Mobile device remote control session activity pattern recognition

• US 9,141,509 B2
• Filed: 03/15/2013
• Issued: 09/22/2015
• Est. Priority Date: 03/30/2012
• Status: Active Grant

• Current Assignee: Omnissa, LLC
• Original Assignee: AetherPal, Inc. (Broadcom, Inc.)
• Inventors: Kutchuk, Artun, Palanichamy, Ranjithkumar, Charles, Calvin
• Primary Examiner(s): BUTLER, SARAI E
• Application Number:
  US13/841,877
• Publication Number:
  US 20130262935A1
• Time in Patent Office: 921 Days
• Field of Search: 714/27, 714/25, 714/2
• US Class Current: 1/1
• CPC Class Codes: G06F 11/3438 monitoring of user actions tracking the activity of the user H04L67/535
• CPC Class Codes: H04L 65/40 Support for services or applications
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

Disclosed is a method of updating Care knowledgebase for specific device models with identification of common device problem types and possible corrective actions for specific mobile device models based on the actions performed by the CSR remotely on the device or by the end user on the device during remote control session.

Claims

1. A remote control session activity pattern recognition method, the method comprising:

requesting a remote session with a mobile device;

initiating a recording session of the remote session;

initiating remote session activity pattern matching at a predetermined time; and

presenting an activity pattern with an associated corrective action on a console on a condition that the activity pattern with an associated corrective action exists.

2. The method according to claim 1, wherein at least one of a session initiation request, all activities performed on the mobile device during the remote session, and device screen snapshots and video streams from the mobile device during the remote session is recorded.

3. The method according to claim 2, wherein the activities include at least key clicks, swipes, rotations, application start, application stop, mobile device state, and signal strength.

4. The method according to claim 1, wherein the predetermined time is at a completion of the remote session.

5. The method according to claim 1, wherein the predetermined time is at real-time as activities are being recorded.

6. The method according to claim 4, further comprising:

reading an activity list for each remote session;

filtering the activities that are relevant to actions taken on the mobile device;

classifying a pattern; and

storing a classification with the pattern on a mobile device model corrective action knowledgebase.

7. The method according to claim 6, further comprising:

grouping patterns; and

ranking according to a number of occurrences for a specific mobile device model.

8. The method according to claim 7, further comprising:

analyzing ranked patterns by subject matter experts (SMES); and

updating the mobile device model corrective action knowledgebase for a specific mobile device model and pattern with a problem categorization and an associated correction action entry by the SMES on a condition that a corrective action is identified.

9. The method according to claim 8, further comprising:

transmitting a ranked list of activity patterns with associated corrective actions to the console upon establishment of the remote session.

10. The method according to claim 9, further comprising:

selecting one of common problems that have been observed and classified with associated corrective actions;

retrieving a corrective action from the mobile device model corrective action knowledgebase with a list of actions; and

recording a result on a condition that the associated corrective action is executed on the mobile device.

11. The remote control session activity pattern recognition method according to claim 10, further comprising:

storing a recorded result with the activity to support the ranking of the corrective action.

12. The remote control session activity pattern recognition method according to claim 1, further comprising:

indexing the recorded session based on a given parameter.

13. The remote control session activity pattern recognition method according to claim 12, wherein the given parameter is at least one of device number, device model and time stamp.

14. The remote control session activity pattern recognition method according to claim 1, wherein the remote session is end user initiated.

15. The remote control session activity pattern recognition method according to claim 1, wherein the remote session is console initiated.

16. A system for remote control session activity pattern recognition, comprising:

a console configured to request a remote session with a mobile device;

the console configured to initiate a recording session of the remote session;

the console configured to initiate remote session activity pattern matching at a predetermined time; and

the console configured to present an activity pattern with an associated corrective action on a condition that the activity pattern with an associated corrective action exists.

17. The system according to claim 16, wherein the predetermined time is at a completion of the remote session.

18. The system according to claim 16, wherein the predetermined time is at real-time as activities are being recorded.

19. The system according to claim 16, further comprising:

an activity pattern recognition entity configured to read an activity list for each remote session from a database;

the activity pattern recognition entity configured to filter the activities that are relevant to actions taken on the mobile device;

the activity pattern recognition entity configured to classify a pattern; and

the activity pattern recognition entity configured to store a classification with the pattern on a mobile device model corrective action knowledgebase.

20. The system according to claim 19, further comprising:

the activity pattern recognition entity configured to group patterns; and

the activity pattern recognition entity configured to rank according to a number of occurrences for a specific mobile device model.

21. The system according to claim 20, further comprising:

an identification entity configured to work with subject matter experts (SMES) to analyze ranked patterns and determine the corrective actions; and

the identification entity configured to update the mobile device model corrective action knowledgebase for a specific mobile device model and pattern with a problem categorization and an associated correction action entry by the SMES on a condition that a corrective action is identified.

22. The system according to claim 21, further comprising:

the console configured to transmit a ranked list of activity patterns with associated corrective actions to the mobile device upon establishment of the remote session.

23. The system according to claim 22, further comprising:

the console configured to select one of common problems that have been observed and classified with associated corrective actions;

the console configured to retrieve the associated corrective action from the mobile device model corrective action knowledgebase with a list of actions; and

the console configured to record a result on a condition that the associated corrective action is executed on the mobile device.

24. The system according to claim 23, further comprising:

the console configured to store a recorded result with the activity to support the ranking of the corrective action in the database.

25. The system according to claim 16, wherein the remote session is end user initiated.

26. The system according to claim 16, wherein the remote session is console initiated.