METHODS AND SYSTEMS FOR DATA COLLECTION OPTIMIZATION IN AN INDUSTRIAL INTERNET OF THINGS ENVIRONMENT
Improved capabilities are described for a data collection system in an industrial environment comprising a data collector communicatively coupled to a plurality of input channels; a data storage structured to store a plurality of collector routes and collected data that correspond to the plurality of input channels, wherein the plurality of collector routes each comprise a different data collection routine; 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; a data analysis circuit structured to analyze the collected data from the plurality of input channels; and a cognitive input selection facility for optimization of an input selection configuration for a collector route of the data collector, wherein the input selection configuration is based on a learning feedback from a learning feedback facility.
1 . A data collection system in an industrial environment, the system comprising:
a data collector communicatively coupled to a plurality of input channels;
a data storage structured to store a plurality of collector routes and collected data that correspond to the plurality of input channels, wherein the plurality of collector routes each comprise a different data collection routine;
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;
a data analysis circuit structured to analyze the collected data from the plurality of input channels; and
a cognitive input selection facility for optimization of an input selection configuration for a collector route of the data collector, wherein the input selection configuration is based on a learning feedback from a learning feedback facility.
2 . The system of claim 1 , wherein the collection system is an automatically adapting, multi-sensor data collection system, wherein data collection routines are selected based on optimizing sensed parameters from the collected data over time.
3 . The system of claim 1 , wherein the learning feedback facility is a remote learning feedback facility associated with a data collection marketplace, and the learning feedback is derived from user feedback metrics.
4 . The system of claim 3 , wherein the user feedback metrics are based on market usage of sensed collected data over time.
5 . The system of claim 1 , wherein the cognitive input selection facility derives input selection from a self-organizing data marketplace for industrial Internet-of-things data that comprises at least in part data collected by the data collection system.
6 . The system of claim 5 , wherein the self-organizing data marketplace utilizes a self-organizing data pool comprising data collected by the data collection system.
7 . The system of claim 1 , wherein the optimization of the input selection configuration modifies a hierarchical template for data collection.
8 . The system of claim 1 , wherein the cognitive input selection facility anticipates state information from machine learning and pattern recognition to optimize the input selection configuration.
9 . The system of claim 1 , wherein the data collector is one of a plurality of self-organized swarm of data collectors, wherein the plurality of self-organized swarm of data collectors organizes among themselves to optimize data collection based at least in part on the optimized input selection configuration.
10 . The system of claim 1 , wherein the optimization of the input selection configuration adjusts a sensor capability for a sensor connected to one of the plurality of input channels.
11 . The system of claim 1 , wherein the optimization of the input selection configuration adjusts a use of at least one detection value from the plurality of detection values for use by the cognitive input selection facility for optimization of the input selection configuration.
12 . The system of claim 1 , wherein the optimization of the input selection configuration for the collector route changes a selected subset of the plurality of input channels for data collection from a first set of input channels to a second set of input channels to optimize data collection from a machine based on a determined life cycle of the machine, duty cycle of the machine, or operating stage of the machine.
13 . The system of claim 1 , wherein the learning feedback facility is an expert system utilizing a neural network to identify optimizations of the input selection configuration.
14 . The system of claim 1 , wherein the cognitive input selection facility stores a distributed ledger for tracking of transactions associated with the collected data.
15 . A computer-implemented method for data collection in an industrial environment, the method comprising:
a data collector communicatively coupled to a plurality of input channels;
a data storage structured to store a plurality of collector routes and collected data that correspond to the plurality of input channels, wherein the plurality of collector routes each comprise a different data collection routine;
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;
a data analysis circuit structured to analyze the collected data from the plurality of input channels; and
a cognitive input selection facility for optimization of an input selection configuration for a collector route of the data collector, wherein the input selection configuration is based on a learning feedback from a learning feedback facility.
16 . The method of claim 15 , wherein the collection system is an automatically adapting, multi-sensor data collection system, wherein data collection routines are selected based on optimizing sensed parameters from the collected data over time.
17 . The method of claim 15 , wherein the learning feedback facility is a remote learning feedback facility associated with a data collection marketplace, and the learning feedback is derived from user feedback metrics.
18 . A monitoring apparatus for data collection in an industrial environment, the system comprising:
a data collector communicatively coupled to a plurality of input channels;
a data storage structured to store a plurality of collector routes and collected data that correspond to the plurality of input channels, wherein the plurality of collector routes each comprise a different data collection routine;
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;
a data analysis circuit structured to analyze the collected data from the plurality of input channels; and
a cognitive input selection facility for optimization of an input selection configuration for a collector route of the data collector, wherein the input selection configuration is based on a learning feedback from a learning feedback facility.
19 . The apparatus of claim 18 , wherein the collection system is an automatically adapting, multi-sensor data collection system, wherein data collection routines are selected based on optimizing sensed parameters from the collected data over time.
20 . The apparatus of claim 18 , wherein the learning feedback facility is a remote learning feedback facility associated with a data collection marketplace, and the learning feedback is derived from user feedback metrics.