Adaptive sensor data selection and sampling based on current and future context

• US 9,568,895 B2
• Filed: 11/16/2015
• Issued: 02/14/2017
• Est. Priority Date: 04/03/2012
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Paul, Sanjoy, Kuntagod, Nataraj
• Primary Examiner(s): CHEN, ALAN S
• Application Number:
  US14/942,334
• Publication Number:
  US 20160070242A1
• Time in Patent Office: 456 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G05B 13/026 using a predictor
• 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 67/125 involving control of end-device applications over a network
• 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: H04W 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/38 for collecting sensor information
• CPC Class Codes: H04W 4/70 Services for machine-to-machine communication [M2M] or machine type communication [MTC]
• CPC Class Codes: H04W 84/18 Self-organising networks, e.g. ad-hoc networks or sensor networks

Abstract

A method for controlling a sensor may be performed by a mobile device including a processor and a memory. The method may include receiving raw data from the sensor, classifying the raw data into a context value, interpreting the context value into a higher-level context, receiving a predicted context based on the higher-level context, and controlling the sensor based on the predicted context. Controlling the sensor may include controlling a frequency at which raw data is received from the sensor, or an on/off state of the sensor. Control of the sensor may also be based on both the higher-level context and the predicted context.

Claims

1. A method, comprising:

receiving, by a device, a data value from a sensor;

determining, by the device, a context value based on the data value;

determining, by the device, a priority framework for handling conflicts when a plurality of applications are able to control the sensor;

determining, by the device, a sampling frequency based on the context value and based on minimizing battery usage or processing requirements; and

controlling, by the device, the sensor based on the sampling frequency and based on the priority framework.

2. The method of claim 1, where determining the context value comprises:

determining, by the device, an amount of processing required to process the data value;

determining, by the device, whether the amount exceeds a threshold; and

transmitting, by the device and to a server, the data value when the amount exceeds the threshold,

the server processing the data value to determine the context value and transmitting the context value to the device.

3. The method of claim 2, where determining the context value comprises:

processing, by a sensor proxy of the device, the data value when the amount does not exceed the threshold.

4. The method of claim 1, further comprising:

determining, by the device and based on the context value, an amount of processing required to generate a higher-level context;

determining, by the device, whether the amount exceeds a threshold; and

transmitting, by the device and to a server, the higher-level context when the amount exceeds the threshold,

the server generating the higher-level context and transmitting the higher-level context to the device,

where determining the sampling frequency comprises;

determining the sampling frequency based on the higher-level context.

5. The method of claim 4, further comprising:

generating, by a context manager of the device, the higher-level context when the amount does not exceed the threshold.

6. The method of claim 1, further comprising:

comparing, by the device and based on the context value, a higher-level context with an immediately prior higher-level context; and

determining, by the device, a change between the higher-level context and the immediately prior higher-level context.

7. The method of claim 6, further comprising:

receiving, by the device, a predicted context based on the change,

where determining the sampling frequency comprises;

determining the sampling frequency based on the predicted context.

8. A device, comprising:

one or more processors to;

receive a data value from a sensor;

determine a context value based on the data value;

determine a priority framework for handling conflicts when a plurality of applications are able to control the sensor;

determine a sampling frequency based on the context value and based on minimizing battery usage or processing requirements; and

control the sensor based on the sampling frequency and based on the priority framework.

9. The device of claim 8, where the one or more processors are further to:

request, based on the context value, a first predicted context; and

receive an indication that the first predicted context is not available based on the first predicted context not being available.

10. The device of claim 8, where the one or more processors are further to:

request, based on the context value, a first predicted context for a first future time; and

receive, based on requesting the first predicted context, a second predicted context for a second future time based on the first predicted context not being available and the second predicted context being available.

11. The device of claim 8, where the one or more processors are further to:

derive a complex context based on the context value.

12. The device of claim 11, where the one or more processors, when determining the sampling frequency based on the context value, are to:

determine the sampling frequency based on the complex context.

13. The device of claim 11, where the one or more processors are further to:

determine action rules based on the complex context; and

select the sensor based on the action rules.

14. The device of claim 8, where the one or more processors are further to:

identify, based on data that includes the sampling frequency, a selection of the sensor; and

disable, based on the data, another sensor that was not selected.

15. A non-transitory computer-readable storage medium, comprising:

one or more instructions that, when executed by one or more processors of a device, cause the one or more processors to;

receive raw data from a sensor;

determine a context value based on the raw data;

determine a sampling frequency based on the context value and based on minimizing battery usage or processing requirements;

determine a priority framework for handling conflicts when a plurality of applications are able to control the sensor; and

control the sensor based on the sampling frequency and based on the priority framework.

16. The non-transitory computer-readable storage medium of claim 15,

where the one or more instructions, when executed by the one or more processors of the device, further cause the one or more processors to:

obtain a higher-level context based on the context value and a plurality of different raw data values,

at least one raw data value, of the plurality of the different raw data values, not being directly obtained from the sensor, and

where the one or more instructions, when determining the sampling frequency, cause the one or more processors to;

determine the sampling frequency based on the higher-level context.

17. The non-transitory computer-readable storage medium of claim 15, where the one or more instructions, when executed by the one or more processors of the device, further cause the one or more processors to:

select a first plurality of sensors from a set of sensors based on the context value;

control the first plurality of sensors based on the context value; and

turn off a second plurality of sensors from the set of sensors.

18. The non-transitory computer-readable storage medium of claim 17, where the one or more instructions, when executed by the one or more processors of the device, further cause the one or more processors to:

select sampling rates for the first plurality of sensors; and

direct the first plurality of sensors to sample the raw data at the sampling rates.

19. The non-transitory computer-readable storage medium of claim 15, where the one or more instructions, when controlling the sensor based on the context value, cause the one or more processors to:

determine rules for controlling the sensor;

select a first plurality of sensors based on the rules;

control the first plurality of sensors to sample the raw data; and

turn off a second plurality of sensors based on the rules.

20. The non-transitory computer-readable storage medium of claim 15, where the one or more instructions, when executed by the one or more processors of the device, further cause the one or more processors to:

identify, based on data that includes the sampling frequency, a selection of the sensor; and

disable, based on the data, another sensor that was not selected.