ABSTRACT
Medical Gas is an important component in the treatment of patients with COVID-19 disease. Medical gas is used to help COVID-19 patients to reduce the effects of respiratory disorders by providing oxygen ventilators to patients. With the surge in typical COVID-19 sufferers as of July 2021, the need for Oxygen in hospitals is getting higher. This is when the control and monitoring of medical gases in hospitals are late because the integrated system is very dangerous. Therefore, a system that can be used to control and monitor medical gases in hospitals that are integrated and automated and can be monitored by the Government and Medical Gas Producers. This is useful for anticipating the lack of availability of Medical Gas in hospitals. In this study, the system used IoT systems as a base in delivery and control. This system uses Arduino as a minimum system that reads the press sensor on the Medical Gas tube and regulates the valve. The data obtained is then sent to the Local Server to be processed and delivered to the Hospital Officer. Local Servers also send the data to cloud servers to be monitored by the government funds of several medical gas producers. This design can help in the process of controlling and monitoring Medical Gases in hospitals in hopes of minimizing the risk of delays in supplying medical gases to hospitals. © 2021 Institute of Physics Publishing. All rights reserved.
ABSTRACT
The use of the IoT protocol on medical equipment is expected to provide protection for medical personnel in dealing with Covid-19 patients, especially when medical personnel are monitoring and setting up an equipment. This study aims to (1) produce a monitoring and control system for a breathing apparatus (Ventilator) based on the Internet of Thing (IoT), (2) test the ventilator control function, (3) test the data transmission function with the IoT protocol. The method used is Define, Design, Develop, and Disseminate (4D). Data collection is done through (1) Testing and Observation (2) Limited field test. This research produces a control and monitoring system for mechanical ventilators. The mechanical ventilator consists of a gripper motion mechanism driven by a dc motor. The movement of the gripper creates pressure and releases pressure on the ambu bag. The depth of pressure exerted by the gripper is measured as the volume and pressure of the air delivered to the lungs. The rate of pressure exerted is measured as the velocity of air flowing into the lungs. Keywords: Ventilator, IoT, Covid19 © 2021 Institute of Physics Publishing. All rights reserved.
ABSTRACT
Currently, the whole world is facing the critical economy crash and enormous casualties as the ongoing coronavirus continues its intensive attack across the planet. Sadly, individuals in billions of numbers continue to face a constant threat from this contagious disease, with the condition unlikely to getting any improvement soon. In this paper, the aim is to provide an overview study of the current situation concerning the COVID-19 outbreak and the potential role of Internet of Things (IoT) as well as the associated technologies acting as technological solution in mitigating the outbreak. Thus, some potential literatures have been briefly reviewed for this paper as a research method. The review results indicate that, several technological solutions are innovated to deal with the COVID-19 pandemic effects. Digital technologies play a major role in the reformation of public health response towards the COVID-19 pandemic. Among digital technologies which have been at the front line include the IoT. Some examples and potential applications of IoT are discussed. © 2021 Published under licence by IOP Publishing Ltd.
ABSTRACT
The spread of the corona virus in Indonesia is still growing until now. One important thing to note is about the handling of patients exposed to the coronavirus. This study aims to be able to classify thorax x-ray images against corona virus infection based on the Internet of Things (IoT). IoT is a concept of internet connectivity that is connected continuously between remote devices. This study uses a supervised learning method, namely directed learning in which the expected results of the user have been trained in advance and the information is stored in the system (database). The training data used is a Thorax x-ray image that is processed based on image processing with segmentation and edge detection based on the Sobel operator with real time connected to the internet. The results showed that the 100 times experiment obtained the accuracy value of the normal Thorax X-ray image of 94% and the Thorax covid-19 X-ray image of 96%. Overall system test showed 95% on target and 5% error. © 2021 Published under licence by IOP Publishing Ltd.