This paper presents a highly accurate intelligent traffic sign recognition system, which has potential to greatly improve safety on roads and make autonomous driving possible. It uses convolutional neural networks (CNN) to detect and classify traffic signs, accurately robustly in real-time systems. The process involves preprocessing a large number of images, training the model and performing real-time detection with OpenCV in Python. The Node MCU Micro-controller is integrated to make the communication and responses more stable and can be set automatically after recognizing traffic signs. The findings show improved precision and stability of the properties that are essential for consideration in autonomous vehicle systems, where harmonious driving is needed to upgrade latest architectures.