  The demand for smartness in embedded systems has been mounting up drastically
in the past few years. Embedded system today must address the fundamental
challenges introduced by cloud computing and artificial intelligence. KubeEdge
[1] is an edge computing framework build on top of Kubernetes [2]. It provides
compute resource management, deployment, runtime and operation capabilities on
geo-located edge computing resources, from the cloud, which is a natural fit
for embedded systems. Here we propose KubeEdge.AI, an edge AI framework on top
of KubeEdge. It provides a set of key modules and interfaces: a data handling
and processing engine, a concise AI runtime, a decision engine, and a
distributed data query interface. KubeEdge.AI will help reduce the burdens for
developing specific edge/embedded AI systems and promote edge-cloud
coordination and synergy.
