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 office action is in response to communication filed 6/6/2025. Claims 1-13 are pending for examination, the rejection cited as stated below.
Claim Rejections - 35 USC § 112
2. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
3. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
4. Claims 1-12 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
a) Claim 1, limitation 1 reciting “a control module to receive a request of operation intent related to a physical asset”, is a means (or step) plus function limitation that invokes 35 U.S.C. 112(f) or 112 (pre-AIA ), sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for the claimed function.
This limitation invokes 35 USC § 112, ¶ 6 because it meets the 3-prong analysis set forth in MPEP 2181 as it recites the phrase “means for” or “step for” (or appellant identifies the limitation as a means (or step) plus function limitation in the appeal brief) and the phrase is modified by functional language and it is not modified by sufficient structure, material, or acts for performing the recited function. Also see Altiris Inc. v. Semantec Corp., 318 F.3d 1363, 1375 (Fed. Cir. 2003).
In the instant limitation, although the phrase "means for" or "step for" is not used in this limitation, the claim limitation is written as a function to be performed and does not recite sufficient structure, material, or acts for performing the claimed function which would preclude application of 35 U.S.C. 112 six paragraph. Therefore claim 1 is considered invoking 35 USC § 112, ¶ 6 as well.
35 USC § 112 (f) or 112 (pre-AIA ), ¶ 6, requires such claim to be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. “If one employs means plus function language in a claim, one must set forth in the specification an adequate disclosure showing what is meant by that language. If an applicant fails to set forth an adequate disclosure, the applicant has in effect failed to particularly point out and distinctly claim the invention as required by the second paragraph of section § 112.” In re Donaldson Co., 16 F.3d 1189, 1195, 29 USPQ 1845, 1850 (Fed. Cir. 1994)(in banc.). For a computer-implemented means-plus-function claim limitation that invokes 35 USC § 112, ¶ 6, the corresponding structure is required to be more than simply a general purpose computer. Aristocrat Technologies, Inc. v. International Game Technology, 521 F.3d 1328, 1333, 86 USPQ2d 1235, 1239-40 (Fed. Cir. 2008). The corresponding structure for a computer-implemented function must include the algorithm as well as the general purpose computer. WMS Gaming,Inc. v. International Game Technology, 184 F.3d 1339, 51 USPQ2d 1385 (Fed. Cir. 1999). The written description must at least disclose the algorithm that transforms the general purpose microprocessor to a special purpose computer programmed to perform the claimed function. Aristocrat, 521 F.3d at 1338, 86 USPQ2d at 1242. However, the specification and drawings do not disclose sufficient corresponding structure, material or acts for performing the claimed function.
b) Claim 1, the limitation reciting “a control module to …implement a configuration mapping produced to the monitoring network and indicating a desired modification in the status of a physical asset in the monitoring network, said configuration mapping being a network setting for deploying different resources of the monitoring network based on operation demands of the physical assets and their associated digital twins”, is a means (or step) plus function limitation that invokes 35 U.S.C. 112(f) or 112 (pre-AIA ), sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for the claimed function. See similar rationale as explained for the first functional limitation above.
c) Claim 1, the limitation reciting “a configuration selection module to select one of the generated configuration mappings” is a means (or step) plus function limitation that invokes 35 U.S.C. 112(f) or 112 (pre-AIA ), sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for the claimed function. See similar rationale as explained for the first functional limitation above.
d) Claim 1, the limitation reciting “a configuration finder module to generate configuration mappings based on the operation intent” is a means (or step) plus function limitation that invokes 35 U.S.C. 112(f) or 112 (pre-AIA ), sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for the claimed function. See similar rationale as explained for the first functional limitation above.
e) Claims 2-12 are similarly rejected due to the respective functional limitations as well as due to the dependency on the respective independent claims.
Applicant is required to:
(a) Amend the claim so that the claim limitation will no longer be a means (or step) plus function limitation under 35 U.S.C. 112(f) or 112 (pre-AIA ), six paragraph; or
(b) Amend the written description of the specification such that is expressly recites what structure, material, or acts perform the claimed function without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts so that one of ordinary skilled in the art would recognize what structure, material, or acts perform the claimed function, applicant is required to clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP 2181 and 608.01(o).
Claim Rejections - 35 USC § 102
5. 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 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.
6. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
7. Claims 1-8 and 10-13 are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being anticipated by ABB (EP 3709195, submitted by IDS).
As to claim 1, ABB discloses a search system for finding configuration mappings in a monitoring network configured to use communication and information technology for connecting physical assets with associated digital twins (0002]; [0007]; [0009]; [0012]; [0016]; [0017]; [0021]; [0039] - [0041]; figures 2, 3A, e.g.,
[0002], “Such a digital presentation is a virtual entity replicating data, structure and functions associated with the real-world entity and, occasionally, with further related real-world entities. There may be multiple digital twins for a real--world entity, each covering certain aspects of the real-world entity. Often, multiple real-world entities use digital twins in t!1eir own (proprietary) formats. If such real-world entities want to exchange digital data, they need to be able to map their own digital twin formats to those digital twin formats of the other real-world entities which are desired communication partners";
[0007], "Embodiments according to the independent claims propose an approach to automatically create by a generative procedure the mapping needed to transform a digital representation (digital twin} of a real-world entity from its proprietary format into the format of another real-world entity for tl1e purpose of interoperability";
[0012], "A mapping module of the second real-world entity generates a mapping between the format of the first digital representation and the format of the second digital representation. For generating said mapping, the mapping module selects at least one mapping strategy from the set of predefined mapping strategies based on ti1e previously determined mapping similarity measure. Tl1e set of predefined mapping strategies can be part of the mapping module or it may be stored within the second real-world entity or even externally on a remote data storage which can be accessed via the interface of the digital representation'';
[0013], "The set of predefined mapping strategies includes at least two of the following strategies: a structure-preserving mapping strategy adapted to generate a mapping when the structure of the first digital representation resembles the structure of the second digital representation which resembles the corresponding mapping model template of said mapping strategy. For example, when the structure of the first digital representation contains the same number of models resulting in a high structure similarity score, and when the leaves of the source model have a correspondence in the leaves of target model template the structure-preserving mapping strategy can be selected. If said models even contain the same number of leaves, an even higher structure similarity score may be determined resulting in tile selection of this strategy. a minimizing mapping strategy adapted to generate a mapping or the second digital representation data models to a minimum number of first digital representation data models. For example, if the target digital representation has a structure witl1 a minimum number of models (e.g., only one model), this strategy may be selected in accordance with its target model template to aggregate all properties from multiple models of the second digital representation into a single model of the first digital representation 1Nithout any additional structure";
[0016], "After the mapping has been generated in accordance with the selected strategy. tl1e requested data is provided to the first real-world entity in accordance with tl1e format of the first digital representation via said mapping.",
[0017], "The analyzing and generating steps of the disclosed method may be repeated iteratively to subsequently try multiple mapping strategies until a mapping strategy is identified which results in the best mapping between the source and target formats . .A. best mapping is defined by showing the highest correspondence between source and target models. In one embodiment the predefined mappin~J strategies are part of a knowledge base and the knowledge base is optimized after each mapping generation by using a machine learning method which incorporates mapping knowledge learned from previously generated mappings. With the optimized knowledge base the selection of the optimal mapping strategy is facilitated when the mapping situation corresponds to a situation which has already been learned earlier";
[0008], “Both real-world entities are connected to the same communication network. The first and second real-world entities have corresponding first and second digital representations. Each digital representation is a virtual entity replicating data, structure and functions associated with any one of the real-world entities. That is, a digital representation of a real-world entity can also include data which originate in other real-world entities. The first and the second digital representations have different formats (Le., the data models used by the digital representations are different). The method, which is described in the following, is executed by the second real-world entity. That is, the method is described from the perspective of one of the communication partners."), the system comprising:
a control module to receive a request of operation intent related to a physical asset (see citation above, and [0009], “The second real world entity has an interface to receive a request for data of the second digital representation to be provided to the first digital representation. For example, the request may be associated with a data request of an application querying the digital representation of the first real-world entity to provide data which originate in the second real-world entity”); and
implement a configuration mapping produced to the monitoring network and indicating a desired modification in the status of a physical asset in the monitoring network, said configuration mapping being a network setting for deploying different resources of the monitoring network based on operation demands of the physical assets and their associated digital twins (see citation above, e.g., [0021], “In one embodiment, the request is received from the first digital representation as a request by the first digital representation to irnport data of the second digital representation into the first one”);
a configuration finder module to generate configuration mappings based on the operation intent (see citation above, e.g., [0039], “The mapping module 132 generates the mapping fv11 between the formats F1 and F2. Firstly, the mapping module selects at least one mapping strategy from the set of predefined mapping strategies 133 based on the determined similarity measures SM1 to SMn"; [0017], “The analyzing and generating steps of the disclosed method may be repeated iteratively to subsequently try multiple mapping strategies until a mapping strategy is identified which results in the best mapping between the source and target formats”);
a configuration selection module to select one of the generated configuration mappings (see citation above, and [0040], “The data-exchange is reliable and robust (i.e., has a low probability for data exchange errors) because of the flexible selection of mapping strategies for dynamic generation of the respective mappings on the fly taking into account the actual data models in the different formats”; [0039], "In other words, a mapping strategy which results in a model structure witl1 model elements having the highest similarity with the target model is selected by the mapping module”;
[0035], “Once the second entity 102 !1as received 1100 the request 1 for data Di to be provided by the second digital representation 112 to the first digital representation 11 ·1 , the computer system 100 generates ·1300 an appropriate mapping Mi to provide the requested data 01 to the first entity 101 in accordance with the format Fi or the first digital representation 11 i (as data Di') via said rr1apping Mi. In more detail, the computer system 100 has an analyzer module 142 to evaluate 1200 a set of predefined mapping strategies 133 and to finally select 1320 one or more appropriate mapping strategies to generate ·1300 said mapping, Each mapping strategy 133 is associated with a target model template 133-T. T!1e target model template describes a target mode! to which a source mode! can be mapped with the corresponding mapping strategy. A mapping similarity measure SM1 to SMn is determined for each mapping strategy i 33 based on similarities in the structure and semantics of respective data models OM1, DM2 of the first and second digital representations with the corresponding target model templates 133”;
[0036], “In more detail, each mapping strategy 133 is associated with a set of mapping rules reflecting the potential target data model that can be generated with said rules. Such mapping rules are now applied to the source data model(s) DM2 of tl1e second entity 102. That is. for each mapping strategy 133, the corresponding mapping rules are applied to the data model(s) DM2 of the second representation 112 wl1ich are related to the requested data D1 resulting in a corresponding target model template 133-T for each mapping strategy. For some mapping strategies, when generating the target model templates, the similarity of single mode! elements of the data mode! DM1 of the first digital representation may be evaluated (e.g., their names for the name-based strategy as later explained later on in the context of FIG. 5D). The similarity between such data elements may be expressed as an element similarity measure”;
[0039], “Once the one or more mapping strategies are selected. the mapping module 132 maps 1340 the one or more data models DM2 which are associated with the requested data D1 of the of the second digital representation 112 to the corresponding one or more data models DM1 of the first digital representation by executing t!1e one or more selected mapping strategies. In other words, the actual mapping between the data models occurs at the level of model element instances. This final mapping 1340 allows to define the mapping links between the model elements of DM1 and DM2”;
[0040]. “Now, the first representation is in possession of all data needed to respond to tt1e query of the application 200. It is to be noted that the scenario disclosed in the context of FIG. 1 is explanatory only in that the request R1 is sent by the first entity in response to an application query. Further embodiments are possible, like for example, the embodiment illustrated in FIG. 3B where the request is actually triggered by the second entity itself in response to the detection of a change in the structure or data of the second representation 112. The disclosed mechanism allows two real-world entities with different formats to exchange data without any need for human interaction. The data-exchange is reliable and robust (i.e., has a low probability for data exchange errors) because of the flexible selection of mapping strategies for dynamic generation of the respective mappings on the fly taking into account the actual data models in the different formats”)
and send it to the control module for its implementation in the monitoring network ([0039], “Once the one or more mapping strategies are selected, the mapping module 132 maps 1340 tl1e one or more data models DM2 which are associated with the requested data 01 ot the of the second digital representation 11 2 to the corresponding one or more data models OM 1 of the first digital representation by executing the one or more selected mapping strategies. In other words, the actual mapping between the data models occurs at the level of model element instances. This final mapping 1340 allows to define the mapping links between the model elements of DM1 and DM2”).
As to claim 13, see similar rejection to claim 1.
As to claim 2, ABB discloses the system according to claim 1, wherein the configuration finder module comprises a fidelity unit to generate a fidelity measure for each configuration mapping based on a comparison between a respective physical as set and its associated digital twin (see [0010]-[0012]; [0035]-[0040] and also [0017], “The analyzing and generating steps of the disclosed method may be repeated iteratively to subsequently try multiple mapping strategies until a mapping strategy is identified which results in the best mapping between the source and target formats. A best mapping is defined by showing the highest correspondence between source and target models”, wherein the criterion such as the degree of correspondence is a fidelity measure).
As to claim 3, ABB discloses the system according to claim 2, wherein the configuration finder module is configured to search for alternative configuration mappings to the implemented configuration mapping offline and/or at runtime and rank them according to their fidelity measures ([0035]-[0040]; [0039]; [0057]; [0061]; and [0017], “The analyzing and generating steps of the disclosed method may be repeated iteratively to subsequently try multiple mapping strategies until a mapping strategy is identified which results in the best mapping between the source and target formats. A best mapping is defined by showing the highest correspondence between source and target models”).
As to claim 4, ABB discloses the system according to claim 3, wherein the configuration finder module is further configured to send the alternative configuration mapping with the highest fidelity measure to the configuration selection module for its implementation ([0017]).
As to claim 5, ABB discloses the system according to claim 1, wherein the configuration
selection unit comprises a configuration library unit to store the configuration mappings found by the
configuration finder module (see citations above and [0017], “the predefined mapping strategies are part of a knowledge base and the knowledge base is optimized after each mapping generation by using a machine learning method which incorporates mapping knowledge learned from previously generated mappings. With the optimized knowledge base the selection of the optimal mapping strategy is facilitated when the mapping situation corresponds to a situation which has already been learned
earlier”).
As to claim 6, ABB discloses the system according to claim 1, wherein the configuration finder module comprises a data-acquisition unit to acquire data from the physical assets, the digital twins and the monitoring network ([0017]; [0039]-[0041]-[0042], wherein generating/selecting the mapping strategy involves comparing data obtained from digital twins, see [0017] and [0039]-[0040], at least some of which are further obtained from physical assets via the monitoring network, see [0041]-[0042]. It is to be noted that the claimed does not require obtaining data directly or specific type of acquiring data).
As to claim 7, ABB discloses the system according to claim 1, wherein the configuration finder module comprises a search unit configured to implement a search algorithm ([0017]).
As to claim 8, ABB discloses the system according to claim 1, wherein the configuration finder module comprises a virtual network unit to generate a digital twin of the monitoring network ([0032]).
As to claim 10, ABB discloses the sys tern according to claim 7, further comprising a virtual network unit with a processing unit to process the digital twin of the monitoring network; wherein the search algorithm uses the processed digital twin of the monitoring network as a variable ([0032]).
As to claim 11, ABB discloses the system according to claim 7, wherein the configuration finder module further comprises an optimization unit to implement an artificial intelligence entity trained and adapted to improve the search algorithm of the search unit ([0017]).
As to claim 12, ABB discloses the system according to claim 8, wherein;
the virtual network unit is further configured to acquire data from a first digital twin of a particular physical asset and a second digital twin of the same physical asset; the second digital twin is generated from the first digital twin using the monitoring network ([0032]).
Claim Rejections - 35 USC § 103
8. 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 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.
9. 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 of this title, 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.
10. 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 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
11. Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over ABB, as applied to claim 1 above, and further in view of Suto et al (US 20220171906 A1).
As to claim 9, ABB discloses the system according to claim 7, wherein the search algorithm implemented in the search unit uses the digital twin of the monitoring network as input ([0046], “As explained previously, the generation of the mapping starts with analyzing the data models of the digital twin providing the input to the intended transformation”), but does not expressly disclose that the digital twin is generated by a virtual network unit. Suto discloses a concept for a digital twin to be generated by a virtual network unit ([0099], ”An environmental mapping program 110a, 110b provides a way to analyze a smart building and generate a digital twin, wherein the digital twin may be applied to a second building”; see also [0097] and Figure 5, wherein the management layer and workloads layer are on top of the virtualization layer).
Before the effective filing date of the invention, it would have been obvious to combine ABB with Suto. The suggestion/motivation of the combination would have been to map digitual twin to buildings (Suto, [0099]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUA FAN whose telephone number is (571)270-5311. The examiner can normally be reached on 9-6.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Umar Cheema can be reached at 571-270-3037. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HUA FAN/Primary Examiner, Art Unit 2458