DETAILED ACTION
This is the second Office action of Application No. 18/423,571 in response to the amendment filed on June 3, 2026. Claims 1-20 are pending. By the amendment, claims 1, 11, and 20 have been amended.
Claim Rejections - 35 USC § 101
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Statutory Categories
Claims 1-20 do fall into at least one of the four statutory subject matter categories
Step 2A: Judicial Exceptions
Prong 1: Recitation of the Judicial Exception
Part of independent claim 1 recites:
determine a performance standard for the machine using a physics-based model and historical data;
a machine learning model, adjustment values to adjust the determined performance standard using based on additional historical data to account for including at least one of a systemic, equipment, environmental, or geographic variation; and
generate at least one calculated parameter for the machine based on the adjusted performance standard and the at least one control parameter, the at least one calculated parameter comprising a state of health or remaining useful life of at least one machine component based on the adjusted performance standard.
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “determine…”, “adjust…”, and “generate…” in the context of this claim encompasses a person (driver or monitor of vehicles) looking at the data collected making a simple judgement on the performance standard, adjusting the judgement based on certain conditions, and determine parameter based on the judgement.
Prong 2: Integration into a practical application
The additional elements of “a data acquisition unit communicatively coupled to the sensor module; the data acquisition unit being configured to receive the at least one control parameter from the sensor module, store the at least one control parameter, and transmit the at least one control parameter to a processor communicatively coupled to the data acquisition unit” and “a machine learning model” do not integrate the judicial exception into a practical application because the additional element(s) do not apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. The additional elements of “a sensor module configured to detect at least one control parameter of a machine” and “display, via a user interface, a startup health indicating at least one startup condition of the machine based on the determined at least one calculated parameter” do not integrate the judicial exception into a practical application because the additional element(s) do not apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception and are found to be insignificant extra-solution activity. The limitation from the sensors are recited at a high level of generality (i.e. as a general means of gathering vehicle and environmental condition data for use in the determine, adjust, and generate limitations), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. The displaying results step on the user interface is also recited at a high level of generality (i.e. as a general means of displaying startup health), and amounts to mere post solution displaying, which is a form of insignificant extra-solution activity.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitations as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. Accordingly, the additional limitations do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Step 2B: Inventive connect/significantly more
The additional elements recited in the claim(s) are not sufficient to amount to significantly more than the judicial exception because they do not add more than insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)) and amount to simply adding the equivalent of the words "apply it" with the judicial exception (MPEP 2106.05(f)), as stated above. Further, the additional elements recited in the claim(s) are well-understood, routine, and conventional activities previously known to the industry, specified at a high level of generality (MPEP 2106.05(d)). The additional limitation of “sensor module” is well-understood, routine, conventional activity (MPEP 2106.05(d)(I)(2)) as the applicant’s specification describes the conventional ‘sensor’ in paragraph [0022]. The additional limitation of “displaying…,” is a well-understood, routine, and conventional activity because the Federal Circuit in Trading Techs. Int’l v. IBG LLC, 921 F.3d 1084, 1093 (Fed. Cir. 2019), for example, indicated that the mere displaying of data is a well understood, routine, and conventional function. Hence, the claim is not patent eligible.
Dependent claims 2-10 do not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application. Therefore, dependent claims 2-10 are not patent eligible under the same rationale as provided for in the rejection of claim 1.
Claims 11-20 are not patent-eligible for the same reasons as 1-10 as explained above.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3, 5-7, 9, 11-12, 14-16, 18, and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Garcia (US Patent Publication 20180143257).
Regarding claim 1, Garcia discloses a startup condition monitoring device (e.g. paragraphs [0001] and [0057]), comprising: a sensor module (paragraph [0060], input/measurement signals 102) configured to detect at least one control parameter (e.g. “voltage” of 102) of a machine (paragraph [0036]) during a startup event; and a data acquisition unit (Fig. 1, Battery condition monitoring system (BCM)) communicatively coupled to the sensor module, the data acquisition unit being configured to receive the at least one control parameter from the sensor module, store the at least one control parameter, and transmit the at least one control parameter to a processor communicatively coupled to the data acquisition unit (e.g. paragraph [0025]); the processor being configured to: determine a performance standard for the machine using a physics-based model and historical data (paragraph [0064-0066], 108 and e.g. paragraph [0069]); generate, using a machine learning model, adjustment values to adjust the determined performance standard using based on additional historical data (Fig. 1, training/learning process 106) to account for at least one of a systemic, equipment, environmental, or geographic variation (Fig. 1, 102, e.g. “offload/underload conditions”, “temperatures”); generate at least one calculated parameter for the machine based on the adjusted performance standard (Fig. 1, e.g. 170 “health estimation/prediction”) and the at least one control parameter, the at least one calculated parameter comprising a state of health or remaining useful life of at least one machine component based on the adjust performance standard (e.g. paragraph [0059]); and display, via a user interface (paragraph [0060]), a startup health (paragraph [0057]) indicating at least one startup condition of the machine based on the determined at least one calculated parameter.
Regarding claim 11, Garcia discloses a system comprising: a sensor module configured to detect at least one control parameter of a machine during a startup event; a data acquisition unit communicatively coupled to the sensor module, the data acquisition unit being configured to receive the at least one control parameter from the sensor module, store the at least one control parameter, and transmit the at least one control parameter to at least one processor; and at least one memory storing instructions; the at least one processor being configured to execute the instructions to perform operations comprising: determining a performance standard for the machine using a physics-based model and historical data; generating, using a machine learning model, adjustment values to adjust the determined performance standard using and the at least one control parameter, the at least one calculated parameter comprising a state of health or remaining useful life of at least one machine component based on the adjust performance standard; and displaying, via a user interface, a startup health indicating at least one startup condition of the machine based on the determined at least one calculated parameter (see annotations to claim 1).
Regarding claim 20, Garcia discloses a method for monitoring a startup condition of a machine, the method comprising: detecting, using a sensor, at least one control parameter of a machine during a startup event; receiving, storing, and transmitting the at least one control parameter to at least one processor; determining, by the at least one processor, a performance standard for the machine using a physics-based model and historical data; generating, using a machine learning model, adjustment values to adjust, by the at least one processor, the determined performance standard using and the at least one control parameter, the at least one calculated parameter comprising a state of health or remaining useful life of at least one machine component based on the adjust performance standard (e.g. paragraph [0059]); and displaying, by the at least one processor via a user interface, a startup health indicating at least one startup condition of the machine based on the determined at least one calculated parameter (see annotations to claim 1).
Regarding claim 2, Garcia discloses the device of claim 1, wherein the machine includes a generator (paragraph [0036]).
Regarding claim 3 and claim 12, Garcia discloses the device of claim 1 or claim 11, wherein the at least one control parameter comprises at least one of a voltage, a crank engine speed, a startup duration, or a temperature (Fig. 1, 102, “voltage” and “temperature”).
Regarding claim 5 and claim 14, Garcia discloses the device of claim 3, wherein the voltage includes at least one of a battery voltage, a minimum voltage, a step voltage, or a peak-to-peak voltage (paragraph [0057], e.g. “peak”).
Regarding claim 6 and claim 15, Garcia discloses the device of claim 1 or claim 11, wherein the historical data includes service or maintenance information recorded during a battery replacement event (Fig. 1, 195 “end of life”, “remaining useful life”, is determined from the learning models).
Regarding claim 7 and claim 16, Garcia discloses the device of claim 1 or claim 11, wherein the at least one calculated parameter includes at least one of a condition of a battery (e.g. paragraph [0057]), a condition of an alternator, a condition of a generator, a condition of a starter, a condition of a cabling connection, or a condition of a crank engine.
Regarding claim 9 and claim 18, Garcia discloses the device of claim 1 and claim 11, wherein the performance standard is configured to be adjustable based on one or more of an application of the machine, an environmental temperature around the machine, or a location of operation of the machine (paragraph [0050]).
Claim Rejections - 35 USC § 103
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 4, 8, 13, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Garcia (US Patent Publication 20180143257) in view of Wilcox (US Patent Publication 20230175926).
Regarding claim 4 and claim 13, Garcia discloses the device of claim 3 or claim 12, wherein the temperature.
Garcia does not disclose at least one of a coolant temperature or an ambient temperature.
Wilcox discloses a monitoring engine starting system wherein the temperature is at least one of a coolant temperature or an ambient temperature (e.g. Fig. 4).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Garcia to incorporate the ambient temperature of Wilcox with a reasonable expectation better evaluating the health of the battery based on the ambient air temperature (abstract).
Regarding claim 8 and claim 13, Garcia discloses the device of claim 1 or claim 11, wherein the processor.
Garcia does not disclose the processor to generate an alert signal when the at least one calculated parameter is less than a predetermined threshold.
Wilcox discloses a monitoring engine starting system wherein the processor is further configured to generate an alert signal when the at least one calculated parameter is less than a predetermined threshold (e.g. paragraphs [0021-0022]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Garcia to incorporate the alert of Wilcox with a reasonable expectation for the alert to notify the operator of an issues and servicing (e.g. paragraphs [0021-0022]).
Claims 10 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Garcia (US Patent Publication 20180143257) in view of Hirschbold (US Patent 9784798, cited in the IDS).
Regarding claim 10 and claim 19, Garcia the device of claim 1 or claim 11, wherein the sensor module is configured to detect the at least one control parameter.
Garcia does not disclose at a position located before a low pass filter of the machine.
Hirschbold discloses the sensor module is configured to detect the at least one control parameter at a position located before a low pass filter of the machine (column 9, lines 38-68).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Garcia to incorporate apply low pass filter of Hirschbold with a reasonable expectation so that the data can be smoothed before processing the predictions (column 9, lines 38-68).
Response to Arguments
Regarding the prior art rejections using Garcia (US Patent Publication 20180143257), applicant's arguments filed 6/3/2026 have been fully considered but they are not persuasive. Applicant provided the arguments that the historical data and additional historical data are the same in Garcia. However, in paragraph [0069], Garcia specifies “The observed, what-if, and forecast module 110 may include databases of historically observed operation as well as forecast predictions and what-if assumptions to construct, refine, or a combination thereof, various models (e.g., aging models) and to support estimations of battery future conditions”. In other words, Garcia discloses multiple set of data (e.g. databases) and they refer to the adjustment as “refine”. Also, Garcia suggests online adjustments can be made specifically for the environmental temperature (paragraph [0134]). Furthermore, Wilcox (US Patent Publication 20230175926) used in the 103 rejection for claims 4, 8, 13, and 17 provides evidence that additional data can be used to adjust as well (paragraph [0051], “At block 308, the example trainer circuitry 220 determines whether to perform additional training. In some examples, the trainer circuitry 220 updates the identified engine starting metrics over time as more historical engine starting system characteristics 118 are collected, and the machine learning engine 222 updates the machine learning model”). As such the prior art rejections using Garcia remains.
Regarding the 35 U.S.C. §101 rejection, applicant's arguments filed 6/3/2026 have been fully considered but they are not persuasive. Applicant provided the following sub-arguments:
The pending claims do not recite an abstract idea.
The pending claims integrate any alleged abstract idea into a practical application.
The pending claims recite “significantly more” than the alleged abstract idea.
Regarding sub-argument a, Examiner disagrees. Applicant argues that the configuration of during startup event detecting sensor data and generating adjustment values cannot be performed by the human mind. However, these steps are considered insignificant extra-solution. The limitation from the sensors are recited at a high level of generality (i.e. as a general means of gathering vehicle and environmental condition data for use in the determine, adjust, and generate limitations), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. The adding of the during startup is just directed to the timing of the data gathering which is still pre-solution activity. Also, the other elements encompasses mental processes practically performed in the human mind by observation, evaluation, judgment, and opinion. While the specification as described by the applicant’s arguments in page 13 gives specific examples, the broadest reasonable interpretation encompasses mental process practically performed by the mind of the observer and the specific examples listed from the specification are not incorporated into the claim.
Regarding sub-argument b, Examiner disagrees. Applicant argues that the claim “is directed to a physical system, complete with hardware and specially designed software, for monitoring and diagnosing startup health of a machine by "determin[ing] a performance standard," "generat[ing], using a machine learning model, adjustment values to adjust the determined performance standard," and "generat[ing] at least one calculated parameter for the machine based on the adjusted performance standard."” The additional elements “generat[ing], using a machine learning model,” limits the identified judicial exceptions “determin[ing] a performance standard” and “generat[ing] at least one calculated parameter for the machine based on the adjusted performance standard” merely confines the use of the abstract idea to a particular technological environment (e.g. machine health monitoring) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h). The generic processor component configuration of e.g. “generat[ing]…” amounts to no more than mere instructions to apply the exception. The applicant argues that the extant solution of not requiring additional sensors is integrating any alleged abstract idea into a practical application, however the removing of sensors in the specification was not reflected in the claim language. Additionally, to the examiner it appears that the lack of sensor is not a technical solution by doing something with less, rather it is an improvement and solution to the abstract idea and applying it.
Regarding sub-argument c, Examiner disagrees. Applicant argues that for instance the machine learning and physics-based models is significantly more. It is acknowledged that these can be an additional element, but it is not enough to be more than applying it. Thus, the 35 U.S.C. §101 rejection remains.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Pho (US Patent Publication 20230203931) discloses methodology that uses the knowledge learned from historical data and real-time data to update a simplified physics-based model (abstract).
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.
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/LORI WU/Primary Examiner, Art Unit 3655
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