Abstract
The recent success of general purpose crowdsourcing platforms like Amazon Mechanical Turk paved the way for a plethora of crowd-enabled applications and workflows. However, the variety of tasks which can be approached via such crowdsourcing platforms is limited by constraints of the web-based interface. In this paper, we propose mobile user interface clients. Switching to mobile clients has the potential to radically change the way crowdsourcing is performed, and allows for a new breed of crowdsourcing tasks. Here, especially the ability to tap into the wealth of precision sensors embedded in modern mobile hardware is a game changer. In this paper, we will discuss opportunities and challenges resulting from such a platform, and discuss a reference architecture.
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He, J., Kunze, K., Lofi, C., Madria, S.K., Sigg, S. (2014). Towards Mobile Sensor-Aware Crowdsourcing: Architecture, Opportunities and Challenges. In: Han, WS., Lee, M., Muliantara, A., Sanjaya, N., Thalheim, B., Zhou, S. (eds) Database Systems for Advanced Applications. DASFAA 2014. Lecture Notes in Computer Science(), vol 8505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43984-5_31
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DOI: https://doi.org/10.1007/978-3-662-43984-5_31
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