A system for dynamically load-balancing at least one redistribution element across a group of computing resources that facilitates at least an aspect of an Industrial Execution Process in an M:N working configuration is illustrated. The system is configured to: access from a central or distributed data store, a configuration component operational data and capabilities or characteristics associated with the M:N working configuration; identify a load-balancing opportunity to trigger redistribution of a redistribution element to a redistribution target selected from a redistribution target pool defined by remaining computing resource components associated with the M:N computing resource working configuration; select at least one redistribution target for redeployment; redeploy the at least one redistribution element to the redistribution target; determine redeployment to the at least one selected redistribution target to be a viable redeployment; and execute the Industrial Execution Process utilizing the at least one redistribution element at the selected redistribution target.

According to some embodiments, system and methods are provided including receiving, via a communication interface of an event detection and classification module comprising a processor, data from one or more sensors in a system; determining an event occurred based on the received data; applying a coherency similarity process to the received data via a classification module; determining whether the event is an actual event or a mal-doer event based on an output of the classification module; transmitting the determination of the event as the actual or the mal-doer event; and modifying operation of the system based on the transmitted output. Numerous other aspects are provided.

In one embodiment, a method for reducing corrosion in an information handling system includes receiving a system setting indicating one or more operation modes; identifying an ambient temperature of the information handling system, the ambient temperature captured by one or more sensors of the information handling system; identifying a humidity level of the information handling system, the humidity level captured by the one or more sensors; identifying a corrosion risk value based on the ambient temperature and the humidity level; determining that the corrosion risk value is greater than a threshold corrosion risk value; and in response to determining that the corrosion risk value is greater than the threshold corrosion risk value: modifying one or more device threshold settings based on the system setting and the corrosion risk value, wherein modifying the one or more device threshold settings causes the ambient temperature to increase and the humidity level to decrease.

An apparatus, methods and systems for data collection in an industrial environment are disclosed. A monitoring system can include a data collector coupled to a plurality of sensors to collect data, a data storage structured to store a plurality of data collection management plans, 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 and select one of the plurality of data collection management plans, wherein the selected one of the plurality of data collection management plans is selected is at least in part based on a data analysis of received data from the plurality of sensors.

A platform for facilitating development of intelligence in an Industrial Internet of Things (IIoT) system generally includes a plurality of distinct data-handling layers comprising an industrial monitoring systems layer that collects data from or about a plurality of industrial entities in the IIoT system; an industrial entity-oriented data storage systems layer that stores the data collected by the industrial monitoring systems layer; an adaptive intelligent systems layer that provisions available computing resources within the platform; and an industrial management application platform layer that manages the platform in a common application environment.

A system for detecting an anomaly in a video of a factory automation scene is disclosed. The system may accept the video; accept a set of training feature vectors derived from spatio-temporal regions of a training video, where a spatio-temporal region is associated with one or multiple training feature vectors; partition the video into multiple sequences of video volumes; produce a sequence of binary difference images for each of the video volumes; count occurrences of each of predetermined patterns of pixels in each binary difference image for each of the video volumes to produce an input feature vector including an input motion feature vector defining a temporal variation of counts of the predetermined patterns for each of the video volumes; produce a set of distances based on the produced input feature vectors and the set of training feature vectors; and detect the anomaly based on the produced set of distances.

Methods and systems for predicting failure in a cyber-physical system include determining a prediction index based on a comparison of input time series, from respective sensors in a cyber-physical system, to failure precursors. A failure precursor is detected in the input time series, responsive to a comparison of the prediction index to a threshold. A subset of the sensors associated with the failure precursor is determined, based on a gradient of the prediction index. A corrective action is performed responsive to the determined subset of sensors.

Systems for self-organizing data collection and storage in a manufacturing environment are disclosed. A system may include a data collector for handling a plurality of sensor inputs from sensors in the manufacturing system, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of at least one target system. The system may also include a self-organizing system for self-organizing a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs. The self-organizing system may organize a swarm of mobile data collectors to collect data from a plurality of target systems.

Methods may comprise: identifying a fault indicator associated with a physical system; collecting first data related to a state of the physical system; applying a surrogate model to the first data to produce a plurality of potential fault modes; applying an optimization algorithm to the plurality of potential fault modes using a similarity metric to produce an input and a plurality of outputs, wherein each of the plurality of outputs corresponds to one of the plurality of potential fault modes, wherein the input provides differentiation between each of the plurality of outputs; applying the input to the physical system; collecting second data from physical system in response to applying the input; identifying a true mode of the physical system based on a comparison of the second data and the plurality of outputs; and diagnosing a fault of the physical system based on the true mode.

A hot water supply device including an inlet pipe, an outlet pipe, a burner unit, a heat exchanger, an exhaust aperture, a first temperature sensor detecting a measured exhaust temperature of the exhaust gas, a second temperature sensor detecting a water temperature of water entering the inlet pipe, and a processor. The processor is configured to obtain an error between the measured exhaust temperature and an estimated exhaust temperature, and detects that scale clogging has occurred inside the heat exchange tubing based on an index which is generated using the error between the measured exhaust temperature and the estimated exhaust temperature. The estimated exhaust temperature is a first predetermined value that is determined using a numerical equation which has at least the water temperature of water entering the inlet pipe and a scale number of the hot water supply device as variables of the numerical equation.