Improving the Performance of Mobile Phone Crowdsourcing Applications
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 the authors’ experiences developing a mobile phone crowd-sourcing app, Kpark, for monitoring parking availability on a university campus. Their 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.
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