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

Electronic Distance Measuring Instruments

Electronic Distance Measuring Instruments

Electronic Distance Measuring Instruments (EDMs) are essential tools in modern surveying, offering precise distance measurements by emitting electromagnetic signals and calculating the time required for these signals to travel to a target and return. Two primary types of signals are used in EDMs — light waves and microwaves — each suited to specific environmental and distance requirements. Light-wave-based EDMs utilize either infrared or laser light, providing high accuracy over...

You might also read

Related Articles

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

Sort by

Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026

Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026

Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026

Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026

Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026

Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026

Search research articles

Related Experiment Video

Updated: Jan 15, 2026

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Published on: May 2, 2018

Tools and Methods for Achieving Wi-Fi Sensing in Embedded Devices.

Jesus A Armenta-Garcia¹, Felix F Gonzalez-Navarro¹, Jesus Caro-Gutierrez¹

¹Engineering Institute, Universidad Autonoma de Baja California, Calle de la Normal S/N Col. Insurgentes Este, Mexicali 21100, Mexico.

Sensors (Basel, Switzerland)

|October 16, 2025

Summary

This summary is machine-generated.

This study introduces an efficient embedded Wi-Fi sensing system for Human Activity Recognition (HAR). It enables accurate, privacy-preserving HAR on edge devices using microcontrollers, overcoming hardware and cloud limitations.

Keywords:

HAR Wi-Fi sensing data augmentation deep learning

More Related Videos

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Published on: February 3, 2023

Related Experiment Videos

Last Updated: Jan 15, 2026

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Published on: May 2, 2018

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Published on: February 3, 2023

Area of Science:

Computer Science
Electrical Engineering
Signal Processing

Background:

Wi-Fi sensing, using Channel State Information (CSI), is a key technology for Human Activity Recognition (HAR).
Existing methods often require specialized hardware and resource-intensive deep learning models, limiting edge deployment.
These limitations hinder the scalability and accessibility of Wi-Fi sensing for privacy-preserving HAR.

Purpose of the Study:

To develop a novel, low-cost, embedded solution for Wi-Fi sensing-based HAR.
To address the challenges of hardware dependency and cloud-based inference in current HAR systems.
To create a privacy-preserving HAR system deployable on resource-constrained edge devices.

Main Methods:

Developed a novel CSI collection tool for low-cost microcontrollers, optimizing packet rate efficiency.
Created an optimized DenseNet-based HAR model for deployment on edge devices.
Introduced an Empirical Mode Decomposition (EMD)-based data augmentation technique to address limited training data.
Presented a new HAR dataset for evaluating embedded Wi-Fi sensing solutions.

Main Results:

The EMD-based data augmentation significantly improved model accuracy from 59.91% to 97.55%.
A compact DenseNet variant achieved 92.43% accuracy with 232 ms inference latency on an ESP32-S3 microcontroller.
The proposed model requires minimal memory (127 kB), demonstrating efficient edge deployment.

Conclusions:

The proposed embedded solution offers a scalable, low-cost, and privacy-preserving approach to Wi-Fi sensing for HAR.
This system overcomes the limitations of existing methods by enabling on-device inference without cloud dependency.
The research demonstrates the feasibility of high-accuracy HAR on resource-constrained edge devices.