Recently, Smart Video Surveillance (SVS) systems have been receiving more
attention among scholars and developers as a substitute for the current passive
surveillance systems. These systems are used to make the policing and
monitoring systems more efficient and improve public safety. However, the
nature of these systems in monitoring the public's daily activities brings
different ethical challenges. There are different approaches for addressing
privacy issues in implementing the SVS. In this paper, we are focusing on the
role of design considering ethical and privacy challenges in SVS. Reviewing
four policy protection regulations that generate an overview of best practices
for privacy protection, we argue that ethical and privacy concerns could be
addressed through four lenses: algorithm, system, model, and data. As an case
study, we describe our proposed system and illustrate how our system can create
a baseline for designing a privacy perseverance system to deliver safety to
society. We used several Artificial Intelligence algorithms, such as object
detection, single and multi camera re-identification, action recognition, and
anomaly detection, to provide a basic functional system. We also use
cloud-native services to implement a smartphone application in order to deliver
the outputs to the end users