Title： Human Activities and WiFi Signals - Recognition and
Authentication
speaker： Professor Alex X. Liu
Abstract：Human activity recognition is the core technology that enables a wide
variety of applications such as health care, smart homes, fitness
tracking, and building surveillance. We recognize human activities using
signals from commercial WiFi devices. Human bodies reflect wireless
signals as they are mostly made of water. Different human activities
cause different changes on wireless signals. Thus, by analyzing the
changes in wireless signals, we can recognize the corresponding human
activities that cause the changes. We classify human activities into
macro activities, which involve mostly arm, leg, or body scale
movements, and micro activities, which involve mostly finger or hand
scale movements. Human activity recognition and monitoring is the
enabling technology for various applications such as elderly/health
care, building surveillance, human-computer interaction, health care,
smart homes, and fitness tracking. In this talk, I will present our
research results on this topic.
CV：
Alex X. Liu received his Ph.D. degree in Computer Science from The
University of Texas at Austin in 2006. He received the IEEE & IFIP
William C. Carter Award in 2004, the National Science Foundation CAREER
Award in 2009, and the Michigan State University Withrow Distinguished
Scholar Award in 2011. He is an Associate Editor of IEEE/ACM
Transactions on Networking, an Associate Editor of IEEE Transactions on
Dependable and Secure Computing, and an Area Editor of Computer
Communications. He received Best Paper Awards from ICNP-2012, SRDS-2012,
and LISA-2010. His research interests focus on networking and security.
His special research interests are in networking, security, and privacy.
His general research interests include computer systems, distributed
computing, and dependable systems.
