People living in big cities often suffer from long queuing time waiting for checking out in supermarkets when the crowd density is high. This paper develops QTime, an application to inform queuing time in nearby supermarkets to help people make time-efficient plan about when and which store to go. QTime uses participatory sensing data collected by commodity sensors built into every-day smartphones without dependence on any pre-installed sensing hardware or software infrastructure. QTime calculates queuing time of an in-store user by detecting his/her queuing movement mode in the phone-side, and estimates the queuing time in given supermarkets by aggregating data from different users in the server-side, and notifies the users who have shopping plans through phones or webpages. Because even in a crowded supermarket, the queuing time of only a few customers can represent the majority, QTime can estimate queuing time accurately even only a few users upload data to the server. An experiment has been conducted and described to prove the validity of QTime.