TRIGGERING GEOLOCATION FIX ACQUISITIONS ON TRANSITIONS BETWEEN PHYSICAL STATES

• US 20150018014A1
• Filed: 07/15/2014
• Published: 01/15/2015
• Est. Priority Date: 07/15/2013
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: Phan, Thomas
• Granted Patent: US 9,591,456 B2
• Time in Patent Office: Days
• US Class Current: 455/456.3
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: G01P 13/00 Indicating or recording presence, absence, or direction, of movement electric switches H01H; counting moving objects G06M7/00
• CPC Class Codes: H04W 4/027 using movement velocity, acceleration information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services

Abstract

A method and device for triggering acquisition of geolocation fix information. The method include determining activity state information based on information from one or more sensors. It is determined if an activity state has transitioned to a particular activity state based on the activity state information. Geolocation fix information is acquired if the activity state transitioned to the particular activity state.

Claims

1. A method for triggering acquisition of geolocation fix information comprising:

determining activity state information based on information from one or more sensors;

determining if an activity state has transitioned to a particular activity state based on the activity state information; and

acquiring geolocation fix information if the activity state transitioned to the particular activity state.

2. The method of claim 1, further comprising acquiring acceleration data from one or more accelerometer sensors coupled with an electronic device, and using the acceleration data for determining the activity state.

3. The method of claim 2, wherein determining activity state information comprises:

determining tri-axis normalization on the acceleration data;

extracting a sliding window based on the tri-axis normalization;

obtaining magnitude of a frequency response based on the sliding window; and

computing features from time-domain information and frequency-domain information based on the magnitude of the frequency response.

4. The method of claim 3, further comprising:

concatenating features from tri-axis information for obtaining a feature vector; and

providing one or more of a trainer and classifier for recognizing activity states.

5. The method of claim 4, wherein the tri-axis information comprises Cartesian magnitude information, true horizontal information and true vertical information.

6. The method of claim 5, wherein the trainer comprises a supervised machine learning trainer that provides offline training for providing mapping to physical activity states using a classification model, and the classifier provides classification of sensor data using information from the classification model for recognizing a plurality of activities.

7. The method of claim 6, further comprising providing information to an electronic device based on the geolocation fix information.

8. The method of claim 1, wherein the geolocation fix information comprises one or more of global positioning system information, Wi-Fi information, and triangulation information.

9. The method of claim 1, wherein acquiring the geolocation fix information comprises controlling an active state of a global positioning system sensor.

10. The method of claim 1, wherein the activity state information comprises an indication of one or more moving and stationary activities.

11. The method of claim 10, wherein the moving activities comprise one or more of walking, running, driving, bicycling, flying, boating, and transporting, and the stationary activities comprise one or more of sitting, standing, and idling.

12. The method of claim 11, wherein determining if an activity state has transitioned to the particular activity state comprises transitioning between particular pairs of activity states.

13. The method of claim 2, wherein the electronic device comprises one or more of a smart phone, a tablet device, a portable computing device, a wearable device and a camera device.

14. An electronic device comprising:

one or more sensors that provide sensed data;

an activity recognizer that determines activity state information based on the sensed data;

a transition manager that determines if an activity state has transitioned to a particular activity state based on the activity state information; and

a geolocation service or geolocation sensor that acquires geolocation fix information if the activity state transitioned to the particular activity state.

15. The electronic device of claim 14, wherein one or more accelerometer sensors provide the sensed data.

16. The electronic device of claim 14, wherein the activity recognizer determines tri-axis normalization on the sensed data, extracts a sliding window based on the tri-axis normalization, obtains magnitude of a frequency response based on the sliding window and computes features from time-domain information and frequency-domain information based on the magnitude of the frequency response.

17. The electronic device of claim 16, further comprising a smoother that concatenates features from tri-axis information for obtaining a feature vector, wherein the tri-axis information comprises Cartesian magnitude information, true horizontal information and true vertical information.

18. The electronic device of claim 17, wherein a supervised machine learning trainer provides offline training for providing mapping to physical activity states using a classification model, and the activity recognizer includes a classifier that classifies the sensed data using information from the classification model for recognizing a plurality of activities.

19. The electronic device of claim 18, wherein a geolocation based application provides information to the electronic device based on the geolocation fix information.

20. The electronic device of claim 14, wherein the geolocation fix information comprises one or more of global positioning system information, Wi-Fi information, and triangulation information.

21. The electronic device of claim 14, wherein the transition manager controls an active state of a global positioning system sensor.

22. The electronic device of claim 14, wherein the activity state information comprises an indication of one or more moving and stationary activities, wherein the moving activities comprise one or more of walking, running, driving, bicycling, flying, boating, and transporting, and the stationary activities comprise one or more of sitting, standing, and idling.

23. The electronic device of claim 14, wherein the transition manager determines if an activity state has transitioned to the particular activity state based on a transition between particular pairs of activity states.

24. The electronic device of claim 14, wherein the electronic device comprises one or more of a smart phone, a tablet device, a portable computing device, a wearable device and a camera device.

25. A non-transitory computer-readable medium having instructions which when executed on a computer perform a method comprising:

determining activity state information based on sensed data;

determining if an activity state has transitioned to a particular activity state based on the activity state information; and

acquiring geolocation fix information if the activity state transitioned to the particular activity state.

26. The medium of claim 25, further comprising providing information to an electronic device based on the geolocation fix information, wherein the geolocation fix information comprises one or more of global positioning system information, Wi-Fi information, and triangulation information.

27. The medium of claim 25, wherein acquiring the geolocation fix information comprises controlling an active state of a global positioning system sensor, wherein the activity state information comprises an indication of one or more moving and stationary activities.

28. The medium of claim 27, wherein the moving activities comprise one or more of walking, running, driving, bicycling, flying, boating, and transporting, and the stationary activities comprise one or more of sitting, standing, and idling.

29. The medium of claim 28, wherein determining if an activity state has transitioned to the particular activity state comprises transitioning between particular pairs of activity states.

30. The medium of claim 26, wherein the electronic device comprises one or more of a smart phone, a tablet device, a portable computing device, a wearable device and a camera device.