Development of an Intelligent Video Surveillance System Based on YOLO Algorithm

In the contemporary landscape characterized by swift technological advancements and escalating security challenges, the evolution of intelligent video surveillance systems emerges as a pivotal innovation. These systems, integral to the security of both public and private domains, harness the power of automated, advanced analytics to enhance operational efficiency and situational awareness without necessitating constant human oversight. This paper focuses on the development of an intelligent video surveillance system tailored specifically for office premises, emphasizing the system’s architecture and the strategic selection of technologies. Through meticulous exploration, this study evaluates state-of-the-art models for real-time object detection tasks, acknowledging the intricate balance between performance and accuracy essential for deploying such algorithms. The proposed framework includes a comprehensive comparison of various models, culminating in the design of a robust system architecture and a web-based infrastructure for seamless implementation. The system’s effectiveness is demonstrated through experimental results, showcasing its capability in real-world scenarios such as occupancy monitoring, boundary control, and facial recognition. This paper contributes to the field by showcasing the development and implementation of a sophisticated intelligent video surveillance system, highlighting its potential in enhancing security and operational efficiency in office environments.