Machine vision-based detecting and processing of table game events

A computer-based method of gameplay tracking at a table game in a gaming environment, the method comprising:

• provisioning a machine learning model on each of an edge server and a cloud server:
• receiving, by the edge server, a first image feed from a first camera system, wherein the first camera system is positioned proximate to a table game in a gaming environment;
• detecting, by the machine learning model executing on the edge server, an object in the first image feed;
• providing training data to the machine learning model on the cloud server to update the machine learning model on the cloud server;
• and
• subsequent to updating the machine learning model on the cloud server, providing the updates to the machine learning model on the edge server.

A gameplay tracking system, comprising:

• a camera system positioned proximate to a table game in a gaming environment, wherein the camera system is configured to generate an image feed;
• an edge server positioned within the gaming environment and in communication with the camera system, wherein the edge server is configured to process the image feed using a machine learning model stored on the edge server;
• and
• a cloud server positioned external to the gaming environment, wherein the cloud server comprises a copy of the machine learning model, wherein the machine learning model of the cloud server is trained to increase accuracy and updated, wherein the updated machine learning model is provided to the edge server.