This paper presents a novel smart parking system that utilizes deep learning techniques to enhance parking management in urban environments. The proposed system employs the Yolo algorithm for real-time object detection, enabling efficient identification of available parking spaces. By integrating advanced technologies, the system aims to reduce the time spent searching for parking, thereby alleviating traffic congestion and improving overall urban mobility. The implementation of this solution demonstrates significant improvements over traditional sensor-based systems, offering a more reliable and user-friendly experience for drivers. The obtained results indicate that the Yolo algorithm achieved an impressive accuracy of 99% in detecting vacant and occupied parking spaces. The effectiveness of the system is tested and validated, showcasing its potential to transform parking management in cities.