Method, system and computer program for detecting and monitoring human activity utilizing location data

• US 8,606,497 B2
• Filed: 11/03/2006
• Issued: 12/10/2013
• Est. Priority Date: 11/03/2006
• Status: Active Grant

• Current Assignee: Salient Imaging, Inc.
• Original Assignee: Salient Imaging, Inc.
• Inventors: Doherty, Sean T., Cwik, Lukasz, Papinski, Dominik
• Primary Examiner(s): Tarcza, Thomas
• Assistant Examiner(s): MUSTAFA, IMRAN K
• Application Number:
  US11/556,365
• Publication Number:
  US 20080125959A1
• Time in Patent Office: 2,594 Days
• Field of Search: 701/400, 701/408, 701/410
• US Class Current: 701/400
• 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. In a message delivery system having a plurality of messages to transmit to a plurality of persons each having attributes of person-based location data and a mobile device with positional co-ordinates communications functionality, a method comprising a plurality of steps each being performed by hardware executing software, wherein the steps, for each said person, include:

receiving the person-based location data, including the positional co-ordinates, from the mobile device;

processing, using an activity detection means, the person-based location data in accordance with an activity detection algorithm that uses;

missing datapoint segments;

activity segments; and

trip segments, wherein the activity detection algorithm;

is probabilistic;

converts the missing data point segments to the activity segments and the trip segments; and

converts and joins the activity segments and the trip segments;

converting the processed person-based location data into activity data in accordance with principles customized to the person, wherein the activity data for the person includes one or more of;

person-based activities;

attributes of the person-based activities; and

predicted activity generated to predict at least the location of the person by one or more of the following;

utilizing a historical track of the processed person-based location data; and

handling and interpreting of signal losses from the mobile device occurring on an approach to, or at, one or more locations by refining, joining or converting the signal losses to identify the person'"'"'s;

activities;

stops;

trips; and

movements; and

transmitting one said message to the mobile device that corresponds to the activity data for the person.

2. The method of claim 1, wherein the one said message contains an instruction to the mobile device to initiate a transmission of information to a logical address.

3. The method of claim 2, wherein the instruction to the mobile device is to initiate a cellular telephone transmission to a telephone number.

4. The method of claim 1, wherein the steps further comprise, for each said person, receiving the principles customized to the person prior to the transmitting of the one said message to the mobile device that corresponds to the activity data for the person.

5. The method of claim 4, wherein the received said principles customized to the person is selected from a group consisting of:

a pre-specified sequence of dialing numbers to be activated to initiate a corresponding transmission from the mobile device; and

a list of logical addresses respectively corresponding to merchants to whom to transmit at least of portion of the activity data for the person.

6. The method of claim 5, wherein each said merchant in the list of merchants is selected from a group consisting of:

a courier;

from whom a delivery to the person is to be made; and

to whom a probable location of the person at a predicted time is to be made known as derived from the activity data for the person; and

a retailer from whom incoming retail “

sale”

information will be received at the mobile device for the person when the person is within a probable predetermined distance from a location of a store of the retailer at a predicted time when the person activity data for the person includes the activity of shopping as derived from the activity data for the person.

7. The method of claim 1, wherein the one said message contains an offer from a merchant pertaining to an activity being engaged by the person and corresponding to the activity data for the person.

8. The method of claim 7, wherein the offer from the merchant corresponds to a location proximal the positional co-ordinates received from the mobile device.

9. The method of claim 1, wherein the handling and interpreting of signal losses from the mobile device occurring on an approach to, or at, one or more locations comprises an approach to, or within, one or more buildings as are proximal to the positional co-ordinates received from the mobile device.

10. The method of claim 1, wherein the processing, using the activity detection means, of the person-based location data in accordance with the activity detection algorithm comprises:

initial classification of the person-based location data according to one or more of;

missing datapoint segments;

activity segments; and

trip segments;

generation of summary statistics for;

missing datapoint segments;

activity segments; and

trip segments; and

refinement, according to one or more activity-based rules and/or parameters, in accordance with the activity detection algorithm, of;

missing datapoint segments;

activity segments; and

trip segments;

wherein the activity-based rules and/or parameters;

are probabilistic;

convert he missing data point segments to the activity segments and the trip segments; and

convert and join the activity segments and the trip segments.

11. A non-transent computer readable medium comprising the software executed by the hardware to perform the steps of the method of claim 1.

12. The method of claim 5, wherein the comparing of the activity data for the person to the received said list of logical addresses to select one said logical address of said merchant that corresponds to the activity data for the person is a function selected from a group consisting of:

a function to select a courier;

from whom a delivery to the person is to be made; and

to whom a probable location of the person at a predicted time is to be made known as derived from the activity data for the person; and

a function to select a retailer from whom incoming retail “

sale ”

information will be received at the mobile device for the person when the person is within a probable predetermined distance from a location of a store of the retailer at a predicted time when the person activity data for the person includes the activity of shopping as derived from the activity data for the person.

16. The method as defined in claim 1, wherein the person-based location data received from the mobile device further comprises physiological person-based data for the person.

17. The Method as defined in claim 16, wherein the one said message transmitted to the mobile device further corresponds to the physiological person-based data for the person.

18. The method as defined in claim 16, wherein the physiological person-based data for the person is selected from a group consisting of:

a heart-rate for the person;

a blood glucose measurement for the person;

a physical activity level for the person (via accelerometer);

an ambient environmental condition for the person; and

a combination of the foregoing.

19. The method as defined in claim 18, wherein the ambient environmental condition for the person for the person is selected from a group consisting of:

an ambient air quality for the person; and

an ambient weather condition for the person; and

a combination of the foregoing.

20. The method as defined in claim 16, wherein the one said message transmitted to the mobile device includes information for the person selected from a group consisting of:

timely delivery of medication for the person;

timely physiological measurement for the person; and

a combination of the foregoing.

21. The method as defined in claim 16, wherein the one said message transmitted to the mobile device includes information for the person selected from a group consisting of:

a blood glucose level measurement for the person;

a remedial action as a function of the blood glucose level measurement for the person; and

a combination of the foregoing.

13. In a message delivery system having a plurality of messages to transmit to a plurality of persons each having attributes of person-based location data and a mobile device with positional co-ordinates communications functionality, a method comprising a plurality of steps each being performed by hardware executing software, wherein the steps, for each said person, include:

receiving the person-based location data, including the positional co-ordinates, from the mobile device;

processing, using an activity detection means, the person-based location data in accordance with an activity detection algorithm that uses;

missing datapoint segments;

activity segments; and

trip segments, wherein the activity detection algorithm;

is probabilistic;

converts the missing data point segments to the activity segments and the trip segments; and

converts and joins the activity segments and the trip segments;

converting the processed person-based location data into activity data in accordance with principles customized to the person, wherein the activity data for the person includes one or more of;

person-based activities;

attributes of the person-based activities; and

predicted activity generated to predict at least the location of the person by one or more of the following;

utilizing a historical track of the processed person-based location data; and

handling and interpreting of signal losses from the mobile device occurring on an approach to, or within, one or more buildings as are proximal to the positional co-ordinates received from the mobile device by refining, joining or converting the signal losses to identify the person'"'"'s;

activities;

stops;

trips; and

movements; and

transmitting one said message to the mobile device that corresponds to the activity data for the person, wherein the one said message contains an offer from a merchant that;

pertaining to an activity being engaged by the person and corresponding to the activity data for the person; and

corresponds to a location proximal the positional co-ordinates received from the mobile device.

14. The method of claim 13, wherein the processing, using the activity detection means, of the person-based location data in accordance with the activity detection algorithm comprises:

initial classification of the person-based location data according to one or more of;

missing datapoint segments;

activity segments; and

trip segments;

generation of summary statistics for;

missing datapoint segments;

activity segments; and

trip segments; and

refinement, according to one or more activity-based rubs and/or parameters, in accordance with the activity detection algorithm, of;

missing datapoint segments;

activity segments; and

trip segments;

wherein the activity-based rules and/or parameters;

are probabilistic;

convert the missing data point segments to the activity segments and the trip segments; and

convert and join the activity segments and the trip segments.

15. A non-transient computer readable medium comprising the software executed by the hardware to perform the steps of the method of claim 13.