The proliferation of Internet of things (IoT) devices in smart cities, transportation, healthcare, and industrial applications, coupled with the explosive growth of AI-driven services, has increased demands for efficient distributed computing architectures and networks, driving cloud-edge-terminal collaborative intelligence (CETCI) as a fundamental paradigm within the artificial intelligence of things (AIoT) community. With advancements in deep learning, large language models (LLMs), and edge computing, CETCI has made significant progress with emerging AIoT applications, moving beyond isolated layer optimization to deployable collaborative intelligence systems for AIoT (CISAIOT), a practical research focus in AI, distributed computing, and communications. This survey describes foundational architectures, enabling technologies, and scenarios of CETCI paradigms, offering a tutorial-style review for CISAIOT beginners. We systematically analyze architectural components spanning cloud, edge, and terminal layers, examining core technologies including network virtualization, container orchestration, and software-defined networking, while presenting categorizations of collaboration paradigms that cover task offloading, resource allocation, and optimization across heterogeneous infrastructures. Furthermore, we explain intelligent collaboration learning frameworks by reviewing advances in federated learning, distributed deep learning, edge-cloud model evolution, and reinforcement learning-based methods. Finally, we discuss challenges (e.g., scalability, heterogeneity, interoperability) and future trends (e.g., 6G+, agents, quantum computing, digital twin), highlighting how integration of distributed computing and communication can address open issues and guide development of robust, efficient, and secure collaborative AIoT systems.

翻译：随着物联网（IoT）设备在智慧城市、交通、医疗和工业应用中的普及，以及人工智能（AI）驱动服务的爆炸式增长，对高效分布式计算架构与网络的需求日益增加，推动了云-边-端协同智能（CETCI）成为人工智能物联网（AIoT）领域的基础范式。随着深度学习、大语言模型（LLMs）和边缘计算的发展，CETCI在AIoT新兴应用中取得了显著进展，从孤立层级优化转向可部署的AIoT协同智能系统（CISAIOT），成为人工智能、分布式计算与通信领域的实际研究焦点。本综述阐述了CETCI范式的基础架构、使能技术与应用场景，为CISAIOT初学者提供教程式综述。我们系统分析了涵盖云、边、端层级的架构组件，审视了包括网络虚拟化、容器编排和软件定义网络在内的核心技术，同时提出了覆盖任务卸载、资源分配及跨异构基础设施优化的协同范式分类。此外，我们通过回顾联邦学习、分布式深度学习、边云模型演进和基于强化学习的方法进展，阐释了智能协同学习框架。最后，我们探讨了挑战（如可扩展性、异构性、互操作性）与未来趋势（如6G+、智能体、量子计算、数字孪生），强调了分布式计算与通信的融合如何应对开放性问题，并指导构建鲁棒、高效、安全的协同AIoT系统。