Security cameras are widely used for surveillance and monitoring purposes, but they often require human intervention to analyze the captured images and videos. In this paper, we review a project that aims to develop a smart security camera system that can automatically detect and track objects of interest using computer vision techniques. The project uses the following python libraries: cv2 for image processing and object detection, winsound for sound alerts, tkinter for graphical user interface, threading for concurrent execution, and PIL for image manipulation. The system runs on a python IDE such as pycharm and uses the built-in camera of the device. We describe the main features of the system, as well as the difficulties and constraints faced throughout the designing procedure. We also discuss the potential applications and future improvements of the system.