DETAILED ACTION
Claims 1-20 are cancelled. Claims 21-40 are new. Claims 21-40 are pending in the application.
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 .
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.
Examiner’s Notes
The Examiner cites particular sections in the references as applied to the claims below for the convenience of the applicant(s). Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant(s) fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
Information Disclosure Statement
The information disclosure statement (IDS) filed 11/04/2024 fails to comply with 37 CFR 1.98(a)(1), which requires the following: (1) a list of all patents, publications, applications, or other information submitted for consideration by the Office; (2) U.S. patents and U.S. patent application publications listed in a section separately from citations of other documents; (3) the application number of the application in which the information disclosure statement is being submitted on each page of the list; (4) a column that provides a blank space next to each document to be considered, for the examiner’s initials; and (5) a heading that clearly indicates that the list is an information disclosure statement. Specifically, the foreign patent document JP 2012184770 (Shimada et al.; filed on 08/24/2012) is not listed with the IDS. The information disclosure statement has been placed in the application file, but the information referred to therein has not been considered.
Specification
The disclosure is objected to because of the following informalities:
The instant application is a continuation of U.S. Patent Application No. 17/170,668 which is now issued as U.S. Patent No. 12,058,212 B2 on 08/06/2024. Both the patent number and the issue date must be disclosed in the first paragraph of the specification and/or with the Application Data Sheet.
Appropriate corrections are required. Applicant is advised to review the entire disclosure for further needed corrections.
Double Patenting
The non-statutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A non-statutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on non-statutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a non-statutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 21-26, 28-33, and 35-39 are rejected on the ground of non-statutory double patenting as being unpatentable over claims 1, 3-7, 10, 12-14, and 17-19 of U.S. Patent No. 12,058,212 B2.
Instant Application
U.S. Patent No. 12,058,212 B2
Claim
Limitation
Claim
Limitation
21
A system, comprising: one or more processors coupled to non-transitory memory, the one or more processors configured to: select, for a building asset of a plurality of building assets identified in a digital representation of a building, based on a type of data accessed or generated by the building asset, a control action for configuration of the building; operate at least one of the plurality of building assets according to the control action to control a parameter of the building; and update a confidence value indicating a validity of a relationship identified in the digital representation responsive to controlling the parameter of the building.
14
A building management system (BMS) comprising a processing circuit including a processor and memory, the memory having instructions stored thereon that, when executed by the processor, cause the processing circuit to: identify a building asset within a digital representation of a building having nodes representative of building assets within the building and edges describing one or more relationships of the building asset within the building; select and execute, based on a type of data monitored by the building asset, a predetermined control action for one or more other building assets included within the digital representation to change an environmental parameter of the building; monitor a response of at least one of the building asset or one of the one or more other building assets to the predetermined control action; and update the digital representation to include a parameter defining a health metric of a node or edge associated with the building asset based on a comparison of the monitored response to the predetermined control action to an expected response, wherein the parameter defining the health metric describes a confidence level in a validity of one of the one or more relationships.
22
The system of claim 21, wherein the one or more processors are further configured to: monitor a response to the control action based on data received from at least one other building asset of the plurality of building assets; and update the confidence value based on the response.
14
monitor a response of at least one of the building asset or one of the one or more other building assets to the predetermined control action; and update the digital representation to include a parameter defining a health metric of a node or edge associated with the building asset based on a comparison of the monitored response to the predetermined control action to an expected response, wherein the parameter defining the health metric describes a confidence level in a validity of one of the one or more relationships.
23
The system of claim 22, wherein the one or more processors are further configured to: update the confidence value based on covariance between sensor measurements received from at least two of the plurality of building assets.
17
he building management system (BMS) of claim 14, wherein generating the confidence level includes analyzing a covariance between sensor measurements of the one or more other building assets associated with the change in the environmental parameter of the building.
24
The system of claim 21, wherein the digital representation includes a graph data structure, and wherein the one or more processors are further configured to: update the confidence value associated with at least one edge of the graph data structure representing the relationship.
18
The building management system (BMS) of claim 14, wherein the digital representation includes a graph data structure and wherein the processing circuit is further configured to update one or more portions of the graph data structure to represent a relationship of the building asset.
25
The system of claim 21, wherein the one or more processors are further configured to: determine a change relative to a prior version of the digital representation by comparing the digital representation with the prior version of the digital representation.
19
The building management system (BMS) of claim 14, wherein the digital representation includes a graph data structure and wherein the processing circuit is further configured to compare versions of the graph data structure representing at least a portion of the building to identify changes between the versions, and wherein identifying the building asset includes selecting an asset based on an identified change between the versions of the graph data structure.
26
The system of claim 25, wherein the one or more processors are further configured to: select the building asset of the plurality of building assets based on the change.
19
The building management system (BMS) of claim 14, wherein the digital representation includes a graph data structure and wherein the processing circuit is further configured to compare versions of the graph data structure representing at least a portion of the building to identify changes between the versions, and wherein identifying the building asset includes selecting an asset based on an identified change between the versions of the graph data structure.
28
A method, comprising: selecting, by one or more processors coupled to non-transitory memory, for a building asset of a plurality of building assets identified in a digital representation of a building, based on a type of data accessed or generated by the building asset, a control action for configuration of the building; operating, by the one or more processors, at least one of the plurality of building assets according to the control action to control a parameter of the building; and updating, by the one or more processors, a confidence value indicating a validity of a relationship identified in the digital representation responsive to controlling the parameter of the building.
1
A method for commissioning a building, comprising: identifying a building asset within a digital representation of the building having one or more parameters describing relationships of the building asset within the building; selecting and executing, based on a type of sensor data monitored by the building asset, a predetermined control action for one or more other building assets included within the digital representation to change an environmental parameter of the building; monitoring a response of at least one of the building asset or one of the one or more other building assets to the change in the environmental parameter; and updating the digital representation to include a parameter defining a health metric for a relationship between the building asset and at least one of the one or more other building assets based on a comparison of the monitored response to the predetermined control action to an expected response, wherein the parameter defining the health metric describes a confidence level in a validity of one of the one or more parameters.
29
The method of claim 28, further comprising: monitoring, by the one or more processors, a response to the control action based on data received from at least one other building asset of the plurality of building assets; and updating, by the one or more processors, the confidence value based on the response.
1
monitoring a response of at least one of the building asset or one of the one or more other building assets to the change in the environmental parameter; and updating the digital representation to include a parameter defining a health metric for a relationship between the building asset and at least one of the one or more other building assets based on a comparison of the monitored response to the predetermined control action to an expected response, wherein the parameter defining the health metric describes a confidence level in a validity of one of the one or more parameters.
30
The method of claim 29, further comprising: updating, by the one or more processors, the confidence value based on covariance between sensor measurements received from at least two of the plurality of building assets.
3
The method of claim 1, wherein updating the digital representation includes analyzing a covariance between sensor measurements of the one or more other building assets associated with the change in the environmental parameter of the building.
31
The method of claim 28, wherein the digital representation includes a graph data structure, and further comprising: updating, by the one or more processors, the confidence value associated with at least one edge of the graph data structure representing the relationship.
4
The method of claim 1, wherein the digital representation includes a graph data structure and wherein the method further comprises updating one or more portions of the graph data structure to represent the relationship of the building asset.
32
The method of claim 28, further comprising: determining, by the one or more processors, a change relative to a prior version of the digital representation by comparing the digital representation with the prior version of the digital representation.
5
The method of claim 1, wherein the digital representation includes a graph data structure and wherein the method further comprises comparing versions of the graph data structure representing at least a portion of the building to identify changes between the versions.
33
The method of claim 32, further comprising: selecting, by the one or more processors, the building asset of the plurality of building assets based on the change.
6
The method of claim 5, wherein identifying the building asset includes selecting an asset based on an identified change between the versions of the graph data structure.
35
One or more non-transitory computer-readable storage media having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to: select, for a building asset identified in a graph data structure storing relationships between a plurality of building assets of a building, based on a type of data accessed or generated by the building asset, a control action for configuration of the building; operate at least one of the plurality of building assets according to the control action to control an environmental parameter of the building; and update a confidence value associated with an edge of the graph data structure indicating a validity of a relationship represented by the edge responsive to controlling the environmental parameter of the building, the confidence value represented as a health metric in the graph data structure.
7
One or more non-transitory computer-readable storage media having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to: receive a digital representation of a building having nodes describing entities representing spaces, locations, building assets, points, or events within the building and edges describing one or more relationships between nodes, the digital representation comprising an identified building asset; control, based on a type of sensor data monitored by the identified building asset, one or more first building assets included within the digital representation to change an environmental parameter of the building; monitor a response of the identified building asset, at least one of the one or more first building assets, or one or more second building assets to the change in the environmental parameter; and update the digital representation to include a parameter defining a health metric of a node or edge associated with the one or more second building assets or the identified building asset based on a comparison of the monitored response to an expected response, wherein the parameter defining the health metric describes a confidence level in a validity of one of the one or more relationships.
36
The one or more non-transitory computer-readable storage media of claim 35, wherein the instructions, when executed, further cause the one or more processors to: monitor a response to the control action based on data received from at least one other building asset of the plurality of building assets; and update the confidence value based on the response.
7
monitor a response of the identified building asset, at least one of the one or more first building assets, or one or more second building assets to the change in the environmental parameter; and update the digital representation to include a parameter defining a health metric of a node or edge associated with the one or more second building assets or the identified building asset based on a comparison of the monitored response to an expected response, wherein the parameter defining the health metric describes a confidence level in a validity of one of the one or more relationships.
37
The one or more non-transitory computer-readable storage media of claim 36, wherein the instructions, when executed, further cause the one or more processors to: update the confidence value based on covariance between sensor measurements received from at least two of the plurality of building assets.
10
The one or more non-transitory computer-readable storage media of claim 7, wherein generating the confidence level includes analyzing a covariance between sensor measurements of the identified building asset or the one or more second building assets associated with the change in the environmental parameter of the building.
38
The one or more non-transitory computer-readable storage media of claim 35, wherein the instructions, when executed, further cause the one or more processors to: determine a change relative to a prior version of the graph data structure by comparing the graph data structure with the prior version of the graph data structure.
12
The one or more non-transitory computer-readable storage media of claim 7, wherein the digital representation includes a graph data structure and wherein the one or more processors are further configured to compare versions of the graph data structure representing at least a portion of the building to identify changes between the versions.
39
The one or more non-transitory computer-readable storage media of claim 38, wherein the instructions, when executed, further cause the one or more processors to :select the building asset of the plurality of building assets based on the change.
13
The one or more non-transitory computer-readable storage media of claim 12, wherein the identified building asset is selected based on an identified change between the versions of the graph data structure.
With respect to claims 21-26, 28-33, and 35-39: Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1, 3-7, 10, 12-14, and 17-19 of U.S. Patent No. 12,058,212 B2 anticipates claims 21-40 as identified above.
Claims 27, 34, and 40 rejected on the ground of non-statutory double patenting as being unpatentable over claims 1, 7, and 14 of U.S. Patent No. 12,058,212 B2 in view of Park et al. (US 2019/0158309 A1; from IDS filed on 11/04/2024; hereinafter “Park”).
With respect to claim 27: U.S. Patent No. 12,058,212 B2 teaches “The system of claim 21” as identified above.
U.S. Patent No. 12,058,212 B2 does not but Park teaches:
receive configuration information indicating the building asset has been added to the digital representation (see e.g. Park, paragraph 440: “space graph learning service 1104 is configured to automatically… deduce new entity types for newly added entities”; and paragraph 452: “at periodic intervals, the space graph learning service 1104 is configured to analyze newly ingested operational data and/or newly added entities”); and
select the control action based on the configuration information (see e.g. Park, paragraph 179: “generate control schedules for a thermostat based on information of the space graph… control schedule can be an entity of the space graph which implements operation of the thermostat and/or may be associated with a relationship between the agent and the control schedule and a relationship between the control schedule and the thermostat”).
With respect to claim 34: Claim 34 is directed to a method corresponding to the active functions implemented by the system disclosed in claim 27; please see the rejection directed to claim 27 above which also covers the limitations recited in claim 34.
With respect to claim 40: Claim 40 is directed to one or more non-transitory computer-readable storage media having instructions stored thereon that, when executed by one or more processors, cause the one or more processor to implement active functions implemented by the one or more processors of the system disclosed in claim 27; please see the rejection directed to claim 27 above which also covers the limitations recited in claim 40.
Claim Rejections - 35 USC § 112(b)
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 21-27 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.
Claim 21 recites “A system, comprising: one or more processors coupled to non-transitory memory, the one or more processors configured to” in lines 1-3. This limitation identifies an intended use for the “one or more processors”. Specifically, it is not clear if the processors actually perform the functions recited therewith (i.e. select, operate, and update) or if the processors merely have the configuration that can perform such functions.
For the following analysis, the Examiner will consider the “one or more processors” actually performing the functions recited in claim 21.
Claims 22-27 inherit the features of claim 21 and are rejected accordingly.
Claim Rejections - 35 USC § 102
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.
Claims 21-34 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Park et al. (US 2019/0158309 A1; from IDS filed on 11/04/2024; hereinafter “Park”).
With respect to claim 21, Park teaches: A system (see e.g. paragraph 225: “building management system (BMS) 500”; and Fig. 5), comprising:
one or more processors (see e.g. Fig. 5: “Processor 506”) coupled to non-transitory memory (see e.g. Fig. 5: “Memory 508”; and paragraph 230: “memory 508 is communicably connected to processor 506”), the one or more processors configured to (see e.g. paragraphs 229-230):
select, for a building asset of a plurality of building assets (see e.g. paragraph 177: “entities, relationships, and/or information to be stored for operating a building”; and paragraph 266: “An asset may be any resource or entity type, such as, for example, a person, building, space, system, equipment, device, sensor, and the like”) identified in a digital representation (see e.g. paragraph 177: “space graph can be a total representation, a digital twin, of an entire space since the space graph can represent the entities of the space, relationships between the entities, and data for the entities”) of a building (see e.g. paragraph 177: “a building management system with space graphs… space graph can be a data structure allowing entities, relationships, and/or information to be stored for operating a building”), based on a type of data accessed or generated by the building asset (see e.g. paragraph 177: “space graph can be a data structure including nodes and edges, the nodes representing particular entities and the edges between the nodes representing a relationship between the entities”; and paragraph 178: “a first entity of a space graph can be linked to a second entity of a space graph with a first relationship while the second entity can be linked to the first entity with a different relationship. For example, a variable air volume and a thermostat could be related to each other, however, their relationships to each other are different. The thermostat can be configured to control the VAV while the VAV can be configured to receive commands from the thermostat. Both relationships, though different, can be captured in the space graph”), a control action for configuration of the building (see e.g. paragraph 179: “generate control schedules for a thermostat based on information of the space graph… control schedule can be an entity of the space graph which implements operation of the thermostat and/or may be associated with a relationship between the agent and the control schedule and a relationship between the control schedule and the thermostat”);
operate at least one of the plurality of building assets according to the control action to control a parameter of the building (see e.g. paragraph 179: “implements operation of the thermostat and/or may be associated with a relationship between the agent and the control schedule and a relationship between the control schedule and the thermostat”; paragraph 197: “attributes that indicate the most recent values collected by the sensor, and/or one or more relational attributes that relate sensors object smart entities to each other and/or to other types of smart entities (e.g., space entities, system entities, data entities, etc.)”; paragraph 205: “configured to measure attributes of the supply airflow. AHU 206 may receive input from sensors located within AHU 206 and/or within the building zone and may adjust the flow rate, temperature, or other attributes of the supply airflow”); and
update a confidence value indicating a validity of a relationship identified in the digital representation (see e.g. paragraph 452: “generate a confidence level that the permanent relationship should exist and, in response to determine a confidence level above a predefined amount, replace the temporary relationship with a permanent relationship”; and paragraph 473: “if an event indicating a relationship occurs every hour, this may indicate a first level for the confidence level. However, if the event indicating the relationship occurs ten times every hour, this may indicate a second level for the confidence level”) for the digital representation associated with the building asset (see e.g. paragraph 177: “space graph can be a total representation, a digital twin, of an entire space since the space graph can represent the entities of the space, relationships between the entities, and data for the entities”) based on the monitoring responsive to controlling the parameter of the building (see e.g. paragraph 452: “analyze newly ingested operational data and/or newly added entities and/or relationship of the space graph database 1120 to generate a confidence level”; paragraph 473: “ingests the new building data into the space graph database 1120 and/or otherwise analyzes the ingested and/or new building data”; and paragraph 197: “attributes that indicate the most recent values collected by the sensor, and/or one or more relational attributes that relate sensors object smart entities to each other and/or to other types of smart entities (e.g., space entities, system entities, data entities, etc.)”).
Park discloses updating a confidence value indicating a relationship between entities of a building is a permanent relationship (i.e. a valid relationship) based on ingested building system data, including attributes (parameters) associated with building system assets.
With respect to claim 22, Park teaches: The system of claim 21, wherein the one or more processors are further configured to:
monitor a response to the control action based on data received from at least one other building asset of the plurality of building assets (see e.g. paragraph 452: “periodically test the temporary relationship to determine whether the temporary relationship should be converted into a permanent relationship. For example, at periodic intervals, the space graph learning service 1104 is configured to analyze newly ingested operational data and/or newly added entities and/or relationship of the space graph database 1120”; and paragraph 473: “ingests the new building data into the space graph database 1120 and/or otherwise analyzes the ingested and/or new building data”); and
update the confidence value based on the response (see e.g. paragraph 452: “at periodic intervals, the space graph learning service 1104 is configured to analyze newly ingested operational data and/or newly added entities and/or relationship of the space graph database 1120 to generate a confidence level that the permanent relationship should exist and, in response to determine a confidence level above a predefined amount”; and paragraph 473: “if an event indicating a relationship occurs every hour, this may indicate a first level for the confidence level. However, if the event indicating the relationship occurs ten times every hour, this may indicate a second level for the confidence level. If the confidence level is greater than a predefined amount”).
With respect to claim 23, Park teaches: The system of claim 22, wherein the one or more processors are further configured to:
update the confidence value based on covariance between sensor measurements received from at least two of the plurality of building assets (see e.g. paragraph 452: “analyze newly ingested operational data and/or newly added entities and/or relationship”; paragraph 178: “a variable air volume and a thermostat could be related to each other, however, their relationships to each other are different. The thermostat can be configured to control the VAV while the VAV can be configured to receive commands from the thermostat. Both relationships, though different, can be captured in the space graph”; paragraph 183: “detect the impact relationship and add the relationship to the space graph to represent the impact which the control configuration has on the entity. For example, heating or cooling a particular zone may have an impact on the temperature of a neighboring zone. Therefore, a direct relationship may exist between heating or cooling equipment and the first zone while an impact relationship may exist between the heating or cooling equipment and the neighboring zone”; paragraph 186: “collect data from a variety of devices… devices may include any of a variety of physical devices, sensors”).
With respect to claim 24, Park teaches: The system of claim 21, wherein the digital representation includes a graph data structure (see e.g. paragraph 177: “a building management system with space graphs… space graph can be a data structure allowing entities, relationships, and/or information to be stored for operating a building”), and wherein the one or more processors are further configured to:
update the confidence value associated with at least one edge of the graph data structure representing the relationship (see e.g. paragraph 473: “the edge is associated with and/or stores a confidence level. The confidence level may be based on machine learning and/or relationship rules. For example, if an event indicating a relationship occurs every hour, this may indicate a first level for the confidence level. However, if the event indicating the relationship occurs ten times every hour, this may indicate a second level for the confidence level. If the confidence level is greater than a predefined amount”).
With respect to claim 25, Park teaches: The system of claim 21, wherein the one or more processors are further configured to:
determine a change relative to a prior version of the digital representation by comparing the digital representation with the prior version of the digital representation (see e.g. paragraph 293: “virtual representations maintain shadow copies of the object entities with versioning information so that entity service 626 can store not only the most recent update of an attribute (e.g., a dynamic attribute) associated with the object, but records of previous states of the attributes (e.g., dynamic attributes) and/or entities. For example, the shadow record may be created as a type of data entity that is related to a linked data entity corresponding to the dynamic attribute of the object entity (e.g., the person, room, building subsystem, device, and the like) … the shadow entity may be used to determine additional analytics for the data point of the dynamic attribute. For example, the shadow entity may be used to determine an average value, an expected value, or an abnormal value of the data point from the dynamic attribute”).
With respect to claim 26, Park teaches: The system of claim 25, wherein the one or more processors are further configured to:
select the building asset of the plurality of building assets based on the change (see e.g. paragraph 293: “maintain shadow copies of the object entities with versioning information so that entity service 626 can store not only the most recent update of an attribute (e.g., a dynamic attribute) associated with the object, but records of previous states of the attributes (e.g., dynamic attributes) and/or entities… shadow entity may be used to determine additional analytics for the data point of the dynamic attribute. For example, the shadow entity may be used to determine an average value, an expected value, or an abnormal value of the data point from the dynamic attribute”).
With respect to claim 27, Park teaches: The system of claim 21, wherein the one or more processors are further configured to:
receive configuration information indicating the building asset has been added to the digital representation (see e.g. paragraph 440: “space graph learning service 1104 is configured to automatically… deduce new entity types for newly added entities”; and paragraph 452: “at periodic intervals, the space graph learning service 1104 is configured to analyze newly ingested operational data and/or newly added entities”); and
select the control action based on the configuration information (see e.g. paragraph 179: “generate control schedules for a thermostat based on information of the space graph… control schedule can be an entity of the space graph which implements operation of the thermostat and/or may be associated with a relationship between the agent and the control schedule and a relationship between the control schedule and the thermostat”).
With respect to claims 28-34: Claims 28-34 are directed to a method corresponding to the active functions implemented by the system disclosed in claims 21-27, respectively; please see the rejections directed to claims 21-27 above which also cover the limitations recited in claims 28-34.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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 35-40 are rejected under 35 U.S.C. 103 as being unpatentable over Park in view of Park et al. (US 2020/0106633 A1; from IDS filed on 11/04/2024; hereinafter “Park-02”).
With respect to claims 35, Park teaches: One or more non-transitory computer-readable storage media having instructions stored thereon (see e.g. Park, paragraph 481) that, when executed by one or more processors, cause the one or more processors to (see e.g. Park, paragraphs 229-230):
select, for a building asset (see e.g. Park, paragraph 177: “entities, relationships, and/or information to be stored for operating a building”; and paragraph 266: “An asset may be any resource or entity type, such as, for example, a person, building, space, system, equipment, device, sensor, and the like”) identified in a graph data structure (see e.g. Park, paragraph 177: “space graph can be a total representation, a digital twin, of an entire space since the space graph can represent the entities of the space, relationships between the entities, and data for the entities”) storing relationships between a plurality of building assets of a building (see e.g. Park, paragraph 177: “relationships between the entities”), based on a type of data accessed or generated by the building asset (see e.g. Park, paragraph 177: “space graph can be a data structure including nodes and edges, the nodes representing particular entities and the edges between the nodes representing a relationship between the entities”; and paragraph 178: “a first entity of a space graph can be linked to a second entity of a space graph with a first relationship while the second entity can be linked to the first entity with a different relationship. For example, a variable air volume and a thermostat could be related to each other, however, their relationships to each other are different. The thermostat can be configured to control the VAV while the VAV can be configured to receive commands from the thermostat. Both relationships, though different, can be captured in the space graph”), a control action for configuration of the building (see e.g. Park, paragraph 179: “generate control schedules for a thermostat based on information of the space graph… control schedule can be an entity of the space graph which implements operation of the thermostat and/or may be associated with a relationship between the agent and the control schedule and a relationship between the control schedule and the thermostat”);
operate at least one of the plurality of building assets according to the control action to control an environmental parameter of the building (see e.g. Park, paragraph 179: “implements operation of the thermostat and/or may be associated with a relationship between the agent and the control schedule and a relationship between the control schedule and the thermostat”; paragraph 197: “attributes that indicate the most recent values collected by the sensor, and/or one or more relational attributes that relate sensors object smart entities to each other and/or to other types of smart entities (e.g., space entities, system entities, data entities, etc.)”; paragraph 205: “configured to measure attributes of the supply airflow. AHU 206 may receive input from sensors located within AHU 206 and/or within the building zone and may adjust the flow rate, temperature, or other attributes of the supply airflow”); and
update a confidence value associated with an edge of the graph data structure indicating a validity of a relationship represented by the edge (see e.g. Park, paragraph 177: “space graph can be a data structure including nodes and edges, the nodes representing particular entities and the edges between the nodes representing a relationship between the entities”; paragraph 452: “generate a confidence level that the permanent relationship should exist and, in response to determine a confidence level above a predefined amount, replace the temporary relationship with a permanent relationship”; and paragraph 473: “if an event indicating a relationship occurs every hour, this may indicate a first level for the confidence level. However, if the event indicating the relationship occurs ten times every hour, this may indicate a second level for the confidence level”) responsive to controlling the environmental parameter of the building (see e.g. Park, paragraph 452: “analyze newly ingested operational data and/or newly added entities and/or relationship of the space graph database 1120 to generate a confidence level”; paragraph 473: “ingests the new building data into the space graph database 1120 and/or otherwise analyzes the ingested and/or new building data”; and paragraph 197: “attributes that indicate the most recent values collected by the sensor, and/or one or more relational attributes that relate sensors object smart entities to each other and/or to other types of smart entities (e.g., space entities, system entities, data entities, etc.)”),
Park does not but Park-02 teaches:
the confidence value represented as a health metric in the graph data structure (see e.g. Park-02, paragraph 162: “Health data 914 can convey various information related to the performance and condition of building asset 910”; and paragraph 174: “Assurance service 800 can be configured to curate and correlate various information received form building assets and apply this information to a set of rules to determine if any assets are out of compliance. Assurance service 800 can analyze information received from building asset 910 related… health data 914 ”).
Park and Park-02 are analogous art because they are in the same field of endeavor: providing a building management system for managing building assets. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify Park with the teachings of Park-02. The motivation/suggestion would be to improve the building asset management efficiency (see e.g. Park-02, paragraph 162).
With respect to claims 36-40: Claims 36-40 are directed to one or more non-transitory computer-readable storage media having instructions stored thereon that, when executed by one or more processors, cause the one or more processor to implement active functions implemented by the one or more processors of the system disclosed in claims 22-23 and 25-27, respectively; please see the rejections directed to claims 22-23 and 25-27 above which also cover the limitations recited in claims 36-40.
CONCLUSION
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Park et al. (US 2020/0092127 A1) discloses a space graph learning service for a building management system that determines if a relationship between entities is temporary or permanent based on a corresponding confidence level (see paragraph 453).
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/UMUT ONAT/Primary Examiner, Art Unit 2194
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