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

69
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...
69
Types of Global Positioning System Surveys01:30

Types of Global Positioning System Surveys

81
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...
81
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

676
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
676
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

82
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...
82
Maximum Power Transfer01:16

Maximum Power Transfer

292
Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...
292
Reducing Line Loss01:18

Reducing Line Loss

174
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
174

You might also read

Related Articles

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

Sort by
Same author

Automatic spread factor and position definition for UAV gateway through computational intelligence approach to maximize <i>signal-to-noise ratio</i> in wooded environments.

PeerJ. Computer science·2024
Same author

Application of Artificial Neural Networks for Prediction of Received Signal Strength Indication and Signal-to-Noise Ratio in Amazonian Wooded Environments.

Sensors (Basel, Switzerland)·2024
Same author

LoRa Technology Propagation Models for IoT Network Planning in the Amazon Regions.

Sensors (Basel, Switzerland)·2024
Same author

Hybrid computational and real data-based positioning of small cells in 5G networks.

PeerJ. Computer science·2023
Same author

Methodology for LoRa Gateway Placement Based on Bio-Inspired Algorithmsfor a Smart Campus in Wooded Area.

Sensors (Basel, Switzerland)·2022
Same author

SNR Prediction with ANN for UAV Applications in IoT Networks Based on Measurements.

Sensors (Basel, Switzerland)·2022

Related Experiment Video

Updated: Jul 23, 2025

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization
06:00

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

5.3K

Intelligent Drone Positioning via BIC Optimization for Maximizing LPWAN Coverage and Capacity in Suburban Amazon

Flávio Henry Cunha da Silva Ferreira1, Miércio Cardoso de Alcântara Neto1, Fabrício José Brito Barros1

  • 1Institute of Technology, Federal University of Pará (UFPA), Belém 66075-110, Brazil.

Sensors (Basel, Switzerland)
|July 14, 2023
PubMed
Summary
This summary is machine-generated.

This study optimizes drone base station placement using bio-inspired algorithms to maximize wireless coverage in Amazon urban forests. Results show improved network performance for Internet of Things (IoT) applications.

Keywords:
IoFTLoRabioinspired computingchannel modelingcoverage optimizationwireless sensor networks

More Related Videos

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

8.1K
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

1.5K

Related Experiment Videos

Last Updated: Jul 23, 2025

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization
06:00

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

5.3K
Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

8.1K
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

1.5K

Area of Science:

  • Wireless Communication Systems
  • Network Optimization
  • Robotics and Automation

Background:

  • Unmanned Aerial Vehicle (UAV) base stations offer flexible network deployment.
  • Low-Power Wireless Area Networks (LPWAN), like LoRa, are suitable for extensive coverage with low data rates.
  • Optimizing UAV positioning is crucial for maximizing coverage in complex environments.

Purpose of the Study:

  • To present a metaheuristic approach for optimizing drone array placement.
  • To maximize coverage area for wireless communication systems using UAV base stations.
  • To analyze performance in suburban, wooded Amazonian urban environments.

Main Methods:

  • Applied Low-Power Wireless Area Network (LPWAN) technology, specifically LoRa.
  • Utilized three bio-inspired computing (BIC) methods: Cuckoo Search (CS), Flower Pollination Algorithm (FPA), and Genetic Algorithm (GA) for UAV positioning.
  • Developed and validated an empirical propagation model for forested environments using MATLAB simulations.

Main Results:

  • Optimized UAV positioning was simulated for high-range IoT-LoRa networks.
  • An empirical propagation model for LoRa in forested areas (SF 8-11) was developed.
  • Comparison between theoretical and measured propagation models for UAVs was conducted.

Conclusions:

  • The metaheuristic approach effectively optimizes drone array placement for enhanced wireless coverage.
  • The developed propagation model provides a more accurate representation of signal behavior in Amazonian urban forests.
  • This research contributes to efficient deployment of UAV-based communication networks in challenging terrains.