Systems and methods for automatically determining a spatial impact zone of an event occurring in real-time

A system, comprising:

• one or more hardware computer processors configured with computer-executable instructions that, when executed, cause the one or more hardware computer processors to:
• gather feature data from electronic updates of an event;
• feed the feature data to a machine learning model;
• cause the machine learning model to estimate in real-time a current spatial impact zone of the event based on the feature data;
• cause the machine learning model to output in real-time data describing the estimated current spatial impact zone of the event;
• receive data describing an actual spatial impact zone of the event as the event is occurring;
• save the data describing the actual spatial impact zone with the feature data;
• and
• retrain the machine learning model on a batch basis with the data describing the actual spatial impact zone and the feature data.

A non-transitory computer-readable storage medium with an executable program stored thereon, wherein the program instructs one or more processors to perform the following steps:

• gather feature data from electronic updates of an event;
• feed the feature data to a machine learning model;
• cause the machine learning model to estimate in real-time the current spatial impact zone of the event based on the feature data;
• cause the machine learning model to output in real-time data describing the estimated current spatial impact zone of the event;
• receive data describing an actual spatial impact zone of the event as the event is occurring;
• save the data describing the actual spatial impact zone with the feature data;
• and
• retrain the machine learning model on a batch basis with the data describing the actual spatial impact zone and the feature data.