Artificial intelligence generated correlators for building digital twin

Patent metadata

Field	Value
Publication number	US-2024394281-A1
Application number	US-202418646590-A
Country	US
Kind code	A1
Filing date	Apr 25, 2024
Priority date	May 24, 2023
Publication date	Nov 28, 2024
Grant date	—

Abstract

A building system can include one or more storage devices storing instructions thereon, that, when executed by one or more processors, cause the one or more processors to generate a building graph, the building graph including nodes representing entities of a building and edges between the nodes, the edges representing relationships between the entities. The building system can execute an artificial intelligence service, the artificial intelligence service to receive at least one of data describing the entities, at least one node of the nodes, or at least one edge of the edges as an input and output a correlator type that identifies that a first entity type of a first entity of the entities impacts a second entity type of a second entity of the entities. The building system can update the building graph to include data representing a correlator based on the correlator type.

First claim

What is claimed:

1 . A building system comprising:
one or more storage devices storing instructions thereon, that, when executed by one or more processors, cause the one or more processors to:
generate a building graph, the building graph comprising a plurality of nodes representing a plurality of entities of a building and a plurality of edges between the plurality of nodes, the plurality of edges representing relationships between the plurality of entities;
execute an artificial intelligence service, the artificial intelligence service to:
receive at least one of data describing the plurality of entities, at least one node of the plurality of nodes, or at least one edge of the plurality of edges as an input; and
output a correlator type that identifies that a first entity type of a first entity of the plurality of entities impacts a second entity type of a second entity of the plurality of entities; and

update the building graph to include data representing a correlator based on the correlator type.

2 . The building system of claim 1 , wherein the instructions cause the one or more processors to:
execute the artificial intelligence service to output an indication to decorrelate a first node of the plurality of nodes and a second node of the plurality of nodes of the building graph; and remove an edge of the plurality of edges between the first node and the second node responsive to the indication to decorrelate the first node and the second node.

3 . The building system of claim 1 , wherein the instructions cause the one or more processors to:
execute the artificial intelligence service after the building graph is deployed for the building to detect changes to the building that occur after the building graph is deployed; and update the building graph while the building graph is deployed responsive to detecting the changes.

4 . The building system of claim 1 , wherein the artificial intelligence service is a large language model that receives at least a portion of the building graph as a plurality of input strings and outputs the correlator type as an output string.

5 . The building system of claim 1 , wherein the instructions cause the one or more processors to:
generate an entity type for an entity to represent a correlation between the first entity of the first entity type and the second entity of the second entity type; and update the building graph to store a node representing the entity, a first edge between a first node representing the first entity and the node, and a second edge between a second node representing the second entity and the node.

6 . The building system of claim 1 , wherein the correlator indicates that the first entity of the first entity type affects an operational performance of the second entity of the second entity type.

7 . The building system of claim 1 , wherein the instructions cause the one or more processors to:
execute the artificial intelligence service to output the correlator type without using any data indicating a direct relationship between the first entity and the second entity.

8 . The building system of claim 1 , wherein the instructions cause the one or more processors to:
generate data to cause a graphical user interface to display the correlator type; receive input from a user via the graphical user interface; and update the building graph with the correlator type responsive to a reception of the input from the user via the graphical user interface.

9 . The building system of claim 1 , wherein the plurality of edges are defined based on a plurality of available edge types;
wherein the instructions cause the one or more processors to:
generate an edge type that indicates a correlation between the first entity of the first entity type and the second entity of the second entity type; and
update the building graph to store an edge based on the edge type between a first node representing the first entity and a second node representing the second entity.

10 . The building system of claim 9 , wherein the instructions cause the one or more processors to:
identify a third entity of the first entity type represented by a third node in the building graph; identify a fourth entity of the second entity type represented by a fourth node in the building graph; and generate a second edge of the edge type responsive to an identification of the third entity of the first entity type and the fourth entity of the second entity type; and
update the building graph to store the second edge between the third node and the fourth node.

11 . The building system of claim 1 , wherein the instructions cause the one or more processors to:
instantiate a correlator artificial intelligence service to process data based on the first entity impacting the second entity; and execute the correlator artificial intelligence service to generate output data indicating an impact that the first entity has on the second entity.

12 . The building system of claim 11 , wherein the instructions cause the one or more processors to:
identify a third entity impacting a fourth entity in the building graph;
replicate the correlator artificial intelligence service to generate a second correlator artificial intelligence service; and
execute the second correlator artificial intelligence service to generate second output data indicating an impact that the third entity has on the fourth entity.

13 . The building system of claim 12 , wherein the instructions cause the one or more processors to:
instantiate the correlator artificial intelligence service to run for a length of time; execute the correlator artificial intelligence service until the length of time expires; and stop executing the correlator artificial intelligence service in response to the length of time expiring.

14 . A method comprising:
generating, by one or more processing circuits, a building graph, the building graph comprising a plurality of nodes representing a plurality of entities of a building and a plurality of edges between the plurality of nodes, the plurality of edges representing relationships between the plurality of entities; executing, by the one or more processing circuits, an artificial intelligence service, the artificial intelligence service to:
receive at least one of data describing the plurality of entities, at least one node of the plurality of nodes, or at least one edge of the plurality of edges as an input; and
output a correlator type that identifies that a first entity type of a first entity of the plurality of entities impacts a second entity type of a second entity of the plurality of entities; and
updating, by the one or more processing circuits, the building graph to include data representing a correlator based on the correlator type.

15 . The method of claim 14 , wherein the artificial intelligence service is a large language model that receives at least a portion of the building graph as a plurality of input strings and outputs the correlator type as an output string.

16 . The method of claim 14 , comprising:
generating, by the one or more processing circuits, an entity type for an entity to represent a correlation between the first entity of the first entity type and the second entity of the second entity type; and updating, by the one or more processing circuits, the building graph to store a node representing the entity, a first edge between a first node representing the first entity and the node, and a second edge between a second node representing the second entity and the node.

1

Assignees

• Tyco Fire & Security Gmbh

Inventors

• Swanson Trent M
• Galvez Miguel

Classifications

• G06F16/9024

  Graphs; Linked lists (G06F16/9027 takes precedence) · CPC title

• G06F16/248

  Presentation of query results · CPC title

• G06F16/288 Primary

  Entity relationship models · CPC title

• G06F16/243 Primary

  Natural language query formulation · CPC title