Reference : Detection of Population Mobility Anomalies in Senegal from Base Station Profiles

	Document type :	Scientific congresses, symposiums and conference proceedings : Unpublished conference
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/21223

Title :	Detection of Population Mobility Anomalies in Senegal from Base Station Profiles
Language :	English
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) >]
Publication date :	8-Apr-2015
Number of pages :	20
Peer reviewed :	Yes
Audience :	International
Event name :	Netmob'15, the main conference on the scientific analysis of mobile phone datasets
Event date :	from 7-04-2015 to 10-04-2015
Event organizer :	MIT Media Lab
Event place (city) :	Boston
Event country :	USA
Keywords :	[en] D4D Challenge ; Big Data ; Mobility Graph
Abstract :	[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 centres :	SnT
Funders :	Fonds National de la Recherche - FnR
Name of the research project :	R-AGR-0476-1 > C13/IS/5825301 MAMBA > 01/04/2014 - 31/03/2017 > ENGEL Thomas
Target :	Researchers ; Professionals ; Students ; General public
Permalink :	http://hdl.handle.net/10993/21223
Other URL :	http://netmob.org/

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