A Novel Framework of Smart Security System Based on Machine Learning Techniques

This work aims to use Python and OpenCV libraries to create a smart camera system that can function independently and help people. The suggested system can also identify absent items using the frame difference technique. It also has a recording function, an alert function for people entering the room, and an alert function for detecting motion. This project's functions include normal recording, monitoring, recognizing members, detecting noise, and detecting visits in rooms. To identify motion, the SSIM approach is employed by the monitor feature; the LBPH algorithm is utilized for face recognition; and the video writer function of OpenCV is used to record live video while the visitor detection feature keeps an eye out for new faces. Numerous iterations of the intended project's execution have been tried, yielding its own results. The outcomes were commensurate with expectations. Functionality testing showed that the features were useful in achieving their goals. The Python graphical user interface (GUI) program is utilized, and it may run on any PC with a webcam or USB camera. The system incorporates a number of characteristics that may detect and identify criminal activity, making it simpler for law enforcement to apprehend and prosecute offenders while satisfying the security demands of individuals and businesses. Only a few potential additions to the proposed project are mentioned.