Internet of things and Health Care in Pandemic COVID -19: System requirments evaluation

Naji, Hasan K.; Goga, Nicolae; Karkar, Ammar; Marin, Iuliana; Ali, Haider Abdullah

doi:10.1109/iec52205.2021.9476116

Cited by 8 publications

(3 citation statements)

References 26 publications

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“…The formal (AVISPA) and informal security analyses showed that it was resistant to assaults such as replay, impersonation, and a man in the middle, among others Naji et al (2021) The goal of this investigation was to determine the utility and needs of a remote surveillance system for COVID-19 sufferers…”

Section: Techniques Used In the Iot To Prevent All Covid-19 Broadcast...mentioning

confidence: 99%

Integration of cloud computing with the Internet of things for the treatment and management of the COVID-19 pandemic

Darbandi

Alrasheedi

Alnowibet

et al. 2022

Inf Syst E-Bus Manage

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The globe is now fighting the COVID-19 epidemic, and a cost-effective method to battle the outbreak is urgently required. In this era, the Internet of Things (IoT) offers healthcare systems or checks and discovers patients in epidemics to prevent the virus from spreading. In order to tackle the current COVID-19 pandemic, intelligent health care based on IoT is becoming increasingly vital in better digital technologies. This technology allows gadgets to link hospitals and other predefined sites to tackle this dilemma. The cognitive Internet of Medical Things (IoMT) is a potential technology for quick analysis, dynamic monitoring and control, improved therapy and management, and prevention of viral transmission. This technology can send a message to the hospital immediately in an emergency. Due to the importance of this subject, the influence of IoT-centered innovations in the management of COVID-19 is examined in this article. The three main areas, including early detection, viral prevention, and patient care, are considered in this paper. The results showed that using IoT, such as drones and robots, has been fruitful in reducing contact with patients and identifying disease symptoms. Also, they showed that the IoT wearable gadgets and the cloud platform to store the patient's information have helped doctors track the patient's condition. Keywords COVID-19 management • Internet of things • Coronavirus • Cloud computing • Internet of medical things * Danial Javaheri

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Section: Techniques Used In the Iot To Prevent All Covid-19 Broadcast...mentioning

confidence: 99%

Integration of cloud computing with the Internet of things for the treatment and management of the COVID-19 pandemic

Darbandi

Alrasheedi

Alnowibet

et al. 2022

Inf Syst E-Bus Manage

View full text Add to dashboard Cite

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“…Hasan K. Naji et al [16] provide the results of an online quantitative survey in which 376 people participated. As a result, most healthcare professionals use the automated wearable gadget, helps them do their jobs more efficiently, and makes their jobs easier.…”

Section: Related Workmentioning

confidence: 99%

Smart Vital Signs Monitoring System for Covid-19 Patients in Quarantine

Veeramanikandasamy¹,

Vasudhaa.²,

Rajesh³

2022

2022 7th International Conference on Communication and Electronics Systems (ICCES)

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A healthcare monitoring system based on the Internet of Things has been designed to monitor the vital signs of patients with COVID-19 while they are isolated at home. The complete system is designed using an embedded controller, medical sensors, a mobile application, and a cloud server. This Internet of Medical Things (IoMT) device is used to evaluate COVID-19 patients' critical levels during home isolation by monitoring their heart rate, body temperature, oxygen saturation (S pO 2 ), cough intensity counts and geographic position. This approach enables physicians to assess COVID-19 patients without the need for direct contact, thereby minimizing the risk of infection. An embedded hardware device with internet connectivity collects and displays vital signs of COVID-19 patients and transmits the data to an IoT platform. The cloud layer and smartphone application store COVID-19 patient records via the API interface. Additionally, the Hospital Management S ystem (HMS ) is utilized to manage physician appointments and the prescriptions given to patients. Mobile applications and email notifications are sent to physicians and patients' families in case of an emergency, allowing them to respond quickly. The users can also view their vital signs and an alert message on the OLED screen.

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“…Patients with suspected exposure or symptoms should be identified as soon as possible. In respiratory infections, vital signs such as body temperature, heartbeat, and blood oxygen saturation are acknowledged as crucial strong indicators [2], [3]. Their monitoring is crucial for detecting early physiological abnormalities in patients who are deteriorating.…”

Section: Introductionmentioning

confidence: 99%

Prediction of COVID-19 Patients Recovery using Ensemble Machine Learning and Vital Signs Data Collected by Novel Wearable Device

Naji¹,

Fatlawi²,

Karkar³

et al. 2022

IJACSA

Self Cite

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During the spread of a pandemic such as COVID-19, the effort required of health institutions increases dramatically. Generally, Health systems' response and efficiency depend on monitoring vital signs such as blood oxygen level, heartbeat, and body temperature. At the same time, remote health monitoring and wearable health technologies have revolutionized the concept of effective healthcare provision from a distance. However, analyzing such a large amount of medical data in time to provide the decision-makers with necessary health procedures is still a challenge. In this research, a wearable device and monitoring system are developed to collect real data from more than 400 COVID-19 patients. Based on this data, three classifiers are implemented using two ensemble classification techniques (Adaptive Boosting and Adaptive Random Forest). The analysis of collected data showed a remarkable relationship between the patient's age and chronic disease on the one hand and the speed of recovery on the other. The experimental results indicate a highly accurate performance for Adaptive Boosting classifiers, reaching 99%, while the Adaptive Random Forest got a 91% accuracy metric.

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Internet of things and Health Care in Pandemic COVID -19: System requirments evaluation

Cited by 8 publications

References 26 publications

Integration of cloud computing with the Internet of things for the treatment and management of the COVID-19 pandemic

Integration of cloud computing with the Internet of things for the treatment and management of the COVID-19 pandemic

Smart Vital Signs Monitoring System for Covid-19 Patients in Quarantine

Prediction of COVID-19 Patients Recovery using Ensemble Machine Learning and Vital Signs Data Collected by Novel Wearable Device

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