This project seeks to develop a web application that combines traffic sign recognition capability with user’s navigation needs. Users will have the ability to upload traffic sign images and capture the live feed from the camera for traffic sign recognition, and an automated system utilizing CNN will be deployed to recognize and encode the sign’s meaning with a speech synthesis. The system is enhanced by the addition of a location service where users can look up the hospitals, restaurants, and gas stations available within a certain distance range from their locations. All the findings are presented to the user as clickable points on a map that shows the best route from the user’s current location to the target place. This project makes use of the Google Maps API to look for locations and draw routes on the map, while Flask captures input data for processing on the server side. This system is implemented in HTML and CSS and JavaScript with the client side being responsive. By integrating location-based technologies using machine learning, the traffic sign detection and real time navigation is fully automated, and it is very useful for various drivers and tourists.