System and method for tracking items at a scale of a self-checkout terminal
A system tracks items in the checkout area of a self-checkout terminal to reduce the likelihood of fraud in item substitution. The system includes a plurality of weight sensors operatively coupled to a checkout area for sensing a distributed weight of an item placed in a checkout area; and an item locator coupled to the plurality of weight sensors for determining a location for the item from the distributed weight as sensed by the sensors. The item locator identifies a location for an item from the weight differentials sensed at the weight sensors in response to movement of an item within the checkout area. The weight distribution and location data may be correlated to the item identifier for a scanned item so the items in the checkout area may be tracked. A security application program associated with the self-checkout terminal may be coupled to the system of the present invention to identify items placed on the checkout area by location as well as weight. As a consequence, the location of an item may be determined by the weight data detected by the sensors in response to an item being placed or removed in the checkout area. The location data for the items in the checkout area may be compared with stored location data for previously scanned items to determine whether another item has been substituted for a scanned item.
1. A method of tracking items in a self-checkout terminal having a bar code scanner and a weight scale, comprising:
scanning a first item with said bar code scanner so as to enter said first item into said self-checkout terminal;
placing said first item on a product support platform of said weight scale after said scanning step;
sensing a first distributed weight of said first item placed on said product support platform with a plurality of sensors and generating first distributed weight data in response thereto;
generating first location data based on said first distributed weight data, said first location data being indicative of location on said product support platform of said first item;
sensing a second distributed weight of a second item on said product support platform with said plurality of sensors and generating second distributed weight data in response thereto;
generating second location data based on said second distributed weight data, said second location data being indicative of location on said product support platform from which said second item was removed; and
in a case in which said second item has been removed from said product support platform, determining if said second location data and said first location data match.
2. The method of claim 1 , further comprising interrogating a user of said self-checkout terminal if said second location data does not match said first location data.
3. The method of claim 1 , further comprising correlating said first distributed weight data and said first location data to an item identifier so as to generate correlated item data.
4. The method of claim 3 further comprising:
providing said correlated item data to a security application associated with a terminal processor; and
using said correlated item data to track items in said self-checkout terminal.
5. The method of claim 1 further comprising:
receiving an item identifier from a processor associated with said self-checkout terminal; and
generating a data structure that correlates said item identifier with said first distributed weight data and said first location data.
6. The method of claim 5 wherein said data structure includes a total weight for said first item.
7. The method of claim 1 wherein said first location data is Cartesian coordinate data.
8. The method of claim 1 wherein said first location data is polar coordinate data.
9. A method of tracking items in a self-checkout terminal having a bar code scanner, a weight scale, and a memory, comprising:
sensing a distributed weight of an item on said product support platform with a plurality of sensors and generating distributed weight data in response thereto;
generating location data based on said distributed weight data, said location data being indicative of location on said product support platform from which said item was removed; and
in a case in which said item has been removed from said product support platform, comparing said location data to other location data stored in said memory, said other location data being indicative of location of items positioned on said product support platform that have been previously scanned in said self-checkout terminal with said bar code scanner.
10. The method of claim 9 , further comprising interrogating a user of said self-checkout terminal if said location data of said item does not match any of said other location data stored in said memory.
11. The method of claim 9 wherein said location data is Cartesian coordinate data.
12. The method of claim 9 wherein said location data is polar coordinate data.
13. A method of tracking items in a self-checkout terminal having a bar code scanner and a weight scale, comprising:
scanning an item with said bar code scanner so as to enter said item into said self-checkout terminal;
placing said item on a product support platform of said weight scale after said scanning step;
sensing a distributed weight of said item placed on said product support platform with a plurality of sensors and generating distributed weight data in response thereto;
generating location data based on said distributed weight data, said location data being indicative of location on said product support platform of said item; and
using said location data to detect movement of said item within said self-service checkout terminal.
14. The method of claim 13 , further comprising correlating said distributed weight data and said location data to an item identifier so as to generate correlated item data.
15. The method of claim 14 further comprising:
providing said correlated item data to a security application associated with a terminal processor; and
using said correlated item data to track said item in said self-checkout terminal.
16. The method of claim 13 further comprising:
receiving an item identifier from a processor associated with said self-checkout terminal; and
generating a data structure that correlates said item identifier with said distributed weight data and said location data.
17. The method of claim 16 wherein said data structure includes a total weight for said item.
18. The method of claim 13 wherein said location data is Cartesian coordinate data.
19. The method of claim 13 wherein said location data is polar coordinate data.