Abstract: Item images and item information for an item identified as being associated with a potential theft during a transaction at a transaction terminal are sent in real time to an alert controller of a management terminal. The item images and item information with transaction details are presented on a display for resolution by a clerk operating the management terminal. A timer is also set and a confidence score calculated representing a confidence level that the item is the subject of theft. When the timer expires and there is still no resolution provided by the clerk a decision is made as to whether to interrupt the transaction processing on the transaction terminal for assistance or whether to permit the transaction to complete on the transaction terminal based on the calculated confidence score.

Abstract: Methods are provided in which a recording service obtains a multimedia stream along with metadata of an established collaboration session in which at least two participants collaborate via respective user devices. The recording service identifies each of the at least two participants of the established collaboration session based on the metadata and obtains an individual recording privacy control associated with each of the at least two participants based on identifying. The recording service further generates a recording of the established collaboration session restricted by the individual recording privacy control for each of the at least two participants.

Abstract: Visual features of a vehicle, a vehicle's orientation with respect to a transaction terminal, and an individual associated with the vehicle are derived from video captured of the terminal and a surrounding area of the terminal. Additional information associated with brute force attacks in a location associated with the terminal are obtained as additional features. The visual features and the additional features are provided as input to a trained Machine-Learning Model (MLM) and the MLM provides as output a confidence value representing a prediction as to whether the current vehicle and the current individual are potentially about to engage in a brute force attack on the terminal. When the confidence value exceeds a threshold value, enhanced feature detection is enabled on the video, external systems are notified, and an incident packet of information is assembled.

Abstract: Payment card slot tampering at a transaction terminal is detected in real time. One or more images from one or more cameras are analyzed. The camera(s) is/are focused overhead of the terminal on an area adjacent to and in front of a card slot for a card reader of the terminal. The images are analyzed for determining whether hands of arms for an operator of the terminal are performing actions that indicate the operator may be attempting to install a card skimmer/shimmer into the card slot and/or attempting to remove an existing skimmer/shimmer from the card slot. When card slot tampering event is detected at the terminal a variety of automated actions are processed, such as shutting down the card reader, shutting down the terminal, confiscating any payment card inserted into the card slot, notifying a financial institution, and/or notifying legal authorities.

Abstract: An identity of a customer within an establishment is authenticated using a variety of captured biometric features obtained from sensors and/or video. Video capturing movements/interactions of the customer is analyzed in real time to identify the customer's behavior and actions. Any staff of the establishment who interact with the customer are identified from the video. Transaction data and other data retained for the customer by the establishment are aggregated and linked with the video and the customer identity. The linked data is analyzed in combination with the customer behavior and actions to determine responses within the establishment to customer-initiated transactions. In an embodiment, the customer is authorized to perform at least one transaction within the establishment based on the authenticated identity and linked data without a presentation by the customer of an identification card, a Personal Identification Number (PIN), a password and/or verification by a staff member.

Abstract: Methods are provided in which a recording service obtains a multimedia stream along with metadata of an established collaboration session in which at least two participants collaborate via respective user devices. The recording service identifies each of the at least two participants of the established collaboration session based on the metadata and obtains an individual recording privacy control associated with each of the at least two participants based on identifying. The recording service further generates a recording of the established collaboration session restricted by the individual recording privacy control for each of the at least two participants.

Abstract: A cross-entity and cross-retailer platform is provided that captures transaction data (and/or browser history data associated with online browser-based transactions), indexes, and stores the data in a cloud-accessible data store. A cloud service is provided that custom processes retailer and entity-defined workflows based on purchase transactions using the data store. The service discovers and updates trends and patterns associated with item sales for a given retailer or for a given entity across channels associated with in-store and online item sales. The trends and patterns are dynamically reported to the corresponding entity or the corresponding retailer. The entities may comprise manufacturers of an item, a supplier of the item, a distributor of the item, and a Consumer Packaging Goods (CPG) company of the item.

Abstract: Payment card slot tampering at a transaction terminal is detected in real time. One or more images from one or more cameras are analyzed. The camera(s) is/are focused overhead of the terminal on an area adjacent to and in front of a card slot for a card reader of the terminal. The images are analyzed for determining whether hands of arms for an operator of the terminal are performing actions that indicate the operator may be attempting to install a card skimmer/shimmer into the card slot and/or attempting to remove an existing skimmer/shimmer from the card slot. When card slot tampering event is detected at the terminal a variety of automated actions are processed, such as shutting down the card reader, shutting down the terminal, confiscating any payment card inserted into the card slot, notifying a financial institution, and/or notifying legal authorities.

Abstract: Visual features of a vehicle, a vehicle's orientation with respect to a transaction terminal, and an individual associated with the vehicle are derived from video captured of the terminal and a surrounding area of the terminal. Additional information associated with brute force attacks in a location associated with the terminal are obtained as additional features. The visual features and the additional features are provided as input to a trained Machine-Learning Model (MLM) and the MLM provides as output a confidence value representing a prediction as to whether the current vehicle and the current individual are potentially about to engage in a brute force attack on the terminal. When the confidence value exceeds a threshold value, enhanced feature detection is enabled on the video, external systems are notified, and an incident packet of information is assembled.

Abstract: A cross-entity and cross-retailer platform is provided that captures transaction data, indexes, and stores the data in a cloud-accessible data store. A service is provided that custom processes retailer and entity-defined workflows based on purchase transactions using the data store. The service also generates and maintains correlations between items, the transactions, geographical locations, retailers, and stores of the retailers. The correlations are provided as timely retail recommendations to the retailers and entities for suggested changes that are likely to optimize purchase transactions. The entities may comprise manufacturers of an item, a supplier of the item, a distributor of the item, and a Consumer Packaging Goods (CPG) company of the item.

Abstract: A method includes generating, by a sensor, physiological data associated with a user during a sleep session. The method also includes processing, by an electronic device including one or more processors, the generated physiological data to distinguish between on-therapy data and off-therapy data. The on-therapy data is the generated physiological data while a respiratory therapy system is coupled to the user and supplies pressurized air to an airway of the user. The off-therapy data is the generated physiological data while the respiratory therapy system is not supplying pressurized air to the airway of the user. The method also includes determining, by the electronic device, a sleep measure based at least in part on the off-therapy data.

Abstract: An item return transaction for an item is identified at a transaction terminal. The item is authenticated using multiple factors at least some of which are independent of item code identification for the item. A fraud score is calculated based on the multiple factors, item code identification, and data that is specific to a customer associated with the transaction, specific to the item, specific to a store associated with the transaction terminal, and specific to a retailer associated with the store. The fraud score and a customer-return grade for the customer are processed to determine whether the transaction can complete at the terminal without assistance or whether the transaction is to be held in abeyance for an audit (onsite audit or remote network-based audit). In an embodiment, the t terminal is a Self-Service Terminal (SST) and the transaction is a self-item return transaction conducted by a customer at the terminal.

Abstract: Individuals, business transactions, and business activities are monitored for actions and behaviors of the individuals during performance of establishment processes through video feeds captured by cameras, sensor data captured by sensors, and information captured by transaction systems. Transaction/activity information associated with transactions/activities being processed by a transaction system of the establishment or performed by individuals within the establishment are monitored. The actions, behaviors, transaction information, activity information, and establishment processes are correlated to process controls, policies, and procedures of the establishment and logged. Non-compliant actions, behaviors, transaction information, activity information, and/or transaction/activity thresholds generate real-time remedial actions, such as audits, training, and notifications.

Abstract: Various embodiments each include at least one of systems, devices, methods, and software for multi-camera simultaneous imaging for multiple processes. Some such embodiments may be embodied in a dedicated appliance or chip while other embodiments may be embodied in a product scanner, in software, or in a combination of hardware and software. One method embodiment includes receiving images from a plurality of cameras, the images from each device captured at various illumination and exposure levels. This method then sorts the images based on illumination and exposure levels for distribution to a plurality of image processing services that each perform at least one task with regard to a received image and then presents the images to respective services for which they are sorted.

Abstract: A ratio associated with capture of image frames by cameras of a scanner during short exposure mode and long exposure mode is configurable for scanner operation. Moreover, camera activation signals for the cameras are controlled during long exposure mode of the cameras to reduce illumination by illumination sources of the scanner during the long exposure mode of the cameras.

Abstract: Zones a defined within an enterprise. Video captured from the zones are monitored for threats (financial or physical). Any transaction data associated with transactions are monitored with the video along with sensor data captured from sensors within the zones. Threat policies are evaluated to identify actions and behaviors of individuals within the zones and threat scores are maintained. When a current threat score associated with a specific type of threat for a given individual or set of individuals exceeds a threshold, one or more automated remediation or threat avoidance actions are processed to mitigate and/or prevent the perceived threat.

Abstract: Payment card slot tampering at a transaction terminal is detected in real time. One or more images from one or more cameras are analyzed. The camera(s) is/are focused overhead of the terminal on an area adjacent to and in front of a card slot for a card reader of the terminal. The images are analyzed for determining whether hands of arms for an operator of the terminal are performing actions that indicate the operator may be attempting to install a card skimmer/shimmer into the card slot and/or attempting to remove an existing skimmer/shimmer from the card slot. When card slot tampering event is detected at the terminal a variety of automated actions are processed, such as shutting down the card reader, shutting down the terminal, confiscating any payment card inserted into the card slot, notifying a financial institution, and/or notifying legal authorities.

Abstract: Visual features of a vehicle, a vehicle's orientation with respect to a transaction terminal, and an individual associated with the vehicle are derived from video captured of the terminal and a surrounding area of the terminal. Additional information associated with brute force attacks in a location associated with the terminal are obtained as additional features. The visual features and the additional features are provided as input to a trained Machine-Learning Model (MLM) and the MLM provides as output a confidence value representing a prediction as to whether the current vehicle and the current individual are potentially about to engage in a brute force attack on the terminal. When the confidence value exceeds a threshold value, enhanced feature detection is enabled on the video, external systems are notified, and an incident packet of information is assembled.

Abstract: Cash trapping at an Automated Teller Machine (ATM) is detected in real time. One or more images from one or more cameras are analyzed. The camera(s) is/are focused overhead of the ATM or on a cash slot of a dispense module for the ATM. The images are analyzed for determining one or more of whether the dispenser module is authentic, whether the cash slot opened or did not open when it should have opened for a cash withdraw, whether visual features of the dispense module have changed over a configurable period of time, and whether hands, gestures, and actions of a person present at the ATM indicate that cash trapping is taking place at the ATM. When cash trapping is detected at the ATM a variety of automated actions are processed, such as shutting down the dispense module, shutting down the ATM, notifying a financial institution, and/or notifying legal authorities.

Abstract: A method includes data associated with a sleep session of a user, including respiration data associated with the user during at least a portion of the sleep session and audio data reproducible as one or more sounds during at least a portion of the sleep session. The method also includes determining a respiration signal associated with the user during the sleep session based, at least in part, on at least a portion of the data. The method also includes identifying an event experienced by the user during the sleep session based, at least in part on, at least a portion of the data. The method also includes causing to be communicated to the user via a user device a graphical representation of a portion of the respiration signal and an event indication that aids in identifying the identified event within the graphical representation of the portion of the respiration signal.