DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Argument
2. Applicant's arguments received 05/27/2025 with respect to the 35 USC 101 rejection have been fully considered but they are not persuasive.
Applicant argues that (REMARKS, p.6):
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Examiner respectfully disagrees. According to the USPTO’s 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence (e.g., Example 47, claim 2), training a machine learning model using a selected algorithm, when given their broadest reasonable interpretation in light of the Spec., is merely a process of computing or optimizing the model’s parameters using a series of mathematical calculations. It is also well-known that, when supervised learning is performed, the input data used to train the algorithms is always labeled to allow the algorithm to learn the relationships between the input features and the desired outputs. Accordingly, the recited limitations regarding the process of machine learning read on mathematical concepts and/or calculations, namely a series of calculations leading to one or more numerical results or answers. Applicant’s Spec. (e.g., para. 0057, 0061) lists a various machine learning models that can be adapted for the present application. However, neither the Spec. nor the claim specifies the algorithms and/or the techniques for training the prediction model. Thus, the claim would monopolize the judicial exception across a wide range of applications. As to the particulars of the training data, they are considered merely data characterization which can be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of pipeline network monitoring and maintenance. Applicant’s arguments in this regard are therefore deemed unpersuasive.
Applicant further argues that (REMARKS, p.9-10):
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Examiner respectfully disagrees. Amended claim 1 recites the limitations of “… implemented by a processor of a system for determining the maintenance time of the pipe network of natural gas, the system further including a server, a storage device, a user terminal, and a network”. Under the BRI, these limitations encompass generic components of a general-purpose computer system. According to the MPEP 2106.04(a)(2), if a claim limitation, under its broadest reasonable interpretation, covers mental processes except for the mention of generic computer components performing computing activities via basic function of the computer, then the claim is considered to be directed to an ineligible abstract idea, as it essentially describes a mental process that could be performed by a human without the computer components adding any significant practical application beyond the abstract concept itself. In the instant case, focusing on what the inventors have invented exactly, it is considered that the “heart” of pending claim 1 is directed to a method of determining maintenance time of pipe networks of natural gas using machine learning model. Using a general-purpose computer system performing computing activities via basic function of the computer to implement and practice this kind of determination is well-known in the art. The limitations in question do not recite any additional element that amounts to “significantly more” or an “inventive concept” under the 2019 PEG (see also MPEP 2106.05). Applicant’s arguments in this regard are therefore deemed unpersuasive.
Applicant further argues that (REMARKS, p.10-11):
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Examiner respectfully disagrees. This eligibility analysis in Step 2A-Prong Two evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. Upon careful review of the amended claims of the present application, Examiner maintains the position that the claim as a whole does not meet any of the criteria established in MPEP 2106.04(d) to integrate the abstract idea into a practical application. See detailed response given in section 4 below in this Office Action,
Applicant further argues that (REMARKS, p.10-11):
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Examiner respectfully disagrees. As set forth in section 4 below, under its BRI, the step of “maintaining the pipe network of natural gas based on the maintenance time of the pipe network” recited in instant claim 1 encompasses an insignificant post-solution activity and a field of use limitation. The claim does not provide any details about how the act of “maintaining” is made, and the plain meaning of “maintaining the pipe network of natural gas based on the maintenance time of the pipe network” does not amount to significantly more than the judicial exception or to provide a specific inventive concept that can be considered an improvement to the relevant technology.
Applicant further argues that (REMARKS, p.14):
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Examiner respectfully disagrees. According to 2019 PEG, the "focus of the claimed advance over the prior art" should be examined to look to whether the claims are directed to "a specific means or method that improves the relevant technology" rather than merely being directed to "a result or effect that itself is the abstract idea". Simply setting forth advantages or benefits of use without providing any rational/evidence to how/why the claimed elements amount to significantly more than the judicial exception could be treated as mere instructions to apply the judicial exception but not be qualified for an improvement in the functioning of such as a computer or an improvement to another technology or technical field (see MPEP 2106.04(d)(I), 2106.05(a), and 2106.05 (f)). In the instant case, focusing on what the inventors have invented exactly, Examiner asserts that the pending claims 1-3, 5-6, 8-10, 12-13 and 15-16 are directed to an abstract idea of determining maintenance time of pipe networks of natural gas but without reciting any additional elements that amount to “significantly more” than the judicial exception (see detailed analysis as set forth in section 4 below in this office action). Examiner further maintains that physical parameters or data such as “vibration fatigue factor of the pipe network” calculated based on the vibration frequency of the pipe network and a vibration time of the pipe network, “feature information” corresponding to a historical running time and historical gas leakage information, a historical pipe network maintenance value, and a historical vibration fatigue factor of the pipe network, etc. are all well-understood and/or conventional in the field (see, for example, US 20190257700 to Lewis et al. as cited in the previous office action). Limiting application of an abstract algorithm of determining maintenance time of pipe networks to these well-understood and/or conventional physical variables/parameters is considered merely an attempt to link the use of the judicial exception to a particular technological environment or field of use but does not reflect a qualified improvement (see MPEP 2106.04(d)(I), 2106.05(a), 2106.05(f) and MPEP 2106.05(h)).
Applicant further argues that (REMARKS, p.18):
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Examiner respectfully disagrees. Under the 2019 PEG, Step 2A - Prong 1 evaluates whether the claim recites a judicial exception. Step 2A - Prong 2 asks does the claim recite additional elements that integrate the judicial exception into a practical application, and, if necessary, Step 2B further analyzes whether or not the claim provides an Inventive Concept. In the instant case, Examiner evaluates the eligibility of the pending claims by strictly following the MPEP/2019 PEG guideline. Identification of the claim elements that are well-known and/or conventional in the field are fully supported by the prior art references such as those cited in the previous office action in compliance with the Berkheimer Memo.
The rest of the Appellant’s arguments with respect to the 35 USC 101 rejection are reliant upon the issues discussed above, and are deemed unpersuasive as well for the reasons provided above.
Appellant’s arguments regarding the 35 USC 103 rejection are considered to be persuasive. Examiner agrees that the amended claims, while there are related references that discuss determining a maintenance time of a pipe network including monitoring/analyzing vibration fatigue of the pipe due to vibration, the prior art of record do not specifically provide teachings for the following limitations: wherein the maintenance time prediction model is obtained by training based on training data, the training data includes feature information corresponding to a historical running time and historical gas leakage information, a historical pipe network maintenance value, and a historical vibration fatigue factor of the pipe network; the historical vibration fatigue factor of the pipe network is determined based on a historical vibration frequency of the pipe network and a historical vibration time of the pipe network, and a label of the training data is the maintenance time of the pipe network corresponding to the training data, wherein the vibration fatigue factor of the pipe network is calculated based on the vibration frequency of the pipe network and a vibration time of the pipe network. It is these limitations found in each of the amended claims 1-3, 5-6, 8-10, 12-13 and 15-16, as they are claimed in the combination recited in independent claim 1, 8 or 15, that would make these claims distinguish over the prior art. As such, the corresponding 35 USC 103 rejection is hereby withdrawn.
Claim Rejections - 35 USC § 101
3. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 101 that form the basis for the rejections under this section made in this Office action:
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.
4. Claims 1-3, 5-6, 8-10, 12-13 and 15-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Under the 2019 PEG (now been incorporated into MPEP 2106), the revised procedure for determining whether a claim is "directed to" a judicial exception requires a two-prong inquiry into whether the claim recites: (1) any judicial exceptions, including certain groupings of abstract ideas (i.e., mathematical concepts, certain methods of organizing human interactions such as a fundamental economic practice, or mental processes); and (2) additional elements that integrate the judicial exception into a practical application (see MPEP § 2106.05(a)-(c), (e)-(h)).
Only if a claim (1) recites a judicial exception and (2) does not integrate that exception into a practical application, do we then look to whether the claim: (3) adds a specific limitation beyond the judicial exception that is not "well-understood, routine, conventional" in the field (see MPEP § 2106.0S(d)); or (4) simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception.
Claims 1-3, 5-6, 8-10, 12-13 and 15-16 are directed to an abstract idea of determining maintenance time of pipe networks of natural gas.
Specifically, representative claim 1 recites:
A method for determining a maintenance time of a pipe network of natural gas, implemented by a processor of a system for determining the maintenance time of the pipe network of natural gas, the system further including a server, a storage device, a user terminal, and a network, the method comprising:
obtaining pipe network information of natural gas in at least one area, the pipe network information including a running time of the system for determining the maintenance time of the pipe network of natural gas and gas leakage information of the pipe network;
extracting feature information based on the running time and the gas leakage information;
(c) generating a pipe network maintenance value through a maintenance value prediction model based on pipe network maintenance information and pipe network environment information, the pipe network maintenance value reflecting a priority of pipe network maintenance processing;
wherein the maintenance value prediction model is a Graph Neural Network model, a plurality of nodes of the Graph Neural Network model include a plurality of historical maintenance locations of the pipe network and historical pipe network environmental information, a plurality of edges of the Graph Neural Network model include one or more pipes between the plurality of historical maintenance locations of the pipe network, features of the nodes include at least one of replacement pipe material, the maintenance time, a maintenance location, gas leakage after maintenance, a vibration detection result, a vibration frequency of the pipe network, and natural gas usage environment information, and features of the edges include at least one of pipe material, a diameter, a connection manner, and a relationship between the historical pipe network environment information and the historical maintenance locations of the pipe network;
(d) predicting the maintenance time of the pipe network based on the feature information, the pipe network maintenance value, and a vibration fatigue factor of the pipe network using a maintenance time prediction model, the maintenance time prediction model being a machine learning model;
wherein the vibration fatigue factor of the pipe network is calculated
based on the vibration frequency of the pipe network and a vibration
time of the pipe network; and the maintenance time prediction model
is obtained by training based on training data, the training data
includes feature information corresponding to a historical running
time and historical gas leakage information, a historical pipe network maintenance value, and a historical vibration fatigue factor of the
pipe network; the historical vibration fatigue factor of the pipe
network is determined based on a historical vibration frequency of
the pipe network and a historical vibration time of the pipe network,
and a label of the training data is the maintenance time of the pipe
network corresponding to the training data;
(e) maintaining the pipe network of natural gas based on the maintenance time of the pipe network;
(f) receiving target system normal running time information carrying a predicted running time difference value and predicted damage cycle information corresponding to historical running time information, wherein the target system normal running time information is a write data request, and the write data request further includes data to be written;
(g) extracting time features according to the predicted running time difference value and the predicted damage cycle information to determine an actual running time difference value and actual damage cycle information corresponding to the predicted running time difference value and the predicted damage cycle information for providing operation services; and
(h) sending the data to be written to the actual running time difference value and the actual damage cycle information to replace data corresponding to the system actual running time identifier, thereby managing the actual system running time based on the target system normal running time information.
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements”.
The highlighted portion of the claim constitutes an abstract idea under the 2019 Revised Patent Subject Matter Eligibility Guidance and the additional elements are NOT sufficient to amount to significantly more than the judicial exceptions, as analyzed below:
Step
Analysis
1. Statutory Category ?
Yes.
Method
2A - Prong 1: Judicial Exception Recited?
Yes.
Under its broadest reasonable interpretation (BRI), step (b) covers a process of data analysis and/or manipulation that can be performed in human mind. The claim
does not provide any details about how the feature information is extracted based on the running time and the gas leakage information, and the plain meaning of “extracting” encompasses mental observations or evaluations, e.g., a
computer programmer’s mental identification of the feature information in a data set. Nothing in the claimed limitation precludes this from practically being performed in the mind or using pen/paper. Note, the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. See CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). See also to MPEP 2106.04(a)(2).III
Under its BRI, step (c) encompasses mathematical concepts, i.e., a series of calculations leading to one or more numerical results or answers, and/or specific mathematical calculations to generate a pipe network maintenance value (see Applicant’s Spec. para. 67-68). The generation of the pipe network maintenance value further encompasses mental processes that can be performed mentally with pen/paper because other than reciting “generating a pipe network maintenance value through (the output) of a maintenance value prediction model based on pipe network maintenance information and pipe network environment information”, nothing in the claimed limitations precludes the processes from practically being performed in the mind and/or using pen/paper.
When read in light of the Spec. and as interpreted by one of ordinary skill in the art, step (d) covers a process of using a machine learning model to make predictions based on existing or known data information. In the context of machine learning, simply describing the process of using a model to make predictions (e.g., receiving data, analyzing data, generating a prediction) is considered as reciting an abstract idea because it focuses on the abstract concept of prediction by means of mathematical calculations and/or mental processes (i.e. data evaluation) to generate the prediction. In light of the USPTO’s July 2024 Subject Matter Eligibility Examples (e.g., Examples 47-49), it is deemed that merely using an artificial neural network to perform calculations that are otherwise abstract does not take the claimed limitation(s) out of the categories of abstract idea.
Step (d) further recites newly added limitations about the training of the maintenance time prediction model based on the training data. According to the USPTO’s July 2024 Subject Matter Eligibility Examples (e.g., Example 47, claim 2), training a machine learning model using a selected algorithm, when given their broadest reasonable interpretation in light of the Spec., is merely a process of computing or optimizing the model’s parameters using a series of mathematical calculations based on labelled data if supervised learning is performed. Accordingly, the recited limitations regarding the process of machine learning read on mathematical concepts and/or calculations, namely a series of calculations leading to one or more numerical results or answers.
Applicant’s Spec. (e.g., para. 0057, 0061) lists a various machine learning models that can be adapted for the present application, including a Graph Neural Network (GNN) model. However, neither the Spec. nor the claim specifies the algorithms and/or the techniques for training the GNN model. Thus, the claim would monopolize the judicial exception across a wide range of applications. As to the particulars of the training data, they are considered merely data characterization which can be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of pipeline network monitoring and maintenance.
Step (g) recites “extracting time features according to the predicted running time difference value and the predicted damage cycle information to determine an actual running time difference value and actual damage cycle information corresponding to the predicted running time difference value and the predicted damage cycle information for providing operation services”. Under its BRI, said “extracting … to determine …” covers a process of data analysis and evaluation that can be performed in human mind. Nothing in the claimed limitation precludes this step from practically being performed in the mind or using pen/paper. The rest of the limitations in step (g) merely adds further details as to the particulars of data being used with the mental process of “extracting … to determine …” which is viewed as part of the recited abstract idea.
As such, the bolded portion of instant claim 1 falls within a combination of the “Mathematical Concepts” and “Mental Process” Groupings of Abstract Ideas defined by the 2019 PEG.
2A - Prong 2: Integrated into a Practical Application?
No.
The claim as a whole does not integrate the abstract idea into a practical application.
Step (a) reciting “obtaining pipe network information of natural gas in at least one area, the pipe network information including a running time of a system for determining a maintenance time of a pipe network of natural gas and gas leakage information of the pipe network” reads on merely a process of gathering the data/information necessary for performing the abstract idea identified above in 2A - Prong 1. According to MPEP 2106.05(g): When determining whether an additional element is insignificant pre-solution activity, examiners may consider the following: (3) Whether the limitation amounts to necessary data gathering and outputting, (i.e., all uses of the recited judicial exception require such data gathering or data output). See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 13863, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering).
Furthermore, the limitations of step (a) as claimed do not require any particular devices or sensors to perform the “obtaining …” Thus claim 1 would monopolize the abstract idea across a wide range of applications. The additional elements such as “pipe network information of natural gas in at least one area, the pipe network information including a running time of a system for determining a maintenance time of a pipe network of natural gas and gas leakage information of the pipe network” are not qualified for a meaningful limitation because they only generally link the use of the judicial exception to a particular technological environment or field of use.
Step (c ) recites the limitations of the maintenance value prediction model including “wherein the maintenance value prediction model is a Graph Neural Network model, a plurality of nodes of the Graph Neural Network model include a plurality of historical maintenance locations of the pipe network and historical pipe network environmental information, a plurality of edges of the Graph Neural Network model include one or more pipes between the plurality of historical maintenance locations of the pipe network, features of the nodes include at least one of replacement pipe material, a maintenance time, a maintenance location, gas leakage after maintenance, a vibration detection result, a vibration frequency of the pipe network, and natural gas usage environment information, and features of the edges include at least one of pipe material, a diameter, a connection manner, and a relationship between the historical pipe network environment information and the historical maintenance locations of the pipe network”, when read in light of the Spec. and as interpreted by one of ordinary skill in the art, it is deemed that these limitations recite merely mathematical concepts or relationship between various physical parameters but without providing any specific technical improvements or applications that go beyond the basic idea of using a computer to analyze data and generate predictions. In light of the USPTO’s July 2024 Subject Matter Eligibility Examples (e.g., Examples 47-49), it is held that merely using an artificial neural network to perform calculations that are otherwise abstract does not take the claimed limitation(s) out of the categories of abstract idea. In the instant case, similarly, the claim recites the additional elements of using “a Graph Neural Network model, a plurality of nodes of the Graph Neural Network model include a plurality of historical maintenance locations of the pipe network and historical pipe network environmental information, a plurality of edges of the Graph Neural Network model include one or more pipes ….” [to generate the pipe network maintenance value]. The use of an artificial neural network in this case is similar to the use of an ANN in example 47 claim 2 and a DNN in example 48 claim 1 which found the use of these neural networks to implement steps that are otherwise abstract to be insufficient to render the claims eligible.
Step (e) recites “maintaining the pipe network of natural gas based on the maintenance time of the pipe network”. It is unclear whether said “the maintenance time of the pipe network” refers to the maintenance time predicted by the prediction model or “the maintenance time of the pipe network corresponding to the training data”. Further, the claim does not provide any details about how the act of “maintaining” is made, and the plain meaning of “maintaining the pipe network of natural gas based on the maintenance time of the pipe network” encompasses an insignificant post-solution activity and a field of use limitation.
Step (h) recites “sending the data … to replace data corresponding to the system actual running time identifier, thereby managing the actual system running time based on the target system normal running time information”. With its BRI, this step also reads on an insignificant post-solution activity and/or a field of use limitation. The claim does not provide any details about how the data is sent, and the plain meaning of “sending” encompasses a process of outputting or displaying the results of the recited abstract idea, which does not amount the abstract idea to be significantly more. See Elec. Power, 830 F.3d at 1354.
In general, the claim as a whole does not meet any of the following criteria to integrate the abstract idea into a practical application:
An additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
Various considerations are used to determine whether the additional elements are sufficient to integrate the abstract idea into a practical application. However, in all of these respects, the claim fails to recite additional elements which might possibly integrate the claim into a particular practical application. Instead, based on the above considerations, the claim would tend to monopolize the algorithm across a wide range of applications.
2B: Claim provides an Inventive Concept?
No.
See analysis given in 2A - Prong 2 above.
Amended claim 1 recites the limitations of “… implemented by a processor of a system for determining the maintenance time of the pipe network of natural gas, the system further including a server, a storage device, a user terminal, and a network”. Under the BRI, these limitations encompass generic components of a general-purpose computer system. According to the MPEP 2106.04(a)(2), if a claim limitation, under its broadest reasonable interpretation, covers mental processes except for the mention of generic computer components performing computing activities via basic function of the computer, then the claim is considered to be directed to an ineligible abstract idea, as it essentially describes a mental process that could be performed by a human without the computer components adding any significant practical application beyond the abstract concept itself.
In the instant case, focusing on what the inventors have invented exactly, it is considered that the “heart” of pending claim 1 is directed to a method of determining maintenance time of pipe networks of natural gas using machine learning model. Using a general-purpose computer system performing computing activities via basic function of the computer to implement and practice this kind of determination is well-known in the art. The claim of the present application does not recite any additional element that amounts to “significantly more” or an “inventive concept” under the 2019 PEG (see also MPEP 2106.05).
The claim is therefore ineligible under 35 USC 101.
The dependent claims 2-3, 5-6, 9-10, 12-13 and 16 inherit attributes of the independent claim 1 or 8, but do not add anything which would render the claimed invention a patent eligible application of the abstract idea. These claims merely extend (or narrow) the abstract idea which do not amount for "significant more" because they merely add details to the algorithm which forms the abstract idea as discussed above.
In particular, regarding the limitations recited in claims 2-3, 5-6, 9-10, and 12-13, it has been held that: A claim reciting a judicial exception can be found eligible under Step 2A Prong 2 if the additional elements in the claim integrate the recited judicial exception into a practical application such that the application or use of the judicial exception in this manner meaningfully limits the claim by going beyond generally linking the use of the judicial exception to a particular technological environment, and thus transforms a claim into patent-eligible subject matter. In the instant case, with weight given to all the identified additional elements in question, Examiner takes the position that the additional elements in claims 2-3, 5-6, 9-10, and 12-13 are not qualified for meaningful limitations because they only generally link the use of the judicial exception (math + mental) to a particular technological environment or field of use. Examiner further asserts that the heart of the invention recited in the pending claims is directed to an algorithm of predicting a maintenance time of the pipe network using artificial neural network prediction models. The additional elements and/or physical parameters are all well-understood and/or conventional in the field but do not provide any inventive concepts or reflect a qualified improvement
Regarding claim 15, according to the MPEP 2106.04(a)(2), if a claim limitation, under its broadest reasonable interpretation, covers abstract ideas except for the mention of generic computer components performing computing activities via basic function of the computer, then the claim is likely considered to be directed to an ineligible abstract idea, as it essentially describes an abstract idea that could be performed by a human without the computer components adding any significant practical application beyond the abstract concept itself.
Regarding claim 16, with the BRI to the claim, each of the steps of “receiving a coefficient corresponding to the actual system running time, wherein the coefficient carries a coefficient value of the actual system running time” and “allocating or (assigning) the predicted running time difference value and the predicted damage cycle information to the actual system running time according to the coefficient value” encompasses a process of data/information gathering, which are NOT sufficient to amount to significantly more than the judicial exceptions. The step of “determining the actual running time difference value and the actual damage cycle information according to the coefficient value” reads on a mental process (data evaluation) that can be performed in the human mind or by a human using a pen and paper. The step of “adding a mapping relationship between the predicted running time difference value, the predicted damage cycle information and the actual running time difference value, the actual damage cycle information into time features” encompasses mathematical concepts (e.g., formatting data values) and also a mental process, i.e. data manipulation that can be performed using pan/paper. Further, the limitation of “allocating the actual system running time and the system actual running time identifier according to the coefficient value, the actual running time difference value, and the actual damage cycle information” amounts to necessary data gathering and/or outputting. See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 13863, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering). The claim as a whole does not meet any of the required criteria (see MPEP § 2106.04(d)) to integrate the abstract idea into a practical application:
Hence the claims 1-3, 5-6, 8-10, 12-13 and 15-16 are treated as ineligible subject matter under 35 U.S.C. § 101.
Examiner’s Note
5. While there are related references that discuss determining a maintenance time of a pipe network including monitoring/analyzing vibration fatigue of the pipe due to vibration, the prior art of record do not specifically provide teachings for the following limitations: wherein the maintenance time prediction model is obtained by training based on training data, the training data includes feature information corresponding to a historical running time and historical gas leakage information, a historical pipe network maintenance value, and a historical vibration fatigue factor of the pipe network; the historical vibration fatigue factor of the pipe network is determined based on a historical vibration frequency of the pipe network and a historical vibration time of the pipe network, and a label of the training data is the maintenance time of the pipe network corresponding to the training data, wherein the vibration fatigue factor of the pipe network is calculated based on the vibration frequency of the pipe network and a vibration time of the pipe network. It is these limitations found in each of the claims 1-3, 5-6, 8-10, 12-13 and 15-16, as they are claimed in the combination recited in independent claim 1, 8 or 15, that would make these claims distinguish over the prior art.
Conclusion
6. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Citation of Relevant Prior Art
7. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US 20190257700 (cited in the previous office action) discloses an apparatus, system, and method for monitoring flow of material through a passage of a member and determining a maintenance time of a pipe network of natural gas (para. 0003, 0007, 0056).
CN 111832924 A (cited in the previous office action) discloses a maintenance value (e.g., dynamic prediction of accident consequences for community gas accidents) prediction model, wherein the prediction model is a Graph Neural Network model (Abstract; para. 0008-0011, 0020).
MUINDA et al. (US 20190187678 A1) discloses a method and a system for monitoring piping network including collecting vibration data from the piping networks. Advanced data analytics and machine learning are applied to continuously improve the maintenance and future designs or modifications of piping networks in particular applications, locations, and configurations.
EP 2628895 A1 (machine translation) discloses a method and a system for material degradation detection in an object by analyzing acoustic vibration data (VD) from said object base on ML technique.
CN 101183249 A (machine translation) discloses a Pre-warning Method For Accident In Fuel Gas Pipe Network.
Contact Information
8. Any inquiry concerning this communication or earlier communications from the examiner should be directed to XIUQIN SUN whose telephone number is (571)272-2280. The examiner can normally be reached 9:30am-6:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shelby A. Turner can be reached on (571) 272-6334. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/X.S/Examiner, Art Unit 2857
/SHELBY A TURNER/Supervisory Patent Examiner, Art Unit 2857
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