Assigning, monitoring and displaying respective statuses of subjects in a cashier-less store

Abstract

A method is provided for monitoring status of subjects in an area for a system including a first data set identifying locations of subjects, a second data set identifying events in the area, and a third data set identifying whether accounts matched to the subjects exist. The method includes executing a graphical user interface including a map of at least part of the area including avatars identifying locations of subjects located on the map, and representing respective statuses assigned to the subjects located on the map, the statuses being assigned to the subjects based on one or more of the first, second and third data sets, wherein the assigning of the respective statuses to the subjects are assigned by utilizing at least one of the first, second and third data sets to determine that at least one subject of the subjects is a high risk of loss subject.

What is claimed is: 
     
         1 . A method for monitoring status of subjects in an area of real space for a system including a first data set identifying locations of subjects in the area of real space over time, a second data set identifying events in the area of real space related to the subjects, and a third data set identifying whether accounts matched to the subjects exist, the method including:
 executing a graphical user interface on a display at a monitoring node, the graphical user interface including a map of at least part of the area of real space including avatars identifying locations of subjects located on the map; and   representing respective statuses assigned to the subjects located on the map, the statuses being assigned to the subjects based on one or more of the first data set, the second data set and the third data set,   wherein the assigning of the respective statuses to the subjects are assigned by utilizing at least one of the first data set, the second data set and the third data set to determine that at least one subject of the subjects is a high risk of loss subject.   
     
     
         2 . The method of  claim 1 , wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set and the third data set to determine that at least one subject of the subjects is to be approached before they exit the area of real space. 
     
     
         3 . The method of  claim 1 , wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set and the third data set to identify at least one subject of the subjects as an employee. 
     
     
         4 . The method of  claim 1 , wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set and the third data set to determine that a subject, of the subjects, corresponding to an identified account was previously not correctly charged for an item. 
     
     
         5 . The method of  claim 1 , wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set and the third data set to determine that a subject, of the subjects, corresponding to an identified account was not previously charged for an item taken from the area of real space after a previous visit to the area of real space. 
     
     
         6 . The method of  claim 1 , wherein the assigning of the respective statuses further includes displaying a video feed of the high risk of loss subject upon identification of the high risk of loss subject. 
     
     
         7 . The method of  claim 1 , wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set and the third data set to determine whether a subject of the subjects is near a kiosk. 
     
     
         8 . The method of  claim 1 , wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set and the third data set to determine whether a subject, of the subjects, corresponding to an identified account has payment information stored in association with the identified account. 
     
     
         9 . The method of  claim 1 , wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set and the third data set to determine a confidence level of an identification of a subject of the subjects. 
     
     
         10 . The method of  claim 1 ,
 wherein the system further includes a fourth data set identifying an item in a cart or basket of a subject of the subjects, and   wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set, the third data set and the fourth data set to determine a confidence level of the identification of the item.   
     
     
         11 . The method of  claim 1 ,
 wherein the system further includes a fourth data set identifying an item in a hand of a subject of the subjects and an interaction time of the subject interacting with the item, and   wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set, the third data set and the fourth data set to determine that the subject needs attention.   
     
     
         12 . The method of  claim 1 ,
 wherein the system further includes a fourth data set identifying an item in possession of a subject of the subjects, and   wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set, the third data set and the fourth data set to determine that the subject poses a security risk because of the identified item.   
     
     
         13 . The method of  claim 1 , wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set and the third data set to determine that a subject of the subjects has been stationary for a period of time and requires attention from an employee. 
     
     
         14 . The method of  claim 1 ,
 wherein the system further includes a fourth data set identifying an item at a location on a shelf, as placed at the location by a subject of the subjects, and   wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set, the third data set and the fourth data set to determine that the location on the shelf is an incorrect location for the item.   
     
     
         15 . The method of  claim 1 ,
 wherein the system further includes a fourth data set identifying multiple items in a hand or hands of a subject of the subjects, and   wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set, the third data set and the fourth data set to determine that the subject needs attention.   
     
     
         16 . The method of  claim 1 ,
 wherein the system further includes a fourth data set identifying a subject of the subjects interacting with an environment, other than purchasable items, in the area of real space, and   wherein the assigning of the respective statuses further includes utilizing at least one of the first data set, the second data set, the third data set and the fourth data set to determine that the subject needs attention.   
     
     
         17 . The method of  claim 1 , further comprising responding to user input produced by interaction with the display to launch procedures linked to locations on the display or content of the display at the time of the user input. 
     
     
         18 . The method of  claim 1 , further comprising generating an alert as a function of an assigned status. 
     
     
         19 . A system for monitoring status of subjects in an area of real space, comprising:
 a processing system, including a display and having access to memory storing a first data set identifying locations of subjects in the area of real space over time, a second data set identifying events in the area of real space related to the subjects, and a third data set identifying whether accounts matched to the subjects exist; and   a graphical user interface that renders, on the display, a map representing at least part of the area of real space, the rendered map including avatars (i) having locations on the map corresponding to locations in the area of real space according to the first data set and (ii) identifying respective statuses assigned to the subjects based on one or more of the first data set, the second data set and the third data set,   wherein the processing system includes or has access to logic that assigns the respective statuses to the subjects, the logic including:
 logic that utilizes at least one of the first data set, the second data set and the third data set to determine that at least one subject of the subjects is a high risk of loss subject. 
   
     
     
         20 . A non-transitory computer readable storage medium impressed with computer program instructions to monitor status of subjects in an area of real space for a system including a first data set identifying locations of subjects in the area of real space over time, a second data set identifying events in the area of real space related to the subjects, and a third data set identifying whether accounts matched to the subjects exist, the instructions, when executed on a processor, implement a method comprising:
 executing a graphical user interface on a display at a monitoring node, the graphical user interface including a map of at least part of the area of real space including avatars identifying locations of subjects located on the map; and   representing respective statuses assigned to the subjects located on the map, the statuses being assigned to the subjects based on one or more of the first data set, the second data set and the third data set,   wherein the assigning of the respective statuses to the subjects are assigned:
 utilizing at least one of the first data set, the second data set and the third data set to determine that at least one subject of the subjects is a high risk of loss subject.