Various embodiments herein each include at least one of systems, methods, and software for model-based data validation to identify when self-scan checkout data requires validation. Some embodiments, in the form of a method includes receiving, via a network from a self-scanning device, a self-scan dataset of items for purchase within a purchase data processing transaction and evaluating the self-scan dataset to determine whether to require a rescan of items represented in the self-scan dataset. In such embodiments when a rescan is determined to be required, the method includes transmitting via the network to at least one of the self-scan device and at least one device of a store employee data indicating a rescan is required. However, when a rescan is not determined to be required, the method includes permitting the purchase data processing transaction to proceed.

A smart product display system has a base on which a product can be placed. A product camera mounted to the base is used to image a field of view over the base. Images from the product camera are analyzed to identify products that are placed on the base and to detect when a customer has interacted with a product, such as by lifting it up. When a product interaction is detected, information about the product is presented on a display. The display can be integrated in a riser extending upwardly from the base. A customer camera can be used to capture images of a person in the vicinity of the system. Images from the customer camera can be analyzed to identify an attribute of an imaged person and an output, such as a content display or an alert, generated responsive to the attribute.

A self-checkout method includes an image recognizing system performing a first recognition process on at least a product placed on a checkout conveyor to obtain an item information corresponding to the at least a product from a product database; performing a second recognition process for positioning a first product of the at least a product to determine a position of the first product relative to the checkout conveyor when the image recognizing system fails to recognize the first product based on the first recognition process; controlling an indicating light to markedly label the first product when the position of the first product is determined, and stopping running the checkout conveyor; and resuming running the checkout conveyor after the first product is removed or when no product cannot be recognized by the first recognition process.

Systems and methods for operating a Point Of Sale (POS) system. The methods comprise: performing operations by the POS system to machine learn at least information about a condition of an article to be purchased using at least one of imaging, sensing, and short range communications; determining by the POS system if the article is accepted for purchase based at least on the machine learned information about the condition of the article; and completing a purchase transaction by the POS system if a determination is made that the article is accepted for purchase. The POS system may also perform operations to deactivate a security tag coupled to the article or actuate a detachment mechanism of the security tag, if the article was successfully purchased during the purchase transaction.

Examples provide a transparent scan platform within an item scanning tunnel on the same plane as a set of conveyor belts. The transparent scan platform includes a plurality of interconnected transparent segments or a transparent band forming a continuous transparent platform rotating about a set of rollers. The transparent scan platform includes a scan device embedded within the platform or positioned under the transparent scan platform. The scan device scans an item identifier, such as a barcode, located on an item sitting on a top surface of the transparent scan platform. The transparent scan platform rolls the item out of the scanning tunnel. If the item becomes wedged between an end of the scan platform and an end of a conveyor belt, a sweeper device extends downward behind the item and sweeps the item out of the scanning tunnel. The sweeper device then retracts back upward.

A registration apparatus comprises a first control module configured to switch an operation mode from a store clerk operation mode in which registration processing of a purchased commodity is performed by an operation of a store clerk to a customer operation mode in which the registration processing is performed by an operation of a customer, and vice versa. A settlement apparatus comprises a second control module configured to switch an operation mode from a store clerk operation mode in which settlement processing is performed by an operation of the store clerk to a customer operation mode in which the settlement processing is performed by an operation of the customer, and vice versa. The first and second control modules switch the operation mode from the store clerk operation mode to the customer operation mode if a sign-off is performed, and vice versa if a sign-on is performed.

Disclosed are systems and methods for completing a transaction using a shelf and interactive tablet. The systems and methods may include receiving, at an interactive tablet comprising a processor, a captured image associated with an item; identifying, by the interactive tablet, a known image of the item based on the captured image of the item; and retrieving, by the interactive tablet, product information associated with the item based on the known image of the item.

An Artificial Intelligence (AI) trained item image identifier identifies item identifiers, item descriptions, item information, and item pricing from item images captured from a mobile self-checkout manager on a mobile device. The item identifiers are automatically placed in a cart. Payment for checkout is processed through the mobile self-checkout manager and a receipt is provided for viewing on the mobile device. The receipt is shown on the display of the mobile device when existing a retail establishment for any auditing of the transaction with the establishment.

Various embodiments herein each include at least one of systems, methods, and software for model-based data validation to identify when self-scan checkout data requires validation. Some embodiments, in the form of a method includes receiving, via a network from a self-scanning device, a self-scan dataset of items for purchase within a purchase data processing transaction and evaluating the self-scan dataset to determine whether to require a rescan of items represented in the self-scan dataset. In such embodiments when a rescan is determined to be required, the method includes transmitting via the network to at least one of the self-scan device and at least one device of a store employee data indicating a rescan is required. However, when a rescan is not determined to be required, the method includes permitting the purchase data processing transaction to proceed.

Disclosed are visual recognition and sensor fusion weight detection system and method. An example method includes: tracking, by a sensor system, objects and motions within a selected area of a store; activating, by the sensor system, a first computing device positioned in the selected area in response to detecting a presence of a customer within the selected area; identifying, by the sensor system, the customer and at least one item carried by the customer; transmitting, by the sensor system, identifying information of the customer and the at least one item to a computing server system via a communication network; measuring, by the first computing device, a weight of the at least one item; transmitting, by the first computing device, the weight to the computing server system via the communication network; and generating, by the computing server system, via the communication network, transaction information of the at least one item.