Generative Artificial Intelligence (GAI) possesses the capabilities of generating realistic data and facilitating advanced decision-making. By integrating GAI into modern Internet of Things (IoT), Generative Internet of Things (GIoT) is emerging and holds immense potential to revolutionize various aspects of society, enabling more efficient and intelligent IoT applications, such as smart surveillance and voice assistants. In this article, we present the concept of GIoT and conduct an exploration of its potential prospects. Specifically, we first overview four GAI techniques and investigate promising GIoT applications. Then, we elaborate on the main challenges in enabling GIoT and propose a general GAI-based secure incentive mechanism framework to address them, in which we adopt Generative Diffusion Models (GDMs) for incentive mechanism designs and apply blockchain technologies for secure GIoT management. Moreover, we conduct a case study on modern Internet of Vehicle traffic monitoring, which utilizes GDMs to generate effective contracts for incentivizing users to contribute sensing data with high quality. Finally, we suggest several open directions worth investigating for the future popularity of GIoT.

翻译：生成式人工智能（GAI）具备生成逼真数据和促进高级决策的能力。通过将GAI集成到现代物联网（IoT）中，生成式物联网（GIoT）正在兴起，并展现出变革社会各领域的巨大潜力，能够支持更高效、更智能的物联网应用，例如智能监控和语音助手。本文提出了GIoT的概念，并探讨了其潜在前景。具体而言，我们首先概述了四种GAI技术，并研究了有前景的GIoT应用。随后，我们阐述了实现GIot所面临的主要挑战，并提出了一种基于GAI的通用安全激励机制框架来应对这些挑战，其中我们采用生成扩散模型（GDMs）进行激励机制设计，并应用区块链技术实现安全的GIoT管理。此外，我们以现代车联网交通监测为例进行了案例研究，利用GDMs生成有效合约，以激励用户贡献高质量传感数据。最后，我们提出了若干值得探索的开放方向，以推动GIoT的未来普及。