Energy Scavenging Methods for WBAN Applications: A Review

Demir, Süleyman Mahircan; Al‐Turjman, Fadi; Muhtaroğlu, Ali

doi:10.1109/jsen.2018.2851187

Cited by 52 publications

(34 citation statements)

References 45 publications

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“…If the range of remitting data is less than the threshold value, then choice to select a new route for next sensor node is reduced. Also the fewer the number of neighbors, the lower the probability of packe to arrive at the destination within a certain hop count [5]. iii.…”

Section: Routing Protocol Design Issuesmentioning

confidence: 99%

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Wireless Body Area Network: A Review on Issues, Routing Techniques and Various Applications

Anand¹,

Malik²

2018

IJTSRD

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Advancements in recent wireless technology, integrated circuit, electronic devices and autonomous sensing of physiological parameters, gave the birth of human monitoring system or short range wireless communication network, called Wireless Body Area Networks (WBANs). It is one of the major applications of Wireless Sensor Networks (WSNs), used in medical and as well as non-medical field. In WBAN, various tiny, intelligent, low powered and invasive/non-invasive sensor nodes are placed inside or outside the human body to collect the data. These sensor nodes are referred to as independent device with limited communication capabilities. Deployed sensor nodes are intended to early detection of various types of life threatening diseases viz. cancer, asthma etc., using different types of biomedical sensor nodes like ECG (Electrocardiogram), EEG (Electroencephalogram), pulse rate, temperature, blood pressure etc.

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Section: Routing Protocol Design Issuesmentioning

confidence: 99%

“…It is very difficult to design a QoS aware routing protocol, using variety of modules. These routing protocols are mainly suffering from high complexity [5]. ii.…”

Section: Classification Of Wbans Routing Protocolmentioning

confidence: 99%

Wireless Body Area Network: A Review on Issues, Routing Techniques and Various Applications

Anand¹,

Malik²

2018

IJTSRD

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“…Before ten years, when 15% of the share had fallen, then the developed countries contribute to the healthcare sector for curing chronic diseases and conventionally emphasize the healing of disease. Although many people seek care at hospitals due to the lack of personnel and supplies at health centers, almost ensuring that health centers will continue to lack the necessary resources (1)(2)(3)(4)(5)(6). But the problem of traveling along with expenses led to the rise in the number of deaths of the patients.…”

Section: Introductionmentioning

confidence: 99%

An Energy Efficient Health Monitoring System using Relay Node in Wireless Body Area Networks

Bilandi¹,

Verma²,

Dhir³

2020

EAI Endorsed Transactions on Pervasive Health and Technology

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INTRODUCTION: In today's world, Wireless Body Area Networks (WBAN) has emanated as a budding field within the healthcare scenario for monitoring, detecting, predicting, and diagnosing various fatal diseases such as cancer, cardiovascular, diabetes and other infectious diseases such as tuberclosis, pneumonia and ebola. It is an assemblage of bio-sensors which could be put on or embedded in a patient's body to surveil the functionality of various body organs. OBJECTIVES: The purpose of that proposed protocol is to select the relay node and record the various physiological parameters like body temperature, blood pressure, rate of blood sugar of human being. Energy consumption is a major hurdle in WBAN as replacing as well as recharging the nodes pinioned to human body may bring about discomfort to the patient. Therefore, in this work, the emphasis is given to improve the performance of WBAN i.e. network lifetime, greater mobility, stability and energy efficiency. METHODS: To find the shortest energy-efficient route and avoid any kind of relay node failure, a novel routing scheme called Enhanced Opportunistic Protocol using Relay nodes (E-OPR) is proposed for data routing. CONCLUSION: Finally, an enhanced opportunistic protocol using relay node in WBAN has been proposed for cost effective real time health monitoring system. The proposed solution seems to give better results as compare single-hop, multi-hop routing protocols in terms of throughput, network lifetime, energy consumption and path loss.

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“…Both academic and industrial communities have recognized the significant attention given to future WLANs (IEEE 802.11) for IoT-based eHealth systems. One of their motivating services is the promisingly high throughput to support extensively advanced technologies even in densely deployed devices environment [10,11]. However, unlicensed WLAN would face huge challenges in the future to access the shared channel resources, especially for highly dense IoT device deployments.…”

Section: Introductionmentioning

confidence: 99%

Q-learning-enabled channel access in next-generation dense wireless networks for IoT-based eHealth systems

Ali

Qadri

Zikria

et al. 2019

J Wireless Com Network

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One of the key applications for the Internet of Things (IoT) is the eHealth service that targets sustaining patient health information in digital environments, such as the Internet cloud with the help of advanced communication technologies. In eHealth systems, wireless networks, such as wireless local area networks (WLAN), wireless body sensor networks (WBSN), and wireless medical sensor networks (WMSNs), are prominent technologies for early diagnosis and effective cures. The next generation of these wireless networks for IoT-based eHealth services is expected to confront densely deployed sensor environments and radically new applications. To satisfy the diverse requirements of such dense IoT-based eHealth systems, WLANs will have to face the challenge of assisting medium access control (MAC) layer channel access in intelligent adaptive learning and decision-making. Machine learning (ML) offers services as a promising machine intelligence tool for wireless-enabled IoT devices. It is anticipated that upcoming IoT-based eHealth systems will independently access the most desired channel resources with the assistance of sophisticated wireless channel condition inference. Therefore, in this study, we briefly review the fundamental models of ML and discuss their employment in the persuasive applications of IoT-based systems. Furthermore, we propose Q-learning (QL) that is one of the reinforcement learning (RL) paradigms as the future ML paradigm for MAC layer channel access in next-generation dense WLANs for IoT-based eHealth systems. Our goal is to contribute to refining the motivation, problem formulation, and methodology of powerful ML algorithms for MAC layer channel access in the framework of future dense WLANs. This paper also presents a case study of next-generation WLAN IEEE 802.11ax that utilizes the QL algorithm for intelligent MAC layer channel access. The proposed QL-based algorithm optimizes the performance of WLAN, especially for densely deployed devices environment.

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Energy Scavenging Methods for WBAN Applications: A Review

Cited by 52 publications

References 45 publications

Wireless Body Area Network: A Review on Issues, Routing Techniques and Various Applications

Wireless Body Area Network: A Review on Issues, Routing Techniques and Various Applications

An Energy Efficient Health Monitoring System using Relay Node in Wireless Body Area Networks

Q-learning-enabled channel access in next-generation dense wireless networks for IoT-based eHealth systems

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