A Low-Cost Wi-Fi-Based Solution for Measuring Human Queues

Abstract

Creating devices or systems that can leverage computationally rich environments to support day-to-day interactions between humans and computers is the goal of mobile computing and communication. The increasing use of mobile devices and their data-intensive apps has generated extensive opportunities to monitor and optimize real-world processes through network traffic and corresponding characteristics. For example, research has already shown that we can use cellular call data records and signal traces to understand patterns of large-scale transportation [1] and the level of congestion on roadways [2], respectively. Likewise, ubiquitous wireless infrastructures (e.g., Wi-Fi and Bluetooth) not only provide convenience in communication, but also enable novel applications, such as indoor localization and user authentication. In addition, we have found that the strength of wireless signals from the Wi-Fi traffic consumed by mobile devices can be utilized to perform fine-grained monitoring on a daily common process, i.e., human queues.