Browse Prior Art Database

Method and System for Detecting Behavior of a Group of People at an Event

IP.com Disclosure Number: IPCOM000247236D
Publication Date: 2016-Aug-17
Document File: 2 page(s) / 21K

Publishing Venue

The IP.com Prior Art Database

Abstract

A method and system is disclosed for detecting behavior of a group of people at an event.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 51% of the total text.

Page 01 of 2

Method and System for Detecting Behavior of a Group of People at an Event

Disclosed is a method and system for detecting behavior of a group of people at an event. The method and system detects transactions in real-time from actions of the group of people at the event and identifies a sentiment or possible outcomes of the transactions. Then, the method and system sends an alert to an event staff to take corrective actions for possible outcomes.

The method and system tracks transactions by monitoring actions of a group of people at an event. The actions include such as but not limited to buying candies, popcorn, beer, hotdog, apparel and using restrooms.

Once the transactions are tracked, the method and system allows a point of sale (PoS) system to correlate the transactions with a seating information. In order to correlate the transactions with the seating information, the PoS system scans a printed ticket of the group of people or asks the group of people to input the seating information. For the transactions using a mobile application, the PoS receives the seating information and a payment information from the mobile application. For the transactions with a credit card, the PoS system pulls names of the group of the people and correlates with the seating information.

Once the transactions are correlated with the seating information, the method and system groups the transactions into buckets based on a type of transaction such as but not limited to popcorn, candies, beer, hotdog and apparel. Then, the method and system continuously monitors the buckets to identify a type of intersection between the buckets that provides information about an amount of transaction associated with the type of transaction at a particular location in the event. Based on the type of the intersec...