Suspicious Behavior Detection Using Man Machine Model with Integration of Virtual Reality

Video or CCTV surveillance plays an important role in the security of any place whether it is residential areas, industries, public spaces like shopping malls, museums and other monuments, banks, offices, building sites, warehouses, airports, railway stations, etc. It will help in preventing theft and damage to manufactured goods and products as well as manufacturing equipment, having complete and recorded production accident data, having complete and recorded production accident data, monitoring every stage of the manufacturing process, and prevention and analysis of any type of crime. But the current systems rely too much on humans monitoring the feeds from these videos which are prone to some problems like reduced attention and fatigue during long stretches of monitoring. So, there is a need for a system where these humans are aided by the machines in the monitoring process. The system proposed and implemented in this study would help to overcome this problem by aiding the man with smart machines and neural networks. Also, the system works on video camera feed instead of static camera shots which would help in capturing the sequential information that may be missed when using static images. And along with this, a model has been proposed using neural network technology that can automatically identify the individuals exhibiting the suspicious behavior from live camera feed input. At last research has been done on whether to use virtual reality on live video or CCTV surveillance or not based on various research papers published in similar domain.