Related Experiment Video
Updated: Aug 16, 2025
05:30
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
Published on: September 8, 2023
634
Transmission Power Control in Wireless Sensor Networks Using Fuzzy Adaptive Data Rate.
Chung-Wen Hung1, Yi-Da Zhuang1, Ching-Hung Lee2
1Department of Electrical Engineering, National Yunlin University of Science and Technology, Yunlin 64002, Taiwan.
Sensors (Basel, Switzerland)
|December 23, 2022
Summary
This study introduces a fuzzy-based adaptive data rate system for wireless sensor networks to reduce power consumption and improve communication reliability. The novel approach significantly cuts energy use while maintaining a low packet error rate, ideal for battery-powered IoT devices.
Area of Science:
- Wireless Sensor Networks
- Internet of Things (IoT)
- Adaptive Control Systems
Background:
- Increasing sensor nodes in IoT demand enhanced network coverage, extensibility, and reliability.
- Battery-powered sensor nodes necessitate low-power consumption due to finite battery capacity.
- Environmental interference complicates reliable wireless communication in sensor networks.
Purpose of the Study:
- To propose a fuzzy-based adaptive data rate for transmission power control in wireless sensor networks.
- To balance communication quality and power consumption in IoT sensor nodes.
- To address challenges of environmental interference and deployment costs.
Main Methods:
- Utilizing a fuzzy system with error count and error interval as inputs.
- Implementing a 'guard' output to limit data rate and transmission power.
- Conducting long-term experiments to validate the control algorithm's performance.
Main Results:
- The proposed algorithm effectively overcomes environmental interference, achieving low-power performance.
- Sensor nodes demonstrated reliable communication with ultra-low power consumption.
- Total power consumption improved by 73% compared to systems without the algorithm.
- Packet Error Rate (PER) was maintained close to 1%.
Conclusions:
- The fuzzy-based adaptive data rate control is suitable for battery-supplied IoT systems.
- The method offers a significant improvement in power efficiency for wireless sensor networks.
- Reliable communication is achieved even under challenging environmental conditions.
Related Concept Videos
01:16Maximum Power Transfer
330
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...
By substituting the entire circuit with...
330
01:28Load-frequency control
227
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...
227
01:20Power Factor Correction
240
The power transmission to a factory involves the transfer of apparent power, a combination of active and reactive power. The power factor measures how effectively electrical power is converted into useful work output. The ratio of the real power (KW) that does the work to the apparent power (KVA) supplied to the circuit.
240
01:24Frequency-Domain Interpretation of PD Control
160
Proportional-Derivative (PD) controllers are widely used in fan control systems to improve stability and performance. A fan control system can be effectively represented using a Bode plot to illustrate the impact of a PD controller through its transfer function. The Bode plot visually conveys how PD control modifies the fan's response across various frequencies, providing a frequency domain interpretation of the controller's behavior.
The proportional control gain, combined with the...
The proportional control gain, combined with the...
160
01:20The Maximum Power Transfer Theorem
702
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.
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.
702
01:23Maximum Power Flow and Line Loadability
158
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
158