Parkllite: Satellite-Assisted Real-Time Parking Detection Using LEO Imaging and AI-Based Urban Segmentation

Urban mobility suffers from chronic inefficiencies due to the lack of real-time information on parking availability. Existing systems rely heavily on ground sensors, CCTV networks, or manual user input, all of which fail to scale across large cities or global regions.This paper proposes a satellite-assisted smart parking system that utilizes Low Earth Orbit (LEO) satellite imagery, geospatial AI, and parking slot segmentation models to determine real-time parking availability across cities worldwide. Inspired by an idea conceptualized in 2024, this system aims to deliver a global, infrastructure-free parking detection solution capable of serving smart cities, autonomous vehicles, and future AR-based mobility systems.