Abstract: In frictionless shopping environments, there may be a variety of age-restricted products. Shopping areas within the frictionless shopping environment can include one or more smart shelving units that have various restricted areas to house these age-restricted products. These restricted areas can be locking cabinets or other method of preventing any customer from grabbing the products. The frictionless shopping environment can comprise customer tracking and matching to customer data within an enrollment server or other device that can include a verified age associated with a customer that can be utilized to provide access to one or more age restricted products. Verification can occur via scanning of identification cards which can be processed by image processing methods or via a human review. Once verified, the customer can be matched and tracked within a frictionless shopping area and provide automatic access to age-restricted products either by customer location, voice request, or time period.

Abstract: An automated inventory intelligence system and methods are provided for authenticating identities of customers to facilitate expedited user purchases. The automated inventory intelligence system includes a facial recognition logic for analyzing one or more captured images of a customer, and a voice recognition logic for analyzing voice samples. Customers may be identified using customer matching logic. The facial recognition logic receives multiple views of the customer with a multiplicity of facial recognition cameras coupled with a retail shelving unit. The voice recognition module receives multiple voice samples with a multiplicity of microphones that may be coupled with the retail shelving unit. Customers may be matched with a corresponding customer account to facilitate purchases at the shelving unit based on payment information associated with the customer account.

Abstract: A smart store management tool and methods are provided for enabling a user to design and stock an entire store. The smart store management tool may include a store builder that enables the user to use familiar techniques to create a layout of the entire retail store, as well as organize locations of gondolas and inventory within the store. A whole-store view comprising the smart store management tool may be configured to show locations and current stock of inventory within the store and enables the user to view the current status of inventory at specific locations within the store. An inventory analysis view comprising the smart store management tool may be configured to show the locations and current stock of inventory on a specific gondola or shelf that is selected by the user in the whole-store view.

Abstract: An automated inventory intelligence system and method are provided for tracking the positions of the retail products as they are moved around on a retail shelf. The automated inventory intelligence system includes a dynamic planogram, or dynamogram, that reflects the existing state of inventory on the shelf, thereby enabling the automated inventory intelligence system to automatically and intelligently determine the amount of inventory stocked on the shelf as well as tracking correct pricing information for misplaced inventory items. As such, the dynamogram is configured to enable the automated inventory intelligence system to provide a frictionless shopping environment when products are moved elsewhere by customers.

Abstract: Data elements from an input document can be automatically organized into rows and columns in a structured output document using a grouping process that automatically applies matching criteria based on horizontal position, data content and horizontal extent and tests for horizontal overlaps between data elements and neighbors of data elements in existing groups, assigns columns to those groups based on horizontal positions of data elements from groups that have already been assigned to columns. Rows may be assigned to data elements based on those data elements' vertical positions.

Abstract: Data elements from an input document can be automatically organized into rows and columns in a structured output document using a grouping process that automatically applies matching criteria based on horizontal position, data content and horizontal extent and tests for horizontal overlaps between data elements and neighbors of data elements in existing groups, assigns columns to those groups based on horizontal positions of data elements from groups that have already been assigned to columns. Rows may be assigned to data elements based on those data elements' vertical positions.