Implementation of Smart Parking Using the Internet of Things and Artificial Intelligence

This paper presents the implementation of a smart parking system using the Internet of Things and artificial intelligence to enhance the efficiency and management of urban parking systems. The focus is on analyzing the potential to provide better services to drivers and optimize resources in urban environments. Through the development of an application implemented using the Python programming language for vehicle recognition and tracking of available and occupied parking spaces from video footage, the system enables fast and precise analysis of the available data. The data is analyzed using artificial intelligence-based technologies. The information resulting from the Python programming language processing is stored in a PostgreSQL database, providing the necessary data for management and analysis. For users, a web application has been implemented, allowing them to track available parking spaces on a map and access video frames from the parking area. The web application is designed to provide parking control services with better insights into the parking facilities. In parallel, Android and iOS applications have been developed, providing users with navigation to selected parking areas.