Current research on Internet of Things (IoT) mainly focuses on how to enable
general objects to see, hear, and smell the physical world for themselves, and
make them connected to share the observations. In this paper, we argue that
only connected is not enough, beyond that, general objects should have the
capability to learn, think, and understand both physical and social worlds by
themselves. This practical need impels us to develop a new paradigm, named
Cognitive Internet of Things (CIoT), to empower the current IoT with a `brain'
for high-level intelligence. Specifically, we first present a comprehensive
definition for CIoT, primarily inspired by the effectiveness of human
cognition. Then, we propose an operational framework of CIoT, which mainly
characterizes the interactions among five fundamental cognitive tasks:
perception-action cycle, massive data analytics, semantic derivation and
knowledge discovery, intelligent decision-making, and on-demand service
provisioning. Furthermore, we provide a systematic tutorial on key enabling
techniques involved in the cognitive tasks. In addition, we also discuss the
design of proper performance metrics on evaluating the enabling techniques.
Last but not least, we present the research challenges and open issues ahead.
Building on the present work and potentially fruitful future studies, CIoT has
the capability to bridge the physical world (with objects, resources, etc.) and
the social world (with human demand, social behavior, etc.), and enhance smart
resource allocation, automatic network operation, and intelligent service
provisioning.

本文主旨在于提出名为 CIoT 的新兴物联网模式，该模式着重于为普遍物品提供高水平智能的 AI 能力，其包含五个认知任务并涵盖了海量数据分析、智能决策和按需服务提供等关键技术。