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Article
Quality of Information in Mobile Crowdsensing: Survey and Research Challenges
ACM Transactions on Sensor Networks
  • Francesco Restuccia
  • Nirnay Ghosh
  • Shameek Bhattacharjee
  • Sajal K. Das, Missouri University of Science and Technology
  • Tommaso Melodia
Abstract

Smartphones have become the most pervasive devices in people's lives and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as an accelerometer, a gyroscope, a microphone, and a camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this article, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing and analyze in depth the current state of the art on the topic. We also outline novel research challenges, along with possible directions of future work.

Department(s)
Computer Science
Research Center/Lab(s)
Intelligent Systems Center
Comments
This work is partially supported by the NSF, under grants CNS-1545037, CNS-1545050, DGE-1433659, and IIS-1404673.
Keywords and Phrases
  • Air pollution control,
  • Image quality,
  • Noise pollution,
  • Pollution control,
  • Smartphones,
  • Surveying,
  • Challenges,
  • Framework,
  • Information,
  • Reputation,
  • Trust,
  • Truth discovery,
  • Surveys,
  • Quality
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 Association for Computing Machinery (ACM), All rights reserved.
Publication Date
11-1-2017
Disciplines
Citation Information
Francesco Restuccia, Nirnay Ghosh, Shameek Bhattacharjee, Sajal K. Das, et al.. "Quality of Information in Mobile Crowdsensing: Survey and Research Challenges" ACM Transactions on Sensor Networks Vol. 13 Iss. 4 (2017) ISSN: 1550-4859; 1550-4867
Available at: http://works.bepress.com/sajal-das/103/