Generative AI for Smart IoT Systems

Abstract

The convergence of Generative Artificial Intelligence (GenAI) and Internet of Things (IoT) is emerging as a transformative paradigm for smart environments. Traditional IoT systems mainly rely on sensing, data collection, and rule?based automation, but lack adaptive intelligence and predictive creativity. Generative AI models, including large language models, generative adversarial networks, and diffusion models, introduce capabilities such as synthetic data generation, autonomous decision?making, scenario simulation, and intelligent interaction. This paper presents a comprehensive review of Generative AI for smart IoT systems, covering architectures, enabling technologies, applications, benefits, and challenges. The role of GenAI in enhancing smart homes, healthcare monitoring, industrial IoT, and smart cities is examined. Integration frameworks combining edge computing, cloud AI, and IoT devices are discussed with comparative analysis. The paper also explores issues such as privacy, security, energy constraints, and model deployment in resource?limited devices. Finally, future research directions including federated generative learning, explainable IoT intelligence, and self?evolving cyber?physical systems are outlined. The study concludes that Generative AI has strong potential to convert IoT networks from passive sensing infrastructures into proactive and adaptive intelligent ecosystems.

KEYWORDS: Generative AI, Smart IoT, Edge Intelligence, Synthetic Data, Smart Cities, Industrial IoT, AIoT, Autonomous Systems