Context-Aware Worker Recruitment for Mobile Crowd Sensing Based on Mobility Prediction
Quan T. Ngo,
Seokhoon Yoon
Abstract:Opportunistic worker (OW) selection is a challenging problem in mobile crowd sensing (MCS), where tasks are assigned to individuals to be completed seamlessly during their daily routines without any deviation from their usual routes. In this paper, we propose a novel framework named context-aware worker recruitment based on a mobility prediction model (CAMP) to address the OW selection problem in MCS. Unlike previous approaches that relied on worker mobility prediction models with limited accuracy or utility-b… Show more
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