DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This action is in reply to the application filed on 10/04/2024.
Claims 1-20 are currently pending and have been examined.
Information Disclosure Statement
Regarding the IDS dated 11/05/2024, the listed reference WO 2023212324 has not been considered as no copy was attached as per the requirements of 37 CFR 1.98. All other references in the IDS forms dated 11/05/2024, 6/24/2025, 4/06/2026, 7/01/2026, and 7/30/2026 have been considered.
Claim Rejections – 35 USC § 112
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.
Claims 4, 6, 8, 10, and 14-15 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 4, 6, 8, 10, and 14-15 each include one or more of the following “similar” terms: similar building sizes, similar sustainability projects, similar utility information, similar building-specific information, similar building use types, and/or similar climate information. Each of these terms are indefinite as relative and subjective terms, as the claims provide no objective boundaries or standards for measuring these terms, and what might be considered “similar” for each of these terms may reasonably vary from individual to individual. Further, the original disclosure additionally provides no objective boundaries or standards for measuring any of these terms, and as such there is no way to correct these indefiniteness issues short of removing each of these terms. In light of this, for the purposes of this examination, Claims 4, 6, 8, 10, and 14-15 are each interpreted as if these “similar” terms (and, where necessary to render these individual claims definite, the larger ideas to which these terms relate) are removed.
Claim Rejections – 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1, the limitations of receive one or more characteristics for one or more buildings of a plurality of buildings, the one or more characteristics including a location for the one or more buildings; retrieve climate information for the one or more buildings from one or more external computing systems based on the location of the one or more buildings; identify energy information for the one or more buildings based on at least one of the location of the one or more buildings or the climate information of the one or more buildings; generate at least one graphic having a plurality of building indicators, each building indicator corresponding to a building of the plurality of buildings, the plurality of building indicators being visually coded based on at least one of the climate information or the energy information; and cause the display of the user interface, as drafted, are processes that, under their broadest reasonable interpretations, cover certain methods of organizing human activity. For example, these limitations fall at least within the enumerated categories of commercial or legal interactions and/or managing personal behavior or relationships or interactions between people (see MPEP 2106.04(a)(2)(II)).
Additionally, the limitations of receive one or more characteristics for one or more buildings of a plurality of buildings, the one or more characteristics including a location for the one or more buildings; retrieve climate information for the one or more buildings from one or more external computing systems based on the location of the one or more buildings; identify energy information for the one or more buildings based on at least one of the location of the one or more buildings or the climate information of the one or more buildings; generate at least one graphic having a plurality of building indicators, each building indicator corresponding to a building of the plurality of buildings, the plurality of building indicators being visually coded based on at least one of the climate information or the energy information; and cause the display of the user interface, as drafted, are processes that, under their broadest reasonable interpretations, cover mental processes. For example, these limitations recite activity comprising observations, evaluations, judgments, and opinions (see MPEP 2106.04(a)(2)(III)).
If a claim limitation, under its broadest reasonable interpretation, covers fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships, or managing interactions between people, it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with the aid of pen and paper but for recitation of generic computer components, it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of one or more memory storage devices storing instructions executable by one or more processors, generate a user interface, and a display device. These, in the context of the claim as a whole, amount to no more than mere instructions to apply a judicial exception (see MPEP 2106.05(f)). Accordingly, these additional elements do not integrate the abstract ideas into a practical application because they do not, individually or in combination, impose any meaningful limits on practicing the abstract ideas. The claim is therefore directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the judicial exception into a practical application, the additional elements amount to no more than mere instructions to apply a judicial exception for the same reasons as discussed above in relation to integration into a practical application. These cannot provide an inventive concept. Therefore, when considering the additional elements alone and in combination, there is no inventive concept in the claim, and thus the claim is not patent eligible.
Claims 2-12, describing various additional limitations to the system of Claim 1, amount to substantially the same unintegrated abstract idea as Claim 1 (upon which these claims depend, directly or indirectly) and are rejected for substantially the same reasons.
Claim 2 discloses wherein the one or more characteristics include the location, a building size, and a building usage type for the one or more buildings (further defining the abstract idea set forth in Claim 1), which does not integrate the claim into a practical application.
Claim 3 discloses wherein the climate information comprises a climate zone code of the one or more buildings (further defining the abstract idea set forth in Claim 1); and the plurality of building indicators are visually coded based on the climate zone code of the one or more buildings (further defining the abstract idea set forth in Claim 1), which do not integrate the claim into a practical application.
Claim 4 discloses wherein the energy information for the one or more buildings includes at least one of average energy use information, average emissions information, or average energy cost information associated with other buildings having one or more of matching climate zone codes, similar building sizes, or matching building use types to the one or more buildings (further defining the abstract idea set forth in Claim 1), which does not integrate the claim into a practical application.
Claim 5 discloses receive a selection of at least one building of the plurality of buildings via the user interface (an abstract idea in the form of a certain method of organizing human activity and a mental process); receive a selection of one or more project options via the user interface, the one or more project options relating to a sustainability project associated with the at least one building (an abstract idea in the form of a certain method of organizing human activity and a mental process); determine one or more project estimates for the sustainability project based on the at least one building, the one or more project options, and at least one of the climate information or the energy information for the plurality of buildings (an abstract idea in the form of a certain method of organizing human activity, a mental process, and a mathematical concept); and wherein the user interface further includes the one or more project estimates (further defining the abstract idea set forth in Claim 1), which do not integrate the claim into a practical application.
Claim 6 discloses wherein the one or more project estimates are based on the at least one building and historical project data associated with similar sustainability projects performed at other buildings having one or more of matching climate zone codes, similar building sizes, or matching building use types to the at least one building (an abstract idea in the form of a certain method of organizing human activity, a mental process, and a mathematical concept), which does not integrate the claim into a practical application.
Claim 7 discloses wherein the user interface is a first user interface (further defining the abstract idea set forth in Claim 1); ingest utility information for the at least one building (an abstract idea in the form of a certain method of organizing human activity and a mental process); determine one or more updated project estimates based on the utility information for the at least one building (an abstract idea in the form of a certain method of organizing human activity, a mental process, and a mathematical concept); generate a second user interface including the one or more updated project estimates (an abstract idea in the form of a certain method of organizing human activity and a mental process); and cause the display device to display the second user interface (an abstract idea in the form of a certain method of organizing human activity and a mental process), which do not integrate the claim into a practical application.
Claim 8 discloses wherein the one or more updated project estimates are based on the at least one building and historical project data associated with similar sustainability projects performed at other buildings having similar utility information and one or more of similar building sizes or matching building use types to the at least one building (an abstract idea in the form of a certain method of organizing human activity, a mental process, and a mathematical concept), which does not integrate the claim into a practical application.
Claim 9 discloses ingest building-specific information for the at least one building, the building-specific information including a list of modifications to be made within the at least one building (an abstract idea in the form of a certain method of organizing human activity and a mental process); determine one or more validated project estimates based on the building-specific information for the at least one building (an abstract idea in the form of a certain method of organizing human activity, a mental process, and a mathematical concept); generate a third user interface including the one or more validated project estimates (an abstract idea in the form of a certain method of organizing human activity and a mental process); and cause the display device to display the third user interface (an abstract idea in the form of a certain method of organizing human activity and a mental process), which do not integrate the claim into a practical application.
Claim 10 discloses wherein the one or more validated project estimates are based on the at least one building and historical project data associated with similar sustainability projects performed at other buildings having similar building-specific information and one or more of similar building sizes or matching building use types to the at least one building (an abstract idea in the form of a certain method of organizing human activity, a mental process, and a mathematical concept), which does not integrate the claim into a practical application.
Claim 11 discloses wherein the one or more validated project estimates include at least one savings estimate determined using at least one energy model (an abstract idea in the form of a certain method of organizing human activity, a mental process, and a mathematical concept), which does not integrate the claim into a practical application.
Claim 12 discloses wherein the at least one graphic includes the plurality of building indicators are arranged on a map showing the location for each building (further defining the abstract idea set forth in Claim 1), which does not integrate the claim into a practical application.
Regarding Claims 13 and 19, the limitations of receiving a location for one or more buildings of a plurality of buildings; retrieving climate information for the one or more buildings from one or more external computing systems based on the location of the one or more buildings; identifying energy information for the one or more buildings based on at least one of the location of the one or more buildings or the climate information of the one or more buildings; receiving a selection of one or more project options relating to a sustainability project associated with the plurality of buildings; determining one or more project estimates for the sustainability project based on the one or more project options and at least one of the climate information or the energy information for the plurality of buildings; generate the one or more project estimates; and cause the display of the user interface, as drafted, are processes that, under their broadest reasonable interpretations, cover certain methods of organizing human activity. For example, these limitations fall at least within the enumerated categories of commercial or legal interactions and/or managing personal behavior or relationships or interactions between people (see MPEP 2106.04(a)(2)(II)).
Additionally, the limitations of receiving a location for one or more buildings of a plurality of buildings; retrieving climate information for the one or more buildings from one or more external computing systems based on the location of the one or more buildings; identifying energy information for the one or more buildings based on at least one of the location of the one or more buildings or the climate information of the one or more buildings; receiving a selection of one or more project options relating to a sustainability project associated with the plurality of buildings; determining one or more project estimates for the sustainability project based on the one or more project options and at least one of the climate information or the energy information for the plurality of buildings; generate the one or more project estimates; and cause the display of the user interface, as drafted, are processes that, under their broadest reasonable interpretations, cover mental processes. For example, these limitations recite activity comprising observations, evaluations, judgments, and opinions (see MPEP 2106.04(a)(2)(III)).
Additionally, the limitation of determining one or more project estimates for the sustainability project based on the one or more project options and at least one of the climate information or the energy information for the plurality of buildings, as drafted, is a process that, under its broadest reasonable interpretation, covers mathematical concepts. For example, these limitations recite mathematical relationships and/or calculations (see MPEP 2106.04(a)(2)(I)).
If a claim limitation, under its broadest reasonable interpretation, covers fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships, or managing interactions between people, it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with the aid of pen and paper but for recitation of generic computer components, it falls within the “Mental Processes” grouping of abstract ideas. If a claim limitation, under its broadest reasonable interpretation, covers mathematical relationships, mathematical formulae or equations, or mathematical calculations, it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of one or more memory devices having instructions executable by one or more processors, one or more processors, generate a user interface, and a display device. These, in the context of the claims as a whole, amount to no more than mere instructions to apply a judicial exception (see MPEP 2106.05(f)). Accordingly, these additional elements do not integrate the abstract ideas into a practical application because they do not, individually or in combination, impose any meaningful limits on practicing the abstract ideas. The claims are therefore directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the judicial exception into a practical application, the additional elements amount to no more than mere instructions to apply a judicial exception for the same reasons as discussed above in relation to integration into a practical application. These cannot provide an inventive concept. Therefore, when considering the additional elements alone and in combination, there is no inventive concept in the claims, and thus the claims are not patent eligible.
Claims 14-18 and 20, describing various additional limitations to the method of Claim 13 or the product of Claim 19, amount to substantially the same unintegrated abstract idea as Claim 1 (upon which these claims depend, directly or indirectly) and are rejected for substantially the same reasons.
Claim 14 is not integrated into a practical application for the same reasons as Claim 4.
Claim 15 is not integrated into a practical application for the same reasons as Claim 6.
Claim 16 is not integrated into a practical application for the same reasons as Claim 7.
Claim 17 is not integrated into a practical application for the same reasons as Claim 9.
Claim 18 discloses generating, by the one or more processors, the energy information based on the at least one of the location of the one or more buildings or the climate information of the one or more buildings (an abstract idea in the form of a certain method of organizing human activity, a mental process, and a mathematical concept); or retrieving, by the one or more processors, the energy information from the one or more external computing systems or one or more second external computing systems based on the at least one of the location of the one or more buildings or the climate information of the one or more buildings (an abstract idea in the form of a certain method of organizing human activity and a mental process), which does not integrate the claim into a practical application.
Claim 20 discloses wherein the user interface further includes at least one graphic having a plurality of building indicators arranged on a map, each building indicator corresponding to a building of the plurality of buildings, the plurality of building indicators being visually coded based on at least one of the climate information or the energy information (an abstract idea in the form of a certain method of organizing human activity and a mental process), which do not integrate the claim into a practical application.
Claims 19-20 are additionally rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because, under its broadest reasonable interpretation, Claims 19-20 encompass transitory forms of signal transmission, or signals per se (see In re Nuijten, 500 F.3d 1346, 84 USPQ2d 1495 (Fed. Cir. 2007) and MPEP 2106.03). In order to overcome these rejections, it is recommended that the claim language “computer memory devices” be amended to “non-transitory computer memory devices” or similar.
Claim Rejections – 35 USC § 102
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 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.
Claims 1-2, 5-11, and 13-19 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Wenzel et al (WO 2023154408, claiming priority to US 17668791 and US 17686320, a copy of which was provided in the IDS dated 7/01/2026) (hereafter, “Wenzel”).
Regarding Claim 1, Wenzel discloses:
A building management system (BMS) (¶ 0027; a building equipped with a building management system (BMS));
one or more memory devices storing instructions executable by one or more processors (¶ 0020; Figs. 4, 6, 13; another implementation of the present disclosures is non-transitory computer readable media storing program instructions that, when executed by one or more processors, perform operations);
receive one or more characteristics for one or more buildings of a plurality of buildings, the one or more characteristics including a location for the one or more buildings (¶ 0110, 0311; Fig. 23; at step 3706, climate data indicating available renewable power is collected (e.g., average number of sunny days, length of days, solar intensity, average wind speed, average number of windy days, etc.) is collected for the location of the building; in some embodiments, building 502 includes multiple buildings (i.e., a campus));
retrieve climate information for the one or more buildings from one or more external computing systems based on the location of the one or more buildings (¶ 0091-0092, 0110-0111, 0132, 0256, 0311; Figs. 4, 23; at step 3706, climate data indicating available renewable power is collected (e.g., average number of sunny days, length of days, solar intensity, average wind speed, average number of windy days, etc.) is collected for the location of the building; in some embodiments, building 502 includes multiple buildings (i.e., a campus); BMS controller is shown to include a communications interface and a BMS interface; interface may facilitate communications between BMS controller and external applications (e.g., monitoring and reporting applications, enterprise control applications, remote systems and applications, applications residing on client devices, etc.); communications interface may be a network interface configured to facilitate electronic data communications between central plant controller and various external systems or devices (e.g., BMS, subplants, utilities, etc.); for example, central plant controller may receive information from BMS indicating one or more measured states of the controlled building (e.g., temperature, humidity, electric loads, etc.) and one or more states of subplants (e.g., equipment status, power consumption, equipment availability, etc.); communications interface may receive inputs from BMS and/or subplants and may provide operating parameters (e.g., on/off decisions, setpoints, etc.) to subplants via BMS);
identify energy information for the one or more buildings based on at least one of the location of the one or more buildings or the climate information of the one or more buildings (¶ 0110, 0311, 0314; Fig. 23; at step 3708, data relating to available space for new energy assets is collected, i.e., physical limits on where a new asset could be positioned (indoor or outdoor, rooftop or ground level, etc.) or how big a new asset could be (roof size, volume of available space, area of available space, etc. in order to fit with an existing building and pre-existing building equipment; in Fig. 23, step 3714: "generate one or more recommended new assets to install at the building);
generate a user interface including at least one graphic having a plurality of building indicators, each building indicator corresponding to a building of the plurality of buildings, the plurality of building indicators being visually coded based on at least one of the climate information or the energy information (¶ 0147, 0175-0178, 0260-0262, 0299, 0306, 0320; Fig. 12; monitoring and reporting applications may include a web-based monitoring application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; the GUI elements may summarize relative energy use and intensity across central plants in different buildings (real or modeled), different campuses, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to access performance across one or more central plants from one screen; configuration tools can allow a user to define various parameters of the simulation; configuration tools can present user interfaces for building simulation; reporting applications may receive the optimized resource allocations from demand response optimizer and, in some embodiments, costs associated with the optimized resource allocations; reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KP/) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user); and
cause a display device to display the user interface (¶ 0147, 0260-0262, 0299, 0306, 0315, 0320; monitoring and reporting applications may include a web-based monitoring application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; the GUI elements may summarize relative energy use and intensity across central plants in different buildings (real or modeled), different campuses, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to access performance across one or more central plants from one screen; at step 3715, a display is generated that shows the recommendation output from step 3714).
Regarding Claim 2, Wenzel discloses the limitations of Claim 1. Wenzel additionally discloses wherein the one or more characteristics include the location, a building size, and a building usage type for the one or more buildings (¶ 0243, 0260, 0311; Fig. 23; at step 3702, building data indicating energy loads of a building (e.g., electrical demand) is collected; at step 3706, climate data indicating available renewable power is collected (e.g., average number of sunny days, length of days, solar intensity, average wind speed, average number of windy days, etc.) is collected for the location of the building; at step 3708, data relating to available space for new energy assets is collected, i.e., physical limits on where a new asset could be positioned (indoor or outdoor, rooftop or ground level, etc.) or how big a new asset could be (roof size, volume of available space, area of available space, etc. in order to fit with an existing building and pre-existing building equipment).
Regarding Claim 5, Wenzel discloses the limitations of Claim 1. Wenzel additionally discloses:
receive a selection of at least one building of the plurality of buildings via the user interface (¶ 0061, 0127, 0147, 0260-0262, 0299, 0306, 0350; configuration tools can allow a user to define (e.g., via graphical user interfaces, via prompt-driven “wizards,” etc.) various parameters of the simulation such as the number and type of subplants, the devices within each subplant, the subplant curves, device-specific efficiency curves, the duration of the simulation, the duration of the prediction window, the duration of each time step, and/or various other types of plan information related to the simulation; configuration tools can present user interfaces for building the simulation; the user interfaces may allow users to define simulation parameters graphically; at step 3608, a user interface is generate that allows a user to select a preferred point along the comfort-vs-carbon curve generated in step; for example, a graphical user interface may show the comfort-vs-carbon curve and allow the user to select a point on the curve by touching or clicking on the preferred point; the user can thus directly select a desired tradeoff between occupant comfort and carbon emissions while seeing the actual relationship between the variables for a particular building, plant, or campus; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user);
receive a selection of one or more project options via the user interface, the one or more project options relating to a sustainability project associated with the at least one building (¶ 0061, 0127, 0147, 0260-0262, 0299, 0306, 0350; configuration tools can allow a user to define (e.g., via graphical user interfaces, via prompt-driven “wizards,” etc.) various parameters of the simulation such as the number and type of subplants, the devices within each subplant, the subplant curves, device-specific efficiency curves, the duration of the simulation, the duration of the prediction window, the duration of each time step, and/or various other types of plan information related to the simulation; configuration tools can present user interfaces for building the simulation; the user interfaces may allow users to define simulation parameters graphically; at step 3608, a user interface is generate that allows a user to select a preferred point along the comfort-vs-carbon curve generated in step; for example, a graphical user interface may show the comfort-vs-carbon curve and allow the user to select a point on the curve by touching or clicking on the preferred point; the user can thus directly select a desired tradeoff between occupant comfort and carbon emissions while seeing the actual relationship between the variables for a particular building, plant, or campus; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user);
determine one or more project estimates for the sustainability project based on the at least one building, the one or more project options, and at least one of the climate information or the energy information for the plurality of buildings (¶ 0061, 0127, 0147, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user); and
wherein the user interface further includes the one or more project estimates (¶ 0061, 0127, 0147, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user).
Regarding Claim 6, Wenzel discloses the limitations of Claim 5. Wenzel additionally discloses wherein the one or more project estimates are based on the at least one building and historical project data associated with similar sustainability projects performed at other buildings having one or more of matching climate zone codes, similar building sizes, or matching building use types to the at least one building (¶ 0061, 0110, 0127, 0147, 0180, 0260-0262, 0298-0299, 0306, 0311-0313, 0350; configuration tools can present user interfaces for building the simulation; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; in some embodiments, the user interfaces allow a user to select a pre-stored or pre-constructed simulated plant and/or plan information (e.g., from plan information database) and adapt it or enable it for use in the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user).
Regarding Claim 7, Wenzel discloses the limitations of Claim 5. Wenzel additionally discloses:
wherein the user interface is a first user interface (¶ 0061, 0127, 0147, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user);
ingest utility information for the at least one building (¶ 0005-0008, 0011, 0110, 0140, 0311, 0314; Fig. 23; at step 3708, data relating to available space for new energy assets is collected, i.e., physical limits on where a new asset could be positioned (indoor or outdoor, rooftop or ground level, etc.) or how big a new asset could be (roof size, volume of available space, area of available space, etc. in order to fit with an existing building and pre-existing building equipment; in Fig. 23, step 3714: "generate one or more recommended new assets to install at the building; the controller is configured to determine an allocation of a predicted demand for the resource over a future time period between the first subsystem and the second subsystem based on a first carbon emissions rate associated with off-site production of the electricity and a second carbon emissions rate associated with on-site consumption of the fuel);
determine one or more updated project estimates based on the utility information for the at least one building (¶ 0061, 0127, 0147, 0253, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user; with each iteration of the optimization process, demand response optimizer may shift the prediction window forward and apply the optimal resource allocation for the portion of the simulation period no longer in the prediction window; demand response optimizer may use the new plan information at the end of the prediction window to perform the next iteration of the optimization process);
generate a second user interface including the one or more updated project estimates (¶ 0061, 0127, 0147, 0253, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user; ; with each iteration of the optimization process, demand response optimizer may shift the prediction window forward and apply the optimal resource allocation for the portion of the simulation period no longer in the prediction window; demand response optimizer may use the new plan information at the end of the prediction window to perform the next iteration of the optimization process); and
cause the display device to display the second user interface (¶ 0061, 0127, 0147, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user).
Regarding Claim 8, Wenzel discloses the limitations of Claim 7. Wenzel additionally discloses wherein the one or more updated project estimates are based on the at least one building and historical project data associated with similar sustainability projects performed at other buildings having similar utility information and one or more of similar building sizes or matching building use types to the at least one building (¶ 0061, 0127, 0147, 0253, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user; with each iteration of the optimization process, demand response optimizer may shift the prediction window forward and apply the optimal resource allocation for the portion of the simulation period no longer in the prediction window; demand response optimizer may use the new plan information at the end of the prediction window to perform the next iteration of the optimization process).
Regarding Claim 9, Wenzel discloses the limitations of Claim 7. Wenzel additionally discloses:
ingest building-specific information for the at least one building, the building-specific information including a list of modifications to be made within the at least one building (¶ 0147, 0260-0262, 0299, 0306; monitoring and reporting applications may include a web-based monitoring application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; the GUI elements may summarize relative energy use and intensity across central plants in different buildings (real or modeled), different campuses, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to access performance across one or more central plants from one screen; configuration tools can allow a user to define various parameters of the simulation; configuration tools can present user interfaces for building simulation; reporting applications may receive the optimized resource allocations from demand response optimizer and, in some embodiments, costs associated with the optimized resource allocations; reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KP/) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like);
determine one or more validated project estimates based on the building-specific information for the at least one building (¶ 0061, 0106, 0127, 0147, 0206, 0253, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user; with each iteration of the optimization process, demand response optimizer may shift the prediction window forward and apply the optimal resource allocation for the portion of the simulation period no longer in the prediction window; demand response optimizer may use the new plan information at the end of the prediction window to perform the next iteration of the optimization process; automated measurement and validation (AM&V) layer may be configured to verify that control strategies commanded by integrated control layer or demand response layer are working properly (e.g., using data aggregated by AM&V layer, integrated control layer, building subsystem integration layer, FDD layer, or otherwise); for example, AM&V layer may compare a model-predicted output with an actual output from building subsystems to determine an accuracy of the model; to prevent high level optimizer from overusing electricity, subplant curve incorporator may check whether the calculated amount of electricity use (determined by the optimization algorithm) for heat recovery chiller subplant is above the corresponding subplant curve; in some embodiments, the check is performed after each iteration of the optimization algorithm);
generate a third user interface including the one or more validated project estimates (¶ 0061, 0106, 0127, 0147, 0206, 0253, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user; ; with each iteration of the optimization process, demand response optimizer may shift the prediction window forward and apply the optimal resource allocation for the portion of the simulation period no longer in the prediction window; demand response optimizer may use the new plan information at the end of the prediction window to perform the next iteration of the optimization process; automated measurement and validation (AM&V) layer may be configured to verify that control strategies commanded by integrated control layer or demand response layer are working properly (e.g., using data aggregated by AM&V layer, integrated control layer, building subsystem integration layer, FDD layer, or otherwise); for example, AM&V layer may compare a model-predicted output with an actual output from building subsystems to determine an accuracy of the model; to prevent high level optimizer from overusing electricity, subplant curve incorporator may check whether the calculated amount of electricity use (determined by the optimization algorithm) for heat recovery chiller subplant is above the corresponding subplant curve; in some embodiments, the check is performed after each iteration of the optimization algorithm); and
cause the display device to display the third user interface (¶ 0061, 0127, 0147, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user).
Regarding Claim 10, Wenzel discloses the limitations of Claim 9. Wenzel additionally discloses wherein the one or more validated project estimates are based on the at least one building and historical project data associated with similar sustainability projects performed at other buildings having similar building-specific information and one or more of similar building sizes or matching building use types to the at least one building (¶ 0061, 0106, 0127, 0147, 0206, 0253, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user; with each iteration of the optimization process, demand response optimizer may shift the prediction window forward and apply the optimal resource allocation for the portion of the simulation period no longer in the prediction window; demand response optimizer may use the new plan information at the end of the prediction window to perform the next iteration of the optimization process; automated measurement and validation (AM&V) layer may be configured to verify that control strategies commanded by integrated control layer or demand response layer are working properly (e.g., using data aggregated by AM&V layer, integrated control layer, building subsystem integration layer, FDD layer, or otherwise); for example, AM&V layer may compare a model-predicted output with an actual output from building subsystems to determine an accuracy of the model; to prevent high level optimizer from overusing electricity, subplant curve incorporator may check whether the calculated amount of electricity use (determined by the optimization algorithm) for heat recovery chiller subplant is above the corresponding subplant curve; in some embodiments, the check is performed after each iteration of the optimization algorithm).
Regarding Claim 11, Wenzel discloses the limitations of Claim 9. Wenzel additionally discloses wherein the one or more validated project estimates include at least one savings estimate determined using at least one energy model (¶ 0061, 0106, 0122, 0127, 0139-0140, 0147, 0206, 0253, 0260-0262, 0276-0277, 0299, 0306, 0348, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption to monetize the costs of running the central plant equipment; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user; with each iteration of the optimization process, demand response optimizer may shift the prediction window forward and apply the optimal resource allocation for the portion of the simulation period no longer in the prediction window; demand response optimizer may use the new plan information at the end of the prediction window to perform the next iteration of the optimization process; automated measurement and validation (AM&V) layer may be configured to verify that control strategies commanded by integrated control layer or demand response layer are working properly (e.g., using data aggregated by AM&V layer, integrated control layer, building subsystem integration layer, FDD layer, or otherwise); for example, AM&V layer may compare a model-predicted output with an actual output from building subsystems to determine an accuracy of the model; to prevent high level optimizer from overusing electricity, subplant curve incorporator may check whether the calculated amount of electricity use (determined by the optimization algorithm) for heat recovery chiller subplant is above the corresponding subplant curve; in some embodiments, the check is performed after each iteration of the optimization algorithm; in some embodiments, load/rate predictor uses a deterministic plus stochastic model trained from historical load data to predict loads; load/rate predictor may use any of a variety of prediction methods to predict loads (e.g., linear regression for the deterministic portion and an AR model for the stochastic portion); load/rate predictor may predict one or more different types of loads for the building or campus; load/rate predictor is shown receiving utility rates from utilities; utility rates may indicate a cost or price per unit of a resource (e.g., electricity, natural gas, water, etc.) provided by utilities at each time step k in the prediction window).
Regarding Claims 3 and 19, Wenzel discloses:
one or more memory devices storing instructions executable by one or more processors (¶ 0020; Figs. 4, 6, 13; another implementation of the present disclosures is non-transitory computer readable media storing program instructions that, when executed by one or more processors, perform operations);
receiving, by one or more processors, a location for one or more buildings of a plurality of buildings (¶ 0110, 0311; Fig. 23; at step 3706, climate data indicating available renewable power is collected (e.g., average number of sunny days, length of days, solar intensity, average wind speed, average number of windy days, etc.) is collected for the location of the building; in some embodiments, building 502 includes multiple buildings (i.e., a campus));
retrieving, by the one or more processors, climate information for the one or more buildings from one or more external computing systems based on the location of the one or more buildings (¶ 0091-0092, 0110-0111, 0132, 0256, 0311; Figs. 4, 23; at step 3706, climate data indicating available renewable power is collected (e.g., average number of sunny days, length of days, solar intensity, average wind speed, average number of windy days, etc.) is collected for the location of the building; in some embodiments, building 502 includes multiple buildings (i.e., a campus); BMS controller is shown to include a communications interface and a BMS interface; interface may facilitate communications between BMS controller and external applications (e.g., monitoring and reporting applications, enterprise control applications, remote systems and applications, applications residing on client devices, etc.); communications interface may be a network interface configured to facilitate electronic data communications between central plant controller and various external systems or devices (e.g., BMS, subplants, utilities, etc.); for example, central plant controller may receive information from BMS indicating one or more measured states of the controlled building (e.g., temperature, humidity, electric loads, etc.) and one or more states of subplants (e.g., equipment status, power consumption, equipment availability, etc.); communications interface may receive inputs from BMS and/or subplants and may provide operating parameters (e.g., on/off decisions, setpoints, etc.) to subplants via BMS);
identifying, by the one or more processors, energy information for the one or more buildings based on at least one of the location of the one or more buildings or the climate information of the one or more buildings (¶ 0110, 0311, 0314; Fig. 23; at step 3708, data relating to available space for new energy assets is collected, i.e., physical limits on where a new asset could be positioned (indoor or outdoor, rooftop or ground level, etc.) or how big a new asset could be (roof size, volume of available space, area of available space, etc. in order to fit with an existing building and pre-existing building equipment; in Fig. 23, step 3714: "generate one or more recommended new assets to install at the building);
receiving, by the one or more processors, a selection of one or more project options relating to a sustainability project associated with the plurality of buildings (¶ 0061, 0127, 0147, 0260-0262, 0299, 0306, 0350; configuration tools can allow a user to define (e.g., via graphical user interfaces, via prompt-driven “wizards,” etc.) various parameters of the simulation such as the number and type of subplants, the devices within each subplant, the subplant curves, device-specific efficiency curves, the duration of the simulation, the duration of the prediction window, the duration of each time step, and/or various other types of plan information related to the simulation; configuration tools can present user interfaces for building the simulation; the user interfaces may allow users to define simulation parameters graphically; at step 3608, a user interface is generate that allows a user to select a preferred point along the comfort-vs-carbon curve generated in step; for example, a graphical user interface may show the comfort-vs-carbon curve and allow the user to select a point on the curve by touching or clicking on the preferred point; the user can thus directly select a desired tradeoff between occupant comfort and carbon emissions while seeing the actual relationship between the variables for a particular building, plant, or campus; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user);
determining, by the one or more processors, one or more project estimates for the sustainability project based on the one or more project options and at least one of the climate information or the energy information for the plurality of buildings (¶ 0061, 0127, 0147, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user);
generating, by the one or more processors, a user interface including the one or more project estimates (¶ 0061, 0127, 0147, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user); and
causing, by the one or more processors, a display device to display the user interface (¶ 0061, 0127, 0147, 0260-0262, 0299, 0306, 0350; configuration tools can present user interfaces for building the simulation; the controller maximizes the life cycle economic value of the central plant equipment while participating in price-based demand response (PBDR) programs, incentive-based demand response (IBDR) programs, or simultaneously in both PBDR and IBDR programs; for IBDR programs, the controller may use statistical estimates of past clearing prices, mileage ratios, and event probabilities to determine the revenue generation potential of selling stored energy to energy purchasers; for PBDR programs, the controller may use predictions of ambient conditions, facility thermal loads, and thermodynamic models of installed equipment to estimate the resource consumption of the building and/or the subplants; the controller may use predictions of the resource consumption; building conditions may include, for example, a temperature of the building or a zone of the building, a power consumption (e.g., electric load) of the building, a state of one or more actuators configured to affect a controlled state within the building, or other types of information relating to the controlled building; BMS may operate subplants to affect the monitored conditions within the building and to serve the thermal energy loads of the building; demand response optimizer may use the planned loads and utility rates to determine an optimal resource allocation over a prediction window; demand response optimizer may output the applied resource allocation to reporting applications for presentation to a client device (e.g., via user interface); reporting applications may include a web-based reporting application with several graphical user interface (GUI) elements (e.g., widgets, dashboard controls, windows, etc.) for displaying key performance indicators (KPI) or other information to users of a GUI; in addition, the GUI elements may summarize relative energy use and intensity across various plants, subplants, or the like; other GUI elements or reports may be generated and shown based on available data that allow users to assess the results of the simulation; a graph such as the first graph, second graph, and third graph, for a particular building, group of buildings, etc. can be automatically generated at step 3508 and displayed via a graphical user interface to allow a user to directly view and assess the relationship between cost savings and carbon savings for the particular building or group of buildings managed by the user).
Regarding Claim 14, Wenzel discloses the limitations of Claim 13. Wenzel discloses the additional limitations of Claim 14 in the same manner as for Claim 4.
Regarding Claim 15, Wenzel discloses the limitations of Claim 13. Wenzel discloses the additional limitations of Claim 15 in the same manner as for Claim 6.
Regarding Claim 16, Wenzel discloses the limitations of Claim 13. Wenzel discloses the additional limitations of Claim 16 in the same manner as for Claim 7.
Regarding Claim 17, Wenzel discloses the limitations of Claim 16. Wenzel discloses the additional limitations of Claim 17 in the same manner as for Claim 9.
Regarding Claim 18, Wenzel discloses the limitations of Claim 13. Wenzel additionally discloses generating, by the one or more processors, the energy information based on the at least one of the location of the one or more buildings or the climate information of the one or more buildings; or retrieving, by the one or more processors, the energy information from the one or more external computing systems or one or more second external computing systems based on the at least one of the location of the one or more buildings or the climate information of the one or more buildings (¶ 0091-0092, 0110-0111, 0132, 0256, 0311, 0314; Figs. 4, 23; at step 3708, data relating to available space for new energy assets is collected, i.e., physical limits on where a new asset could be positioned (indoor or outdoor, rooftop or ground level, etc.) or how big a new asset could be (roof size, volume of available space, area of available space, etc. in order to fit with an existing building and pre-existing building equipment; in Fig. 23, step 3714: "generate one or more recommended new assets to install at the building; BMS controller is shown to include a communications interface and a BMS interface; interface may facilitate communications between BMS controller and external applications (e.g., monitoring and reporting applications, enterprise control applications, remote systems and applications, applications residing on client devices, etc.); communications interface may be a network interface configured to facilitate electronic data communications between central plant controller and various external systems or devices (e.g., BMS, subplants, utilities, etc.); for example, central plant controller may receive information from BMS indicating one or more measured states of the controlled building (e.g., temperature, humidity, electric loads, etc.) and one or more states of subplants (e.g., equipment status, power consumption, equipment availability, etc.); communications interface may receive inputs from BMS and/or subplants and may provide operating parameters (e.g., on/off decisions, setpoints, etc.) to subplants via BMS).
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.
The factual inquiries 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 3-4 are rejected under 35 U.S.C. 103 as being unpatentable over Wenzel in view of Ye et al (AU 2021103663).
Regarding Claim 3, Wenzel discloses the limitations of Claim 1. Wenzel does not explicitly disclose but Ye does disclose:
wherein the climate information comprises a climate zone code of the one or more buildings (Abstract; ¶ 08, 13, 26, 33-35, 52-56; Fig. 3; Claim 2; collecting auxiliary variable information of each provincial-level administrative region based on building characteristics, social and economic conditions, regional climate background, and ambient microclimate of buildings, and creating respective grid maps of the auxiliary variable information; obtaining energy consumption data of each provincial-level administrative region within the same or close building climate zones, where the energy consumption data includes primary energy consumption, heat consumption, and electricity consumption); and
the plurality of building indicators are visually coded based on the climate zone code of the one or more buildings (Abstract; ¶ 08, 13, 26, 33-35, 25-56; Fig. 3; Claim 2; collecting auxiliary variable information of each provincial-level administrative region based on building characteristics, social and economic conditions, regional climate background, and ambient microclimate of buildings, and creating respective grid maps of the auxiliary variable information; obtaining energy consumption data of each provincial-level administrative region within the same or close building climate zones, where the energy consumption data includes primary energy consumption, heat consumption, and electricity consumption).
One of ordinary skill in the art would have been motivated to include the building-based energy visualization techniques of Ye with the energy usage display and decision-making system of Wenzel to improve the location-based energy visualization and assessment functionality already present in Wenzel (see at least Paragraphs 52-56 of Ye).
Regarding Claim 4, Wenzel in view of Ye discloses the limitations of Claim 3. Wenzel additionally discloses wherein the energy information for the one or more buildings includes at least one of average energy use information, average emissions information, or average energy cost information associated with other buildings having one or more of matching climate zone codes, similar building sizes, or matching building use types to the one or more buildings (¶ 0110, 0311; Fig. 23; at step 3706, climate data indicating available renewable power is collected (e.g., average number of sunny days, length of days, solar intensity, average wind speed, average number of windy days, etc.) is collected for the location of the building; in some embodiments, building 502 includes multiple buildings (i.e., a campus)).
Claims 12 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Wenzel in view of Mutani et al, GIS‑based urban energy modelling and energy efficiency scenarios using the energy performance certificate database, Energy Efficiency, vol. 14 (2021), a copy of which was provided in the IDS dated 7/01/2026 (hereafter, “Mutani”).
Regarding Claim 12, Wenzel discloses the limitations of Claim 1. Wenzel does not explicitly disclose but Mutani does disclose wherein the at least one graphic includes the plurality of building indicators are arranged on a map showing the location for each building (pgs. 6, 11-12; Figs. 1-2; EPC database processing, engineering model application, identification of energy efficiency scenarios, and urban energy atlas updates as a decision-making tool).
It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to include the location-based energy usage display techniques of Mutani with the energy usage display and decision-making system of Wenzel because the combination merely applies a known technique to a known device/method/product ready for improvement to yield predictable results (see KSR Int’l Co. v. Teleflex, Inc., 550 U.S. 398, 415-421 (2007) and MPEP 2143). The known techniques of Mutani are applicable to the base device (Wenzel), the technical ability existed to improve the base device in the same way, and the results of the combination are predictable because the function of each piece (as well as the problems in the art which they address) are unchanged when combined.
Regarding Claim 20, Wenzel discloses the limitations of Claim 19. Wenzel does not explicitly disclose but Mutani does disclose wherein the user interface further includes at least one graphic having a plurality of building indicators arranged on a map, each building indicator corresponding to a building of the plurality of buildings, the plurality of building indicators being visually coded based on at least one of the climate information or the energy information (pgs. 6, 11-12; Figs. 1-2; EPC database processing, engineering model application, identification of energy efficiency scenarios, and urban energy atlas updates as a decision-making tool).
The rationale to combine remains the same as for Claim 12.
Discussion of Prior Art Cited but Not Applied
For additional information on the state of the art regarding the claims of the present application, please see the following documents not applied in this Office Action (all of which are prior art to the present application):
PGPub 20230305587 – “Energy Data Presentation and Visualization Dashboard System, Method and Computer Program Product Providing Energy Performance, Diagnostic Data and Economic Impact of All Monitored Energy Consuming and Production Assets,” Thirumurthy et al
PGPub 20170083989 – “Systems and Methods for Advanced Energy Network,” Brockman et al
Mutani et al, GIS‑based urban energy modelling and energy efficiency scenarios using the energy performance certificate database, Energy Efficiency, vol. 14 (2021)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARK C CLARE whose telephone number is (571)272-8748. The examiner can normally be reached Monday-Friday 6:30am-2:30pm EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jeffrey Zimmerman can be reached at (571) 272-4602. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MARK C CLARE/Examiner, Art Unit 3628
/MICHAEL P HARRINGTON/Primary Examiner, Art Unit 3628
Prosecution Insights