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Certain Investigations on IoT system for COVID-19

Authors: Sarah Jaafari; Areej Alhasani; Ebtihal alghosn; Rehab alfahhad; Saad Almutairi;

Certain Investigations on IoT system for COVID-19

Abstract

Corona Viruses are a group of viruses that can cause diseases such as colds, severe acute respiratory syndrome (SARS) and the Middle East Respiratory Syndrome (MERS). A new type of corona virus has been discovered after it was identified as the cause of the spread of one of the diseases that started in China in 2019. This disease is considered one of the most dangerous things in the world, which directly affected many areas and led to high financial losses. The risk in this disease lies in its wide spread and the difficulty in dealing with and responding to it. So remote control technologies is the best solution for monitoring the patient's condition and monitoring the change of symptoms. The internet of thing one of modern technology which aims to shares files, software, programs and other tools to allow user to uses the devises with each other to apply the communication between them. it includes many devices communication between them by intelligent decisions. building modern IOT system based smart devices and sensors is the best solution to detect the patient of COVID-19 at real time. The study shows how effective device to detect of COVID-19 patient in IOT system.

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Subjects by Vocabulary

Microsoft Academic Graph classification: Coronavirus disease 2019 (COVID-19) Computer science business.industry Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Disease Computer security computer.software_genre medicine.disease law.invention Intelligent sensor law medicine Middle East respiratory syndrome The Internet Internet of Things business computer Remote control

30 references, page 1 of 3

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[2] . Mehta, Puja, et al. "COVID-19: consider cytokine storm syndromes and immunosuppression." Lancet (London, England) 395.10229 (2020): 1033.

[3] . Pawar, Praveen, and Aditya Trivedi. "Device-to-device communication based IoT system: benefits and challenges." IETE Technical Review 36.4 (2019): 362-374.

[4] . Swaroop, K. Narendra, et al. "A health monitoring system for vital signs using IoT." Internet o f Things 5 (2019): 116-129.

[5] . Duran-Vega, Luis A., et al. "An iot system for remote health monitoring in elderly adults through a wearable device and mobile application." Geriatrics 4.2 (2019): 34.

[6] . Mookherji, Srijanee, and Suresh Sankaranarayanan. "Traffic data classification for security in iot-based road signaling system." Soft Computing in Data Analytics. Springer, Singapore, 2019. 589-599.

[7] . Ahn, Byeong-Gu, Yun-Hong Noh, and Do-Un Jeong. "Smart chair based on multi heart rate detection system." 2015 IEEE SENSORS. IEEE, 2015.

[8] . AlMotiri, Sultan H., Murtaza A. Khan, and Mohammed A. Alghamdi. "Mobile health (m-health) system in the context of IoT." 2016 IEEE 4th international conference on future internet o f things and cloud workshops (FiCloudW). IEEE, 2016.

[9] . Patru, Irina-Ioana, et al. "Smart home IoT system." 2016 15th RoEduNet Conference: Networking in Education and Research. IEEE, 2016.

[10] . Chiuchisan, Iuliana, Hariton-Nicolae Costin, and Oana Geman. "Adopting the internet of things technologies in health care systems." 2014 International Conference and Exposition on Electrical and Power Engineering (EPE). IEEE, 2014. [OpenAIRE]

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    impulse
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    Top 10%
  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    8
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
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