System and method for determining the occurrence of organized athletic events

• US 10,068,004 B2
• Filed: 07/10/2015
• Issued: 09/04/2018
• Est. Priority Date: 07/10/2015
• Status: Active Grant

• Current Assignee: Under Armour Incorporated
• Original Assignee: Under Armour Incorporated
• Inventors: Eastman, Kyler Maxwell
• Primary Examiner(s): Hylinski, Steven J
• Application Number:
  US14/796,196
• Publication Number:
  US 20170011040A1
• Time in Patent Office: 1,152 Days
• CPC Class Codes: A63B 2024/0025 Tracking the path or location of one or more users, e.g. players of a game
• CPC Class Codes: A63B 2024/0056 for statistical or strategic analysis
• CPC Class Codes: A63B 2024/0071 Distinction between different activities, movements, or kind of sports performed
• CPC Class Codes: A63B 2024/0081 Coaching or training aspects related to a group of users
• CPC Class Codes: A63B 24/0075 Means for generating exercise programs or schemes, e.g. computerized virtual trainer, e.g. using expert databases
• CPC Class Codes: A63B 24/0084 Exercising apparatus with means for competitions, e.g. virtual races
• CPC Class Codes: A63B 24/0087 Electric or electronic controls for exercising apparatus of groups A63B21/00 - A63B23/00, e.g. controlling load
• CPC Class Codes: G06F 16/287 Visualization; Browsing
• CPC Class Codes: G06Q 10/02 Reservations, e.g. for tickets, services or events
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

A method of identifying the occurrence of one or more organized athletic events including a plurality of participants is disclosed. The method includes receiving athletic activity data for the participants from a plurality of athletic activity monitoring devices carried by the participants. The received athletic activity data defines workouts performed by the participants. The method further includes defining a plurality of parameters for the athletic activity data, wherein the parameters define common athletic activity data for the participants of each of the organized athletic events. In addition, the method includes clustering the athletic activity data into one or more clusters of workouts based on the defined parameters for the athletic activity data. Furthermore, the method includes identifying the one or more organized athletic events based on the one or more clusters of workouts.

Claims

1. A method of identifying occurrence of one or more organized athletic events, each of the organized athletic events having a plurality of participants, the method comprising:

receiving athletic activity data for the participants from a plurality of activity monitoring devices carried by the participants, the athletic activity data defining workouts performed by the participants;

defining a plurality of parameters for the athletic activity data, the parameters defining common athletic activity data for the participants of each of the organized athletic events;

clustering the athletic activity data into one or more clusters of workouts based on the defined parameters for the athletic activity data;

identifying the one or more organized athletic events based on the one or more clusters of workouts; and

filtering the one or more organized athletic events to identify one or more relevant organized athletic events within a predetermined distance from a vendor.

2. The method of claim 1 wherein the received athletic activity data includes at least one of distance data, start location data, end location data, and start time data for each of the workouts.

3. The method of claim 2 wherein the plurality of parameters for the athletic activity data include at least one of a distance range, proximity of start location, proximity of end location, and proximity of start time.

4. The method of claim 1 further comprising identifying the participants of each of the one or more organized athletic events based on the clusters of workouts.

5. The method of claim 1 further comprising clustering the clusters of workouts based on an additional clustering parameter.

6. The method of claim 5 wherein the additional clustering parameter is a time parameter configured to remove duplicate identification of the one or more organized athletic events.

7. The method of claim 5 wherein the additional clustering parameter is a waypoint parameter configured to identify a route associated with the one or organized athletic events.

8. The method of claim 1 further comprising generating individual statistics for one of the participants of the one or more organized athletic events and sending those individual statistics to the one of the participants.

9. The method of claim 1 further comprising sending a message to the participants along with a vendor reward.

10. An arrangement for identifying occurrence of one or more organized athletic events, each of the organized athletic events having a plurality of participants, the arrangement comprising:

a plurality geo-position devices configured to be carried by the participants, each of the geo-position devices including at least one sensor configured to obtain athletic activity data for the participant, the athletic activity data defining a workout for the participant;

a database configured to store the athletic activity data; and

an activity data processing system configured to (i) cluster the athletic activity data into one or more clusters of workouts based on parameters for the athletic activity data, the parameters defining common athletic activity data for the participants, (ii) identify the one or more clusters of workouts as indicating existence of the one or more organized athletic events, (iii) filter the one or more organized athletic events to identify one or more relevant organized athletic events within a predetermined distance from a vendor, (iv) identify the participants of the one or more organized athletic events based on the one or more clusters of workouts, and (v) send the identified participants a message.

11. The arrangement of claim 10, wherein the athletic activity data includes one or more of distance data, start location data, end location data, and start time data for each of the workouts.

12. The arrangement of claim 11 wherein the parameters for the athletic activity data include a distance range, proximity of start location, proximity of end location, and proximity of start time.

13. The arrangement of claim 10 wherein the activity data processing system is further configured to cluster the clusters of workouts in order to remove duplicate identification for the one or more organized athletic events or to identify a route associated with the one or organized athletic events.

14. A non-transient computer readable medium containing instructions that when executed by a processor configure one or more computing devices for identifying one or more organized athletic events including a plurality of participants by:

receiving athletic activity data for the participants from a plurality of activity monitoring devices carried by the participants, the athletic activity data defining workouts performed by the participants;

clustering the athletic activity data into one or more clusters of workouts based on parameters for the athletic activity data, the parameters defining common athletic activity data for the participants;

identifying the one or more clusters of workouts as indicating the existence of the one or more organized athletic events;

filtering the one or more organized athletic events to identify one or more relevant organized athletic events within a predetermined distance from a vendor;

identifying the participants of the organized athletic event based on the one or more clusters of workouts, and

sending the participants a message.

15. The computer readable medium of claim 14, wherein the athletic activity data includes distance data, start location data, end location data, and start time data for each of the workouts.

16. The computer readable medium of claim 15 wherein the parameters for the athletic activity data include a distance range, proximity of start location, proximity of end location, and proximity of start time.

17. The computer readable medium of claim 14 further comprising clustering the clusters of workouts in order to remove duplicate identification for the organized athletic event or to identify a route associated with the one or organized athletic events.