Exploration of Advanced Applications of Triboelectric Nanogenerator-Based Self-Powered Sensors in the Era of Artificial Intelligence DOI Creative Commons

Yi‐Feng Su,

D.L. Yin,

Xinmao Zhao

и другие.

Sensors, Год журнала: 2025, Номер 25(8), С. 2520 - 2520

Опубликована: Апрель 17, 2025

The integration of Deep Learning with sensor technologies has significantly advanced the field intelligent sensing and decision making by enhancing perceptual capabilities delivering sophisticated data analysis processing functionalities. This review provides a comprehensive overview synergy between sensors, particular focus on applications triboelectric nanogenerator (TENG)-based self-powered sensors combined artificial intelligence (AI) algorithms. First, evolution is reviewed, highlighting advantages, limitations, application domains several classical models. Next, innovative in autonomous driving, wearable devices, Industrial Internet Things (IIoT) are discussed, emphasizing critical role neural networks precision capabilities. then delves into TENG-based introducing their mechanisms based contact electrification electrostatic induction, material selection strategies, novel structural designs, efficient energy conversion methods. algorithms showcased through groundbreaking motion recognition, smart healthcare, homes, human–machine interaction. Finally, future research directions outlined, including multimodal fusion, edge computing integration, brain-inspired neuromorphic computing, to expand robotics, space exploration, other high-tech fields. offers theoretical technical insights collaborative innovation technologies, paving way for development next-generation systems.

Язык: Английский

Self‐Powered Vibration Sensing and Energy Harvesting via Series‐Resistor‐Enhanced Triboelectric Nanogenerators with Charge Compensation for Autonomous Alarm Systems DOI Open Access
Zhe Li,

Lin Fang,

Leilei Shu

и другие.

Energy Technology, Год журнала: 2025, Номер unknown

Опубликована: Фев. 9, 2025

The ability to efficiently harvest energy while accurately sensing signals with a single device is critical focus in self‐powered vibration monitoring systems and an urgent requirement for the highly integrated development of Internet Things (IoT). This work presents triboelectric nanogenerator that combines harvesting signal (SE‐TENG). By connecting resistor (S‐TENG) series using S‐TENG as pump‐TENG provide charge (E‐TENG), this approach effectively utilizes from component, reducing loss. Under excitation 0.6 mm amplitude, output voltage SE‐TENG remains above 200 V 12–30 Hz. Additionally, we implement external limiter strategy limit displacement moving part, which optimizes waveform signal. Based on SE‐TENG, have successfully realized self‐driven wireless temperature humidity monitoring, frequency alarm, amplitude alarm. provides new idea TENG get both field collection sensing, has potential application IoT.

Язык: Английский

Процитировано

0
Efficient energy harvesting using triboelectric nanogenerators (TENGs): Integration with technologies, wearable applications, and future trends DOI
Seyed Mohammad Vahidhosseini, Saman Rashidi, M.H. Ehsani

и другие.

Renewable and Sustainable Energy Reviews, Год журнала: 2025, Номер 216, С. 115662 - 115662

Опубликована: Апрель 2, 2025

Язык: Английский

Процитировано

0
Exploration of Advanced Applications of Triboelectric Nanogenerator-Based Self-Powered Sensors in the Era of Artificial Intelligence DOI Creative Commons

Yi‐Feng Su,

D.L. Yin,

Xinmao Zhao

и другие.

Sensors, Год журнала: 2025, Номер 25(8), С. 2520 - 2520

Опубликована: Апрель 17, 2025

The integration of Deep Learning with sensor technologies has significantly advanced the field intelligent sensing and decision making by enhancing perceptual capabilities delivering sophisticated data analysis processing functionalities. This review provides a comprehensive overview synergy between sensors, particular focus on applications triboelectric nanogenerator (TENG)-based self-powered sensors combined artificial intelligence (AI) algorithms. First, evolution is reviewed, highlighting advantages, limitations, application domains several classical models. Next, innovative in autonomous driving, wearable devices, Industrial Internet Things (IIoT) are discussed, emphasizing critical role neural networks precision capabilities. then delves into TENG-based introducing their mechanisms based contact electrification electrostatic induction, material selection strategies, novel structural designs, efficient energy conversion methods. algorithms showcased through groundbreaking motion recognition, smart healthcare, homes, human–machine interaction. Finally, future research directions outlined, including multimodal fusion, edge computing integration, brain-inspired neuromorphic computing, to expand robotics, space exploration, other high-tech fields. offers theoretical technical insights collaborative innovation technologies, paving way for development next-generation systems.

Язык: Английский

Процитировано

0