  This paper presents MultiTrack, a commodity WiFi-based human sensing system
that can track multiple users and recognize the activities of multiple users
performing them simultaneously. Such a system can enable easy and large-scale
deployment for multi-user tracking and sensing without the need for additional
sensors through the use of existing WiFi devices (e.g., desktops, laptops, and
smart appliances). The basic idea is to identify and extract the signal
reflection corresponding to each individual user with the help of multiple WiFi
links and all the available WiFi channels at 5GHz. Given the extracted signal
reflection of each user, MultiTrack examines the path of the reflected signals
at multiple links to simultaneously track multiple users. It further
reconstructs the signal profile of each user as if only a single user has
performed activity in the environment to facilitate multi-user activity
recognition. We evaluate MultiTrack in different multipath environments with up
to 4 users for multi-user tracking and up to 3 users for activity recognition.
Experimental results show that our system can achieve decimeter localization
accuracy and over 92% activity recognition accuracy under multi-user scenarios.
