Dataset for: Unleashing the Power of UWB for Indoor Mobility Analytics: A Museum Case Study

Overview This dataset contains fine-grained indoor mobility data collected using Ultra-Wideband (UWB) positioning technology in a real museum environment. It includes both raw trajectories and processed semantic data describing visitor behavior such as stops, peeks, and visits to points of interest (POIs). The dataset was collected over a 3-month campaign, tracking more than 1500 visitors and generating millions of positioning samples, enabling detailed analysis of visitor movement and engagement. For more details please refer to the paper: D. Vecchia, F. Hachem, D. Molteni, M.L. Damiani, G.P. Picco. “Unleashing the Power of UWB for Indoor Mobility Analytics: A Museum Case Study”. Data Science and Engineering -DSEJ. 2026. Dataset Structure The dataset is provided as multiple CSV files. For a detailed description about the fields of each CSV, please refer to the README file. 1. trajectories.csv UWB trajectories representing visitor movement over time. 2. stops_and_peeks.csv Processed data capturing stops and their association to nearby POIs (if any). 3. visits.csv A visit aggregates one or more consecutive peeks to the same POI. 4. exhibits.csv Data describing museum exhibits (POIs). 5. furnitures.csv The spatial objects present in the environment (e.g., furniture, tables). Privacy and Ethics All data is fully anonymized No personal or identifying information is included Participation was voluntary with informed consent Citation If you use this dataset, please cite: D. Vecchia, F. Hachem, D. Molteni, M.L. Damiani, G.P. Picco. “Unleashing the Power of UWB for Indoor Mobility Analytics: A Museum Case Study”. Data Science and Engineering -DSEJ. 2026. Contact For questions or collaboration inquiries, please contact the dataset authors. Acknowledgment This work is partially supported by the Italian government via the NG-UWB project (MIUR PRIN 2017) and by project SERICS (PE00000014) under the NRRP MUR program funded by the EU-NGEU.