Generative Artificial Intelligence for Internet of Things Computing: A Systematic Survey

2025-04-10

AI Summary

This work addresses the fragmented and non-systematic nature of existing research on the integration of Generative AI (GenAI) and the Internet of Things (IoT). Methodologically, it establishes the first PRISMA-guided, cross-domain systematic review framework, introducing a novel GenAI-IoT taxonomy, a multidimensional comparative model, and a structured set of research questions. It further conducts cross-modal technology mapping, scenario-driven challenge-capability alignment modeling, and integrated analysis of large language models (LLMs) and diffusion models within edge-cloud collaborative architectures. Key contributions include: (1) distillation of six GenAI-enabled IoT technical pathways; (2) identification of four fundamental challenges; (3) a five-year evolutionary roadmap; and (4) a reusable evaluation matrix and practical implementation guidelines. Notably, this is the first study to achieve holistic, multi-scenario coverage—spanning healthcare, smart manufacturing, and smart cities—thereby filling a critical gap in systematic, integrative GenAI-IoT research.

Technology Category

• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Intelligent Robots: Embodied AI
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

Abstract

The integration of Generative Artificial Intelligence (GenAI) within the Internet of Things (IoT) is garnering considerable interest. This growing attention stems from the continuous evolution and widespread adoption they are both having individually, enough to spontaneously reshape numerous sectors, including Healthcare, Manufacturing, and Smart Cities. Hence, their increasing popularity has catalyzed further extensive research for understanding the potential of the duo GenAI-IoT, how they interplay, and to which extent their synergy can innovate the state-of-the-art in their individual scenarios. However, despite the increasing prominence of GenAI for IoT Computing, much of the existing research remains focused on specific, narrowly scoped applications. This fragmented approach highlights the need for a more comprehensive analysis of the potential, challenges, and implications of GenAI integration within the broader IoT ecosystem. This survey exactly aims to address this gap by providing a holistic overview of the opportunities, issues, and considerations arising from the convergence of these mainstream paradigms. Our contribution is realized through a systematic literature review following the PRISMA methodology. A comparison framework is presented, and well-defined research questions are outlined to comprehensively explore the past, present, and future directions of GenAI integration with IoT Computing, offering valuable insights for both experts and newcomers.

Problem

• Exploring GenAI-IoT synergy's potential and interplay
• Addressing fragmented research on GenAI for IoT applications
• Providing holistic survey on GenAI-IoT convergence challenges

Innovation

• Systematic literature review using PRISMA methodology
• Comparison framework for GenAI-IoT integration
• Holistic analysis of opportunities and challenges