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

Field Application of Global Positioning System01:28

Field Application of Global Positioning System

137
The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
137
Distance Measurements by Taping01:18

Distance Measurements by Taping

164
Tapes are essential in surveying for accurate, durable, and short-distance measurements. Made from lightweight, nylon-coated steel, they offer flexibility and strength for rugged outdoor use. The nylon coating protects against rust and wear, extending the tape's life. Standard lengths, around 30 meters, are marked in meters and millimeters for precision.Surveyors select tapes based on site conditions and accuracy needs. Lightweight, nylon-coated tapes are commonly used for ease of handling and...
164
Types of Global Positioning System Surveys01:30

Types of Global Positioning System Surveys

156
GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
156
Distance Corrections01:15

Distance Corrections

122
To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
122
Cluster Sampling Method01:20

Cluster Sampling Method

13.2K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
13.2K
Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

208
Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
208

You might also read

Related Articles

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

Sort by
Same author

The NF-κB Inhibitor Pyrrolidinedithiocarbamate Ammonium (PDTC) Exerts an Anti-Pyroptotic Effect in Monocytes.

Current medicinal chemistry·2026
Same author

Correlational Analysis of Liver Metabolites and Pharmacodynamic Indexes in Xanthoxylin-Treated Acute Liver Failure.

Molecules (Basel, Switzerland)·2026
Same author

Early versus delayed enteral nutrition in septic shock: a target trial emulation study.

Frontiers in nutrition·2026
Same author

Experimental and numerical study on the flexural capacity of fiber mesh fabric-reinforced RC slabs.

PloS one·2026
Same author

MFG-E8 inhibits AT1-AA production to alleviate preeclampsia.

Cellular immunology·2026
Same author

Early Antibiotic Therapy in Sepsis Without Shock: A Multimethod Study of Heterogeneous Treatment Effects in ICU Patients.

Infectious diseases and therapy·2026

Related Experiment Video

Updated: Oct 22, 2025

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

9.5K

Research on Location Algorithm Based on Beacon Filtering Combining DV-Hop and Multidimensional Support Vector

Dejing Zhang1, Xiangcheng Zhang1, Fengfeng Xie1

  • 1School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai 264209, China.

Sensors (Basel, Switzerland)
|August 28, 2021
PubMed
Summary

This study introduces a new localization algorithm that improves accuracy by filtering beacon nodes and combining DV-Hop with multidimensional support vector regression (MSVR). The enhanced method significantly reduces positioning errors in wireless sensor networks.

Keywords:
DV-HopMSVRRSSIanisotropic networkswireless sensor network

More Related Videos

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
07:05

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

Published on: October 27, 2016

9.4K
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

1.3K

Related Experiment Videos

Last Updated: Oct 22, 2025

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

9.5K
Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
07:05

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

Published on: October 27, 2016

9.4K
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

1.3K

Area of Science:

  • Wireless Sensor Networks
  • Localization Algorithms
  • Signal Processing

Background:

  • The Distance-based Hop (DV-Hop) algorithm offers simplicity and low cost for node localization but suffers from significant positioning errors.
  • Existing improvements to DV-Hop, like hop and distance-weighted corrections, still face limitations in accuracy, especially in anisotropic networks.
  • Accurate localization is crucial for various applications of wireless sensor networks (WSNs).

Purpose of the Study:

  • To propose a novel localization algorithm that enhances accuracy by integrating DV-Hop with multidimensional support vector regression (MSVR) and a beacon filtering mechanism.
  • To address the limitations of existing DV-Hop based localization methods, particularly in anisotropic network environments.
  • To improve the overall location accuracy of unknown nodes in WSNs.

Main Methods:

  • A hybrid localization approach combining the DV-Hop algorithm with multidimensional support vector regression (MSVR).
  • Incorporation of Received Signal Strength Indication (RSSI) and a weighted least squares method for coordinate estimation.
  • Introduction of a beacon node verification error to select high-quality beacons and reduce localization error.

Main Results:

  • The proposed algorithm demonstrated a significant improvement in location accuracy compared to classical DV-Hop and a multidimensional support vector regression (LMSVR) based algorithm.
  • Simulation results indicated at least a 34% increase in accuracy over DV-Hop and 28% over LMSVR across different network distributions.
  • The algorithm showed robustness and potential for application in small-scale anisotropic wireless sensor networks.

Conclusions:

  • The developed beacon filtering and MSVR-enhanced DV-Hop algorithm effectively reduces localization errors in WSNs.
  • This approach offers a promising solution for achieving higher location accuracy, particularly in challenging anisotropic network conditions.
  • The method provides a valuable advancement for practical WSN deployments requiring precise node positioning.