Detecting Communication Network Insights Of Alerts

One or more computer-readable non-transitory storage media embodying software that is operable when executed to:

• identify one or more geographic areas covered by a communication network;
• determine, for each identified geographic area, a network performance metric for the identified geographic area based at least on a difference between:
• (1) a first average network speed of the communication network in the identified geographic area during one or more first prior time periods in which the communication network is busy, and
• (2) a second average network speed of the communication network in the identified geographic area during one or more second prior time periods in which the communication network is not busy;
• compare the respective performance metrics of the one or more geographic areas to a threshold network performance metric, wherein the threshold network performance metric is determined by a congestion-analysis machine learning (ML) model;
• and
• identify one or more network traffic congestions in one or more of the identified geographic areas having a determined network performance metric below the threshold network performance metric.

A system comprising:

• one or more non-transitory computer-readable storage media embodying instructions;
• and
• one or more processors coupled to the storage media and operable to execute the instructions to:
• identify one or more geographic areas covered by a communication network;
• determine, for each identified geographic area, a network performance metric for the identified geographic area based at least on a difference between:
• (1) a first average network speed of the communication network in the identified geographic area during one or more first prior time periods in which the communication network is busy, and
• (2) a second average network speed of the communication network in the identified geographic area during one or more second prior time periods in which the communication network is not busy;
• compare the respective performance metrics of the one or more geographic areas to a threshold network performance metric, wherein the threshold network performance metric is determined by a congestion-analysis machine learning (ML) model;
• and
• identify one or more network traffic congestions in one or more of the identified geographic areas having a determined network performance metric below the threshold network performance metric.