Sniffer deployment in urban area for human trajectory reconstruction and contact tracing

To study the propagation of information from individual to individual, we need mobility datasets. Existing datasets are not satisfactory because they are too small, inaccurate or target a homogeneous subset of population. To draw valid conclusions, we need sufficiently large and heterogeneous datasets. Thus we aim for a passive non-intrusive data collection method, based on sniffers that are to be deployed at some well-chosen street intersections. To this end, we need optimization techniques for efficient placement of sniffers. We introduce a heuristic, based on graph theory notions like the vertex cover problem along with graph centrality measures.