Towards Mobile Sensor-aware Crowdsourcing: Architecture, Opportunities and Challenges
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. © 2014 Springer-Verlag Berlin Heidelberg.
Recommended Citation
J. He et al., "Towards Mobile Sensor-aware Crowdsourcing: Architecture, Opportunities and Challenges," Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8505 LNCS, pp. 403 - 412, Springer, Jan 2014.
The definitive version is available at https://doi.org/10.1007/978-3-662-43984-5_31
Department(s)
Computer Science
Keywords and Phrases
Location-aware crowdsourcing; Mobile platforms; Sensor-enabled crowdsourcing
International Standard Book Number (ISBN)
978-366243983-8
International Standard Serial Number (ISSN)
1611-3349; 0302-9743
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Springer, All rights reserved.
Publication Date
01 Jan 2014
