DeteClass: a Car Classification for Parking System Management

An efficient and well-organized parking system is crucial in a modern shopping center. Crowded and unorganized parking management can make customers hesitant to go to a shopping center, thus leading to lost revenues. However, the growth of vehicles and rapid urbanization has created a challenge in parking management. DeteClass aims to implement Automated Car Classification in a Parking Management System to improve the efficiency of parking management in shopping centers. Utilizing computer vision technology to detect incoming vehicles and machine learning to categorize them correctly, then assign them to the best possible parking spot for each vehicle class. DeteClass will streamline the process of customer parking, monitor the parking slot availability, and implement fair and smart parking fees. Based on the experimental results, the proposed system has 68.4%, 69.09%, 97.44%, and 80.51% for its accuracy, precision, recall, and F1-Score, respectively. On the other hand, the applications that support the proposed system also work successfully according to the functional testing that has been conducted.