Building management system with building equipment servicing

Patent metadata

Field	Value
Publication number	US-2024403343-A1
Application number	US-202418677658-A
Country	US
Kind code	A1
Filing date	May 29, 2024
Priority date	May 30, 2023
Publication date	Dec 5, 2024
Grant date	—

Abstract

A building management system (BMS) can include one or more memory devices storing instructions thereon that can, when executed by one or more processors, cause the one or more processors to receive a plurality of information, generate a data model to represent the plurality of information in a common format associated with the BMS, execute a pre-processing routine, receive a query that corresponds to a building associated with the BMS, identify a given vector embedding of a plurality of vector embeddings that correlates to first information associated with the building, generate a response to the query that includes at least one of a graphical representation of the first information associated with the building or a textual summary of the first information associated with the building.

First claim

What is claimed is:

1 . A building management system (BMS) comprising one or more memory devices storing instructions thereon that, when executed by one or more processors, causes the one or more processors to:
receive, from one or more devices having subscriptions with the BMS, a plurality of information that corresponds to at least one of a structured data format or a timeseries data format; generate, based at least on one or more rules, a data model to represent the plurality of information in a common format associated with the BMS; execute a pre-processing routine, including:
converting, responsive to generation of the data model, the plurality of information into natural language text, the natural language text including a plurality of segments that represents the plurality of information; and
generating, using a large language model (LLM), a plurality of vector embeddings that represent the plurality of segments, wherein a respective vector embedding of the plurality of vector embeddings represents a respective segment of the plurality of segments;
receive, via a user interface displayed by a user device, a query that corresponds to a building associated with the BMS, the query including a request for first information associated with the building; identify a given vector embedding of the plurality of vector embeddings that correlates to the first information associated with the building; generate, using the LLM based at least on a given segment of the plurality of segments represented by the given vector embedding of the plurality of vector embeddings, a response to the query that includes at least one of:
a graphical representation of the first information associated with the building; or
a textual summary of the first information associated with the building; and
display, via the user interface, the response to the query.

2 . The BMS of claim 1 , wherein the pre-processing routine further include:
generating, prior to generating the plurality of vector embeddings, a plurality of summaries that describe the plurality of segments; and constructing, responsive to generating the plurality of summaries, a plurality of keys to associate the plurality of summaries with the plurality of segments.

3 . The BMS of claim 2 , wherein the instructions cause the one or more processors to:
determine, responsive to receipt of the query, a plurality of values that represent correlations between the query and the plurality of summaries; detect a first value of the plurality of values that conforms to a predetermined threshold, the first value representing a correlation between the query and a given summary of the plurality of summaries; identify, responsive to detection of the first value, a given key of the plurality of keys associated with the given summary of the plurality of summaries; and determine that the given vector embedding correlates to the first information associated with the building based on the given key being associating the given summary with the given segment.

4 . The BMS of claim 1 , wherein the instructions cause the one or more processors to:
identify, responsive to receipt of the query, using the LLM, a first agent of a plurality of agents to process the query, wherein the first agent is identified based on a context of the request for information associated with the building; input, using the LLM, the query and the given segment of the plurality of segments into the first agent to cause the first agent to generate an output; and generate, using the LLM based at least one the output of the first agent, the response to the query.

5 . The BMS of claim 1 , wherein the data model comprises a digital twin of the building, and wherein the instructions cause the one or more processors to:
generate, using the LLM, the digital twin of the building or a portion thereof using data related to a plurality of pieces of building equipment of the building, the LLM configured to generate the digital twin by at least one of:
generating, using the data, at least one first new relationship for the digital twin between first building equipment of the plurality of pieces of building equipment and at least one of second building equipment of the plurality of pieces of building equipment or one or more entities associated with the building, the one or more entities comprising people associated with the building, locations within the building, events associated with the building, or assets of the building; or
generating, using the data, at least one first new entity for the digital twin, the first new entity comprising a digital representation of a person associated with the building, a location within the building, an event associated with the building, or an asset of the building.

6 . The BMS of claim 5 , wherein the data comprises unstructured data conforming to a plurality of different predetermined formats and/or not conforming to a predetermined format, and wherein the LLM is configured to generate the digital twin from the unstructured data.

7 . The BMS of claim 5 , wherein the LLM is configured to autonomously generate the digital twin from the unstructured data without requiring manual user intervention.

8 . The BMS of claim 1 , wherein the LLM comprises a pre-trained generative transformer model.

9 . A method, comprising:
receiving, by one or more processing circuits from one or more devices having subscriptions with a building management system (BMS), a plurality of information that corresponds to at least one of a structured data format or a timeseries data format; generating, by the one or more processing circuits, based at least on one or more rules, a data model to represent the plurality of information in a common format associated with the BMS; executing, by the one or more processing circuits, a pre-processing routine, including:
converting, by the one or more processing circuits, responsive to generation of the data model, the plurality of information into natural language text, the natural language text including a plurality of segments that represents the plurality of information; and
generating, by the one or more processing circuits, using a large language model (LLM), a plurality of vector embeddings that represent the plurality of segments, wherein a respective vector embedding of the plurality of vector embeddings represents a respective segment of the plurality of segments;
receiving, by the one or more processing circuits, from a user device, a query that corresponds to a building associated with the BMS, the query including a request for first information associated with the building; and generating, by the one or more processing circuits, using the LLM based at least on a given segment of the plurality of segments represented by a given vector embedding of the plurality of vector embeddings, a response to the query that includes at least one of:
a graphical representation of the first information associated with the building; or
a textual summary of the first information associated with the building.

10 . The method of claim 9 , wherein the pre-processing routine further include:
generating, by the one or more processing circuits, prior to generating the plurality of vector embeddings, a plurality of summaries that describe the plurality of segments; and constructing, by the one or more processing circuits, responsive to generating the plurality of summaries, a plurality of keys to associate the plurality of summaries with the plurality of segments.

11 . The method of claim 10 , comprising:
determining, by the one or more processing circuits, responsive to receipt of the query, a plurality of values that repr

Assignees

• Tyco Fire & Security Gmbh

Inventors

• Ramanasankaran Rajiv
• Malladi Sastry Km
• Swanson Trent M
• Galvez Miguel
• Makowski Gregory A
• Sudhakar Prashanthi

Classifications

• G05B13/028

  using expert systems only · CPC title

• G06F16/345

  Summarisation for human users · CPC title

• G05B2219/2642

  Domotique, domestic, home control, automation, smart house · CPC title

• G06F16/3347 Primary

  using vector based model · CPC title

• G05B15/02 Primary

  electric · CPC title