Distributed Architecture for Situation Aware Sensory Application

• US 20120096290A1
• Filed: 10/14/2011
• Published: 04/19/2012
• Est. Priority Date: 10/14/2010
• Status: Abandoned Application

• Current Assignee: KEYnetik, Inc.
• Original Assignee: KEYnetik, Inc.
• Inventors: Boshkin, Anatoly V., Shkolnikov, Mark B., Shkolnikov, Diana
• Application Number:
  US13/273,838
• Publication Number:
  US 20120096290A1
• Time in Patent Office: Days
• US Class Current: 713/320
• CPC Class Codes: G06F 1/3228 Monitoring task completion, e.g. by use of idle timers, stop commands or wait commands
• CPC Class Codes: G06F 1/325 Power saving in peripheral device

Abstract

Embodiments of the invention relate to a distributed signal processing system and a method for processing a sensor signal for a mobile device. Raw signal data is received and pre-processed by a processor to filter and split the data signal into multiple data outputs. The split signal data represent both spatial and spectral components, and/or statistical properties pertaining to the sensor. Low rate processing data is communicated to a second processor for limited data processing by select logic components.

Claims

1. A method comprising:

one or more sensors in communication with at least two processors, including a first processor in communication with a second processor, the first processor pre-processing signal data from the one or more sensors for the second processor, the signal pre-processing including converting a high rate raw data stream from the one or more sensors into a low rate data stream of extracted features;

configuring the second processor with two or more logic elements, each logic element configured to process the low rate data stream for a defined set of extracted features; and

selectively operating each configured logic element of the second processor, including transitioning one of the select logic elements from a low power state to a high power state to support feature processing, and transitioning one of the select logic elements operating at the high power state to the low power state at a conclusion of feature processing.

2. The method of claim 1, further comprising configuring the first processor with a filter bank for the signal pre-processing and transition detection logic for selectively determining a logic element of the second processor, wherein the filter bank communicates non-motion data, orientation data, and motion signal variance to the transition detection logic.

3. The method of claim 1, the transition detection logic further comprising instructions for evaluation signal conditions selected from the group consisting of:

non-motion stationary, and motion stationary.

4. The method of claim 1, wherein selectively operating each configured logic element of the second processor reduces signal data processing by the second processor.

5. The method of claim 1, wherein the second processor and the first processor are electronically separated.

6. The method of claim 1, wherein the first processor has a physical proximity relationship with the second processor selected from the group consisting of:

a standalone processor and a processor embedded into an element selected from the group consisting of;

a sensor, a sensor package, and the second processor.

7. The method of claim 1, wherein a data exchange rate between the second processor and the first processor is lower than a polling rate of the one or more sensors.

8. The method of claim 1, wherein the logic elements of the second processor include at least pedestrian navigation logic, situation awareness logic, and other application logic.

9. The method of claim 8, wherein the situation awareness includes an environmental situation change, and the change is selected from the group consisting of:

light, temperature, proximity, orientation, and activity status.

10. The method of claim 1, further comprising the first processor reducing a size of the sensory data received from the one or more sensors with a technique selected from the group consisting of:

de-sampling, compression, and quantization, wherein the quantization technique reduces the size of a sample or feature, and the de-sampling technique reduces a quantity of data samples.

11. The method of claim 1, further comprising the first processor pre-processing signal data from the one or more sensors including reducing a size of the sensory data received from the two or more sensors with a technique selected from the group consisting of:

co-variance and correlation or their mathematical approximations.

12. The method of claim 1, further comprising the first processor extracting situation awareness information from the sensory signal, the situation awareness selected from the group consisting of:

device placement and user activity classification.

16. The system of claim 12, wherein the second processor and the first processor are electronically separated r.

17. The system of claim 12, wherein the first processor has a physical proximity relationship with the second processor selected from the group consisting of:

a standalone processor and a processor embedded into an element selected from the group consisting of;

a sensor, a sensor package, and the second processor.

18. The system of claim 12, wherein a data exchange rate between the second processor and the first processor is lower than a polling rate of the one or more sensors.

19. The system of claim 18, wherein the situation awareness includes an environmental situation change, and the change is selected from the group consisting of:

light, temperature, proximity, orientation, and activity status.

20. The system of claim 12, further comprising the first processor reducing a size of the sensory data received from the one or more sensors with a technique selected from the group consisting of:

de-sampling, compression, and quantization, wherein the quantization technique reduces the size of a sample, and the de-sampling technique reduces a quantity of data samples.

13. A system comprising:

a mobile device having a sensor to generate a motion signal;

a computer system in communication with the mobile device, the computer system including a first processor and a second processor;

the first processor in communication with first memory, and the second processor in communication with second memory;

the second processor configured with two or more embedded logic elements, each logic element to process the low rate data stream for a defined set of extracted features;

a first functional unit in communication with the first memory, the first functional unit comprising a signal manager to pre-process signal data from the sensor for the second processor, including a conversion of high rate raw data from the sensor into a low rate data stream of extracted features; and

a second functional unit in communication with the second memory, the second functional unit comprising;

a logic manager to selectively operate each configured logic element of the second processor, and for each select logic element individually executes a first transition from a low power state to support feature processing and executes a second transition operating at a high power state to the low power state at a conclusion of feature processing.

14. The system of claim 13, further comprising a filter bank local to the first processor, the filter bank having a processing manager to support signal pre-processing and a transition manager in communication with the processing manager, the transition manager to selectively determine a logic element in communication with the second processor, wherein the filter bank communicates non-motion data, orientation data and motion signal variance to the transition detection logic.

15. The system of claim 14, further comprising the transition manager to evaluate a signal condition selected from the group consisting of:

non-motion stationary, and motion stationary.

21. A computer program product for use with a mobile device, the mobile device having a sensor to generate a motion signal, the computer program product comprising a computer readable storage medium having computer readable program code embodied thereon, which when executed causes a computer to implement the method comprising:

setting a first processor in communication with a second processor;

configuring the second processor with two or more logic elements, each logic element configured to process the low rate data stream for a defined set of extracted features;

receiving data from at least one of the sensors, including;

the first processor pre-processing signal data from the one or more sensors for the second processor, the signal pre-processing including converting a high rate raw data stream from the one or more sensors into a low rate data stream of extracted features; and

selectively operating each configured logic element of the second processor, including transitioning one of the select logic elements from a low power state to a high power state to support feature processing, and transitioning one of the select logic elements operating at the high power state to the low power state at a conclusion of feature processing.

22. The computer program product of claim 21, further comprising configuring the first processor with a filter bank for the signal pre-processing and transition detection logic for selectively determining a logic element of the second processor, wherein the filter bank communicates non-motion data, orientation data, and motion signal variance to the transition detection logic.

23. The computer program product of claim 22, wherein the transition detection logic further comprising instructions for evaluation signal conditions selected from the group consisting of:

non-motion stationary, and motion stationary.

24. The computer program product of claim 21, wherein selectively operating each configured logic element of the second processor reduces signal data processing by the second processor.

25. The computer program product of claim 21, wherein the second processor and the first processor are electronically separated.

26. The computer program product of claim 21, wherein the first processor has a physical proximity relationship with the second processor selected from the group consisting of:

a standalone processor and a processor embedded into an element selected from the group consisting of;

a sensor, a sensor package, and the second processor.

27. The computer program product of claim 21, wherein a data exchange rate between the second processor and the first processor is lower than a polling rate of the one or more sensors.

28. The computer program product of claim 21, wherein the logic elements of the second processor include at least pedestrian navigation logic, situation awareness logic, and other application logic.

29. The computer program method of claim 28, wherein the situation awareness includes an environmental situation change, and the change is selected from the group consisting of:

light, temperature, proximity, orientation, and activity status.

30. The computer program product of claim 21, further comprising the first processor reducing a size of the sensory data received from the one or more sensors with a technique selected from the group consisting of:

de-sampling, compression, and quantization, wherein the quantization technique reduces the size of a sample, and the de-sampling technique reduces a quantity of data samples.

31. A distributed signal processing method for mobile devices with sensors and at least two processors, comprising:

one or more sensors are in communication with a first processor and the first processor is in communication with a second processor;

the first processor pre-processing signal data from the one or more sensors for the second processor, the signal pre-processing including filtering and splitting the signal data into multiple outputs representing spatial and spectral components, and statistical properties of the components; and

the second processor running one or more sensory applications utilizing selected outputs from the first processor.

32. The distributed signal processing method of claim 31, wherein the statistical properties include an item selected from the group consisting of:

averages, ranges, modes, medians, variances, co-variances, and associated mathematical approximations.