Edge AI for Real-Time Video Analytics in Surveillance Systems

Abstract

More and more surveillance systems are being used to increase security and safety for the general public. However, the conventional method of processing all video data in the cloud can be ineffective and slow response times. By performing video analytics at the network's edge, close to where the data is created, Edge AI is a promising new strategy that can address these issues.

The most recent developments in edge AI for real-time video analytics in security systems are discussed in this paper. We discuss the different techniques that are being used, as well as the applications that are being enabled by edge AI. The paper also discusses the challenges and limitations of edge AI, and the future research directions in this area.