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Related Concept Videos

Maximum Power Transfer01:16

Maximum Power Transfer

458
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...
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Energy Stored In A Coaxial Cable01:31

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A coaxial cable consists of a central copper conductor used for transmitting signals, followed by an insulator shield, a metallic braided mesh that prevents signal interference, and a plastic layer that encases the entire assembly.
In the simplest form, a coaxial cable can be represented by two long hollow concentric cylinders in which the current flows in opposite directions. The magnetic field inside and outside the coaxial cable is determined by using Ampère's law. The magnetic...
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The Maximum Power Transfer Theorem01:20

The Maximum Power Transfer Theorem

791
Consider a linear AC Thevenin equivalent circuit connected to a load impedance.
The load connected draws the current, and the circuit delivers the power to the load. The alternating current flowing through the load is determined using the rectangular form of voltages, currents, network impedance, and load impedance. The average power delivered to the load is obtained from the product of the square of current and load resistance.
791

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Wireless Power Transfer in Wirelessly Powered Sensor Networks: A Review of Recent Progress.

S M Asiful Huda1, Muhammad Yeasir Arafat1, Sangman Moh1

  • 1Department of Computer Engineering, Chosun University, 309 Pilmun-daero, Gwangju 61452, Korea.

Sensors (Basel, Switzerland)
|April 23, 2022
PubMed
Summary
This summary is machine-generated.

Wirelessly powered sensor networks (WPSNs) offer a solution to limited sensor battery life. This study surveys wireless power transfer (WPT) techniques to enhance sensor node longevity and overcome deployment challenges.

Keywords:
SWIPTenergy harvestingwireless power transferwirelessly powered sensor networks

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Area of Science:

  • Electrical Engineering and Computer Science
  • Wireless Communication Systems
  • Internet of Things (IoT) Technology

Background:

  • The proliferation of Internet of Things (IoT) devices, including sensors and wearables, is rapidly expanding.
  • Limited battery life of sensor nodes presents a significant challenge for widespread IoT adoption and maintenance.
  • Traditional battery replacement in sensor networks is resource-intensive and impractical for large-scale deployments.

Purpose of the Study:

  • To conduct an in-depth survey of wireless power transfer (WPT) techniques for sensor devices.
  • To address the critical issue of limited battery life in sensor nodes within wirelessly powered sensor networks (WPSNs).
  • To explore solutions for improving the operational lifetime and reducing maintenance overhead of IoT sensor nodes.

Main Methods:

  • Overview of wirelessly powered sensor networks (WPSNs) architecture and principles.
  • Demonstration and discussion of three distinct wireless power transfer (WPT) models and their associated enabling technologies.
  • Comprehensive review of existing WPT techniques, evaluating critical design parameters and performance factors.

Main Results:

  • Identification and analysis of various WPT techniques applicable to sensor energy harvesting.
  • Discussion of key performance-enhancing strategies for WPT within WPSN contexts.
  • Evaluation of current WPT methods based on essential design and performance metrics.

Conclusions:

  • WPSNs are a promising solution to overcome the battery limitations of IoT sensor nodes.
  • Further research into WPT techniques is crucial for advancing the efficiency and reliability of sensor networks.
  • The study highlights challenges and future research directions for optimizing WPT in WPSNs.