Towards mobile sensor-aware crowdsourcing: Architecture, opportunities and challenges

Jiyin He, Kai Kunze, Christoph Lofi, Sanjay K. Madria, Stephan Sigg

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 19th International Conference, DASFAA 2014, International Workshops
Subtitle of host publicationBDMA, DaMEN, SIM3, UnCrowd, Revised Selected Papers
PublisherSpringer Verlag
Pages403-412
Number of pages10
ISBN (Print)9783662439838
DOIs
Publication statusPublished - 2014
Event19th International Conference on Database Systems for Advanced Applications, DASFAA 2014 - Bali, Indonesia
Duration: 2014 Apr 212014 Apr 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8505 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other19th International Conference on Database Systems for Advanced Applications, DASFAA 2014
CountryIndonesia
CityBali
Period14/4/2114/4/24

Keywords

  • Location-aware crowdsourcing
  • Mobile platforms
  • Sensor-enabled crowdsourcing

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    He, J., Kunze, K., Lofi, C., Madria, S. K., & Sigg, S. (2014). Towards mobile sensor-aware crowdsourcing: Architecture, opportunities and challenges. In Database Systems for Advanced Applications - 19th International Conference, DASFAA 2014, International Workshops: BDMA, DaMEN, SIM3, UnCrowd, Revised Selected Papers (pp. 403-412). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8505 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-662-43984-5_31