Proximity Detection: Energy Efficient and Accurate (and not just for COVID Contact Tracing)
We all became familiar with proximity detection during the pandemic. Some of us even installed “contact tracing” apps, with proximity detection at their core. While contact tracing on smartphones was ubiquitous, it had other drawbacks. First and foremost, it wasn’t very accurate – a direct consequence of using Bluetooth to “measure” the distance.
In this talk, I will introduce Janus, our contact detection protocol that is both accurate and energy efficient. I will show how reaching inside the communication protocol stack allows us to fully exploit a combination of Bluetooth and ultra-wideband radios for a contact detection protocol that can be used for collecting contact tracing logs as well as for proximity warning systems. I’ll also talk about several real-world experiments with Janus in 2020 including two here at FBK (one in the cafeteria and one with 90 people all around the Povo campus) and another with kids attending Trentino summer camps. I’ll also provide evidence for the accuracy and energy efficiency of Janus.
Bio of the speaker: Amy L. Murphy is a researcher in the Energy Efficient Embedded Digital Architectures (E3DA) unit at the Fondazione Bruno Kessler in Trento, Italy. Her research focuses on applied research for smart cities from the software engineering, distributed computing, and low-power wireless networks, with a recent emphasis on the Internet of Things. The theme that drives her work is to enable reliable applications for dynamic environments with particular attention to the wireless communication protocols necessary to support complex interactions among distributed devices.
The event will be held remotly at following Google Meet link: https://meet.google.com/tnh-vojz-aax?hs=122&authuser=0