scholarly journals Acoustic–Seismic Mixed Feature Extraction Based on Wavelet Transform for Vehicle Classification in Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (6) ◽  
pp. 1862 ◽  
Author(s):  
Heng Zhang ◽  
Zhongming Pan ◽  
Wenna Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Feature Extraction ◽  
Wavelet Transform ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Vehicle Classification

Distributed Data Aggregation Algorithm in Wireless Sensor Networks

2013 ◽  
Vol 442 ◽  
pp. 526-531
Author(s):  
Xian Li Li ◽  
Jia Wei Zhang ◽  
Hai Tao Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Wavelet Transform ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Rational Design ◽  
Wireless Sensor ◽  
Distributed Data ◽  
Lifting Wavelet Transform ◽  
Network Nodes ◽  
Lifting Wavelet

Considering the limited resources and data transmission redundancy of wireless sensor networks, this paper proposes a distributed data aggregation algorithm based on lifting wavelet transform (DDAA-LWT), and carries out the rational design. The algorithm distributes the computing quantity which the lifting wavelet transform requires to all network nodes, eliminates the additional computing and wireless transmission, reduces the information redundancy of network, greatly prolongs the lifecycle of wireless sensor networks. Simulation results demonstrate that the distributed data aggregation algorithm based on lifting wavelet transform (DDAA-LWT) can effectively aggregate the original sensed data and decrease the energy consumption, it significantly outperforms the data aggregation algorithm based on traditional wavelet transform (DAA-WT).

Efficient cooperative image transmission in one-way multi-hop sensor network

2018 ◽  
Vol 57 (4) ◽  
pp. 321-339 ◽  
Author(s):  
Bilal Al-Hayani ◽  
Haci Ilhan
Keyword(s):  
Wireless Sensor Networks ◽  
Wavelet Transform ◽  
Sensor Networks ◽  
Image Quality ◽  
Bit Error Rate ◽  
Error Rate ◽  
Image Transmission ◽  
Wireless Sensor ◽  
Discrete Wavelet ◽  
Relay Nodes

The challenging task while transmitting the high-quality images over the wireless sensor networks is to achieve the higher throughput, minimum bit error rate without compromising the image quality. As the sensor nodes have the limited processing power, designing energy efficient image transmission is another challenge in this research. This paper proposed a novel method of cooperative image transformation from the transmitter to the receiver for wireless sensor networks. We designed the methods for multi-hop one-way relayed cooperative communication model for wireless sensor networks. We believe that the cooperative communication helps to improve the efficiency of image transmission. The proposed approach focused on efficient relayed image transmission through wireless channels with optimum image quality and bit error rate performances. First, lightweight image quality improvement method was proposed at both transmitter and receiver end as images captured under various illumination conditions. Second, the proposed compressive sensing was performed using the approximation coefficient of 2D discrete wavelet transform. We utilized the wavelet denoising advantage by presenting the hybrid thresholding function. And third, use of decode–forward method at relay nodes to perform the task of decode and forward received image data block. The compressed approximation component of 2D discrete wavelet Transform is further used to apply inverse fast Fourier transform and then in modulation using quadrature phase shift keying to transmit over additive white Gaussian noise channel to relay nodes as per the standard orthogonal frequency-division multiplexing model. The simulation results claim the performance efficiency against the state-of-art methods based on mean square error, peak signal-to-noise ratio, and bit error rate.

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