Environment controller and method for inferring via a neural network one or more commands for controlling an appliance

Patent metadata

Field	Value
Publication number	US-12228891-B2
Application number	US-202217988359-A
Country	US
Kind code	B2
Filing date	Nov 16, 2022
Priority date	Dec 12, 2017
Publication date	Feb 18, 2025
Grant date	Feb 18, 2025

Abstract

Method and environment controller for inferring via a neural network one or more commands for controlling an appliance. A predictive model generated by a neural network training engine is stored by the environment controller. The environment controller receives at least one environmental characteristic value (for example, at least one of a current temperature, current humidity level, current carbon dioxide level, and current room occupancy). The environment controller receives at least one set point (for example, at least one of a target temperature, target humidity level, and target carbon dioxide level). The environment controller executes a neural network inference engine, which uses the predictive model for inferring the one or more commands for controlling the appliance based on the at least one environmental characteristic value and the at least one set point. The environment controller transmits the one or more commands to the controlled appliance.

First claim

What is claimed is:

1. An environment controller, comprising:
a communication interface;
memory for storing a predictive model generated by a neural network training engine, the predictive model comprising weights of a neural network determined by the neural network training engine; and
a processing unit comprising at least one processor for:
receiving via the communication interface a current room occupancy of a room;
receiving via one of the communication interface and a user interface of the environment controller a target temperature for the room;
executing a neural network inference engine, the neural network inference engine implementing a neural network using the predictive model for inferring an output based on inputs, the output comprising one or more command for controlling an appliance, the inputs comprising the current room occupancy and the target temperature; and
transmitting the one or more command to the controlled appliance via the communication interface.

2. The environment controller of claim 1 , wherein the processing unit further receives via the communication interface at least one additional environmental characteristic value; and wherein the inputs of the neural network inference engine further comprise the at least one additional environmental characteristic value.

3. The environment controller of claim 2 , wherein the at least one additional environmental characteristic value comprises at least one of the following: a current temperature, a current humidity level, and a current carbon dioxide (CO2) level.

4. The environment controller of claim 1 , wherein the current room occupancy consists of a determination whether the room is occupied or not, or the current room occupancy consists of a number of persons present in the room.

5. The environment controller of claim 1 , wherein the processing unit further receives via one of the communication interface and the user interface at least one additional set point; and wherein the inputs of the neural network inference engine further comprise the at least one additional set point.

6. The environment controller of claim 5 , wherein the at least one additional set point comprises at least one of the following: a target humidity level and a target CO2 level.

7. The environment controller of claim 1 , wherein the controlled appliance consists of a heating, ventilation, and air-conditioning (HVAC) appliance.

8. The environment controller of claim 1 , wherein the one or more command for controlling the appliance include at least one of the following: a command for controlling a speed of a fan, a command for controlling a pressure generated by a compressor, and a command for controlling a rate of an airflow through a valve.

9. A method for inferring via a neural network one or more command for controlling an appliance, the method comprising:
storing a predictive model generated by a neural network training engine in a memory of an environment controller, the predictive model comprising weights of a neural network determined by the neural network training engine;
receiving by a processing unit of the environment controller via a communication interface of the environment controller a current room occupancy of a room;
receiving by the processing unit via one of the communication interface and a user interface of the environment controller a target temperature for the room;
executing by the processing unit a neural network inference engine, the neural network inference engine implementing a neural network using the predictive model for inferring an output based on inputs, the output comprising the one or more command for controlling the appliance, the inputs comprising the current room occupancy and the target temperature; and
transmitting by the processing unit the one or more command to the controlled appliance via the communication interface.

10. The method of claim 9 , further comprising receiving by the processing unit via the communication interface at least one additional environmental characteristic value; and wherein the inputs of the neural network inference engine further comprise the at least one additional environmental characteristic value.

11. The method of claim 10 , wherein the at least one additional environmental characteristic value comprises at least one of the following: a current temperature, a current humidity level, and a current carbon dioxide (CO2) level.

12. The method of claim 10 , wherein the current room occupancy consists of a determination whether the room is occupied or not, or the current room occupancy consists of a number of persons present in the room.

13. The method of claim 9 , further comprising receiving by the processing unit via one of the communication interface and the user interface at least one additional set point; and wherein the inputs of the neural network inference engine further comprise the at least one additional set point.

14. The method of claim 13 , wherein the at least one additional set point comprises at least one of the following: a target humidity level and a target CO2 level.

15. The method of claim 9 , wherein the controlled appliance consists of a heating, ventilation, and air-conditioning (HVAC) appliance.

16. The method of claim 9 , wherein the one or more command for controlling the appliance include at least one of the following: a command for controlling a speed of a fan, a command for controlling a pressure generated by a compressor, and a command for controlling a rate of an airflow through a valve.

17. A non-transitory computer program product storing instructions executable by a processing unit of an environment controller, the execution of the instructions by the processing unit of the environment controller providing for inferring via a neural network one or more command for controlling an appliance by:
storing a predictive model generated by a neural network training engine in a memory of the environment controller, the predictive model comprising weights of a neural network determined by the neural network training engine;
receiving by the processing unit via a communication interface of the environment controller a current room occupancy of a room;
receiving by the processing unit via one of the communication interface and a user interface of the environment controller a target temperature for the room;
executing by the processing unit a neural network inference engine, the neural network inference engine implementing a neural network using the predictive model for inferring an output based on inputs, the output comprising the one or more command for controlling the appliance, the inputs comprising the current room occupancy and the target temperature; and
transmitting by the processing unit the one or more command to the controlled appliance via the communication interface.

18. The computer program product of claim 17 , wherein the execution of the instructions by the processing unit further provide for receiving by the processing unit via the communication interface at least one additional environmental characteristic value; and wherein the inputs of the neural network inference engine further comprise the at least one additional environmental characteristic value; the at least one additional environmental characteristic value comprising at least one of the following: a current temperature, a current humidity level, and a current carbon dioxide (CO2) level.

19. The computer program product of claim 17 , wherein the execution of the instructions by the processing unit further provide for r

Assignees

• Distech Controls Inc

Inventors

• Gervais Francois
• Masciovecchio Carlo
• Laplante Dominique

Classifications

• G01S17/04

  Systems determining the presence of a target · CPC title

• G06F9/451

  Execution arrangements for user interfaces · CPC title

• G06N3/084

  Backpropagation, e.g. using gradient descent · CPC title

• F24F11/76

  by means responsive to temperature, e.g. bimetal springs · CPC title

• F24F11/62

  characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values · CPC title