Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
9-2016
Abstract
By effectively utilizing smartphones to reach out and engage a large population of mobile users, mobile crowdsourcing can become a game-changer for many urban operations, such as last mile logistics and municipal monitoring. To overcome the uncertainties and risks associated with a purely best-effort, opportunistic model of such crowdsourcing, we advocate a more centrally-coordinated approach, that (a) takes into account the predicted movement paths of workers and (b) factors in typical human behavioral responses to various incentives and deadlines. To experimentally tackle these challenges, we design, develop and experiment with a real-world mobile crowd-Tasking platform on an urban campus in Singapore. In this paper, we first introduce TAKer and then demonstrate the effectiveness of different behavioral experiments, such as bundling and differential task pricing methods.
Keywords
mobile, crowdsourcing, context-aware, bundles, incentives, cheating, smart-campus, social-ties, collaboration
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp; Heidelberg; Germany; 2016 September 12-16
First Page
297
Last Page
300
ISBN
9781450344623
Identifier
10.1145/2968219.2971388
Publisher
ACM
City or Country
New York
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/2968219.2971388