Traffic congestion and pollution have become frequent issues in cities due to the limited availability of free spaces and the increasing number of cars. This work aims to develop a parking system application to optimize the use of parking spaces in busy areas. The paper examines the technical aspects of the system, including hardware and software components, as well as the user interface and user experience. It uses the Arduino Uno as the controller, proximity and IR sensors, and a servo motor as the actuator. The real-time data logs collected by the sensors are transmitted to a Redis DB. Analytics are performed and displayed on a website to provide insights into parking usage statistics and revenue. A parking occupancy map is shown to the driver to indicate which parking areas are free or occupied. A pre-trained YOLOv3 model integrated with Raspberry Pi is used for real-time vehicle detection, and license plate numbers are extracted using optical character recognition technology. The proposed system has been able to reduce the waiting time for drivers to park their cars, ensure security, and provide analytical insights.