Battery-free short-range self-powered wireless sensor network (SS-WSN) using TENG based direct sensory transmission (TDST) mechanism

By Feng Wen, Hao Wang, Tianyiyi He, Qiongfeng Shi, Zhongda Sun, Minglu Zhu, Zixuan Zhang, Zhiguang Cao, Yanbing Dai, Ting Zhang and 1 more. 2020

141 citations recorded by the source corpus.

Abstract Wireless Sensor Networks (WSNs) bring the basis that the development of the Internet of Things (IoTs) relies on. However, external power requirement restricts the widespread applications of WSNs. Triboelectric nanogenerator (TENG) has been a promising candidate for energy harvesting and self-powered sensing, but most of the reported TENG-based WSNs need to store energy in a capacitor first and then power the wireless modules without a continuous sensing capability simultaneously. In this work, a battery-free short-range self-powered wireless sensor network (SS-WSN) is proposed by using TENG-based direct sensory transmission (TDST). By leveraging a mechanical switch or diode-switch combination, enhanced output and boosted frequency of TENG signal have been achieved by instantaneous discharging in a short period, initiating the potential for direct signal transmission without additional wireless modules and external power suppliers. Different from others' works, the stable resonant frequency is used to realize the force-sensing function with high sensitivity (434.7 Hz.N−1), in which case a wireless real-time electronic scale is demonstrated. Additionally, by varying the connections of the textile TENGs or the capacitance of an external capacitor for distinguishable resonant frequencies generation, the multiple-freedom-degree 2D toy car control, and 3D VR drone control are demonstrated with a single coil.

Subfields: Biomedical Engineering, Cognitive Neuroscience, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/dbb004ca41023c43c16ff97882bf5602637b9483

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Xinge Guo
2. Chengkuo Lee
3. Long Liu
4. Tianyiyi He
5. Feng Wen
6. Qiongfeng Shi
7. Bowei Dong
8. Jianxiong Zhu

In Cognitive Neuroscience

1. Chengkuo Lee
2. Xinge Guo
3. Long Liu
4. Tianyiyi He
5. Feng Wen
6. Qiongfeng Shi
7. Jianxiong Zhu
8. Bowei Dong

In Mechanical Engineering

1. Xinge Guo
2. Long Liu
3. Qiongfeng Shi
4. Philippe Vachon
5. Feng Wen
6. Yanqin Yang
7. Jianxiong Zhu
8. Bowei Dong

Citations in the corpus

• Progress in TENG technology—A journey from energy harvesting to nanoenergy and nanosystem (2020, methodology): “Copyright 2019, Elsevier.233 G, in vivo powering of the pacemaker by respiration-driven implanted TENG.”
• Promoting smart cities into the 5G era with multi-field Internet of Things (IoT) applications powered with advanced mechanical energy harvesters (2021, methodology): “Wen et al. reported a battery-free short-range self-powered wireless sensor network using TENG [350].”