Results 231 to 240 of about 4,878 (281)

4W1H in mobile crowd sensing [PDF]

open access: yesIEEE Communications Magazine, 2014
With the rapid proliferation of sensor-rich smartphones, mobile crowd sensing has become a popular research field. In this article, we propose a four-stage life cycle (i.e., task creation, task assignment, individual task execution, and crowd data integration) to characterize the mobile crowd sensing process, and use 4W1H (i.e., what, when, where, who,
Daqing Zhang, Leye Wang, Haoyi Xiong
exaly   +3 more sources

Incentives for Mobile Crowd Sensing: A Survey

IEEE Communications Surveys and Tutorials, 2016
Recent years have witnessed the fast proliferation of mobile devices (e.g., smartphones and wearable devices) in people's lives. In addition, these devices possess powerful computation and communication capabilities and are equipped with various built-in functional sensors.
Xinglin Zhang, Zheng Yang, Yunhao Liu
exaly   +3 more sources

Quantifying sensing quality of crowd sensing networks with confidence interval [PDF]

open access: yes2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), 2017
Quantifying sensing quality is fundamentally important for crowd sensing networks. Existing works which focus on quantifying the sensing quality of individual user are not applicable for that of the overall crowd sensing networks. However, it is nontrivial to quantify the sensing quality of crowd sensing networks for two main challenges.
Chaocan Xiang   +3 more
openaire   +2 more sources

APISENSE: Crowd-Sensing Made Easy. [PDF]

open access: yesERCIM News, 2013
The rapid emergence of mobile devices, such as TabletPC and smartphones, equipped with a rich array of sensors, enables a new means of acquiring sensor data, known as crowd-sensing. Crowd-sensing is currently receiving a lot of attention, not only from industry but also from various research communities interested in collecting a new class of data over
Haderer, Nicolas   +3 more
core   +5 more sources

Compressive sensing based data quality improvement for crowd-sensing applications [PDF]

open access: yesJournal of Network and Computer Applications, 2017
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 ...
long cheng   +2 more
exaly   +2 more sources

Secure crowd-sensing protocol for fog-based vehicular cloud [PDF]

open access: yesFuture Generation Computer Systems, 2021
The new paradigm of fog computing was extended from conventional cloud computing to provide computing and storage capabilities at the edge of the network. Applied to vehicular networks, fog-enabled vehicular computing is expected to become a core feature
Lewis Nkenyereye   +2 more
exaly   +1 more source

Opportunities in mobile crowd sensing

IEEE Communications Magazine, 2014
Mobile crowd sensing is a new paradigm that takes advantage of pervasive mobile devices to efficiently collect data, enabling numerous largescale applications. Human involvement is one of the most important features, and human mobility offers unprecedented opportunities for both sensing coverage and data transmission.
Huadong Ma, Dong Zhao 0001, Peiyan Yuan
openaire   +1 more source

Robust Spectrum Sensing With Crowd Sensors

IEEE Transactions on Communications, 2014
This paper investigates the issue of cooperative spectrum sensing with a crowd of low-end personal spectrum sensors (such as smartphones, tablets, and in-vehicle sensors), where one critical challenge is the uncertainty of the quality of sensing data from crowd sensors that may be unreliable, untrustworthy, or even malicious.
Guoru Ding   +6 more
openaire   +1 more source

Urban crowd sensing demonstrator: Sense the Zagreb Air

2014 22nd International Conference on Software, Telecommunications and Computer Networks (SoftCOM), 2014
We demonstrate an urban crowd sensing application for monitoring air quality by use of specially-designed wearable sensors and mobile phones. The application is built upon the OpenIoT platform\footnote{; ; ; ; ; The EU FP7 project OpenIoT is the winner of the Open Source Rookie of the Year 2013.
Aleksandar Antonic   +8 more
openaire   +2 more sources

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