285results about "Alarm indicators" patented technology

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.

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.

Consistent with disclosed embodiments, systems, methods, and computer readable media for conducting wireless transaction communications may be provided. Embodiments may include at least one processor configured to access a data structure containing identities of display areas and identities of products associated with the display areas; receive a request for information related to a particular display area in a vicinity of a mobile communications device; receive location information associated with a locus of the mobile communications device; perform a lookup in the data structure to identify the particular display area; retrieve product-related information associated with products in the particular display area; and transmit the product-related information to the mobile communications device.

Disclosed herein is a novel system and method to reduce theft and errors in the self-checkout process. The system and methods disclosed herein reconcile purchased products with receipts for those products by corresponding, analyzing, and / or comparing information on self-checkout transaction receipts with captured images of purchase products from camera feeds to ensure that all products purchased via a self-checkout system have been properly scanned and accounted for.

Consistent with disclosed embodiments, systems, methods, and computer readable media for electronic security systems for retail establishments may be provided. Embodiments may include an electronic article surveillance (EAS) gate and at least one receiver configured to receive transmissions from wireless tags associated with products offered by a retail establishment. Embodiments may also include at least one processor configured to receive, from a device operated by a prospective purchaser, a tag ID associated with a specific product for prospective purchase; perform a lookup of the tag ID in a data structure to identify the specific product; initiate an electronic purchase transaction to debit an account associated with the prospective purchaser for purchase of the specific product; and disable an ability to initiate an alarm when the at least one receiver receives a transmission from a tag associated with the specific product in proximity to the EAS gate.

The present disclosure utilizes image data analysis to improve the accuracy and integrity of item characteristic information in a database. During point-of-sale (POS) transactions, a security exception may be triggered when an item's stored characteristic information, such as weight or dimensions, is found to be inaccurate or missing. By capturing images of procedures performed to resolve security exceptions, the system can analyze aspects of the individual's appearance or behavior to determine if measurement procedures are performed correctly. Measures from properly performed measurement procedures can be used to selectively update the item's characteristic information in the system, improving the accuracy and integrity the characteristic information.

Systems, computer program products, and methods are described herein for using an anomaly deterrent sensor within a self-service machine for dispensing physical items. The present disclosure is configured to: detect an interaction between a payment instrument with available resources and a self-service machine for dispensing physical items; receive an anomaly notification from an anomaly deterrent sensor within the self-service machine for dispensing physical items wherein the anomaly notification is associated with forced entry into the self-service machine, wherein the anomaly deterrent sensor detects forced entry into a physical item dispensing area within the self-service machine during the interaction between the payment instrument and self-service machine; and trigger a set of security measures associated with the self-service machine for dispensing physical items upon reception of the anomaly notification originating from the anomaly deterrent sensor, wherein the set of security measures comprises playing a pre-recorded alarm.

Method and apparatus for fraud detection are provided. Sensor data from one or more acoustic wave sensors is received, where the one or more acoustic wave sensors transmit acoustic waves towards a set of items within a receptacle and receive reflected acoustic waves from the set of items. A model for the set of items within the receptacle is generated based on the sensor data. One or more features for the set of items are identified by analyzing the model. Checkout data is retrieved from one or more checkout devices. The one or more features for the set of items identified from the model are compared with the checkout data. An alert is generated upon detecting a discrepancy between the one or more features and the checkout data.

A system for monitoring shopping carts uses cameras to generate images of the carts moving in a store. In some implementations, cameras may additionally or alternatively be mounted to the shopping carts and configured to image cart contents. The system may use the collected image data, and / or other types of sensor data (such as the store location at which an item was added to the basket), to classify items detected in the shopping carts. For example, a trained machine learning model may classify item in a cart as “non-merchandise,”“high theft risk merchandise,”“electronics merchandise,” etc. When a shopping cart approaches a store exit without any indication of an associated payment transaction, the system may use the associated item classification data, optionally in combination with other data such as cart path data, to determine whether to execute an anti-theft action, such as locking a cart wheel or activating a store alarm. The system may also compare the classifications of cart contents to payment transaction records (or summaries thereof) to, e.g., detect underpayment events.

The present invention relates to a self-checkout method. The method includes: executing following steps through a control module: activating a first image sensor to capture a first image that includes a hand; activating a second image sensor to capture a second image that includes an item; running a gesture recognition independent model to generate a first recognition result based on the first image; running an object recognition independent model to generate a third recognition result based on the second image; and executing and inputting the first recognition result and the third recognition result into a checkout assistance decision independent model to determine whether a missed scan event has occurred.

The invention relates to a self-checkout method, which comprises the following steps executed by a control module: driving a first image sensor to obtain a first image containing a hand; driving a second image sensor to acquire a second image containing the article; executing a gesture recognition independent model to generate a first recognition result based on the first image; executing an object recognition independent model to generate a third recognition result based on the second image; and executing and inputting the first identification result and the third identification result into a checkout auxiliary decision independent model so as to judge whether a swiping omission event occurs according to the first identification result and the third identification result.

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.

To enable inexpensive and accurate detection of fraudulent acts in which articles are taken out of a store without being settled after registration.SOLUTION: A fraud detection device includes a person detection unit, an article detection unit, and a fraud reporting unit. The person detection unit detects persons in a first area around a target device based on an image of the target device, which is the subject of the fraud detection. The article detection unit detects at least one of the articles in a second area around the target device and a container containing the articles based on the image. The fraud reporting unit reports fraud when the person detection unit does not detect any person and the article detection unit does not detect either the articles or the container while the settlement process is being executed for the articles.SELECTED DRAWING: Figure 9

A smart offline shopping method for improving the offline shopping experience includes obtaining a shopping cart assembly. The shopping cart assembly includes an in-store shopping cart and a wireless computing device. The wireless computing device wirelessly communicates with a point-of-sale device and an inventory management system of a store. The wireless computing device temporarily retains a purchase order and communicates the purchase order to each of the point of sale device and the inventory management system. A customer may input an identification code associated with an item into the wireless computing device and add the item to the purchase order. An employee may fill the purchase order by gathering the item from an inventory stock room. An employee may bring the filled purchase order to the point-of-sale device, where the customer pays for the purchase order before leaving the store.

A method, computer program product, and computer system of artificial intelligence (AI) intervention to detect and mitigate an abnormality associated with an object moving during performance of a process. A trained recurrent neural network (RNN) determines, from sensor data, a probability (Pr1) that the abnormality existed at a first time, where Pr1 exceeds a threshold T1 and in response, an alternative generative adversarial network (AGAN) determines a probability (Pa1) that the abnormality existed at the first time. A score S1, which is computed as a function of Pr1 and Pa1, exceeds T1 and in response the RNN and the AGAN determines, from the senso data, a probability (Pr2) and a probability (Pa2), respectively, that the abnormality existed at a second time. A score S2, which is computed as a function of at least Pr2, Pa2, and (S1-T1), exceeds a threshold (T2) and in response, the abnormality is mitigated.

The present subject matter relates to a system and method for managing one or more SCO terminals in a self-checkout (SCO) environment. The system includes one or more video sensors configured to capture a plurality of video frames. The video frames are processed by a processing unit to detect a primary object of interest and secondary objects of interest after the primary object of interest is detected. Further, changes in the location and time of appearance of the primary object of interest and the secondary objects of interest are determined, and a motion trigger is generated. Based on the motion trigger, transaction data is received and compared with the detected secondary objects of interest. A non-scan event alert is generated based on a discrepancy in the comparison between the transaction data and the detected one or more secondary objects of interest.

To provide a processing device, a portable terminal, a processing method, and a program capable of reducing a possibility to forget to receive small changes.SOLUTION: A processing device includes: a sound detection section for detecting a first sound in accounting of merchandise in a self-register and a second sound indicating generation of small changes in the self-register, and also detecting a volume of the second sound; a comparison section for comparing a first volume of the second sound detected by the sound detection section and a second volume of the second sound detected this time by the sound detection section when the sound detection section detects the first sound and the second sound and then detects the second sound again; and an output section for outputting warning when the second volume is smaller than the first volume.SELECTED DRAWING: Figure 6

To detect a fraud in a self register.SOLUTION: An information processor acquires image data obtained by photographing a predetermined area in front of an accounting machine for registering and accounting a commodity by a user himself / herself. The information processor inputs the image data to a machine learning model trained so as to identify the commodity and a storage for storing the commodity, and acquires an output result. The information processor identifies an action for the commodity of the user using the commodity and the storage included in the output result.SELECTED DRAWING: Figure 5

There are provided systems and methods relating to checking and confirming merchandise purchased at shopping facilities. In one form, the system includes: a shopping cart containing merchandise items to be purchased; a sales transaction database; a point-of-sales system that creates transaction records identified by transaction identifiers; and a mobile device used by an employee that includes a sensor to scan a paper or digital receipt to obtain the transaction identifier and a camera to capture images of the items in the shopping cart. The system also includes a control circuit that receives the transaction identifier, accesses the database using the identifier to determine the purchased items; analyzes the images of the merchandise items in the shopping cart and creates a computer vision receipt listing detected items; compares the purchased items with the detected items; and takes an action if there is a discrepancy.

To prevent the occurrence of inconvenience to sales data processing when contents of captured camera images for detecting operational errors and malpractice are abnormal.SOLUTION: A sales data processor includes: a registration unit that performs registration processing to store information on articles to be transacted in a predetermined storage unit; a settlement unit that performs settlement processing for payment of the articles registered by the registration unit; an operation unit that accepts operations by an operator; an acquisition unit that acquires information obtained by analyzing an image taken by a camera of an area in which the operator is reflected, and indicating that the camera's image capturing direction is deviated from a reference; and a countermeasure unit that performs countermeasure processing to prevent unauthorized operation by the operator when the acquisition unit acquires the information.SELECTED DRAWING: Figure 1

An information processing device includes an input unit and a controller. The controller is configured to perform first processing of outputting, to a display device, a recognition result of recognizing what product corresponds to an object contained in a captured image captured by an image-capturing device, perform second processing of storing the recognition result in a storage device and outputting, to the display device, an inquiry as to whether or not there is an unprocessed product when an input accepting the recognition result is received at the input unit, and perform the first processing again when a response that there is an unprocessed product is received at the input unit in response to the inquiry as to whether or not there is an unprocessed product.

Method and apparatus for enhanced emergency response are provided. An activation signal indicating an event has occurred at a first location is received. An alert is transmitted to a set of transaction processing devices at the first location, where the alert instructs each respective transaction processing device, from the set of transaction processing devices, to suspend respective transactions that are pending for completion. A deactivation signal indicating the event was resolved is received. Responsive to receiving the deactivation signal, diagnostic checks are conducted on each of the set of transaction processing devices to determine operational status. A transaction processing device, from the set of transaction processing devices, is determined to be operational. Responsive to determining the transaction processing device is operational, the transaction processing device is instructed to resume the respective transactions suspended on the transaction processing device.

A server obtains real-time video depicting an area that includes a terminal. The server analyzes the video for depictions of a vehicle and objects associated with attacks on terminals, A server provides factors associated with the analysis to a machine learning model (MLM). The server receives a confidence value as output from the MLM. The server sends an alert when the confidence value exceeds a threshold as an indication that a potential attack on the terminal may be in progress.

An accounting processing apparatus according to an embodiment includes a registration screen display unit, a receiving unit, an accounting screen display unit, and an accounting processing unit. In a case of receiving input operation while a standby screen is being displayed, the registration screen display unit displays a product registration screen for receiving registration of first information related to a product to be purchased. The receiving unit receives second information related to the transaction of the product from the registration machine. In a case of receiving the second information, the accounting screen display unit displays an accounting screen for accounting processing for a product based on the second information. The accounting processing unit performs accounting processing on the product based on the first information received through the product registration screen or the second information received by the receiving unit.

A registration checking apparatus (2000) determines, for a target transaction, whether a relation between the number of times scanning actions are performed and the number of products registered as checkout targets satisfies a predetermined condition. The scanning action is detected by analyzing a video (12). The registration checking apparatus (2000) performs predetermined output processing when the relation does not satisfy the predetermined condition. The predetermined condition is a condition being satisfied when the number of registered products is equal to or greater than the number of detected scanning actions.

Example aspects include a method, apparatus and computer-readable medium of determining losses at a point of sale (POS) device, comprising receiving, by a processor from an imaging device, a video feed of a scanning area. The aspects further include detecting, by the processor, an entry of an item into the scanning area. Additionally, the aspects further include identifying, by the processor, one or more motion parameters of the item. Additionally, the aspects further include determining, by the processor, a dwell-time for the item based at least on the one or more motion parameters. Additionally, the aspects further include identifying, by the processor, a scan time anomaly for the item. Additionally, the aspects further include outputting a notification, by the processor, indicating a suspicious activity for the item, wherein the notification indicating the suspicious activity is based on the scan time anomaly.

The invention discloses an information processing apparatus, a storage medium, and an information processing system, and aims to reduce the risk of false detection notification to a purchaser and effectively prevent or suppress unauthorized behaviors with effectiveness. The information processing apparatus includes a detection unit, an acquisition unit, and a notification unit. The detection unit detects a notification-requiring behavior of a purchaser with respect to the transaction processing device. The acquisition unit acquires the type of the behavior to be reported detected by the detection unit. The notification unit performs notification when a plurality of types of actions requiring notification are acquired by the acquisition unit during a transaction.

Images are captured of a customer during a transaction at a transaction terminal along with images associated with items of the transaction and any bags or cart used to hold the items. The images are processed to track any movement and locations of the customer, items, bags, and cart relative to a known location of the transaction terminal. When a transaction payment is required for the transaction and movement is detected in a direction that is moving away from the transaction terminal before a payment notification is received for the transaction, one or more alerts are raised as an indication to staff and / or security systems of a potential in-progress walk-away theft.

A store server for managing customer information received by a terminal in a store, includes a network interface connectable to the terminal and a first server that stores information about a customer, the information associating identification information of the customer with a state of a medium issued to the customer and that is usable for payment, and a processor configured to: acquire identification information of a customer from the terminal, control the interface to transmit the identification information to the first server, acquire from the first server the state of the medium issued to the customer, and determine whether the medium is in an unusable state, upon determining that the medium is not in a usable state, cause the terminal to accept the medium for payment, and upon determining that the medium is in the unusable state, cause the terminal to display a message indicating that the medium is unusable.