The surveillance systems in the majority of the areas are conventional, i.e., they are only capable of recording the footage. If any burglary occurs in a mall, theatre, or even in a house, then at the time of robbery there will not be any intimation by the security systems that something is going wrong, but this smart surveillance system intimates the same with a beep sound so that we can take the immediate action during the robbery. We can train the model by providing images of the person involved in the robbery or the person whom we want to identify. For this purpose, a Local Binary Pattern Histogram (LBPH) algorithm is used; with the help of these images, it can identify the same person in the image or footage we provide during the investigation. Also, there are many features such as face detection, motion detection in a particular area in the frame, lost item detection, and simple recording features. We are using the OpenCV module in Python. OpenCV is an open-source computer vision and machine learning software library, it has many algorithms that are useful to detect and recognize faces, identify objects, classify human actions in videos, and track camera movements.