LLM Agents for Internet of Things (IoT) Applications

UIUC Spring 2025 CS598 LLM Agent Workshop Submission10 Authors

Keywords: LLM Agents, IoT, Agent Architectures, Edge Computing, Cybersecurity, Smart Homes, Industrial IoT, Healthcare Monitoring

Abstract: The rapid proliferation of Internet of Things (IoT) technologies has transformed numerous sectors by enabling real-time monitoring, automation, and data-driven insights. IoT systems still struggle with challenges stemming from raw, heterogeneous data, limited contextual understanding, and rigid, rule-based analytics. Meanwhile, Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language understanding, reasoning, and human-machine interaction. Integrating large-language models with the Internet of Things (IoT) represents a rapidly evolving research area with significant potential to enhance multi-user connected IoT systems' adaptability, intelligence, and user experience. This survey paper explores the various applications of LLMs in IoT, including their role in recent advancements that integrate LLMs into IoT workflows from edge intelligence and smart interfaces to dynamic task execution and generative interaction. Furthermore, the study will examine key challenges, such as computational overhead, latency, and data privacy concerns associated with deploying LLMs in resource-constrained IoT environments. Through a comprehensive review of the existing literature and recent advancements, this paper seeks to highlight emerging trends and provide insights into the future development of LLM-driven IoT applications. We analyze prominent use cases, architectural trends, and optimization techniques, and we discuss the technical, ethical, and operational challenges that arise. We also outline promising future directions for developing scalable, efficient, and context-aware IoT systems empowered by LLM agents.

Submission Number: 10