Crowdsensing for Public Trasportaion Service

OData support
Supervisor:
Dr. Fehér Gábor
Department of Telecommunications and Media Informatics

Due to the development of mobile technology, crowd-sourced, social smart phone applications which are heavily depending on data collection are getting even more common. The collection can happen in two ways: through the sensors of the device or by manual input of the user. Based on our experience, users do not like to be interrupted by constant interaction during their daily routine. That is the reason why the automation of the data collection process is a substantial requirement, otherwise it leads to a very unpleasant user experience. Today's devices carry a variety of sensors ranging from position- to several types of environment sensors, thus it offers great possibilities which should be taken advantage of.

This project aims to develop Smart City applications, notably in the field of smart public transportation. Our main goal is to create a system, which could extend the basic transportation service by creating online timetables using smartphones as data-collecting agents. Mobile sensors can provide two precious information we can benefit from: the user's location and the user's activity. Thus, evaluating the results, the phases of a traveling session could be observed and tracked on a map. In order the data acquisition to be successful, a substantial amount of participants (data providers) are required. The participation of users needs to be favored, some kind of service needs to be returned in order to keep their interest.

In this paper I would like present the approaches of collecting aforementioned sensory informations on Android platform using the latest developer tools. I detail all the phases of creating the data collecting application. The client application is composed of two main parts: a user-centric timetable application, and a data collector module. These two were developed separately and got integrated into one application in the end. Finally, I would like to share our results and experiences in evaluating collected sensory data and show how can it function as a valuable asset of our Smart Public Transport Service.

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