The present disclosure describes systems for data collection in an industrial environment. A system can include an industrial system including a plurality of components, at least one component operatively coupled to a sensor, and a sensor communication circuit to interpret a plurality of sensor data values in response to a sensed parameter group. A pattern recognition circuit may determine a recognized pattern value in response to at least a portion of the data values, wherein the recognized pattern value includes a secondary value. A sensor learning circuit may update the sensed parameter group in response to the recognized pattern value and adjust the interpreting the plurality of sensor data values in response to the updated sensed parameter group. The pattern recognition circuit and the sensor learning circuit iteratively determine the recognized pattern value and update the sensed parameter group to improve a sensing performance value.

The present disclosure describes systems for self-organized, network-sensitive data collection in an industrial environment. A system can include an industrial system including a plurality of components, at least one operatively coupled to a sensor, a sensor communication circuit to interpret sensor data values, and a system collaboration circuit to communicate a portion of the data values to a storage target according to a sensor data transmission protocol. A transmission environment circuit may determine transmission conditions corresponding to the communication of the portion of data values to the storage target and a network management circuit update the data transmission protocol in response to the transmission conditions.

A method for training a machine-learning model to assess at least one condition of industrial equipment, and/or at least one condition of a process running in an industrial plant, based on measurement data gathered by a plurality of sensors, includes: obtaining a plurality of records of measurement data that correspond to a variety of operating situations and a variety of conditions; obtaining, for each record of measurement data, a label that represents a condition in the operating situation characterized by the record of measurement data; and determining a plausibility of at least one record of measurement data, and/or a plausibility of at least one label, based at least in part on a comparison with at least one other record of measurement data, with at least one other label, and/or with additional information about the industrial equipment, and/or about the industrial plant where the industrial equipment resides, and/or about the process.

A method for storing data for at least one of a device state, device diagnosis and calibration of a field device in a cloud, with the field device having a self-monitoring functionality. The method includes device-internal registering of first data for at least one of a device state, device diagnosis and calibration by the field device and transfer of the device-internally registered first data from the field device to the cloud. Moreover, the method includes registering second data for at least one of a device state, device diagnosis and calibration of the field device using an external service computer and transferring the second data from the external service computer to the cloud. Both the first data as well as also the second data are stored in the cloud.

The present disclosure describes systems for self-organized, network-sensitive data collection in an industrial environment. A system may include an industrial system with a plurality of components operatively coupled to sensors, a sensor communication circuit to interpret the data values from the sensors, and a system collaboration circuit to communicate at least a portion of the data values over a network to a storage target computing device according to a sensor data transmission protocol. A transmission environment circuit may determine transmission feedback corresponding to the communication of the data values over the network, and a network management circuit to update the sensor data transmission protocol in response to the transmission feedback.

The present disclosure describes systems and methods for data collection in an industrial environment. A method can include providing a plurality of sensors to components of an industrial system, interpreting the data values from the sensors in response to a sensed parameter group, the group including a fused plurality of sensors. The method may also include determining a recognized pattern value comprising a secondary value determined in response to the data values, updating the sensed parameter group in response to the recognized pattern value, and adjusting the interpreting the data values in response to the updated sensed parameter group.

The invention relates to a method and to a system for optimizing the commissioning of at least one of a plurality of field devices in an automation technology system, which are used in different applications, wherein the system comprises at least: one database for saving application information and device types of the plurality of field devices and for saving parameter sets of the plurality of field devices; an electronic computation unit that accesses the remotely arranged database and classifies, assigns, compares, and/or processes the data saved there and has an algorithm for creating and proposing an optimal parameter set; software for supporting a user during commissioning of one of the plurality of field devices, wherein the electronic computation unit is operated by means of the software.

The invention relates to a method and to a system for optimizing the operation of a plurality of field devices in an automation technology plant. The method comprises: ascertaining application information and device types of field devices, wherein the application information describes the application of the respective field device; classifying the application information and storing the classified application information; ascertaining parameter sets from each of the plurality of field devices, wherein the parameter sets comprise multiple parameters and each parameter is assigned a parameter value or a parameter value range, and each field device has at least one current parameter set and at least one standard parameter set, and storing the parameter sets; comparing the current parameter sets with the standard parameter sets to determine actually used parameters of a device type for an application; and operating the field device on the basis of the actually used parameters.

An intrinsically-safe handheld field maintenance tool includes a controller, a process communication module, and a display. The process communication module is configured to communicate with a field device using a process communication protocol. The display is coupled to the controller. A user interface module is also coupled to the controller and is configured to receive user input. The controller is configured to detect a user input help request and provide a video output on the display in response to the user input help request.

The present disclosure describes systems for data collection in an industrial environment having a self-sufficient data acquisition box for capturing and analyzing data in an industrial process. A system can include a data circuit for analyzing a plurality of sensor inputs, a network control circuit for sending and receiving information related to sensor inputs to an external system, wherein the system provides sensor data to one or more similarly configured systems, and wherein the data circuit dynamically nominates a similarly configured system capable of providing sensor data to replace the system.