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Three op-amp instrumentation amplifier circuit Equation (1) represents the formula to calculate the gain of the three op-amp instrumentation amplifier circuit. A V V V out = − 2 1
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Rapid transmission of the coronavirus disease via droplets and particles has led to a global pandemic. Expeditious detection of SARS-Cov-2 RNA in the environment is attainable by using Bio-FET sensors. This work proposes a Bio-FET sensor interface module with IoT implementation to amplify signals from a Bio-FET for SARS-Cov-2 detection and monitori...
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... Bio-FET sensor's output signal will be amplified using an instrumentation amplifier module [37], [38]. The instrumentation amplifier circuit has three Operational Amplifiers (op-amp) to obtain a gain of 100 purposely for amplifying the input voltage from mV to V. Figure 3 shows the circuit diagram of the classic three op-amp amplification circuit in a non-inverting configuration. The input (V in ) is connected to the non-inverting terminal and a simple voltage divider is connected to the inverting terminal for signal amplification. ...
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p>Countries throughout the world were experimenting with novel approaches to prevent the spreading of the Coronavirus pandemic illness (COVID-19). The use of IoT and cloud computing for data collection and analysis to avoid disease transmission via smartphone applications was a significant hurdle. Existing cloud services that are that retain the in...
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Looking to prevent future outbreaks of deadly pathogens by early detection? Infectious diseases continue to be a challenge that necessitates increased precision in detection and integration to achieve accurate diagnosis at the point of care (PoC). Field-effect transistors (FETs) have been investigated widely as biosensors for pathogen detection, with advantages such as label-free and real-time detection capabilities. These biosensors have:
In this title, we have invited expert scientific researchers to share their experience in this field. This book focuses on the application and possibility of FETs as biosensors, for rapid and real time detection of pathogens that affect human life. The lack of commercially available efficient devices that can be deployed for this task resulted in the recent global spread of the SARS-CoV-19 virus. The book is an attempt to keep interested parties up to date.
Aimed at scientists and engineers (researchers, academics, and postgraduate students) who are interested in developing and using BioFET based sensors, the information in this book is crucial to help prevent future outbreaks of pathogens which bring with them significant impacts on human health and wellbeing.
Since diagnostic laboratories handle large COVID-19 samples, researchers have established laboratory-based assays and developed biosensor prototypes. Both share the same purpose; to ascertain the occurrence of air and surface contaminations by the SARS-CoV-2 virus. However, the biosensors further utilize internet-of-things (IoT) technology to monitor COVID-19 virus contamination, specifically in the diagnostic laboratory setting. The IoT-capable biosensors have great potential to monitor for possible virus contamination. Numerous studies have been done on COVID-19 virus air and surface contamination in the hospital setting. Through reviews, there are abundant reports on the viral transmission of SARS-CoV-2 through droplet infections, person-to-person close contact and fecal-oral transmission. However, studies on environmental conditions need to be better reported. Therefore, this review covers the detection of SARS-CoV-2 in airborne and wastewater samples using biosensors with comprehensive studies in methods and techniques of sampling and sensing (2020 until 2023). Furthermore, the review exposes sensing cases in public health settings. Then, the integration of data management together with biosensors is well explained. Last, the review ended with challenges to having a practical COVID-19 biosensor applied for environmental surveillance samples.
A smart campus is an emerging trend that will revolutionize the education system by enabling universities to improve services, and processes as well as achieve sustainability goals. With the proliferation of advanced technologies, a smart campus has emerged as an important concept that integrates technology into higher education. A smart campus takes advantage of IoT technologies to facilitate teaching and research activities. The purpose of this study is to identify the IoT technologies that are required in the development of a smart campus. This study uses a Systematic Literature Review (SLR) methodology and PRISMA processes to analyze high-quality articles on the IoT-based smart campuses from the last five years (2017-2022) as extracted from three databases like Scopus, ScienceDirect, and IEEE. The findings of the study reveal that the implementation of an IoT-based smart campus offers many advantages and benefits but also presents challenges requiring further exploration. Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further. The paper explores the many benefits and advantages that are brought by the implementation of IoT-based smart campuses. It also identifies key challenges that are presented by such implementations. Researchers, policymakers, teachers, and students can benefit from this study by gaining insights into the IoT-based smart campus. Keywords—smart campus, smart university, Internet of Things, IoT applications, big data
