DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims 1-20 are currently pending in application 19/234,237.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 8/1/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-9 of U.S. Patent No. 12,361,434. Although the claims at issue are not identical, they are not patentably distinct from each other because both inventions disclose equivalent elements for smart gas pipeline pressure adjustment systems that responds to gas construction projects, such as pipeline repairs or new facility builds.
US 19/234,237
US 12361434 (US 18/823,648)
1./20. A method (programmed apparatus) for smart gas pipeline pressure adjustment, wherein the method is performed by a processor of a government supervision and management platform of an Internet of Things (loT) system for smart gas pipeline pressure adjustment, and the method comprises:
obtaining monitoring image data of a construction region where a gas construction project is located from a gas supervision device;
determining a project impact level and a project estimated completion time of the gas construction project based on the monitoring image data, sending the project impact level to a gas company management platform, and sending the project estimated completion time to a citizen user platform for announcement and display;
5. The method of claim 1, wherein the project impact level is further related to a result of a current inspection of the gas construction project by a gas regulator and project progress of a previous inspection, the result of the current inspection and the project progress of the previous inspection being obtained from the government supervision service platform; and the determining a project impact level and a project estimated completion time of the gas construction project based on the monitoring image data includes:
determining project information of the gas construction project based on the monitoring image data, the result of the current inspection, and the project progress of the previous inspection;
determining the project estimated completion time of the gas construction project based on the project information; and
determining the project impact level of the gas construction project based on the project information, the result of the current inspection, and the project estimated completion time.
determining regulatory parameters based on the project impact level and the project estimated completion time, and sending the regulatory parameters to a gas equipment object platform via the gas company management platform and a gas company sensing network platform, the gas equipment object platform including one or more gas pressure regulating devices, the regulatory parameters including pressure regulating parameters of at least one group of gas pipelines, wherein the pressure regulating parameters are related to a gas regulator arrangement, the gas regulator arrangement is obtained based on the government supervision and management platform, and the determining regulatory parameters based on the project impact level and the project estimated completion time includes:
determining, based on a candidate pressure regulating parameter, the project impact level, the project estimated completion time, and the gas regulator arrangement using an interference level determination model, an interference level of the candidate pressure regulating parameter, the interference level determination model being a machine learning model;
8. The method of claim 1, wherein the regulatory parameters further include an adjusted gas regulator arrangement; and the determining regulatory parameters based on the project impact level and the project estimated completion time includes: determining the adjusted gas regulator arrangement based on the project impact level and the project estimated completion time.
9. The method of claim 8, wherein the determining the adjusted gas regulator arrangement based on the project impact level and the project estimated completion time includes: assessing a potential problem probability in the construction region where the gas construction project is located based on the project impact level, the project estimated completion time, and the gas regulator arrangement; and determining the adjusted gas regulator arrangement based on the potential problem probability.
10. The method of claim 9, wherein the assessing a potential problem probability in the construction region where the gas construction project is located based on the project impact level, the project estimated completion time, and the gas regulator arrangement includes: assessing the potential problem probability in the construction region where the gas construction project is located based on the project impact level, the project estimated completion time, and the gas regulator arrangement, using a problem probability determination model, the problem probability determination model being a machine learning model.
11. The method of claim 10, wherein the problem probability determination model is a supervised machine learning model, the problem probability determination model includes a feature extraction layer and a problem probability prediction layer, the feature extraction layer and the problem probability prediction layer are both neural network models; a training process of the problem probability determination model includes at least a first stage of training, the first stage of training including training based on a first training set, validation based on a first validation set, and testing based on a first test set, wherein the first training set, the first test set, and the first validation set are data sets extracted from historical data and include the project impact level, the project estimated completion time, and the gas regulator arrangement of historical gas construction projects, wherein a data amount of the first training set, a data amount of the first test set, and a data amount of the first validation set are in a first preset ratio; the first training set, the first test set, and the first validation set do not have overlap data; and a statistical difference of samples of the first training set is greater than a preset difference threshold, the preset difference threshold being related to an average construction duration of the historical gas construction projects.
2. The method of claim 1, wherein a training process of the interference level determination model includes: inputting a plurality of first training samples with first training labels into an initial interference level determination model; constructing a loss function based on the first training labels and a result of the initial interference level determination model; iteratively updating parameters of the initial interference level determination model based on the loss function via gradient descent; and completing the iterations until a preset condition is satisfied and obtaining a trained interference level confirmation model, the preset condition including convergence of the loss function converges or a count of iterations reaching a threshold.
determining the pressure regulating parameters of the at least one group of gas pipelines based on the interference level;
obtaining pipeline pressure values of the at least one group of gas pipelines through the one or more gas pressure regulating devices;
determining a fluctuation characteristic or a pressure difference distribution characteristic based on the pipeline pressure values; and
generating a pressure regulating instruction based on the regulatory parameters, and the fluctuation characteristic or the pressure difference distribution characteristic, and sending the pressure regulating instruction to the one or more gas pressure regulating devices to perform pressure adjustment on the at least one group of gas pipelines based on the pressure regulating instruction.
3. The method of claim 1, wherein the loT system for smart gas pipeline pressure adjustment further includes the citizen user platform, a government supervision service platform, a government supervision sensing network platform, a government supervision object platform, the gas company sensing network platform, a gas equipment object platform, a gas user service platform, and a gas user platform; the government supervision service platform includes a government safety supervision service platform; the government supervision and management platform includes a government safety supervision and management platform; the government supervision sensing network platform includes a government safety supervision sensing network platform; and the government supervision object platform includes the gas company management platform; the citizen user platform is configured to obtain user evaluation information, send the user evaluation information to the government supervision service platform, and receive project information and the project estimated completion time uploaded by the government supervision service platform; the government supervision service platform is configured to interact with the citizen user platform and the government safety supervision and management platform; the government supervision and management platform is configured to interact with the government safety supervision service platform and the government safety supervision sensing network platform; the government supervision sensing network platform is configured to interact with the gas company management platform and the government safety supervision and management platform; the government supervision object platform is configured to interact with the gas company sensing network platform, the government safety supervision sensing network platform, and the gas user service platform; the gas equipment object platform is configured to interact with the gas company sensing network platform; and the gas user platform is configured to interact with the gas user service platform.
4. The method of claim 3, wherein the gas equipment object platform includes the gas supervision device, the government supervision and management platform includes the processor and a communication device, and the processor is located on a user terminal; the gas supervision device is configured to capture the monitoring image data of the construction region where the gas construction project is located; and the communication device is configured to communicate between the gas supervision device and the processor.
6. The method of claim 5, wherein the determining the project impact level of the gas construction project based on the project information, the result of the current inspection, and the project estimated completion time includes: sending the project information and the project estimated completion time to the citizen user platform; obtaining user evaluation information based on the citizen user platform; and determining the project impact level of the gas construction project based on the user evaluation information, the result of the current inspection, the project information, and the project estimated completion time.
7. The method of claim 6, wherein the project impact level is further related to an interference level of the pressure regulating parameters of the at least one group of gas pipelines; and the determining the project impact level of the gas construction project based on the user evaluation information, the result of the current inspection, the project information, and the project estimated completion time includes: determining the project impact level of the gas construction project based on the interference level of the pressure regulating parameters of the at least one group of gas pipelines, the user evaluation information, the project information, the result of the current inspection, and the project estimated completion time.
12. An Internet of Things (loT) system for smart gas pipeline pressure adjustment, comprising a citizen user platform, a government supervision and management platform, a government supervision sensing network platform, a government supervision object platform, a gas company sensing network platform, a gas equipment object platform, a gas user service platform, and a gas user platform; wherein
the government supervision service platform includes a government safety supervision service platform;
the government supervision and management platform includes a government safety supervision and management platform;
the government supervision sensing network platform includes a government safety supervision sensing network platform; and
the government supervision object platform includes a gas company management platform;
the citizen user platform is configured to obtain user evaluation information, send the user evaluation information to the government supervision service platform, and receive project information and a project estimated completion time uploaded by the government supervision service platform;
the government supervision service platform is configured to interact with the citizen user platform and the government safety supervision and management platform;
the government supervision and management platform is configured to interact with the government safety supervision service platform and the government safety supervision sensing network platform;
the government supervision sensing network platform is configured to interact with the gas company management platform, the government safety supervision and management platform, and the gas user service platform;
the government supervision object platform is configured to interact with the gas company sensing network platform, the government safety supervision sensing network platform, and the gas user service platform;
the gas equipment object platform is configured to interact with the gas company sensing network platform; and
the gas user platform is configured to interact with the gas user service platform.
13. The loT system of claim 12, wherein
the gas equipment object platform includes a gas supervision device, a processor, a communication device, and a user terminal, the processor being disposed on the user terminal;
the gas supervision device is configured to obtain monitoring image data of a construction region where a gas construction project is located; and
the communication device is configured to communicate between the gas supervision device and the processor;
the processor is configured to:
obtain the monitoring image data from the gas supervision device and upload the monitoring image data to the gas company management platform through the communication device;
determine a project impact level and a project estimated completion time of the gas construction project based on the monitoring image data, send the project impact level to a gas company management platform, and send the project estimated completion time to the citizen user platform for announcement and display;
15. The loT system of claim 13,
wherein the project impact level is further related to a result of a current inspection of the gas construction project by a gas regulator and project progress of a previous inspection, the result of the current inspection and the project progress of the previous inspection being obtained from the government supervision service platform; and the processor is further configured to:
determine the project information of the gas construction project based on the monitoring image data, the result of the current inspection, and the project progress of the previous inspection;
determine the project estimated completion time of the gas construction project based on the project information; and
determine the project impact level of the gas construction project based on the project information, the result of the current inspection, and the project estimated completion time.
determine regulatory parameters based on the project impact level and the project estimated completion time, and send the regulatory parameters to the gas equipment object platform via the gas company management platform and a gas company sensing network platform, the gas equipment object platform including one or more gas pressure regulating devices, the regulatory parameters including pressure regulating parameters of at least one group of gas pipelines,
wherein the pressure regulating parameters are related to a gas regulator arrangement, the gas regulator arrangement is obtained based on the government supervision and management platform, and to determining the regulatory parameters based on the project impact level and the project estimated completion time, the processor is further configured to:
determine, based on a candidate pressure regulating parameter, the project impact level, the project estimated completion time, and the gas regulator arrangement using an interference level determination model, an interference level of the candidate pressure regulating parameter, the interference level determination model being a machine learning model;
17. The loT system of claim 15, wherein the regulatory parameters further include an adjusted gas regulator arrangement; and the processor is further configured to:
determine the adjusted gas regulator arrangement based on the project impact level and the project estimated completion time.
18. The loT system of claim 17, wherein the processor is further configured to:
assess a potential problem probability in the construction region where the gas construction project is located based on the project impact level, the project estimated completion time, and the gas regulator arrangement; and determine the adjusted gas regulator arrangement based on the potential problem probability.
19. The loT system of claim 18, wherein the processor is further configured to:
assess the potential problem probability in the construction region where the gas construction project is located based on the project impact level, the project estimated completion time, and the gas regulator arrangement using a problem probability determination model, the problem probability determination model being a machine learning model.
14. The loT system of claim 13, wherein a training process of the interference level determination model includes: inputting a plurality of first training samples with first training labels into an initial interference level determination model; constructing a loss function based on the first training labels and a result of the initial interference level determination model; iteratively updating parameters of the initial interference level determination model based on the loss function via gradient descent; and completing the iterations until a preset condition is satisfied and obtaining a trained interference level confirmation model, the preset condition including convergence of the loss function converges or a count of iterations reaching a threshold.
determine the pressure regulating parameters of the at least one group of gas pipelines based on the interference level;
obtain pipeline pressure values of the at least one group of gas pipelines through the one or more gas pressure regulating devices;
determine a fluctuation characteristic or a pressure difference distribution characteristic based on the pipeline pressure values; and
generate a pressure regulating instruction based on the regulatory parameters, and the fluctuation characteristic or the pressure difference distribution characteristic, and send the pressure regulating instruction to the one or more gas pressure regulating devices to perform pressure adjustment on the at least one group of gas pipelines based on the pressure regulating instruction.
16. The loT system of claim 15, wherein the processor is further configured to: send the project information and the project estimated completion time to the citizen user platform; obtain user evaluation information based on the citizen user platform; and determine the project impact level of the gas construction project based on the user evaluation information, the result of the current inspection, the project information, and the project estimated completion time.
1. A method for smart gas construction supervision, wherein the method is performed by a processor of a government supervision and management platform of an Internet of Things (IoT) system for smart gas construction supervision, and the method comprises:
obtaining monitoring image data of a construction region where a gas construction project is located from a gas supervision device;
determining a project impact level and a project estimated completion time of the gas construction project based on the monitoring image data, sending the project impact level to a gas company management platform, and sending the project estimated completion time to a citizen user platform for announcement and display,
wherein the project impact level is related to a result of a current inspection of the gas construction project by a gas regulator and project progress of a previous inspection, the result of the current inspection and the project progress of the previous inspection are obtained from the government supervision service platform, and the determining a project impact level and a project estimated completion time of the gas construction project based on the monitoring image data includes:
determining project information of the gas construction project based on the monitoring image data, the result of the current inspection, and the project progress of the previous inspection;
determining the project estimated completion time of the gas construction project based on the project information; and
determining the project impact level of the gas construction project based on the project information, the result of the current inspection, and the project estimated completion time;
determining regulatory parameters based on the project impact level and the project estimated completion time, and sending the regulatory parameters to a gas equipment object platform via the gas company management platform and a gas company sensing network platform, the gas equipment object platform including one or more gas pressure regulating devices, the regulatory parameters including pressure regulating parameters of at least one group of gas pipelines and an adjusted gas regulator arrangement, wherein the pressure regulating parameters are related to a gas regulator arrangement, the gas regulator arrangement is obtained based on the government supervision and management platform, and the determining regulatory parameters based on the project impact level and the project estimated completion time includes:
determining the pressure regulating parameters of the at least one group of gas pipelines based on the project impact level, the project estimated completion time, and the gas regulator arrangement;
determining the adjusted gas regulator arrangement based on the project impact level and the project estimated completion time, including:
assessing a potential problem probability in the construction region where the gas construction project is located through a problem probability determination model based on the project impact level, the project estimated completion time, and the gas regulator arrangement; wherein
the problem probability determination model is a supervised machine learning model and includes a feature extraction layer and a problem probability prediction layer, the feature extraction layer and the problem probability prediction layer being both neural network models;
a training process of the problem probability determination model includes at least a first stage of training, the first stage of training includes a training based on a first training set, a validation based on a first validation set, and a testing based on a first test set, wherein the first training set, the first test set, and the first validation set are data sets extracted from historical data and include the project impact level, the project estimated completion time, and a gas regulator arrangement of historical gas construction projects, a data amount of the first training set, a data amount of the first test set, and a data amount of the first validation set are in a first preset ratio; the first training set, the first test set, and the first validation set do not have overlap data, and a statistical difference of samples of the first training set is greater than a preset difference threshold, the preset difference threshold is related to an average construction duration of the historical gas construction projects; and
determining the adjusted gas regulator arrangement based on the potential problem probability;
obtaining pipeline pressure values of the at least one group of gas pipelines through the one or more gas pressure regulating devices;
determining a fluctuation characteristic or a pressure difference distribution characteristic based on the pipeline pressure values; and
generating a pressure regulating instruction based on the regulatory parameters, and the fluctuation characteristic or the pressure difference distribution characteristic, and sending the pressure regulating instruction to the one or more gas pressure regulating devices to perform pressure adjustment on the at least one group of gas pipelines based on the pressure regulating instruction.
2. The method of claim 1, wherein the IoT system for smart gas construction supervision further includes the citizen user platform, a government supervision service platform, a government supervision sensing network platform, a government supervision object platform, the gas company sensing network platform, a gas equipment object platform, a gas user service platform, and a gas user platform; the government supervision service platform includes a government safety supervision service platform; the government supervision and management platform includes a government safety supervision and management platform; the government supervision sensing network platform includes a government safety supervision sensing network platform; and the government supervision object platform includes the gas company management platform; the citizen user platform is configured to obtain user evaluation information, send the user evaluation information to the government supervision service platform, and receive project information and the project estimated completion time uploaded by the government supervision service platform; the government supervision service platform is configured to interact with the citizen user platform and the government safety supervision and management platform; the government supervision and management platform is configured to interact with the government safety supervision service platform and the government safety supervision sensing network platform; the government supervision sensing network platform is configured to interact with the gas company management platform and the government safety supervision and management platform; the government supervision object platform is configured to interact with the gas company sensing network platform, the government safety supervision sensing network platform, and the gas user service platform; the gas equipment object platform is configured to interact with the gas company sensing network platform; and the gas user platform is configured to interact with the gas user service platform.
3. The method of claim 2, wherein the gas equipment object platform includes the gas supervision device, the government supervision and management platform includes the processor and a communication device, and the processor is located on a user terminal; the gas supervision device is configured to capture the monitoring image data of the construction region where the gas construction project is located and upload the monitoring image data to the gas company management platform via the gas company sensing network platform, wherein the gas supervision device includes a drone, a video camera, and a video recorder; and the communication device is configured to communicate between the gas supervision device and the processor.
4. The method of claim 1, wherein the generating the pressure regulating instruction based on the regulatory parameters, and the fluctuation characteristic or the pressure difference distribution characteristic includes: determining whether regulatory parameters of the at least one group of gas pipelines is within the fluctuation characteristic or the pressure difference distribution characteristic based on the regulatory parameters; in response to the regulatory parameters being within the fluctuation characteristic or the pressure difference distribution characteristic, maintaining the regulatory parameters, generating the pressure regulating instruction based on the regulatory parameters, and sending the pressure regulating instruction to corresponding gas pipeline whose gas pressure needs to be regulated; and in response to the regulatory parameters being not within the fluctuation characteristic or the pressure difference distribution characteristic, discarding the regulatory parameters and performing no pressure regulation.
5. The method of claim 1, wherein the determining the adjusted gas regulator arrangement based on the project impact level and the project estimated completion time further includes: adjusting the gas regulator arrangement in a current group to a specific number based on a count of gas regulators; and controlling the gas regulators to operate based on the specific number.
6. The method of claim 1, wherein the determining the project impact level of the gas construction project based on the project information, the result of the current inspection, and the project estimated completion time includes: sending the project information and the project estimated completion time to the citizen user platform; obtaining user evaluation information based on the citizen user platform; and determining the project impact level of the gas construction project based on the user evaluation information, the result of the current inspection, the project information, and the project estimated completion time.
7. The method of claim 6, wherein the project impact level is further related to an interference level of the pressure regulating parameters of the at least one group of gas pipelines; and the determining the project impact level of the gas construction project based on the user evaluation information, the result of the current inspection, the project information, and the project estimated completion time includes: determining the project impact level of the gas construction project based on the interference level of the pressure regulating parameters of the at least one group of gas pipelines, the user evaluation information, the project information, the result of the current inspection, and the project estimated completion time.
8. The method of claim 1, wherein the determining the pressure regulating parameters of the at least one group of gas pipelines based on the project impact level, the project estimated completion time, and the gas regulator arrangement includes: determining, based on a candidate pressure regulating parameter, the project impact level, the project estimated completion time, and the gas regulator arrangement using an interference level determination model, an interference level of the candidate pressure regulating parameter, the interference level determination model being a machine learning model; and determining the pressure regulating parameters of the at least one group of gas pipelines based on the interference level.
9. An Internet of Things (IoT) system for smart gas construction supervision, comprising a citizen user platform, a government supervision and management platform, a government supervision sensing network platform, a government supervision object platform, a gas company sensing network platform, a gas equipment object platform, a gas user service platform, and a gas user platform; wherein
the government supervision service platform includes a government safety supervision service platform;
the government supervision and management platform includes a government safety supervision and management platform;
the government supervision sensing network platform includes a government safety supervision sensing network platform; and
the government supervision object platform includes a gas company management platform;
the citizen user platform is configured to obtain user evaluation information, send the user evaluation information to the government supervision service platform, and receive project information and a project estimated completion time uploaded by the government supervision service platform;
the government supervision service platform is configured to interact with the citizen user platform and the government safety supervision and management platform;
the government supervision and management platform is configured to interact with the government safety supervision service platform and the government safety supervision sensing network platform;
the government supervision sensing network platform is configured to interact with the gas company management platform, the government safety supervision and management platform, and the gas user service platform;
the government supervision object platform is configured to interact with the gas company sensing network platform, the government safety supervision sensing network platform, and the gas user service platform;
the gas equipment object platform is configured to interact with the gas company sensing network platform;
the gas user platform is configured to interact with the gas user service platform;
the gas equipment object platform includes a gas supervision device, a processor, a communication device, and a user terminal, the processor being disposed on the user terminal;
the gas supervision device is configured to capture monitoring image data of a construction region where a gas construction project is located;
the communication device is configured to communicate between the gas supervision device and the processor;
the processor is configured to:
obtain the monitoring image data from the gas supervision device and upload the monitoring image data to the gas company management platform through the communication device;
determine a project impact level and a project estimated completion time of the gas construction project based on the monitoring image data, send the project impact level to a gas company management platform, and send the project estimated completion time to the citizen user platform for announcement and display,
wherein the project impact level is related to a result of a current inspection of the gas construction project by a gas regulator and project progress of a previous inspection, the result of the current inspection and the project progress of the previous inspection are obtained from the government supervision service platform, and to determine the project impact level and the project estimated completion time of the gas construction project based on the monitoring image data, the processor is further configured to:
determine project information of the gas construction project based on the monitoring image data, the result of the current inspection, and the project progress of the previous inspection;
determine the project estimated completion time of the gas construction project based on the project information; and
determine the project impact level of the gas construction project based on the project information, the result of the current inspection, and the project estimated completion time;
determine regulatory parameters based on the project impact level and the project estimated completion time, and send the regulatory parameters to the gas equipment object platform via the gas company management platform and a gas company sensing network platform, the gas equipment object platform including one or more gas pressure regulating devices, the regulatory parameters including pressure regulating parameters of at least one group of gas pipelines and an adjusted gas regulator arrangement,
wherein the pressure regulating parameters are related to a gas regulator arrangement, the gas regulator arrangement is obtained based on the government supervision and management platform, and to determine the regulatory parameters based on the project impact level and the project estimated completion time, the processor is further configured to:
determine the pressure regulating parameters of the at least one group of gas pipelines based on the project impact level, the project estimated completion time, and the gas regulator arrangement;
determining the adjusted gas regulator arrangement based on the project impact level and the project estimated completion time including:
assessing a potential problem probability in the construction region where the gas construction project is located through a problem probability determination model based on the project impact level, the project estimated completion time, and the gas regulator arrangement; wherein
the problem probability determination model is a supervised machine learning model and includes a feature extraction layer and a problem probability prediction layer, the feature extraction layer and the problem probability prediction layer being both neural network models;
a training process of the problem probability determination model includes at least a first stage of training, the first stage of training includes a training based on a first training set, a validation based on a first validation set, and a testing based on a first test set, wherein the first training set, the first test set, and the first validation set are data sets extracted from historical data and include the project impact level, the project estimated completion time, and a gas regulator arrangement of historical gas construction projects, a data amount of the first training set, a data amount of the first test set, and a data amount of the first validation set are in a first preset ratio; the first training set, the first test set, and the first validation set do not have overlap data, and a statistical difference of samples of the first training set is greater than a preset difference threshold, the preset difference threshold is related to an average construction duration of the historical gas construction projects; and
determining the adjusted gas regulator arrangement based on the potential problem probability:
obtain pipeline pressure values of the at least one group of gas pipelines through the one or more gas pressure regulating devices;
determine a fluctuation characteristic or a pressure difference distribution characteristic based on the pipeline pressure values; and
generate a pressure regulating instruction based on the regulatory parameters, and the fluctuation characteristic or the pressure difference distribution characteristic, and send the pressure regulating instruction to the one or more gas pressure regulating devices to perform pressure adjustment on the at least one group of gas pipelines based on the pressure regulating instruction.
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 12 and 15-19 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to non-statutory subject matter, specifically an abstract idea.
Claims 12 and 15-19 are directed to a judicial exception (i.e., abstract idea), without providing a practical application, and without providing significantly more.
Under the 35 U.S.C. §101 subject matter eligibility two-part analysis, Step 1 addresses whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. See MPEP §2106.03. If the claim does fall within one of the statutory categories, it must then be determined in Step 2A [prong 1] whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea). See MPEP §2106.04. If the claim is directed toward a judicial exception, it must then be determined in Step 2A [prong 2] whether the judicial exception is integrated into a practical application. See MPEP §2106.04(d). Finally, if the judicial exception is not integrated into a practical application, it must additionally be determined in Step 2B whether the claim recites "significantly more" than the abstract idea. See MPEP §2106.05.
Examiner note: The Office’s 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG) is currently found in the Ninth Edition, Revision 10.2019 (revised June 2020) of the Manual of Patent Examination Procedure (MPEP), specifically incorporated in MPEP §2106.03 through MPEP §2106.07(c).
Regarding Step 1,
Claims 12 and 15-19 are directed toward an apparatus (system). Thus, all claims fall within one of the four statutory categories as required by Step 1.
Regarding Step 2A [prong 1],
Claims 12 and 15-19 are directed toward the judicial exception of an abstract idea. Independent claim 12 is directed specifically to the abstract idea of administrative tracking, data gathering, and inter-organizational communication.
Regarding independent claim 12, the underlined limitations emphasized below correspond to the abstract ideas of the claimed invention:
An Internet of Things (loT) system for smart gas pipeline pressure adjustment, comprising:
a citizen user platform, [Certain methods of organizing human activity - Managing personal behavior or relationships / commercial interactions (gathering and reporting customer feedback)]
a government supervision service platform, [Certain methods of organizing human activity - Managing human activity and routine administrative communication (coordinating supervisory information)]
a government supervision and management platform, [Certain methods of organizing human activity - Managing regulatory compliance and data routing between administrative tiers]
a government supervision sensing network platform, [Certain methods of organizing human activity - Managing regulatory compliance and data routing between administrative tiers]
a government supervision object platform/ gas company management platform, [Certain methods of organizing human activity - Keeping business operational records and tracking enterprise assets or objects.]
a gas equipment object platform/ a gas user platforms. [Certain methods of organizing human activity - Observation and data logging regarding physical equipment use.]
As the underlined claim limitations above demonstrate, independent claim 12 are directed to the abstract idea of Certain methods of organizing human activity (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)).
Dependent claims 15-19 provide further details to the abstract idea of claim 12 regarding the received data, therefore, these claims include certain methods of organizing human activities for similar reasons provided above for claim 12.
After considering all claim elements, both individually and in combination and in ordered combination, it has been determined that the claims do not amount to significantly more than the abstract idea itself.
Regarding Step 2A [prong 2],
Claims 12 and 15-19 fail to integrate the recited judicial exception into any practical application. The claims recite additional limitations which are hardware or software elements or particular technological environment, such as a “Internet of Things (loT) system” and a “platform”. However, these limitations are not enough to qualify as “practical application” being recited in the claims along with the abstract idea since these limitations are merely invoked as a tool to perform instruction of an abstract idea in a particular technological environment and/or are generally linking the use of the abstract idea to a particular technological environment or field of use, and merely applying and abstract idea in a particular technological environment and merely limiting use of an abstract idea to a particular field or a technological environment do not provide practical application for an abstract idea (MPEP 2106.05 (f) & (h)). The claims do not amount to "practical application" for the abstract idea because they neither (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; (4) effect a transformation or reduction of a particular article to a different state or thing; (5) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment.
The presence of a machine learning algorithm or computer implementations do not necessarily restrict the claim from reciting an abstract idea. The machine learning algorithm and computer limitations claimed herein are simply used as a tool to apply the abstract idea without transforming the underlying abstract idea into patent eligible subject matter. As claimed (dependent claim 19), the machine learning algorithm as specifically claimed is not a technical improvement, nor is the machine learning algorithm iteratively trained to improve the accuracy of the model itself, it merely processes data to achieve a business scheduling objective based on factors, function objectives, and received input. Examiner notes that the additional limitations of machine learning and computer processing do not result in computer functionality or technical/technology improvement and hence do not result in a practical application. The machine learning algorithm and the computer limitation simply process the data through inputting and outputting data. Processing data is mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 Fed.Cir. 2017) or speeding up a loan application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, Lending Tree, LLLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2019)(non-precedential). Thus, the additional limitations of machine learning algorithm and computer limitations do not transform the abstract idea into a practical application.
The relevant question under Step 2A [prong 2] is not whether the claimed invention itself is a practical application, instead, the question is whether the claimed invention includes additional elements beyond the judicial exception that integrate the judicial exception into a practical application by imposing a meaningful limit on the judicial exception. This is not the case with Applicant’s claimed invention. Automating the recited claimed features as a combination of computer instructions implemented by computer hardware and/or software elements as recited above does not qualify an otherwise unpatentable abstract idea as patent eligible. Examples where the Courts have found selecting a particular data source or type of data to be manipulated to be insignificant extra-solution activity include selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016); Applicant’s limitations as recited above do nothing more than supplement the abstract idea using additional hardware/software computer components as a tool to perform the abstract idea and generally link the use of the abstract idea to a technological environment, which is not sufficient to integrate the judicial exception into a practical application since they do not impose any meaningful limits. Dependent claims 15-19 merely incorporate the additional elements recited above, along with further embellishments of the abstract idea of independent claims respectively, but these features only serve to further limit the abstract idea of independent claims. Therefore, the additional elements recited in the claimed invention individually, and in combination fail to integrate the recited judicial exception into any practical application.
Regarding Step 2B,
Claims 12 and 15-19 fail to amount to “significantly more” than an abstract idea. The claims recite additional limitations which are hardware or software elements or particular technological environment, such as a “Internet of Things (loT) system” and a “platform”. However, these limitations are not enough to qualify as “significantly more” being recited in the claims along with the abstract idea since these limitations are merely invoked as a tool to perform instruction of Abstract idea in a particular technological environment and/or are generally linking the use of the abstract idea to a particular technological environment or field of use, and merely applying and abstract idea in a particular technological environment and merely limiting use of an abstract idea to a particular field or a technological environment do not provide significantly more to an abstract idea (MPEP 2106.05(f) & (h)). The claims do not amount to "significantly more" than the abstract idea because they neither (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; (4) effect a transformation or reduction of a particular article to a different state or thing; (5) add a specific limitation other than what is well-understood, routine and conventional in the field; (6) add unconventional steps that confine the claim to a particular useful application; nor (7) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment.
Dependent claims 15-19 merely recite further additional embellishments of the abstract idea of independent claim 12 respectively, but these features only serve to further limit the abstract idea of independent claim 12; however, none of the dependent claims recite an improvement to a technology or technical field or provide any meaningful limits. The addition of another abstract concept to the limitations of the claims does not render the claim other than abstract. Under the Interim Guidance on Patent Subject Matter Eligibility (PEG 2019), it specifically states that narrowing an abstract idea of claims do not resolve the claims of being "significantly more" than the abstract idea. Thus, the additional elements in the dependent claims only serve to further limit the abstract idea utilizing the computer components as a tool and/or generally link the use of the abstract idea to a particular technological environment.
Therefore, since there are no limitations in the claims 12 and 15-19 that transform the exception into a patent eligible application such that the claims amount to significantly more than the exception itself, and looking at the limitations as a combination and as an ordered combination adds nothing that is not already present when looking at the elements taken individually, claims 12 and 15-19 are rejected under 35 USC § 101 as being directed to non-statutory subject matter under 35 U.S.C. § 101.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 12-19 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Wang et al. (US 2025/0071040 A1).
As per independent Claim 12, Wang discloses an Internet of Things (loT) system for smart gas pipeline pressure adjustment (Intended use), comprising a citizen user platform, a government supervision and management platform, a government supervision sensing network platform, a government supervision object platform, a gas company sensing network platform, a gas equipment object platform, a gas user service platform, and a gas user platform; wherein the government supervision service platform includes a government safety supervision service platform; the government supervision and management platform includes a government safety supervision and management platform; the government supervision sensing network platform includes a government safety supervision sensing network platform; and the government supervision object platform includes a gas company management platform (See at least Figs.1-1B, Equivalent Platforms and connections disclosed – Para 0004, “This disclosure involves the Internet of Things system and its multiple layers, including terminal layer, transmission layer, support layer, artificial intelligence business platform layer and city operation comprehensive IOC layer, also includes: security management platform, unified operation and maintenance management platform and IT resource service. It specifically involves technologies such as industry terminals, edge computing, intelligent data fusion, artificial intelligence, streaming media, blockchain security management, digital twins, integrated communications, intelligent inspection, unified operation and maintenance, and cloud management.”; Para 0008, “The Internet of Things system or industrial Internet system provided by this disclosure is built for the smart twin/smart empowerment of various industries, covering multiple levels. The whole can be divided into five horizontal and three vertical, and the five horizontal from bottom to top are terminal layer, transmission layer, support layer, artificial intelligence business platform layer, and urban operation comprehensive IOC layer. The three verticals are security, operation and maintenance, and IT resource services, in which security and operation and maintenance vertically run through all horizontal levels, providing full-chain, end-to-end services: IT resource services are support layer, artificial intelligence business platform layer and urban operation integration. The IOC layer provides services (For example: FIG. 1B)”; See also Para 0021-0033, Para 0039, Para 0276, and Para 0286).
As for the limitations of the functions of the system/apparatus or what the system/apparatus does, i.e. “the citizen user platform is configured to obtain user evaluation information, send the user evaluation information to the government supervision service platform, and receive project information and a project estimated completion time uploaded by the government supervision service platform”, these carry no patentable weight in an apparatus claim. Apparatus claims should cover what a device is or structures or structural elements, not what a device does. See Hewlett-Packard Co. vs. Bausch & Lomb Inc., 909 F 2.d 1464, 1469, 15 USPQ2d 1525, 1528 (Fed. Cir. 1990).
As for Dependent Claims 13-19, which further deal with other functions of the system/apparatus, they are rejected for the same reason set forth in Claims 12 above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure can be found in the PTO-892 Notice of References Cited. The Examiner suggests the applicant review all of these documents before submitting any amendments.
Sahoo (Sahoo, Nihar Ranjan, "GeoAI in Pipeline Monitoring and Management", CYIENT blog, June 5, 2024.) – Sahoo discloses an automated pipeline monitoring and management system.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JONATHAN P OUELLETTE whose telephone number is (571)272-6807. The examiner can normally be reached on M-F 8am-6pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lynda C Jasmin, can be reached at telephone number (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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August 20, 2026
/JONATHAN P OUELLETTE/Primary Examiner, Art Unit 3629
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