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.
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https://hal.inria.fr/hal-01206622
Contributor : Georgios Bouloukakis <>
Submitted on : Wednesday, September 30, 2015 - 11:30:03 AM
Last modification on : Friday, May 25, 2018 - 12:02:07 PM
Document(s) archivé(s) le : Thursday, December 31, 2015 - 10:16:35 AM

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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⟩

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