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In recent years, smart video surveillance (SVS) systems have become essential in maintaining public safety and security, particularly in smart city environments. We propose an SVS system that uses advanced technologies such as artificial intelligence and computer vision to ensure the timely detection of anomalous behaviors and suspicious objects. The system’s performance is demonstrated through a smartphone application and real-world scenario videos, highlighting its effectiveness in enhancing citizen security with low latency. This paper represents a demonstration of such a system for implementing community-in-the-loop smart video surveillance systems and emphasizes their practicality in improving public safety in various settings. The study adds to the growing research on deploying smart video surveillance systems and underscores the importance of engaging local communities in these projects.