arXiv:2412.14708cs.AIcs.DC2024-12综述被引 12

综述AI驱动的智能空间技术,涵盖感知、通信与AI应用。

Creation of AI-driven Smart Spaces for Enhanced Indoor Environments -- A Survey

  • 系统梳理智能空间的传感、通信与数据管理基础技术
  • 分析传统机器学习与大语言模型在智能空间中的应用潜力
  • 适合关注智慧建筑与人机交互的研究者参考

智能空间是融合多种感知与通信技术的普适计算环境,旨在提升空间功能、优化能源利用并改善用户舒适度与福祉。将新兴人工智能方法融入其中,形成AI驱动的智能空间,可实现个性化舒适设置、互动式生活空间及系统自动化,显著提升室内用户体验。本文系统综述了AI驱动智能空间的核心技术基础,包括传感器技术、数据通信协议、传感器网络管理与维护策略,以及数据采集、处理与分析方法。鉴于AI在构建智能空间中的关键作用,论文深入探讨了传统机器学习(如深度学习)与新兴方法(如大语言模型)面临的机遇与挑战。最后,提出关键技术洞察,展望未来研究方向,为智能空间的发展提供路径指引。

原文摘要 · Abstract (English)

Smart spaces are ubiquitous computing environments that integrate diverse sensing and communication technologies to enhance space functionality, optimize energy utilization, and improve user comfort and well-being. The integration of emerging AI methodologies into these environments facilitates the formation of AI-driven smart spaces, which further enhance functionalities of the spaces by enabling advanced applications such as personalized comfort settings, interactive living spaces, and automatization of the space systems, all resulting in enhanced indoor experiences of the users. In this paper, we present a systematic survey of existing research on the foundational components of AI-driven smart spaces, including sensor technologies, data communication protocols, sensor network management and maintenance strategies, as well as the data collection, processing and analytics. Given the pivotal role of AI in establishing AI-powered smart spaces, we explore the opportunities and challenges associated with traditional machine learning (ML) approaches, such as deep learning (DL), and emerging methodologies including large language models (LLMs). Finally, we provide key insights necessary for the development of AI-driven smart spaces, propose future research directions, and sheds light on the path forward.

智能空间AI应用人机交互物联网

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