Special Topics on Mobile Sensing & Mobile Networks

Fall 2022, University at Buffalo

Instructor:

Course Description: Nowadays, wireless technologies (cellular, Wi-Fi, mmWave) do not only provide data service but also cater to diverse applications including indoor localization, contact-free activity sensing, medical implant tracking and charging, virtual reality (VR) and autonomous driving. This course introduces the students with fundamentals in mobile networking and the state-of-the-art mobile sensing applications in the Era of Internet-of-Things. Mobile sensing is an active research area which involves wireless communication, signal processing, human computer interaction, machine learning and hardware prototyping. The intrinsic nature of sensor-free and contact-free makes mobile and wireless sensing particularly appealing in current pandemic compared to traditional sensor-based sensing. The latest research in mobile sensing has enabled many novel and exciting applications. For example, Wi-Fi signals can now be employed to differentiate very similar materials such as Pepsi and Coke. You can place your phone on the desk and turn the desk surface into a touch (input) panel with acoustic sensing. We can employ LoRa signals to sense your respiration even 50 meters away with a wall in between without any sensors. We will explore the state-of-the-art of both mobile networking and mobile sensing and make our hands dirty by working on some research projects.

Lecture Time & Location:Tuesday 2:00PM-4:00PM, 440 Park Hall, North Campus

Prerequisites: CSE 489/589 Modern Network Concepts

Slack: We will use slack to ask questions. Pleas join the slack via this link.

Paper Presentation: Please sign up for the paper that you want to present from this link

Questions Regarding the Paper: Please use Persuall to ask questions. To find the course, please use the course code XIE-7TTHF.

Grading: The course grade will be based on the following components.

  • Class Participation: 10%
  • Paper Presentation: 20%
  • Midterm: 20%
  • Course Project: 50%