IP Library Granted Patent US 12,283,144
Granted Patent B2
US 12,283,144 · App. 17/532,815 · Granted Apr 22, 2025

System to evaluate and manage people entering a building based on infection risk data, environmental data, and building entrant health data

Inventors: Eamonn Jerry O'Toole (Ballincollig, IE); Ronan Fineen Hennessy (Carrigaline, IE); Róisín Ann O'Brien (Glanmire, IE)
Assignee: TYCO FIRE & SECURITY GMBH
G07C9/00563G06N7/01G08B7/066G16H40/20G16H50/80
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Quick Facts
Patent No.
US 12,283,144
App. No.
17/532,815
Granted
Apr 22, 2025
Kind
B2
Abstract

A method for providing access into a building is shown. The method includes receiving an indication that a potential building occupant is requesting access into the building. The method includes providing input data into a probabilistic model, the input data comprising current health data of the potential building occupant obtained in response to receiving the indication. The method includes analyzing, via the probabilistic model, relationships between a plurality of weighted variables within the probabilistic model to determine an entry decision for the potential building occupant, wherein each of the plurality of weighted variables are representative of subsets of the input data. The method includes, in response to the entry decision permitting the building occupant to enter the building, providing a control signal to a security system to permit access to the building for the building occupant.

Claims (70)

1. A method for providing access into a building, the method comprising:

receiving an indication that a potential building occupant is requesting access into the building;

providing input data into a probabilistic model, the input data comprising current health data of the potential building occupant obtained in response to receiving the indication;

analyzing, via the probabilistic model, relationships between a plurality of variables within the probabilistic model to determine an entry decision for the potential building occupant, wherein each of the plurality of variables are representative of subsets of the input data;

in response to the entry decision permitting the potential building occupant to enter the building, determining a testing center within the building to send the potential building occupant;

providing audible or visual signals within the building to guide the potential building occupant to the testing center; and

in response to determining that the potential building occupant has tested negative for a contagious disease, providing a control signal to a security system to permit access to the building for the potential building occupant.

2. The method of claim 1 , wherein analyzing the relationships between the plurality of variables within the probabilistic model comprises:

determining the subsets of the input data and dependencies between the subsets of the input data, wherein the plurality of variables represent the subsets of the input data and the relationships between the plurality of variables represent the dependencies between the subsets of the input data;

determining a joint probability distribution between two or more of the plurality of variables;

using the joint probability distribution to determine a probability of the potential building occupant having an infectious disease; and

determining the entry decision for the potential building occupant.

3. The method of claim 1 , wherein:

the input data further comprises infectious risk data and profile data from a profile associated with the potential building occupant; and

the subsets of the input data include at least one of local infection rate, contact tracing status, vaccination status, or temperature.

4. The method of claim 1 , wherein:

the probabilistic model is a Bayesian network model; and

the plurality of variables are each weighted based on a likelihood that each of the plurality of variables would affect a probability of the potential building occupant having an infectious disease.

5. The method of claim 1 , wherein the method further comprises:

in response to the entry decision permitting the potential building occupant to enter the building, determining a location within the building to send the potential building occupant; and

providing audible or visual signals within the building to guide the potential building occupant to the location; or

providing instructions to a mobile device of the potential building occupant via a mobile application to guide the potential building occupant to the location.

6. The method of claim 1 , wherein receiving the indication that the potential building occupant is requesting access into the building comprises receiving a request from the potential building occupant via a mobile application to enter the building.

7. A controller for providing access into a building, the controller comprising a processing circuit comprising one or more processors and memory, the memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

receiving an indication that a potential building occupant is requesting access into the building;

providing input data into a probabilistic model, the input data comprising current health data of the potential building occupant obtained in response to receiving the indication;

analyzing, via the probabilistic model, relationships between a plurality of variables within the probabilistic model to determine an entry decision for the potential building occupant, wherein each of the plurality of variables are representative of subsets of the input data, wherein analyzing the relationships between the plurality of variables within the probabilistic model comprises:

determining the subsets of the input data and dependencies between the subsets of the input data, wherein the plurality of variables represent the subsets of the input data and the relationships between the plurality of variables represent the dependencies between the subsets of the input data;

determining a joint probability distribution between two or more of the plurality of variables;

using the joint probability distribution to determine a probability of the potential building occupant having an infectious disease;

determining the entry decision for the potential building occupant; and

in response to the entry decision permitting the potential building occupant to enter the building, providing a control signal to a security system to permit access to the building for the potential building occupant.

8. The controller of claim 7 , wherein:

the input data further comprises infectious risk data and profile data from a profile associated with the potential building occupant; and

the subsets of the input data include at least one of local infection rate, contact tracing status, vaccination status, or temperature.

9. The controller of claim 7 , wherein:

the probabilistic model is a Bayesian network model; and

the plurality of variables are each weighted based on a likelihood that each of the of plurality of variables would affect a probability of the potential building occupant having an infectious disease.

10. The controller of claim 7 , the processing circuit is further configured to:

in response to the entry decision permitting the potential building occupant to enter the building, determining a location within the building to send the potential building occupant; and

providing audible or visual signals within the building to guide the potential building occupant to the location; or

providing instructions to a mobile device of the potential building occupant via a mobile application to guide the potential building occupant to the location.

11. The controller of claim 7 , wherein the processing circuit is further configured to:

in response to the entry decision permitting the potential building occupant to enter the building, determining a testing center within the building to send the potential building occupant;

providing audible or visual signals within the building to guide the potential building occupant to the testing center; and

in response to determining that the potential building occupant has tested negative for a contagious disease, providing access to the building for the potential building occupant.

12. The controller of claim 7 , wherein receiving the indication that the potential building occupant is requesting access into the building comprises receiving a request from the potential building occupant via a mobile application to enter the building.

13. One or more non-transitory computer readable media having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to implement operations comprising

receiving an indication that a potential building occupant is requesting access into a building;

providing input data into a probabilistic model, the input data comprising current health data of the potential building occupant obtained in response to receiving the indication;

analyzing, via the probabilistic model, relationships between a plurality of variables within the probabilistic model to determine an entry decision for the potential building occupant, wherein each of the plurality of variables are representative of subsets of the input data; and

in response to the entry decision permitting the potential building occupant to enter the building:

providing a control signal to a security system to permit access to the building for the potential building occupant;

determining a testing center within the building to send the potential building occupant;

providing audible or visual signals within the building to guide the potential building occupant to the testing center; and

in response to determining that the potential building occupant has tested negative for a contagious disease, providing a control signal to a security system to permit access to the building for the potential occupant.

14. The media of claim 13 , wherein analyzing the relationships between the plurality of variables within the probabilistic model comprises:

determining the subsets of the input data and dependencies between the subsets of the input data, wherein the plurality of variables represent the subsets of the input data and the relationships between the plurality of variables represent the dependencies between the subsets of the input data;

determining a joint probability distribution between two or more of the plurality of variables;

using the joint probability distribution to determine a probability of the potential building occupant having an infectious disease; and

determining the entry decision for the potential building occupant.

15. The media of claim 13 , wherein:

the input data further comprises infectious risk data and profile data from a profile associated with the potential building occupant; and

the subsets of the input data include at least one of local infection rate, contact tracing status, vaccination status, or temperature.

16. The media of claim 13 , wherein:

the probabilistic model is a Bayesian network model; and

the plurality of variables are each weighted based on a likelihood that each of the plurality of variables would affect a probability of the potential building occupant having an infectious disease.

17. The media of claim 13 , wherein the one or more processors are further configured to,

in response to determining that the potential building occupant has tested negative for a contagious disease, providing access to the building for the potential building occupant.

18. The media of claim 13 , wherein receiving the indication that the potential building occupant is requesting access into the building comprises receiving a request from the potential building occupant via a mobile application to enter the building.

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 Jan 4, 2022
From: O'TOOLE, EAMONN JERRY; HENNESSY, RONAN FINEEN; O'BRIEN, RÓISÍN ANN
To: JOHNSON CONTROLS TYCO IP HOLDINGS LLP
Reel/Frame 058540/0212 →
Continuity (1)
Related Publication 20230162546A1 · May 25, 2023
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