A master thesis from Aalborg University
DriveLaB: A Speeding Reductive Mobile Crowd Sensing Platform
Author(s)
Term
4. term
Education
Publication year
2017
Submitted on
2017-06-09
Pages
75 pages
Abstract
I denne rapport udformes, implementeres og evalueres en hastighedsreducerende Mobile Crowd Sensing-platform. Platformen indeholder en klientapplikation tilgængelig til Android og iOS med hastighedsreducerende foranstaltninger indarbejdet. Serveren udfører realtids kortlægning, databeregninger og giver feedback i realtid. Dataene gemmes i et datalager, der gør det muligt for platformen at tilbyde en offentlig API med anonymiserede data. Brugere opfordres til at deltage gennem klientprogrammet ved at tilbyde trafikrelateret feedback, beregne kørselsresultater og vise et konkurrencedygtigt leaderboard.
In this report, a speeding reductive Mobile Crowd Sensing platform is designed, implemented and evaluated. The platform includes a client application available for Android and iOS with speeding reductive measures incorporated. The server performs real-time map matching, data calculations, and provides real-time feedback. The data is stored in a data warehouse which enables the platform to offer a public API with anonymised data. Users are encouraged to participate through the client application by offering traffic related feedback, calculate driving scores and displaying a competitive leaderboard.
Keywords
Documents
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