Automated model building and updating environment

A method of automating building and maintaining of models of a physical process, the method comprising:

• receiving training data associated with a plurality of different data sources, each data source of the plurality of data sources being associated with a physical process;
• for at least one single data source of the plurality of different data sources, building a single source data model based at least in part on the training data associated with the single data source;
• automatically performing a data cleansing process on operational data based on the single source data model, the operational data corresponding to data collected from the single data source;
• and
• automatically updating the single source data model.

A system for building and maintaining of models of a physical process, the system comprising:

• a communication interface configured to receive data from a plurality of different data sources;
• a processor communicatively connected to the communication interface;
• a memory communicatively connected to the processor and communication interface, the memory storing instructions comprising an automated model building and maintenance application which, when executed by the processor, cause the system to:
• automatically perform a clustering process on training data received from the plurality of data sources to form one or more clusters, the plurality of data sources further including at least one single data source not included within the one or more clusters;
• and
• for each of the one or more clusters:
• build a data model based at least in part on the training data associated with the data sources included in the cluster;
• automatically perform a data cleansing process on operational data based on the data model, the operational data corresponding to the data sources included in the cluster;
• and
• automatically update the data model based at least in part on updated training data, the updated training data corresponding to recent data received as operational data.

A system for automatically monitoring sensors measuring parameters of a physical process, the method comprising:

• a communication interface configured to receive data from a plurality of different data sources associated with a physical process, the plurality of different data sources including one or more sensors associated with the physical process;
• a processor communicatively connected to the communication interface;
• a memory communicatively connected to the processor and communication interface, the memory storing instructions comprising an automated model building and maintenance application which, when executed by the processor, cause the system to:
• automatically perform a clustering process on training data received from the plurality of data sources to form one or more clusters, the plurality of data sources further including at least one single data source not included within the one or more clusters;
• and
• for each of the one or more clusters:
• build a data model based at least in part on the training data associated with the data sources included in the cluster;
• automatically perform a data cleansing process on operational data based on the data model, the operational data corresponding to the data sources included in the cluster;
• and
• automatically update the data model based at least in part on updated training data, the updated training data corresponding to recent data received as operational data;
• and;
• for each single data source:
• build a single source data model based at least in part on the training data associated with the single data source;
• automatically perform a data cleansing process on operational tag data based on the data model, the tag data corresponding to operational data collected from the single data source;
• and
• automatically update the single source data model.