116), and wherein the controller is configured to determine, based on a comparison of a signal collected based on the first policy with the reference prediction value, whether there is a failure in at least one of the plurality of parts or whether it is necessary to replace at least one of the plurality of parts (Claessens: “the model may be compared to known operating limits (e.g., fatigue and/or stress conditions of metal, number of cycles, number of revolutions, hours of operations, etc.) to determine when components should be repaired and/or replaced, when components may likely experience a failure and/or anomaly” ¶ 24).
Regarding claim 3, Claessens teaches the apparatus of claim 1, wherein the controller is configured to determine or update (Claessens: “the sensor signatures 434 may include one or more baseline sensor signatures associated with components of the vehicle 402, and may additionally, or alternatively, include one or more progressive sensor signatures (e.g., a sensor signature that keeps being updated” ¶ 60), based on the at least a portion of the dataset, a condition value for collecting the signal, wherein the condition value is comprised in the first policy, and
wherein the condition value comprises at least one of: a collection period for collecting the signal (Claessens: “a “first time,” “second time,” “third time,” and so on may include a specific point in time and/or may include a period of time ... The second and subsequent times may be periodic (e.g., daily, weekly, monthly, etc.) and/or may be triggered by one or more events” ¶ 17, see also ¶ 79), a trigger signal, a collection period of time, or a state of the vehicle.
Regarding claim 4, Claessens teaches the apparatus of claim 1, wherein the signal indicating at least one of the states of the plurality of parts indicates a part of the vehicle needs to be replaced or repaired (Claessens: “to determine when components should be repaired and/or replaced” ¶ 24, “performing the first action may include sending a notification to a remote computing system that an operating status of the vehicle component has changed” ¶ 91, see also ¶ 78), wherein the pieces of part information are comprised in the dataset, and
wherein the pieces of part information comprise at least one of: a part production time, a part model, a part number (Claessens: “The first sensor signature may be determined during a bench test of the component or based on sensor data captured by another vehicle that previously experienced a failure and/or anomaly of a component of a same type (e.g., same or equivalent part number” ¶ 12), or a part application vehicle.
Regarding claim 5, Claessens teaches the apparatus of claim 1, wherein the controller is configured to calculate (Claessens: “the sensor signature may comprise information derived from the raw sensor data such as, but not limited to, Fourier transforms, Laplace transforms, principle component analysis, harmonic decomposition, and/or any other method of determining features associated therewith” ¶ 13), based on vehicle information and driving information of the vehicle, the reference prediction value corresponding to at least one of the plurality of pieces of information (Claessens: “The first sensor signature may, in some instances, comprise a baseline sensor signature” ¶ 16),
wherein the vehicle information and the driving information are comprised in the dataset, wherein the vehicle information comprises at least one of: a model of the vehicle, a production time of the vehicle, a failure code of the vehicle, engine state information of the vehicle (Claessens: “the first sensor signature may be associated with an engine speed” ¶ 16), or battery information of the vehicle, and
wherein the driving information comprises at least one of: fuel efficiency of the vehicle, a driving distance of the vehicle, or a driving speed of the vehicle (Claessens: “the operating parameter may include a speed of the vehicle” ¶ 21).
Regarding claim 6, Claessens teaches the apparatus of claim 1, wherein the plurality of pieces of information comprised in the dataset comprise at least one of: driving information, vehicle information, part information, or characteristic information associated with the vehicle (Claessens: “the first sensor signature may be associated with an engine speed, operating status of other components (e.g., HVAC temperature and/or fan speed), brake pressure, and the like” ¶ 16, see also ¶ 116),
wherein the controller is configured to calculate a plurality of reference prediction values comprising a driving information reference prediction value (Claessens: “a second (e.g., progressive, real-time, current, etc.) sensor signature may be determined for the component of the vehicle” ¶ 12, see also ¶ 32), a vehicle information reference prediction value (Claessens: “the first sensor signature may be associated with an engine speed, operating status of other components (e.g., HVAC temperature and/or fan speed), brake pressure, and the like” ¶ 16, see also ¶ 116), a part information reference prediction value (Claessens: “The first sensor signature may be determined during a bench test of the component or based on sensor data captured by another vehicle that previously experienced a failure and/or anomaly of a component of a same type (e.g., same or equivalent part number” ¶ 12), and a characteristic information reference prediction value (Claessens: “the perception system 422 can provide processed sensor data that indicates one or more characteristics associated with a detected entity” ¶ 52), and
wherein each reference prediction value of the plurality of reference prediction values respectively corresponds to one of the plurality of pieces of information (Claessens: “the training component 446 can label sensor data associated with vehicle components with one or more measured parameters and/or characteristics of the vehicle components associated with the sensor data” ¶ 77).
Regarding claim 7, Claessens teaches the apparatus of claim 1, wherein the controller is configured to transmit, to the electronic device, failure prediction information comprising the reference prediction value and the comparison result (Claessens: Fig. 7, “if a difference does exist between the operating status and the predicted operating status, then at operation 714 the method 700 may determine to proceed on to operation 716 ... the method 700 may include altering one or more parameters of the machine learned model” ¶ 107).
Regarding claim 8, Claessens teaches the apparatus of claim 7, wherein the controller is configured to receive, from the electronic device via the wireless communication interface, a dataset updated based on the failure prediction information after transmitting the failure prediction information (Claessens: Fig. 7, “After adjusting one or more parameters of the machine learned model, the method 700 may, in some examples, proceed to operation 708, where the sensor data may be re-inputted into the machine learned model” ¶ 107).
In regards to claim(s) 11-18, the claim(s) recite analogous limitations to claim(s) 1-8, and are therefore rejected under the same premise.
In regards to claim(s) 20, the claim(s) recite analogous limitations to claim(s) 1, and are therefore rejected under the same premise.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 9, 10, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Claessens in view of Matsui (20220018413; already of record).
Regarding claim 9, Claessens in view of Matsui teaches the apparatus of claim 1, wherein the plurality of parts comprise a brake pad (Claessens: “a brake system of the vehicle, brake pads” ¶ 16), and
wherein the controller is configured to:
select a brake pedal ON time accumulation value as the signal (see obviousness discussion below pertaining to Matsui);
collect, based on the first policy, the signal (Claessens: “The monitoring component 430 receives sensor data from the one or more sensor systems 406” ¶ 58, “the vehicle 402 can send processed sensor data and/or representations of sensor data to the computing device(s)” ¶ 74);
calculate (Claessens: “the sensor signature may comprise information derived from the raw sensor data such as, but not limited to, Fourier transforms, Laplace transforms, principle component analysis, harmonic decomposition, and/or any other method of determining features associated therewith” ¶ 13) the reference prediction value using a brake pad replacement time comprised in the dataset (Claessens: “an “operating status” may include an indication of wear associated with a component of a vehicle, such as a percentage of life used and/or remaining of the component (e.g., 50% life used, 75% life remaining, etc.), a time-to-failure associated with the component” ¶ 11, “The monitoring component 430 receives sensor data from the one or more sensor systems 406, and uses the sensor data to estimate current, and/or predict future, operating statuses associated with one or more components of the vehicle 402” ¶ 58);
compare the calculated reference prediction value with the real-time driving information by comparing (Claessens: ¶ 90, 44, 92) the brake pedal ON time accumulation (see obviousness discussion below pertaining to Matsui) value identified based on the collected signal with the calculated reference prediction value (Claessens: “the method 500 includes determining an association between the first sensor signature and the second sensor signature” ¶ 90, “This progressive sensor signature may be compared to a baseline (e.g., first) sensor signature associated with the ambient noise in the interior of the vehicle to determine an operating status” ¶ 44, “the second action may include determining and/or outputting an operating status associated with the component of the vehicle” ¶ 92); and
display, on a display device and based on the brake pedal ON time accumulation value being greater than the reference prediction value (see obviousness discussion below pertaining to Matsui), the comparison result comprising information indicating that it is necessary to replace the brake pad (Claessens: “the soundwaves 320 may be emitted by the braking system upon activating the braking system to decelerate the vehicle 100. Additionally, in some examples, the sensors 300 (and/or sensors 102 and/or sensors 202) may capture inertial sensor data indicating that one of the components of the propulsion system (e.g., the drive motor 302, the gear box 304, and/or the axles 306) is vibrating, which may indicate wear or failure of the respective component(s)” ¶ 46, see also ¶ 42).
While Claessens remains silent regarding select a brake pedal ON time accumulation value as the signal ... the brake pedal ON time accumulation ... display, on a display device and based on the brake pedal ON time accumulation value being greater than the reference prediction value, in a similar field of endeavor, Matsui teaches the claim limitation a brake pedal ON time accumulation value and a display device to display the comparison result (Matsui: “The brake duration tb can be acquired from a time during which the brake pressure Pb is generated” ¶ 50, “the brake pad state estimation device 100 may output an alert through an output device 60 (e.g., a display” ¶ 52)). As such, it would have been obvious to one of ordinary skill in the art, at the time of effective filing and with a reasonable expectation for success, to have modified the monitoring system of Claessens so that it also includes the element of a brake pedal ON time and a display, as taught by Matsui, in order to improve brake life estimation and to inform a user of estimation (Matsui: ¶ 80).
Regarding claim 10, Claessens in view of Matsui teaches the apparatus of claim 9, wherein the controller is configured to reset, based on the brake pad being replaced (Claessens: “a new braking system may be installed in the drive assembly, or the existing braking system may be serviced” ¶ 42, “the vehicle computing device 404 may implement a “test mode” at a first time (e.g., when the vehicle is first commissioned or when a new component is put into service). At the first time, the vehicle 402 may perform one or more operations associated with causing a component to activate under one or more conditions so that sensor data associated with the component may be captured by the one or more sensors systems 406” ¶ 55, Note: wherein it can be seen that the data regarding the replaced component is implemented to set a new baseline, therein resetting its first signature), the brake pedal ON time accumulation value and display, on the display device, a user interface comprising information indicating that the brake pad is replaced (see obviousness discussion below pertaining to Matsui).
While Claessens remains silent regarding the brake pedal ON time accumulation value and display, on the display device, a user interface comprising information indicating that the brake pad is replaced, in a similar field of endeavor, Matsui teaches the claim limitation a brake pedal ON time accumulation value and a display device to display the comparison result (Matsui: “The brake duration tb can be acquired from a time during which the brake pressure Pb is generated” ¶ 50, “the brake pad state estimation device 100 may output an alert through an output device 60 (e.g., a display” ¶ 52)). As such, it would have been obvious to one of ordinary skill in the art, at the time of effective filing and with a reasonable expectation for success, to have modified the monitoring system of Claessens so that it also includes the element of a brake pedal ON time and a display, as taught by Matsui, in order to improve brake life estimation and to inform a user of estimation (Matsui: ¶ 80).
In regards to claim(s) 19, the claim(s) recite analogous limitations to claim(s) 9, and are therefore rejected under the same premise.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Gusikhin et al. (20210241128) is in the similar field of endeavor as the claimed invention of vehicle component prediction.
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/C.P./ Examiner, Art Unit 3663
/ABBY J FLYNN/ Supervisory Patent Examiner, Art Unit 3663