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 Concept Videos

Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it instrumental in...

You might also read

Related Articles

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

Sort by
Same author

Precision and Robust Models on Healthcare Institution Federated Learning for Predicting HCC on Portal Venous CT Images.

IEEE journal of biomedical and health informatics·2024
Same author

Brain-wide correspondence of neuronal epigenomics and distant projections.

Nature·2023
Same author

Recurrent Neural Network Methods for Extracting Dynamic Balance Variables during Gait from a Single Inertial Measurement Unit.

Sensors (Basel, Switzerland)·2023
Same author

A Trustable and Secure Usage-Based Insurance Policy Auction Mechanism and Platform Using Blockchain and Smart Contract Technologies.

Sensors (Basel, Switzerland)·2023
Same author

A Near-Optimal Energy Management Mechanism Considering QoS and Fairness Requirements in Tree Structure Wireless Sensor Networks.

Sensors (Basel, Switzerland)·2023
Same author

Machine learning of home blood pressure to predict short-term and long-term cardiovascular outcomes.

Blood pressure monitoring·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

Related Experiment Video

Updated: May 26, 2026

Image-based Lagrangian Particle Tracking in Bed-load Experiments
10:32

Image-based Lagrangian Particle Tracking in Bed-load Experiments

Published on: July 20, 2017

An efficient Lagrangean relaxation-based object tracking algorithm in wireless sensor networks.

Frank Yeong-Sung Lin1, Cheng-Ta Lee

  • 1Department of Information Management, National Taiwan University, No 1, Sec 4, Roosevelt Rd, Taipei City 106, Taiwan. yslin@im.ntu.edu.tw

Sensors (Basel, Switzerland)
|December 14, 2011
PubMed
Summary
This summary is machine-generated.

We developed an energy-efficient object tracking algorithm for wireless sensor networks (WSNs). This heuristic algorithm efficiently handles complex network topologies and object movements, optimizing energy usage.

Keywords:
Lagrangean relaxationobject trackingwireless sensor networks

More Related Videos

A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

Related Experiment Videos

Last Updated: May 26, 2026

Image-based Lagrangian Particle Tracking in Bed-load Experiments
10:32

Image-based Lagrangian Particle Tracking in Bed-load Experiments

Published on: July 20, 2017

A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Wireless Sensor Networks (WSNs) are crucial for monitoring applications but face energy constraints.
  • Efficient object tracking in WSNs is challenging due to dynamic environments and limited resources.
  • Existing algorithms often struggle with arbitrary network topologies and bi-directional object movement.

Purpose of the Study:

  • To propose a novel energy-efficient object tracking algorithm for WSNs.
  • To address the challenge of arbitrary network topologies and bi-directional object movement.
  • To optimize energy consumption during object tracking in WSNs.

Main Methods:

  • Formulated the object tracking problem as a 0/1 integer-programming problem.
  • Developed a Lagrangean relaxation-based (LR-based) heuristic algorithm to solve the optimization problem.
  • Considered bi-directional moving objects with given frequencies and link transmission costs.

Main Results:

  • The proposed LR-based algorithm achieves near-optimal performance in energy-efficient object tracking.
  • Experimental results demonstrate significant energy savings compared to existing methods.
  • The algorithm shows high efficiency and scalability in terms of solution time.

Conclusions:

  • The proposed algorithm offers an effective solution for energy-efficient object tracking in WSNs.
  • The LR-based approach provides a scalable and efficient method for complex tracking scenarios.
  • This work contributes to extending the operational lifetime of WSNs through optimized energy management.