Implementation of a Remote Real-Time Surveillance Security System for Intruder Detection

Family security is one of the key goals of a digital home system. At present, webcams are widely used in home remote monitoring systems. This is due to the fact that its passive monitoring nature leaves a potential security problem and cannot be used for providing proactive security. To solve this problem, this paper proposes the design of a remote embedded intelligent security monitoring system based on the background modeling algorithm in computer vision which can proactively detect intruders. The system uses the ViBe algorithm to model the background image which is acquired from the camera, and then carries out the object detection in the monitored environment. If a moving object (including people) is detected, the system will automatically sound an alarm, while sending a message or calling the user to take preventive measures. Users can log in to the server through the mobile application to detect the intruder from the intercepted picture, and to get a better understanding of the situation. After testing, the system can accurately determine whether there is something intruding the monitoring area or not. It is robust, real-time, and with a good practical application value.