A terminal device, server, weighing scale, system and method for weighing an article are provided. The system (800) includes the terminal device (802), the server (804) and the weighing scale (806). These components communicate with each other to weigh an article placed on the weighing scale. The method of weighing the article includes receiving, at a terminal device, a selection of a container from a user for storing an article, retrieving a weight of the selected container from a first look-up table, wherein the first look-up table includes a container identifier and an associated container weight for one or more containers; prompting, by the terminal device, the user to place the container storing the article onto a weighing scale, the weighing scale being associated with a weighing scale identifier code; receiving the weighing scale identifier code of the weighing scale, inputted or scanned on the terminal device by the user; retrieving, at the server, the weight measurement value associated with the weighing scale identifier code from a second look-up table, the weight measurement value corresponding to the combined weight of the container and the article; and subsequently calculating the weight of the article from the difference between the weight of the container and the combined weight of container and the article.

A self-service checkout terminal includes an optical code reader, a platform on which items to be purchased are placed, a weight sensor configured to detect a weight of objects placed on the platform, and a processor configured to operate in a first mode and a second mode. The processor carries out a registration process based on a merchandise code corresponding to a code symbol read from an item by the optical code reader while enabling a confirmation process to confirm proper item placement based on the weight detected by the weight sensor in the first mode, and carries out the registration process while disabling the confirmation process in the second mode.

This disclosure is directed to item-identifying carts that may be utilized by users to automatically identify items that the users place in their carts. In addition, these carts may automatically determine the outcome of respective events that occur with respect to these identified items. For example, the carts may be configured to identify one or more items that are placed into or removed from the cart, and thereafter determine one or more actions taken with respect to the identified items and a quantity of the items involved. For example, after identifying a first item and a second item either placed into or removed from the cart, the cart may determine that the user added two instances of the first item and removed one instance of the second item. In response to making this determination, the cart may update a virtual cart of a user operating the physical cart.

Disclosed embodiments provide transaction validation systems and methods for use in self-checkout at a retail establishment. An exemplary system may include a scale sized to support and weigh a shopping basket thereon. At least one image sensor is arranged to capture at least one image of the weighed shopping basket. A processor receives a weight measurement of the shopping basket from the scale and determines, based on information received from a wireless communications device of a customer, a record of products in the shopping basket and an expected cumulative weight associated with the products in the shopping basket. The processor determines a discrepancy between the weight measurement of the products in the shopping basket and the expected cumulative weight and reconciles the determined discrepancy using the at least one captured image of the shopping basket by the at least one image sensor.

A system for vending consumer goods in a vehicle includes a container for storing consumable units of at least one sort of consumer goods, a sensor system including at least one first sensor configured to detect removal of a consumable unit from the container by a consumer, and a computer system connected to the sensor system via a data network. The computer system includes a user database storing a user account assigned to the consumer and a service database storing a price for each consumable unit. Each user account comprises a service payment account listing services and a corresponding amount of money due for each service. The computer system is configured to retrieve from the service database a price for the removed consumable unit and to charge the service payment account of the consumer with an amount of money corresponding to the price of the removed consumable unit.

An inspection system of a chip includes a reading device and a determining unit. The reading device is configured to count a number of chips stored in a storage case, the chips associated with a table game and including a chip having a radio tag, read the radio tag while the chips are stored in the storage case, and acquire chip information. The determining unit is configured to compare the chip information of the chips in the storage case with a physical number of the chips in the storage case, determine that there is an abnormal chips among the chips stored in the storage case based on a determination that the counted number of the chips does not match a physical number of the chips in the storage case, and output a result associated with an indication of the abnormal chip.

A method for providing real-time recommendations to user in a shopping environment involves sampling a shopping environment using video cameras to generate video features related to a shopper in connection to an item, the sampling input to a machine learning model to create labels related to a state of a scenario, the scenario including the shopper handling the item. Supplemental information is provided to the shopper in connection with the item. The makeup of the supplemental information may be sourced from online service or device associated with the shopper. The supplemental information may be delivered to the shopper, or to a shopper-aware display in the store, or elsewhere. A processing entity associated with the store detects a scenario to identify the shopper as having finished shopping, and causing a charge of the item to a cashierless shopping cart associated with the shopper. In one example, passive, wireless weight sensors may be used to supplement input features for inferences made by the machine learning model. In another example, wireless, battery-free displays may be coupled to shelves to provide information related to supplemental information relating the item held by the shopper.

In some embodiments, systems, apparatuses and methods are provided herein useful to provide a weight of a product in a machine-readable code on a scale. More specifically, the scale can include an associated display that is configured to display a machine-readable code when a product is weighed on the scale, where the machine-readable code informs a scanning computing device of the weighed amount.

Provided is a shopping payment system and shopping basket that allow for correct payment of the purchase price of products in a short time. The shopping payment system includes a product database that store the product identification codes of products, the prices of the products, and the weights of the products such that each of the product identification codes for identifying each product, each of prices of the product, and each of weights of the product are associated with each other, a product identification code acquisition unit that acquires the product identification code of a product read before the product is put into a shopping basket, a registered weight acquisition unit that acquires the weight of the product associated with the product identification code acquired by the product identification code acquisition unit 201, a measured weight acquisition unit that acquires the measured value of the total weight of one or more product put in the shopping basket, a product price payment unit that when the total weight of the products acquired by the registered weight acquisition unit and the measured value of the total weight of the products acquired by the measured weight acquisition unit 203 are matched, pays the purchase price of the products, and an alarm output unit that when the weights are not matched, outputs an alarm message.

Method of identifying actions of a shopper to account for taken items by the shopper in a cashierless checkout includes sampling a shopping environment using one or more video cameras to generate video features related a shopper in connection to an item and sampling using one or more supplemental sensors to generate supplemental sensor feature data, receiving output of the sampled video and supplemental sensor features as feature inputs to a deep learning model used for making inferences related to the state of a scenario involving shopper action of taking the item into their possession or held and other actions including moving outside a zone initially associated with the item.