OPTIMIZATION OF FRAMES PER SECOND (FPS) IN CAMERA SYSTEMS WITH A FOCUS ON SURVEILLANCE

The optimization of frames per second (FPS) in camera systems is a critical factor in enhancing the efficiency and reliability of modern surveillance applications. FPS directly influences image clarity, motion detection accuracy, and the overall responsiveness of monitoring systems. High FPS ensures smoother video streams, enabling precise identification of fast-moving objects, while low FPS conserves bandwidth and storage resources. This study explores the balance between performance and resource management in surveillance environments, focusing on adaptive FPS optimization techniques. Key strategies include dynamic frame rate adjustment based on scene activity, integration of artificial intelligence for motion-triggered recording, and hardware-software co-optimization to reduce latency. By aligning FPS with contextual surveillance needs—such as crowd monitoring, traffic control, and perimeter security—camera systems can achieve improved situational awareness without excessive computational or storage overhead. The findings highlight that intelligent FPS optimization not only enhances operational efficiency but also strengthens the scalability and sustainability of surveillance infrastructures.