Systems and methods for verifying machine-readable label associated with merchandise

1. A system for verifying a machine-readable label, comprising:

a scan table processing device comprising:

a first input for receiving a list of items with machine-readable labels;

a second input for receiving a list of stores that have an inventory of the items in the list of items and that have at least one sensing device for capturing images of the items, the captured images including a timestamp; and

an output that includes a plurality of electronic records, wherein each electronic record includes a time and location of a scan operation performed on at least one machine-readable label of the machine-readable labels;

a data repository that stores the captured images of the items and that updates the plurality of electronic records with index values to associate the captured images with a portion of the plurality of electronic records based on the time and location of the scan operation and the timestamp of the captured images;

a graphical user interface (GUI) processing apparatus that modifies the captured images in preparation for training an artificial intelligence apparatus to identify the items in the images; and

a machine language (ML) model processor that determines whether the modified images generated for training the artificial intelligence apparatus are correctly identified using the machine-readable labels associated with the items, including by generating a scan accuracy score.

2. The system of claim 1 , wherein the list of items includes items of interest that are identified as being at risk of theft.

3. The system of claim 1 , wherein a record for each of the list of stores includes a unique facility identifier and information about sensors available for generating images of items of interest of the list of items.

4. The system of claim 1 , wherein the output of the scan table processing device includes a table comprising a plurality of data records, which includes at least one of a store identification, a time of the scan operation performed on the at least one machine-readable label, and an identification of a checkout register where the scan operation is performed.

5. The system of claim 1 , wherein the output of the scan table processor includes a time stamp that identifies an image from a video feed taken of an item of interest at a store of the list of stores that is of interest with respect to confirming whether a machine-readable label is associated with a correct item.

6. The system of claim 1 , wherein the GUI processing apparatus compares the captured images and positively identified images of the items to determine whether the captured images are qualified for input to the artificial intelligence apparatus.

7. The system of claim 1 , wherein the artificial intelligence apparatus includes a trained neural network that recognizes a scanning apparatus that performs a scan operation performed on the at least one machine-readable label to distinguish the scanning apparatus from the item at which the at least one machine-readable label is located.

8. The system of claim 1 , wherein the ML model processor generates an event in response to a determination that the machine-readable label is associated with an incorrect item at which the at least one machine-readable label is located.

9. The system of claim 1 , further comprising:

a listing of a plurality of stores that have an item of interest identified by contents of a machine-readable label affixed to the item;

a label processing apparatus that compares the machine-readable label affixed to the item and a valid image of the item to train a neural network; and

the machine learning (ML) processor that identifies the image of the item to which the machine-readable label is affixed.

10. The system of claim 9 , wherein the listing includes a time stamp that identifies when the item of interest was scanned, identifies a store of the plurality of stores, an identification of a register at the identified store where the item is scanned, and an index value that provides an electronic storage location of an image generated at a day and time stated in the time stamp.

11. The system of claim 9 , wherein a record for each of the stores includes a unique facility identifier and information about sensors available for generating images of items of interest of the listing.

12. The system of claim 1 , wherein the GUI processing apparatus compares the captured images and positively identified images of the items in the images to determine whether the captured images are qualified for input to the artificial intelligence apparatus.

13. The system of claim 1 , wherein the artificial intelligence apparatus includes a trained neural network that recognizes a scanning apparatus that performs a scan operation performed on the at least one machine-readable label to distinguish the scanning apparatus from the item at which the at least one machine-readable label is located.

14. A method for verifying a machine-readable label, the method comprising:

receiving, as a first input, a list of items with machine-readable labels;

receiving, as a second input, a list of stores that have an inventory of the items in the received list of items and that have at least one sensing device for capturing images of the items, the captured images including a timestamp;

storing the captured images of the items;

generating an output that includes a plurality of electronic records, wherein each electronic record includes a time and location of a scan operation performed on at least one machine-readable label of the machine-readable labels;

updating the plurality of electronic records with index values to associate the captured images with a portion of the plurality of electronic records based on the time and location of the scan operation and the timestamp of the captured images;

modifying the captured images in preparing for training an artificial intelligence apparatus to identify the items in the images; and

determining whether the modified images generated for training the artificial intelligence apparatus are correctly identified using the machine-readable labels associated with the items, including by generating a scan accuracy score.

15. The method of claim 14 , wherein a record for each store of the list of stores includes a unique facility identifier and information about sensors available for generating images of items of interest of the list of items.

16. The method of claim 14 , wherein the generated output further includes a table comprising a plurality of data records, which includes at least one of a store identification, a time of the scan operation performed on the at least one machine-readable label, and an identification of a checkout register where the scan operation is performed.

17. The method of claim 14 , wherein the generated output further includes a time stamp that identifies an image from a video feed taken of an item of interest at a store of the list of stores that is of interest with respect to confirming whether a machine-readable label is associated with a correct item.

18. The method of claim 14 , further comprising:

generating an event in response to a determination that the machine-readable label is associated with an incorrect item at which the at least one machine-readable label is located.