Compact and Streamlined Transmission of 3D Urban Models: An Enhanced Approach

With the rapid development of 3D urban models, the need for efficient data transmission formats has become paramount. Traditional formats, like CityGML, have been widely used but present challenges in terms of data size and streaming efficiency. This work introduces an innovative format designed to improve the handling and transfer of large-scale 3D city datasets. The proposed method refines the original JSON-based format, offering a more compact and memory-efficient structure tailored for real-time data transmission. By restructuring the data and introducing a sequential, feature-by-feature processing approach, this format significantly reduces memory consumption during data transfer. Additionally, it achieves an approximate 12% improvement in file compression compared to previous implementations. The paper outlines the technical details of the new format and presents an open-source tool for seamless conversion between the traditional format and the optimized structure. Through this approach, we address the growing demand for efficient transmission of extensive urban models, which is crucial for modern smart city applications and real-time urban analysis.