DETAILED ACTION
Status of Claims
This Final Office Action is responsive to Applicant's reply filed 7/17/2025.
Claims 1, 7, 12, and 18 have been amended and claims 21-23 have been added new.
Claims 1, 4-5, 7, 12, 15-16, 18, and 20-23 are currently pending and have been examined.
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 .
Priority
This application claims priority of Foreign Application CN202411814720.1 filed on 12/11/2024. Applicant's claim for the benefit of this prior-filed application is acknowledged. Acknowledgment is made of applicant' s claim for foreign priority under 35 U.S.C. 119 (a)-(d).
Response to Amendments
The previously pending 35 USC 103 rejections have been withdrawn. See below for reasoning.
Applicant’s amendments have been fully considered, but do not overcome the previously pending 35 USC 101 rejections.
Response to Arguments
Applicant's arguments have been fully considered but they are not persuasive.
With regard to the limitations of claims 1, 4-5, 7, 12, 15-16, 18, and 20-23, Applicant argues that the claims are patent eligible under 35 USC 101 because the pending claims are not directed toward an abstract idea and integrate the abstract idea into practical application. The Examiner respectfully disagrees. The Examiner has already set forth a prima facie case under 35 USC 101. The Examiner has clearly pointed out the limitations directed towards the abstract idea, what the additional elements are and why they do not integrate the abstract idea into a practical application, and why the additional elements and remaining limitations do not amount to significantly more than the abstract idea. Applicant’s claims are scheduling transportation of gas/liquid products using a general purpose computer, where the physical transportation is done by a human. Generic recitation of a machine learning model does not make the claims eligible (See MPEP 2106.05). Applicant’s arguments are not persuasive.
The Examiner asserts the claims machine learning model training is recited at such a high level of generality that it merely adds the words apply it with the judicial exception (See MPEP 2106.05). Claim 7 recites what data is being input into a model that then, as recited, uses a loss function for training purposes. The claims do not recite specifics of what the loss function entails or details of the gradient decent manner, but rather recite generic use. The Examiner further points to Paragraph 0152 of Applicant’s specification which shows how high level these manners actually are recited. Applicant’s arguments are not persuasive.
Applicant argues the claims integrate the abstract idea into a practical application. The Examiner respectfully disagrees. The Examiner asserts the determinations are the abstract idea. Then, the commands/controls are generically displayed to a transporter (e.g. a human) for driving the gas from one location to another. The claims are merely using a general purpose computer to implement the abstract idea, e.g. ITO system (See MPEP 2106.05). Applicant also does not properly identify the additional elements.
The Examiner further asserts that Example 45 is directly controlling the machine for injection molding purposes of producing a physical product. Applicant’s claims are unrelated as they are merely using a general purpose computer to run the abstract idea and display the results so a human can make a determination. Applicant’s arguments are not persuasive.
Applicant argues the claims amount to significantly more. The Examiner respectfully disagrees. Applicant merely copy and pastes the claim and alleges that it is eligible. Telling a human to transport something, using a general purpose computer, and using machine learning does not make the claims eligible (See MPEP 2106.05). Applicant’s arguments are not persuasive.
The Examiner further asserts that there is no support for any sort of automation including the automatic transport of gas. Applicant’s arguments are not persuasive.
The Examiner further asserts that the MPEP has been cited as the supporting evidence required under Berkheimer. Applicant’s arguments are not persuasive.
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, 4-5, 7, 12, 15-16, 18, and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter;
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea), and if so, it must additionally be determined whether the claim is a patent-eligible application of the exception. If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself.
In the instant case (Step 1), claims 1, 4-5, 7, 12, 15-16, 18, and 20-23 are directed toward a process, product, and system; which are statutory categories of invention. Additionally (Step 2A Prong One), the independent claims are directed toward a method for demand management of natural gas in distributed energy pipelines, the method being executed by a distributed energy demand management platform of an Internet of Things (loT) system for demand management of natural gas in distributed energy pipelines, and the method comprising: determining a commercial gas consumption change sequence in at least one gas supply region in a predetermined future time period based on a production parameter sequence and a commercial impact sequence of factories in the at least one gas supply region in the predetermined future time period, wherein the commercial gas consumption change sequence refers to a sequence consisting of commercial gas consumption change coefficients, the commercial gas consumption change sequence includes a plurality of commercial gas consumption change coefficients corresponding to a plurality of sub-periods, each of the plurality of commercial gas consumption change coefficients reflects a commercial gas usage rate in a corresponding sub-period among the plurality of sub-periods; obtaining gas flow data of a low-pressure transportation network in the at least one gas supply region via a distributed energy sensing network platform through a distributed energy sensing control platform; obtaining historical gas consumption data of the at least one gas supply region based on the gas flow data; determining a residential gas consumption change sequence for the at least one gas supply region in the predetermined future time period based on a historical gas cost, the historical gas consumption data, seasonal information, and a gas cost sequence of the at least one gas supply region in the predetermined future time period, wherein the residential gas consumption change sequence refers to a sequence consisting of residential gas consumption change coefficients, the residential gas consumption change sequence includes a plurality of residential gas consumption change coefficients corresponding to the plurality of sub-periods, each of the plurality of residential gas consumption change coefficients is a ratio of a residential gas usage volume in a corresponding sub-period among the plurality of sub-periods to a residential gas usage volume in a previous sub-period; determining a demand volume sequence for the at least one gas supply region in the predetermined future time period based on the residential gas consumption change sequence, the commercial gas consumption change sequence, and the historical gas consumption data; constructing a micro-pipeline network map for the at least one gas supply region based on the low-pressure transportation network in the at least one gas supply region, a current gas storage amount of a gas field station, the demand volume sequence, and a storage capacity of the gas field station; determining a gas storage coverage rate and a gas supply priority of at least one node based on the micro-pipeline network map, wherein the gas storage coverage rate refers to a proportion of a current gas storage volume that satisfies a gas demand volume; determining a gas storage adjustment parameter based on the gas storage coverage rate and the gas supply priority, the gas storage adjustment parameter including a gas supply volume, a gas supply location, and a gas supply time of the gas field station, wherein in response to determining that a count of nodes having a gas storage coverage rate less than 100% is greater than a second predetermined threshold, for each of the nodes having a gas storage coverage rate less than 100%, determining a corresponding gas supply volume based on a current gas storage amount of a node and a gas demand volume of the node in the predetermined future time period; and generating a storage adjustment instruction based on the gas storage adjustment parameter; sending the storage adjustment instruction to the gas field station; and controlling a plurality of tankers to automatically transport a plurality of storage tanks corresponding to the gas supply volume to the gas supply location via a tanker transportation path during the gas supply time in accordance with the gas supply priority of each node, based on the storage adjustment instruction (Organizing Human Activity), which are considered to be abstract ideas (See MPEP 2106.05). The steps/functions disclosed above and in the independent claims are directed toward the abstract idea of Organizing Human Activity because the claimed limitations are analyzing demand and gas usages of residential areas and forecasting future demand based on historical and current readings to make determinations about how to move gas around a network by further analyzing usage ratios for sub-periods to compare to amounts of gas stored in certain substations and taking into account capacities and coverage rates, which is a commercial interaction.
Step 2A Prong Two: In this application, even if not directed toward the abstract idea, the above “obtaining gas flow data of a low-pressure transportation network in the at least one gas supply region via a distributed energy sensing network platform through a distributed energy sensing control platform; obtaining historical gas consumption data of the at least one gas supply region based on the gas flow data; sending the storage adjustment instruction to the gas field station; and controlling a plurality of tankers” steps/functions of the independent claims would not account for additional elements that integrate the judicial exception (e.g. abstract idea) into a practical application because receiving/storing data and displaying data merely add insignificant extra-solution activity and merely adds the words to apply it with the judicial exception. Also, the claimed “executed by a distributed energy demand management platform of an Internet of Things (loT) system; a low-pressure transportation network; gas field station; a distributed energy sensing network platform through a distributed energy sensing control platform; Internet of Things (loT) system for demand management of natural gas in distributed energy pipelines, comprising a distributed energy sensing control platform, a distributed energy sensing network platform, a distributed energy demand management platform, a distributed energy service platform, and a distributed energy user platform that are connected in sequence, wherein the distributed energy demand management platform is configured to; non-transitory computer-readable storage medium storing computer instructions, wherein when reading the computer instructions in the storage medium, a computer implements; a machine learning model; a plurality of tankers” would not account for additional elements that integrate the judicial exception (e.g. abstract idea) into a practical application because the claimed structure merely adds the words to apply it with the judicial exception and mere instructions to implement an abstract idea on a computer (See MPEP 2106.05).
In addition, dependent claims 4-5, 7, 15-16, 18, and 21-23 further narrow the abstract idea and dependent claims 7 and 18 additionally recite “a machine learning model” which is recited at such a high level of generality that it does not account for additional elements that integrate the judicial exception (e.g. abstract idea) into a practical application but rather merely adds the words to apply it with the judicial exception and mere instructions to implement an abstract idea on a computer (See MPEP 2106.05).
The claimed “executed by a distributed energy demand management platform of an Internet of Things (loT) system; a low-pressure transportation network; gas field station; a distributed energy sensing network platform through a distributed energy sensing control platform; Internet of Things (loT) system for demand management of natural gas in distributed energy pipelines, comprising a distributed energy sensing control platform, a distributed energy sensing network platform, a distributed energy demand management platform, a distributed energy service platform, and a distributed energy user platform that are connected in sequence, wherein the distributed energy demand management platform is configured to; non-transitory computer-readable storage medium storing computer instructions, wherein when reading the computer instructions in the storage medium, a computer implements; a machine learning model; a plurality of tankers” are recited so generically (no details whatsoever are provided other than that they are general purpose computing components and regular office supplies) and at such a high level of generality that they represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. Even when viewed in combination, the additional elements in the claims do no more than use the computer components as a tool. There is no change to the computers and other technology that is recited in the claim, and thus the claims do not improve computer functionality or other technology (See MPEP 2106.05).
Step 2B: When analyzing the additional element(s) and/or combination of elements in the claim(s) other than the abstract idea per se the claim limitations amount(s) to no more than: a general link of the use of an abstract idea to a particular technological environment and merely amounts to the application or instructions to apply the abstract idea on a computer (See MPEP 2106.05). Further, method; System; and Product claims 1, 4-5, 7, 12, 15-16, 18, and 20-23 recite executed by a distributed energy demand management platform of an Internet of Things (loT) system; a low-pressure transportation network; gas field station; a distributed energy sensing network platform through a distributed energy sensing control platform; Internet of Things (loT) system for demand management of natural gas in distributed energy pipelines, comprising a distributed energy sensing control platform, a distributed energy sensing network platform, a distributed energy demand management platform, a distributed energy service platform, and a distributed energy user platform that are connected in sequence, wherein the distributed energy demand management platform is configured to; non-transitory computer-readable storage medium storing computer instructions, wherein when reading the computer instructions in the storage medium, a computer implements; a machine learning model; a plurality of tankers; however, these elements merely facilitate the claimed functions at a high level of generality and they perform conventional functions and are considered to be general purpose computer components which is supported by Applicant’s specification in Paragraphs 0021-0024 and 0175. The Applicant’s claimed additional elements are mere instructions to implement the abstract idea on a general purpose computer and generally link of the use of an abstract idea to a particular technological environment. Also, the above “obtaining gas flow data of a low-pressure transportation network in the at least one gas supply region via a distributed energy sensing network platform through a distributed energy sensing control platform; obtaining historical gas consumption data of the at least one gas supply region based on the gas flow data; sending the storage adjustment instruction to the gas field station; and controlling a plurality of tankers” steps/functions of the independent claims would not account for significantly more than the abstract idea because receiving data and displaying/presenting data (See MPEP 2106.05) have been identified as well-known, routine, and conventional steps/functions to one of ordinary skill in the art. When viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself.
In addition, claims 4-5, 7, 15-16, 18, and 21-23 further narrow the abstract idea identified in the independent claims. The Examiner notes that the dependent claims merely further define the data being analyzed and how the data is being analyzed. Similarly, claims 7 and 18 additionally recite “a machine learning model” which do not account for additional elements that amount to significantly more than the abstract idea because the claimed structure merely amounts to the application or instructions to apply the abstract idea on a computer and does not move beyond a general link of the use of an abstract idea to a particular technological environment (See MPEP 2106.05) because it is recited at such a high level of generality. The additional limitations of the independent and dependent claim(s) when considered individually and as an ordered combination do not amount to significantly more than the abstract idea. The examiner has considered the dependent claims in a full analysis including the additional limitations individually and in combination as analyzed in the independent claim(s). Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 4-5, 7, 12, 15-16, 18, and 20-23 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding Claims 1, 4-5, 7, 12, 15-16, 18, and 20-23: Claims 1, 4-5, 7, 12, 15-16, 18, and 20-23 recite “controlling a plurality of tankers to automatically transport a plurality of storage tanks”. There is no support for any sort of automation in this application. The Examiner asserts that the transporting is done by a human transporter. This is considered an introduction of new matter and rejected accordingly.
Allowable over 35 USC 103
Claims 1, 4-5, 7, 12, 15-16, 18, and 20-23 are allowable over the prior art, but remain rejected under 35 USC 101 for the reasons set forth above. Claims 1, 4-5, 7, 12, 15-16, 18, and 20-23 disclose a system, product, and method for analyzing demand and gas usages of residential areas and forecasting future demand based on historical and current readings to make determinations about how to move gas around a network by further analyzing usage ratios for sub-periods to compare to amounts of gas stored in certain substations and taking into account capacities and coverage rates.
Regarding a possible 103 rejection: The closest prior art of record is:
Cella et al. (US 2018/0284735 A1) – which discloses industrial internet of things data collection for an oil and gas environment.
Hoff (US 2019/0311283 A1) – which discloses estimating fuel consumption.
Finkel et al. (US 2017/0140469 A1) – which discloses a management system for oil and gas control between parties using predictive analysis.
The prior art of record neither teaches nor suggests all particulars of the limitations as recited in claims 1, 4-5, 7, 12, 15-16, 18, and 20-23, such as analyzing demand and gas usages of residential areas and forecasting future demand based on historical and current readings to make determinations about how to move gas around a network by further analyzing usage ratios for sub-periods to compare to amounts of gas stored in certain substations and taking into account capacities and coverage rates. While individual features may be known per se, there is no teaching or suggestion absent applicants’ own disclosure to combine these features other than with impermissible hindsight and the combination/arrangement of features are not found in analogous art. Specifically the claimed “a method for demand management of natural gas in distributed energy pipelines, the method being executed by a distributed energy demand management platform of an Internet of Things (loT) system for demand management of natural gas in distributed energy pipelines, and the method comprising: determining a commercial gas consumption change sequence in at least one gas supply region in a predetermined future time period based on a production parameter sequence and a commercial impact sequence of factories in the at least one gas supply region in the predetermined future time period, wherein the commercial gas consumption change sequence refers to a sequence consisting of commercial gas consumption change coefficients, the commercial gas consumption change sequence includes a plurality of commercial gas consumption change coefficients corresponding to a plurality of sub-periods, each of the plurality of commercial gas consumption change coefficients reflects a commercial gas usage rate in a corresponding sub-period among the plurality of sub-periods; obtaining gas flow data of a low-pressure transportation network in the at least one gas supply region via a distributed energy sensing network platform through a distributed energy sensing control platform; obtaining historical gas consumption data of the at least one gas supply region based on the gas flow data; determining a residential gas consumption change sequence for the at least one gas supply region in the predetermined future time period based on a historical gas cost, the historical gas consumption data, seasonal information, and a gas cost sequence of the at least one gas supply region in the predetermined future time period, wherein the residential gas consumption change sequence refers to a sequence consisting of residential gas consumption change coefficients, the residential gas consumption change sequence includes a plurality of residential gas consumption change coefficients corresponding to the plurality of sub-periods, each of the plurality of residential gas consumption change coefficients is a ratio of a residential gas usage volume in a corresponding sub-period among the plurality of sub-periods to a residential gas usage volume in a previous sub-period; determining a demand volume sequence for the at least one gas supply region in the predetermined future time period based on the residential gas consumption change sequence, the commercial gas consumption change sequence, and the historical gas consumption data; constructing a micro-pipeline network map for the at least one gas supply region based on the low-pressure transportation network in the at least one gas supply region, a current gas storage amount of a gas field station, the demand volume sequence, and a storage capacity of the gas field station; determining a gas storage coverage rate and a gas supply priority of at least one node based on the micro-pipeline network map, wherein the gas storage coverage rate refers to a proportion of a current gas storage volume that satisfies a gas demand volume; determining a gas storage adjustment parameter based on the gas storage coverage rate and the gas supply priority, the gas storage adjustment parameter including a gas supply volume, a gas supply location, and a gas supply time of the gas field station, wherein in response to determining that a count of nodes having a gas storage coverage rate less than 100% is greater than a second predetermined threshold, for each of the nodes having a gas storage coverage rate less than 100%, determining a corresponding gas supply volume based on a current gas storage amount of a node and a gas demand volume of the node in the predetermined future time period; and generating a storage adjustment instruction based on the gas storage adjustment parameter; sending the storage adjustment instruction to the gas field station; and controlling a plurality of tankers to automatically transport a plurality of storage tanks corresponding to the gas supply volume to the gas supply location via a tanker transportation path during the gas supply time in accordance with the gas supply priority of each node, based on the storage adjustment instruction (as required by claims 1, 4-5, 7, 12, 15-16, 18, and 20-23)”, thus rendering claims 1, 4-5, 7, 12, 15-16, 18, and 20-23 as allowable over the prior art.
Conclusion
THIS ACTION IS MADE FINAL. 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.
The prior art made of record, but not relied upon is considered pertinent to applicant's disclosure is listed on the attached PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW D HENRY whose telephone number is (571)270-0504. The examiner can normally be reached on Monday-Thursday 9AM-5PM.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MATTHEW D HENRY/Primary Examiner, Art Unit 3625
Prosecution Insights