Medical images transmission over Wireless Multimedia Sensor Networks with high data rate

Kasban, H.; Nassar, Sabry S.; El‐Bendary, Mohsen A. M.

doi:10.1007/s10470-021-01854-7

Cited by 24 publications

(6 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, the outcomes generated by ML systems are often non-uniform and contingent on the context. Despite the growing prevalence of such systems in various domains [20][21] [22], there is a conspicuous absence of established frameworks addressing the need for a standardized approach to organize and manage the diverse data outputs of ML models [23] [24] in this specific application, as documented in the existing literature.…”

Section: Framework Of Saltus For Handling Big Datamentioning

confidence: 99%

Saltus - “A Sudden Transition” Empowered by Federated Learning for Efficient Big Data Handling in Multimedia Sensor Networks

Pillai,

Sha

et al. 2024

Preprint

View full text Add to dashboard Cite

In the realm of sensor networks, the substantial rise in multimedia data production, covering audio, video, and acoustic measurements, has expanded the scale of big data. Multimedia Sensor Networks (MSN) excel in managing diverse sensor outputs, representations, and encoding across domains. Existing models for event detection in sensor networks fall short in handling the sheer volume and speed of these measurements from a Big Data perspective. This research work introduces “Saltus,” a model that aligns multimedia data from sensor networks to a standardized feature space. Saltus employs a machine learning-centric architecture to enhance data analysis possibilities. Crucially, the model integrates federated learning to address the evolving landscape of sensor networks. This approach optimizes the collaborative learning capabilities by allowing distributed nodes to train machine learning models locally, preserving data privacy. Saltus emerges as a solution that not only streamlines multimedia data processing but also establishes a more secure and privacy-preserving analytics framework in large-scale sensor networks. The model signifies a step forward in integrating multimedia data into an easily analyzable format, leveraging the advantages of federated learning in big data analytics.

show abstract

Section: Framework Of Saltus For Handling Big Datamentioning

confidence: 99%

Saltus - “A Sudden Transition” Empowered by Federated Learning for Efficient Big Data Handling in Multimedia Sensor Networks

Pillai,

Sha

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…For instance, H. Kasban et al propounded a medical image transmission over a wireless multimedia sensor network scheme [9]. The researchers sought to establish a secure wireless channel for transmitting medical images, primarily focusing on maintaining error performance.…”

Section: Introductionmentioning

confidence: 99%

“…In their study of audio watermarking, the researchers employed the Singular Value Decomposition (SVD) method to conceal the images as a watermark within the audio signal. The researcher's main aim in [9] was to develop the dynamic/multi-secret key technique, experiments carried out on MRI and X-Ray images, and reduce energy consumption as tasks were executed at a slower speed. Sengupta et al propose an efficient security approach for safeguarding compressed healthcare images through structural obfuscation and hardware steganography [10].…”

Section: Introductionmentioning

confidence: 99%

Image encryption scheme using a new 4-D chaotic system with a cosinoidal nonlinear term in WMSNs

Fan,

Verma,

Long

et al. 2024

Phys. Scr.

View full text Add to dashboard Cite

To protect the sensitive data captured in the wireless media sensor networks (WMSNs), this paper propounds a novel data encryption scheme by employing a new chaotic system and the semi-tensor product compressive sensing model driven by a linear congruence generator. In this scheme, the coefficients yielded by sparsely decomposing the plaintext image onto a wavelet packet basis are firstly compressed using a key-controlled measurement matrix. To minimize the threat of various attacks, the compressed image is then subjected to bidirectional diffusion manipulation to conceal its statistical properties under the control of chaotic sequences. Additionally, it is worth explaining that a lightweight 4-D chaotic system with only one nonlinear term is designed to accommodate the resource-constrained situation in WMSNs. Finally, theoretical analysis and investigations affirm its significant enhancement in visual security, compressibility, and encryption efficiency. Moreover, the proposed scheme is significantly superior to existing relevant encryption ones.

show abstract

“…The image compression over wireless networks has been studied [5][6][7][8][9][10][11][12]. Our work in [12] focused on the wireless transmission of compressed images using only the DFT as a basis function in the OFDMA system.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of wireless transmission of compressed images using DCT‐OFDMA system with different compression schemes

Soufy

Al‐Ashwal

Al-Kamali

et al. 2023

The Journal of Engineering

View full text Add to dashboard Cite

Transmitting images over an Orthogonal Frequency Division Multiplexing Access (OFDMA) system poses a significant challenge. The process entails sending a substantial amount of data, which consumes a significant amount of bandwidth. Consequently, compressing the transmitted image becomes essential to reduce the required bandwidth. The aim of this paper is to examine and analyse the wireless transmission of a compressed image via Discrete Cosine Transform (DCT‐OFDMA). A comparison is made with Discrete Fourier Transform (DFT‐OFDMA), across various subcarrier mapping schemes (localized and inter‐leaved), and different modulation schemes (16 Quadrature Amplitude Modulation (16QAM) and Quadrature Phase Shift Keying (QPSK)) using vehicular A, Stanford University Interim (SUI3), and uniform channel models. To evaluate the performance of the system, the minimum Signal‐to‐Noise Ratio (SNR) necessary to recover the transmitted compressed image is calculated. This work considers nine standard compression techniques. The results are carried out using the MATLAB simulator. According to the simulation results, the minimum SNR required to recover the transmitted compressed image was found to be 19 dB. This result was achieved when using Discrete Cosine Transform‐Loaclized‐Orthogonal Frequency Division Multiplexing Access (DCT‐LOFDMA) with QPSK modulation and set partitioning in hierarchical trees (SPIHT) compression method over the SUI3 channel model. Moreover, it was observed that the DCT‐LOFDMA and DFT‐IOFDMA systems attained equal SNR while utilizing the SPIHT_3D compression technique and QPSK modulation on the SUI3 channel model. Overall, the results suggest that the performance of DCT‐based localized OFDMA is somewhat superior to DFT‐based localized OFDMA, particularly when utilizing the SUI3 channel model and the QPSK modulation scheme. Therefore, it is feasible to transmit and receive a compressed image effectively over an OFDMA system with DCT.

show abstract

Medical images transmission over Wireless Multimedia Sensor Networks with high data rate

Cited by 24 publications

References 21 publications

Saltus - “A Sudden Transition” Empowered by Federated Learning for Efficient Big Data Handling in Multimedia Sensor Networks

Saltus - “A Sudden Transition” Empowered by Federated Learning for Efficient Big Data Handling in Multimedia Sensor Networks

Image encryption scheme using a new 4-D chaotic system with a cosinoidal nonlinear term in WMSNs

Performance analysis of wireless transmission of compressed images using DCT‐OFDMA system with different compression schemes

Contact Info

Product

Resources

About