哪些建筑已具备 AI 就绪条件？基于测量的 AI 问答与控制评估框架
Which Buildings Are Artificial Intelligence-Ready? A Measurement-Based Assessment Framework for AI Question Answering and Actuation
AI 导读
一项研究提出量化建筑对 Agentic AI 就绪程度的评估框架：以建筑知识图谱设定可问答与可控制两个上限，再用参考 AI 智能体的准确率衡量实现程度。在模拟办公楼中，智能体达到 0.64 可问答上限中的 0.62，说明主要瓶颈是数据缺失而非 AI 本身；对 37 个公开真实建筑图谱的中位可问答上限仅 0.16，其中 45 个案例里有 15 个因传感器未关联而拉低上限。
正文 · 原文
Abstract:Agentic artificial intelligence (AI) systems are becoming the interface to buildings, answering questions and controlling operations, but a building's readiness for them has not been systematically assessed. This study proposes a framework to quantify it. First, a building's knowledge graph sets two ceilings. The answerable-readiness ceiling is the share of operational questions its data could answer, and the actuation-readiness ceiling is the share of control actions it exposes. Second, a reference AI agent's accuracy on a fixed set of these questions shows how much of the ceilings is realized. On a simulated office, the agent realizes 0.62 of a 0.64 answerable ceiling, so missing data, not the AI, limit readiness, except in naming a fault's cause. Across 37 public real-building graphs, the median answerable ceiling is 0.16, and in 15 of 45, unlinked sensors lower it. The framework turns "is this building AI-ready?" into an auditable, ranked retrofit question.
| Comments: | 45 pages, 11 figures, 23 tables. Code, results and data supplement: this https URL. Re-set in the HUBS Lab paper layout (HUBS Lab Paper No. 2026-008); content unchanged |
| Subjects: | Artificial Intelligence (cs.AI) |
| ACM classes: | I.2.1; J.2 |
| Report number: | HUBS Lab Paper No. 2026-008 |
| Cite as: | arXiv:2610.09119 [cs.AI] |
| (or arXiv:2610.09119v2 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.09119 arXiv-issued DOI via DataCite |
Submission history
From: Wooyoung Jung [view email]
[v1]
Tue, 6 Oct 2026 21:12:03 UTC (400 KB)
[v2]
Tue, 10 Nov 2026 22:39:32 UTC (391 KB)
来源：arXiv cs.AI · arxiv.org