Pengembangan Sistem Visualisasi 3D Berbasis Web Menggunakan Data LiDAR dari iPhone 17 Pro

Abstract

This study develops a web-based 3D visualization system for a public wall mural captured using the LiDAR sensor of the iPhone 17 Pro. The workflow includes data acquisition, point cloud and mesh generation, conversion to glTF, packaging into 3D Tiles, semantic metadata integration, and interactive web visualization. The dataset contains 6,079,580 XYZRGB points with a local spatial extent of approximately 40.24 m × 5.93 m × 35.61 m. The reconstructed glTF model consists of 801,949 vertices and about 1,372,979 triangles, while the final 3D Tiles package uses implicit octree tiling with 89 GLB tiles across five levels. Results show that the conversion pipeline significantly improves web readiness, reducing data size by about 93.33% from raw XYZRGB to the final 3D Tiles package. External JSON-based metadata also supports dataset description and semantic grouping within the viewer. The novelty of this study lies in the end-to-end integration of low-cost mobile LiDAR acquisition, web-oriented geometric optimization, implicit tiling, and semantic 3D publication for documenting public art. These findings demonstrate that smartphone-based LiDAR can provide a practical and low-cost solution for 3D digitization and web publication of mural objects.