[en] The analysis of Call Detail Records has captured the attention of traffic and transportation researchers to optimize people's mobility. In our work, we would like to analyze Call Detail Records in order to extract realistic human mobility models adapted to the Senegal use case. In this paper, we describe our analysis of the available D4D datasets. The first contribution is the modeling of the daily traffic demand profile of each antenna, by considering voice and short message services. The evaluation of mobility models will help to better design and develop future infrastructures in order to better support the actual demand. A classification has been performed into urban, suburban and rural modes. An algorithm has been developed to detect traffic anomalies in 2013, based on the daily profiles. The second contribution corresponds to the generation of inter-antennas and inter-arrondissements mobility graphs for each month of 2013.
Research center :
SnT
Disciplines :
Computer science
Author, co-author :
Melakessou, Foued ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Derrmann, Thierry ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Frank, Raphaël ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Castignani, German ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Engel, Thomas ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
External co-authors :
no
Language :
English
Title :
Detection of Population Mobility Anomalies in Senegal from Base Station Profiles
Publication date :
08 April 2015
Number of pages :
20
Event name :
Netmob'15, the main conference on the scientific analysis of mobile phone datasets