RadioMic: Sound Sensing via mmWave Signals Muhammed Zahid Ozturk Chenshu Wu
[email protected] [email protected] University of Maryland University of Maryland College Park, USA College Park, USA Origin Wireless Inc. Origin Wireless Inc. Greenbelt, USA Greenbelt, USA Beibei Wang K. J. Ray Liu
[email protected] [email protected] University of Maryland University of Maryland College Park, USA College Park, USA Origin Wireless Inc. Origin Wireless Inc. Greenbelt, USA Greenbelt, USA ABSTRACT Soundproof wall Noisy room Quiet room UWHear Voice interfaces has become an integral part of our lives, with WaveEar the proliferation of smart devices. Today, IoT devices mainly RadioMic rely on microphones to sense sound. Microphones, however, have fundamental limitations, such as weak source separa- tion, limited range in the presence of acoustic insulation, and Mixed sounds Music only being prone to multiple side-channel attacks. In this paper, RadioMic Figure 1: An illustrative scenario of RadioMic we propose RadioMic, a radio-based sound sensing system to mitigate these issues and enrich sound applications. Ra- dioMic constructs sound based on tiny vibrations on active sources (e.g., a speaker or human throat) or object surfaces (e.g., paper bag), and can work through walls, even a sound- proof one. To convert the extremely weak sound vibration in the radio signals into sound signals, RadioMic introduces smart speakers like Amazon Alexa or Google Home can now radio acoustics, and presents training-free approaches for ro- understand user voices, control IoT devices, monitor the envi- bust sound detection and high-fidelity sound recovery. It then ronment, and sense sounds of interest such as glass breaking exploits a neural network to further enhance the recovered or smoke detectors, all currently using microphones as the sound by expanding the recoverable frequencies and reduc- primary interface.