Incorporating the Markov Chain Model in WBSN for Improving Patients’ Remote Monitoring Systems

Rabei Raad Ali, Salama A. Mostafa, Hairulnizam Mahdin, Aida Mustapha, Saraswathy Shamini Gunasekaran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Wireless body sensor network (WBSN) allows remote monitoring for different types of applications in security, healthcare and medical domains. Medical applications involve monitoring a large number of patients in real-time environments. The WBSNs in such environments have to be efficient and reliable in terms of data transfer rate, accuracy, latency, and power consumption. This work focuses on studying the slotted access protocol variables in the Contention Access Period (CAP) with the acknowledged uplink traffic (nodes-to-coordinator) under the WBSN channel. This paper proposes a Markov Chain model in WBSN (MC-WBSN) for improving the efficiency and reliability of patients’ remote monitoring systems. The application of the model includes propagating human arm sensory data and analyzing the latency, power consumption, throughput, and higher path loss channel of the WBSN. The results show that the hidden nodes have a great impact on WBSNs performance and throughput. This issue is highly associated with the capacity of the transmitted power.

Original languageEnglish
Title of host publicationRecent Advances on Soft Computing and Data Mining - Proceedings of the 4th International Conference on Soft Computing and Data Mining, SCDM 2020
EditorsRozaida Ghazali, Nazri Mohd Nawi, Mustafa Mat Deris, Jemal H. Abawajy
PublisherSpringer
Pages35-46
Number of pages12
ISBN (Print)9783030360559
DOIs
Publication statusPublished - 01 Jan 2020
Event4th International Conference on Soft Computing and Data Mining, SCDM 2020 - Melaka, Malaysia
Duration: 22 Jan 202023 Jan 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume978 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference4th International Conference on Soft Computing and Data Mining, SCDM 2020
CountryMalaysia
CityMelaka
Period22/01/2023/01/20

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

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  • Cite this

    Ali, R. R., Mostafa, S. A., Mahdin, H., Mustapha, A., & Gunasekaran, S. S. (2020). Incorporating the Markov Chain Model in WBSN for Improving Patients’ Remote Monitoring Systems. In R. Ghazali, N. M. Nawi, M. M. Deris, & J. H. Abawajy (Eds.), Recent Advances on Soft Computing and Data Mining - Proceedings of the 4th International Conference on Soft Computing and Data Mining, SCDM 2020 (pp. 35-46). (Advances in Intelligent Systems and Computing; Vol. 978 AISC). Springer. https://doi.org/10.1007/978-3-030-36056-6_4