Method, system and apparatus are provided for smart window activation to prevent laser disturbance. The apparatus may include a window formed of smart glass capable of being activated in discrete sections to be impenetrable to laser light and having a smart glass activation system. A sensor arrangement may detect laser light impacting on the window and may provide data as to the position of the impact on the window. A computer-implemented window protection system may receive input regarding detecting a laser beam impacting a window from the sensor arrangement, determine the position of the laser beam impact on the window and determine a section of the window in which the smart glass is to be activated, and control activation of the smart glass in the section of the window to make the section impenetrable to laser light by instructing the smart glass activation system.

A system for managing the data of an aircraft includes a device of avionics type installed in the aircraft, the installed device being: connectable to an electrical power source of avionics type; connectable to the avionics data bus; comprising a docking support; a removable device of non-avionics type being able to be fixed onto the docking support, the removable device comprising computation and storage resources for the processing of avionics data and, optionally, wireless communication. Developments of the invention describe electrical isolation mechanisms, the facility to cut any wireless communication, in particular cellular, of the removable device, the control and/or the updating of the removable device by ground teams. Method and software aspects are described.

Subject matter described herein includes generating a visual environment for interactive development of a machine learning (ML) model. The method includes accessing observations of data each of which includes values of independent variables and a dependent variable. The method includes performing an interactive feature construction and selection in which select independent variables are selected as or transformed into a set of features for use in building a ML model to predict the dependent variable. The method includes building the ML model using a ML algorithm, the set of features, and a training set produced from the set of features and observations of the data. And the method includes outputting the ML model for deployment to predict the dependent variable for additional observations of the data.

An unmanned vehicle capable of operating in harsh environments is disclosed. The unmanned vehicle includes an aerial platform, a piloting system supported by the aerial platform, a medium source supported by the aerial platform, and a control system having a processor running computer executable code that actuates the medium source to emit a medium away from the aerial vehicle with an intensity sufficient to disorient a subject when the medium interacts with an exteroceptive sense of a subject.

An unmanned autonomous device includes an isolation kernel having plurality of drivers respectively dedicated to a plurality of subsystems. The drivers are configured to facilitate communication between the subsystems. A gateway in the unmanned autonomous device is configured to control routing of data between the subsystems via the drivers respectively dedicated to the subsystems, such that data is only allowed to be passed between the subsystems along predefined routes.

A cockpit access security system controls changes to a record of personnel authorized to access the cockpit by reference to the state of the aircraft as determined by a plurality of on-board sensors indicating the state of particular aircraft subsystems.

A situation recognition device (10) including a surveillance processor (1) and an Al system (3). The surveillance processor receives visual and/or acoustic surveillance signals (E) from an aircraft passenger compartment (20) via an input interface (7). The Al system (3) includes an Al processor (4), a rule set generator (5) based on self-learning algorithms, and a reference rule set memory (6). The Al system is in bidirectional data communication with the surveillance processor (1). The Al processor (4) checks, upon a request (Q) from the surveillance processor (1), data patterns in the received visual and/or acoustic surveillance signals (E) for deviations from data patterns in a reference rule set (R) stored in the reference rule set memory (6). The surveillance processor (1) outputs indicator signals (A) via the output interface (8) if deviations determined by the Al processor (4) exceed one or more predefinable deviation threshold values.

An unmanned vehicle capable of operating in harsh environments is disclosed. The unmanned vehicle includes an aerial platform, a piloting system supported by the aerial platform, a medium source supported by the aerial platform, and a control system having a processor running computer executable code that actuates the medium source to emit a medium away from the aerial vehicle with an intensity sufficient to disorient a subject when the medium interacts with an exteroceptive sense of a subject.

A door locking system for a door module that separates compartments in an aircraft. Door locking system has locking element that is adapted to maintain door panel of door module in a closed position. Door locking system further includes first and second mechanisms that are adapted to release door panel from the closed position in a normal and an abnormal mode, respectively. Second mechanism is spatially segregated from and operates independently of first mechanism. Second mechanism includes locking element release actuator, pressure sensor, and controller that directs locking element release actuator to act on locking element when pressure sensor detects a difference in pressure between the compartments that exceeds a predetermined threshold.

An aircraft barrier system separating, within an aircraft, a secure area from a passenger cabin of the aircraft, comprises a barrier installed inside the passenger cabin and configured to move between an open position and a closed position, a latch mounted to the barrier, and a locking device comprising a latching clamp configured to lock the latch when the barrier is in the closed position. The aircraft barrier system further comprises a release mechanism configured to move the latching clamp from a locking state locking the latch to an unlocking state releasing the latch, wherein the release mechanism is further configured to delay the moving of the latching clamp from the locking state to the unlocking state. Also, an aircraft area and an aircraft having such aircraft barrier system.