Edge/Fog-based Architecture Design for Intelligent Surveillance Systems in Smart Cities: A Software Perspective
Sandra Fares, Nour Ahmed Ghoniem, Mariam Hesham, Samiha Hesham, Nour Elhoda Hesham, Lobna Shaheen, Islam Tharwat Abdel Halim · 2021
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, resource-efficient, 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.