A system and method for a vending machine is provided. One embodiment has a user interface configured to receive a plurality of user selections of a plurality of food products of interest from the user; a robotic system configured to transport a container to a plurality of food tanks to receive food products dispensed from selected ones of the plurality of food tanks, wherein a unique machine readable code is printed on an outside surface of at least one of the container and a container seal; and a scanner configured to scan the machine readable code. Wherein prior to delivery of the container with the machine readable code, the controller system controls the robotic system so that the scanner acquires the machine readable code, and wherein the controller system associates at least food product information with the received machine readable code information.

A method of auxiliary data capture control includes: storing, at a data capture device, (i) detection criteria corresponding to events having respective event identifiers; and (ii) a registration indicator associated with at least one of the event identifiers; controlling a primary data capture sensor to obtain primary captured data; in response to detecting, based on the primary captured data, that the detection criteria are satisfied for a detected one of the event identifiers, determining whether the registration indicator is associated with the detected event identifier; and when the registration indicator is associated with the detected event identifier, controlling an auxiliary data capture sensor to obtain auxiliary captured data.

In some embodiments, a user device may detect, via pattern recognition by a user application, a pattern (indicative of a given code type) presented on a physical object. The user device may cause, via the user application, a code scanning application to be launched based on the detection to scan the pattern. The user device may obtain, via the user application, a code (associated with a biller entity) of the given code type from the code scanning application based on the code scanning application's scan. The user device may cause, via the user application, the code or information derived from the code to be provided over the Internet to a computer system hosting accounts of a user of the user application. The code or the derived information may be used by the computer system to complete transactions between the biller entity and at least one of the accounts.

A machine-learning algorithm is trained with features relevant to basket data for items of transactions. The trained algorithm is trained to predict whether a given transaction is more or less likely to be associated with theft being engaged in by a transaction operator for the transaction. The trained algorithm is then provided basket data for a given transaction and produces as output a theft prediction value. When the theft prediction value exceeds a configured threshold value, the transaction is flagged for manual intervention or the transaction is flagged for subsequent manual verification.

An automated system/method for identifying and enabling viewer selection/purchase of products or services associated with digital content presented on a display device. Products within the digital content are identified and existing product placement data is ascertained. For products that do not include such data, other methodologies, with the assistance of third-party servers, are employed to assess identity and purchase availability. Viewer input designate products to assess or products can be automatically assessed. Viewers initiate purchase of identified products via the display device or other electronic devices controlled by viewers, such as via viewers' smart phones. Various processes for identifying products include use of AI processing, access to data on third-party servers, crowd sourcing and other methodologies. Various techniques for selecting products for purchases are employed including employing 3D codes (e.g., QR codes) alongside presented products to enable other portable electronic devices to facilitate purchase. Other features are described.

Barcode readers and barcode reader assemblies with lift handles are disclosed herein. An example bioptic barcode reader assembly includes a barcode reader having a housing and a metal frame secured to the housing. A retractable first lift handle having an elongated first aperture is positioned on a first side of the housing and a retractable second lift handle having an elongated second aperture is positioned on a second side of the housing, opposite the first side. Each of the first and second lift handles is movable relative to the housing between a retracted position and an extended position and the first and second apertures in the first and second lift handles overlie a first center of gravity of the barcode reader and a second center of gravity of the barcode reader assembly.

Disclosed herein are systems and methods for determining whether an unknown product matches a scanned barcode during a checkout process. An edge computing device or other computer system can receive, from an overhead camera at a checkout lane, image data of an unknown product that is placed on a flatbed scanning area, identify candidate product identifications for the unknown product based on applying a classification model and/or product identification models to the image data, and determine based on the candidate product identifications, whether the unknown product matches a product associated with a barcode that is scanned at a POS terminal in the checkout lane. The classification model can be used to determine n-dimensional space feature values for the unknown product and determine which product the unknown product likely matches. The product identification models can be used to determine whether the unknown product is one of the products that are modeled.

A system includes a server and merchant device. The server receives product information for a product scanned by a mobile device. The server stores the product information for the product in a digital cart. The server receives a transaction request from the mobile device, determines that the product is associated with a validation requirement, and transmits a validation request to the merchant device. The server receives, from the merchant device, an indication that the validation requirement is satisfied, processes a transaction, and transmits, to the merchant device, an indication that the transaction is complete. The merchant device receives the validation request, determines that the validation requirement is satisfied, and transmits the indication that the validation requirement is satisfied to the server. The merchant device receives, from the server, the indication that the transaction is complete and displays the indication that the transaction on the display.

A scanner apparatus (1A) includes: a housing (11); a hand scanner (20); and a hand scanner holder (30) attached to a side of the housing (11) and configured to hold the hand scanner (20), in which the hand scanner holder (30) includes a base part (31) configured to be attached to the side of the housing (11), the base part (31) includes a pair of holding pieces (34a, 34b) opposed to each other with a first interval therebetween, and the pair of holding pieces (34a, 34b) form a holding recess (34) configured to hold a lower part (21a) of a grasping part (21) of the hand scanner (20), which is inserted, from above the pair of the holding pieces (34a, 34b), between the pair of holding pieces (34a, 34b), in a state in which an upper part (21b) of the grasping part (21) protrudes upward.

According to an embodiment, a self-checkout device has a commodity placing section where a commodity to be purchased can be placed prior to commodity registration processing and a commodity storing section where a commodity can be placed after registration. A commodity registration camera is positioned to capture images for commodity registration processing. A processor is configured to cause the commodity registration camera to capture images of a symbol attached to the commodity passing near the commodity registration camera. The camera also images the vicinity of the placing section and the storage section. Acquired images are stored in a data storage device. The processor executes commodity registration processing based on the commodity symbols and then commodity settlement processing after the commodity registration.