Study on a Distributed Cognitive Support Architecture for Multimodal AI Chat Systems Using Resonance Interfaces and Dynamic Mesh Networks

This study proposes a distributed cognitive support architecture for multimodal AI chat systems using resonance-based interfaces and dynamic mesh networks. Instead of invasive neural interfaces, the system non-invasively detects user cognitive states through environmental and wearable nodes, forming a distributed network that assists decision making. Probabilistic multi-model simulations, dynamic encryption, secret sharing, and a digital forgetting engine enable secure and fluid data processing without permanent storage. Parallel decision models and shadow processing support resilient decision making under uncertainty. The architecture aims to reduce cognitive load, enhance privacy, and optimize computational resource allocation while enabling advanced multimodal AI interaction.