Human attention is a finite resource, and this limitation becomes critically apparent when monitoring multiple video feeds in real-time using a CCTV program. Security professionals tasked with observing dozens of surveillance cameras experience a sharp drop in performance after as little as 20 to 30 minutes of continuous viewing. Cognitive science and practical research both indicate that a human can effectively monitor only between 4 to 8 video streams simultaneously before attention lapses begin to occur. This phenomenon, known as vigilance decrement, not only leads to slower reaction times but also increases the chances of missing important security events. After 8 hours of uninterrupted monitoring, operator efficiency significantly deteriorates, and the risk of critical incidents being overlooked becomes unacceptably high. The problem becomes exponentially worse when a CCTV program is configured to display massive grids of video feeds - 32, 64, or even 100 at once. In such scenarios, even the most experienced operator cannot maintain full awareness. Studies suggest that the optimal number of feeds on a screen for effective human monitoring lies between 9 and 16. Anything above that threshold creates visual clutter and overwhelms cognitive processing capabilities, especially when there's frequent motion in the footage. Modern security environments - such as airports, shopping malls, smart cities, and industrial complexes - often require surveillance over hundreds or thousands of cameras. In these cases, expecting a team of humans to maintain effective 24/7 monitoring becomes not only inefficient but also logistically impossible. This is where intelligent features of a modern CCTV program make a significant impact. Leveraging artificial intelligence and machine learning, today's top CCTV software can automatically detect motion, recognize faces, identify license plates, and even detect unusual behavior patterns. These AI-powered tools drastically reduce the reliance on human attention by filtering out non-essential footage and flagging only events that require human review. The result is a system that works smarter, not harder. Rather than watching every feed at all times, security personnel are only alerted when actionable events occur. Additionally, modern CCTV programs are scalable, allowing organizations to expand their surveillance coverage without adding more human operators. A single intelligent program can process data from hundreds or even thousands of cameras, analyze patterns in real-time, and generate alerts within milliseconds. While AI in CCTV programs has not completely replaced the need for human judgment - especially in nuanced or context-sensitive situations - it has dramatically reduced the need for constant manual oversight. Security teams can now shift their focus from passive observation to proactive incident response and strategic planning. In large-scale environments, AI-assisted CCTV programs are no longer optional - they're essential. As surveillance systems grow in complexity and scale, the role of traditional monitoring continues to evolve, with AI becoming the primary force multiplier. This shift marks a significant transformation in how we approach real-time security, making intelligent CCTV programs the backbone of modern surveillance infrastructure.