High Sensitive Sensing Using WiFi

Smartphones and other "smart gadgets" (eg., watches, fridges) enabled an unprecedented level of interaction between users and applications through an ever evolving set of sensors. Buttons, touch-screens, cameras and voice are some of the examples which are continuously transforming the pervasiveness of modern mobile devices. Nonetheless, recent research has show how wireless signals (eg., UWB, WiFi) can be used to authenticate users, perform gestures recognition and monitor vital signs.

Building on existing work at our Chairn, in this thesis you will setup and evaluate various WiFi CSI sensing alternatives (ie., Intel, Atheros, Nexmon) on one of the following use cases (but not limited to):

  • Continuous user authentication (examples: paper)
  • Vitals signs monitoring (examples: paper)
  • Precise indoor localization (examples: paper, paper)
  • Crowd sensing (related: paper)

Note that several of these use cases will require extensive use of Machine Learning, especially Neural Networks.


  • Experience with hardware and low-level programming
  • Good writing skills

Good to have

  • Excellent experience with C programming
  • Experience with Neural Networks and other Machine Learning models
  • Experiences with any of the aforementioned use cases

If you're interested, please email me your CV and university transcripts.

Leonardo Tonetto - tonetto at in tum de