Data-driven and distributed governance of building facilities management using decentralized autonomous organization, digital twin, and large language models

· Source: cs.MA updates on arXiv.org · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Blockchain & Distributed Ledger Technology, Internet of Things (IoT) & Connected Devices · Depth: Expert, short

Summary

A novel AI- and data-driven distributed governance framework has been introduced for smart building management, addressing limitations of traditional centralized approaches such as cyber vulnerabilities and limited stakeholder inclusion. This framework integrates decentralized autonomous organizations (DAOs) for transparent collective decision-making, digital twins and IoT for data-driven management, large language models (LLMs) for enhanced decision support via virtual assistants, and blockchain technology for secure building automation. A full-stack decentralized application was developed to enable user interaction with these components. The system underwent evaluation for cost efficiency, scalability, data security, and usability using the System Usability Scale (SUS), with expert interviews also conducted to assess practical benefits and implementation challenges. The paper, submitted on April 16, 2026, spans 33 pages and includes 20 figures and 4 tables.

Key takeaway

For AI Architects designing smart building solutions, this framework offers a robust alternative to centralized systems. You should consider integrating DAOs, digital twins, LLMs, and blockchain to enhance security, transparency, and stakeholder participation in facilities management. This approach can mitigate cyber risks and improve operational efficiency by distributing governance and leveraging advanced AI for decision support.

Key insights

Integrating DAOs, digital twins, LLMs, and blockchain enables secure, transparent, and distributed smart building governance.

Principles

Method

The proposed method involves developing a full-stack decentralized application that integrates DAOs for governance, IoT and digital twins for data management, LLMs for virtual assistants, and blockchain for secure automation.

In practice

Topics

Best for: AI Scientist, Research Scientist, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by cs.MA updates on arXiv.org.