Maria Luisa Damiani
Representation, protection, analysis of mobility data. Mobility data grasp the movement of entities , e.g. humans, animals, assets, in a reference space, opening up to the analysis of individual and collective behavior . Focus on:
mobility pattern conceptualization and analysis
mobility data modeling
location privacy and location-based access control
applications in: animal ecology, museums, geologya
Paper @ IEEE Percom 2022. Fine-grained stop detection in UWB-based trajectories, F. Hachem, D. Vecchia, M.L. Damiani, G.P. Picco. Teaser @ https://www.youtube.com/watch?Paper v=8ZNcMFzp0AI.
Abstract: Ultra-wideband (UWB) localization enables user tracking with high spatio-temporal resolution, whose exploitation for detecting higher-level mobility patterns is largely unexplored. We study whether i) existing detection techniques, developed for coarser-grained localization, apply also to UWB trajectories, and ii) the quantitative extent to which this enables finer-grained analyses. We focus on the well-known stop-move pattern, and offer a concrete use case of capturing visits in a real museum. We contribute a novel metric suited to the high UWB spatio-temporal resolution and use it to evaluate representative techniques. We deploy a UWB system in a 25x15 m2 museum area and base our analysis on 70000+ positions and 200+ ground-truth stops. These are very close in space and time, yet results confirm very accurate spatio-temporal estimation in the vast majority of cases.
Project MUR Prin : NG-UWB : Next-generation Ultra-wideband Localization and Communication for the Internet of Things [Sept 2019- Feb 2023]
Workshop co-chair @ ACM SIGSPATIAL 2022: https://sigspatial2022.sigspatial.org/org/
Advanced Seminars co-chair @ IEEE MDM 2022: https://mdm2022.cs.ucy.ac.cy/
Member of the Executive Committee @ ACM Special Interest Group on Spatial Information : https://www.sigspatial.org/.