Working paper Open Access
Kioumourtzis, George; Skitsas, Michael; Zotos, N; Sideris, A
Current Surveillance systems in enterprise facilities and public places produce massive amounts of video content while operating at a 24/7 mode. There is an increasing need to process, on the fly, such huge video data streams to enable a quick summary of “interesting” events that are happening during a specified time frame in a particular location. Concepts like fog computing based on localisation of data processing will relax the need of existing cloud-based solutions from extensive bandwidth and processing needs at remote cloud resources. In this paper, we describe a novel architecture for a smart surveillance system based on edge and fog computing concepts. We provide the main architectural components, the hardware options and key software components of the system. Edge computing is realized by a camera embedded system while fog computing is used for the processing and data fusion of video streams in small areas. Lab tests concentrated on the different versions of edge computing devices have shown the efficiency of the system.