Publication Type

Conference Proceeding Article

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

Bundles, Cheating, Collaboration, Context-Aware, Crowdsourcing, Incentives, Mobile, Smart-Campus, Social-Ties

Discipline

Computer Sciences | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct: Heidelberg, Germany, September 12-16, 2016

First Page

297

Last Page

300

ISBN

9781450344623

Identifier

10.1145/2968219.2971388

Publisher

ACM

City or Country

New York

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1145/2968219.2971388

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