Next Article in Journal
On the Acoustic Filtering of the Pipe and Sensor in a Buried Plastic Water Pipe and its Effect on Leak Detection: An Experimental Investigation
Previous Article in Journal
Estimates of Minor Ocean Tide Loading Displacement and Its Impact on Continuous GPS Coordinate Time Series
Sensors 2014, 14(3), 5573-5594; doi:10.3390/s140305573

Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing Systems

1,* , 2
Received: 13 December 2013 / Revised: 20 January 2014 / Accepted: 10 March 2014 / Published: 20 March 2014
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [666 KB, 21 June 2014; original version 21 June 2014]   |   Browse Figures


The ubiquity of mobile devices brings forth a sensing paradigm, participatory sensing, to collect and interpret sensory information from the environment. Participants join in multifarious sensing tasks and share their data. The sensing result can be obtained in light of shared data. It is not uncommon that some corrupted data is provided by participants, which makes sensing result unreliable accordingly. To address this nontrivial issue, we proposed the accumulated reputation model (ARM) to improve the accuracy of the sensing result. In ARM, participants’ reputation will be computed and accumulated based on their sensing data. The sensing data from reputable participants make higher contributions to the sensing result. ARM performs well on calculating accurate sensing results, even in extreme scenarios, where there are many inexperienced or malicious participants.
Keywords: participatory sensing; reputation; contribution; data quality participatory sensing; reputation; contribution; data quality
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
MDPI and ACS Style

Yu, R.; Liu, R.; Wang, X.; Cao, J. Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing Systems. Sensors 2014, 14, 5573-5594.

View more citation formats

Related Articles

Article Metrics

For more information on the journal, click here


Cited By

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert