Inferring placement of mobile electronic devices

• US 9,244,888 B2
• Filed: 03/15/2013
• Issued: 01/26/2016
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Zhigu Holdings Limited
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Bernheim Brush, Alice Jane, Saponas, T. Scott, Wiese, Jason
• Primary Examiner(s): Hong, Dung
• Application Number:
  US13/841,221
• Publication Number:
  US 20140274159A1
• Time in Patent Office: 1,047 Days
• Field of Search: 455/550.1, 455/418, 455/414.1, 455/411, 455/456.1, 455/456.3, 455/566, 702/127
• US Class Current: 1/1
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: H04M 1/72412 using two-way short-range wireless interfaces
• CPC Class Codes: H04M 1/72454 according to context-related or environment-related conditions
• 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 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

A “Placement Detector” enables handheld or mobile electronic devices such as phones, media players, tablets, etc., to infer their current position or placement. Placement inference is performed by evaluating one or more sensors associated with the device relative to one or more trained probabilistic models to infer device relative to a user. Example placement inferences include, but are not limited to, inferring whether the device is currently in a user'"'"'s pocket, in a user'"'"'s purse (or other carrying bag or backpack), in a closed area such as a drawer or box, in an open area such as on a table, indoors, outdoors, etc. These types of placement inferences facilitate a wide range of automated user-device interactions, including, but not limited to, placement-dependent notifications, placement-dependent responses to various inputs, prevention of inadvertent “pocket dialing,” prevention of inadvertent power cycling of devices, lost or misplaced device location assistance, etc.

Claims

1. A mobile electronic device, comprising:

a display screen;

one or more sensors;

one or more trained sensor-based probabilistic placement models;

in response to an inference as to whether the mobile electronic device is currently on a user'"'"'s person, separately illuminating each of a plurality of different sections of the display screen, each separate illumination causing one of the plurality of different sections of the display screen to emit light while each of the other different sections are not emitting light;

applying one or more of the sensors to capture separate reflected light inputs for each of the separate illuminations;

a sensor evaluation module for evaluating the reflected light inputs relative to one or more of the probabilistic models to probabilistically infer whether the mobile electronic device is in an enclosed space; and

a placement response module for automatically initiating one or more actions in response to the inferred device placement.

2. The mobile electronic device of claim 1 further comprising an input evaluation module for evaluating sensors available to the mobile electronic device, and selecting one or more of the available sensors to provide input to the sensor evaluation module.

3. The mobile electronic device of claim 1 further comprising evaluating reflected inputs received from one or more of the sensors to perform a probabilistic inference of device placement relative to a user.

4. The mobile electronic device of claim 3 wherein the probabilistic inference of device placement comprises a determination as to whether the mobile electronic device is within a user'"'"'s pocket.

5. The mobile electronic device of claim 4 wherein a capacitive sensor array associated with the mobile electronic device is used to measure a capacitive signal generated in response to near contact with the body of a user through material lining the pocket positioned between the capacitive sensor array and the body of the user.

6. The mobile electronic device of claim 3 wherein the probabilistic inference of device placement comprises a determination as to whether the mobile electronic device is within a user'"'"'s carrying bag.

7. The mobile electronic device of claim 3 further comprising automatically preventing call initiation when the inferred device placement is a user'"'"'s pocket or carrying bag.

8. The mobile electronic device of claim 1 wherein the sensors include one or more of a proximity sensor, a light sensor, a capacitive sensor array, and a multi-spectral sensor.

9. The mobile electronic device of claim 1 wherein the mobile electronic device is a carrying case for holding a mobile computing device.

10. A computer-implemented process, comprising using a computing device to perform process actions for:

in response to an automated inference as to whether the computing device is currently associated with a user'"'"'s person, receiving sensor data, including data from reflected light resulting from sequential illumination of each of a plurality of different areas of a display screen, from one or more sensors associated with the computing device;

each sequential illumination causing one of the plurality of different areas of the display screen to emit light while each of the other different areas are not emitting light;

evaluating the sensor data relative to one or more trained probabilistic models to automatically infer whether a current computing device placement is within an enclosed space; and

initiating one or more actions in response to the inferred computing device placement.

11. The computer-implemented process of claim 10 wherein the automatic inference of computing device placement further comprises a determination of computing device placement relative to a user.

12. The computer-implemented process of claim 10 wherein the automatic inference of computing device placement comprises a determination as to whether the computing device is within a user'"'"'s pocket.

13. The computer-implemented process of claim 12 wherein a capacitive sensor array associated with the computing device is used to measure a capacitive signal generated in response to near contact with the body of a user through material lining the pocket positioned between the capacitive sensor array and the body of the user.

14. The computer-implemented process of claim 10 wherein the computing device is a phone and further comprising automatically preventing call initiation when the inferred computing device placement is an enclosed space.

15. The computer-implemented process of claim 10 wherein the computing device is a carrying case for holding other objects.

16. A computer-readable storage device having computer executable instructions stored therein, said instructions causing a computing device to execute a method comprising:

in response to an automated inference as to whether the computing device is currently associated with a user'"'"'s person, receiving sensor data, including data from reflected light resulting from separate illumination of different areas of a display screen of the computing device, from one or more sensors associated with the computing device;

each separate illumination causing one of the plurality of different areas of the display screen to emit light while each of the other different areas are not emitting light;

evaluating the sensor data relative to one or more trained probabilistic models to automatically infer whether a current computing device placement is within an enclosed space; and

initiating one or more predefined actions in response to the inferred computing device placement.

17. The computer-readable storage device of claim 16 wherein the automatic inference of computing device placement further comprises a determination of computing device placement relative to a user.

18. The computer-readable storage device of claim 17 wherein the automatic inference of computing device placement comprises a determination as to whether the computing device is within a user'"'"'s pocket.

19. The computer-readable storage device of claim 18 wherein a capacitive sensor array associated with the computing device is used to measure a capacitive signal generated in response to near contact with the body of a user through material lining the pocket positioned between the capacitive sensor array and the body of the user.

20. The computer-readable storage device of claim 16 wherein the computing device is a phone and further comprising automatically preventing call initiation when the inferred computing device placement is an enclosed space.