Dynamic resource allocation method for sensor-based neural networks using shared confidence intervals

A computer system for resource allocation for sensor-based neural networks, the computer system comprising:

• one or more computer-readable non-transitory storage media configured to store computer program code;
• and
• one or more computer processors configured to access said computer program code and operate as instructed by said computer program code, said computer program code including:
• identifying code configured to cause the one or more computer processors to identify nodes associated with an edge computing environment;
• receiving code configured to cause the one or more computer processors to receive data corresponding to a classification dataset from the identified nodes, wherein the dataset includes a reference classification and confidence value data;
• selecting code configured to cause the one or more computer processors to select a node from among the identified nodes based on selected node having a greatest confidence interval associated with the reference classification within the confidence value data;
• and
• assigning code configured to cause the one or more computer processors to assign the selected node to process the classification dataset.

A non-transitory computer readable medium having stored thereon a computer program for resource allocation for sensor-based neural networks, the computer program configured to cause one or more computer processors to:

• identify nodes associated with an edge computing environment;
• receive data corresponding to a classification dataset from the identified nodes, wherein the dataset includes a reference classification and confidence value data;
• select a node from among the identified nodes based on selected node having a greatest confidence interval associated with the reference classification within the confidence value data;
• and
• assign the selected node to process the classification dataset.