LLMs and IoT: A Comprehensive Survey on Large Language Models and the Internet of Things

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Authors: Fatemeh Sarhaddi, Ngoc Thi Nguyen, Agustin Zuniga, Musfira Khan, Pan Hui, Sasu Tarkoma, Huber Flores, Petteri Nurmi
Cited by: 4
References: 203

Abstract

The Internet of Things (IoT) has emerged as a technological cornerstone, enabling highly interconnected systems that integrate billions of diverse devices. The combined data output of these devices is estimated at hundreds of exabytes per day. The rise of Large Language Models (LLMs) presents new opportunities for managing these devices, processing the data they generate, and addressing the technological and societal challenges posed by IoT ecosystems. However, the integration of LLMs into IoT also introduces significant challenges. This article offers the most comprehensive survey to date on the integration of LLMs into IoT ecosystems. We cover various technical layers, including devices, software engineering, sensing, networking, data processing, privacy and security, and human interaction.We synthesize insights from more than 300 articles, identify open research gaps, and highlight promising future directions, ranging from semantic reasoning and communication to the integration of quantum computing. By addressing the characteristics, challenges, and opportunities associated with LLM integration, this article serves as a foundational resource for researchers and practitioners aiming to enhance IoT functionalities with LLMs while navigating the associated complexities.

Fields of Study & Subjects

Big Data and Digital Economy Artificial Intelligence in Healthcare and Education IoT and Edge/Fog Computing

Publication details

Journal / source
IEEE Open Journal of the Communications Society
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
7
Pages
3585–3616
Publication date
1 January 2026