Blazer and Flip Flops, Inc.

Blazer and Flip Flops, Inc. Dba the Experience Engine, Inc.

Benjamin Keeling Mathews

Scott Sahadi

Benjamin Harry Ziskind

Joshua David Bass

Matthias Oberdorfer

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

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

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.

Growing community of inventors

Orlando, FL, United States of America

Benjamin Keeling Mathews