Edge-Based Video Surveillance with Embedded Devices

Kavalionak H., Gennaro C., Amato G., Vairo C., Perciante C., Meghini C., Falchi F., Rabitti F.

Edge computing  Distributed architectures  Internet of things  Video surveillance  Embedded devices 

Video surveillance systems have become indispensable tools for the security and organization of public and private areas. In this work, we propose a novel distributed protocol for an edge-based face recogni-tion system that takes advantage of the computational capabilities of the surveillance devices (i.e., cameras) to perform person recognition. The cameras fall back to a centralized server if their hardware capabili-ties are not enough to perform the recognition. We evaluate the proposed algorithm via extensive experiments on a freely available dataset. As a prototype of surveillance embedded devices, we have considered a Rasp-berry PI with the camera module. Using simulations, we show that our algorithm can reduce up to 50% of the load of the server with no negative impact on the quality of the surveillance service.

Source: 28th Symposium on Advanced Database Systems (SEBD), pp. 278–285, Villasimius, Sardinia, Italy, 21-24/06/2020