Your browser doesn't support javascript.
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 653
Filtrar
Adicionar filtros

Tipo de documento
Intervalo de ano
1.
Measurement: Sensors ; 25:100653, 2023.
Artigo em Inglês | ScienceDirect | ID: covidwho-2165693

RESUMO

Covid Protocol Monitoring with Multiprocessor Architecture (CPMMA) is proposed in this study as an approach for implementing a Distributed Sensor System (DSS) for covid protocol monitoring utilising multiprocessor architecture. OpenMP and MPI were used to implement the distributed system's parallel programmes, with the OpenMP code working best when used with 60–100 threads in use. CPMMA distributed sensor data was efficiently processed by a multiprocessor with 16 cores. According to the results, using a multithreaded-multiprocessing architecture and optimised Support Vector Machine classifier, the proposed design greatly enhances computing efficiency. The results of our experiments suggest that our approach may significantly enhance computing performance while also delivering adequate outcomes in a short period of time.

2.
Chemical Engineering Journal ; : 141260, 2022.
Artigo em Inglês | ScienceDirect | ID: covidwho-2165133

RESUMO

Standard clinical care of neonates and the ventilation status of human patients affected with coronavirus disease involves continuous CO2 monitoring. However, existing noninvasive methods are inadequate owing to the rigidity of hard-wired devices, insubstantial gas permeability and high operating temperature. Here, we report a cost-effective transcutaneous CO2 sensing device comprising elastomeric sponges impregnated with oxidized single-walled carbon nanotubes (oxSWCNTs)-based composites. The proposed device features a highly selective CO2 sensing response (detection limit 155±15 ppb), excellent permeability and reliability under a large deformation. A follow-up prospective study not only offers measurement equivalency to existing clinical standards of CO2 monitoring but also provides important additional features. This new modality allowed for skin-to-skin care in neonates and room-temperature CO2 monitoring as compared with clinical standard monitoring system operating at high temperature to substantially enhance the quality for futuristic applications.

3.
Biosensors and Bioelectronics ; 223:115037, 2023.
Artigo em Inglês | ScienceDirect | ID: covidwho-2165110

RESUMO

The current coronavirus disease 2019 (COVID-19) pandemic is caused by several variants of severe acute respiratory syndrome coronavirus-2 virus (SARS-CoV-2). With the roll-out of vaccines and development of new therapeutics that may be targeted to distinct viral molecules, there is a need to screen populations for viral antigen-specific SARS-CoV-2 antibodies. Here, we report a rapid, multiplexed, electrochemical (EC) device with on-chip control that enables detection of SARS-CoV-2 antibodies in less than 10 min using 1.5 μL of a patient sample. The EC biosensor demonstrated 100% sensitivity and specificity, and an area under the receiver operating characteristic curve of 1, when evaluated using 93 clinical samples, including plasma and dried blood spot samples from 54 SARS-CoV-2 positive and 39 negative patients. This EC biosensor platform enables simple, cost-effective, sensitive, and rapid detection of anti-SARS-CoV-2 antibodies in complex clinical samples, which is convenient for evaluating humoral-responses to vaccination or infection in population-wide testing, including applications in point-of-care settings. We also demonstrate the feasibility of using dried blood spot samples that can be collected locally and transported to distant clinical laboratories at ambient temperature for detection of anti-SARS-CoV-2 antibodies which may be utilized for serological surveillance and demonstrate the utility of remote sampling.

4.
Synthetic Metals ; 293:117235, 2023.
Artigo em Inglês | ScienceDirect | ID: covidwho-2165881

RESUMO

During the novel coronavirus pandemic, hydrogen peroxide (H2O2) played an important role as a disinfectant. However, high concentrations of H2O2 can also cause damage to the skin and eyes. Therefore, the quantitative and qualitative detection of H2O2 is an important research direction. In this work, we report a one-step laser-induced synthesis of graphene doped with Ag NPs composites. It directly trims screen printed electrodes (SPE). Firstly, we did the timekeeping current method (CA) test on H2O2 using a conventional platinum sheet as the counter electrode, and obtained linear ranges of 1–110 μM and 110–800 μM with a sensitivity of 118.7 and 96.3 μAmM−1cm−2 and a low detection limit of (LOD) 0.24 μM and 0.31 μM. On this basis we have also achieved a good result in CA testing using Screen printed carbon electrodes (SPCE), laying the foundation for portable testing. The sensor has excellent interference immunity and high selectivity.

5.
5th International Conference on Information Science and Systems, ICISS 2022 ; : 35-42, 2022.
Artigo em Inglês | Scopus | ID: covidwho-2162026

RESUMO

The emergence and occurrence of COVID-19 pandemic has affected the lives of many people around the world, implementing different protocols to further prevent the spread of this deadly virus. Overcrowding is one of the common reasons for the spread of any virus or diseases. The researchers aim to create a system that monitors crowd density inside a building or infrastructure to avoid overcrowding. This system primarily utilizes ultrasonic sensors to detect entry and exit of an individual. The feedback will be sent to the user and the data will be used to effectively monitor the number of people inside the building. © 2022 ACM.

6.
2022 International Symposium on Information Technology and Digital Innovation, ISITDI 2022 ; : 6-10, 2022.
Artigo em Inglês | Scopus | ID: covidwho-2161430

RESUMO

This paper presents a vibration monitoring system for electrical appliances. This system is based on RFID sensors and edge processing technologies. For long-term monitoring, two different operation modes referred to as standby and active modes are introduced. The difference between the two modes is radio wave radiation times. The standby mode is useful to reduce energy consumption and temperature increase of an RFID reader, and amount of data uploaded to a network. This mode also detects a beginning of a vibration event caused by the motor of an electrical appliance. The standby mode subsequently triggers the active mode. The active mode accurately monitors the vibration event and keeps the measured data only for the active mode. Experiments for monitoring a refrigerator demonstrate that the proposed modes enable efficient vibration detections. This system can prevent unintended COVID-19 vaccine disposals caused by the problematic operation and management of refrigerators. © 2022 IEEE.

7.
13th International Conference on Information and Communication Technology Convergence, ICTC 2022 ; 2022-October:2022-2025, 2022.
Artigo em Inglês | Scopus | ID: covidwho-2161407

RESUMO

Early stage arrhythmia detection is very important to prevent progress. However, under COVID-19 hospital accessibility deeply decreased and the risk of arrhythmia raised. Thus, we attached our activity sensor and environmental sensor attached to commercial tonometry system: Daeyomedi lifeplus. Tonometry system is one of the most accurate cardiovascular diseases detection system but it is very hard to make it portable. Photoplethysmogram sensors are less accurate than tonometry system but they are very small and can fit into the watch size. Environmental sensors are collecting additional data, temperature, humidity, carbon dioxide level, micro dust and Volatile Organic Compounds. Our IoT sever system collects all data from DMP lifeplus, activity sensor and environmental sensor. Processing data with implemented algorithms for service was developed as well. We successfully attached DMP lifeplus to our activity and environmental sensor. This work shows that our activity and environmental sensors can be attached to other medical system and enlarge the medical service area. © 2022 IEEE.

8.
Rsc Advances ; 12(53):34512-34519, 2022.
Artigo em Inglês | Web of Science | ID: covidwho-2160359

RESUMO

An accurate, sensitive and selective RP-HPLC-UV method has been established for the estimation of Molnupiravir (MOL) in pure bulk powder and pharmaceutical formulation. Separation was achieved on an Inertsil C-18 column (150.0 mm x 4.6 mm, 5.0 mu m), using a mobile phase of 20 mM phosphate buffer pH 2.5 : acetonitrile (80 : 20, v/v%) in isocratic mode with a flow rate of 1.0 mL min(-1). The lambda(max) of MOL prepared in the chosen diluent (ethanol : water in equal proportions) was found to be 230.0 nm. The constructed calibration curve was found to be linear in the concentration range of 0.2-80.0 mu g mL(-1). The recovery% of MOL using the proposed method was 100.29%. The limit of detection (LOD) and limit of quantification (LOQ) were 0.04 mu g mL(-1) and 0.12 mu g mL(-1), respectively. No significant interference was detected in the presence of the common pharmaceutical formulation excipients. The method was validated following the ICH recommendations. All the obtained results were statistically compared with those using reported methods and there were no significant differences. The method developed in this work was successfully employed for the assessment of MOL in bulk powder and pharmaceutical formulation.

9.
9th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2022 ; 2022-October:210-214, 2022.
Artigo em Inglês | Scopus | ID: covidwho-2156043

RESUMO

Currently the world is being reported with the emergence of a new virus, namely the Covid-19 virus, so the Indonesian government implements a Health protocol in the form of Physical Distancing. However, as time goes by, the government recommends that we get used to what is going on, one example is starting to allow on-site teaching and learning activities but on the condition that we continue to implement the existing protocol, namely implementing Physical Distancing. Through the design of this tool, namely smart presence using RFID and ultrasonic sensors based on the Internet Of Things (IoT) by paying attention to the object distance <50 cm which then sends a notification to the Telegram application when the object distance is less than 50 cm and the attendance status is successful. After testing is carried out on all components of the tool, all systems that have been made can work and function properly in accordance with the desired system design. It is hoped that the system created can make it easier for students to apply Physical Distancing health protocols in classroom learning activities and add insight into the importance of maintaining health. © 2022 Institute of Advanced Engineering and Science (IAES).

10.
Environment and Urbanization ASIA ; 13(2):265-283, 2022.
Artigo em Inglês | Scopus | ID: covidwho-2153396

RESUMO

In Delhi, the capital city of India, air pollution has been a perpetual menace to urban sustainability and public health. The present study uses a mixed-method approach to enumerate to the urban authorities: (a) the state of air pollution in the city;(b) systemic flaws in the current monitoring network;(c) potential means to bolster it;and (d) need of a participatory framework for monitoring. Information about Air Quality Index (AQI), obtained from 36 monitoring stations across Delhi is compared between 2021 (20 April–25 May;2nd year/phase of SARS-CoV-2 lockdown), and the corresponding time periods in 2020 (1st year/phase of lockdown), and 2019 (business-as-usual) using the Mann–Whitney U Test. AQI during the 2021 lockdown (a) appeared statistically more similar (p <.01) to that of 2019 and (b) exceeded the environmental health safety benchmark for 85% days during the study period (20 April–25 May). However, this only presented a partial glimpse into the air pollution status. It owes to numerous ‘holes’ in the AQI data record (no data and/or insufficient data). Moreover, certain areas in Delhi yet have no monitoring station, or only too few, to yield a ‘representative’ estimate (inadequate spatial coverage). Such shortcomings in the existing monitoring network may deter future research and targeted/informed decision-making for pollution control. To that end, the present research offers a summary view of Low-Cost Air Quality Sensors (LCAQS), to offer the urban sustainability authorities, ‘complementary’ technique to bolster and diversify the existing network. The main advantages and disadvantages of various LCAQS sensor technologies are highlighted while emphasizing on the challenges around various calibration techniques (linear and non-linear). The final section reflects on the integration of science and technology with social dimensions of air quality monitoring and highlights key requirements for (a) community mobilization and (b) stakeholder engagement to forge a participatory systems’ design for LCAQS deployment. © 2022 National Institute of Urban Affairs.

11.
10th International Conference on Cyber and IT Service Management, CITSM 2022 ; 2022.
Artigo em Inglês | Scopus | ID: covidwho-2152437

RESUMO

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.

12.
Journal of Colloid and Interface Science ; 2022.
Artigo em Inglês | ScienceDirect | ID: covidwho-2150008

RESUMO

Acetaminophen plays a key role in first-line Covid-19 cure as a supportive therapy of fever and pain. However, overdose of acetaminophen may give rise to severe adverse events such as acute liver failure in individual. In this work, 3D-hierarchical mesoporous carbon nanosheet (hMCNS) microspheres with superior properties were fabricated using simple and quick strategy and applied for sensitive quantification of acetaminophen in pharmaceutical formulation and rat plasmas after administration. The hMCNS microspheres are prepared via chemical etching of zinc oxide (ZnO) nanoparticles from a zinc-gallic acid precursor composite (Zn-GA) synthesized by high-temperature anaerobic pyrolysis. The obtained hMCNS could enhance analytes accessibility and accelerate proton transfer in the interface, hence increasing the electrochemical performance. Under optimized experimental conditions, the proposed electrochemical sensor achieves a detection limit of 3.5 nM for acetaminophen. The prepared electrochemical sensor has been successfully applied for quantification of acetaminophen in pharmaceutical formulations and the rat plasma samples before and after administration. Meanwhile, this sensor is compared with high-performance liquid chromatography (HPLC) as a reference technology, showing an excellent accuracy. Such an electrochemical sensor has great potential and economic benefits for applications in the fields of pharmaceutical assay and therapeutic drug monitoring (TDM).

13.
7th International Conference on ICT for Sustainable Development , ICT4SD 2022 ; 520:749-761, 2023.
Artigo em Inglês | Scopus | ID: covidwho-2148698

RESUMO

The most prominent symptom in corona-infected person is increased body temperature. Population in India is very high, and it is very difficult to provide medical services to everyone at a time. This paper presents how can we reduce the pressure on medical service providers in current pandemic situation and stop the community spreading. Initially in the paper, impact of lockdown on COVID-19 situation is observed using the Python language. According to that two lockdown applied in the country at initial level, the growth rate of pandemic was under control. But as the lockdown rules were relaxed, quick hike in corona cases was noted. On the basis of this result proposed model is designed, if one scans the temperature of different domain areas at regular intervals from above the surface using zero touch technology, i.e., drone camera installed with thermal sensor, the increased temperature reading can help screening the infected hot spots. The proposed idea is to collect thermal data through thermal sensors and process these data using visualization of images/videos and quantitative methods. Machine learning and artificial intelligence are used to process biometric features of corona suspects and collect personal detail of corona suspect from the databases. The residential area of infected person is marked with red color, and monitoring the movement of the infected person is done with help of machine learning. With the taken of timely action, not only the spreading can be controlled but also the patients can get appropriate attention and treatment on time. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

14.
4th International Conference on Futuristic Trends in Networks and Computing Technologies, FTNCT 2021 ; 936:349-362, 2022.
Artigo em Inglês | Scopus | ID: covidwho-2148678

RESUMO

In this COVID-19 pandemic situation, health care is on the priority of every human being. The recent development in the miniaturization of intelligent devices has opened many opportunities and played a crucial role in the healthcare industry. The amalgamation of wireless sensor network and Internet of Things is the best example of wireless body area network. These tiny sensor devices have two essential evaluation parameters named as energy efficiency and stability while performing in a group. This paper focuses on various issues of the healthcare system and their solutions. An energy-efficient routing protocol that can provide sensed data to the collection centre or data hub for further processing and treatment of the patients is proposed. Here, we fixed zones for sending data to zone head using distance aware routing, and then zone head send the aggregated data to the data hub. It is better than the low energy adaptive clustering hierarchy (LEACH) by 42% and distance-based residual energy-efficient protocol (DREEP) by 30% in energy efficiency and stability 58% more by LEACH and 39% by DREEP. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

15.
Front Chem ; 10: 1060322, 2022.
Artigo em Inglês | MEDLINE | ID: covidwho-2141704

RESUMO

As a powerful and effective analytical tool, surface-enhanced Raman scattering (SERS) has attracted considerable research interest in the fields of wearable flexible sensing and non-invasive point-of-care testing (POCT) medical diagnosis. In this mini-review, we briefly summarize the design strategy, the development progress of wearable SERS sensors and its applications in this field. We present SERS substrate analysis of material design requirements for wearable sensors and highlight the benefits of novel plasmonic particle-in-cavity (PIC)-based nanostructures for flexible SERS sensors, as well as the unique interfacial adhesion effect and excellent mechanical properties of natural silk fibroin (SF) derived from natural cocoons, indicating promising futures for applications in the field of flexible electronic, optical, and electrical sensors. Additionally, SERS wearable sensors have shown great potential in the fields of different disease markers as well as in the diagnosis testing for COVID-19. Finally, the current challenges in this field are pointed out, as well as the promising prospects of combining SERS wearable sensors with other portable health monitoring systems for POCT medical diagnosis in the future.

16.
7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering ; 12294, 2022.
Artigo em Inglês | Scopus | ID: covidwho-2137314

RESUMO

This paper designs a smart car that can automatically deliver meals in dormitories, isolated hotels and other scenarios. This system uses i.MX RT1064 as the main controller, and completes the route tracking and room number recognition of the smart car through the MT9V034 camera and the OpenART mini visual sensor module respectively. The target detection method is the SSD algorithm in the one-stage method. After optimization, the recognition rate is as high as 90%, which can successfully complete the meal delivery task. This system greatly reduces the risk of human-to-human contact, reduces the probability of contracting COVID-19, and contributes to epidemic prevention and control measures to minimize risks. © 2022 SPIE. All rights reserved.

17.
2022 Sensor Data Fusion: Trends, Solutions, Applications, SDF 2022 ; 2022.
Artigo em Inglês | Scopus | ID: covidwho-2136478

RESUMO

Window ventilation is important in everyday life. The COVID-19 pandemic in particular has shown that air exchange is necessary to minimize the spread of viruses. Efficient ventilation can be supported with the help of sensors and intelligent data processing. A CO2 sensor, for example, can be used to measure CO2 levels and, together with IoT hardware, indicating when ventilation is needed. By combining these components together with algorithms, an assessment of such window ventilation can be made. This paper presents a measurement setup to measure CO2. The measured values in the form of time series are used in the setup to learn the time points ventilation. Two approaches are taken to analyze these time series. The first approach is based on the simple K-Means and K nearest neighbors algorithm, the second approach uses Dynamic Time Warp (DTW) Barycenter Averaging (DBA). Both approaches are compared in this work in the detection of ventilation events. © 2022 IEEE.

18.
IEEE Sensors Journal ; : 1-1, 2022.
Artigo em Inglês | Scopus | ID: covidwho-2136429

RESUMO

Due to the COVID-19 global pandemic, there are more needs for remote patient care especially in rehabilitation requiring direct contact. However, traditional Chinese rehabilitation technologies, such as gua sha, often need to be implemented by well-trained professionals. To automate and professionalize gua sha, it is necessary to record the nursing and rehabilitation process and reproduce the process in developing smart gua sha equipment. This paper proposes a new signal processing and sensor fusion method for developing a piece of smart gua sha equipment. A novel stabilized numerical integration method based on information fusion and detrended fluctuation analysis (SNIF-DFA) is performed to obtain the velocity and displacement information during gua sha operation. The experimental results show that the proposed method outperforms the traditional numerical integration method with respect to information accuracy and realizes accurate position calculations. This is of great significance in developing robots or automated machines that reproduce the nursing and rehabilitation operations of medical professionals. IEEE

19.
IEEE Sensors Journal ; 22(23):23529-23538, 2022.
Artigo em Inglês | ProQuest Central | ID: covidwho-2136428

RESUMO

The rising aging population, inequality of medical resources, and severe COVID-19 infection rate raise inevitable individual and social contradictions. One of the representative developing technologies, smart wearables, is dedicated to offering accurate personal healthcare. Nevertheless, energy constraints as well as unpredictable data transmission are critical in the development of wearable devices. In this regard, we investigate the key concerns of energy life and quality of service (QoS) for smart clothing. Unlike general wireless sensing networks (WSNs), the wireless body area network (WBAN) embedded in smart clothing is highly affected by human postural changes. In this article, we formulate the smart clothing with multiposture participated from two perspectives: 1) for energy life, we address the energy consumption, the energy harvested by the nodes, and the battery discharge and 2) the QoS involves the path loss and time delay. Moreover, five typical daily activity states have been discussed to model the impact of posture changes. Under the influence of the posture state, the tradeoff between the collected tribological electrical energy and the consumed energy is also presented in the article. We parameterize the path loss, transmission delay, energy consumption, and collection in each posture and integrally formulate the energy problem and QoS to a joint optimization problem. Particle swarm optimization (PSO), sine cosine algorithm (SCA), and Q-learning algorithm are adopted to optimize the overall cost, time delay, and energy consumption. In addition, a comparison of the battery power of the nodes is conducted. Simulation results show that each algorithm achieves certain optimization effects, for example, PSO, SCA, and Q-learning reduce total costs by 14%, 22%, and 30%, respectively. Q-learning is also effectively decreasing latency and energy consumption and improving battery life.

20.
2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022 ; 2022-May:1332-1336, 2022.
Artigo em Inglês | Scopus | ID: covidwho-2136386

RESUMO

Low-resolution infrared (IR) array sensors offer a low-cost, low-power, and privacy-preserving alternative to optical cameras and smartphones/wearables for social distance monitoring in indoor spaces, permitting the recognition of basic shapes, without revealing the personal details of individuals. In this work, we demonstrate that an accurate detection of social distance violations can be achieved processing the raw output of a 8x8 IR array sensor with a small-sized Convolutional Neural Network (CNN). Furthermore, the CNN can be executed directly on a Microcontroller (MCU)-based sensor node.With results on a newly collected open dataset, we show that our best CNN achieves 86.3% balanced accuracy, significantly outperforming the 61% achieved by a state-of-the-art deterministic algorithm. Changing the architectural parameters of the CNN, we obtain a rich Pareto set of models, spanning 70.5-86.3% accuracy and 0.18-75k parameters. Deployed on a STM32L476RGMCU, these models have a latency of 0.73-5.33ms, with an energy consumption per inference of 9.38-68.57\muJ. © 2022 IEEE.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA