Detecting smoothness of pedestrian flows by participatory sensing with mobile phones

In this paper, we propose a novel system for estimating crowd density and smoothness of pedestrian flows in public space by participatory sensing with mobile phones. By analyzing walking motion of the pedestrians and ambient sound in the environment that can be monitored by accelerometers and microphones in off-the-shelf smartphones, our system classifies the current situation at each area into four categories that well represent the crowd behavior. Through field experiments using Android smartphones, we show that our system can recognize the current situation with accuracy of 60--78%.