Dual Band RFID-Based Blood Glucose Monitoring System in Wireless Sensor Network Platform

Hamid, Shabinar Abdul; Ismail, Widad; Zulkifli, Che Zalina; Abdullah, Syahrul Afzal Che

doi:10.1007/s11277-018-5906-z

Cited by 12 publications

(1 citation statement)

References 13 publications

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“…Tags [14] are small components that consist of integrated circuits connected to an antenna and a small amount of memory to store data. In practice, problems of collisions and interference are mainly related to the deployment of the tags and readers [15].…”

Section: Introductionmentioning

confidence: 99%

FTSMAC: A Multi-Channel Hybrid Reader Collision Avoidance Protocol for RFID Network

Mafamane

Mansour

Ouadou

et al. 2021

JSAN

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Due to the emergence of the Internet of Things, the need for effective identification and traceability has increased. Radio-frequency identification (RFID), a simple and cheap approach for gathering information, has therefore drawn the attention of research communities. However, this system suffers from problems caused by high density, such as collisions and duplication. Thus, the deployment of RFID is more effective in a dense environment where it may improve overage and delays. A wide range of solutions have been proposed; however, the majority of these are based on the application context. In this paper, we propose a general MAC layer protocol FTSMAC (Frequency Time Scheme MAC) in which the spectrum frequency is efficiently used by dividing the signal into different time slots via a messaging mechanism used by RFID readers. This limits the collisions in high-density RFID deployment that affect the performance of the system. Thus, our solution allows the communication system to converge to a stable state within a convenient time.

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Section: Introductionmentioning

confidence: 99%

FTSMAC: A Multi-Channel Hybrid Reader Collision Avoidance Protocol for RFID Network

Mafamane

Mansour

Ouadou

et al. 2021

JSAN

View full text Add to dashboard Cite

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Intelligent Healthcare System Using Emerging Technologies: A Comprehensive Survey

Mohapatra,

Mohanty,

Maharana

et al. 2024

Lecture Notes in Networks and Systems

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An Intelligent and Energy-Efficient Wireless Body Area Network to Control Coronavirus Outbreak

2021

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The coronaviruses are a deadly family of epidemic viruses that can spread from one individual to another very quickly, infecting masses. The literature on epidemics indicates that the early diagnosis of a coronavirus infection can lead to a reduction in mortality rates. To prevent coronavirus disease 2019 (COVID-19) from spreading, the regular identification and monitoring of infected patients are needed. In this regard, wireless body area networks (WBANs) can be used in conjunction with machine learning and the Internet of Things (IoT) to identify and monitor the human body for health-related information, which in turn can aid in the early diagnosis of diseases. This paper proposes a novel coronavirus-body area network (CoV-BAN) model based on IoT technology as a real-time health monitoring system for the detection of the early stages of coronavirus infection using a number of wearable biosensors to examine the health status of the patient. The proposed CoV-BAN model is tested with five machine learning-based classification methods, including random forest, logistic regression, Naive Bayes, support vector machine and multi-layer perceptron classifiers, to optimize the accuracy of the diagnosis of COVID-19. For the long-term sustainability of the sensor devices, the development of energy-efficient WBAN is critical. To address this issue, a long-range (LoRa)-based IoT program is used to receive biosensor signals from the patient and transmit them to the cloud directly for monitoring. The experimental results indicate that the proposed model using the random forest classifier outperforms models using the other classifiers, with an average accuracy of 88.6%. In addition, power consumption is reduced when LoRa technology is used as a relay node.

show abstract

Dual Band RFID-Based Blood Glucose Monitoring System in Wireless Sensor Network Platform

Cited by 12 publications

References 13 publications

FTSMAC: A Multi-Channel Hybrid Reader Collision Avoidance Protocol for RFID Network

FTSMAC: A Multi-Channel Hybrid Reader Collision Avoidance Protocol for RFID Network

Intelligent Healthcare System Using Emerging Technologies: A Comprehensive Survey

An Intelligent and Energy-Efficient Wireless Body Area Network to Control Coronavirus Outbreak

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