DETAILED ACTION
This is the first Office action on the merits of Application No. 18/423,571. Claims 1-20 are pending.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 1/26/2024 has been considered by the examiner.
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;
adjust the determined performance standard using a machine learning model and additional historical data to account for 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.
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]); 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); adjust the determined performance standard using a machine learning model and 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 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; 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; adjusting the determined performance standard using a machine learning model and additional historical data to account for at least one of systemic, equipment, environmental, or geographic variations; generating at least one control parameter to determine at least one calculated parameter for the machine based on the adjusted 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; 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; adjusting, by the at least one processor, the determined performance standard using a machine learning model and additional historical data to account for at least one of systemic, equipment, environmental, or geographic variations; generating, by the at least one processor, at least one calculated parameter for the machine based on the adjusted performance standard; 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 disclose 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).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Narasimalu (US Patent Publication 20250237702) discloses an alternator monitoring system and methods.
Aykol (US Patent Publication 20220074993) discloses a vehicle battery analysis system.
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/LORI WU/Primary Examiner, Art Unit 3655