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 sensor management system includes a historical data repository, a building management system (BMS) controller, and a sensor diagnostics system. The historical data repository may store historical data by a plurality of sensors. The BMS controller may control one or more components of a building subsystem based on data provided by one or more sensors. The sensor diagnostic system may receive, from a sensor, sensor data. The sensor diagnostic system may determine at least one fault in the sensor data. The sensor diagnostic system may select, from the historical data repository, substitute sensor data for the sensor based on a comparison of one or more attributes of the sensor data and one or more attributes of the historical data in the data repository. The sensor diagnostic system may provide, in replacement of the sensor data from the sensor, the supplemental sensor data to the BMS controller.

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.

An apparatus, methods and systems for data collection related to an oil and gas process and disclosed. A system may include a multi-sensor acquisition component including a plurality of inputs and a plurality of outputs, a sensor data storage profile circuit structured to determine a data storage profile including a data storage plan for the plurality of inputs, a sensor communication circuit structured to interpret a plurality of inputs, a sensor data storage implementation circuit structured to store at least a portion of the inputs in response to the data storage profile, a data analysis circuit structured to analyze the plurality of inputs and determine a data quality parameter, and a data response circuit structured to adjust at least one of the data storage profile and the data collection routine in response to the data quality parameter.

A platform for facilitating development of intelligence in an Industrial Internet of Things (IIoT) system generally includes a plurality of distinct data-handling layers having an industrial monitoring systems layer that collects data from or about a plurality of industrial entities in an industrial environment; an industrial entity-oriented data storage systems layer that stores the data collected by the industrial monitoring systems layer; and an adaptive intelligent systems layer that facilitates the coordinated development and deployment of intelligent systems in the IIoT system; wherein the adaptive intelligent systems layer includes an adaptive edge compute management system that adaptively manages edge computation, storage, and processing in the IIoT system.

A microcontroller system which employs an intermediate approach in hybrid FRAM-SRAM that involves memory mapping of program sections to retain the reliability benefits provided by FRAM while performing almost as efficiently as an SRAM-based system. They system utilizes an energy-aware memory mapping method which maps different program sections to the hybrid FRAM-SRAM MCU such that energy consumption is minimized without sacrificing reliability. The method comprises a memory initialization map, which performs a one-time characterization to find the optimal memory map for the functions that constitute a program. The method further comprises an energy alignment, a hardware/software method that aligns the system's powered-on time intervals to function execution boundaries, which results in further improvements in energy efficiency and performance.

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.

Methods and systems for a data marketplace in a conveyor environment includes a self-organizing data marketplace. The self-organizing data marketplace includes at least one data collector and at least one corresponding conveyor in an industrial environment, wherein the at least one data collector is structured to collect detection values from at least one sensor of a power roller of the at least one corresponding conveyor; a data storage structured to store a data pool comprising at least a portion of the detection values; a data marketplace structured to self-organize the data pool; and a transaction system structured to interpret a user data request, and to selectively provide a portion of the self-organized data pool to a user in response to the user data request.

An information processing system includes: a setting unit to set a normal range showing a range of normal values of monitoring target data of time series signals by defining an upper limit and a lower limit; a determination unit to determine whether the monitoring target data is out of the normal range or not and to feed the determined time which is output in case of deviation and which is judged to be the time for the monitoring target data to turn to be out of the normal range; and a detection unit to determine the start time that is before the determined time entering from the determination unit and which is the time for the monitoring target data to start to show an anomaly on the basis of the degree of deviation showing a deviation of the monitoring target data from a mean of multiple learning data which consist of normal value signals from among already-acquired monitoring target data. This enables the system to more accurately determine the time for the signal to start to show an anomaly.

A method includes identifying a statistical performance of a monitoring rule associated with an asset monitoring system. The monitoring rule includes logic configured to identify one or more faults with at least one asset, and the statistical performance includes an effectiveness of the monitoring rule in identifying the one or more faults. The method also includes identifying an economic performance of the monitoring rule, where the economic performance is based on costs associated with different outcomes of the monitoring rule. The method further includes updating or replacing the monitoring rule based on the economic performance.