用大模型和生成式AI重构物联网机器人系统，实现动态智能决策。
Innovative Research on IoT Architecture and Robotic Operating Platforms: Applications of Large Language Models and Generative AI
- 基于物联网架构融合大模型与生成式AI，提升机器人自主性。
- 在智能制造、医疗等领域验证了流程优化与效率提升效果。
- 适合关注智能机器人与产业智能化的开发者与研究者。
本文提出一种创新的机器人操作系统设计，依托变革性的物联网（IoT）架构，无缝整合大型语言模型（LLMs）、生成式AI、边缘计算及5G网络等前沿技术。该平台旨在提升物联网系统与机器人的智能化与自主性，使其能够实时决策并动态适应环境变化。通过在智能制造、医疗健康及服务行业中的系列案例研究，论文展示了物联网赋能机器人在优化运营流程、提升生产力以及提供可扩展创新解决方案方面的巨大潜力。研究强调了大模型与生成式AI在推动智能机器人与物联网演进中的核心作用，揭示了这些技术对未来产业进步的深远影响。研究结果不仅展现了技术的变革力量，也提供了其更广泛社会与工业意义的前瞻性视角，将其定位为下一代自动化与技术融合的催化剂。
原文摘要 · Abstract (English)
This paper introduces an innovative design for robotic operating platforms, underpinned by a transformative Internet of Things (IoT) architecture, seamlessly integrating cutting-edge technologies such as large language models (LLMs), generative AI, edge computing, and 5G networks. The proposed platform aims to elevate the intelligence and autonomy of IoT systems and robotics, enabling them to make real-time decisions and adapt dynamically to changing environments. Through a series of compelling case studies across industries including smart manufacturing, healthcare, and service sectors, this paper demonstrates the substantial potential of IoT-enabled robotics to optimize operational workflows, enhance productivity, and deliver innovative, scalable solutions. By emphasizing the roles of LLMs and generative AI, the research highlights how these technologies drive the evolution of intelligent robotics and IoT, shaping the future of industry-specific advancements. The findings not only showcase the transformative power of these technologies but also offer a forward-looking perspective on their broader societal and industrial implications, positioning them as catalysts for next-generation automation and technological convergence.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。