Automated monitoring and control using augmented streaming decision tree

A method, comprising:

• receiving, via one or more processors, a first operational parameter for one or more automation devices, wherein the one or more automation devices are configured to implement control logic generated based on a decision tree;
• receiving, via the one or more processors, a classification output by the decision tree corresponding to an expected operating condition of the one or more automation devices based on the first operational parameter;
• determining, via the one or more processors, a constraint indicating a threshold range of operational parameters based on the classification output;
• determining, via the one or more processors, the classification output is an anomalous classification output based on the threshold range of the operational parameters;
• generating, via the one or more processors, an updated decision tree based on the constraint by modifying a portion of the decision tree such that the updated decision tree is configured to link the first operational parameter to an alternative classification output;
• generating, via the one or more processors, updated control logic for the one or more automation devices based on the updated decision tree;
• and
• sending, via the one or more processors, a control signal based on the updated control logic to the one or more automation devices, wherein the one or more automation devices adjust one or more operations based on the control signal such that the operational parameters are within the threshold range.

A non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause a processor to perform operations comprising:

• receiving process input data associated with one or more automation devices over a period of time;
• receiving a plurality of operational parameters implemented by the one or more automation devices in response to the process input data;
• generating a decision tree representative of the plurality of operational parameters and corresponding process input data;
• generating control logic for the one or more automation devices based on the decision tree, wherein the control logic is configured to cause the one or more automation devices to implement the plurality of operational parameters based on the process input data;
• sending the control logic to the one or more automation devices;
• receiving process data associated with the one or more automation devices implementing the control logic;
• providing the process data as input to the decision tree;
• receiving a classification output from the decision tree corresponding to an expected operating condition of the one or more automation devices based on the process data;
• determining a constraint indicating a threshold range of the process data based on the classification output;
• determining the classification output is an anomalous classification output based on the threshold range of the process data;
• generating an updated decision tree by modifying a portion of the decision tree associated with the anomalous classification output based on the constraint, wherein the decision tree links the process data to an alternative operating condition instead of the anomalous classification output;
• generating updated control logic for the one or more automation devices based on the updated decision tree;
• and
• sending a control signal based on the updated control logic to the one or more automation devices, wherein the one or more automation devices adjust one or more operations based on the control signal such that the operational parameters are within the threshold range.