Supporting Human-to-Machine Applications in Next-Gen Optical Access Networks through Explainable AI

We propose a novel SHAP-enhanced haptic feedback prediction framework to extract key feature knowledge and advance predicted transmissions of human-to-machine applications. Through experiments and simulations, the framework shows significantly improved training and inference times and propagation delay, meeting latency requirements.