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: Aug 2, 2025

Implantation and Control of Wireless, Battery-free Systems for Peripheral Nerve Interfacing
07:13

Implantation and Control of Wireless, Battery-free Systems for Peripheral Nerve Interfacing

Published on: October 20, 2021

3.3K

Data Acquisition Control for UAV-Enabled Wireless Rechargeable Sensor Networks.

Ikjune Yoon1

  • 1Division of AI Computer Science and Engineering, Kyonggi University, Suwon-si 16227, Republic of Korea.

Sensors (Basel, Switzerland)
|April 13, 2023
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

Stability-Controlled Continual Federated Learning for Energy-Harvesting AIoT Systems.

Sensors (Basel, Switzerland)·2026
Same author

Error Recovery Using Cooperative ARQ in Energy-Harvesting Wireless Sensor Networks with Data Allocation.

Sensors (Basel, Switzerland)·2026
Same author

Dual-Mode Data Collection for Periodic and Urgent Data Transmission in Energy Harvesting Wireless Sensor Networks.

Sensors (Basel, Switzerland)·2025
Same author

Efficient Location Service for a Mobile Sink in Solar-Powered Wireless Sensor Networks.

Sensors (Basel, Switzerland)·2019
Same author

Energy-Aware Control of Data Compression and Sensing Rate for Wireless Rechargeable Sensor Networks.

Sensors (Basel, Switzerland)·2018
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

This study enhances wireless sensor network (WSN) lifetime by optimizing energy use in hotspot nodes and improving data collection. The new method balances energy, reduces depletion, and increases data acquisition for IoT applications.

Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Wireless sensor networks (WSNs) face energy limitations, driving research in energy harvesting and wireless power transfer (WPT).
  • Mobile sinks like cars or unmanned aerial vehicles (UAVs) are explored to balance energy and reduce hops in WSNs.
  • Existing strategies often struggle with energy imbalance and hotspot node depletion, limiting network lifetime and data acquisition.

Purpose of the Study:

  • To increase the network lifetime of Internet of Things (IoT) wireless sensor networks (WSNs).
  • To reduce energy consumption in hotspot nodes and maximize data acquisition from all sensors.
  • To address energy imbalance and enhance overall network efficiency by integrating energy harvesting, WPT, and mobile sinks.

Main Methods:

Keywords:
data acquisition controlenergy awaremobile sinksensing rateunmanned aerial vehiclewireless power transferwireless sensor network

More Related Videos

In Situ Soil Moisture Sensors in Undisturbed Soils
08:20

In Situ Soil Moisture Sensors in Undisturbed Soils

Published on: November 18, 2022

6.4K
Insect-machine Hybrid System: Remote Radio Control of a Freely Flying Beetle Mercynorrhina torquata
10:17

Insect-machine Hybrid System: Remote Radio Control of a Freely Flying Beetle Mercynorrhina torquata

Published on: September 2, 2016

12.3K

Related Experiment Videos

Last Updated: Aug 2, 2025

Implantation and Control of Wireless, Battery-free Systems for Peripheral Nerve Interfacing
07:13

Implantation and Control of Wireless, Battery-free Systems for Peripheral Nerve Interfacing

Published on: October 20, 2021

3.3K
In Situ Soil Moisture Sensors in Undisturbed Soils
08:20

In Situ Soil Moisture Sensors in Undisturbed Soils

Published on: November 18, 2022

6.4K
Insect-machine Hybrid System: Remote Radio Control of a Freely Flying Beetle Mercynorrhina torquata
10:17

Insect-machine Hybrid System: Remote Radio Control of a Freely Flying Beetle Mercynorrhina torquata

Published on: September 2, 2016

12.3K
  • Development of multiple minimum depth trees (MDTs) considering UAV and sensor node energy levels.
  • Adaptive control of sensed data by parent nodes to prevent self-depletion and ensure balanced data transmission.
  • Integration of energy harvesting, wireless power transfer (WPT), and mobile sinks (UAVs) for robust network operation.

Main Results:

  • Significant reduction in energy depletion, particularly in hotspot nodes.
  • Increased network connectivity and improved data collection rates from all sensors.
  • Demonstrated superiority over state-of-the-art methods in key performance metrics.

Conclusions:

  • The proposed scheme effectively balances energy consumption and enhances data acquisition in WSNs.
  • Achieved longer network lifetimes and reduced maintenance costs, suitable for environmental monitoring.
  • Offers a viable solution for energy-constrained IoT applications requiring reliable data collection.