arXiv cs.AI· Wooyoung Jung·· 1 天前AI 评分31
哪些建筑已为 AI 做好准备？面向 AI 问答与执行控制的基于测量的评估框架
Which Buildings Are Artificial Intelligence-Ready? A Measurement-Based Assessment Framework for AI Question Answering and Actuation
AI 导读
研究提出一套量化建筑 AI 就绪度的框架：建筑知识图谱设定"可回答就绪度"与"可执行就绪度"两个上限，再由参考 AI 智能体在固定问题集上的准确率衡量上限的实现程度。
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