Abstract
Despite significant research efforts and great advances on Mobile CrowdSensing (MCS), building MCS applications remains difficult. In this paper, we develop and run Dining Halls on Live (DHOL), a campus dining population density monitoring system over several months. We make a holistic reality examination, discover key technical and practical difficulties, develop effective solutions and share our experiences and insights. We find two main obstacles on data fusion and incentive design: insufficient data quantity/quality and ``irrational'' user behavior. We develop effective methods by combining historical and real time data, and allocating a given budget among users to address them. We also conduct a detailed user survey to identify reasons behind interesting discoveries, important practical difficulties in acquiring sufficient users and location data, and share our experiences dealing with them. Our main insight is that insufficient data quantity/quality and ``irrational'' user behavior demand practical yet effective data fusion and incentive mechanisms, and one must provide values to users to acquire and retain a large user base.
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