DESIGN AND IMPLEMENTATION OF A VIDEO SURVEILLANCE SYSTEM

Surveillance cameras have recently been utilized to provide physical security services globally in diverse private and public spaces. The number of cameras has been increasing rapidly due to the need for monitoring and recording abnormal events. This process can be difficult and time consuming when detecting anomalies using human power to monitor them for special security purposes. Abnormal events deviate from normal patterns and are considered rare. Furthermore, collecting or producing data on these rare events and modeling abnormal data are difficult. Therefore, there is a need to develop an intelligent approach using artificial intelligence (AI) to overcome this challenge. Many research studies have been conducted on detecting abnormal events using machine learning and deep learning techniques. This project focused on abnormal event detection, potential intrusion, and vandalism, particularly for video surveillance applications. The project discusses the potential benefits of using AI to analyze video feed data, including identifying environmental movement anomalies. The project provides an example of the practical implementation and use of AI and video surveillance technologies in today's security system.