Systems and methods for intelligent customization of an automation control service

• US 10,168,676 B2
• Filed: 03/25/2015
• Issued: 01/01/2019
• Est. Priority Date: 04/29/2014
• Status: Active Grant

• Current Assignee: Cox Communications Incorporated (Cox Enterprises Incorporated)
• Original Assignee: Cox Communications Incorporated (Cox Enterprises Incorporated)
• Inventors: Patel, Dipan, Finnerty, Nadine, Shrum, Jr., Edgar V., Goldberg, Andrew, Taylor, Haynes
• Primary Examiner(s): Ali, Mohammad
• Assistant Examiner(s): Sanders, Joshua T
• Application Number:
  US14/668,442
• Publication Number:
  US 20150309491A1
• Time in Patent Office: 1,378 Days
• Field of Search: 700275
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: H04L 12/2803 Home automation networks

Abstract

Aspects of the disclosure relate to intelligent automation control of an environment based at least on intelligence associated with behavior of an operator and/or equipment.

Claims

1. A method for automation control, comprising:

accessing, by a computing system comprising at least one memory device and at least one processor, one or more information streams from a group of agents associated with an operational environment of a physical premises, wherein the group of agents transmits the one or more information streams over one or more network links to a gateway device, further wherein the one or more information streams are indicative of interactivity between the group of agents and one or more automation control assets of the operational environment;

determining, by the computing system and based at least on one of the one or more information streams, intelligence that is indicative of a behavior of an agent of the group of agents with an automation control asset of the one or more automation control assets;

supplying, by the computing system, a recommendation for an automation control service for the operational environment based at least on the determined intelligence; and

transmitting, by the computing system, instructions to hardware that is in electrical communication with the automation control service based upon the recommendation, wherein the instructions regulate operation of the hardware,

wherein determining, by the computing system, the intelligence comprises determining a correlation between events associated with at least one second agent of the group of agents, the at least one second agent being in at least one of (i) a specific control state of a control sequence based at least on the automation control service or (ii) a specific agent state,

wherein the control state comprises a condition of the operational environment, the condition being responsive to implementation of the control sequence, and

wherein an agent state comprises a condition of the at least one second agent responsive to one or more of activities within the operational environment or the control state.

2. The method of claim 1, wherein the supplying comprises supplying a second recommendation for an automation control asset, wherein the second recommendation is configured to regulate operation of at least one agent of the group of agents.

3. The method of claim 2, wherein the second recommendation comprises at least one of a recommendation for a specific control mode of the automation control asset, the specific control mode comprising a configuration of tasks for the at least one agent.

4. The method of claim 1, wherein the supplying comprises supplying a second recommendation for adjusting operation of the agent.

5. The method of claim 1, wherein the recommendation for the automation control service complements an extant automation control service configured to regulate the operational environment.

6. The method of claim 1, wherein determining, by the computing system, the intelligence comprises generating, by the computing system, a model of the behavior based at least on unsupervised learning, wherein the model comprises one or more of statistical Markov model, a neural network model, or a Gaussian mixture model.

7. The method of claim 1, wherein determining, by the computing system, the intelligence comprises generating, by the computing system, a model of the behavior based at least on supervised learning, wherein the model comprises one or more of statistical Bayes model, a neural network model, or regression analysis.

8. The method of claim 1, wherein the determining, by the computing system, the intelligence comprises determining a structure of events associated with the agent, the agent being in a specific control state or a specific agent state, and wherein the structure comprises a predetermined sequence of control tasks or a pattern of activity of the agent.

9. A system, comprising:

at least one memory device having instructions encoded thereon; and

at least one processor coupled to the at least one memory device and configured to execute the instructions and, in response, further configured at least to;

access one or more information streams from a group of agents associated with an operational environment of a physical premises, wherein the group of agents transmits the one or more information streams over one or more network links to a gateway device, further wherein the one or more information streams are indicative of interactivity between the group of agents and one or more automation control assets of the operational environment;

determine intelligence that is indicative of a behavior of an agent of the group of agents with an automation control asset of the one or more automation control assets based at least on one of the one or more information streams;

supply a recommendation for an automation control service for the operational environment based at least on the determined intelligence; and

transmit instructions to hardware that is in electrical communication with the automation control service based upon the recommendation, wherein the instructions regulate operation of the hardware,

wherein to determine the intelligence further comprises to determine a correlation between events associated with at least one second agent of the group of agents, the at least one second agent being in at least one of (i) a specific control state of a control sequence based at least on the automation control service or (ii) a specific agent state,

wherein the control state comprises a condition of the operational environment, the condition being responsive to implementation of the control sequence, and

wherein an agent state comprises a condition of the at least one second agent responsive to one or more of activities within the operational environment or the control state.

10. The system of claim 9, wherein to supply further comprises to supply a second recommendation for an automation control asset, wherein the second recommendation is configured to regulate operation of at least one agent of the group of agents.

11. The system of claim 10, wherein the second recommendation comprises at least one of a recommendation for a specific control mode of the automation control asset, the specific control mode comprising a configuration of tasks for the at least one agent.

12. The system of claim 9, wherein to supply further comprises to supply a second recommendation for adjusting operation of the agent.

13. The system of claim 9, wherein the recommended recommendation for the automation control service complements an extant automation control service configured to regulate the operational environment.

14. The system of claim 9, wherein to determine the intelligence further comprises to generate a model of the behavior based at least on unsupervised learning, wherein the model comprises one or more of statistical Markov model, a neural network model, or a Gaussian mixture model.

15. The system of claim 9, wherein to determine the intelligence further comprises to generate a model of the behavior based at least on supervised learning, wherein the model comprises one or more of statistical Bayes model, a neural network model, or regression analysis.

16. The system of claim 9, wherein to determine the intelligence further comprises to determine a structure of events associated with the agent, the agent being in a specific control state or a specific agent state, and wherein the structure comprises a predetermined sequence of control tasks or a pattern of activity of the agent.