METHOD, SYSTEM AND COMPUTER PROGRAM FOR DETECTING AND MONITORING HUMAN ACTIVITY UTILIZING LOCATION DATA

• US 20080125959A1
• Filed: 11/03/2006
• Published: 05/29/2008
• Est. Priority Date: 11/03/2006
• Status: Active Grant

• Current Assignee: Salient Imaging, Inc.
• Original Assignee: Salient Imaging, Inc.
• Inventors: Cwik, Lukasz, Papinski, Dominik, Doherty, Sean T.
• Granted Patent: US 8,606,497 B2
• Time in Patent Office: Days
• US Class Current: 701/200
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G07C 1/10 together with the recording, indicating or registering of other data, e.g. of signs of identity
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services

Abstract

A method, system and computer program for detecting and displaying a person'"'"'s activity-travel pattern over time and space is provided. Person-based location data is acquired by a personal communication device and processed in accordance with an algorithm. The invention goes beyond applications that focus on the detection of the current location of the user, but rather the enhanced knowledge of the users current, past, and likely future activities and their multi-dimensional attributes. The present invention can be implemented on common hardware and is easily accessible via web-based interfaces and reporting, making various applications achievable at very low cost.

Claims

1. A method for monitoring human activity utilizing location data comprising:

(a) receiving person-based location data from a mobile device, the person-based location data being sent from a user; and

(b) processing the person-based location data using an activity detection means by converting the person-based location data into activity data, the activity data including person-based activities and optionally attributes of the person-based activities.

2. The method of claim 1 further comprising:

(a) displaying the activity data to the user; and

(b) receiving feedback from the user;

wherein the feedback is dynamically used by the activity detection means.

3. The method of claim 1 wherein the mobile device is a cellular phone, a personal digital assistant, a wireless handheld, or a portable computer.

4. The method of claim 1 wherein the location data includes longitude and latitude coordinates.

5. The method of claim 1 wherein the person-based location data is sent at an interval based on desired activity data.

6. The method of claim 5 wherein the interval consists of 1 second or more.

7. The method of claim 1 wherein the processing of the person-based location data comprises the steps of:

(a) initial classification of the person-based location data according to one or more of missing data point segments, activity segments and/or trip segments;

(b) generation of summary statistics for the missing data point segments, the activity segments and/or the trip segments;

(c) refinement of the missing data point segments, the activity segments and/or the trip segments; and

(d) optionally detection of additional attributes related to the person-based activities.

8. The method of claim 7 wherein spatial data is included in the generation of the summary statistics.

9. The method of claim 7 wherein the refinement of the missing data point segments, the activity segments, and the trip segments is achieved according to one or more activity-based rules and/or parameters.

10. The method of claim 9 wherein the activity-based rules and/or parameters are probabilistic.

11. The method of claim 9 wherein the activity-based rules and/or parameters:

(a) convert the missing data point segments to the activity segments and the trip segments;

or

(b) convert and join the activity segments and the trip segments.

12. The method of claim 9 wherein the activity-based rules and/or parameters include meta rules.

13. The method of claim 7 wherein the detection of additional attributes for activities includes the start/end time, duration, location coordinates, whether it is a within-activity movement episodes, whether it is a brief pick-up/drop-off, or whether it is a brief mode-switch point.

14. The method of claim 7 wherein the detection of additional attributes for activities includes preferred attributes estimated by activity-based probabilistic rules.

15. The method of claim 14 wherein the activity-based probabilistic rules relate to whether a building is indoors or outdoors, a building name, or land-use.

16. The method of claim 7 wherein the detection of additional attributes for trips include start/end time, duration, speed/distance statistics, or whether it is a within-trip stop episode.

17. The method of claim 7 wherein the detection of additional attributes for trips includes preferred attributes estimated by trip probabilistic rules.

18. The method of claim 17 wherein the trip probabilistic rules relate to travel mode, leisure travel/exercise detection, or route.

19. The method of claim 7 wherein learned attributes are linked to the detection of additional attributes, wherein the learned attributes comprise a historical database.

20. The method of claim 7 further comprising providing an output table with a listing of events and attributes.

21. A system for monitoring human activity utilizing location data comprising:

(a) a server computer; and

(b) a server application linked to the server computer, the server application being operable to provide instructions to the server that enable the server to;

(i) receive person-based location data from a mobile device, the person-based location data being sent from a user; and

(ii) process the person-based location data by operation of an activity detection facility included in or linked to the server application, the activity detection facility being operable to convert the person-based location data into activity data, the activity data including person-based activities and optionally attributes of the person-based activities.

22. The system of claim 21, wherein the server computer is operable to connect to one or more remote computers and thereby to provide access to the resources of the system at said one or more remote computers.

23. The system of claim 22, wherein the server computer is operable to make the activity data accessible from the one or more remote computers.

24. The system of claim 22, wherein the server application is operable on the server to receive feedback from the one or more remote computers, and wherein the feedback is dynamically used by the activity detection facility.

25. The system of claim 21 wherein the mobile device is a cellular phone, a personal digital assistant, a wireless handheld, or a portable computer.

26. The system of claim 21 wherein the location data includes longitude and latitude coordinates.

27. The system of claim 21 wherein the person-based location data is sent at an interval based on desired activity data.

28. The system of claim 27 wherein the interval consists of 1 second or more.

29. The system of claim 21 wherein the activity detection facility is further operable for:

(a) initial classification of the person-based location data according to one or more of missing data point segments, activity segments and/or trip segments;

(b) generation of summary statistics for the missing data point segments, the activity segments and/or the trip segments;

(c) refinement of the missing data point segments, the activity segments and/or the trip segments; and

(d) optionally detection of additional attributes.

30. The system of claim 29 wherein spatial data is included in the generation of the summary statistics.

31. The system of claim 29 wherein the refinement of the missing data point segments, the activity segments and the trip segments is achieved according to one or more activity-based rules and/or parameters.

32. The system of claim 31 wherein the activity-based rules and/or parameters are probabilistic.

33. The system of claim 31 wherein the activity-based rules and/or parameters:

(a) convert the missing data point segments to the activity segments and the trip segments;

or

(b) convert and join the activity segments and the trip segments.

34. The system of claim 31 wherein the rules and parameters include meta rules.

35. The system of claim 29 wherein the detection of additional attributes for activities includes the start/end time, duration, location coordinates, whether it is a within-activity movement episodes, whether it is a brief pick-up/drop-off, or whether it is a brief mode-switch point.

36. The system of claim 29 wherein the detection of additional attributes for activities includes preferred attributes estimated by activity probabilistic rules.

37. The system of claim 36 wherein the activity probabilistic rules relate to whether a building is indoors or outdoors, a building name, or land-use.

38. The system of claim 29 wherein the detection of additional attributes for trips include start/end time, duration, speed/distance statistics, or whether it is a within-trip stop episode.

39. The system of claim 38 wherein the detection of additional attributes for trips includes preferred attributes estimated by trip probabilistic rules.

40. The system of claim 39 wherein the trip probabilistic rules relate to travel mode, leisure travel/exercise detection, or route.

41. The system of claim 21 wherein the person-based location data is sent at a frequency that is determined according to:

(a) spatial-temporal circumstances as defined by parameters established by the user; and

/or

(b) the data output of the activity detection algorithm, wherein a low frequency is achieved when a stationary event is sustained for a sleep minimum duration, and wherein a high frequency is achieved when a movement event is sustained for a wake minimum duration.

42. The system of claim 29 wherein learned attributes are linked to the detection of additional attributes, wherein the learned attributes comprise a historical database.

43. The system of claim 29 further comprising providing an output table with a listing of events and attributes.

44. A computer program product for monitoring human activity utilizing location data comprising, the computer program product for use on a server computer, the computer program product comprising:

(a) a computer usable medium;

(b) computer readable program code recorded or storable in the computer usable medium, the computer readable program code defining a server application on the server computer that is operable on the server computer to;

(i) receive person-based location data from a mobile device, the person-based location data being sent from a user; and

(ii) process the person-based location data using an activity detection means by converting the person-based location data into activity data, the activity data including person-based activities and optionally attributes of person-based activities.

45. The computer program product of claim 44 wherein the server application is further operable on the server computer to:

(a) display the activity data to the user; and

(b) receive feedback from the user;

wherein the feedback is dynamically used by the activity detection means.

46. A mobile device for monitoring human activity utilizing location data comprising:

(a) a mobile device; and

(b) a computer program loaded on, or downloadable to the mobile device, the computer program being operable on the mobile device to;

(i) process person-based location data provided to the computer program, by operation of an activity detection facility included in the computer program;

or

(ii) process the person-based location data by operation of an activity detection facility provided by the computer program on the mobile device in cooperation with a server application linked to a server, the server being accessible to the mobile device via a wireless network;

wherein the activity detection facility is operable to convert the person-based location data into activity data, the activity data including person-based activities and optionally attributes of the person-based activities.

47. A computer program product for monitoring human activity utilizing location data comprising, the computer program product for use on a mobile device, the computer program product comprising:

(a) computer readable program code loaded on, or downloadable to the mobile device, the computer program being operable on the mobile device to;

(i) process person-based location data provided to the computer program, by operation of an activity detection facility included in the computer readable program code;

or

(ii) process the person-based location data by operation of an activity detection facility provided by the computer readable program code on the mobile device in cooperation with a server application linked to a server, the server being accessible to the mobile device via a wireless network;

wherein the activity detection facility is operable to convert the person-based location data into activity data, the activity data including person-based activities and optionally attributes of the person-based activities.