Edge Device for Executing a Lightweight Pattern-Aware generative Adversarial Network

A mobile handheld computing device that is configured to execute machine learning procedures with a sparse dataset, the mobile handheld computing device comprising:

• at least a receiver;
• one or more processing devices;
• one or more memories in communication with the one or more processing devices, wherein the one or more memories contain one or more executable instructions that cause the one or more processing devices to perform operations that include at least:
• receiving the sparse data via the receiver from one or more mobile devices;
• creating augmented data with the sparse data and generated synthetic data;
• and
• training one or more machine learning models with the augmented data, wherein the augmented data has a greater variety of features compared with the sparse data.

A resource-constrained edge device that is configured to execute machine learning procedures with a sparse dataset, the resource-constrained edge device comprising:

• one or more sensor interfaces;
• one or more microcontrollers (MCUs);
• one or more memories in communication with the one or more microcontrollers, wherein the one or more memories contain one or more executable instructions that cause the one or more microcontrollers to perform operations that include at least:
• receiving one or more batches of real-time sensor data via the one or more sensor interfaces, the one or more batches defining the sparse dataset;
• creating one or more batches of augmented data with the one or more batches of real-time sensor data and one or more batches of generated synthetic data;
• and
• training at least a discriminator at least in part with the one or more batches of augmented data.