METHODS AND SYSTEMS FOR DATA COLLECTION OPTIMIZATION IN AN INDUSTRIAL INTERNET OF THINGS ENVIRONMENT

Abstract

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.

Claims

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.