DriveLaB: A Speeding Reductive Mobile Crowd Sensing Platform
Student thesis: Master thesis (including HD thesis)
- Dennis Rasmussen
- Thomas Frisk Olsen
- Kasper Fromm Pedersen
4. term, Computer Science (IT), Master (Master Programme)
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.
Language | English |
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Publication date | 9 Jun 2017 |
Number of pages | 75 |