Machine learning and augmented-reality for proactive thermal amelioration

A system, comprising:

• one or more computer processors;
• and
• a memory containing a program which when executed by the one or more computer processors performs an operation, the operation comprising:
• collecting data from one or more sensors in a physical environment;
• generating a digital model depicting physical machinery in the physical environment, based on the data collected from the one or more sensors;
• simulating one or more operations of the physical machinery, based on the digital model and the data collected from the one or more sensors;
• predicting thermal conditions of the physical environment, using a machine learning (ML) model, based on the simulating of the operations and the data collected from the one or more sensors;
• generating a recommendation comprising one or more proactive actions to mitigate potential thermal issues, based on the predicted thermal conditions;
• and
• projecting the predicted thermal conditions, the potential thermal issues, and the one or more proactive actions into the digital model via an augmented-reality (AR) display.

A computer program product comprising one or more computer-readable storage media collectively containing computer-readable program code that, when executed by operation of one or more computer processors, performs an operation comprising:

• collecting data from one or more sensors in a physical environment;
• generating a digital model depicting physical machinery in the physical environment, based on the data collected from the one or more sensors;
• simulating one or more operations of the physical machinery, based on the digital model and the data collected from the one or more sensors;
• predicting thermal conditions of the physical environment, using a machine learning (ML) model, based on the simulating of the operations and the data collected from the one or more sensors;
• generating a recommendation comprising one or more proactive actions to mitigate potential thermal issues, based on the predicted thermal conditions;
• and
• projecting the predicted thermal conditions, the potential thermal issues, and the one or more proactive actions into the digital model via an augmented-reality (AR) display.