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 .
DETAILED ACTION
This action is final.
This action is in response to the amendments filed on 03/272026.
Claims 7-9 have been canceled.
Claims 1-6, 10-20 are pending and have been considered.
Claims 1, 4, 10, 13, 16, and 20 have been amended.
Claims 1-6, 10-20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter, a judicial exception, an abstract idea (mental process), without significantly more. The amendments have not made the claim eligible.
Claim 1-6, 10-20 remain rejected under 35 U.S.C. 103 as being unpatentable over Brebner, D. US 20200285788 A1 (‘BRE’), in view of Knight et al, US 20210006622 A1 (‘KNI’).
Response to Amendments/Arguments
The Amendments and Arguments filed on 03/27/2023 have been considered. Claims 1-6, 10-20 are pending, claims 7-9 are canceled, claims 1, 4, 10, 13, 16, and 20 are amended.
Regarding the 35 USC 101 rejection, the amendments have not made the claims eligible; the arguments have been considered but have not been found persuasive. The claim continues to recite abstract ideas that a person exercising evaluations and judgement would be able to perform, thus mental processes which are abstract ideas. The addition of the words “by one or more processors” does not change the abstract nature of the limitation, as found by the courts when additional elements such as “by a computer” are recited in the claim.
The data receiving limitation is still recited at a high level of generality, without reciting any special mechanism by which data is obtained, and the fact it contains an image of an indicia of an asset it does not confer a special mechanism of gathering data than a generic one, and can not transform it into a practical application, and is as insignificant extra solution activity as taking a photo of a painting in an exhibition along the note indicating the painting name and painter’s name and code of acquisition. Nor does the generating of a digital twin using a contextual discovery model. There is no improvement or transformation or other factors that would make the additional elements integrate the abstract idea into a practical application or provide significantly more. The analysis in the rejection below provides more details.
The 35 USC 101 rejections are maintained.
Regarding the rejection of the independent claims under 35 U.S.C. 103, Applicant’s arguments have been considered but have not been found persuasive. The limitations added to the independent claims were limitations previously in the canceled dependent claims, shown in the non-final office action to be disclosed by BRE. Regarding the argument that “BRE's imaging pipeline is thus system-commanded monitoring of metering devices, not user-initiated field imaging of asset indicia to bootstrap onboarding” Examiner does not find the argument persuasive. Claim analysis is performed in view of what is recited in the claims . Terms like bootstrap or onoarding are not found in the specification. According to the abstract BRE disclosure relates to an application system and server kit that create and serve digital twin-enabled applications. Even if the prior art would focus on other aspects than the instant application, the rejection is based on what claim recites. Arguments such as BRE contains not teaching of “template-matching… or confidence thresholds” were not found persuasive – the claims do not recite any of the words “template”, “matching” or “confidence”… Applicant also makes the argument s ((“yet neither BRE nor KNI teaches OCR/vision on indicia to derive”) . Examiner points out that, same as before, th words “OCR”, or “vision” are terms that not only are not recited in the claims, but they don’t even appear in the specification.
On the other hand, the prior art teaches what in the broadest reasonable interpretation is recited in the claim language.
Finally the applicant’s argument that there is no motivation to combine BRE and KNI. The Examiner does not find the argument persuasive, but brings more detail why there is strong motivation to combine, in provides more details in the motivation paragraph.
Claims 1-6, 10-20 are rejected under 35 USC 103 in view of the same art, over BRE/KNI.
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 are analyzed under the Alice/Mayo framework to determine if directed to an ineligible judicial exception. Recitation of judicial exceptions are highlighted in bold font. Paraphrasing (in italics) is used to simplify referencing. Claims with similar limitations (even though not verbatim identical) and sharing the same rationale under Alice/Mayo steps S1 and S2, are grouped, as follows. The analysis is performed on a representative claim of the group; an additional analysis is performed if any claims in the group have additional limitations.
Claims 1-6, 10-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter, a judicial exception (abstract idea, mental process) without significantly more.
(S1) Prima facie, claims 1-6, 10-20 are each directed to a statutory category of invention: process (Claims 1-6.-10-12 directed to a method), machine (claims 13-19 directed to a system) and manufacture (claim 20 directed to a non-transitory computer readable medium).
(S2A1)
Claim 1, representative for claims 13, 20, recites (with bold highlighting abstract idea) a method comprising:
[A] receiving from a user device input data associated with an asset, wherein the input data comprises at least image data captured by the device, wherein the image data comprises an image of the indicia associated with asset (additional elements of data gathering, which does not recite any special way in which data is received, but does have more detail about which type of data is received which is an image of an indicia associated with an asset - an insignificant extra solution activity, for example taking a photo with the painting’s tag, a persons name tag at a conference, etc.)
[B] determining one or more attributes of the asset based at least on an automated extraction of information from the input data; (something that can be performed in the mind, that us the determination itself – A person can determine how old a painting based on a number presented by Optical character recognition showing the year of the painting)
[C1] determining whether the one or more attributes satisfy a predefined threshold associated with a stored asset data unit based at least on querying an asset database; (something that can be performed in the mind, for example determining the painting preceeds the date of the earliest painting in the museum collection. Querying is also a process by which data is gathered, and recited at such level of generality, with no details that would make it more specific and different, it is an insignificant extra solution activity, a data gathering that is also WURC.
[C2] in accordance with a determination that the one or more attributes do not satisfy the predefined threshold: ( continues the mental process defined above, a judgement on following the evaluation, preparing a number of actions).
[D1] accessing sensor data associated with the asset using a contextual discovery model; (an observation, part of mental process; it could also be interpreted as additional elements of data gathering, an insignificant extra solution activity )
[D2] based at least on the sensor data and the one or more attributes, generating a suggested digital twin of the asset using a contextual discovery model; and (additional element, mere instructions to apply an exception, as the claim recites only the idea of a solution, fails to recite details of how the solution to a problem is accomplished MPEP 2106.05(f)){1))
[D3] causing presentation, via a user interface, of data associated with the suggested digital twin of the asset at a user device. (insignificant extra solution activity, data outputting)
In broadest reasonable interpretation claim 1 recites: determine attributes based on inputs [B] compare attributes with thresholds [C1] and if attributes below a threshold follow with a set of actions [C2] , of which the first is observing sensor data [D1]. In view of the guidance from MPEP 2106.04 II. B, the limitations are considered together as a single abstract idea for further analysis, as a process aimed at: “make a determination if measured characteristics are less than prescribed characteristics”.
This is a combination that, under its broadest reasonable interpretation covers performance of limitations expressing observation, evaluation, judgement. Nothing in the claim elements precludes the steps from being practically performed mentally or manually by a human. These are Mental Processes – Concepts Performed in the Human Mind (MPEP § 2106.04(a)(2).
Accordingly, claims 1, 13, 20 recite an abstract idea.
(S2A2) In BRI, the additional claim elements are elements of data gathering (A). generation of a digital twin, recited at high level of generality (D2), and data outputting (D3). The additional elements, taken individually or in combination, fail to integrate the recited judicial exception into a practical application when evaluated using the considerations in MPEP §§ 2106.04(d), 2106.05(a)-(c), (e)-(h) because these do not impose any meaningful limits on practicing the abstract idea., nor do they effect an improvement to any technology or technical field. According, the claim as a whole does not integrate the abstract idea into a practical application, and thus the claim remains directed to a judicial exception.
(S2B) Claims 1, 13, 20 do not include additional elements, which individually or in combination amount to significantly more than the judicial exception. As analyzed in step S2A2 the additional elements recite data gathering, and data output, amounting to nothing more than data gathering, apply it, and data outputting, insignificant extra solution activities.
The additional elements, when considered individually, are limitations that the courts have found not enough to qualify as “significantly more” than the judicial exception; and amount to no more than a recitation of the words "apply it" (or an equivalent) or are no more than mere instructions to implement an abstract idea or other exception on a computer.
For situations substantially similar to those here, these additional elements, including data gathering, data manipulation, and data transmission, recited at high level of generality were found by the courts to be Well-Understood, Routine and Conventional - WURC (see MPEP § 2106.05(d)(ll)). Regarding the generation of a digital twin of an asset based on data and attributes using a contextual discovery model (i.e. using contextual discovery algorithms) as per Specification [0068] [0099] is also considered WURC as in US20190138970A1 Contextual Digital Twin, Singh et al Advancing digital twin implementation: a toolbox for modelling and simulation 14th CIRP Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME ’20; Contextual digital twin runtime environment, US Patent 10,564,993.
When considered as a whole, with additional elements in an ordered combination, the additional elements in the claim only amount to data gathering and, data manipulation and outputting, and instructions to apply the abstract idea on a computer. Additional elements elaborate on the identified abstract idea but do not practically or significantly alter how the identified abstract idea would be performed. Moreover, as noted above, there is nothing about the computing environment or the additional steps that is significant or meaningful to the underlying judicial exception because the identified abstract idea - make a determination if measured characteristics are less than prescribed characteristics, could have been reasonably performed when provided with the relevant data and/or information. There is no inventive concept beyond the judicial exception, and thus the claim as a whole does not amount to significantly more than the judicial exception itself.
Therefore, it is concluded that claims 1, 13, 20 are ineligible.
Claims 2(1), 14(13) recites further limitations, which are analyzed as follows:
in accordance with a determination that the one or more attributes satisfy the predefined threshold:
generating a digital twin of the asset based at least on the stored asset data unit; and (apply it, similar analysis to the limitation in the independent claim)
storing the digital twin of the asset in association with at least one additional digital twin of a shared asset site. (data outputting/storing, generic enough recitation without detailing specific mechanisms for storing, insignificant extra activity similar to ones found by the courts to be WURC)
Based on the analysis presented in the parent claim, the additional elements in the claim are limitations of data manipulation/storage and ‘apply it’, which are insignificant extra elements. When considered individually or on combination, these claim elements do not provide any specific improvements and do not practically or significantly alter how the identified abstract idea would be performed. Therefore, these claim elements fail to integrate the judicial exception into a practical application. The claim is thus directed to a judicial exception.
When considered individually the additional elements were found to be WURC. Individually, in combination taking the claim as a whole, they do not provide an inventive concept beyond the judicial exception, and thus the claim as a whole does not amount to significantly more than the judicial exception itself. Claims 2, 14 are thus found ineligible under 35 USC 101.
Claims 3(2), 15(14) recites further limitations, which are analyzed as follows:
causing presentation, via the user interface, of data associated with the digital twin of the asset.
The additional elements are interpreted as data outputting, and based on the same rationale as in the analysis of the independent claim, an insignificant extra-solution activity which is also WURC. The claims have no additional limitations to provide significantly more, in order to change the nature of the abstract idea, and thus the claims remaining directed to the abstract idea.
For the foregoing reasons, claims 3, 15 are directed to an abstract idea without significantly more, and is rejected as not patent eligible under 35 U.S.C. 101.
Claims 4(1), 16(13) recites further limitations, which are analyzed as follows:
the generating of the suggested digital twin comprising applying the sensor data and the one or more attributes to a contextual discovery model to determine one or more suggested digital twins of the asset.
The additional elements are interpreted as ‘apply it’ and based on the same rationale as in the analysis of the independent claim, an insignificant extra-solution activity, which is also WURC. The claims have no additional limitations to provide significantly more, in order to change the nature of the abstract idea, and thus the claims remaining directed to the abstract idea of ”make a determination if measured characteristics are less than prescribed characteristics“.
For the foregoing reasons, claims 4, 16 are directed to an abstract idea without significantly more, and is rejected as not patent eligible under 35 U.S.C. 101.
Claims 5(4), 17(16) recites further limitations, which are analyzed as follows:
providing training data associated with a determination that the one or more attributes satisfy the predefined threshold to the contextual discovery model.
In broadest reasonable interpretation, the additional elements are interpreted as data gathering and data manipulation, and based on the same rationale as in the analysis of the independent claim, an insignificant extra-solution activity which is also WURC. The claims have no additional limitations to provide significantly more, in order to change the nature of the abstract idea, and thus the claims remaining directed to the abstract idea.
For the foregoing reasons, claims 5, 17 are directed to an abstract idea without significantly more, and is rejected as not patent eligible under 35 U.S.C. 101.
Claims 6(1), 18(13) recites further limitations, which are analyzed as follows:
receiving, via input to the user interface, an extension of the suggested digital
twin;
modifying the suggested digital twin based on the extension.
In broadest reasonable interpretation, the additional elements are interpreted as data gathering and data manipulation, and based on the same rationale as in the analysis of the independent claim, an insignificant extra-solution activity which is also WURC. The claims have no additional limitations to provide significantly more, in order to change the nature of the abstract idea, and thus the claims remaining directed to the abstract idea.
For the foregoing reasons, claims 6, 18 are directed to an abstract idea without significantly more, and is rejected as not patent eligible under 35 U.S.C. 101.
Claims 11(1), 19(13) recites further limitations, which are analyzed as follows:
determining a location of the asset based at least on location data associated with the user device.
In broadest reasonable interpretation, this recites an abstract idea, which can be performed in the mind, as someone can determine an asset location if one sees or knows the location of the devices that records the info of the asset. There are no additional elements to provide significantly more, in order to change the nature of the abstract idea, and thus the claims remaining directed to the abstract idea.
For the foregoing reasons, claims 11, 19 are directed to an abstract idea without significantly more, and is rejected as not patent eligible under 35 U.S.C. 101.
Claim 12(11) recites further limitations, which are analyzed as follows:
generating a geospatial plan of an asset site associated with the asset, the geospatial plan comprising location data of a plurality of assets within the asset site.
In broadest reasonable interpretation, this recites an abstract idea, which can be performed in the mind, or pen and paper, as someone can imagine or draw a map marking location of various assets on the map. There are no additional elements to provide significantly more, in order to change the nature of the abstract idea, and thus the claims remaining directed to the abstract idea.
For the foregoing reasons, claim 12 is directed to an abstract idea without significantly more, and is rejected as not patent eligible under 35 U.S.C. 101.
Claim 10 recites further limitations, which are analyzed as follows:
10(7) - the input data comprising sound data captured by the user device.
These further elements in the dependent claim 10 do not perform any claimed method steps. The nature, form or structure of the other claim elements themselves do not practically or significantly alter how the identified abstract idea would be performed and do not provide more than a general link to a technological environment. They describe the nature, structure and/or content of other claim elements (input data) and as such, cannot change the nature of the identified abstract idea from a judicial exception into eligible subject matter, because they do not represent significantly more (see MPEP 2106.07).
For the foregoing reasons, claim 10 is directed to an abstract idea without significantly more, and are rejected as not patent eligible under 35 U.S.C. 101.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) are summarized as follows:
i. Determining the scope and contents of the prior art.
ii. Ascertaining the differences between the prior art and the claims at issue.
iii. Resolving the level of ordinary skill in the pertinent art.
iv. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 1, 13, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Brebner, D. US 20200285788 A1 (‘BRE’), in view of Knight et al, US 20210006622 A1 (‘KNI’)
Regarding claim 1, 13, 20 BRE teaches
a processor, and a memory that stores executable instructions that, when executed by the processor, cause the processor to: receiving, from a user device, input data associated with an asset; {BRE [0498] The processing system 1200 may include one or more processors and memory.; [0503] The data ingestion module 1202 is configured to acquire data from one or more data sources (e.g., data sources 1104 from FIG. 19). Data sources may include any suitable devices or systems that capture and/or store data. Data sources may include websites, news articles, publically available databases (e.g., municipality databases, product databases, building permit databases, and the like), maps, video camera feeds, audio feeds, user devices, data collection devices, IoT devices and sensors, LIDAR devices, radar devices, and the like.; }
the input data being received from the user device. {BRE: [0058] In embodiments, the plurality of images are received in response to commanding the classification device to capture the plurality of images.}
wherein the input data comprises at least image data captured by the user device. {BRE: [0058] In embodiments, the plurality of images are received in response to commanding the classification device to capture the plurality of images. [0810] … such machines may include, but may not be limited to, personal digital assistants, laptops, personal computers, mobile phones, other handheld computing devices} user device interpreted as mobile phone or other handheld device.
wherein the image data comprising an image of indicia associated with the asset.
{BRE: [0058] In embodiments, the plurality of images are received in response to commanding the classification device to capture the plurality of images. [0062] In embodiments, the object being monitored by the image classification device is a meter. In embodiments, the meter is a wheel counter meter. In embodiments, the meter is an LED meter. [0113] FIG. 35 depicts an example of a wheel counter meter (e.g., a water meter) that may be read by an image classification device} As per the specification [0089] “ the indicia may comprise a label, tag, and/or the like located on or connected to the asset that comprises a barcode, QR code, and/or other scannable element. The image shows at least two types of “indicia” – Gallons label and the number of gallons counted by the meter.
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accessing , by one or more processors, sensor data associated with the asset; based at least on the sensor data and the one or more attributes, generating, by one or more processors, a suggested digital twin of the asset using a contextual discovery model; and.{Fig 20, 1200 Processing System; [0002] the disclosure relates to an application system and server kit that create and serve digital twin-enabled applications. [0064] receive first digital twin data from a first digital twin data source, the first digital twin data pertaining to a first aspect of an environment to be represented by a digital twin; receive second digital twin data from a second digital twin data source, the second digital twin data pertaining to a second aspect of the environment; and generate the digital twin representing the environment based on the first digital twin data and the second digital twin data. [0065] In some embodiments, the system further includes a server kit executed by a second set of processors that cause the server kit to: receive real-time data from one or more real-time data sources, wherein the real-time data source corresponds to the environment represented by the digital twin; and provide an instance of the application with the real-time data, wherein the instance of the application receives the real-time data and updates an instance of the digital twin with the real-time data. In some embodiments, the real-time data source is a set of Internet of Things sensors.; [0694] The gaming engine capability may recognize an explicit state of an object, such as a digital content asset and respond based on the context of the object in which the explicit state is expressed; The gaming engine may recognize a 3D object behavior at runtime and respond based on the context of the object in which the 3D behavior is recognized. [0717] In embodiments, the system that facilitates 3D projection at runtime with a 2D-to-3D code generation engine may include a gaming engine that may enable handling of a state, such as a state of a digital content asset expressed in the declarative language. The gaming engine may recognize an explicit state of an object, such as a digital content asset and respond based on the context of the object in which the explicit state is expressed. Thus, while the foregoing drawings and descriptions set forth functional aspects of the disclosed systems, no particular arrangement of software for implementing these functional aspects should be inferred from these descriptions unless explicitly stated or otherwise clear from the context. Similarly, it will be appreciated that the various steps identified and described above may be varied, and that the order of steps may be adapted to particular applications of the techniques disclosed herein. All such variations and modifications are intended to fall within the scope of this disclosure. As such, the depiction and/or description of an order for various steps should not be understood to require a particular order of execution for those steps, unless required by a particular application, or explicitly stated or otherwise clear from the context.} one or more attributes interpreted as attributes present in the first digital twin; The contextual discover model is interpreted in view of the specification “[0099]…comprise a contextual discovery model (e.g., one or more contextual discovery algorithms) [0068] The knowledge graph 251 can then use these inputs to run the context discovery algorithms.
One cannot stop from remarking in view of the dual use of the term, contextual and context, that the literature uses the term context, and the term “contextual” used interchangeably here with “context” must have the same meaning as “context” used in the literature, which is thus clearly a term a POSITA would recognize as WURC, and that is the interpretation given here by the Examiner, as otherwise 112b and 112a rejections may be warranted since there is no definition of what “contextual” would be, if different than “context discovery” model/algorithm.
causing presentation, via a user interface, of data associated with the suggested digital twin of the asset at a user device {BRE: [0651] In embodiments, the user may define different states that correspond to different display options of the digital twin via the application system 100. In some of these embodiments, the user may define variances that define different display options, given a state of a digital twin. For example, if the application is to display a portion of a digital twin in red when a temperature of the real-world entity represented by the digital twin exceeds a threshold}
BRE teaches generation of the digital twin and broadly about alarm conditions though not explicitly related to threshold related to attribute, however, KNI teaches
Determining, by one or more processors, one or more attributes of the asset based at least on the input data; determining, by one or more processors, whether the one or more attributes satisfy a predefined threshold associated with a stored asset data unit based at least on querying an asset database;[0027] The IoT Gateway may be configured to control the IoT devices based on evaluating incoming real-time data with rules. [0036] The IoT Gateway 125 may include a Dell 500 box with a Linux operating system, and the Intelligent Building Edge Application Server {KNI [0028] a rule may trigger an action based on receiving real-time data related to a supply air temperature that has exceeded a min/max alarm threshold… [0058] the data collected from the devices may be stored in a time series database… the cloud platform may be accessed for querying the cloud stored big data related to the device. This may happen based on both the end user triggering or requesting the query or automatically based on preset parameters and thresholds.}
in accordance with a determination that the one or more attributes do not satisfy the predefined threshold: KNI [0028] a rule may trigger an action based on receiving real-time data related to a supply air temperature that has exceeded a min/max alarm threshold; [0053] An actor that triggers a rule may query connected devices and assets to find an optimum solution based on the current situation of the system…the exact behavior of a device may be modeled by training a data analytics machine learning algorithm on the real-time data of the input and output data points of the device.
Furthermore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined BRE and KNI. These are in the same field of digital twins that involved IoT devices. BRE is directed to generation of digital twins and presentation over user interface and addresses response based on context of the object in which an explicit state is expressed, IoT devices and sensors; KNI is directed to contextually-aware digital twins taking actions in response of IoT and sensor data. BRE is generating a digital based on data from a first digital twin data and a second digital twin data, and makes determinations on data based on comparing with lower and upper thresholds. KNI teaches performing edge-based analytics and checks for real-time data and also makes determination of abnormal data based on thresholds. One of ordinary skill in the art would have been motivated to combine the teachings of BRE with teaching of KNI to have the advantage of better selections on matches based on attributes satisfying specified conditions and improved confidence on the candidate location of the user device.
Regarding claims 2(1), 14(13) BRE/KNI disclose the limitations of the parent claim. BRE further discloses:
in accordance with a determination that the one or more attributes satisfy the predefined threshold: generating a digital twin of the asset based at least on the stored asset data unit; and {BRE: [0649] FIG. 39 illustrates an example system 2400 for creating, enhancing, and utilizing digital twins. In the illustrated example, a user may create a digital twin using the application system 100. [0276] The declarative programming language 140 may include objects, classes, properties and methods. Objects may be discrete bundles of components, often relating to a visual element (a button) or an abstract real world analogy (a customer). A keyword “INSTANCE” may be used to create an instance of a class, otherwise known as an object. A class may define a new type of object. A keyword “DEFINE” may be used to create a sub-class which may be based on an existing class. A property may be an attribute of an object represented by a value,
storing the digital twin of the asset in association with at least one additional digital twin of a shared asset site. { BRE:[0064] According to some embodiments of the present disclosure, a system for providing digital twin enabled applications is disclosed. The system includes an application system executed by a first set of processors. The processors cause the application system to: receive first digital twin data from a first digital twin data source, the first digital twin data pertaining to a first aspect of an environment to be represented by a digital twin; receive second digital twin data from a second digital twin data source, the second digital twin data pertaining to a second aspect of the environment; and generate the digital twin representing the environment based on the first digital twin data and the second digital twin data. [0501] In embodiments, the representation datastore 1234 stores virtual representations 1236 of respective environments generated by the generative content system 1100}
Regarding claims 3(2), 15(14) BRE/KNI disclose the limitations of the parent claim. BRE further discloses:
causing presentation, via the user interface, of data associated with the digital twin of the asset. { BRE:[0008] According to some embodiments of the present disclosure, a method for determining a location of a user device in a building is disclosed. The method includes presenting, by a user interface of the user device executing an application, a graphical user interface the application, the graphical user interface including a selectable alert user interface element; [0650] Upon the developer defining the digital twin in an application, the visual editor of the application system 100 may depict the digital twin in the graphical user interface of the application. }
Regarding claims 4(1) 16(13) BRE/KNI disclose the limitations of the parent claim. BRE further discloses:
the generating of the suggested digital twin comprising applying the sensor data and the one or more attributes to a contextual discovery model to determine one or more suggested digital twins of the asset.{BRE: [0543] In example embodiments, the generative content system 1100 may be configured to train machine-learned classification models (e.g., random forests, support vector machines SVMs, neural networks, deep neural networks, recurrent neural networks, etc.) that are used to estimate a location of a client user device 1106 based on signal-related attributes (and other relevant attributes); [0065] In some embodiments, the real-time data source is a set of Internet of Things sensors.}
Regarding claims 5(4), 17(16) BRE/KNI disclose the limitations of the parent claim. KNI further discloses:
providing training data associated with a determination that the one or more attributes satisfy the predefined threshold to the contextual discovery model. { KNI [0005] a computer-implemented method of generating a contextually-aware digital twin of a commercial real estate or residential building.[0006] In some implementations, the identifying of the at least one controller associated with the new device is based on information generated by training a machine learning algorithm on one or more previously generated graph representations of the commercial real estate building. The relationships for a device may be determined based on training a machine learning algorithm on the digital twins of various commercial real-estate buildings. If a device is known, then the relationships that come from that device may be predicted, enabling automatic creation of all or some of the related entities and relationships, thereby automatically setting up the nodes and relationships of an asset in the digital twin.[0028] Once data related to various solutions is received, the best option may be determined based on pre-determined constraints and settings, such as energy usage, time required, etc; [0054] . For example, a rule may be set to trigger an action based on receiving real-time data related to a supply air temperature that has exceeded a min/max alarm threshold. The rule may indicate that if the supply air temperature falls below a minimum threshold value or exceeded a maximum threshold value for more than five minutes, then actions must be taken to adjust air temperature to a preferred temperature set as a predetermined value. The rule may be stored in the Rules 815 of the actor 800} thresholds interpreted broadly as predetermined constraints, an example being the min/max alarm threshold.
Furthermore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined BRE/KNI (directed to generation of digital twins including context-aware) and further elements of KNI (directed to training a learning context-aware model trained based on attributes conditions) and arrived at generation of context-aware digital twins with updated models trained based on attribute conditions. One of ordinary skill in the art would have been motivated to make such a combination to obtain the advantage of having up-to-date accurate model in the twin and thus accurately present status and predict future scenarios.
Regarding claims 6(1), 18(13) BRE/KNI disclose the limitations of the parent claim. BRE further discloses:
receiving, via input to the user interface, an extension of the suggested digital
twin; modifying the suggested digital twin based on the extension.{ BRE: [0064]The processors further cause the application system to receive coding statements via a user interface of the application system from one or more developers, wherein the coding statements define one or more actions to be performed with respect to the digital twin; generate an application that leverages the digital twin based on the coding statements
Regarding claim 10(7) BRE/KNI disclose the limitations of the parent claim. BRE further discloses:
the input data comprising sound data captured by the user device. {BRE: [0271] In embodiments, the application system 100 may include an engine UI 106; [0671] In embodiments, a digital agent UI 2502 may include a voice input box 2504.} sound input data interpreted as voice input.
Regarding claims 11(1), 19(13) BRE/KNI disclose the limitations of the parent claim. BRE further discloses:
determining a location of the asset based at least on location data associated with the user device. {BRE:[0008] According to some embodiments of the present disclosure, a method for determining a location of a user device in a building is disclosed. [0024] According to some embodiments of the present disclosure, a method for determining a location in a building of one or more physical assets using a tracking device that executes a tracking application is disclosed.}
Regarding claim 12(11) BRE/KNI disclose the limitations of the parent claim. BRE further discloses:
generating a geospatial plan of an asset site associated with the asset, the geospatial plan comprising location data of a plurality of assets within the asset site.{BRE:[0008] According to some embodiments of the present disclosure, a method for determining a location of a user device in a building is disclosed. [0024] According to some embodiments of the present disclosure, a method for determining a location in a building of one or more physical assets using a tracking device that executes a tracking application is disclosed.} . [0649] FIG. 39 illustrates an example system 2400 for creating, enhancing, and utilizing digital twins. … may upload/import maps of a city from a map application, a city planning database, or the like from the defined digital twin data sources 2404… link the input data (e.g., data obtained from multiple data sources) to the appropriate objects of the digital twin. For example, the application system 100 may execute a script that links the building-related data of each respective building to the map of the city based on the addresses of the buildings. In this way, each building object (or child objects of the building object) may be linked to the appropriate “location” within the digital twin of the city and may be parameterized with the corresponding building-related data corresponding to the building} Location data of the assets is in the maps and other info from city planning database. It is generated by linking the data with the digital twin.
Prior art made of record
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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US 20130097545 A1
Sommer et al, Automatic Generation of Digital Twin Based on Scanning and Object Recognition, Transdisciplinary Engineering for Complex Socio-technical Systems, IOS Press 2019
Campos et al, Automatic generation of digital twin industrial system from a high level specification; Procedia Manufacturing Volume 38, 2019, Pages 1095-1102;
Denkena eta al Efficient Generation of a Digital Twin Using Object Detection for Data Acquisition and XML-Interface for Model Creation, Procedia CIRP 93 (2020) 274–279.
Hbeich et al, Semantic and Multi-scale BIM/CIM/LIM Regulation compliance checking https://hal.science/hal-02279645/document )
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.
the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/A.S./Examiner, Art Unit 2188
/RYAN F PITARO/Supervisory Patent Examiner, Art Unit 2188
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