{
  "id": 5758,
  "url": "https://arxiv.org/abs/2605.16298v1",
  "title": "Data-driven and distributed governance of building facilities management using decentralized autonomous organization, digital twin, and large language models",
  "summary": "While traditional AI and data-driven facilities management approaches have improved building operational efficiency, they remain constrained by centralized organizational structures that are vulnerable to cyber attacks, limited contextual understanding, and decision-making processes that exclude key stakeholders from governance. This paper introduces a novel AI- and data-driven distributed governance framework for smart building management that integrates decentralized autonomous organizations (",
  "authors": "Reachsak Ly, Alireza Shojaei, Xinghua Gao, Philip Agee, Abiola Akanmu",
  "category": "research",
  "topics": "regulation,military-security",
  "orgs": null,
  "regions": null,
  "published_at": "2026-04-16T20:10:35.000Z",
  "fetched_at": "2026-07-14T16:31:57.536Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/5758",
  "original_url": "https://arxiv.org/abs/2605.16298v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}