A wireless tag reading device of an embodiment includes: a housing portion formed by a bottom surface portion and a side surface portion erected upward from the bottom surface portion; an opening through which an article is allowed to be taken in and out of the housing portion; a reading unit that reads tag information from a wireless tag attached to the article housed in the housing portion via the opening by transmitting and receiving a radio wave to and from the wireless tag; a detection unit that detects a position of the article in the housing portion; and an announcement unit that makes an announcement to prompt approach of the article to a predetermined position of the housing portion based on output of the detection unit.

An unrecognized item code is identified during a transaction at a transaction terminal. When the unrecognized code is determined to be associated with a typographical error, alternative corrected item codes are supplied to the transaction terminal to replace the unrecognized code. When the unrecognized code is determined to be missing from a product catalogue, an ordered list of most likely corrected item codes for the unrecognized code is provided to the transaction terminal for selection of one of the corrected item codes by an operator.

According to one or more embodiments, a settlement processing device includes an interface and a processor. The interface communicates with a reading device. The processor acquires an image of a commodity captured by the reading device via the interface, obtains symbol information based on the captured image, executes settlement processing based on the symbol information, and stores the captured image and the symbol information in correlation with each other in a storage device.

Embodiments of the present invention provide a skip-scanning identification method and apparatus, a self-service cash register terminal and system. The method includes: obtaining a video of a user scanning an item; determining posture data of the user based on the obtained video; determining, according to the posture data of the user, a time period in which a scanning action of the user takes place; receiving a scanning result of the item; and determining whether the user has skipped scanning the item based on the scanning result and the time period.

Systems and methods for conducting sales transactions are provided. Embodiments include portable, electronic, point of purchase devices configured to acquire identification information from articles to be purchased, to determine a purchase price, and to acquire payment information for the purchase price. The point of purchase devices may include one or more input devices such as a communication device, a camera, a scanner, and a sensor system for acquiring identification information and/or the payment information. The point of purchase devices also may contain an electronic display, communication interfaces (such as a near field communication interface, a local area network interface, Bluetooth® configurations, etc.) for transmitting and/or receiving information to/from connectable devices such as a mobile phone, BLE beacon and/or an external server. Additional provision is made for an embodiment that avoids battery depletion anxiety by shoppers, through the provision of a handheld portable charging point device.

Performing point of sale transactions are performed by configuring a point of service (POS) environment with a sensor pod including an active sensor and a passive sensor. A first signal is sent from the active sensor of the sensor pod to a user device that is initiating a sale for a service. A converted first signal is received at the active sensor, wherein the converted version of the first signal includes identification information for the user. It can be determined that the active sensor of the sensor pod of the point of service environment has not functioned. A user wake up call is received from the user device at the passive sensor of the sensor pod. Functionality of the active sensor is restored with a POS wake up signal sent from the passive sensor to the active sensor.

Disclosed in the present specification is a self-checkout device to which hybrid product recognition technology is applied and which helps a user to more conveniently and quickly make a payment. The self-checkout device according to the present specification photographs a product with a plurality of cameras, and then recognizes a barcode by detecting a barcode region from the captured images and, simultaneously, extracts a feature point of the images such that a product can be recognized through the calculation of the proportion that matches with a reference image of the product. Thus, a product can be quickly recognized through barcode recognition and packaging paper recognition in a product image.

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.

Disclosed are systems and methods for determining whether an unknown product matches a scanned barcode during checkout. The system includes a checkout lane having a flatbed scanning area with scanning devices and a point of sale (POS) terminal that scans a product identifier of an unknown product, identifies a product associated with the scanned product identifier, and transmits, to a computing system, product information. An overhead camera idnentifies, based on detecting an optical signal from the POS terminal, that a scanning event occurred, captures image data of the unknown product, and transmits, to the computing system, the image data. The computing system generates machine learning product identification models for identifying unknown products, identifies candidate product identifications for the unknown product based on applying the models to the image data, and determines, based on the candidate product identifications and the information about the product, whether the unknown product matches the product.

A product checkout system using automatic barcode scanning according to the present invention may comprise: an imaging unit photographing a product and generating a product image; a processor recognizing a barcode position of a barcode that is provided on one side of the product and contains price information of the product, based on the product image, and a robot arm unit grasping and moving the product to a barcode scanning device so that the barcode is scanned.