Ultra-wideband (UWB) radios enable decimeter-level positioning. This is posited to unlock unprecedented sophistication and detail in indoor mobility analytics. However, to date industry and academia have resorted to primitive analyses based only on raw trajectories, unable to ascertain where individuals stop and for how long, crucial in many domains. Among these is the museum providing the real-world context and dataset for this paper. We deployed a UWB localization system in a area containing 42 exhibits and track more than 1500 visitors over a 3 months period. We confirm that commonplace analyses relying on UWB trajectories alone offer practical insights, yet cannot capture the two key dimensions above. Instead, we exploit state-of-the-art techniques to extract higher-level semantic trajectories directly capturing visitor behavior, and distill a multitude of detailed, multi-layered, actionable insights. Our experience concretely highlights the untapped, disruptive potential of UWB-based mobility analytics—and a way to seize it. To foster further research, in museums and beyond, we publicly release our large UWB dataset (more than 9 million positions) along with the one resulting from our higher-level analyses.
Unleashing the Power of UWB for Indoor Mobility Analytics: A Museum Case Study / D. Vecchia, F.H.. - In: DATA SCIENCE AND ENGINEERING. - ISSN 2364-1185. - (2026). [Epub ahead of print] [10.1007/s41019-026-00358-6]
Unleashing the Power of UWB for Indoor Mobility Analytics: A Museum Case Study
F. HachemSecondo
;M.L. DamianiPenultimo
;
2026
Abstract
Ultra-wideband (UWB) radios enable decimeter-level positioning. This is posited to unlock unprecedented sophistication and detail in indoor mobility analytics. However, to date industry and academia have resorted to primitive analyses based only on raw trajectories, unable to ascertain where individuals stop and for how long, crucial in many domains. Among these is the museum providing the real-world context and dataset for this paper. We deployed a UWB localization system in a area containing 42 exhibits and track more than 1500 visitors over a 3 months period. We confirm that commonplace analyses relying on UWB trajectories alone offer practical insights, yet cannot capture the two key dimensions above. Instead, we exploit state-of-the-art techniques to extract higher-level semantic trajectories directly capturing visitor behavior, and distill a multitude of detailed, multi-layered, actionable insights. Our experience concretely highlights the untapped, disruptive potential of UWB-based mobility analytics—and a way to seize it. To foster further research, in museums and beyond, we publicly release our large UWB dataset (more than 9 million positions) along with the one resulting from our higher-level analyses.| File | Dimensione | Formato | |
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