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）具备生成逼真数据并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，并蕴含着彻底改变社会各个层面的巨大潜力，能够实现更高效、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，并对其潜在前景进行了探索。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。接着，我们详细阐述了实现GIoT面临的主要挑战，并提出了一种通用的基于GAI的安全激励机制框架来应对这些挑战，其中采用生成扩散模型（GDM）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控为例进行案例研究，利用GDM生成有效合约，以激励用户贡献高质量的传感数据。最后，我们展望了若干值得研究的开放方向，以推动GIoT未来的普及。