An apparatus is provided which includes a processing circuit and a plurality of sensors connected to a vehicle, where at least one of the plurality of sensors is positioned on an undercarriage of the vehicle. The plurality of sensors can detect variations in a road on which the vehicle is traveling. The plurality of sensors can also generate information corresponding to the variations of the road. The plurality of sensors can also transmit the information corresponding to the variations in the road to the processing circuit. The information collected by the plurality of sensors may then be used to augment a driving capability of the vehicle.

A compressed air provision device (4) for carrying out a closed-loop control, in particular a closed-loop position control and/or a closed-loop pressure control, on the basis of controller parameters (RP), wherein the compressed air provision device (4) has a machine-learning model (55) and is designed to provide, using the machine-learning model (55), the controller parameters (RP) on the basis of entered system parameters (SP) which describe physical properties of a system (100) in which the compressed air provision device (4) is to be used, and to carry out the closed-loop control on the basis of the provided controller parameters (RP).

A policy creation unit creates a plurality of policies each including a predetermined number of rules in which a condition for determining a state of an object is combined with an action in the state. An action determination unit determines, for each of the plurality of created policies, an action to be performed while a state of the object is changed from a first state to a second state in accordance with the policy. A policy evaluation unit determines, in accordance with a difference between a state between the first state and the second state and a desired state, the quality of the determined action and determines, for each of the plurality of policies, the quality of the policy based on the determined quality of the action. A policy selection unit selects the policy that is determined to have a high quality.

In order to control a technical system by means of control model a data container is received, in which data container a control model having a training structure and model type information are encoded over all the model types. One of multiple model-type specific execution modules is selected for the technical system as a function of the model type information. Furthermore, operating data channels of the technical system are assigned input channels of the control model as a function of the model type information. Operating data of the technical system are acquired via a respective operating data channel and are transferred to the control model via an input channel assigned to this operating data channel. The control model is executed by means of the selected execution module, wherein control data are derived from the transferred operating data according to the training structure and are output to control the technical system.

A method for increasing a meantime between service visits in an industrial system includes receiving event information from at least one information source, building an event network from the received event information, identifying a sequence of events indicative of a fault, and determining a cost-minimizing resolution to address the fault, wherein the event network is configured to identify a sequence of events that do not occur in direct chronological sequence. A services diagnostic engine may be configured to receive the event information, extract features of each event in the event information, identify a relationship between a first event and a second event and create a logical connection between the first and second event. The cost minimizing recommendation includes a remote operation to reset a component, for example remotely resetting a circuit breaker. The cost minimizing recommendation may be carried out automatically or presented to a user for consideration.

An information processing device according to one aspect of the present invention includes a first acquirer configured to acquire measured data of a sensor, a second acquirer configured to acquire maintenance information related to maintenance performed on the sensor, a learner configured to learn teacher data in which the acquired maintenance information as label information is associated with the acquired measured data to generate a determination model, and a storage storing the generated determination model.

A method for ascertaining emissions of a motor vehicle driven with the aid of an internal combustion engine in a practical driving operation. A machine learning system is trained to generate time curves of the operating variables with the aid of measured time curves of operating variables of the motor vehicle and/or of the internal combustion engine, and to then ascertain the emissions as a function of these generated time curves.

Using a read sensor to sense wrong-way driving. A method may include sensing, by a rear sensor of a vehicle, an environment of the vehicle to provide rear sensed information; processing the rear sensed information to provide at least one rear-sensed vehicle progress direction indications; generating or receiving at least one front-sensed vehicle progress direction indications; wherein the at least one front-sensed vehicle progress direction indications is generated by processing front-sensed information acquired during right-way progress; comparing at least one rear-sensed vehicle progress direction indications to the at least one front-sensed vehicle progress direction indications to determine whether the vehicle is wrong-way driving; and responding to the finding of the wrong-way driving.

A control device which predicts the timing of disconnection of a power supply is provided with a machine learning device configured to learn the disconnection timing of the power supply. The machine learning device is provided with a state observation unit configured to observe an operation content for the control device for each user as one of state variables representative of a present state of an environment, a determination data acquisition unit configured to acquire determination data which indicates that power disconnection of the control device is commanded by the user, and a learning unit configured to learn the operation content for each user and a command for the power disconnection in association with each other by using the state variable and the determination data.

A vision system (1) for a motor vehicle, includes a sensing device (40) adapted to sense data (99), a data processing device (7) adapted to process the sensed data (99), wherein the data processing device (7) includes a controller (30) adapted to switch a power mode of the data processing device (7) between a low-power mode and a high-power mode, wherein a high-power application (110) can be executed in the high-power mode. The data processing device (7), in a low-power mode, is adapted to execute a power mode classifier (20), and the power mode classifier (20) is adapted to classify any input data (99) from the sensing device (40) as requiring executing the high-power application (110) or not, and to output a high-power mode request (130) to the controller (30) to switch the power mode of the data processing device (7) from the low-power mode to the high-power mode in case the power mode classifier (20) has classified the input data (99) as requiring executing the high-power application (110).