DETAILED ACTION
Status of the Claims
The following is a non-final Office Action in response to claims filed 03 April 2025.
Claims 1-20 are pending.
Claims1-20 have been examined.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 24 June 2025 are being considered by the Examiner.
Priority
Applicant’s claim for the benefit of a prior-filed application(s) 18/619,142, filed on March 27, 2024, which claims priority to Chinese Patent Application No. 202410249944.6, filed on March 5, 2024 under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) is acknowledged.
Examiner’s Note
The claims and specification appear to be a literal translation and are replete with typographical and grammatical errors. More specifically, the claims recites various limitations which have very broad and vague meanings when interpreted in light of the specification.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO internet Web site contains terminal disclaimer forms which may be used. Please visit http://www.uspto.gov/forms/. The filing date of the application will determine what form should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1-2, 5, 7, 9-13, 15, and 17-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 4, 6, 13, 18, 19, 22, and 23 of copending Application No. 18/619,142 (now Patent No. 12,299,696). Although the claims at issue are not identical, they are not patentably distinct as shown below:
19/169,026
18/619,142
1. A method for processing gas regulatory information, the method being executed by a gas company management platform of a system for processing gas regulatory information, the system comprising a public user platform, a government regulatory service platform, a government regulatory management platform, a government regulatory sensing network platform, a government regulatory object platform, a gas company sensing network platform, a gas user object platform, and a gas device object platform, wherein the public user platform is configured as terminal device, the government regulatory object platform includes the gas company management platform, the gas user object platform interacts with the gas company management platform via the gas company sensing network platform, the gas company management platform is configured on a gas company management server, the gas device object platform is configured in a gas pipeline facility and a gas pipeline auxiliary facility; the method comprising: obtaining gas regulatory information of a plurality of gas regulatory regions based on the gas company sensing network platform, wherein the gas company sensing network platform includes a plurality of sets of communication sub-devices configured in different gas regulatory regions of the plurality of gas regulatory regions, and communication priorities of the plurality of sets of communication sub-devices in the different gas regulatory regions are different; determining target gas regulatory information from the gas regulatory information based on a target regulatory characteristic; updating data accountability levels of the different gas regulatory regions based on the target gas regulatory information; determining redundant data and contradictory data based on the target gas regulatory information and the data accountability levels; obtaining processed target gas regulatory information based on the redundant data and the contradictory data, and transmitting the processed target gas regulatory information to the government regulatory management platform via the government regulatory sensing network platform, so as to enable the government regulatory management platform to establish a gas regulatory database based on the processed target gas regulatory information and further provide a gas regulatory query service to a user through the public user platform; and adjusting the communication priorities of the plurality of sets of communication sub- devices based on the data accountability levels, wherein the higher the data accountability level of a gas regulatory region is, the higher the communication priority of the communication sub-device corresponding to the gas regulatory region is adjusted.
13. A system for processing gas regulatory information, comprising a public user platform, a government regulatory service platform, a government regulatory management platform, a government regulatory sensing network platform, a government regulatory object platform, a gas company sensing network platform, a gas user object platform, and a gas device object platform, wherein the government regulatory service platform includes a citizen cloud service sub-platform and a government safety management service sub-platform, the government regulatory management platform includes a government gas business management sub-platform and a government safety management sub-platform, the government regulatory sensing network platform includes a government gas regulatory authority sensing network sub-platform and a government safety management department sensing network sub-platform, the government regulatory object platform includes a gas company management platform, the public user platform is configured as terminal device, the gas user object platform interacts with the gas company management platform via the gas company sensing network platform, the gas company management platform is configured on a gas company management server, the gas device object platform is configured in a gas pipeline facility and a gas pipeline auxiliary facility, and the gas company management platform is configured to: obtain gas regulatory information of a plurality of gas regulatory regions based on the gas company sensing network platform, wherein the gas company sensing network platform includes a plurality of sets of communication sub-devices configured in different gas regulatory regions of the plurality of gas regulatory regions, and communication priorities of the plurality of sets of communication sub-devices in the different gas regulatory regions are different; determine target gas regulatory information from the gas regulatory information based on a target regulatory characteristic; update data accountability levels of the different gas regulatory regions based on the target gas regulatory information; determine redundant data and contradictory data based on the target gas regulatory information and the data accountability levels; obtain processed target gas regulatory information based on the redundant data and the contradictory data, and transmitting the processed target gas regulatory information to the government regulatory management platform via the government regulatory sensing network platform, so as to enable the government regulatory management platform to establish a gas regulatory database based on the processed target gas regulatory information and further provide a gas regulatory query service to a user through the public user platform; and adjust the communication priorities of the plurality of sets of communication sub- devices based on the data accountability levels, wherein the higher the data accountability level of a gas regulatory region is, the higher the communication priority of the communication sub-device corresponding to the gas regulatory region is adjusted.
1. A method for processing smart gas regulatory information based on a regulatory Internet of Things (IoT), the method being executed by a gas company management platform of a system for processing the smart gas regulatory information, the system comprising a public user platform, a government regulatory service platform, a government regulatory management platform, a government regulatory sensing network platform, a government regulatory object platform, a gas company sensing network platform, a gas user object platform, and a gas device object platform, wherein the public user platform is configured as a terminal device, the government regulatory object platform includes a gas company management platform, the gas user object platform interacts with the gas company management platform via the gas company sensing network platform, the gas company management platform is configured on a gas company management server, the gas device object platform is configured in a gas pipeline facility and a gas pipeline ancillary facility; the method comprising: obtaining gas regulatory information of a plurality of gas regulatory regions based on the gas company sensing network platform of the system for processing the smart gas regulatory information, wherein the gas company sensing network platform includes a plurality of sets of communication sub-devices configured in different gas regulatory regions of the plurality of gas regulatory regions, and communication priorities of the plurality of sets of communication sub-devices in the different gas regulatory regions are different; and the gas regulatory information includes gas business data and gas safety data, the gas business data includes gas engineering construction data, the gas safety data includes gas pipeline network maintenance data; determining target gas regulatory information from the gas regulatory information based on a target regulatory characteristic; updating data accountability levels of the different gas regulatory regions based on the target gas regulatory information; wherein the data accountability levels are used to reflect division of accountability regarding data quality in the different gas regulatory regions, and the updating data accountability levels of the different gas regulatory regions includes: establishing a regulatory graph based on the different gas regulatory regions and different target gas regulatory information corresponding to the different gas regulatory regions, wherein nodes of the regulatory graph include the different gas regulatory regions and edges of the regulatory graph connect gas regulatory regions involved in data cross-management; and determining, based on the regulatory graph, updated data accountability levels of the different gas regulatory regions through a regulatory model, the regulatory model being a neural network model; wherein the regulatory graph refers to a graph established based on the different gas regulatory regions; the regulatory graph includes edges and nodes; a node attribute of the nodes of the regulatory graph includes historical redundant data, historical contradictory data, and the target gas regulatory information; an edge attribute of an edge of the regulatory graph includes historical data accountability levels and current data accountability levels of the gas regulatory regions corresponding to each of two nodes connected by the edge; wherein the regulatory model is obtained through a training process including: inputting, by the gas company management platform, a plurality of training samples with labels into an initial regulatory model; wherein the training samples include a sample regulatory graph established based on actual data, the labels for the model training is a sequence of updated data accountability levels; constructing a loss function based on the labels and a result of the initial regulatory model; iteratively updating parameters of the initial regulatory model based on the loss function; completing training of the initial joint regulatory model until the loss function satisfies a preset training condition, and obtaining a joint regulatory model; wherein the preset training condition includes that the loss function converges or a count of iterations reaches a first threshold; determining redundant data and contradictory data based on the target gas regulatory information and the data accountability levels; obtaining processed target gas regulatory information based on the redundant data and the contradictory data, and transmitting the processed target gas regulatory information to the government regulatory management platform of the system for processing the smart gas regulatory information via the government regulatory sensing network platform of the system for processing the smart gas regulatory information, so as to enable the government regulatory management platform to establish a gas regulatory database based on the processed target gas regulatory information and further provide a gas regulatory query service to a user through the public user platform of the system for processing the smart gas regulatory information; and adjusting the communication priorities of the plurality of sets of communication sub-devices based on the data accountability levels.
13. A system for processing smart gas regulatory information based on a regulatory Internet of Things (IoT), comprising a public user platform, a government regulatory service platform, a government regulatory management platform, a government regulatory sensing network platform, a government regulatory object platform, a gas company sensing network platform, a gas user object platform, and a gas device object platform, wherein the public user platform is configured as a terminal device, the government regulatory service platform includes a citizen cloud service sub-platform and a government safety management service sub-platform, the government regulatory management platform includes a government gas business management sub-platform and a government safety management sub-platform, the government regulatory sensing network platform includes a government gas regulatory authority sensing network sub-platform and a government safety management department sensing network sub-platform, the government regulatory object platform includes a gas company management platform, the gas user object platform interacts with the gas company management platform via the gas company sensing network platform, the gas company management platform is configured on a gas company management server, the gas device object platform is configured in a gas pipeline facility and a gas pipeline ancillary facility; the gas company management platform is configured to: obtain gas regulatory information of a plurality of gas regulatory regions based on the gas company sensing network platform of the system for processing the smart gas regulatory information, wherein the gas regulatory information is obtained and stored based on the gas device object platform and the gas user object platform of the plurality of gas regulatory regions, the gas company sensing network platform includes a plurality of sets of communication sub-devices configured in different gas regulatory regions of the plurality of gas regulatory regions, and communication priorities of the plurality of sets of communication sub-devices in the different gas regulatory regions are different; and the gas regulatory information includes gas business data and gas safety data, the gas business data includes gas engineering construction data, the gas safety data includes gas pipeline network maintenance data; determine a target regulatory characteristic based on the government regulatory management platform and determine target gas regulatory information from the gas regulatory information based on the target regulatory characteristic; update data accountability levels of the different gas regulatory regions based on the target gas regulatory information; wherein the data accountability levels are used to reflect division of accountability regarding data quality in the different gas regulatory regions, and the updating data accountability levels of the different gas regulatory regions includes: establishing a regulatory graph based on the different gas regulatory regions and different target gas regulatory information corresponding to the different gas regulatory regions, wherein nodes of the regulatory graph include the different gas regulatory regions and edges of the regulatory graph connect gas regulatory regions involved in data cross-management; and determining, based on the regulatory graph, updated data accountability levels of the different gas regulatory regions through a regulatory model, the regulatory model being a neural network model; wherein the regulatory graph refers to a graph established based on the different gas regulatory regions; the regulatory graph includes edges and nodes; a node attribute of the nodes of the regulatory graph includes historical redundant data, historical contradictory data, and the target gas regulatory information; an edge attribute of an edge of the regulatory graph includes historical data accountability levels and current data accountability levels of the gas regulatory regions corresponding to each of two nodes connected by the edge; wherein the regulatory model is obtained through a training process including: inputting, by the gas company management platform, a plurality of training samples with labels into an initial regulatory model; wherein the training samples include a sample regulatory graph established based on actual data, the labels for the model training is a sequence of updated data accountability levels; constructing a loss function based on the labels and a result of the initial regulatory model; iteratively updating parameters of the initial regulatory model based on the loss function; completing training of the initial joint regulatory model until the loss function satisfies a preset training condition, and obtaining a joint regulatory model; wherein the preset training condition includes that the loss function converges or a count of iterations reaches a first threshold; determining redundant data and contradictory data based on the target gas regulatory information and the data accountability levels; obtaining processed target gas regulatory information based on the redundant data and the contradictory data, and transmit the processed target gas regulatory information to the government regulatory management platform via the government regulatory sensing network platform; adjusting the communication priorities of the plurality of sets of communication sub-devices based on the data accountability levels; the government regulatory management platform is configured to establish a gas regulatory database based on the processed target gas regulatory information; and the public user platform is configured to provide a gas regulatory query service to a user.
The independent claims 1 and 13 of the copending Application No. 18/619,142 (now Patent No. 12,299,696, hereinafter ‘696 Patent) are not identical to the instant claims 1 and 13 but however claim the same inventive concept adjusting communication priorities based upon determined regulatory information and data accountability levels (the instant claims are much more broad). Here, specifically, instant claim 1 is rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claim 1 of the ‘696 Patent. The claims differ in that instant claim 1 recites that the regulatory information, accountability levels, redundant and contradictory data for communication adjustment whereas claim 1 of the ‘696 Patent recites that the gas regulatory information is limited to a specific type and the establishing of a gas regulatory graph (as highlighted in the table above). This is recited in dependent claims 2, 10-12, and 18-20, which one of ordinary skill in the art would find obvious to combine in instant claims 1 and 13 to arrive at the claims 1 and 13 of the ‘696 patent. The portion of the specification in the ‘696 Patent that supports the recited regulatory information, accountability levels, redundant and contradictory data for communication adjustment and also includes an embodiment that would anticipate instant claims 1 and 13 herein. Instant claims 1 cannot be considered patentably distinct over claims 1 and 13 of the ‘696 Patent when there is a specifically disclosed embodiment that supports claims 1 and 13 of that patent and falls within the scope of claims 1 and 13 herein because it would have been obvious to one having ordinary skill in the art to modify the method of claim 1 by selecting a specifically disclosed embodiment that supports that claim, (i.e., the gas regulatory information is limited to a specific type and the establishing of a gas regulatory graph). One having ordinary skill in the art would have been motivated to do this because that embodiment is disclosed as being a preferred embodiment within claim 1. Instant independent claim 13 are rejected under the same rationale, mutatis mutandis.
Dependent claims 5 and 15 are substantially similar to claims 4 and 18 of the ‘696 Patent.
Dependent claims 7 and 17 are substantially similar to claims 6 and 19 of the ‘696 Patent.
Dependent claims 9 are substantially similar to claims 22 and 23 of the ‘696 Patent.
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 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims are directed to a process (an act, or series of acts or steps), a machine (a concrete thing, consisting of parts, or of certain devices and combination of devices), and a manufacture (an article produced from raw or prepared materials by giving these materials new forms, qualities, properties, or combinations, whether by hand labor or by machinery). Thus, each of the claims falls within one of the four statutory categories (Step 1). The claims recite a method (process) and a system with apparatuses, however, the claim(s) recite(s) adjusting communication priorities based upon determined regulatory information and data accountability levels which is an abstract idea of organizing human activities as well as performing a mental process..
The limitations of “determining target gas regulatory information from the gas regulatory information based on a target regulatory characteristic; updating data accountability levels of the different gas regulatory regions based on the target gas regulatory information; determining redundant data and contradictory data based on the target gas regulatory information and the data accountability levels; obtaining processed target gas regulatory information based on the redundant data and the contradictory data, and transmitting the processed target gas regulatory information to the government regulatory management platform via the government regulatory sensing network platform, so as to enable the government regulatory management platform to establish a gas regulatory database based on the processed target gas regulatory information and further provide a gas regulatory query service to a user through the public user platform; and adjusting the communication priorities of the plurality of sets of communication sub- devices based on the data accountability levels, wherein the higher the data accountability level of a gas regulatory region is, the higher the communication priority of the communication sub-device corresponding to the gas regulatory region is adjusted,” as drafted, is a process that, under its broadest reasonable interpretation, covers organizing human activities--fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) as well as a mental process—concepts performed in the human mind (including an observation, evaluation, judgment, opinion) but for the recitation of generic computer components (Step 2A Prong 1). That is, other than reciting “A method for processing gas regulatory information, the method being executed by a gas company management platform of a system for processing gas regulatory information, the system comprising a public user platform, a government regulatory service platform, a government regulatory management platform, a government regulatory sensing network platform, a government regulatory object platform, a gas company sensing network platform, a gas user object platform, and a gas device object platform, wherein the public user platform is configured as terminal device, the government regulatory object platform includes the gas company management platform, the gas user object platform interacts with the gas company management platform via the gas company sensing network platform, the gas company management platform is configured on a gas company management server, the gas device object platform is configured in a gas pipeline facility and a gas pipeline auxiliary facility; the method comprising:,” (or “A system for processing gas regulatory information, comprising a public user platform, a government regulatory service platform, a government regulatory management platform, a government regulatory sensing network platform, a government regulatory object platform, a gas company sensing network platform, a gas user object platform, and a gas device object platform, wherein the government regulatory service platform includes a citizen cloud service sub-platform and a government safety management service sub-platform, the government regulatory management platform includes a government gas business management sub-platform and a government safety management sub-platform, the government regulatory sensing network platform includes a government gas regulatory authority sensing network sub-platform and a government safety management department sensing network sub-platform, the government regulatory object platform includes a gas company management platform, the public user platform is configured as terminal device, the gas user object platform interacts with the gas company management platform via the gas company sensing network platform, the gas company management platform is configured on a gas company management server, the gas device object platform is configured in a gas pipeline facility and a gas pipeline auxiliary facility, and the gas company management platform is configured to:” in claim 13) nothing in the claim element precludes the step from the methods of organizing human interactions grouping or from practically being performed in the mind. For example, but for the. For example, but for the “A method for processing gas regulatory information, the method being executed by a gas company management platform of a system for processing gas regulatory information, the system comprising a public user platform, a government regulatory service platform, a government regulatory management platform, a government regulatory sensing network platform, a government regulatory object platform, a gas company sensing network platform, a gas user object platform, and a gas device object platform, wherein the public user platform is configured as terminal device, the government regulatory object platform includes the gas company management platform, the gas user object platform interacts with the gas company management platform via the gas company sensing network platform, the gas company management platform is configured on a gas company management server, the gas device object platform is configured in a gas pipeline facility and a gas pipeline auxiliary facility; the method comprising:,” (or “A system for processing gas regulatory information, comprising a public user platform, a government regulatory service platform, a government regulatory management platform, a government regulatory sensing network platform, a government regulatory object platform, a gas company sensing network platform, a gas user object platform, and a gas device object platform, wherein the government regulatory service platform includes a citizen cloud service sub-platform and a government safety management service sub-platform, the government regulatory management platform includes a government gas business management sub-platform and a government safety management sub-platform, the government regulatory sensing network platform includes a government gas regulatory authority sensing network sub-platform and a government safety management department sensing network sub-platform, the government regulatory object platform includes a gas company management platform, the public user platform is configured as terminal device, the gas user object platform interacts with the gas company management platform via the gas company sensing network platform, the gas company management platform is configured on a gas company management server, the gas device object platform is configured in a gas pipeline facility and a gas pipeline auxiliary facility, and the gas company management platform is configured to:” in claim 13)” language, “determining,” “updating,” determining,” “obtaining,” and “adjusting” in the context of this claim encompasses the user manually adjusting communication priorities based upon collected regulatory information for regions which is a business relation/fundamental economic practice/commercial or legal interaction/managing personal behavior that utility companies would provide to their customers. Similarly, the aforementioned limitations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of a computer or with computing components, such as the user mentally making a judgement on which type of region would need different priority of communications based upon the data. However, if possible, the Examiner should consider the limitations together as a single abstract idea rather than as a plurality of separate abstract ideas to be analyzed individually. “For example, in a claim that includes a series of steps that recite mental steps as well as a mathematical calculation, an examiner should identify the claim as reciting both a mental process and a mathematical concept for Step 2A, Prong One to make the analysis clear on the record.” MPEP 2106.04, subsection II.B. Under such circumstances, however, the Supreme Court has treated such claims in the same manner as claims reciting a single judicial exception. Id. (discussing Bilski v. Kappos, 561 U.S. 593 (2010)). Here, the limitations are considered together as a single abstract idea for further analysis. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations as a mathematical concept, while some of the limitations may be performed in the mind after certain limitations are performed, but for the recitation of generic computer components, then it falls within the grouping of abstract ideas. (Step 2A, Prong One: YES). Accordingly, the claim(s) recite(s) an abstract idea.
This judicial exception is not integrated into a practical application (Step 2A Prong Two). The “obtaining…gas company sensing network platform…sub-devices” steps and elements are simply insignificant extrasolution data gathering activities. Next, the claim only recites one additional element – using gas company management platform to perform the steps. The gas company management platform in the steps is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of electronic data query, storage and retrieval; some of the most basic functions of a computer) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Specifically the claims amount to nothing more than an instruction to apply the abstract idea using a generic computer or invoking computers as tools by adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.04(d)(I) discussing MPEP 2106.05(f). The claims recitation of the “A method for processing gas regulatory information, the method being executed by a gas company management platform of a system for processing gas regulatory information, the system comprising a public user platform, a government regulatory service platform, a government regulatory management platform, a government regulatory sensing network platform, a government regulatory object platform, a gas company sensing network platform, a gas user object platform, and a gas device object platform, wherein the public user platform is configured as terminal device, the government regulatory object platform includes the gas company management platform, the gas user object platform interacts with the gas company management platform via the gas company sensing network platform, the gas company management platform is configured on a gas company management server, the gas device object platform is configured in a gas pipeline facility and a gas pipeline auxiliary facility; the method comprising:,” (or “A system for processing gas regulatory information, comprising a public user platform, a government regulatory service platform, a government regulatory management platform, a government regulatory sensing network platform, a government regulatory object platform, a gas company sensing network platform, a gas user object platform, and a gas device object platform, wherein the government regulatory service platform includes a citizen cloud service sub-platform and a government safety management service sub-platform, the government regulatory management platform includes a government gas business management sub-platform and a government safety management sub-platform, the government regulatory sensing network platform includes a government gas regulatory authority sensing network sub-platform and a government safety management department sensing network sub-platform, the government regulatory object platform includes a gas company management platform, the public user platform is configured as terminal device, the gas user object platform interacts with the gas company management platform via the gas company sensing network platform, the gas company management platform is configured on a gas company management server, the gas device object platform is configured in a gas pipeline facility and a gas pipeline auxiliary facility, and the gas company management platform is configured to:” in claim 13)” are only generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.04(d)(I) discussing MPEP 2106.05(h). Accordingly, the combination of these additional elements does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea, even when considered as a whole (Step 2A Prong Two: NO).
The claim does not include a combination of additional elements that are sufficient to amount to significantly more than the judicial exception (Step 2B). As discussed above with respect to integration of the abstract idea into a practical application (Step 2A Prong 2), the combination of additional elements of using a gas company management platform to perform the steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Reevaluating here in Step 2B, the “obtaining…” step(s) which are insignificant extrasolution activities are also determined to be well-understood, routine and conventional activity in the field. The Symantec, TLI, and OIP Techs court decisions in MPEP 2106.05(d)(II) indicate that the mere receipt or transmission of data over a network is well-understood, routine, and conventional function when it is claimed in a merely generic manner (as is here). Therefore, when considering the additional elements alone, and in combination, there is no inventive concept in the claim. As such, the claim(s) is/are not patent eligible, even when considered as a whole.
Claims 2 recite the additional limitations that limit the types of data collected which is still directed towards the abstract idea(s) previously identified and is not an inventive concept that meaningfully limits the abstract idea. Again, as discussed with respect to claims 1 and 13, the claims are simply limitations which are no more than mere instructions to apply the exception using a computer or with computing components. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Even when considered as a whole, the claims do not integrate the judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claims 3-4 and 14 recite the additional limitations that further limit the technical environment which is not an inventive concept that meaningfully limits the abstract idea. Again, as discussed with respect to claims 1 and 13, the claims are simply limitations which are no more than mere instructions to apply the exception using a computer or with computing components. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Even when considered as a whole, the claims do not integrate the judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claims 5-12 and 15-20 recite the additional limitations that introduce mathematical concepts which is not an inventive concept that meaningfully limits the abstract idea. Again, as discussed with respect to claims 1 and 13, the claims are simply limitations which are no more than mere instructions to apply the exception using a computer or with computing components. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Even when considered as a whole, the claims do not integrate the judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claims 1-20 are therefore not eligible subject matter, even when considered as a whole.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the 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.
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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bain et al. (US PG Pub. 2019/0372345) and further in view of Cella et al. (US PG Pub. 2018/0284758).
As per claims 1 and 13, Bain a method and system for processing gas regulatory information, the method being executed by a gas company management platform of a system for processing gas regulatory information, the system comprising a public user platform, a government regulatory service platform, a government regulatory management platform, a government regulatory sensing network platform, a government regulatory object platform, a gas company sensing network platform, a gas user object platform, and a gas device object platform, wherein the public user platform is configured as terminal device, the government regulatory object platform includes the gas company management platform, the gas user object platform interacts with the gas company management platform via the gas company sensing network platform, the gas company management platform is configured on a gas company management server, the gas device object platform is configured in a gas pipeline facility and a gas pipeline auxiliary facility; the method comprising (platform, Bain ¶5; smart meters, ¶329, ¶333, and ¶379; internet of things, sensors, ¶407; distribution network, government entity, ¶289-¶290; the methods and systems described herein, such as those that relate to an energy marketplace platform and the like may be employed to provide notifications to consumers, to energy providers, to energy service organizations (e.g., ISOs, regulated energy service companies, and the like), to automated energy monitoring and management systems, and the like, ¶487; unified data repository, ¶330):
obtaining gas regulatory information of a plurality of gas regulatory regions based on the gas company sensing network platform, wherein the gas company sensing network platform includes a plurality of sets of communication sub-devices configured in different gas regulatory regions of the plurality of gas regulatory regions, and communication priorities of the plurality of sets of communication sub-devices in the different gas regulatory regions are different (An automated marketplace platform for energy and other utilities, referred to in some cases simply as the utility marketplace, utility marketplace, the marketplace, or the platform, is disclosed herein, with various systems, components, modules, services, facilities and processes (these being collectively referred to herein for convenience as “modules,” “components,” or the like), including information technology components specifically configured to enable consumers, such as retail consumers of energy and other utilities, to purchase and consume utilities efficiently and according to their preferences and needs, and including characteristics (such as relating to current and future energy and utility prices, sources of energy or utilities of particular types, and the like) of the underlying energy or utility infrastructure and marketplaces that are managed by incumbent entities like utilities, energy companies, and independent service organizations (ISOs). References to “energy” throughout this disclosure should be understood to encompass various types of energy, such as electricity, gas, and the like, and, except where the context indicates otherwise, embodiments referring to energy should be understood to encompass other utilities, such as water. The platform may include an architecture and components for obtaining and integrating data from a wide range of sources, including pricing and cost data, tax and credit data (such as relating to renewable energy credits), weather data, and other types of data from utilities, ISOs and other sources, Bain ¶5; smart meters, ¶329, ¶333, and ¶379; internet of things, sensors, ¶407);
determining target gas regulatory information from the gas regulatory information based on a target regulatory characteristic (target level of consumption, Bain ¶417-¶420; the usage reading and/or regulating devices behind the meter may use energy costs, capacity, raw energy sourcing, and related information to adjust how one or more devices that are associated with the usage reading and/or regulating device operate. Regulating how an energy consuming device operates, such as by controlling when it consumes energy and how much it consumes in a given timeframe, may contribute to regulation of consumption. Criteria may be set to guide the consumption of energy. In embodiments, criteria may include limits on cost of operation, carbon use (e.g., operating when renewable energy is used as a source of electricity), transmission and distribution grid congestion management, compliance with standards for electrical energy signal frequency, voltage, and the like, ¶334; based upon regulatory information, ¶468-¶471; markets with deregulation which is based upon location, ¶400);
updating data accountability levels of the different gas regulatory regions based on the target gas regulatory information (The various embodiments disclosed herein produce data that can be mined for a myriad of value-producing purposes, including device design by manufacturers, device selection and replacement at the consumer's home, grid management by the ISOs, and power station optimization. Home automation of energy use can be effected through increased control (such as enabled by the IoT), using information from the platform. Also, investment in grid infrastructure (such as new peak load investment as infrastructure needs replacement and new infrastructure projects reflect changes in population densities and usage habits) can use information from the platform 100, such as to predict changes in peak demand that may result from aggregate changes in user behavior. In embodiments, real time data mining may be used to better match generation operation with load demand, sidestepping or complementing the conventional ISO function of using marginal cost to balance the grid. Also, as rooftop solar becomes a bigger part of the energy mix in high solar markets, data collection on the generation side at the home can be collected, aggregated and fed into the real-time generation/load balancing process, Bain ¶399; net energy score, based upon location, ¶423; for taxes and credits, ¶330; ) (Examiner interprets the energy scores to be the accountability levels, which are based upon regulatory regions);
obtaining processed target gas regulatory information based on the redundant data and the contradictory data, and transmitting the processed target gas regulatory information to the government regulatory management platform via the government regulatory sensing network platform, so as to enable the government regulatory management platform to establish a gas regulatory database based on the processed target gas regulatory information and further provide a gas regulatory query service to a user through the public user platform (A utility marketplace platform 100 may match demand and supply. A utility marketplace platform 100 may match consumer demand and available wholesale energy supply, including via the work of a real-time pricing engine. A real-time pricing engine may calculate prices using real-time usage data across an aggregated set of consumer users, as well as using real-time energy production data across multiple production types (and across the different real-time wholesale prices associated with each of the production types). Historically, consumer energy meters were read about once per month or once per calendar quarter. Meters were measured and multiplied over a month or more and consumption amounts were multiplied by a fixed price to generate prices. A utility marketplace platform 100 may perform similar functions in much smaller increments (e.g., 15-minute increments), which may present vastly greater opportunities for consumers to obtain, and act upon, prices that are accurate in real time (i.e., on smaller time scales of as little as seconds, minutes, a fraction of an hour, an hour, a day, or the like). Real-time pricing handled in the real time pricing engine may reflect current market pricing and/or forward-looking market pricing, such as day-ahead pricing or pricing associated with other future time periods. In embodiments, the platform may separately handle forward-looking pricing, such as day-ahead pricing, using data from, for example, a day-ahead market in a manner similar to that depicted for real-time pricing. References to real-time pricing throughout this disclosure should be understood to encompass embodiments that use forward-looking pricing in combination with or as an alternative to current market pricing, except where context indicates otherwise, Bain ¶328); and
adjusting the communication priorities of the plurality of sets of communication sub- devices based on the data accountability levels, wherein the higher the data accountability level of a gas regulatory region is, the higher the communication priority of the communication sub-device corresponding to the gas regulatory region is adjusted (automatically notifying, Bain ¶104; notifications of actions to take, ¶487-¶491).
However, Cella teaches determining redundant data and contradictory data based on the target gas regulatory information and the data accountability levels (This may include computation of various statistics or measures. In embodiments, the analytic system 4018 may be disposed, at least in part, on a data collection system 102, such that a local analytic system can calculate one or more measures, such as measures relating to any of the items noted throughout this disclosure. For example, measures of efficiency, power utilization, storage utilization, redundancy, entropy, and other factors may be calculated onboard, so that the data collection 102 can enable various cognitive and learning functions noted throughout this disclosure without dependence on a remote (e.g., cloud-based) analytic system, Cella ¶328; favorable sources with reliable and accurate data, ¶330 and ¶950; see also data accuracy ¶1523) (Examiner interprets Cella’s ability to measure and provide information regarding the data accuracy as the determination of redundant and contradictory data).
Both the Bain and Cella references are analogous in that both are directed towards/concerned with management and analysis of utility consumption such as gas. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use Cella’s ability to determine data accuracy in Bain’s system to improve the system and method with reasonable expectation that this would result in a gas utility management system that is able to provide reliable real-time information.
The motivation being that there is a need for reporting of reliable data by sensors in order to facilitate grid stability (Cella ¶2145 and ¶2176).
As per claim 2, Bain and Cella disclose as shown above with respect to claim 1. Bain further discloses wherein the gas regulatory information includes gas business data and gas safety data, the gas business data includes gas engineering construction data, and the gas safety data includes gas pipeline network maintenance data (historical usage, demand patterns, maintenance, Bain ¶442; market information, capacity information, ¶81-¶82; aging of utility infrastructure, ¶346).
As per claims 3-4 and 14, Bain and Cella disclose as shown above with respect to claims 1 and 13. Bain further discloses wherein each communication sub-device of the plurality of sets of communication sub-devices includes and a routing device; wherein the communication priorities include a switching forwarding priority of the data switch and (The methods and systems described herein may be deployed in part or in whole through network infrastructures. The network infrastructure may include elements such as computing devices, servers, routers, hubs, firewalls, clients, personal computers, communication devices, routing devices and other active and passive devices, modules and/or components as known in the art. The computing and/or non-computing device(s) associated with the network infrastructure may include, apart from other components, a storage medium such as flash memory, buffer, stack, RAM, ROM, and the like. The processes, methods, program codes, instructions described herein and elsewhere may be executed by one or more of the network infrastructural elements. The methods and systems described herein may be adapted for use with any kind of private, community, or hybrid cloud computing network or cloud computing environment, including those which involve features of software as a service (SaaS), platform as a service (PaaS), and/or infrastructure as a service (IaaS), Bain ¶540).
Cella teaches a data switch, a packet concentrator, a routing forwarding priority of the routing device (self-organizing network, packet, Cella ¶346; cross point switching, ¶373-¶374; least cost routing, prioritization, ¶339).
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use Cella’s ability to determine data accuracy in Bain’s system to improve the system and method with reasonable expectation that this would result in a gas utility management system that is able to provide reliable real-time information.
The motivation being that there is a need for reporting of reliable data by sensors in order to facilitate grid stability (Cella ¶2145 and ¶2176).
As per claims 5 and 15, Bain and Cella disclose as shown above with respect to claims 1 and 13. Bain further discloses wherein the determining target gas regulatory information from the gas regulatory information based on a target regulatory characteristic includes: determining necessary regulatory information based on the target regulatory characteristic; automatically performing a dynamic adjustment on the target regulatory characteristic based on a feedback result of the government regulatory management platform and sending an adjustment result to the government regulatory management platform for record; obtaining historical regulatory data of the different gas regulatory regions and determining additional regulatory information from the gas regulatory information; and determining the target gas regulatory information based on the necessary regulatory information and the additional regulatory information (feedback of consumer responses, Bain ¶181; adjusting gamification for user, ¶185; use of historical data, ¶339; see also ¶421-¶422 for improving performance).
As per claims 6 and 16, Bain and Cella disclose as shown above with respect to claims 5 and 15. Bain further discloses wherein the dynamic adjustment further includes: adjusting the necessary regulatory information based on the feedback result, and historical problem data and an average data accountability level of the different gas regulatory regions (rewards, credits, rebates for clustering of behavior to improve, adjusting rules, weights, parameters, Bain ¶421-¶425).
As per claims 7 and 17, Bain and Cella disclose as shown above with respect to claims 5 and 15. Bain further discloses wherein the method further comprises: determining weighted frequency values of historical problem data corresponding to the different gas regulatory regions based on the historical problem data of the different gas regulatory regions, the historical problem data including historical gas fault data, historical communication transmission problem data, and historical gas processing problem data; determining the additional regulatory information corresponding to the different gas regulatory regions respectively based on the historical problem data, the weighted frequency values, historical redundant data, and historical contradictory data; and issuing a control command based on the additional regulatory information to adjust data collection frequencies of data monitoring devices corresponding to the different gas regulatory regions (Patterns classified, recognized or predicted in the platform 100, or used to make predictions within the platform 100 may further include consumer energy usage patterns, such as based on time of day, day of week, season, weather patterns, regional or geographic patterns, or the like. Patterns may include consumer energy source selection patterns, patterns in pricing differences, patterns in total overall energy cost, patterns in responsiveness to pricing alerts or other messages, patterns in consumer generated energy (e.g., solar) usage, and patterns in consumer generated energy sell-back to the grid, among others. Patterns may also include ones related to allocation of energy demand to providers who use different raw energy sources, including based on relative price of energy from different raw energy sources and/or based on availability of energy from the different raw energy sources. Patterns may include gamification patterns, such as reward types, reward allocations, reward amounts, filters used to arrange groups into games, and the like. Patterns may include price patterns for different raw energy sources for a given energy grid. Patterns may include patterns relating to the impact of other factors on energy prices, such as supply patterns, weather (e.g., outdoor temperature, hours of daily sun, wind patterns, water flow patterns, and the like), current and near-term usage and demand patterns, historical usage and demand patterns, and the like. Patterns may include maintenance patterns, such as for maintaining grid infrastructure, maintaining consumption devices, maintaining production devices, and the like, Bain ¶442; aging of utility infrastructure, ¶346; pattern of energy transmission, ¶437).
As per claim 8, Bain and Cella disclose as shown above with respect to claim 7. Bain further discloses wherein the weighted frequency values are determined based on different historical problem sub-data, and weights of the different historical problem sub-data are different (the machine learning engine uses a neural network is used to adjust presence of elements and/or weights on a model to improve the model, Bain ¶173).
As per claim 9, Bain and Cella disclose as shown above with respect to claim 6. Bain further discloses wherein an amount of data of the additional regulatory information is negatively correlated with an amount of data of the historical redundant data and an amount of data of the historical contradictory data, and a degree of the negative correlation is related to a data accountability level of another gas regulatory region corresponding to the historical redundant data and the historical contradictory data (negative wholesale, Bain ¶400; debt, ¶357; see also gamification of prediction in order to optimize quality of data, ¶339) (Examiner interprets the negative correlation related to a data accountability level as either a negative wholesale or debt).
As per claims 10 and 18, Bain and Cella disclose as shown above with respect to claims 1 and 13. Bain further discloses wherein the data accountability levels reflect a division of accountability regarding data quality in the different gas regulatory regions, and the updating data accountability levels of the different gas regulatory regions based on the target gas regulatory information includes: establishing a regulatory graph based on the different gas regulatory regions and different target gas regulatory information corresponding to the different gas regulatory regions, wherein nodes of the regulatory graph include the different gas regulatory regions and edges of the regulatory graph connect gas regulatory regions involved in data cross-management; and determining, based on the regulatory graph, updated data accountability levels of the different gas regulatory regions through a regulatory model, the regulatory model being a machine learning model (In embodiments, methods and systems described herein that involve an expert system or self-organization capability may use a recurrent neural network, which may allow for a bi-directional flow of data, such as where connected units (e.g., neurons or nodes) form a directed cycle. Such a network may be used to model or exhibit dynamic temporal behavior, such as involved in dynamic systems, such as a wide variety of the conditions, states, and systems described throughout this disclosure, such as involving behavior of a consumer 132 in response to dynamic conditions, such as the shift of energy mix, energy pricing, situations in a game, weather, or the like, Bain ¶410).
As per claims 11 and 19, Bain and Cella disclose as shown above with respect to claims 10 and 18. Cella further teaches wherein the regulatory graph refers to a graph established based on the different gas regulatory regions, the regulatory graph includes edges and nodes, an edge attribute of an edge of the edges of the regulatory graph includes a historical data accountability level and a current data accountability level of each of the gas regulatory regions corresponding to two nodes connected by the edge, and a node attribute of a node of the nodes of the regulatory graph includes historical redundant data, historical contradictory data, and a feedback result from the government regulatory management platform; and a type of the historical data accountability level includes a variable type and a fixed type, wherein the variable type refers to a value of the historical data accountability level is changeable, and the fixed type refers to that the value of the historical data accountability level remains constant (edge storage (e.g., in edge-based network nodes), usage, redundancy, reliability, Cella ¶1616; edge server, ¶1867).
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use Cella’s ability to determine data accuracy in Bain’s system to improve the system and method with reasonable expectation that this would result in a gas utility management system that is able to provide reliable real-time information.
The motivation being that there is a need for reporting of reliable data by sensors in order to facilitate grid stability (Cella ¶2145 and ¶2176).
As per claims 12 and 20, Bain and Cella disclose as shown above with respect to claims 10 and 18. Bain further discloses wherein the regulatory model is obtained through a training process including: inputting, by the gas company management platform, a plurality of training samples with labels into an initial regulatory model, wherein a training sample of the training samples include a sample regulatory graph, a label of the labels is a sequence of the updated data accountability levels, the sample regulatory graph includes positive samples and negative samples, and a difference between a count of the positive samples and a count of the negative samples is less than a first preset threshold; constructing a loss function based on the labels and a result of the initial regulatory model; iteratively updating a parameter of the initial regulatory model based on the loss function; and in response to determining that the loss function satisfies a preset condition, completing the training of the regulatory model, and obtaining the regulatory model, wherein the preset condition includes that the loss function converges, or a count of iterations reaches a first threshold (infrastructure nodes, seeded by training set, Cella ¶1664; The method may include maintaining, at the first node, a queue of preemptively computed redundancy messages for the number of messages and, in response to receiving a feedback message indicating successful delivery of the number of messages, removing any preemptively computed redundancy messages associated with the number of messages from the queue of preemptively computed redundancy messages. The degree of redundancy associated with each of the messages may characterize a probability of correctability of an erasure of the message. The probability of correctability may depend on a comparison of between the degree of redundancy and a loss probability, ¶1732).
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use Cella’s ability to determine data accuracy in Bain’s system to improve the system and method with reasonable expectation that this would result in a gas utility management system that is able to provide reliable real-time information.
The motivation being that there is a need for reporting of reliable data by sensors in order to facilitate grid stability (Cella ¶2145 and ¶2176).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure can be located on the PTO-892.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to ANDREW B WHITAKER whose telephone number is (571)270-7563. The examiner can normally be reached on M-F, 8am-5pm, EST.
If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Lynda Jasmin can be reached on (571) 272-6782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ANDREW B WHITAKER/Primary Examiner, Art Unit 3629