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

PI Controller: Design01:24

PI Controller: Design

703
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
703
Maximum Power Transfer01:16

Maximum Power Transfer

556
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...
556
MOSFET: Enhancement Mode01:22

MOSFET: Enhancement Mode

557
Enhancement-mode MOSFETs are pivotal components in electronics, distinguished by their capacity to act as highly efficient switches. They are part of the larger family of metal-oxide Semiconductor Field-Effect Transistors (MOSFETs). They are available in two types: p-channel and n-channel, each tailored to specific polarity operations.
In their basic form, enhancement-mode MOSFETs are typically non-conductive when the gate-source voltage (Vgs) is zero. This default 'off' state means no...
557
Load-frequency control01:28

Load-frequency control

305
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
305
Control of Power Flow01:30

Control of Power Flow

352
There are several methods to control power flow in power systems:
352
MOSFET: Depletion Mode01:20

MOSFET: Depletion Mode

566
Depletion-mode MOSFETs represent a unique subset of MOSFET technology, functioning fundamentally differently from their enhancement-mode counterparts. Unlike enhancement MOSFETs, which require a positive gate-source voltage (Vgs) to turn on, depletion-mode MOSFETs are inherently conductive and "normally on" devices.
The primary characteristic of depletion-mode MOSFETs is their ability to conduct current between the drain and source terminals without gate bias. This inherent conductivity...
566

You might also read

Related Articles

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

Sort by
Same author

Neuromorphic spike-based large language model.

National science review·2026
Same author

Dynamic spatio-temporal pruning for efficient spiking neural networks.

Frontiers in neuroscience·2025
Same author

Neuromorphic neuromodulation: Towards the next generation of closed-loop neurostimulation.

PNAS nexus·2024
Same author

Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing.

Nature communications·2024
Same author

Spiking neural networks for nonlinear regression.

Royal Society open science·2024
Same author

Modeling and hardware implementation of universal interface-based floating fractional-order mem-elements.

Chaos (Woodbury, N.Y.)·2023

Related Experiment Video

Updated: Nov 3, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

884

Low-Power Wireless Sensor Network Using Fine-Grain Control of Sensor Module Power Mode.

Seongwon You1, Jason K Eshraghian2, Herbert C Iu3

  • 1Department of Information and Communication Engineering, Chungbuk National University, Chungbuk 28644, Korea.

Sensors (Basel, Switzerland)
|June 2, 2021
PubMed
Summary

This study introduces fine-grained power modes (FGPM) for wireless sensor nodes, significantly reducing idle state energy consumption. The new method lowers power usage by 74.2% compared to traditional systems, extending battery life for IoT devices.

Keywords:
power managementpower modesensor nodewireless sensor networks

More Related Videos

Construction of a Wireless-Enabled Endoscopically Implantable Sensor for pH Monitoring with Zero-Bias Schottky Diode-based Receiver
08:25

Construction of a Wireless-Enabled Endoscopically Implantable Sensor for pH Monitoring with Zero-Bias Schottky Diode-based Receiver

Published on: August 27, 2021

2.7K
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

3.5K

Related Experiment Videos

Last Updated: Nov 3, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

884
Construction of a Wireless-Enabled Endoscopically Implantable Sensor for pH Monitoring with Zero-Bias Schottky Diode-based Receiver
08:25

Construction of a Wireless-Enabled Endoscopically Implantable Sensor for pH Monitoring with Zero-Bias Schottky Diode-based Receiver

Published on: August 27, 2021

2.7K
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

3.5K

Area of Science:

  • Electrical Engineering
  • Computer Science
  • Embedded Systems

Background:

  • Wireless sensor nodes (WSNs) face severe resource constraints, necessitating low-power techniques to prolong battery life.
  • Conventional power management in WSNs often exhibits significant energy consumption in the idle state.
  • Optimizing power management is crucial for the widespread adoption and efficiency of Internet of Things (IoT) devices.

Purpose of the Study:

  • To propose and evaluate a novel power management method for wireless sensor nodes.
  • To minimize energy consumption, particularly in the idle state, for resource-constrained WSNs.
  • To enhance the operational lifespan of IoT sensor modules through efficient power utilization.

Main Methods:

  • Analysis and benchmarking of power consumption across Sleep, Idle, and Run modes.
  • Development of a fine-grained power mode (FGPM) system with five distinct states.
  • Modulation of energy consumption based on the sensor node's real-time communication status.
  • Experimental evaluation of the FGPM method on a Mica2 test bench.

Main Results:

  • The proposed FGPM method demonstrated a substantial reduction in power consumption.
  • Achieved a 74.2% decrease in power usage compared to conventional power management approaches.
  • Validated the effectiveness of fine-grained power state modulation for energy savings.

Conclusions:

  • The developed FGPM strategy offers a significant improvement in energy efficiency for wireless sensor nodes.
  • This method is particularly beneficial for IoT applications with long sleep durations or frequent short data transmissions.
  • The findings contribute to the development of more sustainable and longer-lasting IoT sensor networks.