This deep learning model is designed to detect and classify parking spaces using high-resolution drone and aerial imagery.

With the rise in private vehicle ownership, locating available parking spots has become increasingly difficult, especially in metropolitan areas, resulting in time loss, increased fuel consumption, and elevated vehicular emissions that contribute to urban air pollution. Traditionally, mapping and classifying parking lots is performed manually, a process that is both time-consuming and labour-intensive.

This model automates the detection and classification of parking spots, offering a scalable and efficient alternative. It leverages high-resolution aerial and drone imagery, which provides the necessary spatial and temporal detail to accurately identify and assess parking areas in complex urban environments.