相关实验视频

一个基于人工智能的技术数据提取工具,用于物联网应用系统

Dezheng Kong¹, Nobuo Funabiki¹, Htoo Htoo Sandi Kyaw¹

¹Department of Information and Communication Systems, Okayama University, Okayama 700-8530, Japan.

Sensors (Basel, Switzerland)

|February 27, 2026

概括

一个新的生成AI工具从物联网设备文档中提取技术数据,提高AI设置辅助的可靠性. 这通过将技术规范整合到检索增强生成 (RAG) 中来增强对新设备的支持.

科学领域:

计算机科学计算机科学
人工智能的人工智能
物联网的物联网,就是物联网.

背景情况:

物联网 (IoT) 系统对于智能应用程序至关重要,但对于非专家来说,其配置具有挑战性.
当前的人工智能设置工具与新的或未见的设备进行斗争,导致配置错误.
检索增强生成 (RAG) 可以通过整合技术文档数据来提高AI可靠性.

研究的目的:

开发一种生成性AI工具,从物联网设备数据表中提取技术数据.
增强基于人工智能的物联网设备,特别是新型设备的设置帮助.
为了提高物联网配置任务的可靠性和准确性.

主要方法:

提出了一个生成性AI工具,用于PDF/HTML数据表的基于模式的提取.
实现了局部向量数据库,用于语义相似性检索和RAG.
在传感器和设备数据表上评估该工具,将提取的数据与地面真相进行比较.
与商业基线 (ChatPDF) 相比,评估了端到端配置问答 (QA) 的可靠性.

主要成果:

该工具可靠地提取关键的物联网设备规格.
与ChatPDF相比,显著提高了端到端配置QA可靠性.
在960个QA对中实现了更高的回忆 (0.926对比0.636) 和精度 (0.807对比0.595).

结论:

生成型AI技术数据提取工具有效地补充了对物联网配置的AI知识.
拟议的方法确保对以前未见的物联网设备提供一致的支持.
这种方法提高了AI在复杂物联网系统设置中的实际可用性.

关键词:

在这里,我们可以看到AIAIAI.数据表数据表的数据表.物联网的东西互联网.提取增强生成的提取基于方案的提取方法技术信息技术信息技术信息矢量数据库是一个矢量数据库.

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