RTL Implementation of image compression techniques in WSN

Deepthi, S. Aruna; Rao, E. Sreenivasa; Prasad, M. H. M. Krishna

doi:10.11591/ijece.v9i3.pp1750-1756

Cited by 9 publications

(8 citation statements)

References 15 publications

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“…Furthermore, Aruna Deepthi et al [14] designed in WSNs the different methods of images compression like SVD, NMF, and PNMF with Matlab and RTL schematic. results found that the PNMF was better in energy consumption in-camera nodes.…”

Section: Figure 2 the Basic Idea Of The Image Compression In Wmsnmentioning

confidence: 99%

Forest Fire Detection Using Wireless Multimedia Sensor Networks and Image Compression

Bouakkaz¹,

Wided²,

Derdour³

2021

I2M

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Recently, the issue of multimedia sensors received considerable critical attention, that led to the apparition of Wireless Multimedia Sensor Networks (WMSNs) WMSN that different from wireless sensor networks (WSN) by using multimedia sensors that can process video, audio, image data besides scalar data and send it to station base (SB). Multimedia data have a big volume bigger than scalar data and need more resources and consumed more energy. The ideal solution to solve the problems of WMSN (big volume, energy consumption) is data compression. Forest plays a critical role in our daily life we can summarize the importance of forests in human life. Among the most dangerous events the forest fires that happen because of natural or Man-made. Many methods used to detect forest fires the newest are: wireless multimedia sensor networks. Our system of detecting forest fire has been developed using a wireless multimedia senor network with two types of sensors (scalar, images). In the first phase when the scalar sensors detected a high temperature its announced alarm to activate the image sensors. In the second phase for detecting fire the image sensors, we used image processing tools. When the zone of fire in the image captured was detected the phase of compression started using the down sampling method. the final phase is transmission data to the station base using the grid chain transmission protocol technique, which allows a critical optimization of energy consumption. So, maximizing network life. The competence of the proposed system is achieved by minimizing size of image transmitted with grid chain routing protocol.

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Section: Figure 2 the Basic Idea Of The Image Compression In Wmsnmentioning

confidence: 99%

Forest Fire Detection Using Wireless Multimedia Sensor Networks and Image Compression

Bouakkaz¹,

Wided²,

Derdour³

2021

I2M

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“…In the simulation, authors considered time and energy consumption values and evaluated different nodes lifetime. In the previous study [53] similar wake-up radio scheduling approach is applied for traditional WSNs and shown it outperforms in terms of energy efficiency.The authors introduce the different MAC scheduler mechanisms with the aim to minimize the energy consumption rate in WSN [54][55][56].…”

Section: Related Workmentioning

confidence: 99%

Survey: energy efficient protocols using radio scheduling in wireless sensor network

Mathew¹,

Jones²

2020

IJECE

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An efficient energy management scheme is crucial factor for design and implementation of any sensor network. Almost all sensor networks are structured with numerous small sized, low cost sensor devices which are scattered over the large area. To improvise the network performance by high throughput with minimum energy consumption, an energy efficient radio scheduling MAC protocol is effective solution, since MAC layer has the capability to collaborate with distributed wireless networks. The present survey study provides relevant research work towards radio scheduling mechanism in the design of energy efficient wireless sensor networks (WSNs). The various radio scheduling protocols are exist in the literature, which has some limitations. Therefore, it is require developing a new energy efficient radio scheduling protocol to perform multi tasks with minimum energy consumption (e.g. data transmission). The most of research studies paying more attention towards to enhance the overall network lifetime with the aim of using energy efficient scheduling protocol. In that context, this survey study overviews the different categories of MAC based radio scheduling protocols and those protocols are measured by evaluating their data transmission capability, energy efficiency, and network performance. With the extensive analysis of existing works, many research challenges are stated. Also provides future directions for new WSN design at the end of this survey.

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“…To handle the nonlinear correlation, the polynomial NMF (PNMF) algorithm was proposed. The main idea of PNMF [18] is to first transform data into higher dimensional feature space [26] by using a polynomial kernel-induced nonlinear mapping and then perform decomposition in that feature space. Based on this, a novel method which we called Projective Non-negative Matrix Factorization (PNMF) as the solution to the following optimality problem.…”

Section: Projective Non-negative Matrix Factorizationmentioning

confidence: 99%

Design of various Image Compression Methods in Wireless Sensor Networks

Deepthi,

Rao*,

Giriprasad

2019

IJEAT

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The processing capacity and power of nodes in a Wireless Sensor Network (WSN) are restricted. The quality of the images is deficient, and the contents of the images may vary after decoding when we apply image compression algorithms in WSN. Various compression algorithms are compared in this paper. An Image Compression method based on Restricted Boltzmann Machine (RBM), Auto encoders and Non-negative Matrix Factorization (NMF), Least Square Non-Negative Matrix Factorization (LSNMF), Projective Non-Negative Matrix Factorization (PNMF) network are proposed in this paper. For the WSN, we have used a Message Queue Telemetry Transport (MQTT) protocol. We have used a three Raspberry Pi’s to build a WSN; Publisher, Broker, Subscriber. A Publisher, where it can trigger the camera and captures the images then compress it and send it to another raspberry pi which is a MQTT broker. The PSNR values for those image compression methods were analyzed and compared against each other for images evaluated from the MNIST dataset. Along with the simulation results, all these compression methods are implemented using hardware implementation. Raspberry Pi, a single-board computer with in-built Wi-Fi capabilities, was used in establishing a WSN. Message Queue Telemetry Transport (MQTT) protocol was used for transmitting the compressed images across the WSN, that offers fast and reliable transmission

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RTL Implementation of image compression techniques in WSN

Cited by 9 publications

References 15 publications

Forest Fire Detection Using Wireless Multimedia Sensor Networks and Image Compression

Forest Fire Detection Using Wireless Multimedia Sensor Networks and Image Compression

Survey: energy efficient protocols using radio scheduling in wireless sensor network

Design of various Image Compression Methods in Wireless Sensor Networks

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