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 .
Response to Amendment
The amendment filed 12/25/25 has been entered. Claims pending: 1-6, 8-9 and 14-25.
1) Claims amended:
(1) Independent claims: 1 and 14,
(2) Dependent claims: 2-4, 15-16.
2) Claims canceled: dep. claims: 7, 10-13.
3) Claims new: dep. claims: 21-25.
Claim Status
Claims 1-6, 8-9 and 14-25 are pending. They comprising of 3 groups:
1) Method1: 1-6, 8-9 and 21-24, and
2) System (machine)1: 14-19 and 25, and
3) Article1: 20 (dependent on method claim 1).
They all of similar scope.
As of 05/22/23, independent claim 1 is as followed:
1. (Currently Amended) A method for creating a smart gas call center work order, wherein the method is executed by a smart gas safety management platform of an Internet of things (loT) system for creating a smart gas call center work order; the IoT system for creating the smart gas call center work order includes a smart gas user platform, a smart gas service platform, the smart gas safety management platform, a smart gas sensor network platform, and a smart gas object platform; the smart gas service platform is configured to send a work order allocation plan to the smart gas user platform, the smart gas user platform is configured to obtain a user input instruction through a terminal device and query information related to the smart gas call center work order, the smart gas object platform is configured to obtain an execution progress of the work order allocation plan and transfer the work order allocation plan to the smart gas safety management platform through the smart gas sensor network platform, and the method comprises:
[1] obtaining maintenance work order information, wherein the maintenance work order information includes user information, a maintenance location of at least one maintenance task, a maintenance device type, a current status of a maintenance device, image data, and audio data uploaded by a user;
[2] determining, based on the maintenance work order information by using a maintenance prediction model, a maintenance type and a maintenance difficulty level of the at least one maintenance task, wherein
(a) the maintenance prediction model is a machine learning model;
(b) the maintenance prediction model is obtained by training a plurality of labeled first training samples, wherein each of the plurality of labeled first training samples includes sample maintenance work order information and a corresponding label, and the corresponding label includes an actual maintenance type, an actual maintenance difficulty level, and a corresponding first confidence level and second confidence level for the sample maintenance work order information; and
(c ) a training process includes: inputting the plurality of labeled first training samples into an initial maintenance prediction model, constructing a loss function based on the corresponding labels and predicted results from the initial maintenance prediction model, iteratively updating parameters of the initial maintenance prediction model based on the loss function, and completing the training when the loss function satisfies a preset condition, wherein the preset condition includes convergence;
[3] predicting, based on the maintenance type and the maintenance difficulty level, a man-hour requirement and a material requirement for the at least one maintenance task; and
[4] determining, based on the man-hour requirement and the material requirement, a work order allocation plan, including:
(a) obtaining an available allocation time of at least one maintenance person to be allocated;
(b) determining, based on the available allocation time and the man-hour requirement, at least one candidate maintenance person, including:
(b1) determining, based on customer feedback and maintenance frequencies of a plurality of historical work orders, a plurality of feedback clusters and a plurality of frequency clusters through a clustering algorithm;
(b2) determining, based on the maintenance work order information, the plurality of feedback clusters, and the plurality of frequency clusters, estimated customer feedback and an estimated maintenance frequency of the maintenance work order information through a similarity calculation; and
(b3) determining the at least one candidate maintenance person based on the available allocation time, the man-hour requirement, the estimated customer feedback, and the estimated maintenance frequency, wherein if the estimated customer feedback is poor and the estimated maintenance frequency is greater than a frequency threshold, the at least one candidate maintenance person is determined through a preset list;
(b4) determining, based on the material requirement and the at least one candidate maintenance person, a target maintenance person for the at least one maintenance task in the work order allocation plan, wherein the work order allocation plan includes a preferred plan, the preferred plan includes at least one priority allocation work order, and determining the preferred plan includes:
(i) determining at least one maintenance work order in a preferred plan corresponding to previous i maintenance work orders as the at least one priority allocation work order, wherein determining the preferred plan corresponding to the previous maintenance work orders includes:
(x) in response to a man-hour requirement of an i-th maintenance work order being not greater than a preset man-hour, determining the preferred plan corresponding to the previous i maintenance work orders and a planning value of the preferred plan based on a comparison of a first value and a second value, wherein the first value is determined based on a preferred plan that does not include the i-th maintenance work order, the second value is determined based on a value impact of the i-th maintenance work order and a reference plan corresponding to previous i-1 maintenance work orders, and a plan man-hour of the reference plan is relevant to the man-hour requirement of the i-th maintenance work order; and
(y) in response to the man-hour requirement of the i-th maintenance work order being greater than the preset man-hour, determining the preferred plan corresponding to the previous i maintenance work orders and the planning value of the preferred plan based on the reference plan corresponding to the previous i-1 maintenance work orders, wherein the planning value is related to the material requirement;
(b5) obtaining, based on a mobile device of the target maintenance person, a current Iocation of the target maintenance person;
(b6) determining, based on the current location of the target maintenance person and a maintenance location of the at least one maintenance task, a path planning and a travel time of the target maintenance person, to execute the at least one maintenance task.
Note: for referential purpose, numerals [1]-[4] are added to the beginning of each element.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-6, 8-9 and 14-25 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.
When considering subject matter eligibility under 35 U.S.C. § 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e.,
(1) process,
(2) machine,
(3) manufacture or product, or
(4) composition of matter.
If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception, i.e.,
(1) law of nature,
(2) natural phenomenon, and
(3) abstract idea.
and if so, it must additionally be determined whether the claim is a patent-eligible application of the exception. If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself. Examples of abstract ideas include:
(i) a method of organizing human activities,
(2i) an idea of itself, or
(3i) a mathematical relationship or formula.
For instance, in Alice Corp. (Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 134 S. Ct. 2347 (2014)), the Court found that “intermediated settlement” was a fundamental economic practice, which is considered as (i) a certain method of organizing human activities, which is an abstract idea.
Step 1:
In the instant case, with respect to claims 1-6, 8-9 and 14-25:
Claim categories:
Method: 1-6, 8-9 and 21-24
System: 14-20 and 25.
Analysis:
Method: claims 1-6, 8-9 and 21-24 are directed to a method for creating a smart gas call center work order by obtaining work order information, determining a maintenance type and difficulty level of the task, predicting time and material requirements, and determine a work order allocation plan. (Step 1:Yes).
Apparatus: claims 14-20 and 25 are directed to a system comprising an IoT (Internet of things) for creating a smart gas call center work order by obtaining work order information, determining a maintenance type and difficulty level of the task, predicting time and material requirements, and determine a work order allocation plan. (Step 1:Yes).
Thus, the claims are generally directed towards one of the four statutory categories under 35 USC § 101.
Step 2A,
(1) Prong One: Does the claim recite a judicial exception?
(2) Prong Two: Are there any additional elements that integrate the judicial exception into a practical application?
Only if a claim (1) recites a judicial exception and (2) does not integrate that exception into a practical application, then proceeds to step 2B.
Step 2B: Are there any additional elements that adds an inventive concept to the claim? Determine whether the claim:
(3) adds a specific limitation beyond the judicial exception that is not “well-understood, routine, and conventional” in the field (see MPEP 2106.05(d)); or
(4) simply appends well-understood, routine, and conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception.
Step 2A, Prong One:
Claims 1-6, 8-9 and 14-25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1, as exemplary, recites the abstract idea of a method for creating a smart gas call center work order by obtaining work order information, determining a maintenance type and difficulty level of the task, predicting time and material requirements, and determine a work order allocation plan.
These recited limitations fall within the “Certain Methods of Organizing Human activities” grouping of abstract ideas as it relates to a business process for creating a work order for carrying a maintenance task. Accordingly, the claim recites an abstract idea.
(ii) commercial or legal interactions (including agreements in the form of contracts; Legal obligations; Advertising, marketing or sales activities or behaviors; business relations);
Furthermore, the recited limitations fall within the “mental steps” grouping of abstract ideas as it relates to a business process for creating a work order for carrying a maintenance task, which is an abstract idea.
B. Step 2A, Prong Two:
The judicial exception is not integrated into a practical applications because it deals with a method for a business process for creating a work order for carrying a maintenance task by carrying out steps of:
The claims recites the additional elements of:
Steps: Types
[1] obtaining work order information (data). Data gathering, insignificant extra-solution activity, IESA.
[2] determining … type & level (data) using a model. Mental step (evaluate/analyze using a MP model).
[3] predicting … requirements (data) using model. Mental step (evaluate/analyze using a MP model).
[4] determining a WO allocation plan (data). Mental step (evaluate/analyze using a MP model).
(a) obtain allocation time (data)…. IE-SA.
(b) determine … person (data). Evaluate/analyze using a MP model.
(b1) determining … feedback (data) Evaluate/analyze using a MP model.
(b2) determining … feedback (data) Evaluate/analyze using a MP model.
(b3) determining … person (data) Evaluate/analyze using a MP model.
(b4) determining … person (data) Evaluate/analyze using a MP model.
(i) determine work order (data) Evaluate/analyze using a MP model.
(x) in response to … Evaluate/analyze using a MP model.
(y) in response to … Evaluate/analyze using a MP model.
(b5) obtaining … location (data) Evaluate/analyze using a MP model.
(b6) determine … plan & time (data) Evaluate/analyze using a MP model.
* Note: the term MP stands for “maintenance prediction.”
Step [1] is data gathering which is considered as insignificant extra-solution activity steps.
Steps [2-4] are well known mental steps for evaluating/analyzing the condition using a maintenance prediction (MP) model to determine the maintenance tasks and determine work order allocation plan. Steps (a), (b), and (b1) - (b6) are further details of the maintenance planning work order allocation plan using a maintenance prediction model.
The claim does not result in an improvement to the functioning of the computer system or to any other technology or technical field. Further, the claim limitations are not indicative of integration into a practical application by applying or using the judicial exception in some other meaningful way. The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer devices or modules or software, i.e. Internet of things (IoT) system having a processing unit with a software application that functions as a controller. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea for creating a smart gas call center work order by obtaining work order information, determining a maintenance type and difficulty level of the task, predicting time and material requirements, and determine a work order allocation plan, which does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
C. Step 2B:
The claims recites the additional elements of steps [1]-[4] above.
Step [1] is data gathering which is considered as insignificant extra-solution activity steps.
Steps [2-4] are well known mental steps for evaluating/analyzing the condition using a maintenance prediction (MP) model to determine the maintenance tasks and determine work order allocation plan. Steps (a), (b), and (b1) - (b6) are further details of the maintenance planning work order allocation plan using a maintenance prediction model.
The claim does not result in an improvement to the functioning of the computer system or to any other technology or technical field. Further, the claim limitations are not indicative of integration into a practical application by applying or using the judicial exception in some other meaningful way. The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer devices or modules or software, i.e. Internet of things (IoT) system having a processing unit with a software application that functions as a controller. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea for creating a smart gas call center work order by obtaining work order information, determining a maintenance type and difficulty level of the task, predicting time and material requirements, and determine a work order allocation plan, which does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above, the additional elements, steps [2-4] and steps (a), (b), and (b1) - (b6), the “IoT”, when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea(s). As for the system or article claims, mere instructions to apply an exertion using generic computer components cannot provide an inventive concept. The IoT components, i.e. a processor, a memory to store a set of instructions. The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer network devices, i.e. a software for carrying out the method for a business process for creating a work order for carrying a maintenance task, are claimed at high level of generality to perform their basis functions which amount to no more than generally linking the use of the judicial exception to the particular technological environment of field of use and further see insignificant extra-solution activity MPEP 2106.05 (f), (g) and (h). The Symantec, TLI, and OIP Techs, court decisions cited in MPEP 2106.05(d)(II) indicate that mere receipt or transmission of data over a network, sorting data, analyzing data, and transmitting the data is a well-understood, routine and conventional function when it is claimed in a merely generic manner (as it is here). The claim are basically collect data, analyze data, and provide set of results, which are not patent eligible, see Electric Power Group, LLC. For these reasons, there is no inventive concept in the claim, and thus the claim is not patent eligible.
As for dep. claim 2 (part of 1 above), which deal with the various platforms interconnected to carry out the IoT system, these further limit the conventional IoT system, without including: (a) an improvement to another technology or technical field, (b) an improvement to the functioning of the computer itself, or (c ) meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, claim 2 is not considered as being “significantly more”, and thus does not facilitate the claim to meet the “inventive concept”.
As for dep. claims 3-4 (part of 1 above), which deal with details of the determination of the WO maintenance task using a prediction model, these further limit the abstract idea of the maintenance task, without including: (a) an improvement to another technology or technical field, (b) an improvement to the functioning of the computer itself, or (c ) meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, claims 3-4 are not considered as being “significantly more”, and thus does not facilitate the claim to meet the “inventive concept”.
As for dep. claims 5-6 (part of 1 above), which deal with details of the man-hour and material requirements of the WO maintenance task using a prediction model, these further limit the abstract idea of the maintenance task, without including: (a) an improvement to another technology or technical field, (b) an improvement to the functioning of the computer itself, or (c ) meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, claims 5-6 are not considered as being “significantly more”, and thus does not facilitate the claim to meet the “inventive concept”.
As for dep. claims 8-9 (part of 1 above), which deal with details of the man-hour and material requirements of the WO maintenance task using a prediction model, these further limit the abstract idea of the maintenance task, without including: (a) an improvement to another technology or technical field, (b) an improvement to the functioning of the computer itself, or (c ) meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, claims 8-9 are not considered as being “significantly more”, and thus does not facilitate the claim to meet the “inventive concept”.
As for dep. claims 21-22 (part of 1 above), which deal with further details of the material usage and requirement analysis of the prediction model, these further limit the abstract idea of the requirement analysis, without including: (a) an improvement to another technology or technical field, (b) an improvement to the functioning of the computer itself, or (c ) meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, claims 21-22 are not considered as being “significantly more”, and thus does not facilitate the claim to meet the “inventive concept”.
As for dep. claims 23-24 (part of 1 above), which deal with further details of the material and labor requirement analysis of the prediction model, these further limit the abstract idea of the requirement analysis, without including: (a) an improvement to another technology or technical field, (b) an improvement to the functioning of the computer itself, or (c ) meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, claims 23-24 are not considered as being “significantly more”, and thus does not facilitate the claim to meet the “inventive concept”.
Therefore, claims 1-6, 8-9 and 14-25 are not drawn to eligible subject matter as they are directed to an abstract idea without significantly more. step 2B: NO
Citations of Pertinent Prior Art
The teachings of (1) CN 113.283.915, in view of (2) SHAO, US 2020/0.293.997, (3) CN 114.693.070, and (4) SHAFIEE ET AL., US 2012/0.159.503, cited in the previous rejections, do not teach the amended features in the independent claims 1 or 14.
Response to Arguments
Applicant's arguments filed 12/25/26 have been fully considered but they are not persuasive.
1) 101 Rejection:
Step 2A,
(1) Prong One: Does the claim recite a judicial exception?
(2) Prong Two: Are there any additional elements that integrate the judicial exception into a practical application?
Only if a claim (1) recites a judicial exception and (2) does not integrate that exception into a practical application, then proceeds to step 2B.
Step 2B: Are there any additional elements that adds an inventive concept to the claim? Determine whether the claim:
(3) adds a specific limitation beyond the judicial exception that is not “well-understood, routine, and conventional” in the field (see MPEP 2106.05(d)); or
(4) simply appends well-understood, routine, and conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception.
(1) Step 2A, Prong 1:
* Applicant’s arguments on pages 17-23 are not persuasive. As shown in the preamble “creating a smart gas call center work order” and the last step of independent claim 1 “[4] determining, … allocation plan, steps (a), (b), and (b1) - (b6),” the scope of the claim is creating a work order with an allocation of resources plan for a smart gas call center using a maintenance prediction model which is an abstract idea. As for the phrase “to execute the at least one maintenance task” in step “(b6), it appears to be the “intended use” of the step. The IoT system, smart gas call center or platform, machine learning (ML) model, etc., appear to be well-understood, routine, and conventional devices or models. In other word, it merely “apply the well known technology or device” on the method for creating a work order allocation plan.
Applicant’s argument on page 22 that the current claim scope of independent claim 1 is similar to Example 39 “Method for training a Neural Network for Facial Detection” is not persuasive. The current claim is as shown in the preamble “creating a smart gas call center work order” and the last step of independent claim 1 “[4] determining, … allocation plan, steps (a), (b), and (b1) - (b6),” the scope of the claim is creating a work order with an allocation of resources plan for a smart gas call center using a maintenance prediction model which is an abstract idea. The use of machine learning appears to be minimal or use it, “the maintenance prediction model is a machine learning model.” The training steps of the ML model appears conventional practice.
(2) Step 2A, Prong 2:
* Applicant’s arguments on pages 23-28 are not persuasive. As shown above, the scope of the claim is creating a work order with an allocation of resources plan for a smart gas call center using a maintenance prediction model which is an abstract idea. As for the phrase “to execute the at least one maintenance task” in step “(b6), it appears to be the “intended use” of the step. The IoT system, smart gas call center or platform, machine learning (ML) model, etc., appear to be well-understood, routine, and conventional devices or models. In other word, it merely “apply the well known technology or device” on the method for creating a work order allocation plan. As for the benefits of optimizing and allocation of the resources, improving maintenance person allocation, scheduling, etc., they appear to be related with the prediction model and computer efficiency.
Step [1] is data gathering which is considered as insignificant extra-solution activity steps. Steps [2-4] are well known mental steps for evaluating/analyzing the condition using a maintenance prediction (MP) model to determine the maintenance tasks and determine work order allocation plan. Steps (a), (b), and (b1) - (b6) are further details of the maintenance planning work order allocation plan using a maintenance prediction model.
Applicant’s argument on page 22 that the current claim scope of independent claim 1 is similar to Example 39 “Method for training a Neural Network for Facial Detection” is not persuasive. The current claim is as shown in the preamble “creating a smart gas call center work order” and the last step of independent claim 1 “[4] determining, … allocation plan, steps (a), (b), and (b1) - (b6),” the scope of the claim is creating a work order with an allocation of resources plan for a smart gas call center using a maintenance prediction model which is an abstract idea. The use of machine learning appears to be minimal or use it, “the maintenance prediction model is a machine learning model.” The training steps of the ML model appears conventional practice.
The claim does not result in an improvement to the functioning of the computer system or to any other technology or technical field.
(3) Step 2B:
* Applicant’s arguments on pages 28-35 are not persuasive. As shown above, the scope of the claim is creating a work order with an allocation of resources plan for a smart gas call center using a maintenance prediction model which is an abstract idea. As for the phrase “to execute the at least one maintenance task” in step “(b6), it appears to be the “intended use” of the step. The IoT system, smart gas call center or platform, machine learning (ML) model, etc., appear to be well-understood, routine, and conventional devices or models. In other word, it merely “apply the well known technology or device” on the method for creating a work order allocation plan. As for the benefits of optimizing and allocation of the resources, improving maintenance person allocation, scheduling, etc., they appear to be related with the prediction model and computer efficiency.
The claims recites the additional elements of steps [1]-[4] above.
Step [1] is data gathering which is considered as insignificant extra-solution activity steps. Steps [2-4] are well known mental steps for evaluating/analyzing the condition using a maintenance prediction (MP) model to determine the maintenance tasks and determine work order allocation plan. Steps (a), (b), and (b1) - (b6) are further details of the maintenance planning work order allocation plan using a maintenance prediction model.
As for the argument on pages 31-33 with respect to the detailed analysis of the step of determining a work order allocation plan with steps of (b1)-(b6), these are analysis parameters and further limit the “prediction analysis” with respect to time and resources. They are considered as “mathematical algorithms” or “evaluation analysis” which are considered as abstract idea.
The claim does not result in an improvement to the functioning of the computer system or to any other technology or technical field.
2) 103 Rejection:
The previous rejection using (1) CN 113.283.915, in view of (2) SHAO, US 2020/0.293.997, (3) CN 114.693.070, and (4) SHAFIEE ET AL., US 2012/0.159.503, has been withdrawn. They do not teach the amended features in the independent claims 1 or 14.
Conclusion
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 nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
No claims are allowed.
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/TAN D NGUYEN/Primary Examiner, Art Unit 3689