LLM Applications in the Internet of Things

Dear Colleagues,

The Internet of Things (IoT) has experienced rapid growth in recent years, generating widespread interest in domains such as smart cities, healthcare, industrial systems, and wearable devices. The increasing ubiquity of connected sensors and actuators has led to unprecedented volumes of heterogeneous data, demanding more intelligent, adaptive, and human-centered ways of managing and exploiting this information. In parallel, Large Language Models (LLMs) have emerged as a prominent development in Artificial Intelligence (AI), enabling users to interact with computer systems through natural language and offering new capabilities in understanding, summarizing, and reasoning complex data.

The convergence of IoT and LLMs represents a natural next step in the evolution of intelligent environments. LLMs can serve as an interpretative and interaction layer on top of IoT infrastructures, transforming raw, low-level signals into higher-level, context-aware insights accessible to non-expert users. This opens the door to more intuitive interfaces, proactive decision support, and automated control mechanisms better aligned with human needs and expectations. At the same time, this integration raises important challenges related to resource constraints at the edge, data privacy and security, robustness, explainability, and the alignment of LLM-driven behaviors with domain-specific requirements and regulations.

This Special Issue will present cutting-edge research and comprehensive reviews on the application of LLMs in the IoT domain. We welcome contributions that address the analysis and interpretation of IoT data, the generation of coherent and understandable information to support individual and organizational decision-making processes, and comparative assessments of LLM-based solutions against alternative approaches in terms of performance, scalability, robustness, and usability. Submissions may include novel architectures and frameworks, methodologies for deployment at the edge or in resource-constrained environments, security- and privacy-preserving solutions, evaluation benchmarks, and real-world case studies and applications in domains such as smart cities, healthcare, industry, agriculture, transport, and ambient assisted living.

Dr. António Jorge Morais
Dr. Henrique São Mamede
Dr. Vitor Rocio
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. IoT is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• large language models
• Internet of Things
• artificial intelligence
• natural language
• data interpretation