Wang, Jiangtao and Wang, Yasha and Zhang, Daqing and Wang, Leye and Chen, Chao and Lee, Jae Woong and He, Yuanduo (2017) Real-time and generic queue time estimation based on mobile crowdsensing. FRONTIERS OF COMPUTER SCIENCE, 11 (1). pp. 49-60. ISSN 2095-2228
Full text not available from this repository.Abstract
People often have to queue for a busy service in many places around a city, and knowing the queue time can be helpful for making better activity plans to avoid long queues. Traditional solutions to the queue time monitoring are based on pre-deployed infrastructures, such as cameras and infrared sensors, which are costly and fail to deliver the queue time information to scattered citizens. This paper presents CrowdQTE, a mobile crowdsensing system, which utilizes the sensor-enhanced mobile devices and crowd human intelligence to monitor and provide real-time queue time information for various queuing scenarios. When people are waiting in a line, we utilize the accelerometer sensor data and ambient contexts to automatically detect the queueing behavior and calculate the queue time. When people are not waiting in a line, it estimates the queue time based on the information reported manually by participants. We evaluate the performance of the system with a two-week and 12-person deployment using commercially-available smartphones. The results demonstrate that CrowdQTE is effective in estimating queuing status.