INTELLIGENT VIDEO SURVEILLANCE USING DEEP LEARNING

Abstract

Video surveillance, also known as CCTV (closed-circuit television), is a rapidly growing industry that has been around for more than 30 years and has seen its fair share of technological advancements. In today's world, video surveillance has become an essential component for ensuring public safety. Security can be defined in a variety of ways depending on the context, such as theft detection, violence detection, explosion risk, and so on. The term "security" in crowded public places refers to almost any type of abnormal event.Intelligent video surveillance delivers cutting-edge smart security by recording unexpected activities in homes, offices, and public locations based on the preferences of the user. In the event of an abnormal incident, the video surveillance system will actively respond to detect actions in advance through real-time monitoring and promptly communicate data. The primary focus is on the use of deep learning techniques to provide tracking of a moving target, high-definition picture quality, and night vision technology triggered by motion sensors, which means the system isn't running when nothing is happening at your location, automatic audio and visual detection, video recording initiation, and detection of suspicious activities that can trigger and alert the systems in all climate conditions.Deep learning technology will be used in the data processing model design to visualise data for abnormal activities, and this design also proposes an intelligent surveillance system to quickly and effectively detect activities by sending a video image and an alert message to the web via real-time processing. Recent improvements in computer vision, particularly deep learning approaches, have opened up new possibilities for these systems, enhancing their capabilities and launching new research areas in this field.