An Adaptive Fuzzy-Based Clustering Model for Healthcare Wireless Sensor Networks

Chithaluru, Premkumar; Jena, Lambodar; Singh, Debabrata; Teja, K. M. V. Ravi

doi:10.1007/978-981-19-6068-0_1

Cited by 7 publications

(9 citation statements)

References 24 publications

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“…The proposed work in [11], was based on the TOSSIM tool to solve the time delay and power consumption through the WSN nodes' clustering. A fuzzy-neural hybrid model was introduced to improve the network throughput, which led to an increase in the WSN lifetime and decreased message delay.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation of Multimedia Data Transmission Over WSN Based on MATLAB/SIMULINK

Dawood¹,

Abdul-Aziz²,

Daood³

et al. 2023

IJCDS

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The wireless sensor network (WSN) design requires investigating the effect of the transmit/receive operations on data quality. Having a convenient simulation model that facilitates and speeds up the work is a challenging task. The MATLAB/SIMULINK is considered as a handy tool that mimics real events for many applications. Unfortunately, the complete WSN model for multidimensional signals is not provided. Therefore, this paper introduces the MATLAB/SIMULINK model to deal with 1-D and 2-D signals in WSN. Many simulation blocks and codes have been programmed in this work to facilitate multimedia transmission over the WSN. The proposed multimedia WSN (MWSN) model will help WSN designers to plan and test their topology, taking into account most parameters and effects before implementing the network in real life. Hence, the WSN design time and cost will be reduced, as well as the malfunctioning will be avoided. Noise ,interference and path loss were the major parameters that affect the quality of the transferred data. Those parameters are experimented in this work using different multimedia signals and the received signal quality is measured using peak signal-to-noise ratio (PSNR), and bit error rate (BER). Additionally, different channels that add many levels of interference and signal-to-noise ratio are used to imitate reality. The ultimate goal of this research is to model the physical layer and modify the internal architecture of WSN nodes to deal with multimedia signals. Therefore, floating-point re-quantization and buffers are invoked to cope with the design requirements. The resultant simulation model is designed to be scalable and easy to expand for many different WSN topologies. The proposed MWSN has visualization features, in addition to the assessment tools that simplify results' analysis. Besides, the availability of tuning its parameters can help researchers to adopt it for different channels.

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Section: Literature Reviewmentioning

confidence: 99%

Simulation of Multimedia Data Transmission Over WSN Based on MATLAB/SIMULINK

Dawood¹,

Abdul-Aziz²,

Daood³

et al. 2023

IJCDS

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“…The sensor node's responsibility is to collect and transmit information to the cluster's CH. Furthermore, during the clustering of the sensor nodes, the physical location of the sensor nodes must be communicated to all sensor nodes in the nearby clusters in order to inform the clusters to combine the sensor nodes during the clustering process 7 . The BS node is in charge of selecting sensor nodes within clusters to sense information from the environment and transmit it to the corresponding CH.…”

Section: Introductionmentioning

confidence: 99%

An opportunistic energy‐efficient dynamic self‐configuration clustering algorithm in WSN‐based IoT networks

Tumula,

Ramadevi,

Padmalatha

et al. 2023

Int J Communication

Self Cite

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SummaryThe demand for the Internet of Things (IoT) has significantly increased in the current scenario; specific sectors that require IoT include industrial automation, home control, health care applications, military and surveillance applications, habitat monitoring, and nanoscopic sensor applications. The use of optimal wireless sensor networks (WSNs) in transmission techniques has resulted in their involvement. A WSN is made up of thousands of randomly distributed sensor nodes that sense and transmit environmental data such as temperature, pressure, humidity, light, and sound. One of the most important requirements when using these sensor nodes is energy. As a result, it has become a major area of research in recent years; additionally, several design techniques and protocols have been presented in the last decade, particularly for IoT‐based applications. As a result, the systemization of an energy‐optimized WSN in dynamic functional conditions with automatic self‐configuration of sensor nodes is a critical goal. This paper proposed an opportunistic energy‐efficient dynamic self‐configuration routing (OEDSR) algorithm for IoT‐based applications. Initially, the optimal route to the base station (BS) is calculated by using the residual energy and mobility factor of the sensor nodes obtained through a routing tree model based on graph theory. To reduce the number of connections, an optimal path is determined based on dynamic cluster generation through a hierarchical tree architecture. Finally, the network‐related parameters, such as throughput, delay and packet delivery ratio (PDR), are compared with the peer existing routing protocols to depict the efficiency of the OEDSR protocol.

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“…The advent of Wireless Sensor Networks (WSNs) has ushered in a new era in the healthcare industry, marking a significant shift towards more efficient, reliable, and accessible patient care [6] [7]. The integration of WSNs in healthcare systems transcends traditional boundaries, offering innovative solutions for remote health monitoring and data management [] [9].…”

Section: Introductionmentioning

confidence: 99%

“…This paradigm shift not only enhances the quality of patient care but also optimizes resource allocation and operational efficiencies within healthcare settings [10]. Central to this transformation is the capability of WSNs to facilitate real-time data acquisition and transmission, enabling continuous monitoring of patients' health parameters without geographical limitations [6]. The deployment of these networks in medical environments, ranging from hospitals to remote patient monitoring, underscores their potential in managing a broad spectrum of healthcare needs [7].…”

Section: Introductionmentioning

confidence: 99%

“…This paper aims to explore the multifaceted role of Wireless Sensor Networks in healthcare, highlighting their impact on improving patient outcomes, reducing healthcare costs, and expanding the reach of medical services [9]. Through a detailed examination of current research and developments in the field, this study underscores the transformative potential of WSNs in reshaping the healthcare landscape [6] [7][8] [9].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An efficient monitoring of HELLP syndrome pre-eclampsia in wireless sensors networks

ullah,

Young,

khan

et al. 2023

Preprint

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This paper explores the application of wireless sensing using 5G technology in the 4.8 GHz C-band, a significant step forward in healthcare innovation. It focuses on the application of wireless sensing to monitor HELLP syndrome in cases of pre-eclampsia, showcasing how Wireless Sensor Networks (WSNs), enhanced by 5G's high-speed capabilities, substantially improve real-time data transmission and healthcare decision-making. The integration of WSNs with 5G technology enables non-invasive, continuous patient monitoring, providing advanced solutions for remote health surveillance and efficient data management in critical healthcare situations. Specifically, the study highlights the use of a wireless transceiver in indoor environments to monitor various body movements, including those indicative of HELLP syndrome symptoms. These movements generate unique wireless data, thus enriching the understanding of wireless channel information. The research explores deep learning models such as ANN, CNN, and especially VGGNet, which achieved a notable 99.26% accuracy in classifying patient activities. Additionally, the paper discusses model optimization, emphasizing the need for adjustments in parameters such as batch sizes and hidden units to enhance performance. The study's outcomes, evaluated using metrics such as accuracy, recall, precision, specificity, and F-measure, demonstrate the superior performance of VGGNet compared to other classifiers. These findings underscore the potential of integrating advanced technologies like WSNs and 5G in healthcare, highlighting their role in creating more effective, reliable, and patient-centric healthcare systems

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An Adaptive Fuzzy-Based Clustering Model for Healthcare Wireless Sensor Networks

Cited by 7 publications

References 24 publications

Simulation of Multimedia Data Transmission Over WSN Based on MATLAB/SIMULINK

Simulation of Multimedia Data Transmission Over WSN Based on MATLAB/SIMULINK

An opportunistic energy‐efficient dynamic self‐configuration clustering algorithm in WSN‐based IoT networks

An efficient monitoring of HELLP syndrome pre-eclampsia in wireless sensors networks

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