{
  "annotation_id": "bcda2388-2168-4917-ade7-8835bf3a7b61",
  "date_created": "2026-02-17T05:53:08.671000Z",
  "date_modified": "2026-02-17T05:53:08.671000Z",
  "file_hash": "f363a57bcd8f3f7567cfa3105137b14c9fc5cd0b69eb0b28252806a0fcf59ecb",
  "private": false,
  "record": {
    "abstract": "This paper presents an AI glasses system that integrates real-time voice processing, artificial intelligence(AI) agents, and cross-network streaming capabilities. The system employs dual-agent architecture where Agent 01 handles Automatic Speech Recognition (ASR) and Agent 02 manages AI processing through local Large Language Models (LLMs), Model Context Protocol (MCP) tools, and Retrieval-Augmented Generation (RAG). The system supports real-time RTSP streaming for voice and video data transmission, eye tracking data collection, and remote task execution through RabbitMQ messaging. Implementation demonstrates successful voice command processing with multilingual support and cross-platform task execution capabilities.",
    "arxiv_id": "2601.06235",
    "authors": [
      "Sheng-Kai Chen",
      "Jyh-Horng Wu",
      "Ching-Yao Lin",
      "Yen-Ting Lin"
    ],
    "categories": [
      "cs.SD",
      "cs.AI",
      "cs.HC"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "title": "An Intelligent AI glasses System with Multi-Agent Architecture for Real-Time Voice Processing and Task Execution",
    "url": "https://arxiv.org/abs/2601.06235",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "8c3c25cd-9bc4-43b1-a377-e0028a273d1f",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}