Network device predictive modeling

• US 10,460,243 B2
• Filed: 03/26/2015
• Issued: 10/29/2019
• Est. Priority Date: 12/10/2014
• Status: Active Grant

• Current Assignee: Belkin International Incorporated (Hon Hai Precision Industry Co., Ltd.)
• Original Assignee: Belkin International Incorporated (Hon Hai Precision Industry Co., Ltd.)
• Inventors: Kim, Ryan Yong
• Primary Examiner(s): Chaki, Kakali
• Assistant Examiner(s): Zidanic, Michael
• Application Number:
  US14/670,285
• Publication Number:
  US 20160171374A1
• Time in Patent Office: 1,678 Days
• Field of Search: None
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 2219/2642 Domotique, domestic, home control, automation, smart house
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: H04L 43/16 Threshold monitoring
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46

Abstract

Techniques and systems are provided for predictive modeling based on interactions with a network device. For example, a method may include generating a prediction including a correlation between an interaction with a network device and a context, wherein the interaction is associated with a function performed by the network device. Confidence parameters associated with the prediction can be determined. The prediction can be tested by analyzing received interaction data and contextual data, and the analysis can include determining whether the interaction with the network device occurred in the correlated context. A confidence value can be calculated based on the testing outcome, and can be compared to the confidence parameters. A message relating to modification of the confidence parameters can be transmitted.

Claims

1. A computer-implemented method, comprising:

generating, at a computing device, a prediction including a correlation between an interaction with a network device and a context, wherein the interaction is associated with a function performed by the network device;

determining confidence parameters associated with the prediction;

generating a testing outcome by testing the prediction, wherein testing includes analyzing received interaction data and contextual data, and wherein analyzing includes determining whether the interaction with the network device occurred in the context;

calculating a confidence value based on the testing outcome;

comparing the confidence value to the confidence parameters;

determining that the confidence value does not exceed at least one of the confidence parameters in response to comparing the confidence value to the confidence parameters;

transmitting a message that relates to a modification of the confidence parameters;

receiving, from a user at the computing device, input corresponding to an instruction to modify the confidence parameters;

modifying the confidence parameters based on the input;

comparing the confidence value to the modified confidence parameters;

determining that the confidence value exceeds the modified confidence parameters in response to comparing the confidence value to the modified confidence parameters;

detecting, by the computing device, the context associated with prediction;

transmitting, by the computing device and to the network device, an execution instruction associated with the function of the network device in response to detecting the context associated with the prediction; and

executing, by the network device, the function performed by the network device in response receiving the execution instruction.

2. The computer-implemented method of claim 1, wherein the confidence parameters include a threshold confidence value and a threshold number of observations, wherein the observations correspond to the context occurring.

3. The computer-implemented method of claim 2, wherein comparing the confidence value to the confidence parameters includes determining whether the confidence value has reached the threshold confidence value and determining whether the threshold number of observations has been reached.

4. The computer-implemented method of claim 1, wherein the message is transmitted as part of an initial setup process.

5. The computer-implemented method of claim 1, wherein the message is transmitted in response to determining that the confidence value has not reached a threshold confidence value.

6. The computer-implemented method of claim 1, wherein the message is transmitted in response to:

determining that the confidence value has been reached; and

determining that a threshold number of observations has not been reached.

7. The computer-implemented method of claim 1, wherein modifying the confidence parameters includes transitioning from an initial operational mode to a new operational mode.

8. The computer-implemented method of claim 1, wherein the computing device is the network device, a user device, or a cloud-based device.

9. The computer-implemented method of claim 1, wherein the message further relates to a modification of confidence parameters associated with a different prediction, wherein the different prediction includes a correlation between an interaction with a different network device and a different context.

10. A system, comprising:

a computing device comprising;

one or more processors; and

a non-transitory computer-readable storage medium containing instructions which when executed on the one or more processors, cause the one or more processors to perform operations including;

generating a prediction including a correlation between an interaction with a network device and a context, wherein the interaction is associated with a function performed by the network device;

determining confidence parameters associated with the prediction;

generating a testing outcome by testing the prediction, wherein testing includes analyzing received interaction data and contextual data, and wherein analyzing includes determining whether the interaction with the network device occurred in the context;

calculating a confidence value based on the testing outcome;

comparing the confidence value to the confidence parameters;

determining that the confidence value does not exceed at least one of the confidence parameters in response to comparing the confidence value to the confidence parameters;

transmitting a message that relates to a modification of the confidence parameters;

receiving input corresponding to an instruction to modify the confidence parameters;

modifying the confidence parameters based on the input;

comparing the confidence value to the modified confidence parameters;

determining that the confidence value exceeds the modified confidence parameters in response to comparing the confidence value to the modified confidence parameters;

detecting the context associated with prediction; and

transmitting, to the network device, an execution instruction, the execution instruction configured to direct the network device to execute the function of the network device;

the network device comprising;

one or more processors; and

a non-transitory computer-readable storage medium containing instructions which when executed on the one or more processors, cause the one or more processors to perform operations including;

receiving, from the computing device, the execution instruction associated the function of the network device; and

executing the function performed by the network device in response receiving the execution instruction.

11. The system of claim 10, wherein the confidence parameters include a threshold confidence value and a threshold number of observations, wherein the observations correspond to the context occurring.

12. The system of claim 11, wherein comparing the confidence value to the confidence parameters includes determining whether the confidence value has reached the threshold confidence value and determining whether the threshold number of observations has been reached.

13. The system of claim 10, wherein the message is transmitted as part of an initial setup process.

14. The system of claim 10, wherein the message is transmitted in response to determining that the confidence value has not reached a threshold confidence value.

15. The system of claim 10, wherein the message is transmitted in response to:

determining that the confidence value has been reached; and

determining that a threshold number of observations has not been reached.

16. The system of claim 10, wherein modifying the confidence parameters includes transitioning from an initial operational mode to a new operational mode.

17. The system of claim 10, wherein the computing device is the network device, a user device, or a cloud-based device.

18. The system of claim 10, wherein the message further relates to a modification of confidence parameters associated with a different prediction, wherein the different prediction includes a correlation between an interaction with a different network device and a different context.

19. A non-transitory machine-readable storage medium including instructions that, when execute on one or more processors, cause the one or more processors to perform operations including:

generating a prediction including a correlation between an interaction with a network device and a context, wherein the interaction is associated with a function performed by the network device;

determining confidence parameters associated with the prediction;

generating a testing outcome by testing the prediction, wherein testing includes analyzing received interaction data and contextual data, and wherein analyzing includes determining whether the interaction with the network device occurred in the context;

calculating a confidence value based on the testing outcome;

comparing the confidence value to the confidence parameters;

transmitting a first message that relates to a modification of the confidence parameters;

receiving input corresponding to an instruction to modify the confidence parameters;

modifying the confidence parameters;

calculating an updated confidence value based the testing outcome;

comparing the updated confidence value to the modified confidence parameters;

determining that the updated confidence value exceeds the confidence parameters in response to comparing the updated confidence value to the modified confidence parameters;

transmitting a second message, wherein the second message includes an automation request corresponding to the function performed by the network device;

receiving input indicating approval to automate the function of the network device;

detecting the context associated with the prediction; and

transmitting, to the network device, an execution instruction, wherein the network device, upon receiving the execution instruction, executes the function of the network device.

20. The non-transitory machine-readable storage medium of claim 19, wherein the confidence parameters include a threshold confidence value and a threshold number of observations, wherein the observations correspond to the context occurring.

21. The non-transitory machine-readable storage medium of claim 20, wherein comparing the confidence value to the confidence parameters includes determining whether the confidence value has reached the threshold confidence value and determining whether the threshold number of observations has been reached.

22. The non-transitory machine-readable storage medium of claim 19, wherein the first message is transmitted as part of an initial setup process.

23. The non-transitory machine-readable storage medium of claim 19, wherein the first message is transmitted in response to determining that the confidence value has not reached a threshold confidence value.

24. The non-transitory machine-readable storage medium of claim 19, wherein the first message is transmitted in response to:

determining that the confidence value has been reached; and

determining that a threshold number of observations has not been reached.

25. The non-transitory machine-readable storage medium of claim 19, wherein modifying the confidence parameters includes transitioning from an initial operational mode to a new operational mode.

26. The non-transitory machine-readable storage medium of claim 19, wherein the one or more processors are included within the network device, a user device, or a cloud-based device.

27. The non-transitory machine-readable storage medium of claim 19, wherein the first message further relates to a modification of confidence parameters associated with a different prediction, wherein the different prediction includes a correlation between an interaction with a different network device and a different context.