Adjusting mobile device state based on user intentions and/or identity

Patent metadata

Field	Value
Publication number	US-9052896-B2
Application number	US-201213554838-A
Country	US
Kind code	B2
Filing date	Jul 20, 2012
Priority date	Jul 20, 2012
Publication date	Jun 9, 2015
Grant date	Jun 9, 2015

Abstract

In one embodiment, when a computing system is in a first state, a first set of inputs from one or more first sensors is detected. A first sensor value array is generated, and the first value array is fed as input to a first function generated by a first neural network. One or more first output values are calculated based on the first function, and a determination is made based on these first output values if a first action has occurred. If a first action has occurred, a second sensor value array is generated from a second set of inputs from one or more second sensors. The second sensor value array is fed as input to a second function generated by a second neural network. One or more second output values are calculated based on the second function, and the first state is exited based on these second output values.

First claim

What is claimed is:

1. A method comprising, by one or more computing systems:
detecting, while the one or more computing systems is in a first state, a first set of inputs from a plurality of first sensors;
generating a first sensor value array, each of the sensor values in the first sensor value array corresponding to one of the first set of inputs;
feeding the first sensor value array as input to a first function generated by a first neural network;
calculating one or more first output values based at least in part on the first function;
determining, based at least in part on the one or more first output values, if a first action has occurred; and
in response to a determination that the first action has occurred:
polling one or more second sensors for a second set of sensor inputs;
generating a second sensor value array including a second set of sensor values, each of the second set of sensor values corresponding to one of the second set of sensor inputs;
feeding the second sensor value array as input to a second function generated by a second neural network;
calculating one or more second output values based at least in part on the second function; and
based at least in part on the one or more second output values returned by the second function, exiting the first state.

2. The method of claim 1 , wherein the one or more first output values are calculated by a low-power microcontroller; and in response to a determination that the first action has occurred, the micro-controller wakes up a processor from a sleep mode for calculation of the one or more second output values.

3. The method of claim 1 , wherein the first sensors comprise touch sensors.

4. The method of claim 3 , wherein the touch sensors are capacitive.

5. The method of claim 1 , wherein the one or more second sensors comprise:
an accelerometer;
a light sensor; or
a multi-touch display surface.

6. The method of claim 1 , wherein the first state is a locked state.

7. The method of claim 1 , wherein the first action is a grab action.

8. The method of claim 1 , wherein the first and second functions are received from a server.

9. One or more computer-readable non-transitory storage media in one or more computing systems, the media embodying logic that is operable when executed to:
detect, while the one or more computing systems is in a first state, a first set of inputs from a plurality of first sensors;
generate a first sensor value array, each of the sensor values in the first sensor value array corresponding to one of the first set of inputs;
feed the first sensor value array as input to a first function generated by a first neural network;
calculate one or more first output values based at least in part on the first function;
determine, based at least in part on the one or more first output values, if a first action has occurred; and
in response to a determination that the first action has occurred:
poll one or more second sensors for a second set of sensor inputs;
generate a second sensor value array including a second set of sensor values, each of the second set of sensor values corresponding to one of the second set of sensor inputs;
feed the second sensor value array as input to a second function generated by a second neural network;
calculate one or more second output values based at least in part on the second function; and
based at least in part on the one or more second output values returned by the second function, exit the first state.

10. The media of claim 9 , wherein the one or more first output values are calculated by a low-power microcontroller; and in response to a determination that the first action has occurred, the micro-controller wakes up a processor from a sleep mode for calculation of the one or more second output values.

11. The media of claim 9 , wherein the first sensors comprise capacitive touch sensors.

12. The media of claim 9 , wherein the one or more second sensors comprise:
an accelerometer;
a light sensor; or
a multi-touch display surface.

13. The media of claim 9 , wherein the first state is a locked state.

14. The media of claim 9 , wherein the first action is a grab action.

15. The media of claim 9 , wherein the first and second functions are received from a server.

16. A device comprising:
a processor;
a plurality of first sensors;
one or more second sensors; and
a memory coupled to the processor comprising instructions executable by the processor, the processor being operable when executing the instructions to:
detect, while the device is in a first state, a first set of inputs from the plurality of first sensors;
generate a first sensor value array, each of the sensor values in the first sensor value array corresponding to one of the first set of inputs;
feed the first sensor value array as input to a first function generated by a first neural network;
calculate one or more first output values based at least in part on the first function;
determine, based at least in part on the one or more first output values, if a first action has occurred; and
in response to a determination that the first action has occurred:
poll one or more of the second sensors for a second set of sensor inputs;
generate a second sensor value array including a second set of sensor values, each of the second set of sensor values corresponding to one of the second set of sensor inputs;
feed the second sensor value array as input to a second function generated by a second neural network;
calculate one or more second output values based at least in part on the second function; and
based at least in part on the one or more second output values returned by the second function, exit the first state.

17. The device of claim 16 , wherein the device further comprises a low-power microcontroller, and wherein one or more first output values are calculated by the low-power microcontroller, and in response to a determination that a first action has occurred, the micro-controller wakes up the processor from a sleep mode for calculation of the one or more second output values.

18. The device of claim 16 , wherein the plurality of first sensors comprise touch sensors.

19. The device of claim 18 , wherein the touch sensors are capacitive.

20. The device of claim 16 , wherein one or more of the second sensors comprise:
an accelerometer;
a light sensor; or
a multi-touch display surface.

21. The device of claim 16 , wherein the first state is a locked state.

22. The device of claim 16 , wherein the first action is a grab action.

23. The device of claim 16 , wherein the first and second functions are received from a server.

Assignees

• Schillings Benoit M
• Garcia David Harry
• Facebook Inc

Inventors

• Schillings Benoit M
• Garcia David Harry

Classifications

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06N3/045

  Combinations of networks · CPC title

• G06N3/096

  Transfer learning · CPC title

• G06N3/09

  Supervised learning · CPC title

• G06N3/0442

  characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU] · CPC title