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Abstract: Car License Plate Recognition is one of the important modules for a camera surveillance-based security system. This can be done by extracting the license plate from an image using computer vision techniques and by using Optical Character Recognition to recognize the license number. This project will also be making a drowsiness detection system. Day and night, a countless number of people drive on the highway. Truck drivers, bus drivers, and taxi drivers traveling long-distance suffer from a lack of sleep. Driving while sleepy becomes very dangerous as it may lead to accidents. Most accidents occur due to the drowsiness of the driver. The purpose of this project is to build a security system that prevents these accidents using Python, OpenCV, and Keras which will alert the driver when he feels sleepy. The aim of this project is to use the traffic database and apply the Deep Learning algorithms to it. This project can be used to help urban cities, especially smart cities, have a better understanding of traffic patterns. This leads us to better traffic management, which is a great need today. It can also be used to ensure that smart car drivers get their route without any further delays or traffic waiting time, solving many problems. Traffic forecasting can be used for infrastructure and security development. Traffic forecasts can be made in many cities. The main purpose of this project is to build an automated system that detects traffic signal violations and makes it easier for the traffic police department to monitor traffic and take action against the owner of the vehicle who drives in a fast manner. Detecting and tracking a vehicle and its operations accurately is a priority for the system.