Morse 2022 - Program (Oct 21, 2022)

(9:30am - 10:15am) Keynote 1

"Towards Continuous Health Sensing with Everyday Clothing"

Prof. Deepak Ganesan, University of Massachusetts Amherst

Abstract: Computational textiles that allow us to use everyday fabrics as a substrate for sensing offers a promising new direction for wearable computing. In this talk, I will describe several examples of computational textiles that can measure a range of biometrics and can be literally “woven into the fabric of everyday life” as Mark Weiser articulated in his vision for ubiquitous computing. We demonstrate how we can imperceptibly modify everyday loose-fitting clothing made of materials such as cotton to design unconventional ways to sense physiological and electrical signals on the body. I will describe some of the challenges in designing smart textiles for wearable health sensing and describe examples involving triboelectric textiles, pressure-sensing textiles and gel electrodes in smart sleepwear and smart toys to monitor cardio-respiratory rhythm, brain signals, limb movements and interactions. This work is done in collaboration with Trisha Andrew from Chemistry at UMass Amherst.

Bio: Deepak Ganesan is a Professor and Donna M and Robert J Manning Faculty Fellow in the Department of Computer Science at the University of Massachusetts Amherst, the Director of the Massachusetts AI and Technology Center for Connected Care in Aging and Alzheimer’s Disease, a $20m multi-disciplinary center funded by the National Institute of Aging, and the Director of the Center for Personal Health Monitoring at UMass Amherst, a $40 million center for new health devices. He received his Ph.D. in Computer Science from UCLA in 2004 and his bachelors in Computer Science from IIT, Madras in 1998. He is an ACM Fellow.

(10:15am - 11:15am) Paper Session

  • "RMVS: Remote Monitoring of Vital Signs with mm-Wave Radar."
    Zhanjun Hao, Hao Yan, Xiaochao Dang, Zhongyu Ma, Wenze Ke, Peng Jin (Northwest Normal University ).
  • "A Federated Learning-enabled Smart Street Light Monitoring Application: Benefits and Future Challenges."
    Diya Anand (University of Bristol, Toshiba Europe Limited), Ioannis Mavromatis (Toshiba Europe Limited), Pietro Carnelli (Toshiba Europe Limited), Aftab Khan (Toshiba Europe Limited).
  • "Detecting and Controlling Smart Lights with LiTalk."
    Jagdeep Singh (Toshiba Europe Ltd.), Dan Watkinson (University of Bristol), Tim Farnham (Toshiba Europe Ltd.), Daniele Puccinelli (University of Applied Sciences and Arts of Southern Switzerland).
  • "HueSense: Featuring LED Lights Through Hue Sensing."
    Jagdeep Singh (Toshiba Europe Ltd.), Qing Wang (Delft University of Technology), Marco Zuniga (Delft University of Technology), Tim Farnham (Toshiba Europe Ltd.).

(11:15am - 12:00pm) Keynote 2

"Understanding the Position Dependent Problem in WiFi/4G/5G Sensing"

Prof. Daqing Zhang, Peking University and IP Paris

Abstract: WiFi/4G/5G based wireless sensing has attracted a lot of attention from both academia and industry in recent years. However, duo to the received signal pattern variation of a certain activity caused by the location, heading and speed change, i.e., the so-called position dependent problem, most of the WiFi/4G/5G based human activity recognition systems developed so far fail to work robustly in real settings. In this talk, I will introduce the Fresnel zone model as a new theoretic basis for device-free and contactless human sensing with WiFi/4G/5G signals. The Fresnel-zone based sensing theory not only reveals the relationship among the WiFi CSI signal, the distance between two transceivers, the sensing target’s relative location/heading and velocity with respect to the transceivers, but also intuitively explains how the location/heading affects the received CSI signal pattern in time and frequency domain. Building on the Fresnel zone model, we further investigate the dependency of a target’s velocity estimation accuracy on its location and heading, and derive a closed-form solution to understand the fundamental limitation of velocity estimation. I will use human respiration monitoring, gesture recognition and indoor human tracking as application examples to demonstrate the effectiveness of our proposed position independent sensing solutions.

Bio: Daqing Zhang is a Chair Professor with Peking University, China and IP Paris, France. His research interests include ubiquitous computing, context-aware computing, big data analytics and Intelligent IoT. He has published more than 280 technical papers in leading conferences and journals, where his work on context model and WiFi-based sensing theory is widely accepted by pervasive computing, mobile computing and service computing communities. He is the winner of the Ten Years CoMoRea Impact Paper Award at IEEE PerCom 2013 and Ten Years Most Influential Paper Award at IEEE UIC 2019, the Distinguished Paper Award of IMWUT (Ubicomp 2021), Honorable Mention Award at ACM UbiComp 2015 and 2016, etc.. He served as the general or program chair for more than a dozen of international conferences, and in the editorial board of IEEE Pervasive Computing and Proceeding of ACM IMWUT. Daqing Zhang is a Fellow of IEEE and Member of Academy of Europe, he obtained his Ph.D. from University of Rome "La Sapienza", Italy in 1996.

(12:00pm - 1:00m) Panel


  • Prof. Wenyao Xu, University at Buffalo, the State University of New York

    Wenyao Xu is a Professor of Computer Science and Engineering Department in the State University of New York (SUNY) at Buffalo, where he founds and directs the ESC (Embedded Sensing and Computing) Group. He has published over 200 technical papers, co-authored 2 books and is a named inventor on many international and U.S. patents. His group has focused on exploring novel Embedded Sensing and Computing technologies to build up innovative Internet-of-Things (IoT) systems for high-impact real-world applications in the fields of healthcare, security and advanced manufacturing.

  • Prof. Jie Yang, Florida State University

    Jie Yang is an Associate Professor in the Department of Computer Science at Florida State University. He directs research in mobile computing and cybersecurity, is a pioneer in the area of WiFi sensing and mobile authentication. His work has been regularly featured in the media, including MIT Technology Review, New Scientist, Yahoo News, NPR, the New York Times, and The Wall Street Journal. He has published one book and three book chapters and 100+ research papers in prestigious journals and conferences. His recognitions include the FSU Developing Scholar Award, FSU CS Faculty Research Award, Google Faculty Research Award, the Stevens Francis T. Boesch Award, as well as Best Paper (Runner-up) Awards at IEEE CNS 2014, IEEE CNS 2013, and ACM MobiCom 2011.

  • Prof. Jeremy Gummeson, University of Massachusetts Amherst

    Jeremy Gummeson is an Assistant Professor of ECE at the University of Massachusetts Amherst. His research is multidisciplinary in and looks at how we can co-design computer hardware and software to enable energy-efficient mobile computing systems that can accurately sense humans and the world that surrounds them. More specifically, his current research largely focuses on developing novel sensing, communication, and energy management/harvesting techniques that enable closed-loop energy efficient systems for human-in-the-loop and autonomous sensing applications.