Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Role-Based Identity

Role-Based Identity

Role-based identities are central to understanding how individuals navigate social environments by adopting distinct self-conceptions aligned with various societal roles. These identities are not fixed traits but are constructed through personal actions and the social feedback individuals receive in context-specific interactions. Each social role, such as student, teacher, or friend, carries a set of expectations and norms that influence how people think, feel, and behave within that...

Issues And Trends In Healthcare Delivery System

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...

Rapid Identification of Pathogens

Rapid Identification of Pathogens

MALDI-TOF MS has transformed clinical microbiology by offering a rapid and reliable method for pathogen identification. The traditional approach to microbial identification typically involves time-consuming culture techniques and biochemical tests, which can delay the initiation of appropriate antimicrobial therapy. MALDI-TOF MS avoids these delays by using characteristic ribosomal protein mass patterns of microbial cells, enabling accurate species-level identification within minutes.Principle...

IR Frequency Region: Fingerprint Region

IR Frequency Region: Fingerprint Region

IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the C=O, C=N, and C=C occur between 1600–1850 cm−1.
The...

You might also read

Related Articles

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

Sort by

Same author

Hyperspectral Face Recognition with Adaptive and Parallel SVMs in Partially Hidden Face Scenarios.

Sensors (Basel, Switzerland)·2022

Same author

Analytical Model for the Duty Cycle in Solar-Based EH-WSN for Environmental Monitoring.

Sensors (Basel, Switzerland)·2018

See all related articles

Search research articles

Related Experiment Videos

Extreme Edge Computing for Secure and Private Multimodal Biometric Identification in Intelligent IoT Systems.

José Antonio de la Torre¹, Fernando Rincón¹, Soledad Escolar¹

¹Technology and Information Systems Department, School of Computer Science, University of Castilla-La Mancha, 13071 Ciudad Real, Spain.

Sensors (Basel, Switzerland)

|June 26, 2026

Summary

This study introduces a secure, privacy-preserving multimodal biometric authentication system for resource-constrained Internet of Things (IoT) devices. The TinyML-powered system achieves low error rates and exceptional energy efficiency for edge computing applications.

Keywords:

Compute Continuum Internet of Things (IoT)TinyML edge AI embedded systems energy efficiency facial recognition multimodal biometrics privacy-by-design voice recognition

Related Experiment Videos

Area of Science:

Computer Science
Electrical Engineering
Cybersecurity

Background:

The proliferation of Internet of Things (IoT) devices necessitates decentralized computing architectures to overcome cloud limitations.
Edge computing offers solutions but faces security and privacy challenges in data transmission.
The Compute Continuum paradigm extends computation to the extreme edge for enhanced efficiency.

Purpose of the Study:

To develop a secure and privacy-preserving multimodal biometric authentication system for resource-constrained embedded devices.
To leverage TinyML for pushing intelligence to the extreme edge within the Compute Continuum.
To demonstrate the feasibility of standalone, privacy-by-design biometric sensors for intelligent IoT environments.

Main Methods:

Implementation of a hierarchical processing chain on embedded devices.
Utilizing an ultra-lightweight person-detection filter as a wake-up mechanism.
Integration of robust facial and voice recognition modules for multimodal authentication.

Main Results:

Achieved a combined False Acceptance Rate (FAR) of 0.12% through a strict hierarchical pipeline.
Demonstrated exceptional energy efficiency, requiring only 0.15 J per inference cycle on an ESP32 microcontroller.
Showcased autonomous operation for over 39 hours on a 600 mAh battery.

Conclusions:

The proposed TinyML-based multimodal biometric system is viable for secure and private authentication in edge computing.
The system's low power consumption and high accuracy validate its use in standalone, privacy-centric IoT applications.
This approach effectively addresses security and privacy concerns in decentralized IoT ecosystems.