Object detection is a significant challenge in computer vision, and machine learning has advanced its performance over the last decade. This concept extends to tasks like classification, localization, and segmentation using deep models. The “Smart City” solution responds to urban challenges like pollution and traffic congestion by leveraging machine learning, artificial intelligence, and IoT devices to optimize functions and data analysis. Machine learning aids autonomous vehicle control, while Intelligent Transportation Systems enhance road safety through IoT-enabled data exchange. A lab study demonstrates a reliable traffic light assistant system via inter-vehicle communication. The paper also suggests a smart traffic detector using OpenCV and neural networks to tackle urban traffic congestion, enabling real-time image processing for traffic signal control and safety monitoring, with the potential for signal management and accident prevention.