Selecting periods of time for payload transmission based on detected attributes

A method comprising:

• obtaining, at a first time, a first set of current attributes corresponding to a device;
• training a machine learning model using training datasets to predict criticality levels for operations being executed by the device, each training dataset comprising a particular set of current attributes and a corresponding criticality level;
• based on the first set of current attributes, determining that the device is currently executing an operation that meets one or more criticality criteria, wherein determining that the device is currently executing the operation that meets one or more criticality criteria comprises:
• applying the machine learning model to first set of current attributes to determine a criticality level of the operation being executed by the device;
• and
• comparing the criticality level to the one or more criticality criteria;
• and
• responsive to determining that the device is currently executing the operation that meets the one or more criticality criteria, causing the device to refrain from transmitting a particular dataset generated by the device,
• wherein the method is performed by at least one device including a hardware processor.

A system comprising:

• at least one device including a hardware processor;
• and
• the system being configured to perform operations comprising:
• obtaining, at a first time, a first set of current attributes corresponding to a device;
• training a machine learning model using training datasets to predict criticality levels for operations being executed by the device, each training dataset comprising a particular set of current attributes and a corresponding criticality level;
• based on the first set of current attributes, determining that the device is currently executing an operation for a patient that meets one or more criticality criteria, wherein determining that the device is currently executing the operation that meets one or more criticality criteria comprises:
• applying the machine learning model to first set of current attributes to determine a criticality level of the operation being executed by the device, and
• comparing the criticality level to the one or more criticality criteria;
• and
• responsive to determining that the device is currently executing the operation that meets the one or more criticality criteria, causing the device to refrain from transmitting a particular dataset generated by the device.