3037results about "Cash registers" patented technology

The invention relates to the technical field of encryption communication, in particular to a data encryption communication method and system applied to an intelligent cash register. The method comprises the following steps: collecting user touch data and equipment hardware fingerprints, and carrying out high-dimensional feature fusion coding to obtain a joint identity certificate; obtaining an original key negotiation protocol and transmission metadata of an opposite-end server, and executing multi-logic path mapping and channel encryption configuration to obtain distributed ciphertext channel parameters; encrypting the distributed ciphertext channel parameters and the corresponding transmission metadata, and then performing block content packaging and node hash calculation to obtain an audit chain hash block; performing homomorphic encryption processing on the obtained real-time transaction data to obtain a to-be-transmitted homomorphic ciphertext; and performing communication transmission anomaly detection on information transmission data acquired in real time, and triggering dynamic key re-negotiation so as to improve the communication feedback capability. According to the invention, the overall security and stability of data encryption communication between the cash register and the back-end server can be improved.

The present invention relates to a system (100) and method (300) for automated product validation, identification, and transaction management in shopping environments. The system (100) integrates a smart shopping cart (102) equipped with at least one camera (106), a load cell (108), and a user interface (110). An AI model trained on a dataset of high-resolution, 360° product images generate unique image embeddings for each product. The system performs multimodal validation by comparing the extracted image embeddings, measured weight data, and scanned barcode information with reference data stored in a vector database. Further, discrepancies, such as unscanned products or mismatches, are flagged, and payment is blocked until resolved.

The invention relates to the technical field of self-service, and particularly discloses a non-inductive payment method and device, and the method comprises the steps: collecting goods taking pictures of a plurality of clients through a binocular camera and an infrared array which are disposed at the top and side surfaces of a cabinet body, extracting hand key points through posture estimation, and distinguishing the identity through multi-target tracking; a gravity sensor under a shelf board detects the weight change of each goods allocation, and combines with a visual track to construct the space-time correlation of goods movement, so as to realize the cross validation of goods taking behaviors; the convolutional neural network performs abnormal behavior detection on the multi-modal data and generates a risk score; creating a virtual shopping basket containing a space-time mark for each customer, and judging commodity attribution by adopting a decision tree algorithm; and executing distributed bill generation and multi-channel fee deduction according to the risk level, and completing real-time settlement in a multi-client concurrent scene. According to the method, the commodity affiliation accuracy and the payment security are remarkably improved, and efficient and stable unmanned retail operation can be realized.

Implementations of this application provide a checkout device, including a housing, a display screen, and a near-field communication (NFC) module. The housing includes a support portion for support of the housing on a countertop. The display screen is fastened to the housing, and when the checkout device is used, the display screen faces a consumer. The NFC module is located in space enclosed by the housing, and located to permit an electronic device to make an electronic payment.

An information processing system according to an aspect of the present disclosure includes: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: estimate an age of a customer from a customer image; receive input of identification information about a product; display a first age verification screen requesting the customer to express his / her age in response to the input of the identification information about an age-restricted product in a case where the estimated age of the customer meets a predetermined condition; and display a second age verification screen requesting the customer for proof of age in response to the input of the identification information about an age-restricted product in a case where the estimated age of the customer does not meet the predetermined condition.

Disclosed is a storage cabinet. An embodiment has one or more shelves, one or more doors for enclosing the cabinet, and an electromagnetic lock for locking the door or doors. The shelves have one or more cameras, an opened- or closed-door state sensor, and a weight sensor arranged to measure weight of products placed on said shelves. An electronic data processor carries out a machine learning computer vision method for processing data received from cameras and sensors to identify products removed from said shelves. The processor detects when a cabinet door is in an open state, acquires image and weight data from the associated camera and weight sensor. When a weight change at a shelf is detected, processing of image data acquired including when the weight change occurred occurs, with said machine learning computer vision method.

A product checkout device operable to couple to a shopping cart and facilitate a checkout process for items placed in the shopping cart.

Techniques for intelligent system optimization are provided. Capacity data of one or more exit devices at a physical location is received. Demand data that indicates a current demand for exit service at the physical location is received from one or more monitoring devices. A decision is generated based on the capacity data and the demand data using a machine learning (ML) model. Commands corresponding to the decision are transmitted to the one or more exit devices for implementation.

Implementations of this application provide a checkout device, a checkout assembly, and a checkout method. An example checkout device includes a housing, a display screen, and a Near Field Communication (NFC) module. The display screen is fastened to the housing, and is configured to display at least one of a to-be-paid amount of a product, payment method guidance, or a payment result. The NFC module is located in a space enclosed by the housing to be in close proximity to an electronic device to make an electronic payment. The display screen displays the payment method guidance to direct a consumer to quickly make an electronic payment. The display screen displays the to-be-paid amount of the product and the payment result.

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.

Systems and methods of conducting frictionless shopping are provided. In one exemplary embodiment, a method is performed by a network node device operationally coupled over a network to optical sensor devices positioned throughout a retail space having shelf structures. Each shelf structure has display devices with each display device being associated with and proximate a certain stocked item of the set of stocked items that is disposed on that shelf structure. The method includes sending, to a first display device that is associated with and proximate a certain stocked item that is electronically requested, over the network, an indication that includes a request to enable an auditory or visual indication so that the certain stocked item can be located on the corresponding shelf structure of the set of shelf structures in the retail space based on the auditory or visual indication.

A smart shopping cart includes internally facing cameras and an integrated scale to identify objects that are placed in the cart. To avoid unnecessary processing of images that are irrelevant, and thereby save battery life, the cart uses the scale to detect when an object is placed in the cart. The cart obtains images from a cache and sends those to an object detection machine learning model. The cart captures and sends a load curve as input to the trained model for object detection. Labeled load data and labeled image data are used by a model training system to train the machine learning model to identify an item when it is added to the shopping cart. The shopping cart also uses weight data and the image data from a timeframe associated with the addition of the item to the cart as inputs.

The present disclosure describes various embodiments directed at a weighing device with a power supply method for components within the weigh platter. It solves the issue of traditional electrical supply methods interfering with weight measurements by embedding an energy storage assembly within the weigh platter. This assembly supplies power to embedded subsystems when needed and recharges when possible, ensuring efficient power supply without disturbing the weighing process. The power transfer can be selectively controlled based on the weight detected or the reader's operational state. The device can be used in various configurations, extending beyond scales with data capture assemblies.

The invention discloses a non-screen POS machine data acquisition method and system based on NFC and a WeChat applet. A POS machine simulates an NFC Type 4 label through a non-contact chip, performs SM2 signature and encryption on equipment data containing a timestamp and a random number by using a private key instantaneously reconstructed by a PUF, and performs Base64URL-CRC packaging, segmented NDEF writing and 30s TTL setting; the mobile terminal automatically pulls up the WeChat applet after triple verification of radio frequency field stability detection, URL white list and integrity fingerprint; the small program uploads parameters through an AES-128-GCM secondary encryption and a Reed-Solomon fragment tunnel; the background adopts a Redis idempotent lock, an HSM private key decryption, an SGX enclave one-time token display mechanism and other mechanisms to complete signature verification and decryption, and it is ensured that the device data are only briefly visible in the WeChat security sandbox. According to the invention, the problems of difficult operation and maintenance data acquisition, high cost and poor security of the non-screen POS machine are solved, and cross-platform, anti-replay and man-in-the-middle-resistant high-security data acquisition can be completed within 10 seconds.

A Radio Frequency Identification (RFID) enabled Self-Checkout (SCO) station includes an RF antenna that emits RF energy, such as RFID interrogation signals, through the variable apertures of one or more aperture layers into a scan zone. The size of the scan zone is selectively varied by electrically modifying the effective size of the variable aperture in the aperture layer.

Systems and methods of detecting activity at point of sale are provided. In one exemplary embodiment, a method is performed by a POS system having an optical sensor device, an optical scanner device and a load sensor device. The optical sensor device has a field of view that includes a first region about the POS system and the load sensor device is operable to measure a load of an object while positioned in a bagging area of the POS system. Further, the first region includes a second region associated with a certain object type that can be positioned in the bagging area without having to be scanned or weighed. The method includes obtaining a successive image captured by the optical sensor device to enable a determination that the target object corresponds to the certain object type that is exempt from being scanned or weighed based on the successive image.

Self-checkout vehicle systems and methods comprising a self-checkout vehicle having a camera(s), a weight sensor(s), and a processor configured to: (i) identify via computer vision a merchandise item selected by a shopper based on an identifier affixed to the selected item, and (ii) calculate a price of the merchandise item based on the identification and weight of the selected item. Computer vision systems and methods for identifying merchandise selected by a shopper comprising a processor configured to: (i) identify an identifier affixed to the selected merchandise and an item category of the selected merchandise, and (ii) compare the identifier and item category identified in each respective image to determine the most likely identification of the merchandise.

Systems and methods of verifying utilization of a blockchain registered container at POS are presented. In one exemplary embodiment, a method is performed by a POS system having a sensing device operable to sense an identifier specific to a container configured to transport items after checkout. The POS system is communicatively coupled to a blockchain network that includes network nodes that are collectively configured to operate a blockchain. The container identifier is specific to a cryptographic digital asset stored on the blockchain as a container identifier code. Further, the cryptographic digital asset includes a user identifier code, with the container identifier code and the user identifier code being included in a transaction entry of a block on the blockchain that is associated with the cryptographic digital asset. The method includes sending, to the blockchain, a request for block data associated with the cryptographic digital asset based on the container identifier.

Embodiments are directed to using an NFC capable portable device to conduct a transaction at a resource provider location. The portable device (e.g., a wearable device, a physical token) may be temporarily associated with a user account at the resource provider location. The resource provider location includes one or more terminals that are configured to generate a list of items (e.g., items picked by the user) to be associated with the portable device. At checkout, the user surrenders the portable device, items on the list get automatically charged to the user account, and the user leaves the resource provider location. All communication between terminals, portable device and the resource provider computer occurs over a closed, local area network. Among the terminals, portable device and the resource provider computer, the resource provider computer is the only device configured to communicate with external entities over an external network.

An interactive shopping system, or smart cart. The system allows a user to select items in a store and complete a purchase without having to wait in lines or interact with store personnel. The system can have a container for holding products selected by at least one user, a user interface, a scanner in communication with the user interface, a processor in communication with the user interface, and a data storage comprising computer instructions executable by the processor. A user can select products, place them within the container, scan the products, and initiate a payment transaction to complete a purchase.

The present invention provides a method for connecting to a communication network associated with a micro market. The method includes scanning a code associated with an ephemeral app to be downloaded to a mobile communication device. In an example, the method includes associating a web address with a code to find the ephemeral app and linking the web address with the mobile device. In an example, the method includes transferring the ephemeral app in a first format using the Internet to a storage location on the mobile communication device, and initiating the ephemeral app onto the mobile device to open the ephemeral app. The method includes sensing for a Bluetooth beacon associated with a spatial area of one of the micro markets and connecting using the Internet to a server associated with the micro market to transfer the catalog and list of items associated with the micro market.

A self-service checkout system has a processor and a non-transitory computer-readable storage medium storing executable instructions. The executable instructions, when executed by the processor, cause the processor to perform operations including: receiving a message from a vision system that includes a current list of identified items on a tray positioned adjacent to the vision system for a current transaction, comparing the current list of identified items to a previous list of identified items, and adding any items on the current list that are not on the previous list to a transaction list for a current transaction, determining that the current transaction is complete when the current list of identified items has no items, enabling a customer to review the transaction list and remove any duplicate entries, and completing the current transaction.

The invention provides a self-service weighing settlement system and method for a cafeteria, and relates to the technical field of self-service weighing, and the method comprises the steps: determining the zero drift characteristics actually measured by a weighing platform according to the no-load state of the weighing platform, carrying out the mapping correlation of the zero drift characteristics and environment temperature information, and obtaining the zero temperature coefficient of a weighing instrument; extracting temperature deviation characteristics of the weighing platform in each temperature interval in the on-load state, and determining a sensitivity temperature coefficient of the weighing instrument through all the temperature deviation characteristics; determining a temperature drift error caused by the environment temperature to the weighing instrument based on the zero temperature coefficient and the sensitivity temperature coefficient, and determining a compensation characteristic of the weighing platform through the temperature drift error and the current environment temperature; and carrying out temperature drift compensation on the actual measurement of the weighing platform based on the compensation characteristics to obtain the actual weight, and carrying out weighing settlement according to the actual weight, so that the drift compensation of the actual measurement in self-service weighing can be realized, and the accuracy of self-service weighing settlement is improved.

A depth image of items on a scale are captured. Depth information for the depth image is processed to produce a three-dimensional (3D) map of the depth information. The items are identified as blobs within the 3D map. A plane is generated and projected into the 3D map and each separate blob that intersects the plane is counted to determine an item quantity for the items depicted in the original depth image. The item quantity is provided back to a terminal for item quantity verification of the items during a checkout transaction at the terminal. In an embodiment, the plane is projected onto the 3D map and animated to move from a top of the 3D map to a bottom of the 3D map while the separate blobs are counted for the item quantity determination as the plane moves.

The invention provides an electronic book borrowing management system based on OPAC bidirectional hitching, and relates to the technical field of library informatization. Comprising the steps that a hardware acceleration layer constructs a dynamic resource distribution matrix through an FPGA coprocessor and calculates a matrix norm in real time, and request queue scanning and a redundant copy generation algorithm per 100 ms are achieved in combination with an ASIC anti-conflict controller; a system service layer deploys a dynamic priority scheduling engine, realizes intelligent resource distribution based on a cross-campus coordination coefficient and an edge cloud coordination strategy, records borrowing operation through a block chain evidence storage service and executes automatic copyright division auditing; the user interaction layer provides a bidirectional association retrieval interface and a priority borrowing channel based on credit scores. According to the system, the resource scheduling efficiency in a high-concurrency scene is improved through matrix norm calculation accelerated by hardware, an elastic copy allocation mechanism and an anti-conflict algorithm solidified in ASIC, and cross-campus resource collaboration and accurate copyright revenue allocation are realized in combination with geographic position scoring and block chain technologies.

To provide a gate apparatus through which a user can efficiently pass.A gate apparatus is communicatively connected to an information processing apparatus including a first reading unit that reads a store leaving code to acquire first identification information for individually identifying a product for which a payment process has been completed. The gate apparatus includes a pair of side wall portions that are disposed to face each other with a passage interposed therebetween, a second reading unit that is provided on at least one of the pair of side wall portions and outputs predetermined radio waves to read, from an RFID tag attached to the product, second identification information for individually identifying a product that has passed through the passage, and a placement portion on which the information processing apparatus is placed. The placement portion is disposed above a reading region of the second reading unit.

To provide a relay device and a POS system capable of forming a better organized system.SOLUTION: A relay device 1, 200, comprises: a case 40, 240; a main substrate 3 housed in the case 40, and 240; a power source adapter 28 which a power source cord can be inserted into and extracted from; and a power source adaptor cable 27 that connects the power source adapter 28 and the main substrate 3. Therein: the main substrate 3 is provided with device connectors for connecting external devices; and the power source adapter 28 and the power source adaptor cable 27 are housed in the case 40, 240.SELECTED DRAWING: Figure 4

In a purchase management system using a self-checkout register, pieces of information, which are respectively registered by individual terminal devices, are shared among a plurality of customers. A terminal device capable of acquiring item identification information of each item to be purchased first acquires a cooperation ID. Next, the terminal device shares the information in real time with a cooperative terminal device that is another terminal device and includes the same cooperation ID.

A hybrid checkout system that enables in-motion, multi-signal, bulk item identification is disclosed. The hybrid checkout system includes a computer vision apparatus that includes a plurality of cameras fixed at different locations relative to a conveyor belt. The conveyor belt includes markings that assist a user with item placement. RFID sensors are provided with the hybrid checkout apparatus. The cameras capture multiple images of items placed on the belt as the items are in motion. Each camera captures multiple images of the items captured from different vantage points as the items are in motion. In addition, the RFID sensors gather RFID data from RFID tags affixed to the items, as the items are in motion. The image data and other sensor data is provided as a multi-signal input to a machine learning model that is trained to recognize items and output item identifiers for the items. Pricing information corresponding to the item identifiers received from the model is determined and the items and their respective prices are added to a transaction record.