Internet of Things Concept in the Context of the COVID-19 Pandemic: A Multi-Sensor Application Design

Lavric, Alexandru; Petrariu, Adrian I.; Mutescu, Partemie-Marian; Coca, Eugen; Popa, Valeríu

doi:10.3390/s22020503

Cited by 19 publications

(12 citation statements)

References 37 publications

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“…The technologies have the potential to provide significant benefits, such as remote monitoring of the symptoms. The data acquired utilizing the created IoT wearable gadget will aid us in completely comprehending the COVID-19 virus's propagation (Lavric et al 2022). IoT technology can potentially be tremendously helpful in combating this epidemic; however, it is vital to address data privacy (Yang et al 2021).…”

Section: Implementation Smart Braceletsmentioning

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: Implementation Smart Braceletsmentioning

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 IoT concept is usually implemented by means of sensors that are able to transmit information in a wireless network configuration. Applications based on wireless sensor networks (WSN) technologies range from healthcare systems, the military, smart city, and smart homes to agricultural applications [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ] focused on increasing efficiency and improving resource allocation.…”

Section: Introductionmentioning

confidence: 99%

The Design and Development of a Microstrip Antenna for Internet of Things Applications

Anchidin

Lavric

Mutescu

et al. 2023

Sensors

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The Internet of Things (IoT) has become a part of modern life where it is used for data acquisition and long-range wireless communications. Regardless of the IoT application profile, every wireless communication transmission is enabled by highly efficient antennas. The role of the antenna is thus very important and must not be neglected. Considering the high demand of IoT applications, there is a constant need to improve antenna technologies, including new antenna designs, in order to increase the performance level of WSNs (Wireless Sensor Networks) and enhance their efficiency by enabling a long range and a low error-rate communication link. This paper proposes a new antenna design that is able to increase the performance level of IoT applications by means of an original design. The antenna was designed, simulated, tested, and evaluated in a real operating scenario. From the obtained results, it ensured a high level of performance and can be used in IoT applications specific to the 868 MHz frequency band.By inserting two notches along x axis, we find an optimal structure of the microstrip patch antenna with a reflection coefficient of −34.3 dB and a bandwidth of 20 MHz. After testing the designed novel antenna in real IoT operating conditions, we concluded that the proposed antenna can increase the performance level of IoT wireless communications.

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“…Indeed, the use of computational intelligence and data analytics approaches for the vigilance and early survey of SARS-CoV2 infection has been an extremely relevant topic during the COVID-19 pandemic. Shabbir and collaborators (28) have implemented a strategy based on exploratory data analytics from diverse sources, coupled with telemonitoring and the use of internet of things (29)(30)(31) to detect COVID-19 severity in the context of smart hospitals (32)(33)(34). Also relevant is the use of concepts from computational social science (ambient intelligence, in particular) and again data from wearables (in this case, smartwatches) to develop early warning alerts (35)(36)(37).…”

Section: Introductionmentioning

confidence: 99%

Individual Factors Associated With COVID-19 Infection: A Machine Learning Study

Real

Martínez-García²,

Márquez³

et al. 2022

Front. Public Health

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The fast, exponential increase of COVID-19 infections and their catastrophic effects on patients' health have required the development of tools that support health systems in the quick and efficient diagnosis and prognosis of this disease. In this context, the present study aims to identify the potential factors associated with COVID-19 infections, applying machine learning techniques, particularly random forest, chi-squared, xgboost, and rpart for feature selection; ROSE and SMOTE were used as resampling methods due to the existence of class imbalance. Similarly, machine and deep learning algorithms such as support vector machines, C4.5, random forest, rpart, and deep neural networks were explored during the train/test phase to select the best prediction model. The dataset used in this study contains clinical data, anthropometric measurements, and other health parameters related to smoking habits, alcohol consumption, quality of sleep, physical activity, and health status during confinement due to the pandemic associated with COVID-19. The results showed that the XGBoost model got the best features associated with COVID-19 infection, and random forest approximated the best predictive model with a balanced accuracy of 90.41% using SMOTE as a resampling technique. The model with the best performance provides a tool to help prevent contracting SARS-CoV-2 since the variables with the highest risk factor are detected, and some of them are, to a certain extent controllable.

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Internet of Things Concept in the Context of the COVID-19 Pandemic: A Multi-Sensor Application Design

Cited by 19 publications

References 37 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

The Design and Development of a Microstrip Antenna for Internet of Things Applications

Individual Factors Associated With COVID-19 Infection: A Machine Learning Study

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