ADAPTIVE SENSOR DATA SELECTION AND SAMPLING BASED ON CURRENT AND FUTURE CONTEXT

• US 20130282149A1
• Filed: 09/14/2012
• Published: 10/24/2013
• 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
• Granted Patent: US 9,191,442 B2
• Time in Patent Office: Days
• US Class Current: 700/73
• 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 for controlling a sensor, the method being performed by a mobile device including a processor and a memory, the method comprising:

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.

2. The method of claim 1, wherein the controlling includes controlling the sensor based on the higher-level context and the predicted context.

3. The method of claim 1, wherein the controlling includes controlling at least one of a frequency at which raw data is received from the sensor, or an on/off state of the sensor.

4. The method of claim 3, wherein the controlling includes adjusting, over time, based on the predicted context, at least one of the frequency at which raw data is received from the sensor, or the on/off state of the sensor.

5. The method of claim 1, further including:

receiving raw data from a plurality of sensors;

classifying the raw data into a plurality of context values;

interpreting the context values into the higher-level context; and

controlling the sensors based on the higher-level context and the predicted context.

6. The method of claim 5, wherein the controlling includes controlling at least one of a frequency at which raw data is received from each of the sensors, or a selection of the sensors to be enabled.

7. The method of claim 5, wherein the controlling includes turning off at least a first one of the sensors and increasing a sampling frequency of at least a second one of the sensors.

8. The method of claim 1, further including:

sending the higher-level context to a server configured to determine the predicted context from the higher-level context; and

receiving the predicted context from the server.

9. The method of claim 8, wherein interpreting the context value into the higher-level context is performed by one of the mobile device or the server, based on whether an amount of processing required for the interpreting exceeds a threshold processing limit.

10. The method of claim 1, wherein the sensor is physically integrated with the mobile device.

11. The method of claim 1, wherein the sensor is not physically integrated with the mobile device and communicates wirelessly with the mobile device.

12. The method of claim 1, further comprising:

receiving a priority framework that defines priority of control of the sensor between at least two applications running on the mobile device; and

controlling the sensor based on the priority framework and the predicted context.

13. The method of claim 12, wherein receiving a priority framework comprises receiving a priority framework that assigns priority to an affirmative selection of the sensor and a highest sampling frequency of the sensor.

14. A system for controlling sensors, the system comprising:

a plurality of sensors;

a mobile device, the mobile device including a processor and a memory; and

a server;

wherein the mobile device is configured to;

receive raw data from the sensors;

classify the raw data into context values;

interpret the context values into a higher-level context;

send the higher-level context to the server;

receive a predicted context based on the higher-level context from the server; and

control the sensors based on the predicted context; and

wherein the server is configured to receive the higher-level context and generate the predicted context based on the higher-level context.

15. The system of claim 14, wherein controlling the sensors includes controlling at least one of a frequency at which raw data is received from each of the sensors, or a selection of the sensors to be enabled.

16. The system of claim 15, wherein the controlling further includes adjusting, over time, based on the predicted context, at least one of the frequency at which raw data is received from each of the sensors, or the selection of the sensors to be enabled.

17. The system of claim 14, wherein at least one of the sensors is physically integrated with the mobile device.

18. The system of claim 17, wherein at least one of the sensors is not physically integrated with the mobile device and communicates wirelessly with the mobile device.

19. The system of claim 14, wherein the mobile device is a cell phone.

20. The system of claim 14, wherein the mobile device is further configured to:

receive a priority framework that defines priority of control of the sensors between at least two applications running on the mobile device; and

control the sensors based on the priority framework and the predicted context.

21. A non-transitory computer-readable storage medium storing instructions which, when executed by a processor, cause the processor to perform a method for controlling a plurality of sensors, the method comprising:

receiving raw data from the sensors;

classifying the raw data into context values;

interpreting the context values into a higher-level context;

receiving a predicted context based on the higher-level context; and

controlling the sensors based on the higher-level context and the predicted context.

22. The storage medium of claim 21, wherein the controlling includes controlling at least one of a frequency at which raw data is received from the sensors, or a selection of the sensors to be enabled.

23. The storage medium of claim 21, wherein the controlling includes turning off at least a first one of the sensors and increasing a sampling frequency of at least a second one of the sensors.

24. The storage medium of claim 21, the method further comprising:

receiving a priority framework that defines priority of control of the sensors between at least two applications running on the mobile device; and

controlling the sensors based on the priority framework and the predicted context.