Over the past few years, there has been an increasing demand for crowd sensing applications. While existing mobile app designers greatly facilitate the development of crowd sensing applications for non-ICT experts, they do not yet provide technological support for other aspects required to manage crowd sensing applications, such as support for data gathering campaigns, advanced forms of data aggregation, and participant coordination. In this paper, we present DisCoPar, a novel platform for designing crowd sensing applications, which utilises a distributed flow-based programming approach to facilitate the development of mobile applications and their matching server-side logic. The data-driven nature of our approach enables users to contribute data and receive feedback in real-time, which greatly facilitates user collaboration. We demonstrate the features of our prototype platform by creating a noise measuring application with a corresponding collaborative data collection campaign.
Original languageEnglish
Title of host publication2016 IEEE International Conference on Mobile Services (MS)
Number of pages8
ISBN (Electronic)978-1-5090-2625-8
ISBN (Print)978-1-5090-2626-5
Publication statusPublished - 19 Dec 2016
Event2016 IEEE International Conference on Mobile Services - San Francisco, United States
Duration: 27 Jun 20162 Jul 2016


Conference2016 IEEE International Conference on Mobile Services
Abbreviated titleMS
CountryUnited States
CitySan Francisco
Internet address

    Research areas

  • End-User Design, Crowd Sensing, Mobile Applications, Flow-based Programming, Citizen Observatory

ID: 30248601