Methods and systems for detection in an industrial internet of things data collection environment with a self-organizing adaptive sensor swarm for industrial processes include a plurality of data collectors communicatively coupled to a plurality of input channels, wherein each of the plurality of data collectors is structured to collect detection values as collected data, an expert system circuit structured to self-organize one or more detection packages and an associated subset of the plurality of data collectors using a swarm optimization algorithm, a data acquisition circuit structured to interpret the collected data, a data analysis circuit structured to analyze the collected data, and a cognitive input selection facility for optimization of an input selection configuration for a collector route of the plurality of data collectors.

Methods and systems for a monitoring system for data collection in an industrial environment including a data collector communicatively coupled to a plurality of input channels connected to data collection points related to machine components, wherein at least one of the plurality of input channels is connected to a data collection point on a rotating machine component; a data acquisition circuit structured to interpret a plurality of detection values from the collected data, each of the plurality of detection values corresponding to at least one of the plurality of input channels; and an expert system analysis circuit structured to analyze the collected data, wherein the expert system analysis circuit determines a failure state for the rotating machine component based on analysis of the plurality of detection values, wherein upon determining the failure state the expert system analysis circuit provides the failure state to a data storage.

Methods and systems for a monitoring system for data collection in an industrial environment including a data collector communicatively coupled to a plurality of input channels connected to data collection points operationally coupled to an industrial component vibrationally coupled to a second industrial component in the industrial environment; a data storage structured to store a plurality of stored system response patterns; a data acquisition circuit; a data analysis circuit structured to: determine a measured noise pattern for the at least one industrial component; compare the measured noise pattern to the plurality of stored system response patterns to determine an identified noise pattern; and a response circuit structured to modify data collection from at least one input channel connected to data collection points operationally coupled to the second industrial component in response to the identified noise pattern.

Methods and systems for a monitoring system for data collection in an industrial environment may include a data collector communicatively coupled to a plurality of input channels connected to data collection points operatively coupled to at least one industrial component of an industrial power station; a data acquisition circuit structured to interpret a plurality of detection values from the plurality of input channels; a data analysis circuit structured to utilize an expert system diagnostic tool to identify an off-nominal process state in response to the plurality of detection values; and a response circuit to adjust a process parameter in response to the off-nominal process state.

An apparatus, methods and systems for network-sensitive data collection in an industrial drilling environment are disclosed. The system can include a data storage circuit to store a data collector route and a sensor specification, wherein the data collector route includes a sensor collection routine, a data collector providing a plurality of detection values from the input channels in response to the sensor collection routine and the sensor specification, a network coding circuit to provide a plurality of network coding value, a storage implementation circuit to store a first portion of detection values according to a first network coding value. The network coding circuit also determines a performance indicator related to the first network coding value and provides a second network coding value based on the performance indicator. The storage implementation circuit then stores a second portion of the detection values according to the second network coding value.

Methods and systems for a monitoring system for data collection in an industrial environment including a data collector communicatively coupled to a plurality of input channels connected to data collection points operationally coupled to at least one industrial component in at least one of an industrial boiler system or industrial pipeline system; a data storage structured to store a library of stored noise patterns associated with operation of the at least one industrial component; a data acquisition circuit structured to interpret a plurality of detection values from the collected data; and a data analysis circuit structured to: analyze the collected data, determine a measured noise pattern for the at least one industrial component, and compare the measured noise pattern to the library of stored noise patterns to identify a changed condition of the at least one industrial component.

An apparatus, methods and systems for a monitoring system for data collection in a vehicle are disclosed. The system can include a data acquisition circuit structured to interpret a plurality of detection values, each of the plurality of detection values corresponding to input received from at least one of a plurality of input sensors, each of the plurality of input sensors operatively coupled to at least one of a plurality of components of the vehicle, a data analysis circuit structured to determine a state value, wherein the data analysis circuit includes a pattern recognition circuit structured to determine the state value by analyzing a subset of the plurality of detection values and at least one external detection value using at least one of a neural net or an expert system, and an analysis response circuit structured to adjust a parameter of the vehicle in response to the state value.

According to some embodiments of the present invention there is provided a computerized method for automatic monitoring of control systems. The method may comprise receiving electronic measurement values, measured on one or more conductors of computerized control devices, where the conductors may be a system bus conductor and/or and input-output line of a programmable logic controller. The method may comprise automatically calculating normal data patterns based on an analysis of the electronic measurement values. The method may comprise matching between new electronic measurement values measured on the computerized control devices and the normal data patterns to automatically detect abnormal data patterns. The method may comprise sending automatically an abnormal operation alert in response to the abnormal data patterns.

A plant control supporting apparatus includes a segment selector configured to select, from among a plurality of segments defined in a plant, a segment for which learning for acquiring an optimal value of at least one parameter representing an operation state is executed, a reward function definer configured to define a reward function used for the learning, a parameter extractor configured to extract at least one parameter that is a target for the learning in the selected segment on the basis of input and output information of a device used in the plant and segment information representing a configuration of a device included in the selected segment, and a learner configured to perform the learning for acquiring the optimal value for each segment on the basis of the reward function and the at least one parameter.

This disclosure provides an apparatus and method for deployment assurance checks for monitoring industrial control systems and other systems. A method includes identifying, by a risk manager system, a plurality of connected devices that are vulnerable to cyber-security risks. The method includes determining devices to be monitored from the plurality of connected devices. The method includes evaluating system resource usage, by the risk manager system, on each device to be monitored. The method includes providing recommendations to a user as to whether or not the user should proceed with the monitoring, based on the evaluation.