An embodiment of the invention provides a method and system including a sensor on a vehicle and a processor connected to the sensor. The processor determines a probability of falling based on input from the sensor, whether the probability of falling exceeds a threshold, and a state of an operator of the vehicle. An actuator connected to the processor receives a signal from the processor when the probability of falling exceeds the threshold and when the state of the operator includes an impaired state. Stabilizer wheels are connected to the actuator, where the signal includes a command to deploy the stabilizer wheels.

An embodiment of the invention provides a method and system including a sensor on a vehicle and a processor connected to the sensor. The processor determines a probability of falling based on input from the sensor, whether the probability of falling exceeds a threshold, and a state of an operator of the vehicle. An actuator connected to the processor receives a signal from the processor when the probability of falling exceeds the threshold and when the state of the operator includes an impaired state. Stabilizer wheels are connected to the actuator, where the signal includes a command to deploy the stabilizer wheels.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

A technique for enabling efficient retrieval of a digital representation of personality data of a user (402) by a client device (406) from a server (404) is disclosed, wherein the digital representation of the personality data is processed at the client device (406) to provide a user-adapted service to the user (402). A method implementation of the technique is performed by the server (404) and comprises storing a neural network being trained to compute personality data of a user based on input obtained from the user (402), receiving, from the client device (406), a request for a digital representation of personality data for a user (402), and sending, to the client device (406), the requested digital representation of the personality data of the user (402), wherein the personality data of the user is computed using the neural network based on input obtained from the user (402).

A technique for enabling efficient retrieval of a digital representation of personality data of a user (402) by a client device (406) from a server (404) is disclosed, wherein the digital representation of the personality data is processed at the client device (406) to provide a user-adapted service to the user (402). A method implementation of the technique is performed by the server (404) and comprises storing a neural network being trained to compute personality data of a user based on input obtained from the user (402), receiving, from the client device (406), a request for a digital representation of personality data for a user (402), and sending, to the client device (406), the requested digital representation of the personality data of the user (402), wherein the personality data of the user is computed using the neural network based on input obtained from the user (402).

An abnormal physical condition determination system includes: an extraction unit that extracts a plurality of feature quantities indicating a condition of a target person from an image of the target person; an accumulation unit that accumulates the plurality of feature quantities as time series data; a calculation unit that calculates a relationship between each feature quantity from the plurality of feature quantities accumulated in the accumulation unit; and a determination unit that determines an abnormal physical condition of the target person on the basis of the relationship. According to such an abnormal physical condition determination system, it is possible to appropriately determine the abnormal physical condition of the target person.

To better fulfill a sleep-inducing function for a seated person, a seat device includes a pressing device provided in a seat back and configured to press a back or a waist of a seated person to induce breathing; at least one of a temperature adjusting device configured to change a temperature of a seat cushion and/or the seat back and a shape adjusting device configured to change a surface shape of the seat cushion and/or the seat back; and a controller configured to control the pressing device to press the back or the waist of the seated person at a set cycle corresponding to a breathing cycle of a person at a sleeping time, and control the at least one of the temperature adjusting device and the shape adjusting device.

To better fulfill a sleep-inducing function for a seated person, a seat device includes a pressing device provided in a seat back and configured to press a back or a waist of a seated person to induce breathing; at least one of a temperature adjusting device configured to change a temperature of a seat cushion and/or the seat back and a shape adjusting device configured to change a surface shape of the seat cushion and/or the seat back; and a controller configured to control the pressing device to press the back or the waist of the seated person at a set cycle corresponding to a breathing cycle of a person at a sleeping time, and control the at least one of the temperature adjusting device and the shape adjusting device.

A terminal is disclosed. The terminal according to an embodiment of the present invention comprises: an output unit for outputting a notification; a storage unit for storing a database; a control unit for controlling the outputting of the notification; and an artificial intelligence unit for acquiring information regarding a user's context, and outputting a notification when the user's context corresponds to information included in the database, wherein the database includes at least one of a user's personal database, a standard activity database, and an accident type database.