Analysis of Call Detail Records Based on Scilab
Collecting, analyzing and modeling the distribution of the mobility flows is an important factor that enables the optimization of the current transportation infrastructure (vehicle routes, bus and train schedules, etc.) in order to efficiently support the user demand. The analysis of Call Detail Rec...
Main Author: | |
---|---|
Other Authors: | |
Format: | Conference Object |
Language: | English |
Published: |
2015
|
Subjects: | |
Online Access: | https://orbilu.uni.lu/handle/10993/21225 https://orbilu.uni.lu/bitstream/10993/21225/1/ScilabTechFouedMelakessou_Final.pdf |
id |
ftunivluxembourg:oai:orbilu.uni.lu:10993/21225 |
---|---|
record_format |
openpolar |
spelling |
ftunivluxembourg:oai:orbilu.uni.lu:10993/21225 2024-04-21T08:13:08+00:00 Analysis of Call Detail Records Based on Scilab Melakessou, Foued SnT 2015-05-22 https://orbilu.uni.lu/handle/10993/21225 https://orbilu.uni.lu/bitstream/10993/21225/1/ScilabTechFouedMelakessou_Final.pdf en eng http://www.scilabtec.com/ https://orbilu.uni.lu/handle/10993/21225 info:hdl:10993/21225 https://orbilu.uni.lu/bitstream/10993/21225/1/ScilabTechFouedMelakessou_Final.pdf open access http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess SCILABTEC2015, 7th International Scilab Users Conference, Paris, France [FR], from 21-05-2015 to 22-05-2015 Big Data CDR Mobility Graph Engineering computing & technology Computer science Ingénierie informatique & technologie Sciences informatiques conference paper not in proceedings http://purl.org/coar/resource_type/c_18cp info:eu-repo/semantics/conferencePaper 2015 ftunivluxembourg 2024-03-27T14:10:46Z Collecting, analyzing and modeling the distribution of the mobility flows is an important factor that enables the optimization of the current transportation infrastructure (vehicle routes, bus and train schedules, etc.) in order to efficiently support the user demand. The analysis of Call Detail Records has captured the attention of traffic and transportation researchers to optimize people's mobility. We have used Call Detail Record (CDR) datasets, provided by Orange Senegal, combined with demographic data and maps (base stations geolocalization), in order to compute, characterize and identify the mobility flows of Senegalese population. Studies and researches were performed using mobile communication data made available by SONATEL and Orange within the D4D Challenge. Scilab has been the central component of our model analysis platform. Thus we have extracted realistic human mobility models adapted to the Senegal use case. Daily traffic demand profile of each mobile phone base station has been modeled, by considering voice and also messaging activities. The evaluation of mobility models will help to better design and develop future infrastructures in order to better support the actual demand. This facilitates the impact evaluation of efficiency of the transportation services and infrastructure modifications, such as the addition of new roads. We have built mobility maps from CDRs' statistical analysis, based on the Scilab NARVAL toolbox. Mobility patterns have been highlighted, in respect with specific vizualization tools. A classification of each base station has been performed into urban, suburban and rural modes. An algorithm has also been developed in order to detect traffic anomalies, based on the computed daily profiles. The second contribution corresponds to the generation of inter-antenna and inter-district mobility graphs for each month of 2013. This work was supported by the research project named MAMBA that intends to propose and validate a multimodal mobility platform that relies on new Internet ... Conference Object narval narval University of Luxembourg: ORBilu - Open Repository and Bibliography |
institution |
Open Polar |
collection |
University of Luxembourg: ORBilu - Open Repository and Bibliography |
op_collection_id |
ftunivluxembourg |
language |
English |
topic |
Big Data CDR Mobility Graph Engineering computing & technology Computer science Ingénierie informatique & technologie Sciences informatiques |
spellingShingle |
Big Data CDR Mobility Graph Engineering computing & technology Computer science Ingénierie informatique & technologie Sciences informatiques Melakessou, Foued Analysis of Call Detail Records Based on Scilab |
topic_facet |
Big Data CDR Mobility Graph Engineering computing & technology Computer science Ingénierie informatique & technologie Sciences informatiques |
description |
Collecting, analyzing and modeling the distribution of the mobility flows is an important factor that enables the optimization of the current transportation infrastructure (vehicle routes, bus and train schedules, etc.) in order to efficiently support the user demand. The analysis of Call Detail Records has captured the attention of traffic and transportation researchers to optimize people's mobility. We have used Call Detail Record (CDR) datasets, provided by Orange Senegal, combined with demographic data and maps (base stations geolocalization), in order to compute, characterize and identify the mobility flows of Senegalese population. Studies and researches were performed using mobile communication data made available by SONATEL and Orange within the D4D Challenge. Scilab has been the central component of our model analysis platform. Thus we have extracted realistic human mobility models adapted to the Senegal use case. Daily traffic demand profile of each mobile phone base station has been modeled, by considering voice and also messaging activities. The evaluation of mobility models will help to better design and develop future infrastructures in order to better support the actual demand. This facilitates the impact evaluation of efficiency of the transportation services and infrastructure modifications, such as the addition of new roads. We have built mobility maps from CDRs' statistical analysis, based on the Scilab NARVAL toolbox. Mobility patterns have been highlighted, in respect with specific vizualization tools. A classification of each base station has been performed into urban, suburban and rural modes. An algorithm has also been developed in order to detect traffic anomalies, based on the computed daily profiles. The second contribution corresponds to the generation of inter-antenna and inter-district mobility graphs for each month of 2013. This work was supported by the research project named MAMBA that intends to propose and validate a multimodal mobility platform that relies on new Internet ... |
author2 |
SnT |
format |
Conference Object |
author |
Melakessou, Foued |
author_facet |
Melakessou, Foued |
author_sort |
Melakessou, Foued |
title |
Analysis of Call Detail Records Based on Scilab |
title_short |
Analysis of Call Detail Records Based on Scilab |
title_full |
Analysis of Call Detail Records Based on Scilab |
title_fullStr |
Analysis of Call Detail Records Based on Scilab |
title_full_unstemmed |
Analysis of Call Detail Records Based on Scilab |
title_sort |
analysis of call detail records based on scilab |
publishDate |
2015 |
url |
https://orbilu.uni.lu/handle/10993/21225 https://orbilu.uni.lu/bitstream/10993/21225/1/ScilabTechFouedMelakessou_Final.pdf |
genre |
narval narval |
genre_facet |
narval narval |
op_source |
SCILABTEC2015, 7th International Scilab Users Conference, Paris, France [FR], from 21-05-2015 to 22-05-2015 |
op_relation |
http://www.scilabtec.com/ https://orbilu.uni.lu/handle/10993/21225 info:hdl:10993/21225 https://orbilu.uni.lu/bitstream/10993/21225/1/ScilabTechFouedMelakessou_Final.pdf |
op_rights |
open access http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess |
_version_ |
1796933673886416896 |