Detecting driving and modifying access to a user device

• US 10,469,305 B2
• Filed: 11/26/2018
• Issued: 11/05/2019
• Est. Priority Date: 10/13/2016
• Status: Active Grant

• Current Assignee: AirWatch LLC (Broadcom, Inc.)
• Original Assignee: AirWatch LLC (Broadcom, Inc.)
• Inventors: Xuan, Chaoting, Chawla, Ravish, Wang, Jianling, Tse, Kar Fai
• Primary Examiner(s): Bui, Jonathan A
• Application Number:
  US16/199,688
• Publication Number:
  US 20190109758A1
• Time in Patent Office: 344 Days
• CPC Class Codes: G06F 3/0481 based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
• CPC Class Codes: H04L 41/046 comprising network management agents or mobile agents therefor
• CPC Class Codes: H04L 41/22 comprising specially adapted graphical user interfaces [GUI]
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04M 1/673 the user being required to key in a code
• CPC Class Codes: H04M 1/72463 to restrict the functionality of the device
• CPC Class Codes: H04M 1/724631 by limiting the access to the user interface, e.g. locking a touch-screen or a keypad
• CPC Class Codes: H04M 2250/10 including a GPS signal receiver
• CPC Class Codes: H04M 2250/12 including a sensor for measuring a physical value, e.g. temperature or motion telephones including GPS signal receivers H04M2250/10
• CPC Class Codes: H04W 12/08 Access security
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/027 using movement velocity, acceleration information
• CPC Class Codes: H04W 4/40 for vehicles, e.g. vehicle-to-pedestrians [V2P]

Abstract

Systems and methods are included for detecting driving based on user-specific models for driving detection, and restricting access to an application of the user device while a user is driving. A management agent installed on the user device can collect data from sensors in a user device and provide the data to a management server, which can build a user-specific model for driving detection for that user. The management agent can then use that user-specific model for detecting when the user is driving. When the agent determines that the user is driving, it can enforce a driving policy that limits access to applications and delay or modify notifications generated by applications.

Claims

1. A method for detecting driving using user-specific models for driving detection, comprising:

collecting sensor data and user-interaction data from a user device of a first user, the user-interaction data reflecting the first user'"'"'s interaction with a graphical user interface (GUI) of the user device;

training a first model, at a server remote from the user device, using the sensor data and user-interaction data, wherein training comprises modifying the first model according to whether the first model correctly predicts that the first user is driving;

storing the first model at the server, wherein the first model is different than a second model trained for a second user; and

sending the first model from the server to the user device, for use when the first user is logged into the user device, wherein the user device detects that the first user is driving by using the first model to analyze data collected from the user device.

2. The method of claim 1, further comprising:

determining a processed feature at the user device; and

providing information associated with the processed feature as an input to the first model.

3. The method of claim 1, further comprising determining a calibrated orientation of the user device based on at least data received from an accelerometer and gyroscope of the first user device.

4. The method of claim 1, wherein correctly predicting that the first user is driving is determined by prompting the first user with a GUI element that requires the first user'"'"'s interaction.

5. The method of claim 1, wherein the first model distinguishes between the first user driving a vehicle and the first user being a passenger in the vehicle.

6. The method of claim 1, wherein the first model is further trained at the user device in an instance in which the first model correctly predicts that the first user is driving.

7. The method of claim 1, further comprising enforcing a driving mode at the first user device in an instance in which driving is detected.

8. A non-transitory, computer-readable medium containing instructions that, when executed by a hardware-based processor of a computing device, performs stages for detecting driving using user-specific models for driving detection, the stages comprising:

collecting sensor data and user-interaction data from a user device of a first user, the user-interaction data reflecting the first user'"'"'s interaction with a graphical user interface (GUI) of the user device;

training a first model, at a server remote from the user device, using the sensor data and user-interaction data, wherein training comprises modifying the first model according to whether the first model correctly predicts that the first user is driving;

storing the first model at the server, wherein the first model is different than a second model trained for a second user; and

sending the first model from the server to the user device, for use when the first user is logged into the user device, wherein the user device detects that the first user is driving by using the first model to analyze data collected from the user device.

9. The non-transitory, computer-readable medium of claim 8, the stages further comprising:

determining a processed feature at the user device; and

providing information associated with the processed feature as an input to the first model.

10. The non-transitory, computer-readable medium of claim 8, the stages further comprising determining a calibrated orientation of the user device based on at least data received from an accelerometer and gyroscope of the first user device.

11. The non-transitory, computer-readable medium of claim 8, wherein correctly predicting that the first user is driving is determined by prompting the first user with a GUI element that requires the first user'"'"'s interaction.

12. The non-transitory, computer-readable medium of claim 8, wherein the first model distinguishes between the first user driving a vehicle and the first user being a passenger in the vehicle.

13. The non-transitory, computer-readable medium of claim 8, wherein the first model is further trained at the user device in an instance in which the first model correctly predicts that the first user is driving.

14. The non-transitory, computer-readable medium of claim 8, the stages further comprising enforcing a driving mode at the first user device in an instance in which driving is detected.

15. A system for detecting driving using user-specific models for driving detection, comprising:

a non-transitory, computer-readable medium that contains instructions; and

a hardware-based processor of a computing device that executes the instructions to perform stages comprising;

collecting sensor data and user-interaction data from a user device of a first user, the user-interaction data reflecting the first user'"'"'s interaction with a graphical user interface (GUI) of the user device;

training a first model, at a server remote from the user device, using the sensor data and user-interaction data, wherein training comprises modifying the first model according to whether the first model correctly predicts that the first user is driving;

storing the first model at the server, wherein the first model is different than a second model trained for a second user; and

sending the first model from the server to the user device, for use when the first user is logged into the user device, wherein the user device detects that the first user is driving by using the first model to analyze data collected from the user device.

16. The system of claim 15, the stages further comprising:

determining a processed feature at the user device; and

providing information associated with the processed feature as an input to the first model.

17. The system of claim 15, the stages further comprising determining a calibrated orientation of the user device based on at least data received from an accelerometer and gyroscope of the first user device.

18. The system of claim 15, wherein correctly predicting that the first user is driving is determined by prompting the first user with a GUI element that requires the first user'"'"'s interaction.

19. The system of claim 15, wherein the first model distinguishes between the first user driving a vehicle and the first user being a passenger in the vehicle.

20. The system of claim 15, wherein the first model is further trained at the user device in an instance in which the first model correctly predicts that the first user is driving.