scholarly journals CLOUD-BASED TEMPERATURE MONITORING MECHANISM FOR COVID-19 PANDEMIC TRACKING

2021 ◽  
Vol 84 (1) ◽  
pp. 241-247
Author(s):  
Loo Tung Lun ◽  
Tam Swee Chin ◽  
Mohamad Khairi Ishak ◽  
Mohd Shahrimie Mohd Asaari
Keyword(s):  
Body Temperature ◽  
Screening Method ◽  
Warning Signal ◽  
Temperature Monitoring ◽  
Raspberry Pi ◽  
Single Individual ◽  
Real Time System ◽  
Monitoring Mechanism ◽  
Body Temperature Measurement ◽  
Novel Coronavirus

The unprecedented outbreak of novel coronavirus 2019 (COVID-19) globally has a huge impact to our daily life in numerous ways. To effectively minimize the spread of the virus, early symptom detection is crucial, especially in closed environment with high human traffic areas which post higher chances of human-to-human transmission. Body temperature measurement has been identified among the vital monitoring parameters. However, current available temperature monitoring mechanism is costly, limited to single individual and limited to locally without integrating to cloud and database. This led to difficulty in effective surveillance for suspicious COVID cases. Hence, the purpose of this paper is to introduce an end-to-end Internet of Things-enabled application for thermal monitoring as an early signal detection and screening method. This work integrates Raspberry Pi, thermal sensor, LCD display, buzzer, and LED light with Raspbian and Restful API for device-to-cloud communication. The system implemented is capable for user identification, body temperature remote monitoring and warning signal for fever symptoms. The result of this real-time system is capable to detect and screen the suspected contagious person in an organization effectively. Future works on integrating face recognition with machine learning and artificial intelligent enhancement.

scholarly journals Continuous Body Temperature Monitoring to Improve the Diagnosis of Female Infertility

2020 ◽  
Vol 80 (07) ◽  
pp. 702-712
Author(s):  
Maren Goeckenjan ◽  
Esther Schiwek ◽  
Pauline Wimberger
Keyword(s):  
Body Temperature ◽  
Luteal Phase ◽  
Polycystic Ovary ◽  
Diagnostic Procedures ◽  
Temperature Monitoring ◽  
Ovary Syndrome ◽  
Menstrual Cycles ◽  
Ovulatory Dysfunction ◽  
Body Temperature Measurement ◽  
Continuous Body

Abstract Introduction Ovulatory dysfunction is a major cause of female infertility. We evaluated the use of continuous body temperature monitoring with a vaginal biosensor to improve standard diagnostic procedures for determining ovulatory dysfunction. Material and Methods This prospective interventional study was performed in a reproductive medicine department of a university hospital. The menstrual cycles of 51 women with infertility were monitored and analysed using three different strategies: sonographic and hormonal assessment (standard approach), continuous core body temperature measurement and analysis using the algorithm of OvulaRing, and lowest daily body temperature measurement monitored with a vaginal biosensor and analysed based on the body temperature curves used in natural family planning. Results Statistically significant differences were found in the temperature curves of women with luteal phase deficiency and polycystic ovary syndrome compared to women with normal menstrual cycles. The analysis of individual cyclofertilograms can be used to detect cycle phases and estimate the date of ovulation. Conclusions Continuous body temperature monitoring with a vaginal biosensor can improve the standard diagnostic procedures used to determine ovulatory dysfunction, especially if dysfunction is due to luteal phase deficiency and polycystic ovary syndrome. Analysis of the lowest daily body temperature combined with the basal body temperature measurements used in fertility awareness methods may be equieffective to continuous body temperature measurements with OvulaRing. The results of this study show that a revised diagnostic approach using fewer hormonal assessments combined with continuous body temperature monitoring can reduce the number of appointments in an infertility clinic as well as the costs.

scholarly journals An AI(Artificial Intelligence) based Device for Covid-19 Fever Detection

2021 ◽  
Vol 9 (VI) ◽  
pp. 2745-2748
Author(s):  
Gangadhara Rao Kommu
Keyword(s):  
Body Temperature ◽  
Temperature Measurement ◽  
Raspberry Pi ◽  
Global Pandemic ◽  
Human Body Temperature ◽  
Labour Requirement ◽  
Body Temperature Measurement ◽  
Prevention Method ◽  
Low Efficiency ◽  
Temperature Measurement System

Coronavirus disease (covid-19) is a global pandemic, and every country is actively fighting against the virus. It is an effective way to prevent the spread of the virus in finding the person with abnormal temperature promptly to perform the further medical observation. However, the traditional method of temperature measurement has low efficiency and accuracy. Body temperature acting as important role in medicine, several diseases is characterized by a change in human body temperature. Monitoring body temperature also allows the doctor to track the effectiveness of treatments. But current continuous body temperature measurement system is mainly limited by reaction time, movement noise, and labour requirement. In addition, the traditional contact body temperature measurement has the problem of wasting consumables and causing discomfort. To address the above issues, we present a non contact, automatic system using a single thermal non-contact sensor. The Proposed Covid prevention method scans body temperature through MLX9014 Contactless Temperature Sensor and sends the data to Raspberry pi model 3+ architecture. Our application takes data from MLX9014 and analyzes it to see whether the temperature is greater than 370 Celsius , which then captures the image through pi camera.

Assessing the Use of Biometric Ear Tags as Body Temperature Monitoring Devices in Swine

2021 ◽  
Vol 99 (Supplement_2) ◽  
pp. 45-46
Author(s):  
Ellie A Amerson ◽  
Harrison Moss ◽  
Suresh Kumar ◽  
Terry D Brandebourg
Keyword(s):  
Body Temperature ◽  
Pearson Correlation ◽  
Disease Outbreaks ◽  
Correlation Coefficients ◽  
Raspberry Pi ◽  
Herd Health ◽  
Swine Industry ◽  
Sickness Behaviors ◽  
Large Production ◽  
Monitoring Devices

Abstract It is difficult to detect the subtle changes associated with sickness behaviors in individual pigs early enough to prevent disease outbreaks in group housing settings within large production facilities. This failure results in significant losses to the swine industry. Strategies that allow early detection of parameters such as febrile responses could therefore significantly improve herd health and producer profitability. Our objective was to determine if the use of a biometric ear tag capable of measuring temperature could be used to accurately monitor body temperature in swine. To accomplish this, 42-d-old pigs (n = 21) were fitted with biometric ear tags for 35 d. These devices continuously measured auricular skin temperature and allowed data collection via a paired raspberry pi aggregator. During this period, repeated epidermal temperatures were also taken daily on the rump, shoulder, and ear using a clinical grade infrared thermometer. Correlation analysis using the PROC CORR procedure of SAS was then conducted to determine the ability of the biometric device to estimate body temperature relative to estimates from the clinical device. Infrared temperature readings for the ear significantly correlated with those taken at the shoulder (P < 0.0001) and rump (P < 0.0001). Importantly, temperature readings measured by the biometric ear tags also significantly correlated with infrared readings at the ear (P < 0.0001), shoulder (P < 0.0001) and rump (P < 0.0001) with Pearson Correlation coefficients of 0.51, 0.21, and 0.23, respectively. Collectively, these data support the hypothesis that the biometric ear tag device tested during this trial can be used to continuously monitor body temperature in young swine. These results indicate that further efforts to develop these devices as novel herd health monitoring devices is indeed warranted with the next step involving the assessment of their ability to detect physiological changes in body temperature.

scholarly journals Apply IOT technology to practice a pandemic prevention body temperature measurement system: A case study of response measures for COVID-19

2021 ◽  
Vol 17 (5) ◽  
pp. 155014772110181
Author(s):  
Wei-Ling Lin ◽  
Chun-Hung Hsieh ◽  
Tung-Shou Chen ◽  
Jeanne Chen ◽  
Jian-Le Lee ◽  
...  
Keyword(s):  
Body Temperature ◽  
Temperature Measurement ◽  
Measurement System ◽  
Disease Surveillance ◽  
Disease Surveillance System ◽  
Temperature Detection ◽  
Wide Range ◽  
Body Temperature Measurement ◽  
Analysis System ◽  
Temperature Measurement System

Today, the most serious threat to global health is the continuous outbreak of respiratory diseases, which is called Coronavirus Disease 2019 (COVID-19). The outbreak of COVID-19 has brought severe challenges to public health and has attracted great attention from the research and medical communities. Most patients infected with COVID-19 will have fever. Therefore, the monitoring of body temperature has become one of the most important basis for pandemic prevention and testing. Among them, the measurement of body temperature is the most direct through the Forehead Thermometer, but the measurement speed is relatively slow. The cost of fast-checking body temperature measurement equipment, such as infrared body temperature detection and face recognition temperature machine, is too high, and it is difficult to build Disease Surveillance System (DSS). To solve the above-mentioned problems, the Intelligent pandemic prevention Temperature Measurement System (ITMS) and Pandemic Prevention situation Analysis System (PPAS) are proposed in this study. ITMS is used to detect body temperature. However, PPAS uses big data analysis techniques to prevent pandemics. In this study, the campus field is used as an example, in which ITMS and PPAS are used. In the research, Proof of Concept (PoC), Proof of Service (PoS), and Proof of Business (PoB) were carried out for the use of ITMS and PPAS in the campus area. From the verification, it can be seen that ITMS and PPAS can be successfully used in campus fields and are widely recognized by users. Through the verification of this research, it can be determined that ITMS and PPAS are indeed feasible and capable of dissemination. The ITMS and PPAS are expected to give full play to their functions during the spread of pandemics. All in all, the results of this research will provide a wide range of applied thinking for people who are committed to the development of science and technology.

scholarly journals Conservatively Treated Femoral Intertrochanteric Fracture With Early Asymptomatic Novel Coronavirus Disease 2019 (COVID-19): A Case Report

2020 ◽  
Vol 11 ◽  
pp. 215145932096938
Author(s):  
Yuki Suzuki ◽  
Toshihiko Kasashima ◽  
Kazutoshi Hontani ◽  
Yasuhiro Yamamoto ◽  
Kanako Ito ◽  
...  
Keyword(s):  
Intertrochanteric Fracture ◽  
Screening Method ◽  
Oxygen Demand ◽  
Japanese Woman ◽  
Trauma Patients ◽  
Lung Field ◽  
Old Japanese ◽  
Femoral Intertrochanteric Fracture ◽  
Novel Coronavirus ◽  
The Right

Introduction: The ongoing outbreak of novel coronavirus disease 2019 (COVID-19) is a worldwide problem. Although diagnosing COVID-19 in fracture patients is important for selecting treatment, diagnosing early asymptomatic COVID-19 is difficult. We describe herein a rare case of femoral intertrochanteric fracture concomitant with early asymptomatic novel COVID-19. Case presentation: An 87-year-old Japanese woman was transferred to our emergency room with a right hip pain after she fell. She had no fever, fatigue, or respiratory symptoms on admission and within the 14 days before presenting to our hospital, and no specific shadow was detected in chest X-ray. However, chest computed tomography (CT) was performed considering COVID-19 pandemic, and showed ground-glass opacities with consolidation in the dorsal segment of the right lower lung field. Then, qualitative real-time reverse-transcriptase-polymerase-chain-reaction (RT-PCR) was carried out and turned out to be positive. She was diagnosed right femoral intertrochanteric fracture with concomitant COVID-19 infection. Conservative treatment was applied to the fracture due to infection. After admission, fever and oxygen demand occurred but she recovered from COVID-19. Throughout the treatment period, no cross-infection from the patient was identified in our hospital. Conclusion: This case highlights the importance of considering chest CT as an effective screening method for infection on hospital admission in COVID-19-affected areas, especially in trauma patients with early asymptomatic novel COVID-19.

scholarly journals Design of Fixed-Wing and Multi-Copter Hybrid Drone System for Human Body Temperature Measurement during COVID-19 Pandemic

2021 ◽  
Vol 20 ◽  
pp. 31-39
Author(s):  
Zayed Almheiri ◽  
Rawan Aleid ◽  
Sharul Sham Dol
Keyword(s):  
Body Temperature ◽  
Temperature Measurement ◽  
Human Body ◽  
Equivalent Strain ◽  
Simulation Software ◽  
Operational Conditions ◽  
Drag Forces ◽  
Human Body Temperature ◽  
Body Temperature Measurement ◽  
Lift And Drag

The purpose of this research is to conduct aerodynamics study and design a hybrid drone system of fixed-wing and multi-copter. The mission of this drone is to measure human body temperature during COVID19 pandemic. The specific aim of the drone is to fly and cover larger industrial areas roughly about 50 km2 with longer flying time than the conventional drone, of about 1.5 hours. The applications of the simulation software such as XFLR5 and ANSYS have a big impact in identifying areas that need to be improved for the drone system. XFLR5 software was used to compare the characteristics of different airfoils with highest lift over drag, L/D ratio. Based on the airfoil selection, it was found that NACA 4412 airfoil produces the highest L/D ratio. The detailed geometry of the drone system includes a fuselage length of 1.9 meters and wingspan of 2 meters. Moreover, 10 sheets of solar panels were placed along the wing for sustainable flight operation to cover wider areas of mission. The structural analysis was done on ANSYS to test the elastic stress, equivalent strain, deformation, factor of safety pressure as well as lift and drag forces under various operational conditions and payloads. The landing gear was analyzed for harsh landing. ANSYS Computational Fluid Dynamics (CFD) was utilized to study the aerodynamics of the drone at different parameters such as the velocities and angles of attack during the operation. This design ensures the stability of the drone during the temperature measurement phase. The best thermal-imaging camera for such purpose would be the Vue Pro R 336, 45° radiometric drone thermal camera with a resolution of 640 x 512 pixels. This camera has the advantage of a permanent continuous out focus that give the ability of taking measurements even if there was changing on the altitude or any kind of vibrations.

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