Context sensing for computing devices

1. A method for context sensing, comprising:

determining if sensor data obtained via a plurality of sensors exceed a predetermined threshold;

if the sensor data exceed the threshold, increasing a sampling rate of any of the plurality of sensors to obtain context data corresponding to a computing device;

analyzing the context data to classify a context of the computing device;

analyzing the context data to determine meaningful context data and meaningless context data;

discarding the meaningless context data; and

analyzing the meaningful context data to classify the context of the computing device via an offload engine.

2. The method of claim 1 , comprising providing the context to a processor of the computing device, wherein the processor is configured to send the context to any of a plurality of context-aware applications.

3. The method of claim 1 , comprising:

analyzing the context data to determine changes in an environment of the computing device; and

notifying a processor of the computing device of the changes in the environment.

4. The method of claim 1 , comprising:

combining the context data obtained via the plurality of sensors; and

analyzing the combined context data to determine the threshold.

5. The method of claim 1 , comprising:

determining a power level of the computing device; and

lowering the sample rate of the plurality of sensors if the power level is below a specified lower threshold.

6. The method of claim 1 , comprising increasing a sampling rate of a plurality of common context sensors via a common context source trigger of a context sensing system when sensor data obtained from the plurality of common context sensors exceed the threshold.

7. The method of claim 1 , comprising increasing the sampling rate of an audio sensor via an audio classifier trigger of a context sensing system when sensor data obtained from the audio sensor exceed the threshold.

8. A computing device, comprising:

a context sensing system configured to:

increase a sampling rate of a plurality of sensors when sensor data obtained via the plurality of sensors exceed a threshold;

obtain context data corresponding to the computing device via the plurality of sensors;

analyze the context data to determine context information corresponding to the computing device and to determine meaningful context data and meaningless context data;

discard the meaningless context data; and

analyze the meaningful context data to determine the context information corresponding to the computing device via an offload engine;

send the context information to a central processing unit (CPU) of the computing device; and

the central processing unit (CPU) configured to:

accept the context information from the context sensing system; and

send the context information to a context-aware application.

9. The computing device of claim 8 , wherein the context sensing system is configured to:

analyze the context data to determine changes in an environment of the computing device; and

notify the CPU of the changes in the environment.

10. The computing device of claim 8 , wherein a common context source trigger of the context sensing system is configured to increase a sampling rate of a plurality of common context sensors when sensor data obtained from the plurality of common context sensors exceed the threshold.

11. The computing device of claim 8 , wherein an audio classifier trigger of the context sensing system is configured to increase a sampling rate of an audio context sensor when sensor data obtained from the audio context sensor exceed the threshold.

12. The computing device of claim 8 , wherein the context sensing system is configured to:

combine the context data from the plurality of sensors; and

analyze the combined context data to determine the threshold for increasing the sampling rate of the plurality of sensors.

13. The computing device of claim 8 , wherein the context sensing system is configured to:

determine a power level of the computing device; and

decrease the sampling rate of the plurality of sensors if the power level is below a specified lower threshold.

14. The computing device of claim 8 , wherein the context sensing system is configured to:

determine the threshold based on a power consumption of the computing device; and

increase the threshold if the power consumption exceeds a specified upper threshold.

15. The computing device of claim 8 , wherein the context sensing system is configured to:

receive a request for context information from a context-aware application via the CPU;

determine the context information; and

return the context information to the CPU; and

wherein the CPU is configured to send the context information to the context-aware application.

16. At least one non-transitory machine readable medium having instructions stored therein that, in response to being executed on a computing device, cause the computing device to:

increase a sampling rate of a plurality of sensors when sensor data obtained via the plurality of sensors exceed a threshold;

obtain context data corresponding to the computing device via the plurality of sensors;

analyze the context data to classify a context of the computing device;

analyzing the context data to determine meaningful context data and meaningless context data;

discarding the meaningless context data; and

analyzing the meaningful context data to classify the context of the computing via an offload engine.

17. The at least one non-transitory machine readable medium of claim 16 , wherein the instructions cause the computing device to send the context to a central processing unit (CPU) of the computing device, and wherein the CPU is configured to send the context to any of a plurality of context-aware applications running on the CPU.

18. The at least one non-transitory machine readable medium of claim 16 , wherein the threshold is determined based on a power consumption of the computing device, and wherein the threshold is increased if the power consumption of the computing device exceeds a specified upper threshold.