| Summary: | 碩士 === 國立交通大學 === 資訊科學與工程研究所 === 104 === Queuing behavior is an important kind of group activities in human’s life. In many real-life scenarios like movie theaters, amusement parks, and restaurant, people spend a substantial amount of time waiting on lines. Detecting the status of the queuing behavior may benefit both customers and businesses. In view of this, a new research topic called queuing detection has emerged in recent by machines. Providing such queuing information helps customers better spend time doing something alternative rather than blindly waiting in line, thereby mitigating their anxiety and improving their experience. In addition, managing queues is important for business since it can help reduce inefficient resource allocation and revenue loss. Therefore, there is a need for a better understanding of emerging trends of the queues in order to not only improve user experience but also benefit business. We implement a prototype on Android platforms using widely available sensors such as accelerometer and gyroscope on mobile phone. Our method not only has achieved high precision and estimate the waiting time efficiently.
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