Improving The Performance Of Mobile Phone Crowdsourcing Applications
Keywords
Mobile phone crowdsourcing; Trust-based fusion
Abstract
Mobile phone crowdsourcing is a powerful tool for many types of distributed sensing problems. However, a central issue with this type of system is that it relies on user contributed data, which may be sparse or erroneous. This paper describes our experiences developing a mobile phone crowdsourcing app, Kpark, for monitoring parking availability on a university campus. Our system combines multiple trust-based data fusion techniques to improve the quality of user submitted parking reports and is currently being used by over 1500 students.
Publication Date
1-1-2015
Publication Title
Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume
1
Number of Pages
145-153
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
84944682525 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84944682525
STARS Citation
Davami, Erfan and Sukthankar, Gita, "Improving The Performance Of Mobile Phone Crowdsourcing Applications" (2015). Scopus Export 2015-2019. 1792.
https://stars.library.ucf.edu/scopus2015/1792