This article introduces a novel distributed model for handling in real-time, edge-based
Artificial Intelligence analytics, such as the ones required for smart video surveillance. The …

Edge computing has opened new doors for real-time video analytics applications due to its
ability to offer significantly faster response times by processing videos near the source …

Edge computing has been getting a momentum with ever-increasing data at the edge of the
network. In particular, huge amounts of video data and their real-time processing …

Intelligent video analytics systems have come to play an essential role in many fields,
including public safety, transportation safety, and many other industrial areas, such as …

Video analysis typically requires a significant amount of computing resources and energy.
Traditional cloud-based video analysis relies on concentrating computing resources in the …

This paper introduces a novel distributed AI model for managing in real-time, edge based
intelligent analytics, such as the ones required for smart video surveillance. The novelty …

Edge computing has gained momentum in recent years, and can provide more immediate
analysis of streaming video data. However, the edge devices often lack the computing …

Real-time video analytics services are expected to deliver accurate recognition results to
users timely. However, existing studies usually fail in the dilemma between reducing delay …

With the advent of the Edge and Cloud server in the 5G system, an application needs to be
designed to have multiple components, where a part of it (Data Intensive Component (DIC)) …

Video analytics will drive a wide range of applications with great potential to impact society.
A geographically distributed architecture of public clouds and edges that extend down to the …