A point of sale (POS) security system includes a POS device including a non-transitory memory, one or more hardware processors, and one or more environment sensors. A plurality of POS instructions are located on the non-transitory memory in the POS device and executable by the one or more hardware processors in the POS device to provide a POS engine that is configured to receive and transmit payment information for conducting a payment transaction associated with a purchase. A plurality of security instructions are located on the non-transitory memory in the POS device and are executable by the one or more hardware processors in the POS device to provide a security engine that is configured to receive environment signals from the one or more environment sensors in the POS device and analyze those environment signals to determine a security breach.

A point of sale (POS) security system includes a POS device including a non-transitory memory, one or more hardware processors, and one or more environment sensors. A plurality of POS instructions are located on the non-transitory memory in the POS device and executable by the one or more hardware processors in the POS device to provide a POS engine that is configured to receive and transmit payment information for conducting a payment transaction associated with a purchase. A plurality of security instructions are located on the non-transitory memory in the POS device and are executable by the one or more hardware processors in the POS device to provide a security engine that is configured to receive environment signals from the one or more environment sensors in the POS device and analyze those environment signals to determine a security breach.

A virtual management system comprises video cameras, and various other sensors that acquire event data indicative relating to the processing of stock. This data is passed to a local data collection device that aggregates the event data and passes it via a network to a number of remote data processing modules. The event data is allocated to each of the data processing modules based upon their assigned tasks by a virtual manager agent. A data processing module receives the aggregated event data from the local data collection device via a network and processes the event data according to a set of pre-defined rules. The data processing module generates an alert in response to the processing of the event data indicating that a predefined event has occurred, and transmits the alert to a remote device associated with an employee.

Systems and methods are disclosed for security breach notification. In one implementation, an indication of a security breach is received, at a first device with respect to a user account. Based on the indication of the security breach, a processing device generates a security breach notification, the security breach notification including an instruction to initiate at an account repository one or more actions with respect to the user account. An attempt is made to transmit the security breach notification to the account repository via a first communication interface of the first device. In response to a determination that the security breach notification was not successfully transmitted to the account repository, the security breach notification is transmitted to a second device via a second communication interface of the first device.

The present disclosure is directed to systems and methods for generating investigations of user behavior. In an example embodiment, the system includes a video camera configured to capture video of user activity, a video analytic module to perform real-time video processing of the captured video to generate non-video data from video, and a computer configured to receive the video and the non-video data from the video camera. The computer includes a video analytics module configured to analyze one of video and non-video data to identify occurrences of particular user behavior, and an investigation generation module configured to generate an investigation containing at least one video sequence of the particular user behavior. In some embodiments, the investigation is generated in near real time. The particular user behavior may be defined as an action, an inaction, a movement, a plurality of event occurrences, a temporal event and/or an externally-generated event.

Aspects of the present disclosure include methods, systems, and non-transitory computer readable media that perform the steps of receiving a visual code identifier associated with a transaction of one or more transaction merchandises, receiving a radio frequency identification (RFID) identifier associated with the transaction, analyzing the image, determining at least one of one or more detected merchandises, a number of the one or more detected merchandises, and a price of the one or more detected merchandises based on information in the RFID identifier and the analyzed image, determining a merchandise discrepancy, a number discrepancy, or a price discrepancy, and transmitting, in response to determining the at least one of the merchandise discrepancy, the number discrepancy, or the price discrepancy, an alert.

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 system and method for replaying a security video at the time of a fraudulent incident at a point-of-sale checkout terminal is presented. The video playback takes place in real-time, when the event occurs, allowing personnel to take appropriate measures, corrective or otherwise, to deal with the event. Examples of such events may include when a weight-based security alert is triggered at a self-checkout, when a cashier or customer has missed scanning an item at the checkout, or other possible events where rapid replay of relevant video is required.

A system and method for verifying a non-scan item at a self-checkout point-of-sale terminals provided. A merchandise item that isn't scanned at the self-checkout terminal is identified by a detection system. Further, a user helper device is provided to verify the incident by prompting the shopper for an input. The user helper device is operably connected to the self-checkout point-of-sale terminal and the detection system to determine and verify a fraudulent incident occurring during a transaction activity by the shoppers. Further, a store attendant device is provided for human intervention when necessary.

Disclosed herein are systems and methods for determining whether an unknown product matches a scanned barcode during a checkout process. An edge computing device or other computer system can receive, from an overhead camera at a checkout lane, image data of an unknown product that is placed on a flatbed scanning area, identify candidate product identifications for the unknown product based on applying a classification model and/or product identification models to the image data, and determine based on the candidate product identifications, whether the unknown product matches a product associated with a barcode that is scanned at a POS terminal in the checkout lane. The classification model can be used to determine n-dimensional space feature values for the unknown product and determine which product the unknown product likely matches. The product identification models can be used to determine whether the unknown product is one of the products that are modeled.