Abstract: A system includes a non-transitory computer-readable medium having instructions stored thereon. The instructions, when executed by one or more processors, cause the one or more processors to acquire image data from one or more cameras, process the image data to determine whether a passenger boarding bridge is docked to an aircraft, determine whether an autolevel wheel of the passenger boarding bridge is in a stowed position or a deployed position where the autolevel wheel engages an exterior surface of the aircraft, and provide an alert in response to the passenger boarding bridge being docked to the aircraft and the autolevel wheel being in the stowed position.

Abstract: In some embodiments, a system is provided that includes an edge computing device and at least one camera configured to obtain image data depicting at least a portion of an operations area. The edge computing device includes a non-transitory computer-readable medium that has a model data store and computer-executable instructions stored thereon. The instructions cause the edge computing device to perform actions including receiving at least one image from the at least one camera; processing the at least one image using at least one machine learning model stored in the model data store to determine at least one environmental state within the operations area; and controlling a device based on the determined at least one environmental state. The machine learning model is trained by a model management computing system that obtains training data via low-bandwidth connections to edge computing devices.

Abstract: In some embodiments, a system is provided that includes an edge computing device and at least one camera configured to obtain image data depicting at least a portion of an operations area. The edge computing device includes a non-transitory computer-readable medium that has a model data store and computer-executable instructions stored thereon. The instructions cause the edge computing device to perform actions including receiving at least one image from the at least one camera; processing the at least one image using at least one machine learning model stored in the model data store to determine at least one environmental state within the operations area; and controlling a device based on the determined at least one environmental state. The machine learning model is trained by a model management computing system that obtains training data via low-bandwidth connections to edge computing devices.

Abstract: A zinc-coated steel may be produced by performing a pre-alloying heat treatment after galvannealing the steel and prior to the hot stamping the steel. The pre-alloying heat treatment is conducted at a temperature between about 850° F. and about 950° F. in an open coil annealing process. The pre-alloying heat treatment allows for shorter time at the austenitization temperature to form a desired ?-Fe phase in the coating by increasing the concentration of iron. This also decreases the loss of zinc, and a more adherent oxide exists after hot stamping.

Abstract: A zinc-coated steel may be produced by performing a pre-alloying heat treatment after galvannealing the steel and prior to the hot stamping the steel. The pre-alloying heat treatment is conducted at a temperature between about 850° F. and about 950° F. in an open coil annealing process. The pre-alloying heat treatment allows for shorter time at the austenitization temperature to form a desired ?-Fe phase in the coating by increasing the concentration of iron. This also decreases the loss of zinc, and a more adherent oxide exists after hot stamping.