Edge Computing Smart Healthcare Cooperative Architecture for COVID-19 Medical Facilities

Authors

Keywords:

smart healthcare, cooperative systems, edge computing, IoT

Abstract

Intelligent healthcare systems are a topic of interest in recent approaches due to novel possibilities created from edge hardware and software development. In 2020, the COVID-19 pandemic displayed the urge to speed up technological systems development to aid medical facilities. In this context, solutions must enhance the experience of both patients and healthcare professionals. Thus, we propose a novel cooperative architecture to improve healthcare facilities involved in pandemic control. On the one hand, this solution helps a faster recognition and link to the patients' data using reality augmentation resources. On the other hand, it helps monitor the conditions of medical professionals working in the facility and exposed to contamination danger.

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Author Biographies

Mateus Coelho Silva, Universidade Federal de Ouro Preto

Mateus Coelho Silva is currently a Ph.D. candidate in Computer Science at the Federal University of Ouro Preto. His current research interests include Edge AI, Cyber-Physical Systems, IoT, Wearable Devices and Robotics.

Andrea Gomes Campos Bianchi, Universidade Federal de Ouro Preto

Andrea G. Campos Bianchi is an Associate Professor at the Computing Department at the Federal University of Ouro Preto (UFOP). She obtained her Ph.D. in Computational Physics at São Paulo University (USP), Brazil, and acted as a postdoc at Lawrence National Berkeley Laboratory in Data Analytics and Visualization Group. She has experience in computer vision and machine learning systems, building tools capable of extracting knowledge of images. Her research interests are image processing and analysis, pattern recognition, machine learning.

Servio Pontes Ribeiro, Universidade Federal de Ouro Preto

Servio Pontes Ribeiro is currently a Full Professor in the Biology Department at the Federal University of Ouro Preto (UFOP). He received his Ph.D. Degree in Ecology from Imperial College at Silwood Park, University of London (1998). He has experience in Ecology and acts on various subjects, including Plant-Insect Interaction and Evolutive Ecology in Forest Canopies, Bioindication of degraded areas, Ecohealth, and Evolutive Ecology of Parasites and Viruses

Jorge Sá Silva, Universidade de Coimbra

Jorge Sa Silva received his PhD in Informatics Engineering in 2001 from the University of Coimbra, where is Associate Professor with Habilitation at the Department of Electrical and Computer Engineering of the Faculty of Sciences and Technology of the University of Coimbra and a Senior Researcher of Laboratory of Communication and Telematics of Centre of Informatics Engineering of University of Coimbra, Portugal. His main research interests are Internet of Things, Network Protocols, Machine to Machine, and Wireless Sensor Networks. He is a senior member of IEEE, and
he is a licensed Professional Engineer.

Ricardo Augusto Rabelo Oliveira, Universidade Federal de Ouro Preto

Ricardo A. Rabelo Oliveira received his Ph.D. degree in Computer Science from the Federal University of Minas Gerais in 2008. Nowadays he is an Associate Professor in the Computing Department at the Federal University of Ouro Preto. Has experience in Computer Science, acting on the following subjects: Wavelets, Neural Networks, 5G, VANT, and Wearables.

References

V. Vippalapalli and S. Ananthula, “Internet of things (iot) based

smart health care system,” in 2016 International Conference on Signal

Processing, Communication, Power and Embedded System (SCOPES),

pp. 1229–1233, IEEE, 2016.

S. Sivagami, D. Revathy, and L. Nithyabharathi, “Smart health care

system implemented using iot,” International Journal of Contemporary

Research in Computer Science and Technology, vol. 2, no. 3, pp. 641–

, 2016.

M. Alhussein and G. Muhammad, “Automatic voice pathology moni-

toring using parallel deep models for smart healthcare,” IEEE Access,

vol. 7, pp. 46474–46479, 2019.

Z. Chen, S. He, F. Li, J. Yin, and X. Chen, “Mobile field hospitals, an

effective way of dealing with covid-19 in china: sharing our experience,”

BioScience Trends, 2020.

A. S. Kliger and J. Silberzweig, “Mitigating risk of covid-19 in dialysis

facilities,” Clinical Journal of the American Society of Nephrology,

vol. 15, no. 5, pp. 707–709, 2020.

J. Wong, Q. Y. Goh, Z. Tan, S. A. Lie, Y. C. Tay, S. Y. Ng, and C. R.

Soh, “Preparing for a covid-19 pandemic: a review of operating room

outbreak response measures in a large tertiary hospital in singapore,”

Canadian Journal of Anesthesia/Journal canadien d’anesthésie, pp. 1–

, 2020.

V. N. Prachand, R. Milner, P. Angelos, M. C. Posner, J. J. Fung,

N. Agrawal, V. Jeevanandam, and J. B. Matthews, “Medically-necessary,

time-sensitive procedures: A scoring system to ethically and efficiently

manage resource scarcity and provider risk during the covid-19 pan-

demic,” Journal of the American College of Surgeons, 2020.

S. Shah, K. Majmudar, A. Stein, N. Gupta, S. Suppes, M. Karamanis,

J. Capannari, S. Sethi, and C. Patte, “Novel use of home pulse oximetry

monitoring in covid-19 patients discharged from the emergency depart-

ment identifies need for hospitalization,” Academic Emergency Medicine,

vol. n/a, no. n/a.

S. B. Baker, W. Xiang, and I. Atkinson, “Internet of things for smart

healthcare: Technologies, challenges, and opportunities,” IEEE Access,

vol. 5, pp. 26521–26544, 2017.

A. Rizwan, A. Zoha, R. Zhang, W. Ahmad, K. Arshad, N. A. Ali,

A. Alomainy, M. A. Imran, and Q. H. Abbasi, “A review on the role of

nano-communication in future healthcare systems: A big data analytics

perspective,” IEEE Access, vol. 6, pp. 41903–41920, 2018.

G. Manogaran, R. Varatharajan, D. Lopez, P. M. Kumar, R. Sun-

darasekar, and C. Thota, “A new architecture of internet of things and

big data ecosystem for secured smart healthcare monitoring and alerting

system,” Future Generation Computer Systems, vol. 82, pp. 375–387,

M. S. Hossain, G. Muhammad, and A. Alamri, “Smart healthcare

monitoring: A voice pathology detection paradigm for smart cities,”

Multimedia Systems, vol. 25, no. 5, pp. 565–575, 2019.

M. A. Salahuddin, A. Al-Fuqaha, M. Guizani, K. Shuaib, and F. Sallabi,

“Softwarization of internet of things infrastructure for secure and smart

healthcare,” arXiv preprint arXiv:1805.11011, 2018.

S. Tuli, N. Basumatary, S. S. Gill, M. Kahani, R. C. Arya, G. S. Wander,

and R. Buyya, “Healthfog: An ensemble deep learning based smart

healthcare system for automatic diagnosis of heart diseases in integrated

iot and fog computing environments,” Future Generation Computer

Systems, vol. 104, pp. 187–200, 2020.

M. C. Silva, V. J. Amorim, S. P. Ribeiro, and R. A. Oliveira, “Field

research cooperative wearable systems: Challenges in requirements,

design and validation,” Sensors, vol. 19, no. 20, p. 4417, 2019.

C. Long, Y. Cao, T. Jiang, and Q. Zhang, “Edge computing framework

for cooperative video processing in multimedia iot systems,” IEEE

Transactions on Multimedia, vol. 20, no. 5, pp. 1126–1139, 2017.

M. S. Mahmoud and A. A. Mohamad, “A study of efficient power

consumption wireless communication techniques/modules for internet

of things (iot) applications,” 2016.

C. Chang, S. N. Srirama, and R. Buyya, “Indie fog: An efficient fog-

computing infrastructure for the internet of things,” Computer, vol. 50,

no. 9, pp. 92–98, 2017.

M. Silva., R. Oliveira., T. D’Angelo., C. Garrocho., and V. Amorim.,

“Faceshield hud: Extended usage of wearable computing on the covid-

frontline,” in Proceedings of the 23rd International Conference

on Enterprise Information Systems - Volume 1: ICEIS,, pp. 893–900,

INSTICC, SciTePress, 2021.

S. Majumder, T. Mondal, and M. J. Deen, “Wearable sensors for remote

health monitoring,” Sensors, vol. 17, no. 1, p. 130, 2017.

K. Cao, G. Xu, J. Zhou, T. Wei, M. Chen, and S. Hu, “Qos-adaptive

approximate real-time computation for mobility-aware iot lifetime opti-

mization,” IEEE Transactions on Computer-Aided Design of Integrated

Circuits and Systems, vol. 38, no. 10, pp. 1799–1810, 2018.

M. Silva and R. Oliveira, “Analyzing the effect of increased distribution

on a wearable appliance,” in 2019 IEEE 43rd Annual Computer Software

and Applications Conference (COMPSAC), vol. 2, pp. 13–18, IEEE,

Published

2022-07-07

How to Cite

Coelho Silva, M., Gomes Campos Bianchi, A., Pontes Ribeiro, S., Sá Silva, J., & Augusto Rabelo Oliveira, R. (2022). Edge Computing Smart Healthcare Cooperative Architecture for COVID-19 Medical Facilities. IEEE Latin America Transactions, 20(10), 2229–2236. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/6843