Haptic-based artificial neural network training

• US 9,530,092 B2
• Filed: 11/10/2015
• Issued: 12/27/2016
• Est. Priority Date: 12/18/2013
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Chatterjee, Aveek N., Adoni, Siddique M., Shanmugam, Dhandapani
• Primary Examiner(s): Holmes, Michael B
• Application Number:
  US14/936,971
• Publication Number:
  US 20160063373A1
• Time in Patent Office: 413 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 3/016 Input arrangements with force or tactile feedback as computer generated output to the user
• CPC Class Codes: G06N 3/08 Learning methods

Abstract

In a method for training an artificial neural network based algorithm designed to monitor a first device, a processor receives a first data. A processor determines a first service action recommendation for a first device using the received first data and an artificial neural network (ANN) algorithm. A processor causes a second device to provide haptic feedback using the received first data. A processor receives a second service action recommendation for the first device based on the haptic feedback. A processor adjusts at least one parameter of the ANN algorithm such that the ANN algorithm determines a third service action recommendation for the first device using the received first data, wherein the third service action recommendation is equivalent to the second service action recommendation.

Claims

1. A method for training an algorithm designed to monitor a first device, the method comprising:

receiving a first data;

determining, by one or more processors, a first recommendation for a first device using the received first data and an algorithm;

causing a second device to provide haptic feedback using the received first data;

receiving a second recommendation for the first device based on the haptic feedback;

determining, by the one or more processors, that the second recommendation is different than the first recommendation; and

adjusting, by the one or more processors, at least one parameter of the algorithm based on the determination that the second recommendation is different than the first recommendation.

2. The method of claim 1, wherein the step of receiving the first data comprises receiving the first data from one or more sensors operably affixed to the first device.

3. The method of claim 2, wherein the one or more sensors collect amplitude and frequency data of vibrations of the first device.

4. The method of claim 1, wherein the step of adjusting, by the one or more processors, the at least one parameter of the algorithm based on the determination that the second recommendation is different than the first recommendation comprises:

adjusting, by the one or more processors, the at least one parameter of the algorithm such that the algorithm determines a third recommendation for the first device using the received first data, wherein the third recommendation is equivalent to the second recommendation.

5. The method of claim 1, further comprising the steps of:

receiving a video feed from one or more video recording devices depicting at least a portion of the first device; and

causing the video feed to be displayed.

6. The method of claim 5, wherein the step of receiving a second recommendation for the first device based on the haptic feedback comprises:

receiving the second recommendation for the first device based on the haptic feedback and the video feed.

7. The method of claim 1, wherein the haptic feedback includes generated physical properties to simulate how a surface of a component of the first device feels.

8. The method of claim 1, wherein the at least one parameter includes a function and a weight.

9. A computer program product for training an algorithm designed to monitor a first device, the computer program product comprising:

one or more computer-readable storage devices and program instructions stored on the one or more computer-readable storage devices, the program instructions comprising;

program instructions to receiving a first data;

program instructions to determine a first recommendation for a first device using the received first data and an algorithm;

program instructions to cause a second device to provide haptic feedback using the received first data;

program instructions to receive a second recommendation for the first device based on the haptic feedback;

program instructions to determine that the second service action recommendation is different than the first recommendation; and

program instructions to adjust at least one parameter of the algorithm based on the determination that the second recommendation is different than the first recommendation.

10. The computer program product of claim 9, wherein program instructions to receive the first data comprises program instructions to receive the first data from one or more sensors operably affixed to the first device.

11. The computer program product of claim 10, wherein the one or more sensors collect amplitude and frequency data of vibrations of the first device.

12. The computer program product of claim 9, wherein program instructions to adjust the at least one parameter of the algorithm based on the determination that the second recommendation is different than the first recommendation comprise:

program instructions, stored on the one or more computer-readable storage devices, to adjust the at least one parameter of the algorithm such that the algorithm determines a third recommendation for the first device using the received first data, wherein the third recommendation is equivalent to the second recommendation.

13. The computer program product of claim 9, further comprising:

program instructions, stored on the one or more computer-readable storage devices, to receive a video feed from one or more video recording devices depicting at least a portion of the first device; and

program instructions, stored on the one or more computer-readable storage devices, to cause the video feed to be displayed.

14. The computer program product of claim 13, wherein program instructions to receive a second recommendation for the first device based on the haptic feedback comprises:

program instructions to receive the second recommendation for the first device based on the haptic feedback and the video feed.

15. The computer program product of claim 9, wherein the haptic feedback includes generated physical properties to simulate how a surface of a component of the first device feels.

16. The computer program product of claim 9, wherein the at least one parameter includes a function and a weight.

17. A computer system for training an algorithm designed to monitor a first device, the computer system comprising:

one or more computer processors, one or more computer-readable storage media, and program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising;

program instructions to receiving a first data;

program instructions to determine a first recommendation for a first device using the received first data and an algorithm;

program instructions to cause a second device to provide haptic feedback using the received first data;

program instructions to receive a second recommendation for the first device based on the haptic feedback;

program instructions to determine that the second recommendation is different than the first recommendation; and

program instructions to adjust at least one parameter of the algorithm based on the determination that the second recommendation is different than the first recommendation.

18. The computer system of claim 17, wherein program instructions to receive the first data comprises program instructions to receive the first data from one or more sensors operably affixed to the first device.

19. The computer system of claim 18, wherein the one or more sensors collect amplitude and frequency data of vibrations of the first device.

20. The computer system of claim 17, wherein program instructions to adjust the at least one parameter of the algorithm based on the determination that the second recommendation is different than the first recommendation comprise:

program instructions, stored on the computer-readable storage media for execution by at least one of the one or more processors, to adjust the at least one parameter of the algorithm such that the algorithm determines a third recommendation for the first device using the received first data,

wherein the third recommendation is equivalent to the second recommendation.