CCTV-based video monitoring technology is one of the fastest growing security technologies markets. The existing video monitoring systems are, however, still not in a position to be used to prevent crime. For public safety purposes, large networks of cameras are increasingly deployed in public places like Residential Buildings, College Campus, offices, airports, railway stations, and shopping malls. Such systems are primarily dependent on human observers and are therefore limited over long periods by factors such as exhaustion and monitoring. In order to overcome this constraint, "intelligent" systems are required, which can highlight the critical data and remove normal conditions that are not a safety hazard. We propose a model utilizing machine learning techniques in order to build these smart systems. This research aims to create an application in real time, which is necessary for labs, places of work or homes where human detection and Recognition will be done for human safety