An open, longitudinal, and synthetic dataset of faked virtual humans generated by an optimization approach applied to a real-life call-detail-records-based anonymized database.
The results in this repository are from a manuscript published at the 16th International Conference on Wireless Communications & Mobile Computing (IWCMC 2020).
If you consider using our findings and dataset in your research, please cite our paper:
Sorce (citation)
H. H. Arcolezi, J-F. Couchot, O. Baala, J-M. Contet, B. Al Bouna and X. Xiao, "Mobility modeling through mobile data: generating an optimized and open dataset respecting privacy," 2020 International Wireless Communications and Mobile Computing (IWCMC), Limassol, Cyprus, 2020, pp. 1689-1694, doi: https://doi.org/10.1109/iwcmc48107.2020.9148138.
@inproceedings{Arcolezi2020,
doi = {10.1109/iwcmc48107.2020.9148138},
url = {https://doi.org/10.1109/iwcmc48107.2020.9148138},
year = {2020},
month = jun,
publisher = {IEEE},
author = {Heber H. Arcolezi and Jean-Franeois Couchot and Oumaya Baala and Jean-Michel Contet and Bechara Al Bouna and Xiaokui Xiao},
title = {Mobility modeling through mobile data: generating an optimized and open dataset respecting privacy},
booktitle = {2020 International Wireless Communications and Mobile Computing (IWCMC)}
}
For any question about the dataset, please contact Héber H. Arcolezi: heber.hwang-arcolezi [at] inria.fr
The original database is from a mobile network operator in France (Orange), which collects statistics on the frequency of users on days and union of days through analyzing mobile phone data (i.e., call detail records). The geographical space is the area of an international music festival aka "Festival International de Musique Universitaire" (FIMU), which happened in June 2017 in Belfort town, France. The period of the analysis is 7 days including one day before the FIMU event (31/05/2017), the five days of the festival (01/06/2017 - 05/06/2017), and one day after it (06/06/2017).
With our methodology, we propose a mobility scenario with the frequency of users per day and per the intersection of days. The image below presents a Boolean map for the 7-days with the number of people in each combination of days.
