Journal article
Compressive sensing based data quality improvement for crowd-sensing applications
Abstract
Crowd-sensing enables to collect a vast amount of data from the crowd by allowing a wide variety of sources to contribute data. However, the openness of crowd-sensing exposes the system to malicious and erroneous participations, inevitably resulting in poor data quality. This brings forth an important issue of false data detection and correction in crowd-sensing. Furthermore, data collected by participants normally include considerable missing …
Authors
Cheng L; Niu J; Kong L; Luo C; Gu Y; He W; Das SK
Journal
Journal of Network and Computer Applications, Vol. 77, , pp. 123–134
Publisher
Elsevier
Publication Date
January 2017
DOI
10.1016/j.jnca.2016.10.004
ISSN
1084-8045