Effective Surveillance using Computer Vision

Human society significantly relies on CCTV cameras to maintain a high standard of security. CCTV footage is usually only utilized a few hours or days following an incident. Although it frequently serves as important evidence in court, it is rarely used for crime prevention or real-time intervention. The fact that only few security officers are primarily in charge of watching the ample amounts of CCTV footage is what causes inefficiency. Human supervision cannot be completely relied due to the weariness and boredom among the workforce, and lag in observation. Developing an effective surveillance system is a significant challenge in computer vision, data processing, and decision-making process. Smart Surveillance Systems use image analysis and machine learning techniques to extract and analyze the data from CCTV footage far more quickly and effectively than a human observer. This would encourage the relevant authorities to create a platform using image processing and machine learning techniques so that the violence in public places might be prevented. The system must also involve cops when the situation worsens and make sure that it captures every human involved in the respected frame. The system must be trained thoroughly to ensure that it can recognize whether there is violence.