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1.
Signals ; 3(1):11-28, 2022.
Article in English | MDPI | ID: covidwho-1613948

ABSTRACT

In late 2019, a new genre of coronavirus (COVID-19) was first identified in humans in Wuhan, China. In addition to this, COVID-19 spreads through droplets, so quarantine is necessary to halt the spread and to recover physically. This modern urgency creates a critical challenge for the latest technologies to detect and monitor potential patients of this new disease. In this vein, the Internet of Things (IoT) contributes to solving such problems. This paper proposed a wearable device that utilizes real-time monitoring to detect body temperature and ambient conditions. Moreover, the system automatically alerts the concerned person using this device. The alert is transmitted when the body exceeds the allowed temperature threshold. To achieve this, we developed an algorithm that detects physical exercise named “Continuous Displacement Algorithm”based on an accelerometer to see whether a potential temperature rise can be attributed to physical activity. The people responsible for the person in quarantine can then connect via nRF Connect or a similar central application to acquire an accurate picture of the person’s condition. This experiment included an Arduino Nano BLE 33 Sense which contains several other sensors like a 9-axis IMU, several types of temperature, and ambient and other sensors equipped. This device successfully managed to measure wrist temperature at all states, ranging from 32 °C initially to 39 °C, providing better battery autonomy than other similar devices, lasting over 12 h, with fast charging capabilities (500 mA), and utilizing the BLE 5.0 protocol for data wireless data transmission and low power consumption. Furthermore, a 1D Convolutional Neural Network (CNN) was employed to classify whether the user is feverish while considering the physical activity status. The results obtained from the 1D CNN illustrated the manner in which it can be leveraged to acquire insight regarding the health of the users in the setting of the COVID-19 pandemic.

2.
Saf Sci ; 130: 104870, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-548132

ABSTRACT

During the recent Covid-19 pandemic, additive Technology and Social Media were used to tackle the shortage of Personal Protective Equipment. A literature review and a social media listening software were employed to explore the number of the users referring to specific keywords related to 3D printing and PPE. Additionally, the QALY model was recruited to highlight the importance of the PPE usage. More than 7 billion users used the keyword covid or similar in the web while mainly Twitter and Facebook were used as a world platform for PPE designs distribution through individuals and more than 100 different 3D printable PPE designs were developed.

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