Venue traffic flow management

• US 10,438,141 B2
• Filed: 06/15/2018
• Issued: 10/08/2019
• Est. Priority Date: 11/30/2016
• Status: Active Grant

• Current Assignee: Blazer And Flip Flops, Inc.
• Original Assignee: Blazer And Flip Flops, Inc.
• Inventors: Sahadi, Scott
• Primary Examiner(s): Hong, Dung
• Application Number:
  US16/010,349
• Publication Number:
  US 20180349808A1
• Time in Patent Office: 480 Days
• CPC Class Codes: G06Q 10/02 Reservations, e.g. for tickets, services or events
• CPC Class Codes: G06Q 10/047 Optimisation of routes or paths, e.g. travelling salesman problem
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 50/14 Travel agencies
• CPC Class Codes: G07C 11/00 Arrangements, systems or apparatus for checking, e.g. the occurrence of a condition, not provided for elsewhere
• CPC Class Codes: G07C 2011/04 related to queuing systems
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences

Abstract

A platform provides recommendations for points of interest in a venue to venue attendees. Different points of interest are recommended in different amounts in order to prevent congestion in the venue in the form of extremely long queues or extremely large crowds. To achieve this, the platform divides a large group of venue attendees into multiple sub-groups, with each sub-group being recommended a different point of interest, and the size of each sub-group based on a difference between an optimal queue or crowd size and an actual queue or crowd size of a queue or crowd associated with that point of interest.

Claims

1. A computer-implemented method for itinerary personalization for a plurality of venue attendees in a predetermined venue area, the method comprising:

identifying a number of venue attendees in the plurality of venue attendees;

receiving locations of a plurality of attendee mobile devices corresponding to the plurality of venue attendees;

retrieving locations of a plurality of points of interest located within the predetermined venue area, wherein each of the plurality of points of interest corresponds to a queue of a plurality of queues;

identifying a plurality of queue sizes by identifying a queue size of each queue of the plurality of queues;

calculating an optimal queue size to be an average queue size based on a sum of the plurality of queue sizes and the number of venue attendees in the plurality of venue attendees;

dividing the plurality of venue attendees into a plurality of groups based on the locations of the plurality of attendee mobile devices, wherein each group of the plurality of groups corresponds to one of the plurality of points of interest and to the queue corresponding to the point of interest, wherein a size of each group is based on a difference between the optimal queue size and the queue size of the queue corresponding to the group;

generating a plurality of recommendations, wherein each recommendation recommends one of the plurality of points of interests; and

sending the plurality of recommendations to the plurality of attendee mobile devices so that a different point of interest of the plurality of points of interest is recommended to each group of the plurality of groups based on the queue corresponding to the group.

2. The method of claim 1, wherein the optimal queue size is calculated by dividing the sum of the plurality of queue sizes and the number of venue attendees in the plurality of venue attendees by a number of queues in the plurality of queues.

3. The method of claim 1, wherein a size of a first group of the plurality of groups is the difference between the optimal queue size and the queue size of the queue corresponding to the first group, rounded up to the nearest integer value exceeding the difference.

4. The method of claim 1, wherein a size of a first group of the plurality of groups is the difference between the optimal queue size and the queue size of the queue corresponding to the first group, rounded down to the nearest integer value less than the difference.

5. The method of claim 1, wherein the size of each group is also based on minimizing foot traffic between the plurality of points of interest.

6. The method of claim 1, wherein at least one of the plurality of queues is a crowd.

7. The method of claim 1, wherein dividing the venue attendees into the plurality of groups is further based on the locations of each of the plurality of attendee mobile devices, such that a first venue attendee of the plurality of venue attendees is selected into a first group of the plurality of groups corresponding to a first point of interest of the plurality of points of interest, wherein a location of a first attendee mobile device associated with the first venue attendee is located closer to the first point of interest than to a remainder of the plurality of points of interest other than the first point of interest, wherein the first attendee mobile device is one of the plurality of attendee mobile devices.

8. The method of claim 1, wherein a location of a first attendee mobile device of the plurality of attendee mobile devices is identified using one or more Global Navigation Satellite System (GNSS) receivers of the first attendee mobile device.

9. The method of claim 1, wherein a location of a first attendee mobile device of the plurality of attendee mobile devices is identified based on the first attendee mobile device being in range of a short-range wireless signal source.

10. The method of claim 1, wherein the average queue size is a mean queue size.

11. The method of claim 1, further comprising:

identifying an additional point of interest other than the plurality of points of interest, the additional point of interest corresponding to an additional queue other than the plurality of queues;

calculating a second average queue size based on a sum of the plurality of queue sizes, an additional queue size corresponding to the additional queue, and the number of venue attendees in the plurality of venue attendees; and

identifying that the second average queue is not optimal because the additional queue size corresponding to the additional queue is greater than the second average queue size.

12. A system for itinerary personalization for a plurality of venue attendees in a predetermined venue area, the system comprising:

a memory that stores instructions, locations of a plurality of attendee mobile devices corresponding to the plurality of venue attendees, and locations of a plurality of points of interest located within the predetermined venue area, wherein each of the plurality of points of interest corresponds to a queue of a plurality of queues; and

a processor, wherein execution of the instructions by the processor causes the processor to;

identify a number of venue attendees in the plurality of venue attendees,

identify a plurality of queue sizes, wherein each queue of the plurality of queues corresponds to a queue size of the plurality of queue sizes,

calculate an optimal queue size to be an average queue size based on a sum of the plurality of queue sizes and the number of venue attendees in the plurality of venue attendees,

divide the plurality of venue attendees into a plurality of groups based on the locations of the plurality of attendee mobile devices, wherein each group of the plurality of groups corresponds to a queue of the plurality of queues and wherein a size of the group is based on a difference between the optimal queue size and the queue size corresponding to the queue, and

generate a plurality of recommendations, wherein each recommendation recommends one of the plurality of points of interests; and

a communication transceiver that sends the plurality of recommendations to the plurality of attendee mobile devices so that a different point of interest of the plurality of points of interest is recommended to each group of the plurality of groups based on the queue corresponding to the group.

13. The system of claim 12, wherein at least one of the plurality of queues is a crowd.

14. The system of claim 12, wherein dividing the venue attendees into the plurality of groups is further based on the locations of each of the plurality of attendee mobile devices, such that a first venue attendee of the plurality of venue attendees is selected into a first group of the plurality of groups corresponding to a first point of interest of the plurality of points of interest, wherein a location of a first attendee mobile device associated with the first venue attendee is located closer to the first point of interest than to a remainder of the plurality of points of interest other than the first point of interest, wherein the first attendee mobile device is one of the plurality of attendee mobile devices.

15. The system of claim 12, further comprising a beacon that emits a short-range wireless signal, wherein a location of a first attendee mobile device of the plurality of attendee mobile devices is identified based on the first attendee mobile device being in range of a short-range wireless signal source.

16. A method for itinerary personalization for a plurality of venue attendees in a predetermined venue area, the method comprising:

identifying a number of venue attendees in the plurality of venue attendees;

receiving, locations of a plurality of attendee mobile devices corresponding to the plurality of venue attendees;

retrieving locations of a plurality of points of interest located within the predetermined venue area;

identifying a plurality of crowd sizes, wherein each of a plurality of crowds located within the predetermined venue area corresponds to one of the plurality of crowd sizes;

calculating an optimal crowd size to be an average crowd size based on a sum of the plurality of crowd sizes and the number of venue attendees in the plurality of venue attendees;

dividing the plurality of venue attendees into a plurality of groups based on the locations of the plurality of attendee mobile devices, wherein each group of the plurality of groups corresponds to a point of interest of the plurality of points of interest and wherein a size of the group is based on a crowd of the plurality of crowds appearing along at least one path to from the group to the point of interest and wherein a size of the group is based on a difference between the optimal crowd size and the crowd size corresponding to the crowd;

generating a plurality of recommendations, wherein each recommendation recommends one of the plurality of points of interests; and

sending the plurality of recommendations to the plurality of attendee mobile devices so that a different point of interest of the plurality of points of interest is recommended to each group of the plurality of groups based on the point of interest corresponding to the group.

17. The method of claim 16, wherein at least one of the plurality of crowds is a queue.

18. The method of claim 16, wherein a size of a first group of the plurality of groups is the difference between the optimal crowd size and the crowd size of the crowd corresponding to the first group, rounded up to the nearest integer value exceeding the difference.

19. The method of claim 16, wherein a size of a first group of the plurality of groups is the difference between the optimal crowd size and the crowd size of the crowd corresponding to the first group, rounded down to the nearest integer value less than the difference.