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 responsive to claims filed on August 28, 2024. Claims 1-24 are pending and presented for examination.
Authorization for Internet Communication
To expedite prosecution, filing a written authorization for internet communication is recommended. Doing so permits the USPTO to communicate using email to schedule interviews and/or discuss other aspects of the application. Without a written authorization in place, the USPTO cannot respond to email communications. The preferred method of providing authorization is by filing form PTO/SB/439, available at: https://www.uspto.gov/patent/forms/forms. See MPEP § 502.03.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “a first translation engine… configured to…” and “a second translation engine… configured to…” in claim 1 (translation engine(s) also appear in claims 4, 8, 10 and 12-14).
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
A first translation engine and a second translation engine in claims 1, 4, 8, 10 and 12-14 are not sufficiently described in the specification and therefore rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112 first paragraph.
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.
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.
Claim limitations “a first translation engine… configured to…” and “a second translation engine… configured to…” in claim 1 (translation engine(s) also appear in claims 4, 8, 10 and 12-14) invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Therefore, claims 1, 4, 8, 10 and 12-14 are indefinite and are rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. Claims 2-3, 5-7, 9 and 11 are rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph due to their dependence on the rejected base claim 1.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, 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 and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should 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 §§ 608.01(o) and 2181.
Double Patenting
A rejection based on double patenting of the “same invention” type finds its support in the language of 35 U.S.C. 101 which states that “whoever invents or discovers any new and useful process... may obtain a patent therefor...” (Emphasis added). Thus, the term “same invention,” in this context, means an invention drawn to identical subject matter. See Miller v. Eagle Mfg. Co., 151 U.S. 186 (1894); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Ockert, 245 F.2d 467, 114 USPQ 330 (CCPA 1957).
A statutory type (35 U.S.C. 101) double patenting rejection can be overcome by canceling or amending the claims that are directed to the same invention so they are no longer coextensive in scope. The filing of a terminal disclaimer cannot overcome a double patenting rejection based upon 35 U.S.C. 101.
Claims 1-24 are provisionally rejected under 35 U.S.C. 101 as claiming the same invention as that of claim 1-15 and 17-25 of copending Application No. 17/111964. This is a provisional statutory double patenting rejection since the claims directed to the same invention have not in fact been patented.
Claims 1 and 15 in both applications recite identical limitations as shown on the table below.
Dependent claims 2-14 and 16-25 of the instant application also recite same features as of the claims 2-14 and 17-25 of the copending application.
Examiner’s note: claims comparison was made with respect to the most recent claims filed in the copending application on 4/24/2023. It is further noted that the copending application has been abandoned.
Instant Application
Copending Application 17/111964
1. A system, comprising:
a first translation engine operably coupled to and associated with a first asset having a first protocol and configured to generate data having a first data type; and
a second translation engine operably coupled to and associated with a second asset having a second protocol different from the first protocol and configured to generate data having a second data type different from the first data type, the first translation engine configured, during operation, to:
receive a signal, representing first data of the first data type, from the first asset, translate the first data from the first protocol to a third protocol, translate at least one of a label or a value of the first data from the first data type, to produce a first transformed data, append a first set of at least one semantic label to the first transformed data, the first set of at least one semantic label representing a relationship between the first asset and the second asset, and send a signal to cause storage of the first transformed data in a repository accessible to a user, and the second translation engine configured, during operation, to:
receive a signal, representing second data of the second data type, from the second asset, translate the second data from the second protocol to the third protocol, translate at least one of a label or a value of the second data from the second data type, to produce a second transformed data, append a second set of at least one at least one semantic label to the second transformed data, the second set of at least one semantic label representing a relationship between the first asset and the second asset, provide the second transformed data as an input to a machine learning algorithm, detect, using the machine learning algorithm, a modification to at least one of the first asset or the second asset, and send a signal to cause storage of the second transformed data in the repository, the storage of the first transformed data and the storage of the second transformed data occurring in time-series order, the repository configured to be queried using a query that does not include a reference to a storage location.
A system, comprising:
a first translation engine operably coupled to and associated with a first asset having a first protocol and configured to generate data having a first data type; and
a second translation engine operably coupled to and associated with a second asset having a second protocol different from the first protocol and configured to generate data having a second data type different from the first data type, the first translation engine configured, during operation, to:
receive a signal, representing first data of the first data type, from the first asset, translate the first data from the first protocol to a third protocol, translate at least one of a label or a value of the first data from the first data type, to produce a first transformed data, append a first set of at least one semantic label to the first transformed data, the first set of at least one semantic label representing a relationship between the first asset and the second asset, and send a signal to cause storage of the first transformed data in a repository accessible to a user, and the second translation engine configured, during operation, to:
receive a signal, representing second data of the second data type, from the second asset, translate the second data from the second protocol to the third protocol, translate at least one of a label or a value of the second data from the second data type, to produce a second transformed data, append a second set of at least one at least one semantic label to the second transformed data, the second set of at least one semantic label representing a relationship between the first asset and the second asset, provide the second transformed data as an input to a machine learning algorithm, detect, using the machine learning algorithm, a modification to at least one of the first asset or the second asset, and send a signal to cause storage of the second transformed data in the repository, the storage of the first transformed data and the storage of the second transformed data occurring in time-series order, the repository configured to be queried using a query that does not include a reference to a storage location.
15. A method, comprising:
receiving, at a translation engine operably coupled to and associated with a first asset from a plurality of assets associated with an energy delivery system, a signal representing operational data from the first asset;
translating, via the translation engine, the operational data from a first protocol to a second protocol, thereby producing a first modified operational data;
translating, via the translation engine, at least one of a data label, a unit of measurement, or a value of the first modified operational data from a first data type to a second data type, to produce a second modified operational data;
sending a signal to cause storage of the second modified operational data in a repository accessible to a user;
providing the second modified operational data as an input to a machine learning algorithm; and detecting, using the machine learning algorithm, a modification to at least one asset from the plurality of assets.
15. A method, comprising:
receiving, at a translation engine operably coupled to and associated with a first asset from a plurality of assets associated with an energy delivery system, a signal representing operational data from the first asset;
translating, via the translation engine, the operational data from a first protocol to a second protocol, thereby producing a first modified operational data;
translating, via the translation engine, at least one of a data label, a unit of measurement, or a value of the first modified operational data from a first data type to a second data type, to produce a second modified operational data;
sending a signal to cause storage of the second modified operational data in a repository accessible to a user;
providing the second modified operational data as an input to a machine learning algorithm; and
detecting, using the machine learning algorithm, a modification to at least one asset from the plurality of assets.
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 1-4 and 6-23 are rejected under 35 U.S.C. 103 as being unpatentable over Behzadi et al “Behzadi”, US-PGPub. No. 20190265971 in view of Devi et al “Devi”, US-PGPub. No. 20190155234.
As per claim 1, Behzadi teaches a system, comprising:
a first translation engine (Fig. 7 - Translator 708a) operably coupled to and associated with a first asset (Fig. 7 - first data handler 704a) having a first protocol and configured to generate data having a first data type (Fig. 7, Paragraph(s) [0212-0213]; data handler 704a provides data according to a data model 706a [first protocol where data provided has a first data type]); and
a second translation engine (Fig. 7 - Translator 708b) operably coupled to and associated with a second asset (Fig. 7 - second data handler 704b) having a second protocol different from the first protocol and configured to generate data having a second data type different from the first data type (Fig. 7, Paragraph(s) [0212-0213]; data handler 704b provides data according to a data model 706b [second protocol where data provided has a second data type]), the first translation engine configured, during operation, to:
receive a signal, representing first data of the first data type, from the first asset (Fig. 7 & Paragraph(s) [0212-0213]; translator 708a receives signal/data from data handler 704a), translate the first data from the first protocol to a third protocol (Fig. 7 & Paragraph(s) [0212-0213]; translators translate data received from a first asset in a first protocol to a another protocol. The data handlers 704a-704d may include one or more of data sources, applications, services, or other components that provide, process, or access data. Because each data handler 704a-704d has a corresponding transformation rule 706a-706d, no specific rules between data handlers are needed. For example, if a first application needs to provide data to a second application, the first application only needs to transform data according to the canonical data model and let the second application or a corresponding transformation place the data in the format needed for processing by the second application. Behzadi discloses in Paragraph(s) [0155] integration component 202 integrates data from the data sources 208 based on a canonical data model into a common format [third protocol] (additionally see Paragraph(s) [0145-0146])),
translate at least one of a label or a value of the first data from the first data type, to produce a first transformed data (Fig. 7 & Paragraph(s) [0212-0213]; translators translate data received from a first asset in a first protocol to another protocol so that it can be received by a second asset, which necessarily translates a label or value of the data. The data handlers 704a-704d may include one or more of data sources, applications, services, or other components that provide, process, or access data. Because each data handler 704a-704d has a corresponding transformation rule 706a-706d, no specific rules between data handlers are needed. For example, if a first application needs to provide data to a second application, the first application only needs to transform data according to the canonical data model and let the second application or a corresponding transformation place the data in the format needed for processing by the second application (additionally see Paragraph(s) [0145-0146]),
append a first set of at least one semantic label to the first transformed data, the first set of at least one semantic label representing a relationship between the first asset and the second asset (Paragraph(s) [0181]; type metadata component 404 may store and or manage entity definitions (e.g., for customer, organization, meter, or other entities) used in an application and their function and relationship to other types (additionally see Paragraph(s) [0182-0184]), and
send a signal to cause storage of the first transformed data in a repository accessible to a user (Paragraph(s) [0148], [0182]; data from sources is stored and is accessible to users. Behzadi discloses in Paragraph(s) [0155] integration component 202 integrates data from the data sources 208 based on a canonical data model into a common format and/or into one or more data stores), and
the second translation engine configured, during operation, to: receive a signal, representing second data of the second data type, from the second asset (Fig. 7 & Paragraph(s) [0212-0213]; translator 708 receives signal/data from data handler 704),
translate the second data from the second protocol to the third protocol (Fig. 7 & Paragraph(s) [0212-0213]; translators translate data received from a first asset in a first protocol to a another protocol. The data handlers 704a-704d may include one or more of data sources, applications, services, or other components that provide, process, or access data. Because each data handler 704a-704d has a corresponding transformation rule 706a-706d, no specific rules between data handlers are needed. For example, if a first application needs to provide data to a second application, the first application only needs to transform data according to the canonical data model and let the second application or a corresponding transformation place the data in the format needed for processing by the second application. Behzadi discloses integration component 202 integrates data from the data sources 208 based on a canonical data model into a common format [third protocol]” (see Paragraph(s) [0145-0146], [0155]),
translate at least one of a label or a value of the second data from the second data type, to produce a second transformed data (Fig. 7 & Paragraph(s) [0212-0213]; translators translate data received from a first asset in a first protocol to another protocol so that it can be received by a second asset, which necessarily translates a label or value of the data. The data handlers 704a-704d may include one or more of data sources, applications, services, or other components that provide, process, or access data. Because each data handler 704a-704d has a corresponding transformation rule 706a-706d, no specific rules between data handlers are needed. For example, if a first application needs to provide data to a second application, the first application only needs to transform data according to the canonical data model and let the second application or a corresponding transformation place the data in the format needed for processing by the second application (see Paragraph(s) [0145-0146]),
append a second set of at least one at least one semantic label to the second transformed data, the second set of at least one semantic label representing a relationship between the first asset and the second asset (Paragraph(s) [0181]; type metadata component 404 may store and or manage entity definitions (e.g., for customer, organization, meter, or other entities) used in an application and their function and relationship to other types (additionally see Paragraph(s) [0182-0184]),
provide the second transformed data as an input to a machine learning algorithm (Fig. 2 & Paragraph(s) [0145]; integration component 202 transforms data and provides it to the modular services component 206. Behzadi further discloses machine learning/prediction component in the modular services component 206 receives transformed data (see Fig. 10 and Paragraph(s) [0228-0230])); and
send a signal to cause storage of the second transformed data in the repository, the storage of the first transformed data and the storage of the second transformed data occurring in time-series order (Paragraph(s) [0148], [0182]; data from sources is stored and is accessible to users. Behzadi further discloses integration component 202 integrates data from the data sources 208 based on a canonical data model into a common format and/or into one or more data stores. In addition, Behzadi discloses storing the time-series data in a key-value store and store the relational data in a relational database (see abstract, Paragraph(s) [0155])),
the repository configured to be queried using a query that does not include a reference to a storage location (Paragraph(s) [0182], [0192]; developers may then work directly with the types defined in the type layer to read and write data. Behzadi further discloses returning information in response to query criteria not location (see Paragraph(s) [0192])).
Behzadi does not explicitly teach but Devi teaches detecting, using the machine learning algorithm, a modification to at least one asset from the plurality of assets (Devi Paragraph(s) [0108], “a machine learning computer software/program/algorithm detecting at least one change to an installed capacity of the plurality of photovoltaic stations”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the applicants' invention to combine the teachings of Behzadi and Devi to teach utilizing a machine learning model to detect a modification to an asset because it allows for the machine learning model to perform retraining based on the detected change and also allows for the system to be reconfigured based on the detected change. See at least Devi Paragraph(s) [0120], “applier 156 is configured to set maximum power value 174, P.sub.max.sub._.sub.curr, of the plurality of photovoltaic stations to a maximum power value of the plurality of photovoltaic stations at an end of learning operation 120, in response to the detecting the at least one change to the installed capacity of the plurality of photovoltaic stations.” Furthermore, this is merely combining prior art elements (machine learning models) according to known methods (methods of utilizing machine learning models to detect changes to assets) to yield predictable results. MPEP 2143(I).
As per claim 2, Behzadi teaches wherein the system is a renewable energy system (Paragraph(s) [0194]; a type used to store solar production data).
As per claim 3, Behzadi teaches wherein at least one of the first transformed data or the second transformed data is presented to the user in the form of an interactive map (Paragraph(s) [0182]; user views data on a screen and manipulates data via user interface. Behzadi further discloses rendering type data on a screen in a graphical, text, or other format (Paragraph(s) [0104])).
As per claim 4, Behzadi teaches a memory communicably coupled to the first translation engine and the second translation engine, the memory storing hierarchical data representing relationships between a plurality of assets of the system, the plurality of assets including the first asset and the second asset (Paragraph(s) [0181]; type metadata component 404 may store and or manage entity definitions (e.g., for customer, organization, meter, or other entities) used in an application and their function and relationship to other types. Behzadi further discloses data stored in the relational database 3014 may include information concerning organizations and organization hierarchies, grid assets and grid asset hierarchies (Paragraph(s) [0182-0184], [0596])).
As per claim 6, Behzadi teaches wherein the first asset is included within a first energy system and the second asset is included within a second energy system different from the first energy system (Paragraph(s) [0191]; Behzadi discloses solar panels associated with multiple facilities).
As per claim 7, Behzadi teaches wherein each of the first asset and second asset is included within a common energy system (Paragraph(s) [0194]; a type used to store solar production data).
As per claim 8, Behzadi teaches wherein the first translation engine is configured, during operation, to append the first set of at least one semantic label to the first transformed data based on a static criteria (Paragraph(s) [0181]; type metadata component 404 may store and or manage entity definitions (e.g., for customer, organization, meter, or other entities. Behzadi further discloses entity definition can include a string [static criteria]) (see Paragraph(s) [0184])).
As per claim 9, Behzadi teaches wherein the static criteria is a user-specified parameter (Paragraph(s) [0181]; type metadata component 404 may store and or manage entity definitions (e.g., for customer, organization, meter, or other entities). Paragraph(s) [0184] discloses entity definition can include a string. Paragraph(s) [0189] discloses the data abstraction layer allow developers to define extensible type models. Additionally, Paragraph(s) [0595] discloses users, such as administrators, can add, rename, and group fields).
As per claim 10, Behzadi teaches wherein the first translation engine is configured, during operation, to append the first set of at least one semantic label to the first transformed data based on a dynamic criteria (Paragraph(s) [0181]; type metadata component 404 may store and or manage entity definitions (e.g., for customer, organization, meter, or other entities). Paragraph(s) [0184] additionally discloses entity definition can include logic to declare functions [dynamic criteria]).
As per claim 11, Behzadi teaches wherein the dynamic criteria includes an algorithm (Paragraph(s) [0181]; type metadata component 404 may store and or manage entity definitions (e.g., for customer, organization, meter, or other entities). Paragraph(s) [0184] additionally discloses entity definition can include logic to declare functions [dynamic criteria]).
As per claim 12, Behzadi teaches wherein: the first translation engine is configured, during operation, to append the first set of at least one semantic label to the first transformed data based on a static criteria and the second translation engine is configured, during operation, to append the first set of at least one semantic label to the first transformed data based on a static criteria (Paragraph(s) [0181], [0184]).
As per claim 13, Behzadi teaches wherein: the first translation engine is configured, during operation, to append the first set of at least one semantic label to the first transformed data based on a static criteria and the second translation engine is configured, during operation, to append the first set of at least one semantic label to the first transformed data based on a dynamic criteria (Paragraph(s) [0181], [0184]).
As per claim 14, Behzadi teaches wherein: the first translation engine is configured, during operation, to append the first set of at least one semantic label to the first transformed data based on a dynamic criteria; and the second translation engine is configured, during operation, to append the first set of at least one semantic label to the first transformed data based on a dynamic criteria (Paragraph(s) [0181], [0184]).
As per claim 15, Behzadi teaches a method, comprising:
receiving, at a translation engine operably coupled to and associated with a first asset from a plurality of assets associated with an energy delivery system, a signal representing operational data from the first asset (Fig. 7 & Paragraph(s) [0212-0213]; data handler 704a provides data according to a data model 706a. Behzadi further discloses in Paragraph(s) [0228] with the integration component 202 and the data services component 204, the system 200 is designed to aggregate, federate, and normalize significant volumes of disparate, real-time operational data);
translating, via the translation engine, the operational data from a first protocol to a second protocol, thereby producing a first modified operational data (Fig. 7 & Paragraph(s) [0212-213]; translators translate data received from a first asset in a first protocol to a another protocol. The data handlers 704a-704d may include one or more of data sources, applications, services, or other components that provide, process, or access data. Because each data handler 704a-704d has a corresponding transformation rule 706a-706d, no specific rules between data handlers are needed. For example, if a first application needs to provide data to a second application, the first application only needs to transform data according to the canonical data model and let the second application or a corresponding transformation place the data in the format needed for processing by the second application. Behzadi further discloses integration component 202 integrates data from the data sources 208 based on a canonical data model into a common format (Paragraph(s) [0145-0146], [0155]));
translating, via the translation engine, at least one of a data label, a unit of measurement, or a value of the first modified operational data from a first data type to a second data type, to produce a second modified operational data (Fig. 7 - plurality of translators, Paragraph(s) [0212-0213]; translators translate data received from a first asset in a first protocol to a another protocol. The data handlers 704a-704d may include one or more of data sources, applications, services, or other components that provide, process, or access data. Because each data handler 704a-704d has a corresponding transformation rule 706a-706d, no specific rules between data handlers are needed. For example, if a first application needs to provide data to a second application, the first application only needs to transform data according to the canonical data model and let the second application or a corresponding transformation place the data in the format needed for processing by the second application. Behzadi further discloses integration component 202 integrates data from the data sources 208 based on a canonical data model into a common format (Paragraph(s) [0145-0146], [0155])); and
sending a signal to cause storage of the second modified operational data in a repository accessible to a user (Paragraph(s) [0148], [0182]; data from sources is stored and is accessible to users. Additionally Paragraph(s) [0155] discloses integration component 202 integrates data from the data sources 208 based on a canonical data model into a common format and/or into one or more data stores);
providing the second modified operational data as an input to a machine learning algorithm (Fig. 2 & Paragraph(s) [0145]; integration component 202 transforms data and provides it to the modular services component 206. Additionally, Paragraph(s) [0228-0230] disclose machine learning/prediction component in the modular services component 206 receives transformed data).
Behzadi does not explicitly teach but Devi teaches detecting, using the machine learning algorithm, a modification to at least one asset from the plurality of assets (Devi Paragraph(s) [0108]; a machine learning computer software/program/algorithm detecting at least one change to an installed capacity of the plurality of photovoltaic stations).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the applicants' invention to combine the teachings of Behzadi and Devi to teach utilizing a machine learning model to detect a modification to an asset because it allows for the machine learning model to perform retraining based on the detected change and also allows for the system to be reconfigured based on the detected change. See at least Devi Paragraph(s) [0120], “applier 156 is configured to set maximum power value 174, P.sub.max.sub._.sub.curr, of the plurality of photovoltaic stations to a maximum power value of the plurality of photovoltaic stations at an end of learning operation 120, in response to the detecting the at least one change to the installed capacity of the plurality of photovoltaic stations.” Furthermore, this is merely combining prior art elements (machine learning models) according to known methods (methods of utilizing machine learning models to detect changes to assets) to yield predictable results. MPEP 2143(I).
As per claim 16, Behzadi teaches detecting a modification event associated with the first asset and sending, in response to detecting the modification event, a signal representing an alert to a compute device (Paragraph(s) [0250]; DemandThresholdAlert may be used to keep a log of thresholds that were exceeded and the emails sent to notify operators of unusually high demand).
As per claim 17, Behzadi teaches detecting a trend of modification associated with the plurality of assets and sending, in response to detecting the trend of modification, a signal representing an alert to a compute device (Paragraph(s) [0250], [0310]).
As per claim 18, Behzadi teaches detecting a plurality of modification events associated with the plurality of assets; generating a plurality of signals, each signal in the plurality of signals associated with a corresponding modification event in the plurality of modification events and representing an alert; and grouping at least some of the signals from the plurality of signals into a notification signal based on an attribute of the plurality of signals, the attribute of the plurality of signals including at least one of a common label, a time, or a size of the plurality of signals (Paragraph(s) [0250], [0298], [0310]).
As per claim 19, Behzadi teaches detecting a plurality of modification events associated with the plurality of assets; generating a plurality of signals, each signal in the plurality of signals associated with a corresponding modification event in the plurality of modification events and representing an alert; and sending a first subset of signals in the plurality of signals to a compute device; and suppressing a second subset of signals in the plurality of signals based on the data label of the second modified operational data associated with the second subset of signals (Paragraph(s) [0250], [0310], [0451], [0461]).
As per claim 20, Behzadi teaches presenting the second modified operational data in the form of an interactive map (Paragraph(s) [0104], [0182], [0231], [0459]).
As per claim 21, Behzadi teaches wherein the operational data is a first operational data, the method further including:
receiving, at the translation engine, a signal representing a second operational data from the first asset (Fig. 7 & Paragraph(s) [0212-0213], [0145-0146], [0155]);
modifying at least one of a protocol, a data label, a unit of measurement, or a value of the second operational data to produce a modified second operational data (Fig. 7, Paragraph(s) [0212-0213]; translators translate data received from a first asset in a first protocol to a another protocol); and
sending a signal representing the modified second operational data to a compute device for presentation, via a GUI and as a part of a visualization, to the user (Paragraph(s) [0148], [0182]).
Claim 22 is rejected under the same rationale as claim 1.
As per claim 23, Behzadi teaches generating a response to the query (Paragraph(s) [0182]; user views data on a screen and manipulates data via user interface based on types. In addition, Behzadi teaches rendering type data on a screen in a graphical, text, or other format (Paragraph(s) [0104]); and filtering the response based on an attribute of data associated with the response, the attribute including at least one of a data label, a threshold, information protection logic, customer licensing configuration, or a protocol to anonymize the data (Paragraph(s) [0104], [0182]; user views data on a screen and manipulates data via user interface based on types. Furthermore, Behzadi teaches all requests for data or types or request to write data include an identifier that identifies a tenant and/or tag to specify the partition corresponding to the request (Paragraph(s) [0179])).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Behzadi et al “Behzadi”, US-PGPub. No. 20190265971 in view of Devi et al “Devi”, US-PGPub. No. 20190155234 and further in view of Deng et al “Deng”, US-PGPub. No. US 20220018113.
As per claim 5, Behzadi in view of Devi fail to explicitly teach but Deng teaches wherein each of the first asset and the second asset is associated with a single energy storage container (Deng Paragraph(s) [0073]; each group of the solar panels consists of five solar panels with the same size and is connected to the storage battery 610).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the applicants' invention to combine the teachings of Behzadi, Devi and Deng to teach solar panels associated with a single battery because this is merely combining prior art according to known elements to yield predictable results. MPEP 2143(I).
Claim 24 is rejected under 35 U.S.C. 103 as being unpatentable over Behzadi et al “Behzadi”, US-PGPub. No. 20190265971 in view of Devi et al “Devi”, US-PGPub. No. 20190155234 and further in view of Delacruz et al “Delacruz”, US-PGPub. No. 20210118864.
As per claim 24, Behzadi in view of Devi fail to explicitly teach but Delacruz teaches determining an activity level of the second modified operational data based on the query and changing a storage protocol of the second modified operational data based on the activity level of the second modified operational data (Delacruz Paragraph(s) [0030]; data stored in NVM 330 and/or Ram cells 322 may be reevaluated from time to time, and moved based on the reevaluation. For example, if a first set of data stored in NVM 330 is accessed more frequently than a second set of data stored in RAM 322, the first set of data may be moved to RAM 322 and/or the second set of data may be moved to NVM 330).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the applicants' invention to combine the teachings of Behzadi, Devi and Delacruz to teach moving data from NVM to RAM based on activity because it allows for such data to be accessed quicker. See Delacruz Paragraph(s) [0017], “loaded into RAM for faster access” & Paragraph(s) [0029], “data usage may be evaluated. What is learned from the evaluations may be used to better classify data that is received, wherein the classifications determine where the data is stored.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Please refer to form PTO-892 (Notice of Reference Cited) for a list of relevant prior art.
Li - US-PGPub. No. 20210385304 – directed to managing internet of things (IoT) comprising receiving first sensing data that conforms to a first type of data transmission protocol, receiving second sensing data that conforms to a second type of data transmission protocol, and converting received data to third type of data transmission protocol (Li- Paragraph [0004]). Additionally, Li also teaches analyzing and processing data from different sensing sub-devices by means of machine learning and deep learning (Li - Paragraph [0054]).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMED A WASEL whose telephone number is (571) 272-2669. The examiner can normally be reached Mon-Fri (8:00 am – 4:30 pm).
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Glenton Burgess can be reached on (571)272-3949. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOHAMED A. WASEL/Primary Examiner, Art Unit 2454