dailyai.report

A new pipeline uses a categorical variational autoencoder to compress raw Wi-Fi signals into discrete representations. This method extracts Linear Temporal Logic rules to make human activity recognition symbolically controllable. It bridges the gap between opaque deep learning and rigid symbolic logic. Practitioners gain a transparent way to audit how signals trigger specific activity labels.