Project Group: Participation Incentives for Location-based Crowd Sourcing Applications

The goal of the FAIR project is to improve weather forecasts computed by the DWD using crowdsourced temperature measurements collected by volunteers. As basis for the large-scale collection of temperature measurements, the participants of the project group CST (Crowd Sourcing of  Temperature Data, Winter Term 2019/20) have developed a mobile application for Android and iOS as well as a web application with an associated backend service (https://www.mowesta.com).

The goal of this project group is the design, implementation, and validation of strategies to incentivize new and existing users to participate in the crowd sourcing process. Some example strategies may include but are not limited to:

  • Removing obstacles for participation, e.g., by providing fine-grained control over the data collection performed by the mobile applications to improve the user’s privacy.
  • Extending data access and usefulness, e.g., by providing integrations with existing services such as Amazon’s Alexa or If-This-Than-That.
  • Improving the motivation of participants, e.g., by gamifying the data collection process with achievements, rankings, etc.

The participants of the project group are free to design and realize other ideas depending on their interests. However, since the groups result shall be tightly integrated into the existing system, some technical aspects such as the programming language and frameworks cannot be adapted easily. Specifically, the group will be using J2EE to extend the backend, the Android SDK and iOS SDK to extend the mobile applications and Angular to extend the web application. Tutorials for these technologies will be held during the first weeks of the project.

From a theoretical perspective, the project group covers fundamental concepts related to the development of location-based services in theory and practice. This includes basic models, algorithms, data structures and applications. In addition, the participants will prepare individual seminar talks and papers on selected research topics related to crowd sensing as well as the processing of temperature and location information.

The admission to this course is managed centrally. If you have any questions, please contact marcus.handte@uni-due.de.