A Predictive AI and IoT-Based Smart Parking and Vehicle Tracking Framework for Urban Mobility

Rapid urbanization and increasing vehicle density have intensified the challenges of effective parking management in modern cities. Conventional parking systems often lack automation, predictive capabilities, and real-time visibility. This study presents a unified AI and IoT-based Smart Parking and Vehicle Tracking Framework designed to optimize parking space utilization and improve user convenience. The system leverages IoT sensors for real-time data acquisition, machine learning models for predictive analysis, and a web interface for interactive user access. The proposed framework enhances parking efficiency, minimizes traffic congestion, and contributes to sustainable urban mobility through data-driven decision-making.