Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4957548 | Pervasive and Mobile Computing | 2017 | 18 Pages |
Abstract
We address the problem of estimating the population density from mobile phone data. After critically examining the relevant network-based data sources (CDR, VLR and passive monitoring systems) a novel methodology is presented with two key novelties. First, it enables the fusion of cell-level and Location Area-level data from heterogeneous data sources. Second, it considers a novel tessellation scheme based on cell coverage maps, instead of cell tower locations. Furthermore, it allows to integrate data from different network operators onto a common reference grid. Within the proposed framework, a Maximum-Likelihood formulation for the population density estimation problem is developed and tested via simulations, showing a significant gain over existing Voronoi-based schemes.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Fabio Ricciato, Peter Widhalm, Francesco Pantisano, Massimo Craglia,