SOURCE-LINKED INTELLIGENCE
KODAMA: Multimodal Digital Twin Reconstruction for Urban RF Propagation Modelling
3D reconstruction typically strives for geometric fidelity or visual plausibility. Radio frequency digital twins (RFDT) are instead judged by whether communication channels behave in them as they do in the real world. RFDTs promise site-specific channel prediction but current practice forces a choice between coarse automated scenes and hand-built, measurement-calibrated models that take weeks to construct per-site. We present KODAMA, an automated pipeline that reconstructs ray tracing-ready RFDTs at city scale from off-the-shelf geospatial data alone: aerial imagery, LiDAR, and photogrammetry
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-07T10:16:44.000Z
First collected: 2026-09-20T20:52:10.320Z. This is not the publication date.