// AUTO-GENERATED by scripts/extract/generate_all.py — DO NOT EDIT BY HAND
import { ResearchProject } from "./types";

export const researchProjects: ResearchProject[] = [
  {
    "slug": "iot-standards",
    "title": "AIoT & AI-RAN",
    "abstract": "AIoT & AI-RAN investigates agent-based IoT architectures in which autonomous AI agents are distributed across sensor, edge, and radio access layers. The project studies agent-to-agent coordination over high-performance transport (gRPC/QUIC) bridged with constrained edge protocols (MQTT/CoAP), targeting AI-RAN designs for distributed autonomous control.",
    "keywords": [
      "AIoT",
      "agent-based IoT",
      "AI-RAN",
      "constrained edge protocols",
      "distributed autonomous control"
    ],
    "standardsTrack": "National Research Foundation of Korea (NRF)",
    "standardsOrg": "NRF",
    "period": "2026 ~ Present",
    "deliverables": []
  },
  {
    "slug": "ccis",
    "title": "MCM",
    "abstract": "Multilateral and Collaborative Metaverse (MCM) refers to metaverse systems in which two or more participants simultaneously interact within a shared virtual space for a common collaborative purpose. Unlike single-user or purely competitive environments, an MCM service is defined by coordinated participation: its intended outcome cannot be achieved by a single user acting alone. The project defines general requirements, service classification, and a gap analysis against existing standards.",
    "keywords": [
      "MCM",
      "metaverse",
      "shared virtual space",
      "coordinated participation",
      "service classification"
    ],
    "standardsTrack": "IEC/TC 100/WG 12 supported by KEIT",
    "standardsOrg": "IEC TC100",
    "period": "2026 ~ Present",
    "deliverables": []
  },
  {
    "slug": "vlc-iot",
    "title": "MVQM",
    "abstract": "Management of Visual Quality in Metaverse Systems (MVQM) is a conceptual and functional approach for managing visual quality by dynamically adapting visual data delivery in response to user context, device capability, and network conditions. It emphasizes user-centric, context-aware quality management over static system-centric optimization, covering hybrid visual assets, level of detail, and area of interest adaptation.",
    "keywords": [
      "MVQM",
      "visual quality",
      "hybrid visual assets",
      "level of detail",
      "area of interest"
    ],
    "standardsTrack": "IEC/TC 100/WG 12 supported by KEIT",
    "standardsOrg": "IEC TC100",
    "period": "2026 ~ Present",
    "deliverables": []
  }
];
