Abstract: Aspects of the disclosure relate to edge-computing (“EC”)-based systems and methods for fraud mitigation. The systems and methods may utilize a multi-layer architecture. The architecture may include a set of N gatekeeper units, and each gatekeeper unit may be associated with an EC device. When a transaction request is received, the request may be processed at a first gatekeeper unit, and, if validated, successively processed by the set of N gatekeeper units. If any gatekeeper unit flags the request as suspicious, the unit may emit an audible alert that may be sensed by the associated EC device. The EC device may transmit a signal to one or more of the other gatekeeper units to perform additional processing for the request. When the request reaches the Nth gatekeeper unit and achieves validation, the transaction may be executed via a central server connected to a transaction network.

Abstract: This application describes apparatus and methods for using edge-computing to control resource distribution among access channels, such as a retail banking center. Edge-nodes may be configured to move a product display in response to detected or expected customer traffic flow in or near a retail location. Edge-nodes may be configured to redirect resources provided by a cloud computing environment to or away from the retail location. Based on customer traffic flow, edge-nodes may direct customers/resources to a retail location and ensure the retail location provides a predetermined quality of service.

Abstract: Aspects of the disclosure relate to edge-computing (“EC”)-based systems and methods for fraud mitigation. The systems and methods may utilize a multi-layer architecture. The architecture may include a set of N gatekeeper units, and each gatekeeper unit may be associated with an EC device. When a transaction request is received, the request may be processed at a first gatekeeper unit, and, if validated, successively processed by the set of N gatekeeper units. If any gatekeeper unit flags the request as suspicious, the unit may emit an audible alert that may be sensed by the associated EC device. The EC device may transmit a signal to one or more of the other gatekeeper units to perform additional processing for the request. When the request reaches the Nth gatekeeper unit and achieves validation, the transaction may be executed via a central server connected to a transaction network.

Abstract: Aspects of the disclosure relate to edge-computing (“EC”)-based systems and methods for fraud mitigation. The systems and methods may utilize a multi-layer architecture. The architecture may include a set of N gatekeeper units, and each gatekeeper unit may be associated with an EC device. When a transaction request is received, the request may be processed at a first gatekeeper unit, and, if validated, successively processed by the set of N gatekeeper units. If any gatekeeper unit flags the request as suspicious, the unit may emit an audible alert that may be sensed by the associated EC device. The EC device may transmit a signal to one or more of the other gatekeeper units to perform additional processing for the request. When the request reaches the Nth gatekeeper unit and achieves validation, the transaction may be executed via a central server connected to a transaction network.

Abstract: This application describes apparatus and methods for using edge-computing to control resource distribution among access channels, such as a retail banking center. Edge-nodes may be configured to move a product display in response to detected or expected customer traffic flow in or near a retail location. Edge-nodes may be configured to redirect resources provided by a cloud computing environment to or away from the retail location. Based on customer traffic flow, edge-nodes may direct customers/resources to a retail location and ensure the retail location provides a predetermined quality of service.

Abstract: This application describes apparatus and methods for using edge-computing to control resource distribution among access channels, such as a retail banking center. Edge-nodes may be configured to move a product display in response to detected or expected customer traffic flow in or near a retail location. Edge-nodes may be configured to redirect resources provided by a cloud computing environment to or away from the retail location. Based on customer traffic flow, edge-nodes may direct customers/resources to a retail location and ensure the retail location provides a predetermined quality of service.

Abstract: Aspects of the disclosure relate to edge-computing (“EC”)-based systems and methods for fraud mitigation. The systems and methods may utilize a multi-layer architecture. The architecture may include a set of N gatekeeper units, and each gatekeeper unit may be associated with an EC device. When a transaction request is received, the request may be processed at a first gatekeeper unit, and, if validated, successively processed by the set of N gatekeeper units. If any gatekeeper unit flags the request as suspicious, the unit may emit an audible alert that may be sensed by the associated EC device. The EC device may transmit a signal to one or more of the other gatekeeper units to perform additional processing for the request. When the request reaches the Nth gatekeeper unit and achieves validation, the transaction may be executed via a central server connected to a transaction network.

Abstract: This application describes apparatus and methods for using edge-computing to control resource distribution among access channels, such as a retail banking center. Edge-nodes may be configured to move a product display in response to detected or expected customer traffic flow in or near a retail location. Edge-nodes may be configured to redirect resources provided by a cloud computing environment to or away from the retail location. Based on customer traffic flow, edge-nodes may direct customers/resources to a retail location and ensure the retail location provides a predetermined quality of service.

Abstract: The invention, as embodied herein, comprises an improved portable maritime scoring and simulation system that comprises three or more buoys that are deployed in an area of water selected for maritime combat training. Attached to each buoy are a global positioning system receiver, an RF radio system, an acoustic analysis system, and a microprocessor. The acoustic analysis system is designed to capture an acoustic signature of ordnance impacting the water with predetermined characteristics. The system includes an RF radio repeater system linked to a system controller to control and monitor the elements of the system. In operation, when an acoustic signature is captured by the acoustic analysis system, the RF radio system, in one embodiment, transmits the time of the capture along with the GPS location of the buoy to the RF radio repeater system linked to the system controller.

Abstract: An apparatus for determining star location includes a star tracker, a star catalog and a controller. The star tracker is used to sense the positions of stars and generate signals corresponding to the positions of the stars as seen in its field of view. The star catalog contains star location data that is stored using a primary and multiple secondary arrays sorted by both declination (DEC) and right ascension (RA), respectively. The controller checks the star catalog and determines which stars to track. The controller does this determination by using an algorithm to sort the primary and secondary arrays to determine which stars are located in the star tracker field of view. The controller then commands the star tracker to track these stars and uses them to determine the spacecraft attitude.

Abstract: An apparatus for determining stellar inertial attitude based upon a plurality of stars includes a star tracker and a controller. The star tracker is used to sense the positions of stars and generate signals corresponding to the positions of the stars as seen in its field of view. The controller checks a star catalog and actively determines which stars to track. The controller does this determination in terms of each star's relative geometry. The controller then commands the star tracker to track these stars and uses them to determine the spacecraft attitude.