DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed 12/29/2025 have been fully considered but they are not persuasive.
Regarding the 101 rejection, the applicant submits that the underlying idea in the amended claim is not merely an abstract idea and additional elements or combination of elements in the claim are sufficient to ensure that the claim amounts to significantly more than the judicial exception. Further that the amended claim integrates the alleged abstract idea into practical application. The examiner respectfully disagrees.
Regarding Claim 1, the examiner relies upon MPEP 2106.04(d) to determine whether a claim amounts to significantly more and integrates the abstract idea into a practical application. The amendments with respect to this assumption fail to integrate the claim into a practical application. In the preamble, the amendment of “issuing a heatwave warning” is considered by MPEP 2106.05(g) as insignificant extra solution activity, mere data outputting. Further this amendment isn’t discloses in the claim limitations. Nowhere does it state the outputting of the warning. There is a limitation that discloses determining whether to issue the warning, but fails to discloses issuing the actual warning itself upon determination. Further, issuing the warning itself is not an improvement in technology or the field. It is merely an outputting a result, failing to include how the output brought about an improvement. The new limitations including a trained model and a clustering algorithm which is an unsupervised machine learning algorithm using generic AI/ML technology to perform data evaluations or calculations, as identified under Prong 1. The claims do not recite any details regarding how the AI/ML algorithm or model functions or is trained. Instead, the claims are found to utilize the AI/ML algorithm as a tool that provides nothing more than mere instructions to implement the abstract idea on a general purpose computer. See MPEP 2106.05(f). Additionally, the clam limitation merely indicates a field of use or technological environment in which the judicial exception is performed. See MPEP 2106.05(h) and the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence; and Example 47, ineligible claim 2. It is for this reason, the examiner maintains the 101 rejection.
Special Definitions
Consistent with the well-established axiom in patent law that a patentee or applicant is free to be his or her own lexicographer, a patentee or applicant may use terms in a manner contrary to or inconsistent with one or more of their ordinary meanings if the written description clearly redefines the terms. See MPEP 2173.05(a).III
Applicant has defined a “sensible temperature” as an atmospheric temperature obtained by adding 3.0 °C to an estimated wet-bulb globe temperature in paragraph [0007].
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: An apparatus for issuing a heatwave warning by calculating a sensible temperature in consideration of outdoor ground heating, the apparatus comprising: a classifier configured to classify data which includes a globe temperature, an atmospheric temperature, a relative humidity, and a ground surface temperature and is observed by an automated synoptic observing system (ASOS) for a certain period of time, as precipitation data and non-precipitation data according to whether there is precipitation; a clustering part configured to cluster the non-precipitation data into K clusters; and an analysis part configured to derive K+1 sensible temperature calculation formulae by performing regression analysis on the K clusters and the precipitation data; a predictor configured to classify new input data as anon-precipitation data group or a precipitation data group by using a classification model for data classification, the classification model being a model trained in advance using training data, select one of the K+1 sensible temperature calculation formulae based on the classification result, and predict a sensible temperature for the new input data based on the selected sensible temperature calculation formula; and a determiner configured to determine whether to issue the heatwave warning based on the predicted sensible temperature, wherein the clustering part is further configured to cluster the non-precipitation data into the K clusters by using a K-means clustering algorithm which is an unsupervised machine learning algorithm for clustering data having similar features into the K clusters in claim 8.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-2, 4-9 and 11-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Specifically, representative Claim 1 recites:
A method of issuing a heatwave warning calculating a sensible temperature in consideration of outdoor ground heating, the method comprising: classifying data which includes a globe temperature, an atmospheric temperature, a relative humidity, and a ground surface temperature and is observed by an automated synoptic observing system (ASOS) for a certain period of time, as precipitation data and non-precipitation data according to whether there is precipitation;
clustering the non-precipitation data into K clusters; and
deriving K+1 sensible temperature calculation formulae by performing regression analysis on the K clusters and the precipitation data;
classifying new input data as a non-precipitation data group or a precipitation data group by using a classification model for data classification, the classification model being a model trained in advance using training data, selecting one of the K+1 sensible temperature calculation formulae based on the classification result, and predicting a sensible temperature for the new input data based on the selected sensible temperature calculation formula; and
determining whether to issue the heatwave warning based on the predicted sensible temperature, wherein the clustering of the non-precipitation data into the K clusters comprises clustering the non-precipitation data into the K clusters by using a K-means clustering algorithm which is an unsupervised machine learning algorithm for clustering data having similar features into the K clusters.
Similar limitations comprise the abstract ideas of Claims 8. Further, Claim 15 recites:
A heatwave warning method based on a sensible temperature in consideration of outdoor ground heating, the heatwave warning method comprising:
classifying new input data into a group and cluster as anon-precipitation data group or a precipitation data group by using a classification model for data classification, the classification model being a model trained in advance using training data;
selecting one of a plurality of prestored sensible temperature calculation formulae based on the basis of the classified group and cluster classification result; predicting a sensible temperature for the new input data using the selected sensible temperature calculation formula; and
determining whether to issue a heatwave warning based on the basis of the predicted sensible temperature, wherein the plurality of sensible temperature calculation formulae are derived by classifying data which includes a globe temperature, an atmospheric temperature, a relative humidity, and a ground surface temperature and is observed by an automated synoptic observing system (ASOS) for a certain period of time, as precipitation data and non-precipitation data according to whether there is precipitation, clustering the non-precipitation data into K clusters, and then performing regression analysis on the K clusters and the precipitation data, and wherein the clustering of the non-precipitation data into the K clusters comprises clustering the non-precipitation data into the K clusters by using a K-means clustering algorithm which is an unsupervised machine learning algorithm for clustering data having similar features into the K clusters.
Similar limitations comprise the abstract ideas of Claims 16.
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements”.
Under the Step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter. The above claim is considered to be in a statutory category (process).
Under the Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, it falls into the grouping of subject matter when recited as such in a claim limitation, that covers mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) and mental processes – concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion.
For example, steps of “clustering the non-precipitation data into K clusters; and deriving K+1 sensible temperature calculation formulae by performing regression analysis on the K clusters and the precipitation data” are treated by the Examiner as belonging to mathematical concept grouping, while the steps of “classifying data which includes a globe temperature, an atmospheric temperature, a relative humidity, and a ground surface temperature and is observed by an automated synoptic observing system (ASOS) for a certain period of time, as precipitation data and non-precipitation data according to whether there is precipitation; classifying new input data as a non-precipitation data group or a precipitation data group by using a classification model for data classification, the classification model being a model trained in advance using training data, selecting one of the K+1 sensible temperature calculation formulae based on the classification result, and predicting a sensible temperature for the new input data based on the selected sensible temperature calculation formula and determining whether to issue the heatwave warning based on the predicted sensible temperature, wherein the clustering of the non-precipitation data into the K clusters comprises clustering the non-precipitation data into the K clusters by using a K-means clustering algorithm which is an unsupervised machine learning algorithm for clustering data having similar features into the K clusters” are treated as belonging to mental process grouping and/or mathematical concept grouping.
An additional example regarding Claim 15, steps of “classifying new input data into a group and cluster as anon-precipitation data group or a precipitation data group by using a classification model for data classification, the classification model being a model trained in advance using training data;
selecting one of a plurality of prestored sensible temperature calculation formulae based on the basis of the classified group and cluster classification result; predicting a sensible temperature for the new input data using the selected sensible temperature calculation formula; and
determining whether to issue a heatwave warning based on the basis of the predicted sensible temperature, wherein the plurality of sensible temperature calculation formulae are derived by classifying data which includes a globe temperature, an atmospheric temperature, a relative humidity, and a ground surface temperature and is observed by an automated synoptic observing system (ASOS) for a certain period of time, as precipitation data and non-precipitation data according to whether there is precipitation, clustering the non-precipitation data into K clusters, and then performing regression analysis on the K clusters and the precipitation data, and wherein the clustering of the non-precipitation data into the K clusters comprises clustering the non-precipitation data into the K clusters by using a K-means clustering algorithm which is an unsupervised machine learning algorithm for clustering data having similar features into the K clusters” are treated as belonging to mental process grouping.
Similar limitations comprise the abstract ideas of Claims 8 and16, respectively.
Next, under the Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application.
In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
The above claims comprise the following additional elements:
In Claim 16: predictor, determiner
The additional element a predictor and determiner are generally recited and are not qualified as particular machines. The specification fails to teach away from the examiners interpretation.
In conclusion, the above additional elements, considered individually and in combination with the other claim elements do not reflect an improvement to other technology or technical field, and, therefore, do not integrate the judicial exception into a practical application. Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B.
However, the above claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception (Step 2B analysis).
The claims, therefore, are not patent eligible.
With regards to the dependent claims, claims 2, 4-7 and 9, 11-14 provide additional features/steps which are part of an expanded algorithm, so these limitations should be considered part of an expanded abstract idea of the independent claims.
Allowable Subject Matter
The following is a statement of reasons for the indication of allowable subject matter:
Claims 1-2, 4-9 and 11-16 would be allowable if written overcome the 101 rejection set forth in this office action.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding Claim 1, Kim et al. (KR20210036085A, 2021-04-02) and Yang et al. (CN102706455B, 2014-03-12) both teach a method of measuring/estimating a sensible temperature, both references along with all other prior art fail to teach classifying data which includes a globe temperature, an atmospheric temperature, a relative humidity, and a ground surface temperature and is observed by an automated synoptic observing system (ASOS) for a certain period of time, as precipitation data and non-precipitation data according to whether there is precipitation; clustering the non-precipitation data into K clusters; and deriving K+1 sensible temperature calculation formulae by performing regression analysis on the K clusters and the precipitation data; classifying new input data as a non-precipitation data group or a precipitation data group by using a classification model for data classification, the classification model being a model trained in advance using training data, selecting one of the K+1 sensible temperature calculation formulae based on the classification result, and predicting a sensible temperature for the new input data based on the selected sensible temperature calculation formula and determining whether to issue the heatwave warning based on the predicted sensible temperature, wherein the clustering of the non-precipitation data into the K clusters comprises clustering the non-precipitation data into the K clusters by using a K-means clustering algorithm which is an unsupervised machine learning algorithm for clustering data having similar features into the K clusters. It is for this reason, Claim 1 and all of its dependencies would be allowable.
Claims 8, 15 and 16 include analogous, though not necessarily coextensive features similar to Claim 1. It would therefore, along with their dependencies, for similar rationale, be allowable.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL J SINGLETARY whose telephone number is (571)272-4593. The examiner can normally be reached Monday-Friday 8:00am-5:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Catherine Rastovski can be reached at 571-270-0349. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL J SINGLETARY/Examiner, Art Unit 2857
/Catherine T. Rastovski/Supervisory Primary Examiner, Art Unit 2857
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