Data for: Effective Truth Discovery and Fair Reward Distribution for Mobile Crowdsensing
Published: 23 October 2018| Version 1 | DOI: 10.17632/93kr7pb7dc.1
Contributor:
Fengrui ShiDescription
The attachment contains two folders: code and data. The code folder contains the Python code implemented for the models proposed and compared by the paper "Effective Truth Discovery and Fair Reward Distribution for Mobile Crowdsensing Using Sensing Expertise from IoT Infrastructures". The data folder contains the real-life sensing data collected from 10 mobile devices, which cover illuminance, sound level and WiFi signal strength.
Files
Categories
Mobile Computing, Crowd Analysis, Data Analysis, Sensor