DETAILED ACTION
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.
3. Claim 1 is 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 being integrated into a practical application and do not include additional elements that amount to significantly more than the judicial exception.
Utilizing the two step process adopted by the Supreme Court (Alice Corp vs CLS Bank Int'l, US Supreme Court, 110 USPQ2d 1976 (2014) and the recent 101 guideline, Federal Register Vol. 84, No., Jan 2019)), determination of the subject matter eligibility under the 35 USC 101 is as follows: Specifically, the Step 1 requires claim belongs to one of the four statutory categories (process, machine, manufacture, or composition of matter). If Step 1 is satisfied, then in the first part of Step 2A (Prong one), identification of any judicial recognized exceptions in the claim is made. If any limitation in the claim is identified as judicial recognized exception, then proceeding to the second part of Step 2A (Prong two), determination is made whether the identified judicial exception is being integrated into practical application. If the identified judicial exception is not integrated into a practical application, then in Step 2B, the claim is further evaluated to see if the additional elements, individually and in combination, provide “inventive concept” that would amount to significantly more than the judicial exception. If the element and combination of elements do not amount to significantly more than the judicial recognized exception itself, then the claim is ineligible under the 35 USC 101.
Looking at the claims, the claims satisfy the first part of the test 1A, namely the claims are directed to one of the four statutory class, method. In Step 2A Prong one, we next identify any judicial exceptions in the claims. In Claim 1, we recognize that the following limitations shown below are abstract ideas, as they involve usage of mental steps involving mathematical concepts and relationships which can be solved by human calculations and data entry.
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With the identification of abstract ideas, we proceed to Step 2A, Prong two, where with additional elements and taken as a whole, we evaluate whether the identified abstract idea is being integrated into a practical application.
In Step 2A, Prong two, the claim does not recite any additional element. As such, the abstract idea is not integrated into a practical application. Consequently, with the identified abstract idea not being integrated into a practical application, we proceed to Step 2B and evaluate whether the additional elements provide “inventive concept” that would amount to significantly more than the abstract idea.
In Step 2B, the claim does not recite any additional elements. As such, the claim does not recite any additional elements that provide “inventive concept” that would amount to significantly more than the abstract idea.
In Summary, the claims recite abstract idea without being integrated into a practical application, and do not provide additional elements that would amount to significantly more than the abstract idea. As such, taken as a whole, the claims are ineligible under the 35 USC 101.
Allowable Subject Matter
Claim 1 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101 set forth in this Office action.
Claim 1 would distinguish over all of the prior art in view of recitation of “A data-knowledge-driven optimisation and control method for a wastewater treatment process in a wastewater treatment system, wherein:
the wastewater treatment system comprises a primary settling tank, an anaerobic digestion tank, an aerobic tank and a secondary settling tank arranged sequentially in fluid communication;
the data-knowledge-driven optimisation and control method comprises establishing a data-driven multi-objective optimisation model, designing a multi-objective particle swarm optimisation method based on evolutionary knowledge, and designing an optimisation setpoint tracking and control method, specific steps of the data-knowledge-driven optimisation and control method comprise:
establishing a data-driven wastewater treatment target model:
taking energy consumption and effluent water quality as objectives to establish a multi- objective optimisation model for the wastewater treatment process:
where F(t) is the data-driven multi-objective optimisation model, fi(t) is an energy consumption model at time t, and f₂(t) is an effluent water quality model at time t;
establishing a data-driven energy consumption and effluent water quality model based on real-time measured input variables of nitrate nitrogen SNO at the anaerobic digestion tank and dissolved oxygen So at the aerobic tank , effluent mixed suspended solids (MLSS), and ammonia nitrogen in effluent SNH, and also …designing multi-objective particle swarm optimization based on evolutionary knowledge”
all of which is cumulatively taught by the cited prior art in view of further recitation of data gathering or data processing steps of solving and recording convergence distribution state and diversity distribution state of each particle during an iteration process, establishing indicators of convergence and diversity for individuals and populations, as instantly claimed.
The closest prior art is represented by the CN (Chinese) patent publications cited on the attached Notice of References cited, Form 892, and US PGPUBS Documents US 20220383062 and 20190359510, as well as patent 9,682872 which cumulatively teach or make obvious the method steps of: A data-knowledge-driven optimisation and control method for a wastewater treatment process in a wastewater treatment system, wherein:
the wastewater treatment system comprises a primary settling tank, an anaerobic digestion tank, an aerobic tank and a secondary settling tank arranged sequentially in fluid communication;
the data-knowledge-driven optimisation and control method comprises establishing a data-driven multi-objective optimisation model, designing a multi-objective particle swarm optimisation method based on evolutionary knowledge, and designing an optimisation setpoint tracking and control method, specific steps of the data-knowledge-driven optimisation and control method comprise:
establishing a data-driven wastewater treatment target model:
taking energy consumption and effluent water quality as objectives to establish a multi- objective optimisation model for the wastewater treatment process:
where F(t) is the data-driven multi-objective optimisation model, fi(t) is an energy consumption model at time t, and f₂(t) is an effluent water quality model at time t;
establishing a data-driven energy consumption and effluent water quality model based on real-time measured input variables of nitrate nitrogen SNO at the anaerobic digestion tank and dissolved oxygen So at the aerobic tank , effluent mixed suspended solids (MLSS), and ammonia nitrogen in effluent SNH, and also …designing multi-objective particle swarm optimization based on evolutionary knowledge”, however lacking such method steps being in combination with further recitation of data gathering or data processing steps of solving and recording convergence distribution state and diversity distribution state of each particle during an iteration process, establishing indicators of convergence and diversity for individuals and populations, as instantly claimed.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Primary Examiner Joseph Drodge at his direct government formal facsimile phone number telephone number of 571-272-1140. The examiner can normally be reached on Monday-Friday from approximately 8:00 AM to 1:00PM and 2:30 PM to 5:30 PM.
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If attempts to reach the examiner are unsuccessful, the examiner' s supervisor, Benjamin Lebron, of Technology Center Unit 1773, can reached at 571-272-0475.
The telephone number, for official, formal communications, for the examining group where this application is assigned is 571-273-8300.
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JWD
09/26/2026
/JOSEPH W DRODGE/Primary Examiner, Art Unit 1773
