TunnelSense: Low-power, Non-Contact Sensing using Tunnel Diodes
<|reference_start|>TunnelSense: Low-power, Non-Contact Sensing using Tunnel Diodes: Sensing the motion of physical objects in an environment enables numerous applications, from tracking occupancy in buildings and monitoring vital signs to diagnosing faults in machines. Typically, these application scenarios involve attaching a sensor, such as an accelerometer, to the object of interest, like a wearable device that tracks our steps. However, many of these scenarios require tracking motion in a noncontact manner where the sensor is not in touch with the object. A sensor in such a scenario observes variations in radio, light, acoustic, and infrared fields disturbed by the object's motion. Current noncontact sensing mechanisms often require substantial energy and involve complex processing on sophisticated hardware. We present TunnelSense, a novel mechanism that rethinks noncontact sensing using tunnel diode oscillators. They are highly sensitive to changes in their electromagnetic environments. The motion of an object near a tunnel diode oscillator induces corresponding changes in its resonant frequency and thus in the generated radio waves. Additionally, the low-power characteristics of the tunnel diode allow tags designed using them to operate on less than 100microwatt of power consumption and with a biasing voltage starting at 70 millivolt. This enables prolonged tag operation on a small battery or energy harvested from the environment. Among numerous applications enabled by the TunnelSense system, this work demonstrates its ability to detect breathing at distances up to 30 centimeter between the subject and the TunnelSense tag.<|reference_end|>
@article{thaddeus2024tunnelsense:,
    title={TunnelSense: Low-power, Non-Contact Sensing using Tunnel Diodes},
    author={Lim Chang Quan Thaddeus, C. Rajashekar Reddy, Yuvraj Singh Bhadauria,
  Dhairya Shah, Manoj Gulati, Ambuj Varshney},
    journal={arXiv preprint arXiv:2405.09155},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.09155},
    primaryClass={cs.ET}
}