Improving public transportation through crowd-sourcing

Abstract

Commuting on roads in densely populated cities of the developing world is fraught with high delays and uncertainties. Wide use of public transportation can ease the load on the road infrastructure, but such use is not convenient, partly due to the unpredictable nature. In this work, our goal is to improve the usability of public transportation, through better information. Such information can lead to better planning and predictability for commuters. We take a crowd-sourced approach where information about transportation units as well as road conditions is crowd-sourced from commuters. The information is then processed and made available to other commuters. In this context, this paper presents a naming framework we have developed, which will enable flexible and scalable content-driven data gathering and dissemination. Based on a preliminary implementation of the framework, we present various field-experiment results which shed light on the practicality of the proposed approach as well as on technical issues which need further careful addressing.