Innovative Research on IoT Architecture and Robotic Operating Platforms: Applications of Large Language Models and Generative AI
This work addresses the problem of improving automation and adaptability in IoT and robotics for industries, but it appears incremental as it integrates existing technologies without claiming new breakthroughs.
This paper tackled the design of robotic operating platforms with an IoT architecture using LLMs and generative AI to enhance intelligence and autonomy, demonstrating through case studies in smart manufacturing, healthcare, and service sectors that it optimizes workflows and boosts productivity.
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.