CTNF 18/184,898 CTNF 96813 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Status Claims 1-20 are pending. Claims 1-20 are rejected under 35 U.S.C. 101. Claims 1, 3, 5-14, and 16-20 are rejected under 35 U.S.C. 102. Claims 2, 4, and 15 are rejected under 35 U.S.C. 103. Information Disclosure Statement 06-49 AIA The information disclosure statement filed 9/8/2023 fails to comply with the provisions of 37 CFR 1.97, 1.98 and MPEP § 609 because the NPL reference 1 is not legible. The reference has not been considered . It has been placed in the application file, but the information referred to therein has not been considered as to the merits. Applicant is advised that the date of any re-submission of any item of information contained in this information disclosure statement or the submission of any missing element(s) will be the date of submission for purposes of determining compliance with the requirements based on the time of filing the statement, including all certification requirements for statements under 37 CFR 1.97(e). See MPEP § 609.05(a). Priority 02-26 AIA Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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. To determine if a claim is directed to patent ineligible subject matter, the Court has guided the Office to apply the Alice/Mayo test, which requires: 1. Determining if the claim falls within a statutory category; 2A. Determining if the claim is directed to a patent ineligible judicial exception consisting of a law of nature, a natural phenomenon, or abstract idea; and Step 2A is a two prong inquiry. MPEP 2106.04(II)(A). Under the first prong, examiners evaluate whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. Abstract ideas include mathematical concepts, certain methods of organizing human activity, and mental processes. MPEP 2106.04(a)(2). The second prong is an inquiry into whether the claim integrates a judicial exception into a practical application. MPEP 2106.04(d). 2B. If the claim is directed to a judicial exception, determining if the claim recites limitations or elements that amount to significantly more than the judicial exception. (See MPEP 2106). Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite a mental process and/or a mathematical calculation; see MPEP 2106.04(a)(2). Step 1: Claims 1-13 are directed to the statutory category of processes, and claims 14-20 are directed to the statutory category of machines. Claim 1 Step 2A prong 1: For the sake of identifying the abstract ideas, a copy of the claim is provided below. Abstract ideas are bolded. 1. A computer-implemented method for machine learning based classification of operations data representing operations of a plant, the computer-implemented method comprising: receiving the operations data representing the operations of the plant, wherein the operations data is associated with one or more data generation types; applying the operations data to an operations data classification model, wherein the operations data classification model comprises a trained machine learning model that classifies the operations data into one or more classification levels based at least in part on the one or more data generation types; and generating an operations data classification report that is specially configured based at least in part on the one or more classification levels and the operations data. The limitation “ applying the operations data to an operations data classification model, … that classifies the operations data into one or more classification levels based at least in part on the one or more data generation types;” is an abstract idea because it is directed to a mental process, an observation, evaluation, judgment, or opinion. The limitation, as drafted and under broadest reasonable interpretation, “can be performed in the human mind or by a human using a pen and paper”. MPEP 2106.04(a)(2)(III). For example, a human could, mentally or on paper, classify operations data into one or more classification levels based on the data type. Also see July 2024 Subject Matter Eligibility Examples, Example 47 Claim 2. Claim 1 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present general field of use or insignificant extra-solution activity. In particular, the claim recites the additional limitations: “ A computer-implemented method for machine learning based classification of operations data representing operations of a plant, the computer-implemented method comprising:” (general field of use – see MPEP 2106.04(d) referencing MPEP 2106.05(h)), and “receiving the operations data representing the operations of the plant, wherein the operations data is associated with one or more data generation types;“ (insignificant extra-solution activity – mere data gathering MPEP 2106.05(g)). “wherein the operations data classification model comprises a trained machine learning model” (the use of the trained machine learning model is mere instructions to apply an exception as per MPEP 2106.05(f)). “generating an operations data classification report that is specially configured based at least in part on the one or more classification levels and the operations data.” (insignificant extra-solution activity – mere data outputting MPEP 2106.05(g)). Claim 1 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). Also, see MPEP 2106.05(f). Considering the claim limitations as an ordered combination, claim 1 does not include significantly more than the abstract idea. Claim 2 Step 2A prong 2: The claim recites no further abstract ideas. Claim 2 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present general field of use or insignificant extra-solution activity. In particular, the claim recites the additional limitations: “ wherein the one or more data generation types include a source sampling type, a simulation model type, a process-based emission factors type, a survey type, a material balance type, a census-based emission factors type, and an extrapolation type.” (general field of use – see MPEP 2106.04(d) referencing MPEP 2106.05(h)), and Claim 2 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). Considering the claim limitations as an ordered combination, claim 2 does not include significantly more than the abstract idea. Claim 3 Step 2A prong 2: The limitation “ wherein the one or more classification levels comprise a first level, a second level, a third level, a fourth level, and a fifth level . ” is an abstract idea because it is directed to a mental process, an observation, evaluation, judgment, or opinion. The limitation, as drafted and under broadest reasonable interpretation, “can be performed in the human mind or by a human using a pen and paper”. MPEP 2106.04(a)(2)(III). For example, a human could, mentally or on paper, classify operations data into one or more classification levels based on the data type. Also see July 2024 Subject Matter Eligibility Examples, Example 47 Claim 2. Claim 3 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because there are no additional claim elements outside the abstract idea. Claim 3 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). Considering the claim limitations as an ordered combination, claim 3 does not include significantly more than the abstract idea. Claim 4 Step 2A prong 2: The claim recites no further abstract ideas. Claim 4 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present general field of use or insignificant extra-solution activity. In particular, the claim recites the additional limitations: “ wherein the first level is associated with an asset-based reporting, the second level is associated with source-based reporting, the third level is associated with source-based reporting and emissions factors-based reporting, the fourth level is associated with source-based reporting, emissions factors based-reporting, and activity factors-based reporting, and the fifth level is associated with source-based reporting, emissions factors based-reporting, activity factors-based reporting, and plant measurement emissions based-reporting.” (general field of use – see MPEP 2106.04(d) referencing MPEP 2106.05(h)), and Claim 4 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). Considering the claim limitations as an ordered combination, claim 4 does not include significantly more than the abstract idea. Claim 5 Step 2A prong 2: The limitation “ generating a simulation model of the plant based at least in part on historical operations data;” is an abstract idea because it is directed to a mental process, an observation, evaluation, judgment, or opinion. The limitation, as drafted and under broadest reasonable interpretation, “can be performed in the human mind or by a human using a pen and paper”. MPEP 2106.04(a)(2)(III). For example, a human could, mentally or on paper, model a plant based on data. The limitation “ applying the simulation model to generate an emissions dataset, wherein the emissions dataset comprises a training emissions dataset and a test emissions dataset.” is an abstract idea because it is directed to a mental process, an observation, evaluation, judgment, or opinion. The limitation, as drafted and under broadest reasonable interpretation, “can be performed in the human mind or by a human using a pen and paper”. MPEP 2106.04(a)(2)(III). For example, a human could, mentally or on paper, create data based on a model, Claim 5 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because there are no additional claim elements outside the abstract idea. Claim 5 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). Considering the claim limitations as an ordered combination, claim 5 does not include significantly more than the abstract idea. Claim 6 Step 2A prong 2: The limitation “ training the trained machine learning model, wherein training the trained machine learning comprises: applying, by the trained machine learning model, one or more machine learning techniques on the training emissions datasets to generate a trained emissions dataset;” is an abstract idea because it is directed to a mathematical calculation. The limitation, as drafted and under broadest reasonable interpretation, is “ a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation. ”. MPEP 2106.04(a)(2)(I)(C). For example, the training may include a clustering technique such as k-means clustering as described in the specification. The limitation “ comparing the trained emissions dataset to the test emissions dataset” is an abstract idea because it is directed to a mental process, an observation, evaluation, judgment, or opinion. The limitation, as drafted and under broadest reasonable interpretation, “can be performed in the human mind or by a human using a pen and paper”. MPEP 2106.04(a)(2)(III). For example, a human could, mentally or on paper, create data based on a model, compare two sets of data. Claim 6 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because there are no additional claim elements outside the abstract idea. Claim 6 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). Considering the claim limitations as an ordered combination, claim 6 does not include significantly more than the abstract idea. Claim 7 Step 2A prong 2: The limitation “ wherein the one or more machine learning techniques comprises a clustering technique.” is an abstract idea because it is directed to a mathematical calculation. The limitation, as drafted and under broadest reasonable interpretation, is “ a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation. ”. MPEP 2106.04(a)(2)(I)(C). For example, the techniques may include a clustering technique such as k-means clustering as described in the specification. Claim 7 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because there are no additional claim elements outside the abstract idea. Claim 7 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). Considering the claim limitations as an ordered combination, claim 7 does not include significantly more than the abstract idea. Claim 8 Step 2A prong 2: The limitation “ wherein the clustering technique comprises a k-means clustering technique.” is an abstract idea because it is directed to a mathematical calculation. The limitation, as drafted and under broadest reasonable interpretation, is “ a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation. ”. MPEP 2106.04(a)(2)(I)(C). For example, the techniques may include a clustering technique such as k-means clustering as described in the specification. Claim 8 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because there are no additional claim elements outside the abstract idea. Claim 8 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). Considering the claim limitations as an ordered combination, claim 8 does not include significantly more than the abstract idea. Claim 9 Step 2A prong 2: The limitation “ wherein the one or more machine learning techniques comprises a regression technique.” is an abstract idea because it is directed to a mathematical calculation. The limitation, as drafted and under broadest reasonable interpretation, is “ a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation. ”. MPEP 2106.04(a)(2)(I)(C). Claim 9 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because there are no additional claim elements outside the abstract idea. Claim 9 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). Considering the claim limitations as an ordered combination, claim 9 does not include significantly more than the abstract idea. Claim 10 Step 2A prong 2: The claim recites no further abstract ideas. Claim 10 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present general field of use or insignificant extra-solution activity. In particular, the claim recites the additional limitations: “ wherein the operations data classification report includes a plurality of classification sections, each classification section of the plurality of classification sections corresponding to one of the one or more classification levels.” (insignificant extra-solution activity – mere data outputting MPEP 2106.05(g).) Claim 10 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). Considering the claim limitations as an ordered combination, claim 10 does not include significantly more than the abstract idea. Claim 11 Step 2A prong 2: The claim recites no further abstract ideas. Claim 11 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present general field of use or insignificant extra-solution activity. In particular, the claim recites the additional limitations: “ generating a user interface configured to display the operations data classification report.” (insignificant extra-solution activity – mere data outputting MPEP 2106.05(g).) Claim 11 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). Considering the claim limitations as an ordered combination, claim 11 does not include significantly more than the abstract idea. Claim 12 Step 2A prong 2: The claim recites no further abstract ideas. Claim 12 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present general field of use or insignificant extra-solution activity. In particular, the claim recites the additional limitations: “ wherein generating the user interface comprises generating a plurality of classification interface components, each classification interface component configured to automatically display a corresponding classification section of the plurality of classification sections.” (insignificant extra-solution activity – mere data outputting MPEP 2106.05(g).) Claim 12 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). Considering the claim limitations as an ordered combination, claim 12 does not include significantly more than the abstract idea. Claim 13 Step 2A prong 2: The claim recites no further abstract ideas. Claim 13 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present general field of use or insignificant extra-solution activity. In particular, the claim recites the additional limitations: “ wherein each classification interface component is configured to automatically display the operations data classified into the classification level corresponding to the classification interface component.” (insignificant extra-solution activity – mere data outputting MPEP 2106.05(g).) Claim 13 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). Considering the claim limitations as an ordered combination, claim 13 does not include significantly more than the abstract idea. Claim 14 Step 2A prong 1: For the sake of identifying the abstract ideas, a copy of the claim is provided below. Abstract ideas are bolded. 14. An apparatus for machine learning based classification of operations data representing operations of a plant, the apparatus comprising at least one processor and at least one non-transitory memory including computer-coded instructions thereon, the computer coded instructions, with the at least one processor, cause the apparatus to: receive the operations data representing the operations of the plant, wherein the operations data is associated with one or more data generation types; apply the operations data to an operations data classification model, wherein the operations data classification model comprises a trained machine learning model that classifies the operations data into one or more classification levels based at least in part on the one or more data generation types; and generate an operations data classification report that is specially configured based at least in part on the one or more classification levels and the operations data. The limitation “ apply the operations data to an operations data classification model, … that classifies the operations data into one or more classification levels based at least in part on the one or more data generation types;” is an abstract idea because it is directed to a mental process, an observation, evaluation, judgment, or opinion. The limitation, as drafted and under broadest reasonable interpretation, “can be performed in the human mind or by a human using a pen and paper”. MPEP 2106.04(a)(2)(III). For example, a human could, mentally or on paper, classify operations data into one or more classification levels based on the data type. Also see July 2024 Subject Matter Eligibility Examples, Example 47 Claim 2. Claim 14 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present general field of use or insignificant extra-solution activity. In particular, the claim recites the additional limitations: “ An apparatus for machine learning based classification of operations data representing operations of a plant, the apparatus comprising at least one processor and at least one non-transitory memory including computer-coded instructions thereon, the computer coded instructions, with the at least one processor, cause the apparatus to:” (“apply it” – MPEP 2106.05(f)) “receive the operations data representing the operations of the plant, wherein the operations data is associated with one or more data generation types;“ (insignificant extra-solution activity – mere data gathering MPEP 2106.05(g)). “wherein the operations data classification model comprises a trained machine learning model” ( that the use of the trained machine learning model is mere instructions to apply an exception as per MPEP 2106.05(f)). “generate an operations data classification report that is specially configured based at least in part on the one or more classification levels and the operations data.” (insignificant extra-solution activity – mere data outputting MPEP 2106.05(g)). Claim 14 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). See also MPEP 2106.05(f). Considering the claim limitations as an ordered combination, claim 14 does not include significantly more than the abstract idea. Claims 15-18 are rejected in the same way as claims 2, 5-6, and 10. Claim 19 is rejected in the same way as claims 11-13. Claim 20 Step 2A prong 1: For the sake of identifying the abstract ideas, a copy of the claim is provided below. Abstract ideas are bolded. 20. A computer program product for machine learning based classification of operations data representing operations of a plant, the computer program product comprising at least one non-transitory computer-readable storage medium having computer program code stored thereon that, in execution with at least one processor, configures the computer program product for: receiving the operations data representing the operations of the plant, wherein the operations data is associated with one or more data generation types; applying the operations data to an operations data classification model, wherein the operations data classification model comprises a trained machine learning mode l that classifies the operations data into one or more classification levels based at least in part on the one or more data generation types; and generating an operations data classification report that is specially configured based at least in part on the one or more classification levels and the operations data. The limitation “ applying the operations data to an operations data classification model, … that classifies the operations data into one or more classification levels based at least in part on the one or more data generation types;” is an abstract idea because it is directed to a mental process, an observation, evaluation, judgment, or opinion. The limitation, as drafted and under broadest reasonable interpretation, “can be performed in the human mind or by a human using a pen and paper”. MPEP 2106.04(a)(2)(III). For example, a human could, mentally or on paper, classify operations data into one or more classification levels based on the data type. Also see July 2024 Subject Matter Eligibility Examples, Example 47 Claim 2. Claim 20 Step 2A prong 2: Under step 2A prong two, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present general field of use or insignificant extra-solution activity. In particular, the claim recites the additional limitations: “ A computer program product for machine learning based classification of operations data representing operations of a plant, the computer program product comprising at least one non-transitory computer-readable storage medium having computer program code stored thereon that, in execution with at least one processor, configures the computer program product for:” (“apply it” – MPEP 2106.05(f)) “receiving the operations data representing the operations of the plant, wherein the operations data is associated with one or more data generation types;“ (insignificant extra-solution activity – mere data gathering MPEP 2106.05(g)). “wherein the operations data classification model comprises a trained machine learning model” (the use of the trained machine learning model is mere instructions to apply an exception as per MPEP 2106.05(f)). “generating an operations data classification report that is specially configured based at least in part on the one or more classification levels and the operations data.” (insignificant extra-solution activity – mere data outputting MPEP 2106.05(g)). Claim 20 Step 2B: The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations considered directed towards field of use or insignificant extra-solution activity. See MPEP 2106.04(d) referencing MPEP 2106.05(h) and MPEP2106.05(g). See also MPEP 2106.05(f). Considering the claim limitations as an ordered combination, claim 20 does not include significantly more than the abstract idea. Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 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 – 07-08-aia AIA (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. 07-12-aia AIA (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. 07-15 AIA Claim s 1, 3, 5-14, and 16-20 are rejected under 35 U.S.C. 102( a)(1 ) as being anticipated by Shi (US 2022/0358606 A1) . Regarding claim 1, Shi discloses a computer-implemented method for machine learning based classification of operations data representing operations of a plant, the computer-implemented method comprising: ([0020] “Information (e.g., data, software etc.) may be communicated to and/or from a computer and/or a computing device 104” [0023] “Still referring to FIG. 1, local grid monitoring device may be configured to report, using any suitable electronic communication protocol, a plurality of power output quantities of a plurality of power generators in a local grid corresponding to the local grid monitoring device. "Power generators," as used in this disclosure, may include without limitation any kind of power plant or other device contributing to any power grid”) receiving the operations data representing the operations of the plant, wherein the operations data is associated with one or more data generation types ([0022] “Still referring to FIG. 1, local grid monitoring device may be configured to report, using any suitable electronic communication protocol, a plurality of power output quantities of a plurality of power generators in a local grid corresponding to the local grid monitoring device.”) ; applying the operations data to an operations data classification model ([0044] “Continuing to refer to FIG. 3, emissions of an entity such as a company may be classified into three scopes.”) , wherein the operations data classification model comprises a trained machine learning model that classifies the operations data into one or more classification levels based at least in part on the one or more data generation types ([0044] “Scope 1 emissions may include direct emissions from onsite sources. Scope 2 emissions may include indirect emissions from the generation of purchased energy from local grids. Scope 3 emissions may include other indirect emissions (not in Scope 2) that occur in a value chain.” “This approach may harness mathematical models, such as machine-learning models, of real-time emissions and grid carbon intensities, which may be combined with prior knowledge for real-time optimization and control.”) ; and generating an operations data classification report that is specially configured based at least in part on the one or more classification levels and the operations data ([0023] “Still referring to FIG. 1, local grid monitoring device may be configured to report, using any suitable electronic communication protocol, a plurality of power output quantities of a plurality of power generators in a local grid corresponding to the local grid monitoring device.”) . Regarding claim 3, Shi discloses the computer-implemented method of claim 1, and Shi discloses wherein the one or more classification levels comprise a first level, a second level, a third level, a fourth level, and a fifth level (Fig. 10 and [0041] “For example, and without limitation, clustering analysis of monthly peaks may help the user better expect a peak and reduce it.” The data is classified based on the month of the measurement.) . Regarding claim 5, Shi discloses the computer-implemented method of claim 1, and Shi discloses further comprising: generating a simulation model of the plant based at least in part on historical operations data (Fig. 9 The model simulates predicted emissions based on previous data.) ; and applying the simulation model to generate an emissions dataset (Fig. 9 The Forecasted Carbon Intensity as charted is a simulated emissions dataset.) , wherein the emissions dataset comprises a training emissions dataset and a test emissions dataset (0031] “Continuing to refer to FIG. 1, data from power quantities data store may be used to make a plurality of training entries 132, to be used as training data in processes described in further detail below. "Training data," as used herein, is data containing correlations that a machine-learning process may use to model relationships between two or more categories of data elements.” [0035] “Models and/or machine learning processes may be updated and/or validated by benchmarking with ground truth, defined for the purposes of this disclosure as ex-post emission data to ensure model accuracy and reliability; such data may be received, without limitation, from reporting services 136, which may, for instance, provide emission data some period of time, such as a year or more, after real time or batch processes have process outputs.”) . Regarding claim 6, Shi discloses the computer-implemented method of claim 5, and Shi discloses further comprising: training the trained machine learning model (Fig. 12 “Training an Emission Projection Machine-Learning Process Using Training Data Entries”) , wherein training the trained machine learning comprises: applying, by the trained machine learning model, one or more machine learning techniques on the training emissions datasets to generate a trained emissions dataset ([0004] “The method also including training, by the computing device, an emission projection machine-learning process using training data entries, wherein the training data entries comprise correlations between past power output quantities and reported carbon emission data.”) ; and comparing the trained emissions dataset to the test emissions dataset ([0035] “Models and/or machine learning processes may be updated and/or validated by benchmarking with ground truth, defined for the purposes of this disclosure as ex-post emission data to ensure model accuracy and reliability; such data may be received, without limitation, from reporting services 136, which may, for instance, provide emission data some period of time, such as a year or more, after real time or batch processes have process outputs.”) . Regarding claim 7, Shi discloses the computer-implemented method of claim 6, and Shi discloses wherein the one or more machine learning techniques comprises a clustering technique ([0041] “Such analysis may be performed using an unsupervised and/or supervised clustering algorithm, such as without limitation a "k-means clustering algorithm" defined as an algorithm for cluster analysis that partitions n observations or unclassified cluster data entries into k clusters in which each observation or unclassified cluster data entry belongs to the cluster with the nearest mean, using, for instance behavioral training set as described above.”) . Regarding claim 8, Shi discloses the computer-implemented method of claim 7, and Shi discloses wherein the clustering technique comprises a k-means clustering technique ([0041] “Such analysis may be performed using an unsupervised and/or supervised clustering algorithm, such as without limitation a "k-means clustering algorithm" defined as an algorithm for cluster analysis that partitions n observations or unclassified cluster data entries into k clusters in which each observation or unclassified cluster data entry belongs to the cluster with the nearest mean, using, for instance behavioral training set as described above.”) . Regarding claim 9, Shi discloses the computer-implemented method of claim 6, and Shi discloses wherein the one or more machine learning techniques comprises a regression technique ([0047] “Such coefficients may be user entered and/or derived using, without limitation, a machine-learning process trained using historical data, such as a regression algorithm as described in further detail below.”) . Regarding claim 10, Shi discloses the computer-implemented method of claim 1, and Shi discloses wherein the operations data classification report includes a plurality of classification sections (Fig. 10 The data is classified by month. [0042] “In historical visualization tab, emissions may be broken down into different fuel types, showing sources of consumed energy.” The power use may be categorized by source. [0044] The power use can be categorized by “Scope”.) , each classification section of the plurality of classification sections corresponding to one of the one or more classification levels ([0044] “Continuing to refer to FIG. 3, emissions of an entity such as a company may be classified into three scopes.”) . Regarding claim 11, Shi discloses the computer-implemented method of claim 10, and Shi discloses further comprising: generating a user interface configured to display the operations data classification report (Fig. 12 “Displaying on a User Interface a Graphical Comparison of the First Plurality of Projected Carbon Emission Rates”) . Regarding claim 12, Shi discloses the computer-implemented method of claim 11, and Shi discloses wherein generating the user interface comprises generating a plurality of classification interface components (Fig. 9 The use is classified by time of day. Fig. 10 The use is classified by month.) , each classification interface component configured to automatically display a corresponding classification section of the plurality of classification sections (Fig. 9 The use is classified by time of day. Fig. 10 The use is classified by month) . Regarding claim 13, Shi discloses the computer-implemented method of claim 12, and Shi discloses wherein each classification interface component is configured to automatically display the operations data classified into the classification level corresponding to the classification interface component (Fig. 9 The use is classified by time of day. Fig. 10 The use is classified by month) . Regarding claim 14, Shi discloses an apparatus for machine learning based classification of operations data representing operations of a plant, the apparatus comprising at least one processor and at least one non-transitory memory including computer-coded instructions thereon, the computer coded instructions, with the at least one processor, cause the apparatus to: (Abstract “A system for machine-learning for prediction grid carbon emissions includes a computing device configured to” [0097] “Computer system 1300 includes a processor 1304 and a memory 1308 that communicate with each other, and with other components, via a bus 1312.”). The remainder of the claim is rejected in the same way as claim 1. Claim 16 is rejected in the same way as claim 5. Claim 17 is rejected in the same way as claim 6. Claim 18 is rejected in the same way as claim 10. Regarding claim 19, Shi discloses the apparatus of claim 18, and Shi discloses wherein the computer coded instructions, further with the at least one processor, cause the apparatus to: ([0097] “Computer system 1300 includes a processor 1304 and a memory 1308 that communicate with each other, and with other components, via a bus 1312.”) generating a user interface configured to display the operations data classification report (Fig. 12 “Displaying on a User Interface a Graphical Comparison of the First Plurality of Projected Carbon Emission Rates”) , wherein generating the user interface comprises generating a plurality of classification interface components (Fig. 9 The use is classified by time of day. Fig. 10 The use is classified by month.) , each classification interface component configured to automatically display a corresponding classification section of the plurality of classification sections (Fig. 9 The use is classified by time of day. Fig. 10 The use is classified by month) wherein each classification interface component is configured to automatically display the operations data classified into the classification level corresponding to the classification interface component (Fig. 9 The use is classified by time of day. Fig. 10 The use is classified by month) . Regarding claim 20, Shi discloses a computer program product for machine learning based classification of operations data representing operations of a plant, the computer program product comprising at least one non-transitory computer-readable storage medium having computer program code stored thereon that, in execution with at least one processor, configures the computer program product for: (Abstract “A system for machine-learning for prediction grid carbon emissions includes a computing device configured to” [0097] “Computer system 1300 includes a processor 1304 and a memory 1308 that communicate with each other, and with other components, via a bus 1312.” [0099] “In another example, memory 1308 may further include any number of program modules including, but not limited to, an operating system, one or more application programs, other program modules, program data, and any combinations thereof.”). The remainder of the claim is rejected in the same way as claim 1 . Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-23-aia AIA 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. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 07-21-aia AIA Claim (s) 2, 4, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Shi (US 2022/0358606 A1) in view of Hanna et al. “Physics-Guided Multitask Learning for Estimating Power Generation and CO2 Emissions From Satellite Imagery” IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 61, 2023 . Regarding claim 2, Shi discloses the computer-implemented method of claim 1, and Shi discloses wherein the one or more data generation types include a source sampling type ([0042] “In historical visualization tab, emissions may be broken down into different fuel types, showing sources of consumed energy.”) , a simulation model type ([0053] “Using calculated grid carbon intensity models, a time series of carbon intensities denoted by {l(t)} may be derived.”) , a process-based emission factors type ([0042] “In historical visualization tab, emissions may be broken down into different fuel types, showing sources of consumed energy.”) , a material balance type [0042] “In historical visualization tab, emissions may be broken down into different fuel types, showing sources of consumed energy.”) . Shi does not explicitly disclose a survey type, a census-based emission factors type, and an extrapolation type. Hanna teaches a survey type (Section III(A) “They consist of two polar-orbiting satellites and provide multispectral data (13 bands) in the visible, near-infrared, and short-wave infrared parts of the spectrum, with a pixel resolution of up to 10 m. ” Each band is a different survey type of data.) , a census-based emission factors type (Section III(B) “This external dataset contains actual production data (in MW) per generation unit for each European power plant, allowing us to sum the production of all generation units in each plant at the time the satellite image was acquired.” The data includes a census of the power plants and the production of each plant, a emission factor.) , and an extrapolation type (Section III(C) The weather data including wind, humidity, and temperature is used to extrapolate. Each variable is a type of data used for extrapolation.) . Shi and Hanna are analogous because they are from the “same field of endeavor” emissions reporting. Before the effective filing date of the claimed invention, it would have been obvious to one of the ordinary skill in the art, having the teachings of Shi and Hanna before him or her, to modify Shi to include data types as taught by Hanna. The suggestion/motivation for doing so would have been Hanna Introduction ¶ 4 “we propose a method to estimate power generation and CO2 emissions from fossil fuel power plants using observations of plumes acquired by Earth observation (EO) satellites. We focus on power plants given that electricity generation is one of the biggest sources of GHG emissions in Europe [2] and across the world. Moreover, quantifying fossil fuel-based power production is an equally important aspect for climate change monitoring, and more specifically for the energy transition, since the latter aims to minimize the environmental impact of the energy sector and promotes a more sustainable and carbon-free model.” Regarding claim 4, Shi discloses the computer-implemented method of claim 3, but Shi does not disclose wherein the first level is associated with an asset-based reporting, the second level is associated with source-based reporting, the third level is associated with source-based reporting and emissions factors-based reporting, the fourth level is associated with source-based reporting, emissions factors based-reporting, and activity factors-based reporting, and the fifth level is associated with source-based reporting, emissions factors based-reporting, activity factors-based reporting, and plant measurement emissions based-reporting. Hanna teaches wherein the first level is associated with an asset-based reporting (Section III(A) The satellite images of the plants is reporting based on the plant asset.) , the second level is associated with source-based reporting (Section III(B) The power plant metadata describes the power source.) , the third level is associated with source-based reporting and emissions factors-based reporting (Section III(C) The wind data is measured at the source of the power and influences the satellite images of emissions.) , the fourth level is associated with source-based reporting, emissions factors based-reporting, and activity factors-based reporting (Section III(C) The humidity is measured at the power source location and influences the satellite images of emissions and power plant activity.) , and the fifth level is associated with source-based reporting, emissions factors based-reporting, activity factors-based reporting, and plant measurement emissions based-reporting (Fig. 2 The combination of the plurality of data sources is used for emissions reporting.) . Shi and Hanna are analogous because they are from the “same field of endeavor” emissions reporting. Before the effective filing date of the claimed invention, it would have been obvious to one of the ordinary skill in the art, having the teachings of Shi and Hanna before him or her, to modify Shi to include data types as taught by Hanna. The suggestion/motivation for doing so would have been Hanna Introduction ¶ 4 “we propose a method to estimate power generation and CO2 emissions from fossil fuel power plants using observations of plumes acquired by Earth observation (EO) satellites. We focus on power plants given that electricity generation is one of the biggest sources of GHG emissions in Europe [2] and across the world. Moreover, quantifying fossil fuel-based power production is an equally important aspect for climate change monitoring, and more specifically for the energy transition, since the latter aims to minimize the environmental impact of the energy sector and promotes a more sustainable and carbon-free model.” Claim 15 is rejected in the same way as claim 2. Conclusion The examiner respectfully requests, in response to this Office action, support is shown for language added to any original claims on amendment and any new claims. Indicate support for newly added claim language by specifically pointing to page(s) and line number(s) in the specification and/or drawing figure(s). When responding to this Office Action, the applicant is advised to clearly point out the patentable novelty which he or she thinks the claims present, in view of the state of the art disclosed by the references cited or the objections made. He or she must also show how the amendments avoid such references or objections. See 37 CFR 1.111(c). Any inquiry concerning this communication or earlier communications from the examiner should be directed to TROY A MAUST whose telephone number is (571)272-1931. The examiner can normally be reached on Monday-Friday from 8AM to 4PM. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rehana Perveen, can be reached at telephone number (571) 272-3676. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from Patent Center. Status information for published applications may be obtained from Patent Center. Status information for unpublished applications is available through Patent Center for authorized users only. Should you have questions about access to Patent Center, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) Form at https://www.uspto.gov/patents/uspto-automated- interview-request-air-form. /T.A.M./Examiner, Art Unit 2189 /REHANA PERVEEN/Supervisory Patent Examiner, Art Unit 2189 Application/Control Number: 18/184,898 Page 2 Art Unit: 2189 Application/Control Number: 18/184,898 Page 3 Art Unit: 2189 Application/Control Number: 18/184,898 Page 4 Art Unit: 2189 Application/Control Number: 18/184,898 Page 5 Art Unit: 2189 Application/Control Number: 18/184,898 Page 6 Art Unit: 2189 Application/Control Number: 18/184,898 Page 7 Art Unit: 2189 Application/Control Number: 18/184,898 Page 8 Art Unit: 2189 Application/Control Number: 18/184,898 Page 9 Art Unit: 2189 Application/Control Number: 18/184,898 Page 10 Art Unit: 2189 Application/Control Number: 18/184,898 Page 11 Art Unit: 2189 Application/Control Number: 18/184,898 Page 12 Art Unit: 2189 Application/Control Number: 18/184,898 Page 13 Art Unit: 2189 Application/Control Number: 18/184,898 Page 14 Art Unit: 2189 Application/Control Number: 18/184,898 Page 15 Art Unit: 2189 Application/Control Number: 18/184,898 Page 16 Art Unit: 2189 Application/Control Number: 18/184,898 Page 17 Art Unit: 2189 Application/Control Number: 18/184,898 Page 18 Art Unit: 2189 Application/Control Number: 18/184,898 Page 19 Art Unit: 2189 Application/Control Number: 18/184,898 Page 20 Art Unit: 2189 Application/Control Number: 18/184,898 Page 21 Art Unit: 2189 Application/Control Number: 18/184,898 Page 22 Art Unit: 2189 Application/Control Number: 18/184,898 Page 23 Art Unit: 2189 Application/Control Number: 18/184,898 Page 24 Art Unit: 2189 Application/Control Number: 18/184,898 Page 25 Art Unit: 2189 Application/Control Number: 18/184,898 Page 26 Art Unit: 2189 Application/Control Number: 18/184,898 Page 27 Art Unit: 2189 Application/Control Number: 18/184,898 Page 28 Art Unit: 2189 Application/Control Number: 18/184,898 Page 29 Art Unit: 2189 Application/Control Number: 18/184,898 Page 30 Art Unit: 2189 Application/Control Number: 18/184,898 Page 31 Art Unit: 2189 Application/Control Number: 18/184,898 Page 32 Art Unit: 2189 Application/Control Number: 18/184,898 Page 33 Art Unit: 2189 Application/Control Number: 18/184,898 Page 34 Art Unit: 2189 Application/Control Number: 18/184,898 Page 35 Art Unit: 2189
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