A vehicle system includes a detection device structurally configured to capture an image, a door lock, where the door lock is positionable between a locked position and an unlocked position, a controller communicatively coupled to the detection device and the door lock, the controller including a processor and a non-transitory computer readable and executable instruction set, which when executed, causes the processor to receive a captured image of a user from the detection device, determine whether the captured image of includes protective equipment worn by the user, and direct the door lock to move into the unlocked position in response to determining that the protective equipment in the captured image meets a configurable protective equipment baseline.

Aspects of the subject disclosure may include, for example, determining, by a system comprising a processor, a driver profile according to a driver identity for a driver of a vehicle, selecting a driver-specific enforcement scenario for the vehicle according to the driver profile and traffic enforcement information that is associated with a vehicle location, and presenting an in-vehicle alert to convey the driver-specific enforcement scenario to the driver. Other embodiments are disclosed.

Aspects of the subject disclosure may include, for example, determining, by a system comprising a processor, a driver profile according to a driver identity for a driver of a vehicle, selecting a driver-specific enforcement scenario for the vehicle according to the driver profile and traffic enforcement information that is associated with a vehicle location, and presenting an in-vehicle alert to convey the driver-specific enforcement scenario to the driver. Other embodiments are disclosed.

Systems and methods are disclosed herein for implementation of a vehicle command operation system that may use multi-modal technology to authenticate an occupant of the vehicle to authorize a command and receive natural language commands for vehicular operations. The system may utilize sensors to receive data indicative of a voice command from an occupant of the vehicle. The system may receive second sensor data to aid in the determination of the corresponding vehicular operation in response to the received command. The system may retrieve authentication data for the occupants of the vehicle. The system authenticates the occupant to authorize a vehicular operation command using a neural network based on at least one of the first sensor data, the second sensor data, and the authentication data. Responsive to the authentication, the system may authorize the operation to be performed in the vehicle based on the vehicular operation command.

Systems and methods are disclosed herein for implementation of a vehicle command operation system that may use multi-modal technology to authenticate an occupant of the vehicle to authorize a command and receive natural language commands for vehicular operations. The system may utilize sensors to receive data indicative of a voice command from an occupant of the vehicle. The system may receive second sensor data to aid in the determination of the corresponding vehicular operation in response to the received command. The system may retrieve authentication data for the occupants of the vehicle. The system authenticates the occupant to authorize a vehicular operation command using a neural network based on at least one of the first sensor data, the second sensor data, and the authentication data. Responsive to the authentication, the system may authorize the operation to be performed in the vehicle based on the vehicular operation command.

A functional device is disclosed that can collect and process data/information/parameter values from one or more sensors and compares the same with one or more predefined/threshold value to suggest one or more actions and/or generate alerts/messages/suggestions to be performed by one or a combination of remote system, wearer, home automation network, healthcare provider, doctor, caretaker, among other stakeholders. Communication between the functional device, home automation server and a computational server that stores the data is also disclosed.

A method includes receiving a first set of images from an image capture device of a vehicle. The method also includes performing a first analysis of movement of biomechanical points of occupants of the vehicle in the first set of images. The method further includes receiving an indication that a traffic incident has occurred. The method also includes receiving a second set of images from the image capture device corresponding to when the traffic incident occurred. The method further includes performing a second analysis of movement of the biomechanical points of the occupants in the second set of images. The method also includes determining a likelihood of injury or a severity of injury to the occupants based on the first analysis of movement and the second analysis of movement.

A method includes receiving a first set of images from an image capture device of a vehicle. The method also includes performing a first analysis of movement of biomechanical points of occupants of the vehicle in the first set of images. The method further includes receiving an indication that a traffic incident has occurred. The method also includes receiving a second set of images from the image capture device corresponding to when the traffic incident occurred. The method further includes performing a second analysis of movement of the biomechanical points of the occupants in the second set of images. The method also includes determining a likelihood of injury or a severity of injury to the occupants based on the first analysis of movement and the second analysis of movement.

Automated occupant protection in stationary vehicles, including: detecting that an occupant is inside a stationary vehicle and that an operator is not in the stationary vehicle; detecting, based on one or more observations of the occupant, that one or more risk conditions have been met; and sending an alert to the operator in response to the one or more risk conditions being satisfied.

Automated occupant protection in stationary vehicles, including: detecting that an occupant is inside a stationary vehicle and that an operator is not in the stationary vehicle; detecting, based on one or more observations of the occupant, that one or more risk conditions have been met; and sending an alert to the operator in response to the one or more risk conditions being satisfied.