Temperature Detection System Research Articles

Self‐Powered Luminescent Solar Concentrators‐Integrated Temperature Detection System with High Thermal Tolerance by Reversible Thermal Photoluminescence Luminophores

AbstractIt is still a challenge to prepare the red‐emissive perovskite‐polymer composite with high photoluminescence quantum yield (PLQY) and reversible thermal photoluminescence (RTPL), which is key for improving the thermal tolerance of luminescent solar concentrators (LSCs). In this work, the red‐emissive (661 nm) CsPb(Br0.25I0.75)3‐PMMA composite with high PLQY of 85.96% and favorable RTPL below 160 °C is reported via a strategy of the defect passivation by halide ligand additives. The composite film possesses excellent long‐term stability in air, water, and high temperature environments. Then, a self‐powered temperature detection system, which consists of LSCs and a temperature detection module based on the RTPL composite film, is fabricated. On one hand, RTPL composite makes LSCs of superior thermal tolerance even after 100 cycles of temperature between room temperature and 160 °C. On the other hand, RTPL composite in the opaque box of the temperature detection module can give rise to the signal light without the interference of ambient light. As a result, the self‐powered temperature detection system achieves the quantitative temperature data display at different environment lights for 24 h in a day.

Ensure the accuracy and consistency of biochemical analyzer test results: Chemometrics for instrument and inter-instrument item comparison in Chinese hospital laboratory

Biochemical analyzers are vital instruments that utilize the principle of photoelectric colorimetry to quantify a specific chemical composition in body fluids. This analysis provides critical data for the diagnosis, treatment, prognosis, and overall health status of various diseases in clinical practice. However, the performance of a biochemical analyzer can vary significantly between different brands or over time within the same brand. Therefore, it is imperative to regularly assess the performance of the analyzer to ensure consistent results for longitudinal studies and to maintain day-to-day data consistency. Additionally, when multiple analyzers are utilized, it is necessary to evaluate the performance of each instrument to ensure accurate results across multiple platforms. In this study, we developed and verified an experimental evaluation scheme for the analytical performance of the instrument, chemometrics for biochemical analyzers, utilizing national reference materials and patient sera as the experimental subjects. We evaluated the performance of the optical system, temperature control system, sample-adding system, and detection system to confirm the feasibility of this scheme. We also compared the analytical performance of different brands of biochemical analyzers for routine biochemical tests, such as liver function, kidney function, ion, blood lipids, blood glucose, and myocardial enzyme spectrum. Using the AU 5400 as a control and the ADVIA 2400 as the comparison system, the relative variation in inter-instrument comparison data was found to be acceptable at the clinical medicine decision level. In conclusion, the performance of a biochemical analyzer can vary significantly between different brands or over time within the same brand. Regular evaluations are necessary to ensure accurate and consistent results across different analyzers. This study provides a feasible scheme for evaluating the analytical performance of biochemical analyzers that can be used to ensure the accuracy and consistency of the results of different brands of automatic chemical analyzers in the laboratory.

The preparation of a suspension of microencapsulated phase change material (MPCM) and thermal conductivity enhanced by MXene for thermal energy storage

A suspension of microencapsulated phase change material (MPCM) and thermal conductivity enhanced by MXene for thermal energy storage was prepared. The dispersion stability of MPCM-suspensions and MPCM-suspensions/MXene was investigated. The phase change behaviors of MPCM-suspensions and MPCM-suspensions/MXene were measured. The thermal conductivity and viscosity of MPCM-suspensions and MPCM-suspensions/MXene at various temperatures from 20 °C to 60 °C were tested. The thermal performance of MPCM-suspensions and MPCM-suspensions/MXene was evaluated by the temperature detection system. Results manifest that the mass ratio of isopropyl alcohol (IPA) to water of 42:58 can be used to prepare the MPCM-suspension with good dispersion stability and the MPCM-suspension containing MXene within 0.5 wt% can maintain the good dispersion stability. The latent heat of suspensions increases with the increase of MPCM and MXene has little effect on the latent heat of MPCM-suspensions. The thermal conductivity of suspensions decreases gradually and the viscosity increases dramatically with the increase of MPCM. MXene can significantly enhance the thermal conductivity of MPCM-suspensions and MXene within 0.3 wt% can decrease the viscosity of MPCM-suspensions. The temperature of the heated suspensions decreases gradually with the increase of MPCM. MXene can effectively increase the temperature of the heated MPCM-suspensions at early stage. The prepared MPCM-suspension/MXene has good dispersion stability and low viscosity, high thermal conductivity and latent heat, and can be applied as an efficient functional thermal fluid for thermal energy storage.

Automatic Temperature Detection System at the Entrance

Ensuring public health and safety has grown to be a top priority as a result of the ongoing COVID-19 outbreak. This abstract describes a novel system that makes use of an Arduino Uno, an infrared temperature sensor, an ultrasonic sensor, and a servo motor to automate temperature detection at entry to public places. The central processing unit of the suggested system is an Arduino Uno microcontroller. It is not necessary to make physical touch to monitor body temperature because an infrared temperature sensor is used. The risk of potential contagion is decreased because of this sensor's ability to precisely measure human body temperature at a secure distance. An ultrasonic sensor is added to the system to improve functionality by determining how far away the person is from the door. This maximizes accuracy and efficiency by ensuring that temperature sensing only happens when a person is inside the appropriate range. The system activates the servo motor, which smoothly regulates the movement of a physical barrier, such as a gate or door when it detects a human within the predetermined distance range. Automated access control is made possible by this technology, prohibiting anyone with unusual body temperatures from entering. The system's brain, the Arduino Uno, is responsible for digesting sensor data and producing the right control signals for the servo motor. In the event of an abnormal temperature reading, it can also be configured to sound an alarm or notify authorized persons. The suggested system has several benefits, including accurate distance measurement, contactless operation, and real-time temperature monitoring. To provide efficient screening and stop the transmission of infectious illnesses, it can be applied at a variety of entrance points, including workplaces, educational institutions, medical facilities, and hubs for public transit. The Automatic Temperature Detection System at Entrance, which is demonstrated in this abstract, offers a reliable method for automating temperature screening procedures.

Machine learning-assisted high-accuracy and large dynamic range thermometer in high-Q microbubble resonators.

Whispering gallery mode (WGM) resonators provide an important platform for fine measurement thanks to their small size, high sensitivity, and fast response time. Nevertheless, traditional methods focus on tracking single-mode changes for measurement, and a great deal of information from other resonances is ignored and wasted. Here, we demonstrate that the proposed multimode sensing contains more Fisher information than single mode tracking and has great potential to achieve better performance. Based on a microbubble resonator, a temperature detection system has been built to systematically investigate the proposed multimode sensing method. After the multimode spectral signals are collected by the automated experimental setup, a machine learning algorithm is used to predict the unknown temperature by taking full advantage of multiple resonances. The results show the average error of 3.8 × 10-3°C within the range from 25.00°C to 40.00°C by employing a generalized regression neural network (GRNN). In addition, we have also discussed the influence of the consumed data resource on its predicted performance, such as the amount of training data and the case of different temperate ranges between the training and test data. With high accuracy and large dynamic range, this work paves the way for WGM resonator-based intelligent optical sensing.

A Liquid Metal Temperature Detection System Based on Multi-Node Sapphire Fiber Sensor.

In order to accurately detect the temperature of molten aluminum and overcome the adverse influence of high temperature and corrosiveness on the sensing results, a temperature detection system based on a multi-node sapphire fiber sensor was proposed and developed. Through the structural parameter design of the fiber sensor, the scheme of utilizing the 0.7 mm diameter fiber and 0.5 mm groove was formulated. Simulation and analysis were carried out to determine the ultrasonic response distribution of the signal passing through the whole fiber sensor. The results indicate that the system is capable of distinguishing test signals from various positions and temperatures. Following the completion of the static calibration, the temperature of the molten aluminum was observed in real-time, and the data of the temperature measurements conducted at the two groove locations were compared. According to the obtained results, the test accuracy was greater than 1 degree Celsius and the temperature test stability was good, laying a solid foundation for the potential development of temperature measurement devices.

A short review on Smart Air Pollution and Temperature Detection System

A short review on Smart Air Pollution and Temperature Detection System

Face Recognition Based Biometric Identification System with COVID-19 Detection

Abstract: In this paper face recognition system for the purpose of security is explored whose design is based on Raspberry Pi system. An add on temperature detection system also gives detection of COVID affected people. With the COVID-19 pandemic, temperature checking before you enter a premise is a necessary step to ensure you are well and help keep others safe. One of the most common ways is to use a handheld digital thermometer to find out your own temperature and recording it on some kind of logbook placed near the front door. For a workplace, employees are encouraged to record their temperature twice a day

A Study on the Impact and Challenges of Temperature Detection System

A Study on the Impact and Challenges of Temperature Detection System

Temperature, Refractive Index, and Corrosion Simultaneous Monitoring Using Raman Anti-Stokes Reflectometric Optical Fiber Sensor

Optical sensors that can measure multiple parameters is a promising area of research. This can also be attributed to the fact that monitoring two or more measurands at the same time is crucial in embedded systems, especially when they are interconnected, as is the case of temperature and corrosion, or temperature and refractive index. In this work, an optical fiber sensor based on Raman scattering in single-mode optical fibers to simultaneously monitor temperature, refractive index and corrosion is proposed and experimentally demonstrated. This sensor consists of a distributed temperature detection system based on Raman scattering with additional sensor heads: for multipoint corrosion monitoring and multipoint refractive index variation measurement. The multiparameter sensor was evaluated for solutions with refractive indices in the range of 1.3370 – 1.3840 RIU (Refractive Index Unit), for temperatures between 30 °C and 100 °C, and for aluminum thin-film corrosion in acid solution. The experimental results show that the sensor presents sensitivities of 0.5 dB/10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> RIU to refractive index variations, of 0.43 dB/nm for corrosion, and of 0.243 dB/°C for temperature, with resolution of 2 °C. The sensor system can also provide the corrosion rate and operate in fiber links several kilometers long.

Real-time temperature detection and Mask entry system

Corona virus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus that causes illness in the Respiratory system in humans. Covid-19 affected our day-to- day life and still, it is continuing to mutate. Though we have discovered vaccines for the treatments, we can’t stop them from spreading. To prevent us from Covid-19, we have to wear a mask and maintain Social distance in public places. Here, we are making an Embedded system device that automatically detects the temperature of a person and checks whether the person wears a mask or not in public places such as Hospitals, Shopping Malls, Stations, etc. The Government of India has made wearing face masks compulsory but the people don&amp;#39;t wear masks in public places. To create awareness among the public, these types of devices would help. Many Face detection models have been developed using different approaches and algorithms. The proposed approach in this paper was developed to avoid mask-less people from entering a desired places by detecting face masks using Deep Learning, Keras library, Tensor Flow and Computer Vision. MLX90614 ESF Non-Contact Human Body Infrared Temperature Measurement Module is used to detect the temperature of a person without contact. Adriano is used as a Microprocessor. If either a person doesn’t wear a mask or the temperature of that person is above normal, then it detects it and starts making a sound (alarm) using Buzzer. If a person wears a mask and the temperature of that person is normal, then it detects it and allows that person to Enter.

Low-temperature argon plasma jet with cascading electrode technique for biological applications

In this study, the design, performance, and characteristics of a low-temperature argon plasma jet with cascading electrode technique (APJCE) are presented. APJCE is designed based on a tip-ring structure with a cascading ring. The effect of plasma jet driven by repetitive high-voltage microsecond pulses in APJCE structure was measured qualitatively in local surface temperature detection system. Then, by applying the generated plasma jet to biological surface and measuring and characterizing the electrical parameters, we obtained a plasma jet, which is electrically and thermally in the cold plasma regime. Simulation of the electric field distribution in the nozzle also yielded similar results to the experimental results. Finally, by cascading electrodes, we guided the plasma column to the nozzle output so that the plasma temperature within four centimeters of the nozzle output is 37 °C. The resulting plasma jets were studied by atomic emission spectroscopy and the intensity of the spectral lines of the atmospheric argon plasma jet spectra was obtained as a final experimental result at the output.

A Cost Efficient Contactless IoT based Body Temperature Detection System

In the recent outbreak of Covid-19 pandemic, various methods has been adopted to prevent and control the wide spread of pandemic. One of the commonly used method is by detecting the body temperature. This is to isolate those obtained higher body temperature who are possibly infected with the virus. Body temperature detection device is commonly deployed at the entrance of merchants for this purpose. However if one person is detected in one merchant with higher body temperature, this information is not bundled with his/her identity information. Therefore his/her entranced to other merchants are not linked and warned, and causing a possible spread of pandemic if other customers who appeared in the same premises are not being notified. In this work, an IoT based body temperature detection system is developed. In this system, the body temperature data is obtained and sent to the internet cloud together with the identity information of that person. This allow easy tracking of the potential virus infected person. The collected data can be further analysed using online analysis tool. Furthermore, the identity information is obtained using QR code which eliminate the ordinary procedure of writing personal data into logbook. The QR code method is contactless and able to avoid the infection of virus through the contact of pen and logbook. This system is developed with low-cost material and is affordable for small merchants.

Fiber-optic temperature sensor based on fabry-perot laser diode strong feedback

A novel, simple, and low-cost optical fiber temperature detection system is proposed and demonstrated in this paper, which uses the strong feedback of the Fabry-Perot Laser Diode (FP-LD) at 1550 nm to demodulate the temperature in real time in the resonator cavity. The experimental system consists of a commercial telecommunication laser source (FP-LD) and a fiber-optic Sagnac ring. In the sensing test, the change in temperature has a perfectly linear relationship with the shift of beat frequency signals (BFS). Measuring signals of different frequency will have different sensing sensitivities. System has an external photodetector (PD) in the first experiment. The temperature monitoring sensitivities is estimated to be 14.87 kHz/°C@2.49 GHz. In the second experimental system, there is no external PD, and the built-in monitor PD of FP-LD is used for photoelectric conversion. The sensitivity of the temperature sensor is 8.14 kHz/°C@1.382 GHz. In this paper, a fiber sensing system with the lowest cost and simplest structure is proposed, which consists of only a laser diode and a Sagnac ring.

A Study on the Impact and Challenges of Temperature Detection System

A Study on the Impact and Challenges of Temperature Detection System

Smart Temperature and Mask detection System using Raspberry Pi and Temperature Sensor with Camera and Barrier Enabled

The COVID-19 pandemic, which is caused by a new corona virus, is still spreading. More than sixteen million individuals have been infected across India so far, and the figure is continually rising. The health-care system is in critical condition. Wearing a mask is one of the many preventive steps adopted to decrease the spread of the disease. It's tough to physically check if someone is wearing their facial mask appropriately and to assess their temperature. Early symptom detection and good hygiene standards are therefore critical, particularly in situations where individuals come into random touch. In this research, we propose a Raspberry Pi-based system for limiting COVID-19 development by detecting and monitoring persons who are not wearing a face mask. Unlike handheld thermometers, which require a person to take a person's body temperature, our system uses the IR Thermal temperature sensor to provide a contactless and efficient temperature check, and an OpenCV subsystem based on a Raspberry Pi single board computer equipped with a camera module to allow or deny a person's entry into buildings and event venues for facial mask detection. Keywords: OpenCV, Python, Tensor Flow, Raspberry pi, Keras, Deep learning, COVID-19.

Identity and body temperature detection system based on image registration

In view of the normalization of epidemic prevention and control work, the low detection efficiency of traditional temperature measurement methods, and the existence of infection risks, an infrared thermal imaging temperature measurement system that can measure and identify the temperature of more than two people is designed. The system uses the Raspberry Pi as the core controller, using visible light and infrared cameras to capture identity and body temperature information. Identity recognition is based on OpenCv, using the Face Recognition face recognition framework to complete the identity recognition; body temperature detection is based on image registration, and the face position is mapped to the infrared image in real time through affine transformation, and finally the temperature of the human face area is obtained and displayed on the screen. The final experimental results show that it can simultaneously identify multiple people and detect body temperature with high accuracy, which can basically meet the requirements of rapid body temperature screening in intensive situations.

SOLAR BASED SMART COVID PROTECTION SYSTEM

The design shown shows the precautions that can be taken around the world during the COVID 19 pandemic. Disinfectants have become one of the most important products these days. Strong disinfection is required to survive the new WHO rules and regulations. The design provided a solution to the problem mentioned. This design introduces an automatic hand disinfection and temperature detection system that allows you to disinfect your hands at any time without touching the disinfectant. The temperature sensor shows the temperature of the person when touched. Keywords:- Automatic hand sanitizer, Arduino, ultrasonic sensor, PIR sensors, TMP36, covid-19.

Live Streaming of Face Mask and Body Temperature Detection System using Transfer Learning and IoT

Since the outbreak of COVID-19 pandemic, enormous development has been done in computer vision systems in face masks and temperature detection. To enforce the mandate for wearing the mask in public places, the authors have suggested a solution using transfer learning (MobileNetV2) architecture as a foundation for image classification. The proposed solution is embedded devices with Raspberry Pi4 and python packages viz TensorFlow, OpenCV, and Keras. In this Work, a combination of transfer learning and IoT has been worked out using live streaming to detect an appropriate use of face masks along with body temperature. This technique includes the Single Shot Single box and Multi-box identification of the face mask. Further, a person can check the Temperature at the entrance. This temperature sensor is in noncontact mode, which senses a temperature from 2 cm to 5 cm and is displayed through LCD. It sends the data to the cloud for visualization and analysis, and an alert message is sent in a real-time environment based on that analysis.

Pengembangan Deteksi Suhu dan Kelembaban Laboratorium Elektronika Dengan Menggunakan Metode Fuzzy Logic

The electronics laboratory is an important place to run the practical activities, especially among electronics students. It is important to protect laboratory equipment and components from the temperature and humidity factors. Whether, the temperature is too cold and the humidity is too high, it caused the corrosion of all electronic components. Thus, it also caused minor until severe damage of the components. Arduino is an open source electronics kit which specially designed to make easier for researcher to develop electronic devices regarding to various sensors and controllers. The laboratory room temperature detection system was carried out by using an Arduino device, which aims to determine the temperature conditions in the laboratory. The method used in this research is the fuzzy logic method. The software used is Arduiono and Matlab, while the hardware is power supply, D1 Mini microcontroller, DHT11 sensor and LCD. The results showed that the temperature data obtained from the DHT11 sensor will be displayed on the LCD. The temperature data obtained is 27 degrees Celsius – 29 degrees Celsius. The system is able to provide information when the temperature and humidity conditions are abnormal and the LED lights up according to room conditions.