IP Library › Granted Patent US 12,591,835
Granted Patent B2
US 12,591,835 · App. 18/544,182 · Granted Mar 31, 2026

Building system with building health recommendations

Inventors: Ravindra Ramanand Warake (Pune, IN); Shawn D. Schubert (Oak Creek, WI); Vineet Binodshanker Sinha (Brookfield, WI); Joseph S. Stangarone (Milwaukee, WI); Nicole A. Madison (Milwaukee, WI); Kerry M. Bell (Mukwonago, WI)
Assignee: TYCO FIRE & SECURITY GMBH
G06Q10/0639G05B19/41845G05B19/41855G06Q10/06315
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Quick Facts
Patent No.
US 12,591,835
App. No.
18/544,182
Filed
Dec 18, 2023
Granted
Mar 31, 2026
Kind
B2
Art Unit
3624
USPC
705/7.38
Abstract

A building system of a building including one or more storage devices storing instructions thereon that, when executed by one or more processors, cause the one or more processors to generate one or more recommendations for improving one or more building scores, the one or more recommendations including a prediction of an increase to a level of the one or more building scores or a decrease to the level of the one or more building scores. The instructions cause the one or more processors to cause the display device of the user device of the user to display the one or more recommendations and receive, via the display device, a selection of one recommendation of the one or more recommendations via the display device from the user and operate the one or more building systems based on one or more operating settings of the one recommendation.

Claims (109)

1 . A building system of a building including one or more storage devices storing instructions thereon that, when executed by one or more processors, cause the one or more processors to:

receive building data from one or more building systems of the building;

determine, responsive to receipt of the building data, building scores of the building including at least two of:

a resource health score indicating a consumption of one or more resources by the one or more building systems of the building during operation;

an occupant health score indicating a comfort or wellbeing of occupants in the building served by the one or more building systems as a result of the operation; or

a system health score indicating a health of the one or more building systems that serve the building as a result of the operation;

transmit one or more first signals to cause a display device to display a user interface including the building scores of the building;

execute a machine learning model to generate a plurality of recommendations to improve one or more scores of the building scores of the building, wherein the machine learning model generates the plurality of recommendations by:

predicting impacts on the building scores of the building predicted to result from operating the one or more building systems using a plurality of different control settings corresponding to the plurality of recommendations;

generating a first recommendation of the plurality of recommendations that prioritizes improving a first score selected from the resource health score, the occupant health score, and the system health score based on the impacts predicted by the machine learning model;

generating a second recommendation of the plurality of recommendations that prioritizes improving a second score selected from the resource health score, the occupant health score, and the system health score based on the impacts predicted by the machine learning model, wherein the second score is different from the first score; and

generating a third recommendation of the plurality of recommendations that balances improving the first score and the second score based on the impacts predicted by the machine learning model;

transmit, responsive to generation of the plurality of recommendations, one or more second signals to cause the display device to update the user interface to include a plurality of selectable elements that correspond to the plurality of recommendations;

receive, responsive to transmission of the one or more second signals, an indication of a selection of a first selectable element of the plurality of selectable elements, the first selectable element of the plurality of selectable elements corresponding to a selected recommendation of the plurality of recommendations; and

operate, responsive to receipt of the indication, the one or more building systems in accordance with control settings corresponding to the selected recommendation, wherein operating the one or more building systems comprises the one or more building systems automatically causing a system to change an environmental condition of the building using a setpoint for the environmental condition defined by the control settings corresponding to the selected recommendation, causing the one or more building systems to affect one or more of the resource health score, the occupant health score, or the system health score as a result of affecting the environmental condition.

2 . The building system of claim 1 , wherein the instructions further cause the one or more processors to:

retrieve, from a cloud system, a digital twin that represents a first building system of the one or more building systems of the building; and

cause, responsive to retrieval of the digital twin, the digital twin to:

ingest one or more portions of the building data that corresponds to the first building system of the one or more building systems of the building;

ingest at least one building score of the building scores of the building that corresponds to the first building system; and

generate, responsive to ingestion of the one or more portions of the building data and the at least one building score of the building scores of the building, one or more enriched events to distribute across the cloud system.

3 . The building system of claim 1 , wherein the instructions further cause the one or more processors to:

determine, responsive to operation of the one or more building systems, an actual impact on the building scores of the building that resulted from implementation of the selected recommendation of the plurality of recommendations;

compare the impacts predicted by the machine learning model with the actual impact on the building scores of the building to determine one or more differences; and

retrain the machine learning model based on the one or more differences.

4 . The building system of claim 3 , wherein the instructions further cause the one or more processors to:

receive, responsive to retraining the machine learning model, indications of selections of one or more second selectable elements of the plurality of selectable elements that correspond to one or more second selected recommendations of the plurality of recommendations; and

retrain, responsive to receipt of the indications, the machine learning model to generate subsequent recommendations that reflect the one or more second selected recommendations of the plurality of recommendations.

5 . The building system of claim 1 , wherein the instructions further cause the one or more processors to:

detect, responsive to operation of the one or more building systems, an occurrence of a predetermined condition of the building;

execute one or more recommendations of the plurality of recommendations to address the occurrence of the predetermined condition of the building; and

transmit one or more third signals to cause the display device to update the user interface to indicate execution of the one or more recommendations.

6 . The building system of claim 5 , wherein the instructions further cause the one or more processors to:

receive, responsive to transmission of the one or more third signals, an indication to adjust one or more parameters associated with the one or more recommendations; and

update a database, stored in the one or more storage devices, to adjust the one or more parameters associated with the one or more recommendations.

7 . The building system of claim 1 , wherein the instructions further cause the one or more processors to:

receive second building data from the one or more building systems of the building;

detect, responsive to receipt of the second building data, a change in one or more variables used by the machine learning model to generate at least one recommendation of the plurality of recommendations;

execute, based on the change in the one or more variables, the machine learning model to update the at least one recommendation of the plurality of recommendations; and

transmit, responsive to the at least one recommendation of the plurality of recommendations having been updated, one or more third signals to adjust implementation of one or more aspects of the at least one recommendation of the plurality of recommendations.

8 . The building system of claim 1 , wherein the instructions further cause the one or more processors to:

receive, responsive to transmission of the one or more second signals, a second indication of a selection of a second selectable element of the plurality of selectable elements, the second selectable element of the plurality of selectable elements corresponding to a second selected recommendation of the plurality of recommendations; and

transmit, responsive to receipt of the second indication, one or more third signals to cause the display device to update the user interface to include a graphical representation that indicates an impact on the building scores of the building based on implementation of the second selected recommendation of the plurality of recommendations.

9 . The building system of claim 1 , wherein the machine learning model is stored by a cloud system, and wherein the instructions further cause the one or more processors to:

retrieve the machine learning model from the cloud system.

10 . A method, comprising:

receiving, by one or more processing circuits, from one or more building systems of a building, building data;

determining, by the one or more processing circuits responsive to receiving the building data, building scores of the building including at least two of:

a resource health score indicating a consumption of one or more resources by the one or more building systems of the building during operation;

an occupant health score indicating a comfort or wellbeing of occupants in the building served by the one or more building systems as a result of the operation; or

a system health score indicating a health of the one or more building systems that serve the building as a result of the operation;

transmitting, by the one or more processing circuits, one or more first signals to cause a display device to display a user interface including the building scores of the building;

executing, by the one or more processing circuits, a machine learning model to generate a plurality of recommendations to improve one or more scores of the building scores of the building, wherein the machine learning model generates the plurality of recommendations by:

predicting impacts on the building scores of the building predicted to result from operating the one or more building systems using a plurality of different control settings corresponding to the plurality of recommendations;

generating a first recommendation of the plurality of recommendations that prioritizes improving a first score selected from the resource health score, the occupant health score, and the system health score based on the impacts predicted by the machine learning model;

generating a second recommendation of the plurality of recommendations that prioritizes improving a second score selected from the resource health score, the occupant health score, and the system health score based on the impacts predicted by the machine learning model, wherein the second score is different from the first score; and

generating a third recommendation of the plurality of recommendations that balances improving the first score and the second score based on the impacts predicted by the machine learning model;

transmitting, by the one or more processing circuits responsive to generation of the plurality of recommendations, one or more second signals to cause the display device to update the user interface to include a plurality of selectable elements that correspond to the plurality of recommendations;

receiving, by the one or more processing circuits responsive to transmission of the one or more second signals, an indication of a selection of a first selectable element of the plurality of selectable elements, the first selectable element of the plurality of selectable elements corresponding to a selected recommendation of the plurality of recommendations; and

operating, by the one or more processing circuits responsive to receipt of the indication, the one or more building systems in accordance with control settings corresponding to the selected recommendation, wherein operating the one or more building systems comprises the one or more building systems automatically causing a system to change an environmental condition of the building using a setpoint for the environmental condition defined by the control settings corresponding to the selected recommendation, causing the one or more building systems to affect one or more of the resource health score, the occupant health score or the system health score as a result of affecting the environmental condition.

11 . The method of claim 10 , further comprising:

retrieving, by the one or more processing circuits from a cloud system, a digital twin that represents a first building system of the one or more building systems of the building; and

causing, by the one or more processing circuits responsive to retrieval of the digital twin, the digital twin to:

ingest one or more portions of the building data that corresponds to the first building system of the one or more building systems of the building;

ingest at least one building score of the building scores of the building that corresponds to the first building system; and

generate, responsive to ingestion of the one or more portions of the building data and the at least one building score of the building scores of the building, one or more enriched events to distribute across the cloud system.

12 . The method of claim 10 , further comprising:

determining, by the one or more processing circuits, responsive to operating the one or more building systems, an actual impact on the building scores of the building that resulted from implementation of the selected recommendation of the plurality of recommendations;

comparing, by the one or more processing circuits, the impacts predicted by the machine learning model with the actual impact on the building scores of the building to determine one or more differences; and

retraining, by the one or more processing circuits, the machine learning model based on the one or more differences.

13 . The method of claim 12 , further comprising:

receiving, by the one or more processing circuits, responsive to retraining the machine learning model, indications of selections of one or more second selectable elements of the plurality of selectable elements that correspond to one or more second selected recommendations of the plurality of recommendations; and

retraining, by the one or more processing circuits, responsive to receipt of the indications, the machine learning model to generate subsequent recommendations that reflect the one or more second selected recommendations of the plurality of recommendations.

14 . The method of claim 10 , further comprising:

detecting, by the one or more processing circuits, responsive to operating the one or more building systems, an occurrence of a predetermined condition of the building;

executing, by the one or more processing circuits, one or more recommendations of the plurality of recommendations to address the occurrence of the predetermined condition of the building; and

transmitting, by the one or more processing circuits, one or more third signals to cause the display device to update the user interface to indicate execution of the one or more recommendations.

15 . The method of claim 14 , further comprising:

receiving, by the one or more processing circuits, responsive to transmission of the one or more third signals, an indication to adjust one or more parameters associated with the one or more recommendations; and

updating, by the one or more processing circuits, a database, stored in one or more storage devices, to adjust the one or more parameters associated with the one or more recommendations.

16 . The method of claim 10 , further comprising:

receiving, by the one or more processing circuits, second building data from the one or more building systems of the building;

detecting, by the one or more processing circuits responsive to receipt of the second building data, a change in one or more variables used by the machine learning model to generate at least one recommendation of the plurality of recommendations;

executing, by the one or more processing circuits, based on the change in the one or more variables, the machine learning model to update the at least one recommendation of the plurality of recommendations; and

transmitting, by the one or more processing circuits, responsive to updating the at least one recommendation of the plurality of recommendations, one or more third signals to adjust implementation of one or more aspects of the at least one recommendation of the plurality of recommendations.

17 . The method of claim 10 , further comprising:

receiving, by the one or more processing circuits, responsive to transmission of the one or more second signals, a second indication of a selection of a second selectable element of the plurality of selectable elements, the second selectable element of the plurality of selectable elements corresponding to a second selected recommendation of the plurality of recommendations; and

transmitting, by the one or more processing circuits, responsive to receipt of the second indication, one or more third signals to cause the display device to update the user interface to include a graphical representation that indicates an impact on the building scores of the building based on implementation of the second selected recommendation of the plurality of recommendations.

18 . One or more non-transitory storage media having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to:

receive building data from one or more building systems of a building;

determine, responsive to receipt of the building data, building scores of the building including at least two of:

a resource health score indicating a consumption of one or more resources by the one or more building systems of the building during operation;

an occupant health score indicating a comfort or wellbeing of occupants in the building served by the one or more building systems as a result of the operation; or

a system health score indicating a health of the one or more building systems that serve the building as a result of the operation;

transmit one or more first signals to cause a display device to display a user interface including the building scores of the building;

execute a machine learning model to generate a plurality of recommendations to improve one or more scores of the building scores of the building, wherein the machine learning model generates the plurality of recommendations by:

predicting impacts on the building scores of the building predicted to result from operating the one or more building systems using a plurality of different control settings corresponding to the plurality of recommendations;

generating a first recommendation of the plurality of recommendations that prioritizes improving a first score selected from the resource health score, the occupant health score, and the system health score based on the impacts predicted by the machine learning model;

generating a second recommendation of the plurality of recommendations that prioritizes improving a second score selected from the resource health score, the occupant health score, and the system health score based on the impacts predicted by the machine learning model, wherein the second score is different from the first score; and

generating a third recommendation of the plurality of recommendations that balances improving the first score and the second score based on the impacts predicted by the machine learning model;

transmit, responsive to generation of the plurality of recommendations, one or more second signals to cause the display device to update the user interface to include a plurality of selectable elements that correspond to the plurality of recommendations;

receive, responsive to transmission of the one or more second signals, an indication of a selection of a first selectable element of the plurality of selectable elements, the first selectable element of the plurality of selectable elements corresponding to a selected recommendation of the plurality of recommendations; and

operate, responsive to receipt of the indication, the one or more building systems in accordance with control settings corresponding to the selected recommendation, wherein operating the one or more building systems comprises the one or more building systems automatically causing a system to change an environmental condition of the building using a setpoint of the environmental condition defined by the control settings corresponding to the selected recommendation, causing the one or more building systems to affect one or more of the resource health score, the occupant health score, or the system health score as a result of affecting the environmental condition.

19 . The one or more non-transitory storage media of claim 18 , wherein the instructions further cause the one or more processors to:

retrieve, from a cloud system, a digital twin that represents a first building system of the one or more building systems of the building; and

cause, responsive to retrieval of the digital twin, the digital twin to:

ingest one or more portions of the building data that corresponds to the first building system of the one or more building systems of the building;

ingest at least one building score of the building scores of the building that corresponds to the first building system; and

generate, responsive to ingestion of the one or more portions of the building data and the at least one building score of the building scores of the building, one or more enriched events to distribute across the cloud system.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 9, 2024
From: JOHNSON CONTROLS TYCO IP HOLDINGS LLP
To: TYCO FIRE & SECURITY GMBH
Reel/Frame 067056/0552 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 18, 2023
From: WARAKE, RAVINDRA RAMANAND; SCHUBERT, SHAWN D.; SINHA, VINEET BINODSHANKER; STANGARONE, JOSEPH S.; MADISON, NICOLE A.; BELL, KERRY M.
To: JOHNSON CONTROLS TYCO IP HOLDINGS LLP
Reel/Frame 065902/0619 →
Priority Claims (2)
IN 202021035549 · Aug 18, 2020 · national
IN 202121004000 · Jan 29, 2021 · national
Continuity (4)
Continuation 17354565 · Jun 22, 2021
Provisional Application 63113019 · Nov 12, 2020
Related Publication 20240135294A1 · Apr 25, 2024
Related Publication 20240232773A9 · Jul 11, 2024
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