Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jul 1, 2026

Artificial Intelligence-Based System for Detecting Attention Levels in Students
06:37

Artificial Intelligence-Based System for Detecting Attention Levels in Students

Published on: December 15, 2023

Deep learning-enabled self-powered bimodal flexible sensor for intelligent access control.

Jiamin Chen1, Xiaochen Wang1, Nan Wang2

  • 1School of Microelectronics, Shanghai University, No. 20 Chengzhong Road, Jiading District, Shanghai, 201800, China.

Nanotechnology
|June 29, 2026
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Operationalizing Digital Health Equity in Artificial Intelligence-Enabled Patient Decision Aids for Older Adults: Mixed Methods Study.

Journal of medical Internet research·2026
Same author

Tianhuang Formula and its active ingredient GsRg1 ameliorate central insulin resistance and oxidative stress by enhancing hypothalamic autophagy.

Journal of ethnopharmacology·2026
Same author

Optimization of a Wedge Shaped T-Type Magnetic Flux Concentrator for High-Sensitivity TMR Sensors.

Micromachines·2026
Same author

Single-Mode Capability Enhancement of Curved Sapphire Fiber Utilizing High-Order Mode Suppression Characteristics Applied at High Temperature.

Micromachines·2026
Same author

All-2D vertical metal-semiconductor field-effect transistor with sub-10 nm channel and contact lengths.

Nature communications·2026
Same author

Aloe emodin isolated from <i>Cassiae</i> semen upregulates IFITM1 to suppress hepatitis B virus replication via the interferon signaling pathway.

mSphere·2026
Same journal

Quantitative Mechanism Separation of Single-Event Transients in Nanosheet Transistors via TCAD Simulation.

Nanotechnology·2026
Same journal

Antibacterial, mechanical and curing properties of PMMA bone cement loaded with copper nanoparticles.

Nanotechnology·2026
Same journal

Thickness-Dependent Decoupling Charge Transport and NH 3 Sensing in Multilayer MoS 2 Transistors.

Nanotechnology·2026
Same journal

Symmetry-Based Tight-Binding Hamiltonian for Monolayer 1T'-MoS 2 : Spin Textures and Spin-Resolved Transport in Nanoribbons.

Nanotechnology·2026
Same journal

Compact Modeling of Pd-MoS2 Self-rectifying RRAM based on modulated Schottky barrier equation.

Nanotechnology·2026
Same journal

Tailored nanomaterials from urban lignocellulosic waste for soil and wastewater remediation: advancing towards sustainable environment.

Nanotechnology·2026
See all related articles

This study introduces a self-powered sensor for intelligent access control, overcoming limitations of traditional biometrics. The innovative device uses a triboelectric nanogenerator and deep learning for high-accuracy material and user identification in smart security systems.

Area of Science:

  • Materials Science
  • Electrical Engineering
  • Computer Science

Background:

  • Intelligent access control systems are vital for smart architecture and urban security.
  • Traditional biometrics face challenges like power dependency, privacy risks, and environmental sensitivity.
  • A need exists for low-power, high-security, and multidimensional sensing solutions.

Purpose of the Study:

  • To develop a self-powered bimodal sensor for intelligent access control.
  • To provide a low-power, high-security, and multidimensional sensing solution.
  • To address the limitations of existing biometric technologies.

Main Methods:

  • A single-electrode triboelectric nanogenerator with a polydimethylsiloxane triboelectric layer and micro-pyramid array was designed.
Keywords:
CNNTENGbimodal sensingsmart securitysurface structure

Related Experiment Videos

Last Updated: Jul 1, 2026

Artificial Intelligence-Based System for Detecting Attention Levels in Students
06:37

Artificial Intelligence-Based System for Detecting Attention Levels in Students

Published on: December 15, 2023

  • Contact electrification and electrostatic induction were used to convert mechanical stimuli into electrical signals.
  • A deep learning framework utilizing a convolutional neural network was implemented for signal analysis.

    • Main Results:

    • The sensor achieved high recognition accuracies: 99.83% for material identification and 98.88% for user authentication in single-dimensional tasks.
    • The system maintained a recognition accuracy of 96.15% even in challenging environments.
    • The device effectively extracts material electronegativity and human kinetic information.

    Conclusions:

    • The developed self-powered bimodal sensor offers a robust technological foundation for future smart security.
    • This technology has potential applications in flexible electronic skins and personalized healthcare monitoring.
    • The study demonstrates a novel approach to human-machine interaction in security systems.