IoT-based cloud framework to control Ebola virus outbreak
Open accessAbstract
Ebola is a deadly infectious virus that spreads very quickly through human-to-human transmission and sometimes death. The continuous detection and remote monitoring of infected patients are required in order to prevent the spread of Ebola virus disease (EVD). Healthcare services based on Internet of Things (IoT) and cloud computing technologies are emerging as a more effective and proactive solution which provides remote continuous monitoring of patients. A novel architecture based on Radio Frequency Identification Device (RFID), wearable sensor technology, and cloud computing infrastructure is proposed for the detection and monitoring of Ebola infected patients. The aim of this work is to prevent the spreading of the infection at the early stage of the outbreak. The J48 decision tree is used to evaluate the level of infection in a user depending on his symptoms. RFID is used to automatically sense the close proximity interactions (CPIs) between users. Temporal Network Analysis (TNA) is applied to describe and monitor the current state of the outbreak using the CPI data. The performance and accuracy of our proposed model are evaluated on Amazon EC2 cloud using synthetic data of two million users. Our proposed model provided 94 % accuracy for the classification and 92 % of the resource utilization.
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A system integrating IoMT architecture and technology comprising RFID, WBAN, and cloud services can provide reliable healthcare monitoring and early-stage detection for pandemic diseases.
“A system that integrates IoMT architecture and technology comprises of RFID, WBAN, and cloud services is able to provide a reliable healthcare monitoring and early-stage detection system for pandemic diseases (Sareen et al., 2016).”
From IoMT amid COVID-19 pandemic: Application, architecture, technology, and security (2021) · cites this paper as Sareen et al., 2016
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IoMT amid COVID-19 pandemic: Application, architecture, technology, and security
Mohd Aman, A. H., Hassan, W. H., Sameen, S., Attarbashi, Z. S., Alizadeh, M., & Latiff, L. A. (2021) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2020.102886 · Cited by 237 · see citing works
- Authors
- Sareen, S., Sood, S. K., & Gupta, S. K.
- Affiliations
- Guru Nanak Dev University (IN)
- Corresponding author
- Sareen, Sanjay
- Venue
- Journal of Ambient Intelligence and Humanized Computing
- Published
- 2016-10-20
- Volume
- 9
- Issue
- 3
- Pages
- 459-476
- ISSN
- 1868-5137 (ISSN-L)
- 1868-5145
- PMC
- PMC7091278
- OpenAlex
- W2533974848
- Cited by
- 123
- References
- 61
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 7 · 2023: 12 · 2022: 18 · 2021: 44 · 2020: 16 · 2019: 8 · 2018: 8 · 2017: 3
- FWCI
- 14.17
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Ambient Intelligence and Humanized Computing (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Arduino and IoT Applications
- Keywords
- Ebola virus disease, outbreak detection, remote patient monitoring, Internet of Things, cloud computing, RFID, wearable sensors, temporal network analysis, J48 decision tree
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