Blazer and Flip Flops, Inc.

Scott Sahadi

Benjamin Harry Ziskind

Joshua David Bass

Benjamin Keeling Mathews

Jannis Raye Brea

Matthias Oberdorfer

A platform identifies that a first venue attendee is similar to a second venue attendee based on at least one shared trait. The platform identifies an indicator of positivity about a particular point of interest corresponding to the second venue attendee. The platform selects the particular point of interest as a recommended point of interest for the first venue attendee based on the similarity between the first venue attendee and the second venue attendee and the indicator of positivity about the particular point of interest corresponding to the second venue attendee.

Venue recommendations based on shared guest traits

An estimate is provided for how long a guest will have to wait to enter a ride, restaurant, restroom, or other point of interest at a venue. Wait times are computed using one or more algorithms (e.g., Bayesian) that can combine direct measurements around the point of interest, historical measurements around the point of interest, and measurements taken from other systems not directly connected to the point of interest. Supporting systems will vary by venue and may include entry ticketing systems, network traffic, point of sale registers, event schedules, and proximity detectors in other parts of the venue. By comparing probabilities generated from this disparate data, current and future wait times can be estimated and provided to front-end devices corresponding to guests or staff.

Intelligent prediction of queue wait times

A platform generates a current path of a venue attendee based on the venue attendee's recorded location data. The platform also generates a suggested path for the venue attendee from the venue attendee's location to the point of interest. The platform identifies a dissimilarity between the current path of the venue attendee and the suggested path for the venue attendee, and based on identification of this dissimilarity, sends an alert to a venue staff member who is near the venue attendee.

Assisted venue staff guidance

Journey information is mapped by first identifying an acceptable trigger condition type, such as a photo trigger condition type, of a plurality of trigger condition types. Once a journey has begun, a trigger condition of the acceptable trigger condition type may be detected at a mobile computing device, for example when the mobile computing device captures a photo. A location of the mobile computing device is then identified in response to the detection of the trigger condition, and a marker is placed on a map identifying the location. The marker is also associated with data associated with the trigger condition, for example by allowing the photo captured by the mobile computing device to be viewable at the marker.

Dynamic journey mapping and recordkeeping

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.

Venue traffic flow management

A platform generates a personalized itinerary and corresponding map for a user within a venue. The personalized itinerary includes at least one recommended point of interest, the recommendation generated based on a location of the recommended point of interest relative to a location of the user, and based on a comparison between user profile information concerning the user and point of interest information concerning the recommended point of interest.

Personalized itinerary generation and mapping system

An application server may receive, from an administrative console, a message and a targeting specification. The targeting specification identifies at least one trait (e.g., ticket type, age, gender) shared by a group of targeted venue guests. The group of targeted venue guests is a subset of the plurality of venue guests of a venue. The application server then uses information obtained from venue guest devices corresponding to venue guests to identify who belongs to the group targeted venue guests as well as their corresponding targeted venue guest devices. The application server then transmits a message to the targeted venue guest devices. The message may further be transmitted according to a schedule set or triggers by the administrator console. The schedule may identify dates and times within which messages should be sent, while the triggers may identify locations that may trigger messages.

Targeted venue message distribution

A system to improve end-user monetization in a captive audience environment is disclosed. Mobile and wearable users may be engaged by way of contextual and perishable messaging. Such messaging is dynamically updated and maintained to provide a unique messaging experience which increases monetization opportunities, which may utilize location based technologies.

Venue guest device message prioritization

A web service platform to improve end-user engagement in a captive audience environment. Mobile and web-based clients allow application users to authorize and approve usage of entitlements of other users, including their children, based upon preconfigured rules and the proximity between the user requesting and the user approving authorization to use the entitlement.

Parental controls

Once a proximity beacon is installed within a venue, mobile devices receive signals transmitted by the proximity beacon. These mobile devices then report their own locations to an application server. These mobile devices also report a signal strength to the application server, the signal strength associated with the signal from the proximity beacon. The application server determines the location of the proximity beacon by triangulating based on the locations of the mobile devices and on the signal strengths from the mobile devices. The location of the proximity beacon is then transmitted to a front-end device that then displays the location of the proximity beacon on a map along with other locations of other proximity beacons. The map may also display range areas and battery levels of the proximity beacon, and any other data that can be gathered by the application server from the mobile devices or the proximity beacon.

Map based beacon management

A wearable device associated with a guest in a venue stores a unique identification code. The unique identification code may correspond to guest information stored at one or more guest information servers. The guest information may include ticket information, room entitlements, vouchers, payment information, credit card information, or folio information. The wearable device transmits unique identification code to a venue scanner associated with a venue device. The venue device may obtain access to at least some of the guest information based on receipt of the unique identification code. The wearable device also includes a light source that may indicate a status of the guest or of the wearable device based on the colors and/or the blinking patterns emitted by the light source. The light source may, for example, indicate a guest's access permissions to portions of the venue.

Growing community of inventors

Solana Beach, CA, United States of America

Scott Sahadi