DriveLaB: A Speeding Reductive Mobile Crowd Sensing Platform
Authors
Rasmussen, Dennis ; Olsen, Thomas Frisk ; Pedersen, Kasper Fromm
Term
4. term
Education
Publication year
2017
Submitted on
2017-06-09
Pages
75
Abstract
Denne rapport præsenterer design, implementering og evaluering af en Mobile Crowd Sensing-platform med fokus på at reducere hastighedsovertrædelser. Mobile Crowd Sensing betyder, at mange brugeres smartphones indsamler data, som systemet kan bruge. Platformen omfatter en klientapp til Android og iOS med funktioner, der skal mindske hastighedsovertrædelser. På serversiden udføres realtids map matching (at matche GPS-spor med vejnettet), beregninger og levering af feedback i realtid. Data lagres i et data warehouse, hvilket gør det muligt at tilbyde et offentligt API med anonymiserede data. Brugere opfordres til at deltage via appen ved at give trafikrelateret feedback, få beregnet kørescorer og deltage i en konkurrencepræget rangliste.
This report presents the design, implementation, and evaluation of a Mobile Crowd Sensing platform aimed at reducing speeding. Mobile Crowd Sensing uses data collected from many users’ smartphones. The platform includes a client app for Android and iOS with features intended to help reduce speeding. On the server side, it performs real-time map matching (aligning GPS traces to the road network), runs data calculations, and provides real-time feedback. Data are stored in a data warehouse, enabling a public API with anonymised data. Users are encouraged to participate through the app by submitting traffic-related feedback, receiving driving scores, and competing on a leaderboard.
[This abstract was generated with the help of AI]
Keywords
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