Edge/Fog-based Architecture Design for Intelligent Surveillance Systems in Smart Cities: A Software Perspective

Surveillance systems are critical for the growth of smart cities. These systems can be thought of as the cities’ vision organs. It is anticipated that smart cities will produce a massive amount of data. Thus, to ensure the safety of its people, it is essential to conduct an efficient and real-time analysis of these data in order to receive timely responses in the event of catastrophic incidents. As a result, the process of transferring this vast data to the cloud for processing is relatively slow. In this paper, we present the software perspective to design and implement EFISS, a multilayer computing-based architecture for an intelligent, resourceefficient, and real-time surveillance system for smart cities. The framework, which is comprised of edge-fog computational layers, would help in the prevention of crime and the prediction of criminal incidents in smart cities. The EFISS can identify and validate crimes in real-time, using artificial intelligence (AI) and an event-driven method to transmit crime data to protective services and police units, allowing rapid intervention while conserving resources.