Arduino based COVID-19 Suspect Detection Device

The COVID-19 outbreak has wreaked havoc on civilization and sparked fear across the globe. COVID-19's apparent deceptiveness may be to blame for the uproar: Transmission and death are around average when compared to previous fatal virus epidemics. This led to a major underestimation of the severity of the SARS-CoV-2 virus at the start of the COVID-19 epidemic. As a result, this research study refers to viruses that share characteristics with SARS-CoV-2 as Panic Zone viruses in this study. To stop the spread of these viruses, early identification, proper isolation, and treatment of affected individuals are critical in containing outbreaks. As the current COVID-19 epidemic demonstrates, this is particularly important when it comes to diseases that are spread via contact or exposure. © 2022 IEEE.

Design and Development Integrated Sensor System for Measuring Body Temperature and Heart Rate

Heart rate and body temperature are some of the important components of a person's main vital signs that need to be monitored regularly and periodically. The detection system technology continues to develop which allows a person to detect his own condition, to avoid exposure to COVID-19. However, the tools that are developing in the market are quite expensive and sometimes complex in operation because they are external products, so that it becomes a difficulty in itself. For this reason, it is important to design a detection device with sensor components that exist in the country and with a simple design so that it is easy to operate and inexpensive. In this paper, utilizing pulse sensors and AD8232 sensors to detect heart rate and MLX90614 sensors to measure body temperature, then NodeMCU ESP8266 to process sensor signals received and will be forwarded to the Display (LCD) to display the results carry out the design and development of an integrated sensor system. From the research results, the accuracy of the MLX90614 temperature sensor is very good with the achievement of 99.24% and the pulse sensor with the achievement of 98.86%. For the test results on each sample obtained accuracy values of 98.4% and 99% for the temperature sensor, and 92.3% and 92.2% for the pulse sensor, respectively. From these results, it is very clear that the sensor design deserves to be promoted as a quality product. © 2022 IEEE.

Convenient Nucleic Acid Detection Method and Point-of-Care Detection Device Rased on CRISPR/Cas12a Molecular Diagnosis

Objective Clustered regularly interspaced short palindromic repeats (CRISPR) has shown significant promise as an emerging nucleic acid detection technology. However, it still requires improvement in terms of sensitivity, detection automation, and anti-pollution. Furthermore, CRISPR technology lacks simple and portable professional equipment to meet the high demand of rapid point-of-care testing. Therefore, this study proposes a CRISPR/Cas12a detection reaction system for SARS-CoV-2. This detection response system and innovative tube-in-tube consumables aid in developing a portable compact device for simultaneous automatic detection of several samples and a coaxial fiber-based fluorescence detection system. Finally, we developed a single-sample user-friendly nucleic acid detection APP based on smartphone recognition and detection results for the manual detection mode. Methods The target in this study was severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which was detected using the CRISPR method and enhanced via the reverse transcription-recombinase polymerase amplification (RT-RPA) technique;the feasibility was assessed using the reverse transcription-polymerase chain reaction (RT-PCR) amplification method in the early stages. Various companies customized the required reagents and the designed sequences. In the detection process, first, with the tube-in-tube consumables developed by our team in the early stage, which comprised the reaction outer and inner tubes, the amplification reagents and detection reagents were loaded into the inner and outer tubes, respectively. The temperature was regulated to 37-42 ℃ to complete the amplification. The reagents in the inner and outer tubes were then mixed by shaking or centrifugation, and the temperature was adjusted to complete the CRISPR reaction. Finally, it was possible to observe if there was any fluorescence occurrence under the illumination of a blue light. The detection instrument was composed of an optical cassette and a base, and automatic detection was realized through a printed circuit board (PCB), a human-computer interaction display screen, etc. In addition, this study also used the fluorescence image recognition algorithm to process the detection images, compared with the international standard polymerase chain reaction (PCR) technology to explore the detection limit, and increased the target types to test the specificity strength. Results and Discussions The lower part of the detection instrument designed by our team integrates the printed circuit board and the human-computer interaction display screen. In the automatic detection mode, the fluorescence recognition circuit was designed with the help of a 470 nm light-emitting diode (LED), an optical filter, a complementary metal oxide semiconductor (CMOS) camera, a collimating lens, and a coaxial fiber. At the same time, the specificity of the theoretical experiment was verified through comparative experiments on several different targets. In addition, to verify the accuracy of this method for detecting actual samples, we compared each actual sample through PCR detection and the method based on the combination of RT-RPA and CRISPR proposed in this study. The detection results showed that the two were perfectly consistent. Conclusions The current study proposed a CRISPR/Cas12a-based anti-pollution portable nucleic acid detection technique. Furthermore, a simple model was proposed based on the naked eye or smartphone to recognize results;additionally, a downsized portable device based on fluorescence detection that can simultaneously detect numerous samples was constructed. The portable device can detect numerous samples simultaneously, and it has a constant heating mechanism and fluorescence stimulation detection optical channel to enhance the detection system’s accuracy and stability. The nucleic acid of SARS-CoV-2 was verified using the proposed method and detection system. The minimum detection limit was <10 copy/μL. The test findings of our method had a good consistency with that of real- ime fluorescence quantitative PCR method, but our method took less than half the time consuming of the PCR method, and the whole detection process could be finished in 32 min. The method and technology developed in this study propose a novel approach for nucleic acid detection at health-care center and home. © 2022 Science Press. All rights reserved.

A Study on COVIDBIT as a COVID-19 Detection Device for an Alternative Reverse Transcription-Polymerase Chain Reaction (RT-PCR) Machine

At the end of 2019, Coronavirus disease (COVID-19) started and as of now, it is still the number one problem of the world today. This virus can be transmitted through droplets of saliva from an infected person which can be from a sneeze, cough, and exhales. As of now, there are a total of 111 million cases of the virus and there are technologies that were introduced to help in the detection of the infection and to reduce the spread of the virus. One of this technology is the Reverse Transcription-Polymerase Chain Reaction (RT-PCR) Machine. This machine detects any specific genetic material, including a virus. Samples from the body are treated with several chemical solutions which remove substances and only allow Ribonucleic Acid (RNA) to remain. But the problem with this machine is the elicitation of false-positive and false-negative results and certain malfunctions. Due to the issues in using RT-PCR, our team has come up with a newer and improvised version of the machine and called it COVIDBIT. COVIDBIT is a more simplified and portable version of the RT-PCR at a cheaper price. In this study, the team analyzed COVIDBIT as a virus detection device and an alternative for RT-PCR machine using SEM model and found out that there is a significant difference in terms of effectiveness and portability in usage and showed that the 210 respondents from the medical industry are most likely to use these kinds of machine. © 2022 ACM.

Simulation of Microfluidic Biosensor for Binding Kinetics of SARS-CoV-2 S Protein Using the Electrothermal Effect

To contribute to the fight versus the coronavirus disease 2019, great efforts have been made by scientists around the world to improve the performance of detection devices so that they can efficiently and quickly detect the virus responsible for this disease. In this context we performed a two-dimensional finite element simulation on the binding kinetics of SARS-CoV-2 S protein of a biosensor using the alternating current electrothermal (ACET) effect. The ACET flow can produce vortex patterns, thereby improving the transportation of the target analyte to the binding surface and thus enhancing the performance of the biosensor. The results showed that the detection time can be improved under the electrothermal effect. The effect of certain design parameters concerning the reaction surface, such as its length as well as its position on the top wall of the microchannel, on the biosensor efficiency were also presented. Results showed that the decrease in the length of the binding surface can lead to an increase in the rate of the binding reaction and therefore decrease the biosensor response time. Also, moving the sensitive surface from an optimal position, which is opposite the electrodes, decreases the performance of the biosensor. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Face Mask Wear Detection by using Facial Recognition System for Entrance Authorization

A Face Mask Wear Detection Device for Entrance Authorization is designed to ensure that everyone wears a face mask at all times in a confined space. It is one of the easiest methods to lower the rate of coronavirus infection and hence save lives. Asthma, high blood pressure, heart failure, and many other chronic conditions can be fatal to those who are infected by the novel Coronavirus (nCoV-21). Consequently, the goal of this research is for face mask wear detection devices that help to reduce the rate of Novel Coronavirus infection on-premises or in public places by ensuring that customers comply with Standard Handling Procedures (SOP) set by the Ministry of Malaysian Health (MOH). Customers' faces are recognized by this device whether or not they are covered by a face mask upon entry into a facility. Additionally, the use of this device can contribute to ensuring compliance with the maximum number of customers allowed on the premises. A facial recognition system is the goal of this study that uses technology designed as an individual disciplinary aid and follows the safety procedure at this critical time. This research was developed using the engineering design process development model which has four phases namely;identifying the problem, making possible solutions, prototype development and testing and evaluating the solution. Results indicate that the developed product can function effectively. Experts have discovered that using this product helps people stick to their face mask routines. The design of this product has improved, which means that the overall quality of the product is elevated to be capable of performing as intended in terms of intelligent technologies © 2022. International Journal of Advanced Computer Science and Applications.All Rights Reserved.

Detecting Pneumonia using Vision Transformer and comparing with other techniques

Pneumonia is life-threatening. It's critical for infants, young children, elders, and people with health problems or enfeebles immune systems. However, someone who has been infected with coronavirus can get intense Pneumonia in each lung. The best way to stumble on Pneumonia is via chest X-ray. Radiotherapist is required for an examination of chest X-Ray. An automated pneumonia detection device would be helpful for early detection in far-off places. The proposed method makes it possible to train ViT models with enhanced performance. Nowadays, ViT is an alternative method of CNN in the field of computer vision. In this research, three models have been proposed, namely convolutional neural network (CNN), VGG16, and Visual Transformer were constructed. Statistical results are obtained after the comparison of all three models. Results indicate that ViT can identify Pneumonia with an accuracy of 96.45%. And also can be used to recognize other lung-related diseases. All the models were trained and tested on a dataset that contains standard chest X-Rays and pneumonia chest X-Rays. © 2021 IEEE.