A NEW SMART PARKING AND VEHICLE OCCUPANCY

Abstract

The rapid growth of urbanization and the increasing number of vehicles have resulted in severe parking management challenges in metropolitan and smart city environments. Conventional parking systems rely on manual monitoring and static signage, which often leads to traffic congestion, increased fuel consumption, and time wastage. In recent years, smart city initiatives and advancements in Internet of Things (IoT), computer vision, and data analytics have enabled the development of intelligent parking management solutions. This project proposes a Smart Parking and Vehicle Occupancy System that provides real-time monitoring and efficient management of parking spaces.The proposed system utilizes sensors and/or camera-based computer vision techniques to detect vehicle presence in parking slots. Vehicle occupancy data is collected and processed using a centralized processing unit, where slot availability is determined accurately. The system supports real-time updates, allowing drivers to quickly identify available parking spaces, thereby reducing unnecessary circulation within parking areas.The system architecture integrates data acquisition modules, occupancy detection algorithms, communication layers, and a user interface. Occupancy data is transmitted to a server and displayed through a web or mobile application, enabling both users and parking administrators to monitor parking status. The system may also include automated entry and exit tracking, reservation functionality, and alert notifications to enhance user experience.Extensive testing and evaluation are conducted to analyze system accuracy, response time, and reliability. The results demonstrate that automated vehicle occupancy detection significantly improves parking efficiency and reduces congestion compared to traditional parking systems. The proposed system also contributes to reduced carbon emissions by minimizing idle driving time.