Remote Health Monitoring Using IoT-Based Smart Wireless Body Area Network

Aadil, Farhan; Mehmood, Bilal; Hasan, Najam Ul; Lim, Sangsoon; Ejaz, Sadaf; Jhanjhi, N. Z.

doi:10.32604/cmc.2021.014647

Cited by 19 publications

(7 citation statements)

References 8 publications

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“…The key themes of data incorporation include mining of features, data reduction, and organization. References 11,12 researched energy ingesting and for the optimum next hop selection to route medical data packets to the BS, 13,14 considers two important criteria. Each on‐body sensor calculates link quality and energy utilization.…”

Section: Related Studymentioning

confidence: 99%

IoT‐based energy efficient and longer lifetime compression approach for healthcare applications

Dewan

Ahmad

Rana

et al. 2023

Trans Emerging Tel Tech

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A wireless body area networks (WBANs) is made up of tiny representations of the Internet of Medical Things (IoMT), which may be executed in the body or worn externally. Today, Internet of Things (IoT) has made it feasible to evaluate healthcare. The IoMT sends the patient's condition to the health center through the Internet rather than keeping them in the hospital all the time for therapy. IoT offers wireless connectivity between virtually anything and smart devices on one side. Data must be transferred to a doctor or other practitioner within the allotted time since this network works with medical and critical circumstances; this shows that routing is the most important problem. Routing is therefore viewed as a very significant difficulty in WBANs. The simulation findings show that, for the WBAN under consideration, the IoT‐based stable increased‐throughput multi‐hop protocol for link efficiency protocol has better throughput, end‐to‐end delay, and propagation delay compared to adaptive threshold‐based thermal‐aware energy‐efficient multi‐hop protocol. Higher packet delivery to the sink is a result of longer stability periods, which is very desirable for ongoing patient monitoring during the COVID‐19 pandemic. This research also identifies potential paths for the development of WBANs of the next generation and suggests ways to boost the selected communication systems' productivity in WBAN solutions for health monitoring.

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Section: Related Studymentioning

confidence: 99%

IoT‐based energy efficient and longer lifetime compression approach for healthcare applications

Dewan

Ahmad

Rana

et al. 2023

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…An optimized health monitoring framework was introduced in [ 35 ]. This work consists of entities such as cluster members, cluster heads and core networks.…”

Section: Review Of Related Literaturementioning

confidence: 99%

Blockchain Based Delay and Energy Harvest Aware Healthcare Monitoring System in WBAN Environment

Anbarasan

Jaisankar

2022

Sensors

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Wireless body area networks (WBANs) are a research area that supports patients with healthcare monitoring. In WBAN, the Internet of Things (IoT) is connected with WBAN for a smart/remote healthcare monitoring system in which various medical diseases are diagnosed. Quality of service (QoS), security and energy efficiency achievements are the major issues in the WBAN-IoT environment. Existing schemes for these three issues fail to achieve them since nodes are resource constrained and hence delay and the energy consumption is minimized. In this paper, a blockchain-assisted delay and energy aware healthcare monitoring (B-DEAH) system is presented in the WBAN-IoT environment. Both body sensors and environment sensors are deployed with dual sinks for emergency and periodical packet transmission. Various processes are involved in this paper, and each process is described as follows: Key registration for patients using an extended version of the PRESENT algorithm is proposed. Cluster formation and cluster head selection are implemented using spotted hyena optimizer. Then, cluster-based routing is established using the MOORA algorithm. For data transmission, the patient block agent (PBA) is deployed and authenticated using the four Q curve asymmetric algorithm. In PBA, three entities are used: classifier and queue manager, channel selector and security manager. Each entity is run by a special function, as packets are classified using two stream deep reinforcement learning (TS-DRL) into three classes: emergency, non-emergency and faulty data. Individual packets are put into a separate queue, which is called emergency, periodical and faulty. Each queue is handled using Reyni entropy. Periodical packets are forwarded by a separate channel without any interference using a multi objective based channel selection algorithm. Then, all packets are encrypted and forwarded to the sink nodes. Simulation is conducted using the OMNeT++ network simulator, in which diverse parameters are evaluated and compared with several existing works in terms of network throughput for periodic (41.75 Kbps) and emergency packets (42.5 Kbps); end-to-end delay for periodic (0.036 s) and emergency packets (0.028 s); packet loss rate (1.1%); residual energy in terms of simulation rounds based on periodic (0.039 J) and emergency packets (0.044 J) and in terms of simulation time based on periodic (8.35 J) and emergency packets (8.53 J); success rate for periodic (87.83%) and emergency packets (87.5%); authentication time (3.25 s); and reliability (87.83%).

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“…Dong et al [22] designed a wearable device for continuous blood pressure (CBP) monitoring [23], but it did not keep health data for further study. Aadil et al [24] proposed a wireless body area network (WBAN) for remote health monitoring that utilized the IoT. Li et al [25] created a ZigBee network to connect devices to a base station.…”

Section: Introductionmentioning

confidence: 99%

Private Backend Server Software-Based Telehealthcare Tracking and Monitoring System

Ali

Al_dahan³

2023

Int. J. Onl. Eng.

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In these recent years, the world has witnessed a kind of social exclusion and the inability to communicate directly due to the Corona Virus Covid 19 (COVID-19) pandemic, and the consequent difficulty of communicating with patients with hospitals led to the need to use modern technology to solve and facilitate the problem of people communicating with each other. healthcare has made many remarkable developments through the Internet of things (IOT) and cloud computing to monitor real-time patients' data, which has enabled many patients' lives to be saved. this paper presents the design and implementation of a Private Backend Server Software based on an IoT health monitoring system concerned emergency medical services utilizing biosensors to detect multivital signs of an individual with an ESP32 microcontroller board and IoT cloud. The device displays the vital data, which is then uploaded to a cloud server for storage and analysis over an IoT network. Vital data is received from the cloud server and shown on the IoT medical client dashboard for remote monitoring. The proposed system allows users to ameliorate healthcare jeopardy and minify its costs by recording, gathering, sharing, and analyzing vast biodata streams such as Intensive Care Units (ICU) (i.e., temperature, heartbeat rate, Oxygen level (CO2), etc.), efficiently in real-time. In this proposal, the data will send from sensors fixed in the patient body to the Web and Mobile App continually in real time for collection and analysis.

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Remote Health Monitoring Using IoT-Based Smart Wireless Body Area Network

Cited by 19 publications

References 8 publications

IoT‐based energy efficient and longer lifetime compression approach for healthcare applications

IoT‐based energy efficient and longer lifetime compression approach for healthcare applications

Blockchain Based Delay and Energy Harvest Aware Healthcare Monitoring System in WBAN Environment

Private Backend Server Software-Based Telehealthcare Tracking and Monitoring System

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