In the pursuit of modernizing urban infrastructure, the creation of an automated car parking system stands as a pivotal development. This technical article delves into the intricate details of building a Smart Car Parking System that seamlessly integrates license plate detection at the entrance and real-time monitoring for parking violations using the sophisticated YOLOv4 model. The technical prerequisites for this endeavour encompass a robust hardware setup, including a powerful GPU for accelerated model inference and strategically positioned cameras both at the entrance and within the parking area. The software stack involves a Python environment with essential packages such as NumPy, OpenCV, TensorFlow, and a YOLOv4 model fine-tuned on a dataset containing annotated images of license plates.