Towards Mobile Social Crowd-Sensing for Transport Information Management

Abstract : Transport in Senegal is chaotic and large, especially in main cities. Additionally, although most people have mobile phones, large part of them still rely on SMS. Considering this, we propose the development of an application platform for large-scale transport information management relying on ‘mobile social crowd-sensing’. To support this platform, we model a large-scale mobile publish/subscribe system using queuing theory. We develop MobileJINQS simulator that uses D4D data for parameterization.
Type de document :
Poster
NetMob, Data for Development (D4D) Challenge, Apr 2015, MIT Media Lab, United States. 2015
Liste complète des métadonnées

https://hal.inria.fr/hal-01206622
Contributeur : Georgios Bouloukakis <>
Soumis le : mercredi 30 septembre 2015 - 11:30:03
Dernière modification le : vendredi 25 mai 2018 - 12:02:07
Document(s) archivé(s) le : jeudi 31 décembre 2015 - 10:16:35

Fichier

D4D_Senegal_A0_poster.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01206622, version 1

Collections

Citation

Georgios Bouloukakis, Nikolaos Georgantas, Rachit Agarwal, Animesh Pathak, Valerie Issarny. Towards Mobile Social Crowd-Sensing for Transport Information Management. NetMob, Data for Development (D4D) Challenge, Apr 2015, MIT Media Lab, United States. 2015. 〈hal-01206622〉

Partager

Métriques

Consultations de la notice

189

Téléchargements de fichiers

84