Jove
Visualize
Contact Us

Related Concept Videos

Application of Linearization and Approximation01:29

Application of Linearization and Approximation

53
A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...
53
Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

475
Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
475
Force Classification01:22

Force Classification

2.3K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
2.3K

You might also read

Related Articles

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

Sort by
Same author

Enhancing Deep-Learning Classification for Remote Motor Imagery Rehabilitation Using Multi-Subject Transfer Learning in IoT Environment.

Sensors (Basel, Switzerland)·2025
Same author

Optimal Channel Selection of Multiclass Motor Imagery Classification Based on Fusion Convolutional Neural Network with Attention Blocks.

Sensors (Basel, Switzerland)·2024
Same author

Adoption of Transformer Neural Network to Improve the Diagnostic Performance of Oximetry for Obstructive Sleep Apnea.

Sensors (Basel, Switzerland)·2023
Same author

Energy-Efficient EEG-Based Scheme for Autism Spectrum Disorder Detection Using Wearable Sensors.

Sensors (Basel, Switzerland)·2023
Same author

Multiscale Encoding of Electrocardiogram Signals with a Residual Network for the Detection of Atrial Fibrillation.

Bioengineering (Basel, Switzerland)·2022
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
See all related articles
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: Jan 18, 2026

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

492

Deep Learning Image-Based Classification for Post-Earthquake Damage Level Prediction Using UAVs.

Norah Alsaaran1, Adel Soudani1

  • 1Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.

Sensors (Basel, Switzerland)
|September 13, 2025
PubMed
Summary
This summary is machine-generated.

Unmanned Aerial Vehicles (UAVs) with lightweight deep learning models enable rapid post-earthquake damage assessment. This study shows MobileNetV3-Small on edge devices provides efficient, real-time structural damage prediction for search and rescue teams.

Keywords:
MobileNetconvolutional neural network (CNN)deep learningearthquakeedge computingreal-time damage assessmentunmanned aerial vehicle (UAV)

More Related Videos

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.6K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

2.1K

Related Experiment Videos

Last Updated: Jan 18, 2026

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

492
Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.6K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

2.1K

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Remote Sensing

Background:

  • Unmanned Aerial Vehicles (UAVs) are crucial for disaster response.
  • Image-based damage assessment requires efficient processing.
  • Lightweight deep learning models offer potential for onboard analysis.

Purpose of the Study:

  • To investigate the MobileNetV3-Small model for real-time post-earthquake damage assessment using UAV imagery.
  • To evaluate the model's performance and efficiency on edge devices.

Main Methods:

  • Utilized the MobileNetV3-Small Convolutional Neural Network (CNN) model.
  • Trained the model to classify three damage levels (none, moderate, severe).
  • Deployed and tested the model on a Raspberry Pi 5 for edge computing.

Main Results:

  • MobileNetV3-Small achieved the lowest FLOPs, outperforming ShuffleNetv2 by 58.8%.
  • Fine-tuning improved accuracy by 4.5% with a minimal FLOPs increase.
  • Achieved a weighted average F-score of 0.93 on a merged dataset.
  • Demonstrated real-time performance on a Raspberry Pi 5.

Conclusions:

  • Lightweight CNNs like MobileNetV3-Small are effective for onboard UAV image analysis.
  • The model enables efficient, real-time damage assessment in resource-constrained environments.
  • This technology can significantly aid Search and Rescue (SAR) operations post-earthquake.