Paper Info
Title
The Curse of Sensing: Survey of techniques and challenges to cope with sparse and dense data in mobile crowd sensing for Internet of Things.
Abstract
In this paper we present a survey on mobile crowdsensing (MCS) techniques that have been developed to address the Curse of Sensing problem i.e. propensity of MCS applications to generate sparse or dense data that can lead to significant gaps in the extracted knowledge. In order to do so, we identify features, based on the terminologies used in the literature, in order to develop a clear classifications among MCS and crowdsourcing applications and methods. Subsequently, we propose a taxonomy outlining both factors and objectives that need to be considered in designing MCS systems and have a direct impact on MCS applications’ tendency to fall into the Curse of Sensing. We then evaluate the majority of the research proposed in the field of MCS and addressing the Curse of Sensing problem with reference to the proposed taxonomy. Finally, we highlight the existing gaps in the literature and possible directions for future research.
Year
DOI
Venue
2018
10.1016/j.pmcj.2018.06.009
Pervasive and Mobile Computing
Keywords
Field
DocType
Internet of Things (IoT),Mobile crowdsensing (MCS),Context awareness,The curse of sensing
Data science,Crowdsensing,Crowdsourcing,Computer science,Internet of Things,Curse,Context awareness,Distributed computing
Journal
Volume
ISSN
Citations 
49
1574-1192
1
PageRank 
References 
Authors
0.35
18
5
Name
Order
Citations
PageRank
Federico Montori1549.22
Prem Prakash Jayaraman237844.66
Yavari, A.321.37
Alireza Hassani4114.37
Dimitrios Georgakopoulos52554580.54