Intelligent Video Surveillance using Deep-Learning Models.

Closed-circuit television, or CCTV, is another name for video surveillance. It is a fast-expanding sector that has been around for more than 30 years and has seen many technological advancements. In the modern world, maintaining public safety now requires the use of video surveillance. One can define security. In a number of ways, depending on the situation, including danger of explosion, theft, violence, and so forth. In busy public spaces, "security" can refer to nearly any kind of unusual event. Depending on the user's preferences, intelligent video surveillance records unforeseen activities in homes, offices, and public spaces to provide state-of- the-art smart security. The video surveillance system will actively react to detect actions ahead of time through real-time monitoring and promptly communicate data in the event of an abnormal incident. The main focus is on the application of deep learning techniques to provide motion-activated night vision technology, high-definition picture quality, and tracking of a moving target. Additionally, the system is equipped with automatic audio and visual detection, video recording initiation, and detection of suspicious activities that can activate and alert the systems in any type of weather. The data processing model design aims to employ deep learning technology to visualize data for anomalous activities. It also suggests an intelligent surveillance system to promptly and efficiently identify activities by transmitting a video image and an alert message to the web through real-time processing. Advances in computer vision, especially in deep learning techniques, have created new avenues for these systems to explore, expanding their potential and stimulating new fields of study. [ABSTRACT FROM AUTHOR]