A Radio Frequency Sensor For Measurement Of Small Dielectric Property Changes

2012 ◽  
Vol 26 (8-9) ◽  
pp. 1180-1191 ◽  
Author(s):  
W.-N. Liu ◽  
Y. Yang ◽  
K.-M. Huang
2013 ◽  
Vol 103 (6) ◽  
pp. 062906 ◽  
Author(s):  
Yan Cui ◽  
Jiwei Sun ◽  
Yuxi He ◽  
Zheng Wang ◽  
Pingshan Wang

2017 ◽  
Vol 17 (18) ◽  
pp. 5900-5907 ◽  
Author(s):  
Muhammad Tayyab ◽  
Mohammad S. Sharawi ◽  
Abdelsalam Al-Sarkhi

Author(s):  
V. Vasu ◽  
N. Fox ◽  
T. Brabetz ◽  
M. Wren ◽  
C. Heneghan ◽  
...  

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1047 ◽  
Author(s):  
Jianfei Chen ◽  
Zhaohua Dai ◽  
ZhiQiang Chen

The advent of autonomous navigation, positioning, and general robotics technologies has enabled the improvement of small to miniature-sized unmanned aerial vehicles (UAVs, or ‘drones’) and their wide uses in engineering practice. Recent research endeavors further envision a systematic integration of aerial drones and traditional contact-based or ground-based sensors, leading to an aerial–ground wireless sensor network (AG-WSN), in which the UAV serves as both a gateway besides and a remote sensing platform. This paper serves two goals. First, we will review the recent development in architecture, design, and algorithms related to UAVs as a gateway and particularly illustrate its nature in realizing an opportunistic sensing network. Second, recognizing the opportunistic sensing need, we further aim to focus on achieving energy efficiency through developing an active radio frequency (RF)-based wake-up mechanism for aerial–ground data transmission. To prove the effectiveness of energy efficiency, several sensor wake-up solutions are physically implemented and evaluated. The results show that the RF-based wake-up mechanism can potentially save more than 98.4% of the energy that the traditional duty-cycle method would otherwise consume, and 96.8% if an infrared-receiver method is used.


Author(s):  
Shunfeng Cheng ◽  
Larry Thomas ◽  
Jason L. Cook ◽  
Michael Pecht

This paper introduces a radio frequency identification sensor system and its application for prognostics and health management. In prognostics and health management applications, the radio frequency identification sensor system collects data and transfers the data wirelessly into computers. The data then is analyzed by failure detection and prediction algorithms. The performance of the sensor system for prognostics and health management is demonstrated by a field application.


Sign in / Sign up

Export Citation Format

Share Document