Modulating a quality of media content

A system, comprising:

• a memory;
• and
• at least one processor, communicatively coupled to the memory, configured to execute instructions, the instructions causing the at least one processor to:
• collect usage data information from one or more locations, the usage data information comprising an indication of how frequent a first media playback device, of a plurality of media playback devices that are located at the one or more locations, that is associated with relatively high consumption of data than compared to a second media device of the plurality of media playback devices is utilized by one or more users;
• determine a data cap for the one or more locations;
• train a machine learning model using the usage data information and the data cap to associate the usage data information with at least one of the one or more users based on how the at least one of the one or more users handles a remote control device to control the first media playback device;
• predict, using the machine learning model, whether at least one of the one or more locations is going to exceed its associated data cap based on the usage data information associated with the at least one of the one or more users;
• and
• determine to modulate a quality of media content transmitted to the at least one of the one or more locations based on the prediction.

A non-transitory, tangible computer-readable medium having instructions stored thereon that, when executed by at least one computing device, cause the at least one computing device to perform operations comprising:

• collecting usage data information from one or more locations, the usage data information comprising an indication of how frequent a first media playback device, of a plurality of media playback devices that are located at the one or more locations, that is associated with relatively high consumption of data than compared to a second media device of the plurality of media playback devices is utilized by one or more users;
• determining a data cap for the one or more locations;
• training a machine learning model using the usage data information and the data cap to associate the usage data information with at least one of the one or more users based on how the at least one of the one or more users handles a remote control device to control the first media playback device;
• predicting, using the machine learning model, whether at least one of the one or more locations is going to exceed its associated data cap based on the usage data information associated with the at least one of the one or more users;
• and
• determining to modulate a quality of media content transmitted to the at least one of the one or more locations based on the prediction.