Methods for data monitoring with changeable routing of input channels are disclosed. An example method includes a data collector communicatively coupled to a plurality of input channels and a data acquisition circuit to interpret the detection values, each corresponding to an input channel. Sensor data is acquired from a first route of input channels and stored together with specifications for the sensors that correspond to the input channels. The sensor data is evaluated with respect to an alarm threshold level and an alarm state set when the alarm threshold level is exceeded. A response circuit changes a routing of the input channels for data collection from a first routing to an alternate routing of input channels, wherein the alternate routing of input channels comprise the first input channel and a group of input channels related to the first input channel.

In an illustrative embodiment, the present disclosure relates to systems, methods, and an industrial internet of things (IIOT) platform and environment for generating a device integration definition to be used for configuring a new device type for interoperability with the IIOT platform and environment, where the device integration definition includes a standardized format in a programming language syntax, the device integration definition is customizable using code hook templates for issuing commands to the device type, and the device integration definition is customizable using control templates for applying the device integration definition as a foundation for preparing a graphical user interface for configuring devices of the device type with the IIOT platform and environment.

An asset condition monitoring method with automatic anomaly detection may include receiving local condition data from an asset fleet, identifying at least one anomaly in the received condition data, identifying a new potential failure case dependent on the identified anomaly, determining a specific condition model dependent on the identified new potential failure case, where the specific condition model is configured for predicting the new potential failure case, and providing the specific condition model to the plurality of assets and/or to digital models of the plurality of assets.

A system and method for controlling a process such as an oil production process is disclosed. The system comprises multiple intelligent agents for processing data received from a plurality sensors deployed in a job site of an oil well, and applies a probabilistic model for evaluating risk and recommending appropriate control action to the process.

According to an embodiment, a monitoring apparatus configured to generate time-series predicted data based on time-series measured data and a prediction model that generates predicted data including one or more predicted values predicted to be output from one or more sensors; and generate, for a first sensor among the one or more sensors, a displayed image including a measured value graph representing a temporal change in a measured value included in the time-series measured data in a second period after a first period, a predicted value graph representing a temporal change in a predicted value included in time-series predicted data in the second period, past distribution information representing a distribution of a measured value in the first period, and measurement distribution information representing a distribution of the measured value included in the time-series measured data in the second period.

Systems for data collection in an industrial environment are disclosed. A system may include a sensor communication circuit to interpret a plurality of sensor data values, a sensor data storage profile circuit to determine a data storage profile, the data storage profile comprising a data storage plan for the plurality of sensor data values. A system may also include a network coding circuit to provide a network coding value in response to the plurality of sensor data values and the data storage profile, and a sensor data storage implementation circuit to store at least a portion of the plurality of sensor data values in response to the data storage profile and the network coding value.

Embodiments describing an approach to aligning multiple time series, calculating an indicator function, estimating a coefficient vector based on the indicator function, and updating the coefficient vector. Additionally, embodiments comprise determining if a change in the coefficient vector is less than a predetermined value, and responsive to determining the change in the coefficient vector is less than the predetermined value outputting a target time series for controlling aluminum smelting.

The disclosure provides an environment in which it is possible to switch an algorithm involved in an abnormality detection process. A control device: calculates a feature quantity from a state value acquired from a monitored object; uses a learning model on the basis of the calculated feature quantity to execute one of a plurality of types of algorithms for calculating a value indicating the probability that an abnormality is occurring in the monitored object; determines, on the basis of the calculated value, whether the abnormality is occurring; and switches, in accordance with a condition defined in advance, the one algorithm that is executed.

An apparatus, methods and systems for monitoring network-sensitive data collection related to an industrial production process are disclosed. The system may include a data collector communicatively coupled to a plurality of input channels and to a network infrastructure, a data storage circuit structured to store a plurality of collector routes wherein the data collector receives collected data utilizing a selected collector route, a data analysis circuit structured to determine a data collection quality parameter and a state value of the industrial production process, a pattern recognition circuit structured to determine an identified pattern in response to at least a portion of the collected data and at least one of the state value or the data collection quality parameter, and an analysis response circuit structured to adjust one of the collector routes or the industrial production process in response to the identified pattern.

Systems and methods for data collection in an industrial environment can include a data collector to route analog signals from a plurality of analog sensor inputs to a plurality of output channels of in accordance with a first routing scheme and a controller configured to adjust the routing scheme to a second routing scheme. The first routing scheme may include providing at least two of the plurality of analog sensor inputs at one of the plurality of output channels and the second routing scheme may include providing at least one of the at least two of the plurality of analog sensor inputs to a different one of the plurality of output channels.