AI Based Surveillance System
Karan Kumar Maheshwari, Shabana Hajano, Saba Baloch, Zarshah Zafar, Tehreem Fatima · 2025
Increased demand for enhanced safety and security in the different sectors has brought with it great advancements in AI-powered smart surveillance systems. Such systems take advantage of the latest developments in computer vision, sensor integration, and Automated Machine Learning to monitor and analyze video and image data automatically. Unlike traditional surveillance systems, which highly rely on human intervention and often fail to provide real-time decision-making or predictive analysis, modern AI-powered systems address these limitations. Specifically, tracking individuals across multiple locations and consolidating their data into a unified framework remains a challenge for conventional setups. The system utilizes powerful AI algorithms, such as HAAR-CASCADE, for face detection. The algorithm ensures that there is accurate and reliable identification of individuals in real time. Furthermore, the system carries out behavior analysis to identify any unusual activities, hence improving its application in the public and private sectors. Multithreaded Python programming is used which allows the efficient handling of high volumes of data since several tasks, including video feed analysis and log generation, can run at the same time without delay. An ideal implementation of this system is in educational institutions, where it streamlines processes such as monitoring student behavior. With this system, upon the detection of students from various locations on campus, a single log is formed for every student, creating an overall record of thatstudent's movements, attending classes, and activities all under one roof. Therefore, this capability improves precision but saves valuable time as well as administrative effort involved.