We are interested in location data (mobility traces) from mobile systems formed by a group of users, to understand how to develop reliable algorithms on such systems. We have thus developed the Souk[1] position capture and analysis platform. Souk captures the precise location (approx. 15cm) of a group of individuals (approx. 60 people) with good temporal resolution (130 points/second), using UWB (Ultra-Wide-Band) radio technology. This data can be used in a number of ways. Firstly, they can be used to represent the communication networks of distributed systems carried by humans via their smartphones, enabling us to test the classic mobility models on which many distributed applications are based. A second use concerns the characterization of co-location attacks in the context of the Internet of Things[2]. Finally, we are exploiting this data from a more theoretical perspective as a dynamic graph[3].

This platform is the basis for a number of interdisciplinary exploratory projects. One series of projects focuses on the study of collective decision-making processes (Deploiements de Souk) and is being carried out in conjunction with the Laboratoire de Physique Théorique - LPT (Clément Sire) and the Centre de Recherche sur la Cognition Animale - CRCA (Guy Theraulaz).This platform is also an innovative means of popularization, enabling us to approach the public by making the recurring object of our work - interaction structures - visible and tangible (LAAS Open House, Forum CNRS Toulouse 2018, Festival Novela, etc.).It has also given rise to an art&sciences collaboration (with R. Sultra and M.Barthélémy; Retina/Pictonique exhibition, Cemes 2018) that questions the self-organizing capacities of human groups.

[1] Killijian M.-O., Pasqua R., Roy M., Tredan, G., Zanon C., Souk: Spatial Observation of hUman Kinetics, Computer Networks, Elsevier, 2016.

[2] Pasqua R.,  Roy M., Tredan G., Loca: A Location-Oblivious Co-location Attack in Crowds Detection, ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp 2016), 2016

[3] Pignolet Y-M., Roy M., Schmid S., Tredan G. The many faces of graph dynamics. Journal of Statistical Mechanics: Theory and Experiment, Volume 2017.