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
This action is responsive to the application filed on June 5, 2023. Claims 1-20 were presented and are pending examination.
Drawings
The drawings filed on June 5, 2023, are accepted.
Examiner’s Note about the Format of 35 U.S.C. 102/103 Rejections
Generally, limitations of a claim are reproduced identically and followed by examiner’s explanation with citation from prior art in Italic enclosed by a parenthesis, (), for each limitation. In examiner’s explanation, the mapping of the key elements of a limitation to the disclosed elements of prior art is shown by stating the disclosed element immediately followed by the claimed element inside a parenthesis. Specific quotation from prior art is delineated with quotation mark, ““. If primary art fails to teach a limitation or part of the limitation, the limitation or the part of the limitation is placed inside double square brackets, [[ ]], for better understandability, and appropriate secondary art(s) is/are applied later addressing the deficiency of the primary art.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-7, 10-17, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Chinnakannan et al. (US Patent No. US 12632617 B1), hereinafter, Chinnakannan, in view of Mukhopadhyay et al. (US PGPUB No. US 20210306416 A1), hereinafter, Mukhopadhyay.
Regarding claim 1:
Chinnakannan teaches:
A system for real-time data analysis of production data utilizing a dynamically-constructed cloud-based simulation environment, comprising (see Fig. 1):
an event exchange layer in communication with an event publishing layer of a production data processing system, the event exchange layer comprising: a plurality of event listeners, each event listener being programmed to identify an occurrence of an event in one of a plurality of production environment systems and each event listener being communicatively coupled to receive event data from the respective one of the plurality of production environment systems via the event publishing layer of the production data processing system (Fig. 1 shows edge gateway (event exchange layer) for receiving telemetry data from client networks 114a-114n (production environment systems). Col. 6, lines 19-21, states “As depicted, an edge gateway 136 may receive the telemetry data (e.g., in a raw form from the sensors and/or other data sources). Fig. 5 shows the edge gateway includes edge event monitor for receiving event from sensors (event publisher) ); and
a real-time data analysis system comprising (Col. 3, lines 53-57, discloses real-time data analysis by the simulation runtime as stated, “FIG. 1 is a logical block diagram illustrating a system for modeling, building, and managing digital twins of systems through ingestion of real time data streams into behavior simulation of system components, according to some embodiments.”):
a processing device; and a non-transitory memory device in communication with the processing device, the non- transitory memory device storing (i) rules and (ii) instructions, that when executed by the processing device result in (see Fig. 13 showing a computer system 1300):
identifying, by a first event listener from the plurality of event listeners, a first event from a respective first production environment system of the plurality of production environment systems (Col. 15, lines 18-39, discloses detecting event in the client network as stated, “The edge gateway implements a gateway service 512. The gateway service may include any functionality that is needed to collect/process data from the physical system and/or instrumentation and to send the data on to one or more destinations of the provider network (e.g., IoT services 514). For example, protocol adapters may enable communication with components of the system/physical system, the edge events monitor may detect various events that occur at components in the system, and the data collectors may collect data and send the data to the data processors, which in turn send the processed data on to the provider network”);
determining, by an application of the stored rules and based on data descriptive of the first event, that the first event comprises a simulation environment build trigger (Col. 10, lines 34-48, discloses determining event, based on criteria and features, to use a trigger for digital twin as stated “In some embodiments, there are certain characteristics of the physical system and criteria (e.g., requirements) for representing a corresponding digital twin of the system. These characteristics and representation criteria provide the functional criteria and features for the system/software system that enables the use of digital twins. In embodiments, the characteristics and/or representation criteria may include 1) digital twins represent a physical system in the digital space; 2) the digital representation may require identification and mapping of A) different components along with their relationships that make up the physical system B) the input/output stimulus and events at the boundaries of the physical system C) the interactions between the components of the physical system identified, and D) the configuration triggers applied to the physical system”);
constructing, dynamically and in response to the determining that the first event comprises the simulation environment build trigger, an instance of a cloud-based simulation environment, wherein the instance of the cloud-based simulation environment, comprises (Col. 17, lines 43-47, discloses constructing a digital twin with model as stated “If not, then at block 812, the service builds the models based on the definitions for each model (e.g., provided in blocks 802-808). At block 814, the service deploys the models to a runtime environment, where they can be instantiated and/or executed to implement a simulation of a physical system of the client site.”):
a plurality of data storage elements (Fig. 5 shows digital twin storge 518);
at least one data analysis model element (Fig. 1 shows models 116); and
at least one composable smart app element (Fig. 5 shows digital twin application 504);
analyzing, by executing the at least one data analysis model element, data stored in the plurality of data storage elements in relation to the first event (Fig. 1 shows telemetry data is analyzed by the digital twin);
generating, based on the analyzing, a response to the first event (Fig. 1 generating result (response) by the digital twin);
publishing, via the at least one composable smart app element, the response to the first event (Col. 18, lines 54-57, discloses sending the result as stated “. At block 914, the runtime environment generates at least one result based on the change. At block 916, the runtime environment sends the at least one result to a destination.”); and
Chinnakannan does not teach deconstructing, dynamically and in response to the publishing, the instance of the cloud- based simulation environment.
Mukhopadhyay deconstructing, dynamically and in response to the publishing, the instance of the cloud- based simulation environment (paragraph 0057 discloses dynamic creation and tear down of digital twin on demand as stated “The image generator 160 uses the server connection data, network-crawling data, and/or telemetry data collected by the discovery module 156 and/or the server graph created by the mapper module 158 to generate executable scripts 166 for replicating the base servers 122 identified in the IT infrastructure 104. In some embodiments, these executable scripts 166 are created and implemented as Docker images that are executable in Docker containers 168. These executable script files 166 represent the digital twin 102 and are executable on demand to create and tear down a replicated version of the IT infrastructure 104”. Paragraph 0019 discloses tearing down digital twin after the job done as stated “Effectively, the digital twins discussed herein provide the ability to quickly replicate an equivalent environment to the IT infrastructure in the cloud, test or backup data therein, and then tear down the replicated environment when done.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Chinnakannan to incorporate the teaching of Mukhopadhyay about dynamic creation and tear down of digital twin. One would be motivated to do that to efficiently use cloud resources on demand (see paragraph 0020 of Mukhopadhyay).
As to claim 2, the rejection of claim 1 is incorporated. Chinnakannan in view of Mukhopadhyay teach all the limitations of claim 1 as shown above.
Chinnakannan further teaches wherein the identifying of the first event by the first event listener comprises: receiving an indication of a transmission of the data descriptive of the first event from the first production environment system to a client device destination; and intercepting the transmission of the data descriptive of the first event (Col. 15, lines 19-29,, discloses the edge gateway monitor and collect event from the client network as stated “The gateway service may include any functionality that is needed to collect/process data from the physical system and/or instrumentation and to send the data on to one or more destinations of the provider network (e.g., IoT services 514). For example, protocol adapters may enable communication with components of the system/physical system, the edge events monitor may detect various events that occur at components in the system, and the data collectors may collect data and send the data to the data processors, which in turn send the processed data on to the provider network”).
As to claim 3, the rejection of claim 1 is incorporated. Chinnakannan in view of Mukhopadhyay teach all the limitations of claim 1 as shown above.
Chinnakannan further teaches wherein the publishing of the response to the first event comprises: transmitting an indication of the response to the first event to the client device destination (Col. 18, lines 54-57, discloses sending the result to destination).
As to claim 4, the rejection of claim 1 is incorporated. Chinnakannan in view of Mukhopadhyay teach all the limitations of claim 1 as shown above.
Chinnakannan further teaches wherein the at least one data analysis model element comprises an Artificial Intelligence (AI) model (Col. 10, lines 22-27, discloses AI model as stated, “In embodiments, a “system behavioral” use case may enable a user to answer any number of what-if questions through different types (physics, machine learning/AI, transforms/metrics) of simulations of physical system components applied on the digital twins (models) of the system components (e.g., by using one or more behavior functions)”).
As to claim 5, the rejection of claim 1 is incorporated. Chinnakannan in view of Mukhopadhyay teach all the limitations of claim 1 as shown above.
Chinnakannan further teaches wherein the at least one data analysis model element comprises a Machine Learning (ML) model (Col. 10, lines 22-27, discloses machine learning model).
As to claim 6, the rejection of claim 1 is incorporated. Chinnakannan in view of Mukhopadhyay teach all the limitations of claim 1 as shown above.
Chinnakannan further teaches wherein the at least one data analysis model element comprises a graph model (Col. 13, lines 53-56, discloses graph model as stated, “The twin operator may then view the digital twin scene rendered with data (e.g., telemetry data and/or model outputs) overlaid on the graphical representations of the components.”).
As to claim 7, the rejection of claim 1 is incorporated. Chinnakannan in view of Mukhopadhyay teach all the limitations of claim 1 as shown above.
Chinnakannan further teaches wherein the at least one data analysis model element comprises a model-as-a-service model (Col. 2, lines 57-67, discloses client uses digital twin as service. Also see Col. 4, lines 36-37, stating “In the depicted embodiment, the compute service 108 is offered as a separate service of the client network 102”).
As to claim 10, the rejection of claim 1 is incorporated. Chinnakannan in view of Mukhopadhyay teach all the limitations of claim 1 as shown above.
Chinnakannan further teaches wherein the at least one composable smart app element comprises an Application Programming Interface (API) (Col. 4, lines 49-53, discloses the digital twin application include API).
Regarding claim 11:
Claim 11 is directed towards a method performed by the system of claim 1. Accordingly, it is rejected under similar rationale.
Claim 12 is directed towards a method performed by the system of claim 2. Accordingly, it is rejected under similar rationale.
Claim 13 is directed towards a method performed by the system of claim 3. Accordingly, it is rejected under similar rationale.
Claim 14 is directed towards a method performed by the system of claim 4. Accordingly, it is rejected under similar rationale.
Claim 15 is directed towards a method performed by the system of claim 5. Accordingly, it is rejected under similar rationale.
Claim 16 is directed towards a method performed by the system of claim 6. Accordingly, it is rejected under similar rationale.
Claim 17 is directed towards a method performed by the system of claim 7. Accordingly, it is rejected under similar rationale.
Claim 20 is directed towards a method performed by the system of claim 10. Accordingly, it is rejected under similar rationale.
Claims 8, 9, 18, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Chinnakannan in view of Mukhopadhyay and further in view of Hughes et al. (US PGPUB No. US 20240020698 A1), hereinafter, Hughes.
As to claim 8, the rejection of claim 1 is incorporated. Chinnakannan in view of Mukhopadhyay teach all the limitations of claim 1 as shown above.
Chinnakannan does not teach wherein the at least one data analysis model element comprises a plurality of models that are evaluated utilizing a champion-challenger technique.
Hughes teaches wherein the at least one data analysis model element comprises a plurality of models that are evaluated utilizing a champion-challenger technique (paragraph 0079 discloses evaluating plurality of models using champion/challenger scheme).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Chinnakannan to incorporate the teaching of Hughes about champion/challenger scheme. One would be motivated to do that to identify the best performing model (see paragraph 0079 of Hughes).
As to claim 9, the rejection of claim 1 is incorporated. Chinnakannan in view of Mukhopadhyay teach all the limitations of claim 1 as shown above.
Chinnakannan does not teach wherein the at least one data analysis model element comprises a plurality of models that are evaluated utilizing an A/B testing technique.
Hughes teaches wherein the at least one data analysis model element comprises a plurality of models that are evaluated utilizing an A/B testing technique (paragraph 0079 discloses evaluating plurality of models against each other).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Chinnakannan to incorporate the teaching of Hughes about evaluating plurality of models against each other. One would be motivated to do that to identify the best performing model (see paragraph 0079 of Hughes).
Claim 18 is directed towards a method performed by the system of claim 8. Accordingly, it is rejected under similar rationale.
Claim 19 is directed towards a method performed by the system of claim 9. Accordingly, it is rejected under similar rationale.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KAMAL M HOSSAIN whose telephone number is (571)270-3070. The examiner can normally be reached 9:30-5:30 M-F.
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September 15, 2026
/KAMAL M HOSSAIN/ Primary Examiner, Art Unit 2444
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