A Self‐Powered and Self‐Absorbing Wireless Sensor Node for Smart Grid DOI
Qiqi Zhou, Zutao Zhang,

Xiaofeng Xia

et al.

Energy Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 19, 2024

The health monitoring of electricity transmission systems has been increasingly attracting the scientific community's attention, especially those power towers built in remote and deserted areas. smart grid provides a realistic solution to problem, but there is problem that energy supplies are still constrained by batteries. This article proposes novel vibration harvester address supply challenges auxiliary equipment mounted on or lines. proposed not only harvests when working also attenuates amplitude line. structure device comprises three modules: module for capturing vibration, motion conversion, management module. analytical response under sinusoidal random excitation investigated, performance harvesting effect tested. prototype achieves maximum 183.96 mW tested using servo hydraulic mechanical testing sensing system, wireless data experiment proves generation ability prototype. experimental results show acceleration line decreases working.

Language: Английский

Magnetic coupling and amplitude truncation based bistable energy harvester DOI

Li Zhao,

Guobiao Hu, Shengxi Zhou

et al.

International Journal of Mechanical Sciences, Journal Year: 2024, Volume and Issue: 273, P. 109228 - 109228

Published: March 27, 2024

Language: Английский

Citations

17

Self-powered sensing for health monitoring and robotics DOI Open Access
Shuzheng Liu, Wentao Guo, Xinhua Zhao

et al.

Soft Science, Journal Year: 2025, Volume and Issue: 5(1)

Published: Feb. 14, 2025

Self-powered sensing technology plays a key role in autonomous and portable systems, with applications health monitoring robotics. These sensors, which do not rely on external power sources, offer stable, continuous data acquisition for real-time complex interactions. For instance, triboelectric nanogenerators have enabled self-powered wearable sensors to monitor vital signs such as heart beat rate respiration by converting body movement into electrical energy, eliminating the need batteries. Despite their advantages, challenges remain large-scale manufacturing, miniaturization, multifunctional integration. Overcoming these may require innovative advances novel materials, intelligent algorithms, integration strategies. This perspective summarizes recent existing technologies robotics applications, provides an outlook future development.

Language: Английский

Citations

2

AI‐Driven TENGs for Self‐Powered Smart Sensors and Intelligent Devices DOI Creative Commons

Aiswarya Baburaj,

Syamini Jayadevan,

Akshaya Kumar Aliyana

et al.

Advanced Science, Journal Year: 2025, Volume and Issue: 12(20)

Published: April 25, 2025

Triboelectric nanogenerators (TENGs) are emerging as transformative technologies for sustainable energy harvesting and precision sensing, offering eco-friendly power generation from mechanical motion. They harness while enabling self-sustaining sensing self-powered devices. However, challenges such material optimization, fabrication techniques, design strategies, output stability must be addressed to fully realize their practical potential. Artificial intelligence (AI), with its capabilities in advanced data analysis, pattern recognition, adaptive responses, is revolutionizing fields like healthcare, industrial automation, smart infrastructure. When integrated TENGs, AI can overcome current limitations by enhancing output, stability, adaptability. This review explores the synergistic potential of AI-driven TENG systems, optimizing materials embedding machine learning deep algorithms intelligent real-time sensing. These advancements enable improved harvesting, predictive maintenance, dynamic performance making TENGs more across industries. The also identifies key future research directions, including development low-power algorithms, materials, hybrid robust security protocols AI-enhanced solutions.

Language: Английский

Citations

2

Magnetic tri-stable triboelectric nanogenerator for harvesting energy from low-frequency vibration DOI

Dongguo Tan,

Xu Ou, Jiaxi Zhou

et al.

Renewable Energy, Journal Year: 2025, Volume and Issue: unknown, P. 122517 - 122517

Published: Jan. 1, 2025

Language: Английский

Citations

1

Fountain-inspired triboelectric nanogenerator as rotary energy harvester and self-powered intelligent sensor DOI
Gefan Yin,

Xuexiu Liang,

Ying Zhang

et al.

Nano Energy, Journal Year: 2025, Volume and Issue: unknown, P. 110779 - 110779

Published: Feb. 1, 2025

Language: Английский

Citations

1

Portable and Self-Powered Sensing AI-Enabled Mask for Emotional Recognition in Virtual Reality DOI
Deqiang He, Hongyu Chen, Xinyi Zhao

et al.

ACS Applied Materials & Interfaces, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

With the increasing development of metaverse and human-computer interaction (HMI) technologies, artificial intelligence (AI) applications in virtual reality (VR) environments are receiving significant attention. This study presents a self-sensing facial recognition mask (FRM) utilizing triboelectric nanogenerators (TENG) machine learning algorithms to enhance user immersion interaction. Various TENG negative electrode materials evaluated improve sensor performance, efficacy single is confirmed. For accurate movement emotion detection, different assessed, leading selection an advanced data processing method with two-layer long short-term memory model, which achieves 99.87% accuracy. The practical FRM system reality, including psychotherapy HMI scenarios, validated through mathematical models. Additionally, digital twin-based monitoring platform developed using 5G, database, visualization technologies oversee status. Overall, these innovative approaches overcome limitations existing face environmental interference high cost, compared other technologies.

Language: Английский

Citations

1

Hybrid Electromagnetic‐Triboelectric Hip Energy Harvester for Wearables and AI‐Assisted Motion Monitoring DOI
Daning Hao,

Chengliang Fan,

Xiaofeng Xia

et al.

Small, Journal Year: 2025, Volume and Issue: unknown

Published: April 6, 2025

Abstract Reliable human motion monitoring is crucial across various fields such as sports, healthcare, and metaverse. This study introduces an AI‐assisted wearable hip joint energy harvester (HJEH) designed to convert mechanical from movements into electric power for devices while simultaneously motion. The HJEH utilizes electromagnetic generator (EMG) in conjunction with a freestanding triboelectric nanogenerator (FS‐TENG) achieve harvesting sensing. EMG specifically recovers the negative generate electricity, flywheel acceleration gears employ enhance output power. Concurrently, FS‐TENG generates signals driven by motions, which are processed using deep learning algorithms accurate detection. performance of thoroughly evaluated through bench tests, treadmill outdoor experiments. achieves peak 357 mW maximum gravitational density 1.67 W kg −1 during running at speed 8 km h . demonstrates remarkable accuracy 99.95% identifying 12 different types motion, validating efficacy integrated system. In particular, incorporating digital twin technology realizes safety elderly.

Language: Английский

Citations

1

AI-Enhanced Backpack with Double Frequency-Up Conversion Vibration Energy Converter for Motion Recognition and Extended Battery Life DOI
Anxin Luo,

Shanghao Gu,

Xinge Guo

et al.

Nano Energy, Journal Year: 2024, Volume and Issue: unknown, P. 110302 - 110302

Published: Sept. 1, 2024

Language: Английский

Citations

6

Artificial Intelligence enabled self-powered sensing and wind energy harvesting system for bridges monitoring DOI
Junwei Hu,

Chengliang Fan,

Minfeng Tang

et al.

Nano Energy, Journal Year: 2024, Volume and Issue: 132, P. 110349 - 110349

Published: Oct. 9, 2024

Citations

5

Self-powered and self-sensing wearable devices from a comfort perspective DOI
Rui Zou, Hongyu Chen,

Hongye Pan

et al.

Device, Journal Year: 2024, Volume and Issue: 2(11), P. 100466 - 100466

Published: Nov. 1, 2024

Language: Английский

Citations

4