TunnelSense: Low-power, Non-Contact Sensing Using Tunnel Diodes

Lim Chang Quan Thaddeus,C. Rajashekar Reddy, Yuvraj Singh Bhadauria,Dhairya Shah,Manoj Gulati,Ambuj Varshney

2024 IEEE INTERNATIONAL CONFERENCE ON RFID, RFID 2024(2024)

引用 0|浏览7
暂无评分
摘要
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 100 mu W of power consumption and with a biasing voltage starting at 70mV. 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 cm between the subject and the TunnelSense tag.
更多
查看译文
关键词
Tunnel Diode,Vital Signs,Accelerometer,Power Consumption,Wearable Devices,Energy Harvesting,Bias Voltage,Radio Waves,Object Motion,Motion Tracking,Electromagnetic Environment,Small Battery,Radiofrequency,Complex Environment,Solar Cells,Outdoor Environments,Low Voltage,Carrier Frequency,Indoor Environments,Objective Presentation,Radio Frequency Signal,Noisy Environments,Self-interference Cancellation,Frequency Drift,Thermoelectric Generators,Negative Differential Resistance,Phase Noise,Receiver Design,RFID Tags,Storage Elements
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要