www.uspto.gov
`
`UNITED STATES DEPARTMENT OF COMMERCE
`United States Patent and TrademarkOffice
`Address: COMMISSIONER FOR PATENTS
`P.O. Box 1450
`Alexandria, Virginia 22313-1450
`
`17/493,793
`
`10/04/2021
`
`Jung Hyun Jun
`
`101940-033500US- 1245233
`
`9615
`
`Trimble (Caterpillar) / Kilpatrick Townsend
`Mailstop: IP Docketing- 22
`1100 Peachtree Street
`Suite 2800
`Atlanta, GA 30309
`
`KNIGHT, CONNOR LEE
`
`PAPER NUMBER
`
`3666
`
`NOTIFICATION DATE
`
`DELIVERY MODE
`
`11/06/2023
`
`ELECTRONIC
`
`Please find below and/or attached an Office communication concerning this application or proceeding.
`
`Thetime period for reply, if any, is set in the attached communication.
`
`Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
`following e-mail address(es):
`
`KTSDocketing2 @ kilpatrick.foundationip.com
`ipefiling @kilpatricktownsend.com
`
`PTOL-90A (Rev. 04/07)
`
`

`

`
`
`Disposition of Claims*
`1-20 is/are pending in the application.
`)
`Claim(s)
`5a) Of the above claim(s) ___ is/are withdrawn from consideration.
`Cj} Claim(s)
`is/are allowed.
`Claim(s) 1-20 is/are rejected.
`S)
`) © Claim(s)___is/are objected to.
`Cj) Claim(s
`are subjectto restriction and/or election requirement
`)
`S)
`* If any claims have been determined allowable, you maybeeligible to benefit from the Patent Prosecution Highway program at a
`participating intellectual property office for the corresponding application. For more information, please see
`http://Awww.uspto.gov/patents/init_events/pph/index.jsp or send an inquiry to PPHfeedback@uspto.gov.
`
`) )
`
`Application Papers
`10)( The specification is objected to by the Examiner.
`11) The drawing(s) filed on 04 October 2021 is/are: a)¥) accepted or b)(_) objected to by the Examiner.
`Applicant may not request that any objection to the drawing(s) be held in abeyance. See 37 CFR 1.85(a).
`Replacement drawing sheet(s) including the correction is required if the drawing(s) is objected to. See 37 CFR 1.121 (d).
`
`Priority under 35 U.S.C. § 119
`12)1) Acknowledgment is made of a claim for foreign priority under 35 U.S.C. § 119(a)-(d)or (f).
`Certified copies:
`_—_c)L) None ofthe:
`b)L) Some**
`a)Q) All
`1.2) Certified copies of the priority documents have been received.
`2.2 Certified copies of the priority documents have been received in Application No.
`3.4.) Copies of the certified copies of the priority documents have been receivedin this National Stage
`application from the International Bureau (PCT Rule 17.2(a)).
`* See the attached detailed Office action for a list of the certified copies not received.
`
`Attachment(s)
`
`1)
`
`Notice of References Cited (PTO-892)
`
`Information Disclosure Statement(s) (PTO/SB/08a and/or PTO/SB/08b)
`2)
`Paper No(s)/Mail Date Attached,
`U.S. Patent and Trademark Office
`
`3)
`
`(LJ Interview Summary (PTO-413)
`Paper No(s)/Mail Date
`4) (J Other:
`
`PTOL-326 (Rev. 11-13)
`
`Office Action Summary
`
`Part of Paper No./Mail Date 20231016
`
`Application No.
`Applicant(s)
`17/493,793
`Jun etal.
`
`Office Action Summary Art Unit|AIA (FITF) StatusExaminer
`ConnorL Knight
`3666
`Yes
`
`
`
`-- The MAILING DATEof this communication appears on the cover sheet with the correspondence address --
`Period for Reply
`
`A SHORTENED STATUTORY PERIOD FOR REPLYIS SET TO EXPIRE 3 MONTHS FROM THE MAILING
`DATE OF THIS COMMUNICATION.
`Extensions of time may be available underthe provisions of 37 CFR 1.136(a). In no event, however, may a reply betimely filed after SIX (6) MONTHSfrom the mailing
`date of this communication.
`If NO period for reply is specified above, the maximum statutory period will apply and will expire SIX (6) MONTHSfrom the mailing date of this communication.
`-
`- Failure to reply within the set or extended period for reply will, by statute, cause the application to become ABANDONED (35 U.S.C. § 133).
`Any reply received by the Office later than three months after the mailing date of this communication, evenif timely filed, may reduce any earned patent term
`adjustment. See 37 CFR 1.704(b).
`
`Status
`
`1) Responsive to communication(s) filed on 04 October 2021.
`C) A declaration(s)/affidavit(s) under 37 CFR 1.130(b) was/werefiled on
`
`2a)() This action is FINAL. 2b)¥)This action is non-final.
`3)02 An election was madeby the applicant in responseto a restriction requirement set forth during the interview
`on
`; the restriction requirement and election have been incorporated into this action.
`4)\0) Since this application is in condition for allowance except for formal matters, prosecution as to the merits is
`closed in accordance with the practice under Exparte Quayle, 1935 C.D. 11, 453 O.G. 213.
`
`

`

`Application/Control Number: 17/493,793
`Art Unit: 3666
`
`Page 2
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`DETAILED ACTION
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`Notice of Pre-AlA orAIA Status
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`The present application, filed on or after March 16, 2013,
`
`is being examined under thefirst
`
`inventorto file provisions of the AIA.
`
`Information Disclosure Statement
`
`The referenceslisted on the information disclosure statementfiled on 1/6/2022 and 2/24/2023
`
`have been considered by the Examiner.
`
`Claim Objections
`
`Claim(s) 11 is/are objected to because of the following informalities:
`
`e
`
`Claim 11 recites the limitations “capturing a vibration signal that is indicative of a movementof
`
`an implement of a construction machine; extracting one or more features from the vibration
`
`signal; providing the one or more features to a machine-learning model to generate a model
`
`output; and predicting an implement-on-ground (lOG) start time and an lOG end time based on
`
`the madel output, the |OG start time and the |OG end time forming the period during which the
`
`implementis interacting with the ground surface”. Claim 11is a system claim, however,it includes
`
`limitations written in method claim format using gerunds (i.e. words ending in "ing"). Claim 11
`
`should be consistent with a system claim format. For example, claim 11 should recite “capturea
`
`vibration signal that is indicative of a movement of an implement of a construction machine...”.
`
`Appropriate correction is required.
`
`Claim Rejections - 35 USC § 101
`
`35 U.S.C. 101 reads as follows:
`
`

`

`Application/Control Number: 17/493,793
`Art Unit: 3666
`
`Page 3
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`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 requirementsof 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.
`
`In January, 2019 (updated October 2019), the USPTO released new examination guidelines
`
`setting forth a two-step inquiry for determining whether a claimis directed to non-statutory subject
`
`matter. According to the guidelines, a claimis directed to non-statutory subject matter if:
`
`e
`
`STEP 1: the claim does notfall within one of the four statutory categories of invention
`
`(process, machine, manufacture or composition of matter), or
`
`e
`
`STEP 2: the claim recites a judicial exception, e.g., anabstract idea, without reciting
`
`additional elements that amountto significantly more than the judicial exception, as
`
`determined using the following analysis:
`
`o
`
`STEP2A (PRONG1): Does the claim recite an abstract idea, law of nature, or natural
`
`phenomenon?
`
`o
`
`STEP2A (PRONG2): Doesthe claim recite additional elements that integrate the
`
`judicial exception into a practical application?
`
`o
`
` STEP2B: Does theclaim recite additional elements that amountto significantly
`
`more than the judicial exception?
`
`Using the two-step inquiry, it is clear that the claims are directed toward non-statutory subject
`
`matter, as shown below:
`
`STEP 1: Do the claimsfall within one of the statutory categories ? Yes. Claims 1-10 are directed
`
`towards a method,i.e., process. Claims 11-19 are directed towards a system,i.e., machine. Claim 20 is
`
`directed towards a method,i.e., process.
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`

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`Application/Control Number: 17/493,793
`Art Unit: 3666
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`Page 4
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`STEP 2A (PRONG1): Is the claim directed to a law of nature, anatural phenomenon oran
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`abstract idea? Yes, the claims are directed to an abstract idea.
`
`With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter
`
`that are considered abstractideas:
`
`1. Mathematical concepts — mathematical relationships, mathematical formulas or equations,
`
`mathematical calculations;
`
`2. Certain methods of organizinghuman activity —fundamental economic principles or
`
`practices (including hedging, insurance, mitigating risk); commercial or legal interactions
`
`(including agreements inthe form of contracts; legal obligations; advertising, marketing or
`
`sales activities or behaviors; business relations); managing personal behavior or
`
`relationships or interactions between people (including social activities, teaching, and
`
`following rules or instructions); and
`
`3. Mental processes — concepts that are practicably performed in the human mind(including
`
`an observation, evaluation, judgment, opinion).
`
`The method in claims 1-10 (also, the system and method in claims 11-19 and 20, respectively)is
`
`a mental process that can be practicably performed in the human mind and, therefore, an abstract idea.
`
`With regard to independentclaims 1 and 11, the method/system (or computer implemented
`
`functionality) recites the steps of: (a) extracting one or more features from the vibration signal and (b)
`
`predicting an implement-on-ground (lOG) start time and an |OG end time based on the model output,
`
`the |OG start time and the lOG end time forming the period during which the implementis interacting
`
`with the ground surface. With regard to independentclaim 20, the method/system (or computer
`
`implemented functionality) recites the steps of: (a) determining aset of implement-on-ground (lOG)
`
`candidates corresponding totimes at which the implementis interacting with the ground surface, (b)
`
`determining a set of implement-in-air (IIA) candidates corresponding to times at which the implementis
`
`

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`Application/Control Number: 17/493,793
`Art Unit: 3666
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`Page5S
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`not interacting with the ground surface, and (c) and predicting an |OG start time and an|lOG end time
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`based on the set of IOG candidates and the set of IIA candidates, the |OG start time and the 1|OG end
`
`time forming the period during which the implementis interacting with the ground surface. These
`
`limitations, under their broadest reasonable interpretation, cover performance of the limitations in the
`
`mind. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process
`
`(thinking) that "canbe performed in the human mind, or by a human using a pen and paper" to be an
`
`abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695
`
`(Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which
`
`are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific
`
`and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694(citing Gottschalkv.
`
`Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs.
`
`Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes [] and abstract intellectual concepts
`
`are not patentable, as they are the basic tools of scientific and technological work’"
`
`(quoting Benson, 409 U.S. at 67, 175 USPQ at 675)): Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193,
`
`197 (1978) (same). For example, a person that has been provided vibration signal data can mentally
`
`extract, e.g., determine, one or more features about the vibration signal and predict an implement-on-
`
`ground (lOG) start time and an |OG end time based on a model output, either mentally or using a pen
`
`and paper. Additionally, a personcan mentally determine implement-on-ground candidates and
`
`implement-in-air candidates. The mere nominal recitation that the processing operations are being
`
`performed by one or more processors(i.e., computer) does not take the limitation out of the mental
`
`process grouping. Thus, the claim recites a mental process.
`
`

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`Application/Control Number: 17/493,793
`Art Unit: 3666
`
`Page 6
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`STEP 2A (PRONG2): Doesthe claim recite additional elements that integrate the judicial
`
`exception into a practical application? No, the claim does not recite additional elements that integrate
`
`the judicial exception into a practical application.
`
`With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate
`
`the judicial exception into a practical application, the guidelines provide the following exemplary
`
`considerations that are indicative that an additional element (or combination of elements) may have
`
`integrated the judicial exception into a practical application:
`
`e
`
`anadditional element reflects an improvementin the functioning of a computer, or an
`
`improvementto other technology or technical field;
`
`e
`
`anadditional element that applies or uses a judicial exception to effect a particular
`
`treatment or prophylaxis for a disease or medical condition;
`
`e
`
`anadditional element implements a judicial exception with, or uses a judicial exception in
`
`conjunction with, a particular machine or manufacturethat is integral to the claim;
`
`e
`
`anadditional element effects a transformation or reduction of a particular articletoa
`
`different state or thing; and
`
`e
`
`anadditional element applies or uses the judicial exception in some other meaningful way
`
`beyond generally linking the use of the judicial exception to a particular technological
`
`environment, such that the claimas a whole is more than a drafting effort designed to
`
`monopolize the exception.
`
`While the guidelines further state that the exemplary considerations are not an exhaustivelist
`
`and that there may be other examplesof integrating the exception into a practical application, the
`
`guidelines alsolist examples in which a judicial exception has not been integrated into a practical
`
`application:
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`

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`Art Unit: 3666
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`Page 7
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`¢
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`anadditional element merely recites the words “apply it” (or an equivalent) with the judicial
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`exception, or merely includes instructions to implement an abstract idea on a computer, or
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`merely uses a computer as a tool to perform an abstractidea;
`
`e
`
`e
`
`anadditional element addsinsignificant extra-solution activity to the judicial exception; and
`
`anadditional element does no more than generally link the use of a judicial exception toa
`
`particular technological environmentorfield of use.
`
`With regardto claim 1, data gathering is a form ofinsignificant extra-solution activity. See MPEP
`
`2106.05(g). Capturing a vibration signal that is indicative of a movement of the implement, is mere data
`
`gathering. Therefore, capturing a vibration signal that is indicative of a movement of the implementis
`
`insignificant extra-solution activity. In addition, outputting data is insignificant extra-solution activity.
`
`See MPEP 2106.05(g). Providing the one or more features toa machine-learning model to generatea
`
`model output, as claimed, is outputting data. Therefore, providing the one or more features toa
`
`machine-learning model to generate a model outputis insignificant extra-solution activity. Therefore,
`
`claim 1 does not recite additional elements that integrate the judicial exception into a practical
`
`application.
`
`Claim 11 recites the additional limitations of a “one or more processors” and “a computer-
`
`readable medium comprising instructions that, when executed by the one or more processors, cause the
`
`one or more processors to perform operations”. These limitations of one or more processors anda
`
`computer-readable medium comprising instructions are simply a computer recited at a high level of
`
`generality. The generic computer is used to perform the abstract idea. Using a computer as a tool to
`
`perform the abstract idea does not integrate the exception into a practical application. Data gatheringis
`
`a form ofinsignificant extra-solution activity. See MPEP 2106.05(g). Capturing a vibration signal that is
`
`indicative of amovementof the implement, is mere data gathering. Therefore, capturing a vibration
`
`signal that is indicative of a movementof the implementis insignificant extra-solution activity. In
`
`

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`Application/Control Number: 17/493,793
`Art Unit: 3666
`
`Page 8
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`addition, outputting data is insignificant extra-solution activity. See MPEP 2106.05(g). Providing the one
`
`or more features to a machine-learning model togenerate a madel output, as claimed, is outputting
`
`data. Therefore, providing the one or more features toa machine-learning model to generate a model
`
`output is insignificant extra-solution activity. Therefore, claim 11 does not recite additional elements
`
`that integrate the judicial exception into a practical application.
`
`With regardto claim 20, data gathering is a form ofinsignificant extra-solution activity. See
`
`MPEP 2106.05(g). Capturing a vibration signal that is indicative of a movementof the implement, is
`
`mere data gathering. Therefore, capturing a vibration signal that is indicative of a movement of the
`
`implementis insignificant extra-solution activity. Therefore, claim 20 does not recite additional elements
`
`that integrate the judicial exception into a practical application.
`
`STEP 2B: Doesthe claim recite additional elements that amount tosignificantly more than the
`
`judicial exception? No, the claim does not recite additional elements that amount tosignificantly more
`
`than the judicial exception.
`
`With regardto STEP 2B, whether the claimsrecite additional elements that provide significantly
`
`more than the recited judicial exception, the guidelines specify that the pre-guideline procedureis still in
`
`effect. Specifically, that examiners should continue to consider whether an additional element or
`
`combination of elements:
`
`e
`
`adds aspecific limitation or combination of limitations that are not well-understood, routine,
`
`conventional activity in the field, which is indicative that an inventive concept may be present;
`
`or
`
`e
`
`simply appends well-understood, routine, conventional activities previously known to the
`
`industry, specified at a high level of generality, to the judicial exception, which is indicative that
`
`an inventive concept may not be present.
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`

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`Application/Control Number: 17/493,793
`Art Unit: 3666
`
`Page 9
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`The following computer functions have been recognized as well-understood, routine, and
`
`conventional functions when they are claimed in a merely generic manner (e.g., at a high level of
`
`generality): receiving or transmitting data over a network. See MPEP 2106.05(d)(II). Providing the one or
`
`more features to a machine-learning model is transmitting data over a network(i.e., from one
`
`computing device networked to another computing device). Therefore, the limitation “Providing the one
`
`or more features to a machine-learning model togenerate a model output” is well-understood, routine,
`
`conventional activity in the field and does not recite additional elements that amountto significantly
`
`more than the judicial exception.
`
`CONCLUSION
`
`Thus, since claims 1, 11, and 20 are: (a) directed toward an abstract idea, (b) does not recite
`
`additional elements that integrate the judicial exception into a practical application, and (c) does not
`
`recite additional elements that amountto significantly more than the judicial exception, it is clear that
`
`claims 1, 11, and 20 are directed towards non-statutory subject matter.
`
`Further, dependent claims 2-10 and 12-19 further limit the abstract idea without integrating the
`
`abstract idea into practical application or adding significantly more. Each of the claimed limitations
`
`either expand upon or add either 1) new mental process, 2) a new additional element, 3) previously
`
`presented mental process, and/or 4) a previously presented additional element. As such, claims 2-10
`
`and 12-19 are similarly rejected as being directed towards non-statutory subject matter.
`
`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-AlA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for
`
`

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`Application/Control Number: 17/493,793
`Art Unit: 3666
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`Page 10
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`the rejection will not be considered a new ground ofrejection 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 claimedinvention 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.
`
`The factual inquiries for establishing a background for determining obviousness under 35 U.S.C.
`
`103 are summarized as follows:
`
`1. Determining the scope and contents of the prior art.
`
`2. Ascertaining the differences between the prior art and the claims at issue.
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`3. Resolving the level of ordinary skill in the pertinent art.
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`4. Considering objective evidence present
`
`in
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`the application indicating obviousness or
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`nonobviousness.
`
`Claim(s) 1-2, 4-5, 8, 11-12, 14, 17, and 19 is/are rejected under 35 U.S.C. 103 as being
`
`unpatentable over Kamonetal. (US 20220220709 A1) in view of Yamada etal. (US 20170314987 A1).
`
`Regarding claims 1 and 11, Kamon teaches asystemcomprising: one or moreprocessors(see at
`
`least 4[0158] and [0286]
`
`regarding a processor); and a computer-readable medium comprising
`
`instructions (see abstract and at least [0141], [0158], [0272], and [0286] regarding a memory and a
`
`program storedin the memory) that, when executed by the one or more processors, cause the one or
`
`moreprocessors to perform operations comprising: capturing a vibration signal that is indicative of a
`
`movement of an implement ofa construction machine (see at least [0155], [0181]-[0182], [0189], [0285],
`
`and [0328]-[0329] regarding a gyroscope detecting vibration of the machine/swiveling body/body part
`
`which is output as reaction data (e.g., reaction force from the ground)); extracting one or more features
`
`

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`Application/Control Number: 17/493,793
`Art Unit: 3666
`
`Page 11
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`from the vibration signal (see at least 4[0189]-[0190], [0320], and [0336]-[0337] regarding a reaction or
`
`reaction data including hardness of the ground(i.e., feature)); providing the one or more features to a
`
`machine-learning model to generate a model output (see at least 4[0189]-[0194], [0337]-[0339], and
`
`[0344] regarding determining the next manipulation based on reaction data magnitude which is acquired
`
`as learning data and inputted into a learning module (i.e., machine learning), the learning module then
`
`outputs the estimated operation command).
`
`Kamonfails to teach predicting an implement-on-ground (lOG) start time and an |OG end time
`
`based on the modeloutput, the lOG start time and the |OG end time forming the period during which
`
`the implement is interacting with the ground surface. However, Yamada discloses an attachment
`
`monitoring system and teaches predicting an implement-on-ground(IOG) start time and an |OG end
`
`time based on the model output, the 1OG start time and the lOG end time forming the period during
`
`which the implement is interacting with the ground surface (see Fig. 7A-B “estimation of operation states
`
`of the breaker” as well as at least 4[0122]-[0123] regarding an operation state of the breaker may be
`
`estimated using a determination model; additionally, see at least [0003], [0043], [0102], and [0105]
`
`regarding estimating time widths and monitoring operation time of a construction machine).
`
`It would have been obvious to one of ordinaryskillin the art before the effective filing date of the
`
`claimed invention to have modified the construction machinery with learning function of Kamon to
`
`provide, with a reasonable expectation of success, predicting an implement-on-ground (IOG) start time
`
`and an I|OG end time based on the madel output, the |OG start time and the |OG end time forming the
`
`period during which the implementis interacting with the ground surface, as taught by Yamada, to provide
`
`monitoring the operating state of the machine to provide a monitored result which can assist each
`
`relevant person suchas maintenance person, a salesperson, or end user sothat the quality of an operation
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`activity is improved. (Yamada at 4|[0046])
`
`

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`Application/Control Number: 17/493,793
`Art Unit: 3666
`
`Page 12
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`Regarding claims 2 and 12, Kamon teaches wherein the vibration signal is captured using a
`
`vibration sensor mounted to the construction machine (see at least [0155] and [0285] regarding a
`
`swiveling body or the body part of the hydraulic excavator that is provided with a gyroscope).
`
`Regarding claim 4, Kamon teaches wherein the vibration sensor includes a gyroscope and the
`
`vibration signalincludes a rotation signal (see at least [0155] and [0285] regarding a swiveling body or
`
`the body part of the hydraulic excavator that is provided with a gyroscope that detects an inclination (i.e.,
`
`rotation)).
`
`Regarding claims 5 and 14, Kamonfails to teach wherein the vibration sensor is mountedto the
`
`implement. However, Yamada discloses an attachment monitoring system and teaches wherein the
`
`vibration sensor is mounted to the implement (see Fig. 1B and 2A which shows the measurementunit
`
`attached to an arm and attachment as well as 4[0033] and [0110] regarding a measurement unit being
`
`attached to anarm which holds an attachment).
`
`It would have been obvious to one of ordinary skillin the art before the effective filing date of the
`
`claimed invention to have modified the construction machinery with learning function of Kamon to
`
`provide, with a reasonable expectation of success, wherein the vibration sensor is mounted to the
`
`implement, as taught by Yamada, to provide measuring at least one of a vibration and the fluid pressure
`
`when each of the attachments is driven. (Yamada at ][0009])
`
`Regarding claims 8 and 17, Kamon teaches wherein the one or more featuresinclude at least
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`one of signalamplitude featuresor signal frequency features (see at least 4[0128]-[0130] regarding the
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`frequency analysis of the vibration data or generating a frequency spectrum ofthe vibration).
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`

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`Application/Control Number: 17/493,793
`Art Unit: 3666
`
`Page 13
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`Regarding claim 19, Kamon teaches wherein the IOG start time and the |IOG end time are
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`predicted further based on a set of implement positions (see at least 4 [0016]-[0017], [0180]-[0182], and
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`[0321] regarding current manipulated positions which is one example of information indicating the
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`operation state of the hydraulic excavator).
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`Claim(s) 3 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kamonetal. (US
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`20220220709 A1) in view of Yamadaetal. (US 20170314987A1), as applied to claims 2 and 12 above, and
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`in further view of Kowalchuk (US 20140196919 A1).
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`Regarding claims 3 and 13, the combination of Kamon and Yamada fails to teach wherein the
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`vibration sensor includes an accelerometer and the vibration signal includes an acceleration signal.
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`However, Kowalchuk discloses a system and method of tractor control based on agricultural implement
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`performance and teaches wherein the vibration sensor includes an accelerometer and the vibration
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`signalincludes an acceleration signal (see at least 4[0008] and [0029] regarding a vibration sensor being
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`an accelerometer configured to generate a plurality of feedback signals, each feedback signal
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`corresponding to an axis of motion).
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`It would have been obvious to one of ordinary skillin the art before the effective filing date of the
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`claimed invention to have modified the construction machinery with learning function of Kamon as
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`modified by Yamada to provide, with a reasonable expectation of success, wherein the vibration sensor
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`includes an accelerometer and the vibration signal
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`includes an acceleration signal, as taught by
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`Kowalchuk, to provide detecting a magnitude of a vibration. (Kowalchuk at 4][0029])
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`Claim(s) 6-7 and 15-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kamon et
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`al. (US 20220220709 A1) in view of Yamada et al. (US 20170314987 A1), as applied to claims 2 and 12
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`above, and in further view of Hamada etal. (US 20210292999 A1).
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`

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`Application/Control Number: 17/493,793
`Art Unit: 3666
`
`Page 14
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`Regarding claims 6 and 15, the combination of Kamon and Yamada fails to teach wherein the
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`model output includes a set of 1OG candidates corresponding to times at which the implement is
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`interacting with the ground surface. However, Hamada discloses a state data acquisition unit which
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`acquires state data of a work machineat a plurality of times and teaches wherein the model output
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`includesa set of |OG candidates corresponding totimes at which the implement is interacting with the
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`ground surface(see at least Fig. 7 and Fig. 9 as well as 4[0121]-[0123] regarding likelihood time series
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`related to the unit works and element works; for example, excavation and scraping are |OG candidates).
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`It would have been obvious to one of ordinary skillin the art before the effective filing date of the
`
`claimed invention to have modified the construction machinery with learning function of Kamon as
`
`modified by Yamada to provide, with a reasonable expectation of success, wherein the model output
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`includes a set of |OG candidates corresponding to times at which the implementis interacting with the
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`ground surface, as taught by Hamada, to provide determining the likelinood of a classification of machine
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`work activity and whether it is high or low at that specific time. (Hamada at 4[0122])
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`Regarding claims 7 and 16, the combination of Kamon and Yamada fails to teach wherein the
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`modeloutput includes a set of 2 implement-in-air (IIA) candidates corresponding to times at which the
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`implement is not interacting with the ground surface. However, Hamada discloses a state data
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`acquisition unit which acquires state data of a work machine ata plurality of times and teaches wherein
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`the modeloutput includes a set of 2 implement-in-air (IIA) candidates correspondingto times at which
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`the implementis notinteracting with the ground surface (see at least Fig. 7 and Fig. 9 as well as 4[0121]-
`
`[0123] regarding likelihood time series related to the unit works and element works; for example,
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`dumping and empty load swing are IIA candidates).
`
`It would have been obvious to one of ordinary skillin the art before the effective filing date of the
`
`claimed invention to have modified the construction machinery with learning function of Kamon as
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`

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`Application/Control Number: 17/493,793
`Art Unit: 3666
`
`Page 15
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`modified by Yamada to provide, with a reasonable expectation of success, wherein the model output
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`includes a set of 2 implement-in-air (IIA) candidates corresponding totimes at whichthe implementis not
`
`interacting with the ground surface, as taught by Hamada, to provide determining the likelihood of a
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`classification of machine workactivity and whether it is high or low at that specific time. (Hamada at
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`4[0122])
`
`Claim(s) 9 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kamonetal. (US
`
`20220220709 A1) in view of Yamadaetal. (US 20170314987A1), as applied to claims 2 and 12 above, and
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`in further view of Hurd et al. (US 20200326715 A1).
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`Regarding claims 9 and 18, the combination of Kamon and Yamada fails to teach wherein the
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`machine-learning model is a pre-trained support-vector machine. However, Hurd discloses a safety
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`system for autonomous operation of off-road and agricultural vehicles using machine learning for
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`detection and identification of obstacles and teaches wherein the machine-learning modelis a pre-
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`trained support-vector machine (see at least [0007], [0024], [0027], [0030], [0040], and [0044] regarding
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`one or moretrained neural networks).
`
`It would have been obvious to one of ordinary skillin the art before the effective filing date of the
`
`claimed invention to have modified the construction machinery with learning function of Kamon as
`
`modified by Yamada to provide, with a reasonable expectation of success, whereinthe machine-learning
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`model is a pre-trained support-vector machine, as taught by Hurd, to provide accurately interpreting data
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`for enabling such safe operation of machinery in response to de